02825nas a2200529 4500008004100000022001400041245011300055210006900168260001300237300001000250490000700260520135800267653000901625653002201634653001001656653002801666653002501694653001101719653002201730653001301752653001101765653001701776653001801793653001401811653000901825653001401834653003501848653003301883653001701916100002301933700002101956700002501977700002102002700002002023700001802043700001402061700002502075700001402100700002302114700002402137700002002161700002202181700001602203700002002219700002002239856003602259 2009 eng d a1873-681500aInflammation and stress-related candidate genes, plasma interleukin-6 levels, and longevity in older adults.0 aInflammation and stressrelated candidate genes plasma interleuki c2009 May a350-50 v443 a
Interleukin-6 (IL-6) is an inflammatory cytokine that influences the development of inflammatory and aging-related disorders and ultimately longevity. In order to study the influence of variants in genes that regulate inflammatory response on IL-6 levels and longevity, we screened a panel of 477 tag SNPs across 87 candidate genes in >5000 older participants from the population-based Cardiovascular Health Study (CHS). Baseline plasma IL-6 concentration was first confirmed as a strong predictor of all-cause mortality. Functional alleles of the IL6R and PARP1 genes were significantly associated with 15%-20% higher baseline IL-6 concentration per copy among CHS European-American (EA) participants (all p<10(-4)). In a case/control analysis nested within this EA cohort, the minor allele of PARP1 rs1805415 was nominally associated with decreased longevity (p=0.001), but there was no evidence of association between IL6R genotype and longevity. The PARP1 rs1805415--longevity association was subsequently replicated in one of two independent case/control studies. In a pooled analysis of all three studies, the "risk" of longevity associated with the minor allele of PARP1 rs1805415 was 0.79 (95%CI 0.62-1.02; p=0.07). These findings warrant further study of the potential role of PARP1 genotype in inflammatory and aging-related phenotypes.
10aAged10aAged, 80 and over10aAging10aCardiovascular Diseases10aCase-Control Studies10aFemale10aGenetic Variation10aGenotype10aHumans10aInflammation10aInterleukin-610aLongevity10aMale10aPhenotype10aPoly (ADP-Ribose) Polymerase-110aPoly(ADP-ribose) Polymerases10aRisk Factors1 aWalston, Jeremy, D1 aMatteini, Amy, M1 aNievergelt, Caroline1 aLange, Leslie, A1 aFallin, Dani, M1 aBarzilai, Nir1 aZiv, Elad1 aPawlikowska, Ludmila1 aKwok, Pui1 aCummings, Steve, R1 aKooperberg, Charles1 aLaCroix, Andrea1 aTracy, Russell, P1 aAtzmon, Gil1 aLange, Ethan, M1 aReiner, Alex, P uhttps://chs-nhlbi.org/node/108103263nas a2200553 4500008004100000022001400041245011200055210006900167260001300236300001100249490000600260520171300266653000901979653002201988653003402010653002102044653001102065653003402076653001102110653000902121653001602130653003602146653002402182100002302206700001602229700002102245700002002266700001902286700001202305700002102317700002302338700002102361700002102382700001602403700001902419700001802438700002302456700001902479700002202498700001702520700001902537700001902556700002102575700001702596700002402613700001702637700001902654856003602673 2011 eng d a1942-326800aAssociation of genetic variants and incident coronary heart disease in multiethnic cohorts: the PAGE study.0 aAssociation of genetic variants and incident coronary heart dise c2011 Dec a661-720 v43 aBACKGROUND: Genome-wide association studies identified several single nucleotide polymorphisms (SNP) associated with prevalent coronary heart disease (CHD), but less is known of associations with incident CHD. The association of 13 published CHD SNPs was examined in 5 ancestry groups of 4 large US prospective cohorts.
METHODS AND RESULTS: The analyses included incident coronary events over an average 9.1 to 15.7 follow-up person-years in up to 26 617 white individuals (6626 events), 8018 black individuals (914 events), 1903 Hispanic individuals (113 events), 3669 American Indian individuals (595 events), and 885 Asian/Pacific Islander individuals (66 events). We used Cox proportional hazards models (with additive mode of inheritance) adjusted for age, sex, and ancestry (as needed). Nine loci were statistically associated with incident CHD events in white participants: 9p21 (rs10757278; P=4.7 × 10(-41)), 16q23.1 (rs2549513; P=0.0004), 6p24.1 (rs499818; P=0.0002), 2q36.3 (rs2943634; P=6.7 × 10(-6)), MTHFD1L (rs6922269, P=5.1 × 10(-10)), APOE (rs429358; P=2.7×10(-18)), ZNF627 (rs4804611; P=5.0 × 10(-8)), CXCL12 (rs501120; P=1.4 × 10(-6)) and LPL (rs268; P=2.7 × 10(-17)). The 9p21 region showed significant between-study heterogeneity, with larger effects in individuals age 55 years or younger and in women. Inclusion of coronary revascularization procedures among the incident CHD events introduced heterogeneity. The SNPs were not associated with CHD in black participants, and associations varied in other US minorities.
CONCLUSIONS: Prospective analyses of white participants replicated several reported cross-sectional CHD-SNP associations.
10aAged10aAged, 80 and over10aContinental Population Groups10aCoronary Disease10aFemale10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aProspective Studies1 aFranceschini, Nora1 aCarty, Cara1 aBůzková, Petra1 aReiner, Alex, P1 aGarrett, Tiana1 aLin, Yi1 aVöckler, Jens-S1 aHindorff, Lucia, A1 aCole, Shelley, A1 aBoerwinkle, Eric1 aLin, Dan-Yu1 aBookman, Ebony1 aBest, Lyle, G1 aBella, Jonathan, N1 aEaton, Charles1 aGreenland, Philip1 aJenny, Nancy1 aNorth, Kari, E1 aTaverna, Darin1 aYoung, Alicia, M1 aDeelman, Ewa1 aKooperberg, Charles1 aPsaty, Bruce1 aHeiss, Gerardo uhttps://chs-nhlbi.org/node/134704377nas a2200829 4500008004100000022001400041245014300055210006900198260001300267300001300280490000600293520197700299653001502276653001002291653000902301653002202310653003402332653001102366653001902377653002502396653003402421653001102455653002702466653002102493653002202514653002202536653000902558653001602567653002702583653003602610653002802646653001702674653001802691653001602709100002202725700001902747700001702766700002802783700002302811700002102834700002102855700001802876700002602894700002102920700002802941700002102969700002102990700002503011700001703036700002203053700002003075700002303095700001903118700002303137700002203160700001903182700002503201700001803226700002203244700002103266700002603287700002103313700002103334700002203355700002703377700002303404700001903427700002403446700001903470700002203489856003603511 2011 eng d a1553-740400aGenetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.0 aGenetic determinants of lipid traits in diverse populations from c2011 Jun ae10021380 v73 aFor the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS-identified variants in diverse population-based studies. We genotyped 49 GWAS-identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (~20,000), African American (~9,000), American Indian (~6,000), Mexican American/Hispanic (~2,500), Japanese/East Asian (~690), and Pacific Islander/Native Hawaiian (~175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.
10aAdolescent10aAdult10aAged10aAged, 80 and over10aContinental Population Groups10aFemale10aGene Frequency10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLinkage Disequilibrium10aLipid Metabolism10aLipoproteins, HDL10aLipoproteins, LDL10aMale10aMiddle Aged10aMolecular Epidemiology10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aRisk Factors10aTriglycerides10aYoung Adult1 aDumitrescu, Logan1 aCarty, Cara, L1 aTaylor, Kira1 aSchumacher, Fredrick, R1 aHindorff, Lucia, A1 aAmbite, José, L1 aAnderson, Garnet1 aBest, Lyle, G1 aBrown-Gentry, Kristin1 aBůzková, Petra1 aCarlson, Christopher, S1 aCochran, Barbara1 aCole, Shelley, A1 aDevereux, Richard, B1 aDuggan, Dave1 aEaton, Charles, B1 aFornage, Myriam1 aFranceschini, Nora1 aHaessler, Jeff1 aHoward, Barbara, V1 aJohnson, Karen, C1 aLaston, Sandra1 aKolonel, Laurence, N1 aLee, Elisa, T1 aMacCluer, Jean, W1 aManolio, Teri, A1 aPendergrass, Sarah, A1 aQuibrera, Miguel1 aShohet, Ralph, V1 aWilkens, Lynne, R1 aHaiman, Christopher, A1 aLe Marchand, Loïc1 aBuyske, Steven1 aKooperberg, Charles1 aNorth, Kari, E1 aCrawford, Dana, C uhttps://chs-nhlbi.org/node/130303344nas a2200517 4500008004100000022001400041245014800055210006900203260001600272300001100288490000800299520172900307653002602036653003402062653001802096653003202114653002502146653003402171653001102205653003302216653003102249653005202280653001402332653001902346653002002365653001702385653001802402100002002420700002302440700001902463700002802482700002102510700002202531700002702553700001902580700002402599700002202623700002102645700001902666700001902685700002402704700002302728700002402751710001502775856003602790 2011 eng d a1476-625600aThe Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.0 aNext PAGE in understanding complex traits design for the analysi c2011 Oct 01 a849-590 v1743 aGenetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the "phenome-wide association study" approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information's Database of Genotypes and Phenotypes and made available via a custom browser.
10aEpidemiologic Methods10aEpidemiologic Research Design10aEthnic Groups10aGenetic Association Studies10aGenetics, Population10aGenome-Wide Association Study10aHumans10aInterinstitutional Relations10aMultifactorial Inheritance10aNational Human Genome Research Institute (U.S.)10aPhenotype10aPilot Projects10aResearch Design10aRisk Factors10aUnited States1 aMatise, Tara, C1 aAmbite, Jose, Luis1 aBuyske, Steven1 aCarlson, Christopher, S1 aCole, Shelley, A1 aCrawford, Dana, C1 aHaiman, Christopher, A1 aHeiss, Gerardo1 aKooperberg, Charles1 aLe Marchand, Loic1 aManolio, Teri, A1 aNorth, Kari, E1 aPeters, Ulrike1 aRitchie, Marylyn, D1 aHindorff, Lucia, A1 aHaines, Jonathan, L1 aPAGE Study uhttps://chs-nhlbi.org/node/131303388nas a2200553 4500008004100000022001400041245012700055210006900182260001300251300001300264490000600277520170800283653002201991653002302013653001802036653001802054653004002072653003202112653003802144653001802182653001102200653002302211653002302234653001402257653002602271653003602297653003402333653003002367653002202397100002202419700001802441700001902459700002102478700002102499700002002520700002302540700002402563700002002587700002102607700002602628700002002654700002402674700002202698700002002720700002202740700001902762700001702781856003602798 2011 eng d a1553-740400aA phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.0 aphenomicsbased strategy identifies loci on APOC1 BRAP and PLCG1 c2011 Oct ae10023220 v73 aDespite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.
10aAfrican Americans10aApolipoprotein C-I10aBlood Glucose10aDyslipidemias10aEuropean Continental Ancestry Group10aGenetic Association Studies10aGenetic Predisposition to Disease10aGenome, Human10aHumans10aMetabolic Syndrome10aObesity, Abdominal10aPhenotype10aPhospholipase C gamma10aPolymorphism, Single Nucleotide10aQuantitative Trait, Heritable10aUbiquitin-Protein Ligases10aVascular Diseases1 aAvery, Christy, L1 aHe, Qianchuan1 aNorth, Kari, E1 aAmbite, José, L1 aBoerwinkle, Eric1 aFornage, Myriam1 aHindorff, Lucia, A1 aKooperberg, Charles1 aMeigs, James, B1 aPankow, James, S1 aPendergrass, Sarah, A1 aPsaty, Bruce, M1 aRitchie, Marylyn, D1 aRotter, Jerome, I1 aTaylor, Kent, D1 aWilkens, Lynne, R1 aHeiss, Gerardo1 aLin, Dan, Yu uhttps://chs-nhlbi.org/node/134503420nas a2200517 4500008004100000022001400041245023700055210006900292260001600361300001000377490000600387520182700393653000902220653002202229653002802251653002102279653002102300653004002321653001102361653002502372653003402397653001302431653001102444653000902455653001602464653003602480653001702516653001102533653001802544100001902562700002102581700002002602700002302622700001802645700001902663700002302682700002302705700001402728700002002742700001602762700002002778700001902798700002502817700002402842856003602866 2012 eng d a1942-326800aAssociations between incident ischemic stroke events and stroke and cardiovascular disease-related genome-wide association studies single nucleotide polymorphisms in the Population Architecture Using Genomics and Epidemiology study.0 aAssociations between incident ischemic stroke events and stroke c2012 Apr 01 a210-60 v53 aBACKGROUND: Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.
METHODS AND RESULTS: Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with [corrected] IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.
CONCLUSIONS: Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.
10aAged10aAged, 80 and over10aCardiovascular Diseases10aCholesterol, HDL10aCholesterol, LDL10aEuropean Continental Ancestry Group10aFemale10aGenetics, Population10aGenome-Wide Association Study10aGenomics10aHumans10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aRisk Factors10aStroke10aTriglycerides1 aCarty, Cara, L1 aBůzková, Petra1 aFornage, Myriam1 aFranceschini, Nora1 aCole, Shelley1 aHeiss, Gerardo1 aHindorff, Lucia, A1 aHoward, Barbara, V1 aMann, Sue1 aMartin, Lisa, W1 aZhang, Ying1 aMatise, Tara, C1 aPrentice, Ross1 aReiner, Alexander, P1 aKooperberg, Charles uhttps://chs-nhlbi.org/node/137103528nas a2200721 4500008004100000022001400041245014600055210006900201260000900270300001100279490000600290520139200296653002201688653002801710653004001738653002101778653002101799653002301820653001901843653001901862653003401881653001301915653001101928653002301939653003601962653002801998100001902026700001302045700001902058700001602077700002902093700002202122700002302144700002202167700002302189700002102212700002102233700002202254700002102276700001802297700002202315700002502337700002302362700002202385700001702407700002002424700002402444700001202468700002302480700002002503700002602523700002202549700002802571700002402599700001802623700002102641700002102662700002702683700001902710700002202729700001902751856003602770 2012 eng d a1932-620300aEvaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study.0 aEvaluation of the metabochip genotyping array in African America c2012 ae356510 v73 aThe Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 × 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 × 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.
10aAfrican Americans10aCardiovascular Diseases10aCholesterol Ester Transfer Proteins10aCholesterol, HDL10aCholesterol, LDL10aChromosomes, Human10aCohort Studies10aGene Frequency10aGenome-Wide Association Study10aGenotype10aHumans10aMetabolic Diseases10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci1 aBuyske, Steven1 aWu, Ying1 aCarty, Cara, L1 aCheng, Iona1 aAssimes, Themistocles, L1 aDumitrescu, Logan1 aHindorff, Lucia, A1 aMitchell, Sabrina1 aAmbite, Jose, Luis1 aBoerwinkle, Eric1 aBůzková, Petra1 aCarlson, Chris, S1 aCochran, Barbara1 aDuggan, David1 aEaton, Charles, B1 aFesinmeyer, Megan, D1 aFranceschini, Nora1 aHaessler, Jeffrey1 aJenny, Nancy1 aKang, Hyun, Min1 aKooperberg, Charles1 aLin, Yi1 aLe Marchand, Loïc1 aMatise, Tara, C1 aRobinson, Jennifer, G1 aRodriguez, Carlos1 aSchumacher, Fredrick, R1 aVoight, Benjamin, F1 aYoung, Alicia1 aManolio, Teri, A1 aMohlke, Karen, L1 aHaiman, Christopher, A1 aPeters, Ulrike1 aCrawford, Dana, C1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/663403996nas a2200625 4500008004100000022001400041245008800055210006900143260000900212300001300221490000600234520220300240653002202443653000902465653002602474653002402500653004002524653001102564653003802575653003402613653001102647653002702658653000902685653001702694653001602711653003602727653002802763653003402791653001702825653001602842653001802858100002202876700002402898700001902922700001802941700001602959700001902975700001902994700001803013700002503031700002303056700002003079700001703099700002303116700001903139700002103158700002203179700002103201700002403222700002703246700002103273700002103294700001903315856003603334 2012 eng d a1553-740400aFine-mapping and initial characterization of QT interval loci in African Americans.0 aFinemapping and initial characterization of QT interval loci in c2012 ae10028700 v83 aThe QT interval (QT) is heritable and its prolongation is a risk factor for ventricular tachyarrhythmias and sudden death. Most genetic studies of QT have examined European ancestral populations; however, the increased genetic diversity in African Americans provides opportunities to narrow association signals and identify population-specific variants. We therefore evaluated 6,670 SNPs spanning eleven previously identified QT loci in 8,644 African American participants from two Population Architecture using Genomics and Epidemiology (PAGE) studies: the Atherosclerosis Risk in Communities study and Women's Health Initiative Clinical Trial. Of the fifteen known independent QT variants at the eleven previously identified loci, six were significantly associated with QT in African American populations (P≤1.20×10(-4)): ATP1B1, PLN1, KCNQ1, NDRG4, and two NOS1AP independent signals. We also identified three population-specific signals significantly associated with QT in African Americans (P≤1.37×10(-5)): one at NOS1AP and two at ATP1B1. Linkage disequilibrium (LD) patterns in African Americans assisted in narrowing the region likely to contain the functional variants for several loci. For example, African American LD patterns showed that 0 SNPs were in LD with NOS1AP signal rs12143842, compared with European LD patterns that indicated 87 SNPs, which spanned 114.2 Kb, were in LD with rs12143842. Finally, bioinformatic-based characterization of the nine African American signals pointed to functional candidates located exclusively within non-coding regions, including predicted binding sites for transcription factors such as TBX5, which has been implicated in cardiac structure and conductance. In this detailed evaluation of QT loci, we identified several African Americans SNPs that better define the association with QT and successfully narrowed intervals surrounding established loci. These results demonstrate that the same loci influence variation in QT across multiple populations, that novel signals exist in African Americans, and that the SNPs identified as strong candidates for functional evaluation implicate gene regulatory dysfunction in QT prolongation.
10aAfrican Americans10aAged10aComputational Biology10aElectrocardiography10aEuropean Continental Ancestry Group10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aLinkage Disequilibrium10aMale10aMetagenomics10aMiddle Aged10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aQuantitative Trait, Heritable10aRisk Factors10aTachycardia10aUnited States1 aAvery, Christy, L1 aSethupathy, Praveen1 aBuyske, Steven1 aHe, Qianchuan1 aLin, Dan-Yu1 aArking, Dan, E1 aCarty, Cara, L1 aDuggan, David1 aFesinmeyer, Megan, D1 aHindorff, Lucia, A1 aJeff, Janina, M1 aKlein, Liviu1 aPatton, Kristen, K1 aPeters, Ulrike1 aShohet, Ralph, V1 aSotoodehnia, Nona1 aYoung, Alicia, M1 aKooperberg, Charles1 aHaiman, Christopher, A1 aMohlke, Karen, L1 aWhitsel, Eric, A1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/608308678nas a2202593 4500008004100000022001400041245012400055210006900179260001600248300001200264490000700276520126400283653001701547653002601564653004001590653003401630653001101664653001501675653002001690653003001710653003801740653003401778653001301812653001801825653001101843653005001854653005501904653002101959653000901980653004601989653001702035653002002052653003602072653002802108653001702136653001302153100001902166700002602185700002502211700001902236700002002255700002502275700001402300700002302314700001602337700001802353700002202371700001202393700001802405700002102423700002202444700002402466700001802490700001702508700003102525700002002556700001802576700001902594700002502613700002402638700001702662700002502679700002102704700002102725700001702746700001702763700002202780700001902802700002602821700001802847700002102865700002002886700002802906700001902934700002102953700002202974700002502996700002203021700002103043700001703064700002403081700002303105700001703128700002203145700002303167700002003190700001903210700002103229700001603250700002603266700002003292700001903312700002103331700001903352700001903371700002003390700002803410700002103438700001903459700002003478700002003498700002703518700001403545700001303559700002103572700002503593700002403618700001703642700002403659700001803683700002203701700001403723700001803737700002003755700003003775700002003805700002103825700002403846700001803870700002203888700002903910700002303939700001503962700002103977700002103998700001604019700002004035700003104055700002004086700003004106700001904136700002204155700002004177700002404197700002004221700002204241700002004263700001704283700001904300700002704319700002404346700003104370700002004401700002104421700002704442700002604469700001504495700001204510700001804522700002804540700002404568700001604592700002204608700002304630700002604653700002304679700002704702700002004729700001704749700002204766700001904788700002504807700002004832700002304852700002104875700002404896700001904920700002404939700002104963700002004984700002405004700001905028700002405047700001805071700001905089700001805108700002205126700001705148700002305165700002205188700002505210700002705235700002705262700001905289700001905308700002305327700002305350700002005373700001705393700001805410700002405428700002105452700002305473700002505496700002305521700002105544700002505565700002205590700002005612700002205632700002605654700002005680700002005700700002405720700002705744700002505771700002805796700001905824700001905843700002005862700002205882700002105904700002805925700002305953700002505976700002106001700002606022856003606048 2012 eng d a1546-171800aGenome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.0 aGenomewide metaanalysis identifies 56 bone mineral density loci c2012 Apr 15 a491-5010 v443 aBone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
10aBone Density10aComputational Biology10aEuropean Continental Ancestry Group10aExtracellular Matrix Proteins10aFemale10aFemur Neck10aFractures, Bone10aGene Expression Profiling10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aGlycoproteins10aHumans10aIntercellular Signaling Peptides and Proteins10aLow Density Lipoprotein Receptor-Related Protein-510aLumbar Vertebrae10aMale10aMitochondrial Membrane Transport Proteins10aOsteoporosis10aPhosphoproteins10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aRisk Factors10aSpectrin1 aEstrada, Karol1 aStyrkarsdottir, Unnur1 aEvangelou, Evangelos1 aHsu, Yi-Hsiang1 aDuncan, Emma, L1 aNtzani, Evangelia, E1 aOei, Ling1 aAlbagha, Omar, M E1 aAmin, Najaf1 aKemp, John, P1 aKoller, Daniel, L1 aLi, Guo1 aLiu, Ching-Ti1 aMinster, Ryan, L1 aMoayyeri, Alireza1 aVandenput, Liesbeth1 aWillner, Dana1 aXiao, Su-Mei1 aYerges-Armstrong, Laura, M1 aZheng, Hou-Feng1 aAlonso, Nerea1 aEriksson, Joel1 aKammerer, Candace, M1 aKaptoge, Stephen, K1 aLeo, Paul, J1 aThorleifsson, Gudmar1 aWilson, Scott, G1 aWilson, James, F1 aAalto, Ville1 aAlen, Markku1 aAragaki, Aaron, K1 aAspelund, Thor1 aCenter, Jacqueline, R1 aDailiana, Zoe1 aDuggan, David, J1 aGarcia, Melissa1 aGarcía-Giralt, Natalia1 aGiroux, Sylvie1 aHallmans, Göran1 aHocking, Lynne, J1 aHusted, Lise, Bjerre1 aJameson, Karen, A1 aKhusainova, Rita1 aKim, Ghi, Su1 aKooperberg, Charles1 aKoromila, Theodora1 aKruk, Marcin1 aLaaksonen, Marika1 aLaCroix, Andrea, Z1 aLee, Seung, Hun1 aLeung, Ping, C1 aLewis, Joshua, R1 aMasi, Laura1 aMencej-Bedrac, Simona1 aNguyen, Tuan, V1 aNogues, Xavier1 aPatel, Millan, S1 aPrezelj, Janez1 aRose, Lynda, M1 aScollen, Serena1 aSiggeirsdottir, Kristin1 aSmith, Albert, V1 aSvensson, Olle1 aTrompet, Stella1 aTrummer, Olivia1 avan Schoor, Natasja, M1 aWoo, Jean1 aZhu, Kun1 aBalcells, Susana1 aBrandi, Maria, Luisa1 aBuckley, Brendan, M1 aCheng, Sulin1 aChristiansen, Claus1 aCooper, Cyrus1 aDedoussis, George1 aFord, Ian1 aFrost, Morten1 aGoltzman, David1 aGonzález-Macías, Jesús1 aKähönen, Mika1 aKarlsson, Magnus1 aKhusnutdinova, Elza1 aKoh, Jung-Min1 aKollia, Panagoula1 aLangdahl, Bente, Lomholt1 aLeslie, William, D1 aLips, Paul1 aLjunggren, Osten1 aLorenc, Roman, S1 aMarc, Janja1 aMellström, Dan1 aObermayer-Pietsch, Barbara1 aOlmos, José, M1 aPettersson-Kymmer, Ulrika1 aReid, David, M1 aRiancho, José, A1 aRidker, Paul, M1 aRousseau, François1 aSlagboom, Eline1 aTang, Nelson, L S1 aUrreizti, Roser1 aVan Hul, Wim1 aViikari, Jorma1 aZarrabeitia, María, T1 aAulchenko, Yurii, S1 aCastano-Betancourt, Martha1 aGrundberg, Elin1 aHerrera, Lizbeth1 aIngvarsson, Thorvaldur1 aJohannsdottir, Hrefna1 aKwan, Tony1 aLi, Rui1 aLuben, Robert1 aMedina-Gómez, Carolina1 aPalsson, Stefan, Th1 aReppe, Sjur1 aRotter, Jerome, I1 aSigurdsson, Gunnar1 avan Meurs, Joyce, B J1 aVerlaan, Dominique1 aWilliams, Frances, M K1 aWood, Andrew, R1 aZhou, Yanhua1 aGautvik, Kaare, M1 aPastinen, Tomi1 aRaychaudhuri, Soumya1 aCauley, Jane, A1 aChasman, Daniel, I1 aClark, Graeme, R1 aCummings, Steven, R1 aDanoy, Patrick1 aDennison, Elaine, M1 aEastell, Richard1 aEisman, John, A1 aGudnason, Vilmundur1 aHofman, Albert1 aJackson, Rebecca, D1 aJones, Graeme1 aJukema, Wouter1 aKhaw, Kay-Tee1 aLehtimäki, Terho1 aLiu, Yongmei1 aLorentzon, Mattias1 aMcCloskey, Eugene1 aMitchell, Braxton, D1 aNandakumar, Kannabiran1 aNicholson, Geoffrey, C1 aOostra, Ben, A1 aPeacock, Munro1 aPols, Huibert, A P1 aPrince, Richard, L1 aRaitakari, Olli1 aReid, Ian, R1 aRobbins, John1 aSambrook, Philip, N1 aSham, Pak, Chung1 aShuldiner, Alan, R1 aTylavsky, Frances, A1 aDuijn, Cornelia, M1 aWareham, Nick, J1 aCupples, Adrienne, L1 aEcons, Michael, J1 aEvans, David, M1 aHarris, Tamara, B1 aKung, Annie, Wai Chee1 aPsaty, Bruce, M1 aReeve, Jonathan1 aSpector, Timothy, D1 aStreeten, Elizabeth, A1 aZillikens, Carola, M1 aThorsteinsdottir, Unnur1 aOhlsson, Claes1 aKarasik, David1 aRichards, Brent1 aBrown, Matthew, A1 aStefansson, Kari1 aUitterlinden, André, G1 aRalston, Stuart, H1 aIoannidis, John, P A1 aKiel, Douglas, P1 aRivadeneira, Fernando uhttps://chs-nhlbi.org/node/801604096nas a2200901 4500008004100000022001400041245007000055210006900125260001500194300001100209490000700220520164400227653001001871653002201881653000901903653002201912653002001934653001101954653001701965653003801982653001802020653003402038653001302072653001102085653002702096653000902123653001602132653001202148653003602160653001602196100001502212700002502227700001502252700002302267700001902290700001902309700002802328700002102356700002102377700002002398700001702418700002102435700002102456700002502477700002002502700001702522700001602539700002002555700002502575700002102600700001602621700002102637700001602658700001902674700001802693700001902711700001702730700002602747700002002773700002202793700002102815700002002836700002402856700001502880700002002895700001602915700003002931700002202961700002102983700002403004700002003028700002303048700002203071700002703093700001903120700001903139856003603158 2013 eng d a1537-660500aFine Mapping and Identification of BMI Loci in African Americans.0 aFine Mapping and Identification of BMI Loci in African Americans c2013 Oct 3 a661-710 v933 aGenome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
10aAdult10aAfrican Americans10aAged10aAged, 80 and over10aBody Mass Index10aFemale10aGenetic Loci10aGenetic Predisposition to Disease10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aLinkage Disequilibrium10aMale10aMiddle Aged10aObesity10aPolymorphism, Single Nucleotide10aYoung Adult1 aGong, Jian1 aSchumacher, Fredrick1 aLim, Unhee1 aHindorff, Lucia, A1 aHaessler, Jeff1 aBuyske, Steven1 aCarlson, Christopher, S1 aRosse, Stephanie1 aBůzková, Petra1 aFornage, Myriam1 aGross, Myron1 aPankratz, Nathan1 aPankow, James, S1 aSchreiner, Pamela, J1 aCooper, Richard1 aEhret, Georg1 aGu, Charles1 aHouston, Denise1 aIrvin, Marguerite, R1 aJackson, Rebecca1 aKuller, Lew1 aHenderson, Brian1 aCheng, Iona1 aWilkens, Lynne1 aLeppert, Mark1 aLewis, Cora, E1 aLi, Rongling1 aNguyen, Khanh-Dung, H1 aGoodloe, Robert1 aFarber-Eger, Eric1 aBoston, Jonathan1 aDilks, Holli, H1 aRitchie, Marylyn, D1 aFowke, Jay1 aPooler, Loreall1 aGraff, Misa1 aFernandez-Rhodes, Lindsay1 aCochrane, Barbara1 aBoerwinkle, Eric1 aKooperberg, Charles1 aMatise, Tara, C1 aLe Marchand, Loïc1 aCrawford, Dana, C1 aHaiman, Christopher, A1 aNorth, Kari, E1 aPeters, Ulrike uhttps://chs-nhlbi.org/node/662606047nas a2201393 4500008004100000022001400041245010400055210006900159260000900228300001300237490000600250520209200256653001402348653003902362653002602401653004002427653001102467653001702478653003402495653001102529653000902540653001202549653003602561653002002597100001802617700001902635700002002654700001802674700002302692700001902715700002402734700002102758700002202779700001502801700002802816700002502844700001602869700002202885700002202907700002302929700001802952700001202970700002802982700001803010700001503028700002403043700002403067700002803091700001903119700001703138700002503155700001603180700002203196700001903218700002003237700002303257700002203280700002803302700001703330700002003347700002303367700001503390700001703405700002003422700002103442700001803463700002203481700002303503700002303526700003103549700002203580700002003602700001703622700002803639700001403667700002403681700002403705700002203729700002103751700001803772700001403790700003203804700002503836700002403861700001703885700002403902700002103926700002103947700002803968700002203996700002004018700002104038700002104059700002704080700002204107700002304129700002104152700002404173700001704197700002404214700002304238700002204261700002104283700002504304700002304329700002204352700001904374700002204393700002104415700002804436700002304464700001804487700002204505700002504527700002504552700001904577700002104596856003604617 2013 eng d a1553-740400aGenome-wide association of body fat distribution in African ancestry populations suggests new loci.0 aGenomewide association of body fat distribution in African ances c2013 ae10036810 v93 aCentral obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 × 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8); RREB1: p = 5.7 × 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.
10aAdiposity10aAfrican Continental Ancestry Group10aBody Fat Distribution10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aMale10aObesity10aPolymorphism, Single Nucleotide10aWaist-Hip Ratio1 aLiu, Ching-Ti1 aMonda, Keri, L1 aTaylor, Kira, C1 aLange, Leslie1 aDemerath, Ellen, W1 aPalmas, Walter1 aWojczynski, Mary, K1 aEllis, Jaclyn, C1 aVitolins, Mara, Z1 aLiu, Simin1 aPapanicolaou, George, J1 aIrvin, Marguerite, R1 aXue, Luting1 aGriffin, Paula, J1 aNalls, Michael, A1 aAdeyemo, Adebowale1 aLiu, Jiankang1 aLi, Guo1 aRuiz-Narvaez, Edward, A1 aChen, Wei-Min1 aChen, Fang1 aHenderson, Brian, E1 aMillikan, Robert, C1 aAmbrosone, Christine, B1 aStrom, Sara, S1 aGuo, Xiuqing1 aAndrews, Jeanette, S1 aSun, Yan, V1 aMosley, Thomas, H1 aYanek, Lisa, R1 aShriner, Daniel1 aHaritunians, Talin1 aRotter, Jerome, I1 aSpeliotes, Elizabeth, K1 aSmith, Megan1 aRosenberg, Lynn1 aMychaleckyj, Josyf1 aNayak, Uma1 aSpruill, Ida1 aGarvey, Timothy1 aPettaway, Curtis1 aNyante, Sarah1 aBandera, Elisa, V1 aBritton, Angela, F1 aZonderman, Alan, B1 aRasmussen-Torvik, Laura, J1 aChen, Yii-Der Ida1 aDing, Jingzhong1 aLohman, Kurt1 aKritchevsky, Stephen, B1 aZhao, Wei1 aPeyser, Patricia, A1 aKardia, Sharon, L R1 aKabagambe, Edmond1 aBroeckel, Ulrich1 aChen, Guanjie1 aZhou, Jie1 aWassertheil-Smoller, Sylvia1 aNeuhouser, Marian, L1 aRampersaud, Evadnie1 aPsaty, Bruce1 aKooperberg, Charles1 aManson, JoAnn, E1 aKuller, Lewis, H1 aOchs-Balcom, Heather, M1 aJohnson, Karen, C1 aSucheston, Lara1 aOrdovas, Jose, M1 aPalmer, Julie, R1 aHaiman, Christopher, A1 aMcKnight, Barbara1 aHoward, Barbara, V1 aBecker, Diane, M1 aBielak, Lawrence, F1 aLiu, Yongmei1 aAllison, Matthew, A1 aGrant, Struan, F A1 aBurke, Gregory, L1 aPatel, Sanjay, R1 aSchreiner, Pamela, J1 aBorecki, Ingrid, B1 aEvans, Michele, K1 aTaylor, Herman1 aSale, Michèle, M1 aHoward, Virginia1 aCarlson, Christopher, S1 aRotimi, Charles, N1 aCushman, Mary1 aHarris, Tamara, B1 aReiner, Alexander, P1 aCupples, Adrienne, L1 aNorth, Kari, E1 aFox, Caroline, S uhttps://chs-nhlbi.org/node/628703673nas a2200601 4500008004100000022001400041245015800055210006900213260000900282300000700291490000700298520191500305653001102220653002602231653001802257653003402275653001102309653001102320653000902331653003602340653002202376100002002398700001902418700002202437700002102459700002102480700002002501700002402521700002202545700002102567700002102588700002202609700002402631700001902655700002302674700002202697700002102719700002102740700001602761700002202777700002602799700002102825700002302846700002402869700002302893700002402916700002202940700001902962700001902981700002003000710001503020856003603035 2013 eng d a1471-215600aInvestigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.0 aInvestigation of genebysex interactions for lipid traits in dive c2013 a330 v143 aBACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.
RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.
CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.
10aFemale10aGenetic Heterogeneity10aGenome, Human10aGenome-Wide Association Study10aHumans10aLipids10aMale10aPolymorphism, Single Nucleotide10aPopulation Groups1 aTaylor, Kira, C1 aCarty, Cara, L1 aDumitrescu, Logan1 aBůzková, Petra1 aCole, Shelley, A1 aHindorff, Lucia1 aSchumacher, Fred, R1 aWilkens, Lynne, R1 aShohet, Ralph, V1 aQuibrera, Miguel1 aJohnson, Karen, C1 aHenderson, Brian, E1 aHaessler, Jeff1 aFranceschini, Nora1 aEaton, Charles, B1 aDuggan, David, J1 aCochran, Barbara1 aCheng, Iona1 aCarlson, Chris, S1 aBrown-Gentry, Kristin1 aAnderson, Garnet1 aAmbite, Jose, Luis1 aHaiman, Christopher1 aLe Marchand, Loïc1 aKooperberg, Charles1 aCrawford, Dana, C1 aBuyske, Steven1 aNorth, Kari, E1 aFornage, Myriam1 aPAGE Study uhttps://chs-nhlbi.org/node/662709008nas a2202809 4500008004100000022001400041245010800055210006900163260001300232300001000245490000700255520108900262653002201351653002001373653002501393653001901418653001701437653003801454653003401492653001101526653002701537653001201564653003601576100001901612700001801631700002001649700002001669700002101689700002101710700001901731700002601750700002401776700002401800700001801824700002201842700002501864700001801889700001201907700001701919700001701936700001801953700002201971700001601993700002402009700001902033700002402052700002202076700002502098700002202123700002102145700002002166700002102186700001602207700002202223700002202245700001802267700001802285700001802303700001502321700002102336700002802357700002402385700002002409700003202429700002002461700002202481700002102503700001302524700002302537700002902560700002002589700001702609700002302626700001902649700002202668700002402690700002302714700002202737700002302759700002302782700002402805700002202829700001702851700002402868700001802892700002102910700002102931700002302952700002202975700001702997700001803014700001603032700002103048700002103069700001703090700002403107700002603131700002003157700002603177700001803203700002803221700001503249700002003264700002203284700001603306700002003322700002903342700002203371700001803393700002503411700002203436700002703458700002303485700002903508700002103537700002803558700002603586700002203612700002503634700003103659700002803690700002203718700002003740700002103760700002303781700002103804700001903825700003203844700002803876700002303904700002003927700001903947700002203966700002403988700002704012700002804039700001904067700002104086700002304107700001904130700002204149700001504171700001904186700002104205700002104226700001904247700001804266700002304284700001904307700001404326700001904340700001404359700002304373700002104396700002604417700002204443700002004465700001904485700002004504700002804524700001704552700002104569700001804590700002104608700002104629700002204650700002104672700002304693700002404716700002204740700001904762700002404781700002304805700002004828700001804848700002204866700001804888700002004906700002704926700002204953700002304975700001504998700001405013700002005027700001705047700001905064700002005083700002205103700002505125700002405150700002105174700002405195700001905219700002505238700002305263700001505286700002205301700002405323700002205347700002705369700002005396700002105416700001905437700002405456700002405480700002005504700001905524700002305543700002505566700002205591700002505613700002405638700002505662700002305687700001905710700002105729700001905750700001505769700002005784700002305804700002005827700001805847700002305865700002405888700002805912700002405940700002005964700002405984700002006008700001906028700002706047710002106074710002106095710002606116710002006142856003606162 2013 eng d a1546-171800aA meta-analysis identifies new loci associated with body mass index in individuals of African ancestry.0 ametaanalysis identifies new loci associated with body mass index c2013 Jun a690-60 v453 aGenome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.
10aAfrican Americans10aBody Mass Index10aCase-Control Studies10aGene Frequency10aGenetic Loci10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aLinkage Disequilibrium10aObesity10aPolymorphism, Single Nucleotide1 aMonda, Keri, L1 aChen, Gary, K1 aTaylor, Kira, C1 aPalmer, Cameron1 aEdwards, Todd, L1 aLange, Leslie, A1 aC Y Ng, Maggie1 aAdeyemo, Adebowale, A1 aAllison, Matthew, A1 aBielak, Lawrence, F1 aChen, Guanjie1 aGraff, Mariaelisa1 aIrvin, Marguerite, R1 aRhie, Suhn, K1 aLi, Guo1 aLiu, Yongmei1 aLiu, Youfang1 aLu, Yingchang1 aNalls, Michael, A1 aSun, Yan, V1 aWojczynski, Mary, K1 aYanek, Lisa, R1 aAldrich, Melinda, C1 aAdemola, Adeyinka1 aAmos, Christopher, I1 aBandera, Elisa, V1 aBock, Cathryn, H1 aBritton, Angela1 aBroeckel, Ulrich1 aCai, Quiyin1 aCaporaso, Neil, E1 aCarlson, Chris, S1 aCarpten, John1 aCasey, Graham1 aChen, Wei-Min1 aChen, Fang1 aChen, Yii-der, I1 aChiang, Charleston, W K1 aCoetzee, Gerhard, A1 aDemerath, Ellen1 aDeming-Halverson, Sandra, L1 aDriver, Ryan, W1 aDubbert, Patricia1 aFeitosa, Mary, F1 aFeng, Ye1 aFreedman, Barry, I1 aGillanders, Elizabeth, M1 aGottesman, Omri1 aGuo, Xiuqing1 aHaritunians, Talin1 aHarris, Tamara1 aHarris, Curtis, C1 aHennis, Anselm, J M1 aHernandez, Dena, G1 aMcNeill, Lorna, H1 aHoward, Timothy, D1 aHoward, Barbara, V1 aHoward, Virginia, J1 aJohnson, Karen, C1 aKang, Sun, J1 aKeating, Brendan, J1 aKolb, Suzanne1 aKuller, Lewis, H1 aKutlar, Abdullah1 aLangefeld, Carl, D1 aLettre, Guillaume1 aLohman, Kurt1 aLotay, Vaneet1 aLyon, Helen1 aManson, JoAnn, E1 aMaixner, William1 aMeng, Yan, A1 aMonroe, Kristine, R1 aMorhason-Bello, Imran1 aMurphy, Adam, B1 aMychaleckyj, Josyf, C1 aNadukuru, Raj1 aNathanson, Katherine, L1 aNayak, Uma1 aN'diaye, Amidou1 aNemesure, Barbara1 aWu, Suh-Yuh1 aLeske, Cristina1 aNeslund-Dudas, Christine1 aNeuhouser, Marian1 aNyante, Sarah1 aOchs-Balcom, Heather1 aOgunniyi, Adesola1 aOgundiran, Temidayo, O1 aOjengbede, Oladosu1 aOlopade, Olufunmilayo, I1 aPalmer, Julie, R1 aRuiz-Narvaez, Edward, A1 aPalmer, Nicholette, D1 aPress, Michael, F1 aRampersaud, Evandine1 aRasmussen-Torvik, Laura, J1 aRodriguez-Gil, Jorge, L1 aSalako, Babatunde1 aSchadt, Eric, E1 aSchwartz, Ann, G1 aShriner, Daniel, A1 aSiscovick, David1 aSmith, Shad, B1 aWassertheil-Smoller, Sylvia1 aSpeliotes, Elizabeth, K1 aSpitz, Margaret, R1 aSucheston, Lara1 aTaylor, Herman1 aTayo, Bamidele, O1 aTucker, Margaret, A1 aVan Den Berg, David, J1 aEdwards, Digna, R Velez1 aWang, Zhaoming1 aWiencke, John, K1 aWinkler, Thomas, W1 aWitte, John, S1 aWrensch, Margaret1 aWu, Xifeng1 aYang, James, J1 aLevin, Albert, M1 aYoung, Taylor, R1 aZakai, Neil, A1 aCushman, Mary1 aZanetti, Krista, A1 aZhao, Jing Hua1 aZhao, Wei1 aZheng, Yonglan1 aZhou, Jie1 aZiegler, Regina, G1 aZmuda, Joseph, M1 aFernandes, Jyotika, K1 aGilkeson, Gary, S1 aKamen, Diane, L1 aHunt, Kelly, J1 aSpruill, Ida, J1 aAmbrosone, Christine, B1 aAmbs, Stefan1 aArnett, Donna, K1 aAtwood, Larry1 aBecker, Diane, M1 aBerndt, Sonja, I1 aBernstein, Leslie1 aBlot, William, J1 aBorecki, Ingrid, B1 aBottinger, Erwin, P1 aBowden, Donald, W1 aBurke, Gregory1 aChanock, Stephen, J1 aCooper, Richard, S1 aDing, Jingzhong1 aDuggan, David1 aEvans, Michele, K1 aFox, Caroline1 aGarvey, Timothy1 aBradfield, Jonathan, P1 aHakonarson, Hakon1 aGrant, Struan, F A1 aHsing, Ann1 aChu, Lisa1 aHu, Jennifer, J1 aHuo, Dezheng1 aIngles, Sue, A1 aJohn, Esther, M1 aJordan, Joanne, M1 aKabagambe, Edmond, K1 aKardia, Sharon, L R1 aKittles, Rick, A1 aGoodman, Phyllis, J1 aKlein, Eric, A1 aKolonel, Laurence, N1 aLe Marchand, Loïc1 aLiu, Simin1 aMcKnight, Barbara1 aMillikan, Robert, C1 aMosley, Thomas, H1 aPadhukasahasram, Badri1 aWilliams, Keoki1 aPatel, Sanjay, R1 aPeters, Ulrike1 aPettaway, Curtis, A1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRedline, Susan1 aRotimi, Charles, N1 aRybicki, Benjamin, A1 aSale, Michèle, M1 aSchreiner, Pamela, J1 aSignorello, Lisa, B1 aSingleton, Andrew, B1 aStanford, Janet, L1 aStrom, Sara, S1 aThun, Michael, J1 aVitolins, Mara1 aZheng, Wei1 aMoore, Jason, H1 aWilliams, Scott, M1 aKetkar, Shamika1 aZhu, Xiaofeng1 aZonderman, Alan, B1 aKooperberg, Charles1 aPapanicolaou, George, J1 aHenderson, Brian, E1 aReiner, Alex, P1 aHirschhorn, Joel, N1 aLoos, Ruth, J F1 aNorth, Kari, E1 aHaiman, Christopher, A1 aNABEC Consortium1 aUKBEC Consortium1 aBioBank Japan Project1 aAGEN Consortium uhttps://chs-nhlbi.org/node/607802686nas a2200697 4500008004100000022001400041245012800055210006900183260001300252300001200265490000800277520066900285653002100954653002100975653001900996653001801015653001101033653001901044653003301063653002501096653003401121653001101155653002101166653000901187653003601196653001501232653001201247653001801259653001601277100002201293700001901315700002301334700002301357700002101380700002101401700002801422700002201450700002301472700002101495700001901516700002101535700002401556700001601580700002201596700002201618700002201640700002601662700002301688700002101711700002101732700002301753700002201776700002301798700002701821700001901848700002401867700001901891700002001910700002201930856003601952 2013 eng d a1432-120300aNo evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.0 aNo evidence of interaction between known lipidassociated genetic c2013 Dec a1427-310 v1323 aGenome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.
10aCholesterol, HDL10aCholesterol, LDL10aCohort Studies10aEthnic Groups10aFemale10aGene Frequency10aGene-Environment Interaction10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLipid Metabolism10aMale10aPolymorphism, Single Nucleotide10aPrevalence10aSmoking10aTriglycerides10aYoung Adult1 aDumitrescu, Logan1 aCarty, Cara, L1 aFranceschini, Nora1 aHindorff, Lucia, A1 aCole, Shelley, A1 aBůzková, Petra1 aSchumacher, Fredrick, R1 aEaton, Charles, B1 aGoodloe, Robert, J1 aDuggan, David, J1 aHaessler, Jeff1 aCochran, Barbara1 aHenderson, Brian, E1 aCheng, Iona1 aJohnson, Karen, C1 aCarlson, Chris, S1 aLove, Shelly-Anne1 aBrown-Gentry, Kristin1 aNato, Alejandro, Q1 aQuibrera, Miguel1 aShohet, Ralph, V1 aAmbite, Jose, Luis1 aWilkens, Lynne, R1 aLe Marchand, Loïc1 aHaiman, Christopher, A1 aBuyske, Steven1 aKooperberg, Charles1 aNorth, Kari, E1 aFornage, Myriam1 aCrawford, Dana, C uhttps://chs-nhlbi.org/node/629203380nas a2200673 4500008004100000022001400041245020100055210006900256260001300325300001100338490000700349520133800356653001001694653000901704653004001713653001101753653003201764653003401796653001101830653001101841653000901852653001601861653003601877653002801913653003401941653001701975100002201992700001902014700002302033700002302056700002102079700002102100700002802121700002202149700002302171700002102194700001902215700002102234700002402255700001602279700002202295700002202317700002102339700002602360700002302386700002102409700002102430700002102451700002302472700002202495700002202517700002702539700001902566700002402585700001902609700002002628700002202648856003602670 2013 eng d a1469-180900aPost-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.0 aPostgenomewide association study challenges for lipid traits des c2013 Sep a416-250 v773 aNumerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.
10aAdult10aAged10aEuropean Continental Ancestry Group10aFemale10aGenetic Association Studies10aGenome-Wide Association Study10aHumans10aLipids10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aQuantitative Trait, Heritable10aRisk Factors1 aDumitrescu, Logan1 aCarty, Cara, L1 aFranceschini, Nora1 aHindorff, Lucia, A1 aCole, Shelley, A1 aBůzková, Petra1 aSchumacher, Fredrick, R1 aEaton, Charles, B1 aGoodloe, Robert, J1 aDuggan, David, J1 aHaessler, Jeff1 aCochran, Barbara1 aHenderson, Brian, E1 aCheng, Iona1 aJohnson, Karen, C1 aCarlson, Chris, S1 aLove, Shelly-Ann1 aBrown-Gentry, Kristin1 aNato, Alejandro, Q1 aQuibrera, Miguel1 aAnderson, Garnet1 aShohet, Ralph, V1 aAmbite, Jose, Luis1 aWilkens, Lynne, R1 aLe Marchand, Loic1 aHaiman, Christopher, A1 aBuyske, Steven1 aKooperberg, Charles1 aNorth, Kari, E1 aFornage, Myriam1 aCrawford, Dana, C uhttps://chs-nhlbi.org/node/611104247nas a2200757 4500008004100000022001400041245023300055210006900288260000900357300001300366490000600379520199400385653004102379653001002420653002202430653000902452653002202461653001202483653002002495653002302515653003402538653004002572653001102612653003802623653003402661653001102695653002702706653000902733653001702742653001602759653001202775653001302787100001902800700001902819700002402838700001802862700001902880700001502899700002502914700002402939700001902963700002502982700001503007700001603022700002103038700001903059700001703078700001603095700001703111700002603128700002003154700001903174700001803193700002503211700001603236700002003252700002103272700002103293700002003314700002303334700002303357700002203380700002703402700002403429856003603453 2013 eng d a1553-740400aA systematic mapping approach of 16q12.2/FTO and BMI in more than 20,000 African Americans narrows in on the underlying functional variation: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.0 asystematic mapping approach of 16q122FTO and BMI in more than 20 c2013 ae10031710 v93 aGenetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 × 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.
10aAdaptor Proteins, Signal Transducing10aAdult10aAfrican Americans10aAged10aAged, 80 and over10aAlleles10aBody Mass Index10aChromosome Mapping10aContinental Population Groups10aEuropean Continental Ancestry Group10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aLinkage Disequilibrium10aMale10aMetagenomics10aMiddle Aged10aObesity10aProteins1 aPeters, Ulrike1 aNorth, Kari, E1 aSethupathy, Praveen1 aBuyske, Steve1 aHaessler, Jeff1 aJiao, Shuo1 aFesinmeyer, Megan, D1 aJackson, Rebecca, D1 aKuller, Lew, H1 aRajkovic, Aleksandar1 aLim, Unhee1 aCheng, Iona1 aSchumacher, Fred1 aWilkens, Lynne1 aLi, Rongling1 aMonda, Keri1 aEhret, Georg1 aNguyen, Khanh-Dung, H1 aCooper, Richard1 aLewis, Cora, E1 aLeppert, Mark1 aIrvin, Marguerite, R1 aGu, Charles1 aHouston, Denise1 aBůzková, Petra1 aRitchie, Marylyn1 aMatise, Tara, C1 aLe Marchand, Loïc1 aHindorff, Lucia, A1 aCrawford, Dana, C1 aHaiman, Christopher, A1 aKooperberg, Charles uhttps://chs-nhlbi.org/node/662805266nas a2201201 4500008004100000022001400041245015400055210006900209260001300278300001300291490000600304520181500310653002202125653002202147653002102169653002102190653004002211653003402251653001102285653002202296653002202318653002702340653002602367653001802393100001302411700002202424700002102446700002102467700001902488700001802507700002102525700002102546700002502567700001902592700001602611700002102627700003002648700002202678700002202700700002302722700001702745700002402762700002302786700001402809700002002823700002202843700001802865700002302883700001202906700002202918700002802940700002502968700001902993700002603012700002103038700002503059700002003084700001703104700001803121700002003139700001903159700001903178700002103197700002003218700002803238700002103266700002603287700002403313700001803337700002103355700001703376700001703393700002003410700002003430700002303450700002603473700002203499700001903521700001903540700001403559700002103573700002003594700002003614700002103634700001903655700002403674700002103698700002203719700002003741700002303761700002003784700002003804700002103824700002703845700002103872700002403893700002903917700002203946700002003968700001903988700002104007856003604028 2013 eng d a1553-740400aTrans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.0 aTransethnic finemapping of lipid loci identifies populationspeci c2013 Mar ae10033790 v93 aGenome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.
10aAfrican Americans10aApolipoproteins A10aCholesterol, HDL10aCholesterol, LDL10aEuropean Continental Ancestry Group10aGenome-Wide Association Study10aHumans10aLipoproteins, HDL10aLipoproteins, LDL10aProprotein Convertases10aSerine Endopeptidases10aTriglycerides1 aWu, Ying1 aWaite, Lindsay, L1 aJackson, Anne, U1 aSheu, Wayne, H-H1 aBuyske, Steven1 aAbsher, Devin1 aArnett, Donna, K1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aCarty, Cara, L1 aCheng, Iona1 aCochran, Barbara1 aCroteau-Chonka, Damien, C1 aDumitrescu, Logan1 aEaton, Charles, B1 aFranceschini, Nora1 aGuo, Xiuqing1 aHenderson, Brian, E1 aHindorff, Lucia, A1 aKim, Eric1 aKinnunen, Leena1 aKomulainen, Pirjo1 aLee, Wen-Jane1 aLe Marchand, Loïc1 aLin, Yi1 aLindström, Jaana1 aLingaas-Holmen, Oddgeir1 aMitchell, Sabrina, L1 aNarisu, Narisu1 aRobinson, Jennifer, G1 aSchumacher, Fred1 aStančáková, Alena1 aSundvall, Jouko1 aSung, Yun-Ju1 aSwift, Amy, J1 aWang, Wen-Chang1 aWilkens, Lynne1 aWilsgaard, Tom1 aYoung, Alicia, M1 aAdair, Linda, S1 aBallantyne, Christie, M1 aBůzková, Petra1 aChakravarti, Aravinda1 aCollins, Francis, S1 aDuggan, David1 aFeranil, Alan, B1 aHo, Low-Tone1 aHung, Yi-Jen1 aHunt, Steven, C1 aHveem, Kristian1 aJuang, Jyh-Ming, J1 aKesäniemi, Antero, Y1 aKuusisto, Johanna1 aLaakso, Markku1 aLakka, Timo, A1 aLee, I-Te1 aLeppert, Mark, F1 aMatise, Tara, C1 aMoilanen, Leena1 aNjølstad, Inger1 aPeters, Ulrike1 aQuertermous, Thomas1 aRauramaa, Rainer1 aRotter, Jerome, I1 aSaramies, Jouko1 aTuomilehto, Jaakko1 aUusitupa, Matti1 aWang, Tzung-Dau1 aBoehnke, Michael1 aHaiman, Christopher, A1 aChen, Yii-der, I1 aKooperberg, Charles1 aAssimes, Themistocles, L1 aCrawford, Dana, C1 aHsiung, Chao, A1 aNorth, Kari, E1 aMohlke, Karen, L uhttps://chs-nhlbi.org/node/662908212nas a2202197 4500008004100000022001400041245013100055210006900186260001600255300001000271490000800281520207900289653001002368653000902378653002602387653002102413653001502434653002102449653001102470653002002481653001302501653001102514653000902525653003702534653001602571653002402587653003602611653001102647100002302658700002202681700001902703700002702722700001502749700001402764700002502778700001902803700002002822700001702842700002002859700001902879700002502898700001702923700002002940700002102960700002202981700002503003700001903028700002403047700002603071700002803097700001703125700001603142700003103158700001503189700002003204700002103224700001803245700002003263700001903283700002403302700002003326700002103346700001803367700002103385700002003406700001903426700002103445700001903466700001803485700002803503700002103531700002503552700001503577700002303592700001903615700002703634700002403661700002403685700002403709700001803733700002103751700001603772700002603788700002303814700001503837700002103852700002303873700002403896700001803920700002603938700002203964700001903986700001804005700001804023700002104041700001904062700001704081700002104098700001904119700002104138700002404159700002404183700003404207700002004241700002204261700002504283700001904308700002104327700001904348700001804367700002004385700002004405700001504425700001904440700002804459700002004487700001404507700002104521700002404542700002504566700001804591700002004609700002804629700002204657700002304679700001504702700002504717700002904742700003104771700002204802700002204824700002204846700002004868700002304888700001804911700002004929700001904949700001904968700002504987700002205012700002005034700002405054700002305078700001805101700002505119700002405144700002005168700001905188700001805207700001505225700002205240700002505262700002005287700002105307700002105328700001905349700002305368700002205391700002205413700002205435700002105457700002505478700001905503700002705522700001905549700002205568700002005590700002505610700002105635700002005656700002105676700002105697700002005718700002405738700002805762700001805790700001905808700002405827700001905851700002005870700002405890700002105914700001905935710002405954856003605978 2014 eng d a1756-183300aAssociation between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data.0 aAssociation between alcohol and cardiovascular disease Mendelian c2014 Jul 10 ag41640 v3493 aOBJECTIVE: To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease.
DESIGN: Mendelian randomisation meta-analysis of 56 epidemiological studies.
PARTICIPANTS: 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers.
MAIN OUTCOME MEASURES: Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption.
RESULTS: Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)).
CONCLUSIONS: Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.
10aAdult10aAged10aAlcohol Dehydrogenase10aAlcohol Drinking10aBiomarkers10aCoronary Disease10aFemale10aGenetic Markers10aGenotype10aHumans10aMale10aMendelian Randomization Analysis10aMiddle Aged10aModels, Statistical10aPolymorphism, Single Nucleotide10aStroke1 aHolmes, Michael, V1 aDale, Caroline, E1 aZuccolo, Luisa1 aSilverwood, Richard, J1 aGuo, Yiran1 aYe, Zheng1 aPrieto-Merino, David1 aDehghan, Abbas1 aTrompet, Stella1 aWong, Andrew1 aCavadino, Alana1 aDrogan, Dagmar1 aPadmanabhan, Sandosh1 aLi, Shanshan1 aYesupriya, Ajay1 aLeusink, Maarten1 aSundström, Johan1 aHubacek, Jaroslav, A1 aPikhart, Hynek1 aSwerdlow, Daniel, I1 aPanayiotou, Andrie, G1 aBorinskaya, Svetlana, A1 aFinan, Chris1 aShah, Sonia1 aKuchenbaecker, Karoline, B1 aShah, Tina1 aEngmann, Jorgen1 aFolkersen, Lasse1 aEriksson, Per1 aRicceri, Fulvio1 aMelander, Olle1 aSacerdote, Carlotta1 aGamble, Dale, M1 aRayaprolu, Sruti1 aRoss, Owen, A1 aMcLachlan, Stela1 aVikhireva, Olga1 aSluijs, Ivonne1 aScott, Robert, A1 aAdamkova, Vera1 aFlicker, Leon1 avan Bockxmeer, Frank, M1 aPower, Christine1 aMarques-Vidal, Pedro1 aMeade, Tom1 aMarmot, Michael, G1 aFerro, Jose, M1 aPaulos-Pinheiro, Sofia1 aHumphries, Steve, E1 aTalmud, Philippa, J1 aLeach, Irene, Mateo1 aVerweij, Niek1 aLinneberg, Allan1 aSkaaby, Tea1 aDoevendans, Pieter, A1 aCramer, Maarten, J1 aHarst, Pim1 aKlungel, Olaf, H1 aDowling, Nicole, F1 aDominiczak, Anna, F1 aKumari, Meena1 aNicolaides, Andrew, N1 aWeikert, Cornelia1 aBoeing, Heiner1 aEbrahim, Shah1 aGaunt, Tom, R1 aPrice, Jackie, F1 aLannfelt, Lars1 aPeasey, Anne1 aKubinova, Ruzena1 aPajak, Andrzej1 aMalyutina, Sofia1 aVoevoda, Mikhail, I1 aTamosiunas, Abdonas1 avan der Zee, Anke, H Maitland1 aNorman, Paul, E1 aHankey, Graeme, J1 aBergmann, Manuela, M1 aHofman, Albert1 aFranco, Oscar, H1 aCooper, Jackie1 aPalmen, Jutta1 aSpiering, Wilko1 ade Jong, Pim, A1 aKuh, Diana1 aHardy, Rebecca1 aUitterlinden, André, G1 aIkram, Arfan, M1 aFord, Ian1 aHyppönen, Elina1 aAlmeida, Osvaldo, P1 aWareham, Nicholas, J1 aKhaw, Kay-Tee1 aHamsten, Anders1 aHusemoen, Lise, Lotte N1 aTjønneland, Anne1 aTolstrup, Janne, S1 aRimm, Eric1 aBeulens, Joline, W J1 aVerschuren, W, M Monique1 aOnland-Moret, Charlotte, N1 aHofker, Marten, H1 aWannamethee, Goya1 aWhincup, Peter, H1 aMorris, Richard1 aVicente, Astrid, M1 aWatkins, Hugh1 aFarrall, Martin1 aJukema, Wouter1 aMeschia, James1 aCupples, Adrienne, L1 aSharp, Stephen, J1 aFornage, Myriam1 aKooperberg, Charles1 aLaCroix, Andrea, Z1 aDai, James, Y1 aLanktree, Matthew, B1 aSiscovick, David, S1 aJorgenson, Eric1 aSpring, Bonnie1 aCoresh, Josef1 aLi, Yun, R1 aBuxbaum, Sarah, G1 aSchreiner, Pamela, J1 aEllison, Curtis1 aTsai, Michael, Y1 aPatel, Sanjay, R1 aRedline, Susan1 aJohnson, Andrew, D1 aHoogeveen, Ron, C1 aHakonarson, Hakon1 aRotter, Jerome, I1 aBoerwinkle, Eric1 ade Bakker, Paul, I W1 aKivimaki, Mika1 aAsselbergs, Folkert, W1 aSattar, Naveed1 aLawlor, Debbie, A1 aWhittaker, John1 aSmith, George, Davey1 aMukamal, Kenneth1 aPsaty, Bruce, M1 aWilson, James, G1 aLange, Leslie, A1 aHamidovic, Ajna1 aHingorani, Aroon, D1 aNordestgaard, Børge, G1 aBobak, Martin1 aLeon, David, A1 aLangenberg, Claudia1 aPalmer, Tom, M1 aReiner, Alex, P1 aKeating, Brendan, J1 aDudbridge, Frank1 aCasas, Juan, P1 aInterAct Consortium uhttps://chs-nhlbi.org/node/656905943nas a2201657 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2014 eng d a1537-660500aAssociation of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks.0 aAssociation of lowfrequency and rare codingsequence variants wit c2014 Feb 06 a223-320 v943 aLow-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1% and 2%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited.
10a1-Alkyl-2-acetylglycerophosphocholine Esterase10aAdult10aAfrican Continental Ancestry Group10aAged10aAlleles10aAnimals10aCholesterol, HDL10aCholesterol, LDL10aCohort Studies10aCoronary Disease10aEuropean Continental Ancestry Group10aFemale10aGene Frequency10aGenetic Association Studies10aGenetic Code10aGenetic Variation10aHumans10aLinear Models10aMale10aMice10aMice, Inbred C57BL10aMicrotubule-Associated Proteins10aMiddle Aged10aPhenotype10aSequence Analysis, DNA10aSubtilisins10aTriglycerides1 aPeloso, Gina, M1 aAuer, Paul, L1 aBis, Joshua, C1 aVoorman, Arend1 aMorrison, Alanna, C1 aStitziel, Nathan, O1 aBrody, Jennifer, A1 aKhetarpal, Sumeet, A1 aCrosby, Jacy, R1 aFornage, Myriam1 aIsaacs, Aaron1 aJakobsdottir, Johanna1 aFeitosa, Mary, F1 aDavies, Gail1 aHuffman, Jennifer, E1 aManichaikul, Ani1 aDavis, Brian1 aLohman, Kurt1 aJoon, Aron, Y1 aSmith, Albert, V1 aGrove, Megan, L1 aZanoni, Paolo1 aRedon, Valeska1 aDemissie, Serkalem1 aLawson, Kim1 aPeters, Ulrike1 aCarlson, Christopher1 aJackson, Rebecca, D1 aRyckman, Kelli, K1 aMackey, Rachel, H1 aRobinson, Jennifer, G1 aSiscovick, David, S1 aSchreiner, Pamela, J1 aMychaleckyj, Josyf, C1 aPankow, James, S1 aHofman, Albert1 aUitterlinden, André, G1 aHarris, Tamara, B1 aTaylor, Kent, D1 aStafford, Jeanette, M1 aReynolds, Lindsay, M1 aMarioni, Riccardo, E1 aDehghan, Abbas1 aFranco, Oscar, H1 aPatel, Aniruddh, P1 aLu, Yingchang1 aHindy, George1 aGottesman, Omri1 aBottinger, Erwin, P1 aMelander, Olle1 aOrho-Melander, Marju1 aLoos, Ruth, J F1 aDuga, Stefano1 aMerlini, Piera, Angelica1 aFarrall, Martin1 aGoel, Anuj1 aAsselta, Rosanna1 aGirelli, Domenico1 aMartinelli, Nicola1 aShah, Svati, H1 aKraus, William, E1 aLi, Mingyao1 aRader, Daniel, J1 aReilly, Muredach, P1 aMcPherson, Ruth1 aWatkins, Hugh1 aArdissino, Diego1 aZhang, Qunyuan1 aWang, Judy1 aTsai, Michael, Y1 aTaylor, Herman, A1 aCorrea, Adolfo1 aGriswold, Michael, E1 aLange, Leslie, A1 aStarr, John, M1 aRudan, Igor1 aEiriksdottir, Gudny1 aLauner, Lenore, J1 aOrdovas, Jose, M1 aLevy, Daniel1 aChen, Y-D, Ida1 aReiner, Alexander, P1 aHayward, Caroline1 aPolasek, Ozren1 aDeary, Ian, J1 aBorecki, Ingrid, B1 aLiu, Yongmei1 aGudnason, Vilmundur1 aWilson, James, G1 aDuijn, Cornelia, M1 aKooperberg, Charles1 aRich, Stephen, S1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aO'Donnell, Christopher, J1 aRice, Kenneth1 aBoerwinkle, Eric1 aKathiresan, Sekar1 aCupples, Adrienne, L1 aNHLBI GO Exome Sequencing Project uhttps://chs-nhlbi.org/node/659003296nas a2200565 4500008004100000022001400041245008800055210006900143260001300212300001000225490000700235520169900242653000901941653003401950653002401984653001102008653003802019653001502057653001102072653002102083653000902104653001602113653001402129653003602143653002802179653003402207653001702241100002302258700002102281700002002302700002302322700002302345700001202368700001902380700001702399700002302416700002302439700002402462700002002486700001902506700002002525700002002545700002402565700002102589700001902610700001902629700002402648700002202672856003602694 2014 eng d a1531-548700aEvidence of heterogeneity by race/ethnicity in genetic determinants of QT interval.0 aEvidence of heterogeneity by raceethnicity in genetic determinan c2014 Nov a790-80 v253 aBACKGROUND: QT interval (QT) prolongation is an established risk factor for ventricular tachyarrhythmia and sudden cardiac death. Previous genome-wide association studies in populations of the European descent have identified multiple genetic loci that influence QT, but few have examined these loci in ethnically diverse populations.
METHODS: Here, we examine the direction, magnitude, and precision of effect sizes for 21 previously reported SNPs from 12 QT loci, in populations of European (n = 16,398), African (n = 5,437), American Indian (n = 5,032), Hispanic (n = 1,143), and Asian (n = 932) descent as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Estimates obtained from linear regression models stratified by race/ethnicity were combined using inverse-variance weighted meta-analysis. Heterogeneity was evaluated using Cochran's Q test.
RESULTS: Of 21 SNPs, 7 showed consistent direction of effect across all 5 populations, and an additional 9 had estimated effects that were consistent across 4 populations. Despite consistent direction of effect, 9 of 16 SNPs had evidence (P < 0.05) of heterogeneity by race/ethnicity. For these 9 SNPs, linkage disequilibrium plots often indicated substantial variation in linkage disequilibrium patterns among the various racial/ethnic groups, as well as possible allelic heterogeneity.
CONCLUSIONS: These results emphasize the importance of analyzing racial/ethnic groups separately in genetic studies. Furthermore, they underscore the possible utility of trans-ethnic studies to pinpoint underlying casual variants influencing heritable traits such as QT.
10aAged10aContinental Population Groups10aElectrocardiography10aFemale10aGenetic Predisposition to Disease10aHaplotypes10aHumans10aLong QT Syndrome10aMale10aMiddle Aged10aPhenotype10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aQuantitative Trait, Heritable10aRisk Factors1 aSeyerle, Amanda, A1 aYoung, Alicia, M1 aJeff, Janina, M1 aMelton, Phillip, E1 aJorgensen, Neal, W1 aLin, Yi1 aCarty, Cara, L1 aDeelman, Ewa1 aHeckbert, Susan, R1 aHindorff, Lucia, A1 aJackson, Rebecca, D1 aMartin, Lisa, W1 aOkin, Peter, M1 aPerez, Marco, V1 aPsaty, Bruce, M1 aSoliman, Elsayed, Z1 aWhitsel, Eric, A1 aNorth, Kari, E1 aLaston, Sandra1 aKooperberg, Charles1 aAvery, Christy, L uhttps://chs-nhlbi.org/node/659805734nas a2201333 4500008004100000022001400041245007800055210006900133260001500202300001000217490000800227520196900235653003902204653002502243653002102268653004002289653001002329653001302339653001702352653001102369653001002380653001302390653001702403653002702420653001802447110010402465700001702569700002002586700001802606700002302624700002402647700002102671700001802692700002202710700001402732700001802746700002002764700002302784700002202807700001202829700001302841700001402854700002002868700001602888700001502904700002002919700001802939700002802957700002102985700002203006700002303028700002303051700001203074700001903086700002503105700002103130700002003151700002303171700001803194700002303212700002903235700002303264700002303287700001903310700002003329700001903349700001903368700002203387700002403409700002403433700002303457700002203480700001703502700002203519700002003541700001903561700001903580700002003599700001903619700002603638700002003664700002403684700003003708700002003738700002803758700002203786700002103808700001903829700001803848700002503866700002103891700002003912700002003932700002303952700002203975700002203997700002204019700002004041700002404061700002104085700002404106700002104130700002204151700001604173700002104189700002004210700002604230700002004256700002504276700002004301700002104321700002204342856003604364 2014 eng d a1533-440600aLoss-of-function mutations in APOC3, triglycerides, and coronary disease.0 aLossoffunction mutations in APOC3 triglycerides and coronary dis c2014 Jul 3 a22-310 v3713 aBACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype.
METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons.
RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)).
CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).
10aAfrican Continental Ancestry Group10aApolipoprotein C-III10aCoronary Disease10aEuropean Continental Ancestry Group10aExome10aGenotype10aHeterozygote10aHumans10aLiver10aMutation10aRisk Factors10aSequence Analysis, DNA10aTriglycerides1 aTG and HDL Working Group of the Exome Sequencing Project, National Heart, Lung, and Blood Institute1 aCrosby, Jacy1 aPeloso, Gina, M1 aAuer, Paul, L1 aCrosslin, David, R1 aStitziel, Nathan, O1 aLange, Leslie, A1 aLu, Yingchang1 aTang, Zheng-Zheng1 aZhang, He1 aHindy, George1 aMasca, Nicholas1 aStirrups, Kathleen1 aKanoni, Stavroula1 aDo, Ron1 aJun, Goo1 aHu, Youna1 aKang, Hyun, Min1 aXue, Chenyi1 aGoel, Anuj1 aFarrall, Martin1 aDuga, Stefano1 aMerlini, Pier, Angelica1 aAsselta, Rosanna1 aGirelli, Domenico1 aOlivieri, Oliviero1 aMartinelli, Nicola1 aYin, Wu1 aReilly, Dermot1 aSpeliotes, Elizabeth1 aFox, Caroline, S1 aHveem, Kristian1 aHolmen, Oddgeir, L1 aNikpay, Majid1 aFarlow, Deborah, N1 aAssimes, Themistocles, L1 aFranceschini, Nora1 aRobinson, Jennifer1 aNorth, Kari, E1 aMartin, Lisa, W1 aDePristo, Mark1 aGupta, Namrata1 aEscher, Stefan, A1 aJansson, Jan-Håkan1 aVan Zuydam, Natalie1 aPalmer, Colin, N A1 aWareham, Nicholas1 aKoch, Werner1 aMeitinger, Thomas1 aPeters, Annette1 aLieb, Wolfgang1 aErbel, Raimund1 aKönig, Inke, R1 aKruppa, Jochen1 aDegenhardt, Franziska1 aGottesman, Omri1 aBottinger, Erwin, P1 aO'Donnell, Christopher, J1 aPsaty, Bruce, M1 aBallantyne, Christie, M1 aAbecasis, Goncalo1 aOrdovas, Jose, M1 aMelander, Olle1 aWatkins, Hugh1 aOrho-Melander, Marju1 aArdissino, Diego1 aLoos, Ruth, J F1 aMcPherson, Ruth1 aWiller, Cristen, J1 aErdmann, Jeanette1 aHall, Alistair, S1 aSamani, Nilesh, J1 aDeloukas, Panos1 aSchunkert, Heribert1 aWilson, James, G1 aKooperberg, Charles1 aRich, Stephen, S1 aTracy, Russell, P1 aLin, Dan-Yu1 aAltshuler, David1 aGabriel, Stacey1 aNickerson, Deborah, A1 aJarvik, Gail, P1 aCupples, Adrienne, L1 aReiner, Alex, P1 aBoerwinkle, Eric1 aKathiresan, Sekar uhttps://chs-nhlbi.org/node/660503769nas a2200937 4500008004100000022001400041245009400055210006900149260001600218300001200234490000700246520111800253653002201371653001601393653002301409653004001432653001101472653001701483653002201500653003401522653001101556653001401567653001801581100002501599700001801624700001801642700002501660700002101685700001801706700002301724700002301747700002201770700001201792700002001804700002301824700002201847700002201869700002001891700002801911700002201939700002201961700002001983700002302003700001802026700002802044700001802072700002202090700002202112700001902134700002002153700001702173700002302190700002302213700002202236700002102258700001802279700002202297700002202319700002202341700002002363700002202383700001402405700001502419700002202434700002202456700002402478700002402502700002402526700001702550700002202567700001702589700002102606700002402627700002302651700002502674700002302699700002402722700002402746700002502770856003602795 2014 eng d a1460-208300aMeta-analysis of loci associated with age at natural menopause in African-American women.0 aMetaanalysis of loci associated with age at natural menopause in c2014 Jun 15 a3327-420 v233 aAge at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA.
10aAfrican Americans10aAge Factors10aChromosomes, Human10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenetic Variation10aGenome-Wide Association Study10aHumans10aMenopause10aUnited States1 aChen, Christina, T L1 aLiu, Ching-Ti1 aChen, Gary, K1 aAndrews, Jeanette, S1 aArnold, Alice, M1 aDreyfus, Jill1 aFranceschini, Nora1 aGarcia, Melissa, E1 aKerr, Kathleen, F1 aLi, Guo1 aLohman, Kurt, K1 aMusani, Solomon, K1 aNalls, Michael, A1 aRaffel, Leslie, J1 aSmith, Jennifer1 aAmbrosone, Christine, B1 aBandera, Elisa, V1 aBernstein, Leslie1 aBritton, Angela1 aBrzyski, Robert, G1 aCappola, Anne1 aCarlson, Christopher, S1 aCouper, David1 aDeming, Sandra, L1 aGoodarzi, Mark, O1 aHeiss, Gerardo1 aJohn, Esther, M1 aLu, Xiaoning1 aLe Marchand, Loïc1 aMarciante, Kristin1 aMcKnight, Barbara1 aMillikan, Robert1 aNock, Nora, L1 aOlshan, Andrew, F1 aPress, Michael, F1 aVaiyda, Dhananjay1 aWoods, Nancy, F1 aTaylor, Herman, A1 aZhao, Wei1 aZheng, Wei1 aEvans, Michele, K1 aHarris, Tamara, B1 aHenderson, Brian, E1 aKardia, Sharon, L R1 aKooperberg, Charles1 aLiu, Yongmei1 aMosley, Thomas, H1 aPsaty, Bruce1 aWellons, Melissa1 aWindham, Beverly, G1 aZonderman, Alan, B1 aCupples, Adrienne, L1 aDemerath, Ellen, W1 aHaiman, Christopher1 aMurabito, Joanne, M1 aRajkovic, Aleksandar uhttps://chs-nhlbi.org/node/655204315nas a2200901 4500008004100000022001400041245006300055210006000118260001600178300001200194490000700206520174600213653002201959653003701981653001802018653004002036653001802076653003402094653001302128653001102141653002002152653001502172653002702187653001402214653003602228653002802264100002302292700002502315700002002340700002602360700002302386700002002409700002102429700002202450700002002472700002002492700002302512700002202535700001902557700002002576700002502596700001802621700001902639700002102658700002102679700002402700700002102724700001602745700001402761700002102775700002302796700002002819700002202839700002102861700001902882700001502901700001902916700002102935700001902956700002802975700002303003700002103026700001803047700002503065700002003090700002303110700002503133700002203158700003003180700002303210700002103233700002203254700001903276710002203295710001103317710004903328856003603377 2014 eng d a1460-208300aTrans-ethnic meta-analysis of white blood cell phenotypes.0 aTransethnic metaanalysis of white blood cell phenotypes c2014 Dec 20 a6944-600 v233 aWhite blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.
10aAfrican Americans10aAsian Continental Ancestry Group10aBayes Theorem10aEuropean Continental Ancestry Group10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aLeukocyte Count10aLeukocytes10aLinkage Disequilibrium10aPhenotype10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci1 aKeller, Margaux, F1 aReiner, Alexander, P1 aOkada, Yukinori1 avan Rooij, Frank, J A1 aJohnson, Andrew, D1 aChen, Ming-Huei1 aSmith, Albert, V1 aMorris, Andrew, P1 aTanaka, Toshiko1 aFerrucci, Luigi1 aZonderman, Alan, B1 aLettre, Guillaume1 aHarris, Tamara1 aGarcia, Melissa1 aBandinelli, Stefania1 aQayyum, Rehan1 aYanek, Lisa, R1 aBecker, Diane, M1 aBecker, Lewis, C1 aKooperberg, Charles1 aKeating, Brendan1 aReis, Jared1 aTang, Hua1 aBoerwinkle, Eric1 aKamatani, Yoichiro1 aMatsuda, Koichi1 aKamatani, Naoyuki1 aNakamura, Yusuke1 aKubo, Michiaki1 aLiu, Simin1 aDehghan, Abbas1 aFelix, Janine, F1 aHofman, Albert1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aFranco, Oscar, H1 aLongo, Dan, L1 aSingleton, Andrew, B1 aPsaty, Bruce, M1 aEvans, Michelle, K1 aCupples, Adrienne, L1 aRotter, Jerome, I1 aO'Donnell, Christopher, J1 aTakahashi, Atsushi1 aWilson, James, G1 aGanesh, Santhi, K1 aNalls, Mike, A1 aCHARGE Hematology1 aCOGENT1 aBioBank Japan Project (RIKEN) Working Groups uhttps://chs-nhlbi.org/node/657305955nas a2201657 4500008004100000022001400041245011000055210006900165260001600234300001100250490000700261520138800268653001001656653000901666653002201675653002101697653001901718653001801737653001001755653001101765653002201776653001901798653001701817653003401834653001301868653001101881653001101892653000901903653001601912653001401928653003601942653002801978653002702006653001902033653002702052653002602079100002102105700001402126700001402140700001602154700002202170700002202192700001702214700002002231700002102251700002102272700001302293700002002306700001702326700001502343700001702358700002002375700001402395700002702409700001802436700002202454700001602476700001902492700001702511700002102528700002302549700002002572700001802592700002202610700001802632700001502650700001202665700001702677700001502694700001802709700001902727700001902746700001902765700002502784700002602809700002102835700002502856700002102881700001902902700002502921700001702946700002502963700001202988700002303000700002003023700002603043700002903069700002303098700002803121700001803149700002003167700002303187700002103210700001903231700001803250700002803268700001903296700002403315700002303339700002803362700001703390700002203407700002203429700002403451700002403475700002003499700002303519700002203542700001603564700001703580700002403597700002003621700001803641700002003659700002103679700001603700700001903716700002203735700002803757700002303785700003003808700001903838700001903857700002503876700002103901700002003922700002103942700002203963700001603985700002004001700002504021700002404046700002104070700002604091700002504117700002104142700002204163700002304185710005304208856003604261 2014 eng d a1537-660500aWhole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.0 aWholeexome sequencing identifies rare and lowfrequency coding va c2014 Feb 06 a233-450 v943 aElevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.
10aAdult10aAged10aApolipoproteins E10aCholesterol, LDL10aCohort Studies10aDyslipidemias10aExome10aFemale10aFollow-Up Studies10aGene Frequency10aGenetic Code10aGenome-Wide Association Study10aGenotype10aHumans10aLipase10aMale10aMiddle Aged10aPhenotype10aPolymorphism, Single Nucleotide10aProprotein Convertase 910aProprotein Convertases10aReceptors, LDL10aSequence Analysis, DNA10aSerine Endopeptidases1 aLange, Leslie, A1 aHu, Youna1 aZhang, He1 aXue, Chenyi1 aSchmidt, Ellen, M1 aTang, Zheng-Zheng1 aBizon, Chris1 aLange, Ethan, M1 aSmith, Joshua, D1 aTurner, Emily, H1 aJun, Goo1 aKang, Hyun, Min1 aPeloso, Gina1 aAuer, Paul1 aLi, Kuo-Ping1 aFlannick, Jason1 aZhang, Ji1 aFuchsberger, Christian1 aGaulton, Kyle1 aLindgren, Cecilia1 aLocke, Adam1 aManning, Alisa1 aSim, Xueling1 aRivas, Manuel, A1 aHolmen, Oddgeir, L1 aGottesman, Omri1 aLu, Yingchang1 aRuderfer, Douglas1 aStahl, Eli, A1 aDuan, Qing1 aLi, Yun1 aDurda, Peter1 aJiao, Shuo1 aIsaacs, Aaron1 aHofman, Albert1 aBis, Joshua, C1 aCorrea, Adolfo1 aGriswold, Michael, E1 aJakobsdottir, Johanna1 aSmith, Albert, V1 aSchreiner, Pamela, J1 aFeitosa, Mary, F1 aZhang, Qunyuan1 aHuffman, Jennifer, E1 aCrosby, Jacy1 aWassel, Christina, L1 aDo, Ron1 aFranceschini, Nora1 aMartin, Lisa, W1 aRobinson, Jennifer, G1 aAssimes, Themistocles, L1 aCrosslin, David, R1 aRosenthal, Elisabeth, A1 aTsai, Michael1 aRieder, Mark, J1 aFarlow, Deborah, N1 aFolsom, Aaron, R1 aLumley, Thomas1 aFox, Ervin, R1 aCarlson, Christopher, S1 aPeters, Ulrike1 aJackson, Rebecca, D1 aDuijn, Cornelia, M1 aUitterlinden, André, G1 aLevy, Daniel1 aRotter, Jerome, I1 aTaylor, Herman, A1 aGudnason, Vilmundur1 aSiscovick, David, S1 aFornage, Myriam1 aBorecki, Ingrid, B1 aHayward, Caroline1 aRudan, Igor1 aChen, Eugene1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aSætrom, Pål1 aHveem, Kristian1 aBoehnke, Michael1 aGroop, Leif1 aMcCarthy, Mark1 aMeitinger, Thomas1 aBallantyne, Christie, M1 aGabriel, Stacey, B1 aO'Donnell, Christopher, J1 aPost, Wendy, S1 aNorth, Kari, E1 aReiner, Alexander, P1 aBoerwinkle, Eric1 aPsaty, Bruce, M1 aAltshuler, David1 aKathiresan, Sekar1 aLin, Dan-Yu1 aJarvik, Gail, P1 aCupples, Adrienne, L1 aKooperberg, Charles1 aWilson, James, G1 aNickerson, Deborah, A1 aAbecasis, Goncalo, R1 aRich, Stephen, S1 aTracy, Russell, P1 aWiller, Cristen, J1 aNHLBI Grand Opportunity Exome Sequencing Project uhttps://chs-nhlbi.org/node/657704486nas a2200901 4500008004100000022001400041245009600055210006900151260001600220300001100236490000700247520184700254653001002101653002202111653002302133653002802156653001902184653004002203653001002243653001102253653001902264653003802283653003402321653003802355653001102393653000902404653001102413653003602424653002902460653001702489100002202506700001802528700001902546700001902565700001402584700002102598700002102619700002002640700002402660700001902684700002802703700002002731700002202751700001202773700002402785700002402809700002102833700002002854700002102874700001902895700002102914700001602935700002002951700001502971700001902986700002003005700001803025700002103043700001803064700002203082700002403104700002303128700002303151700001903174700002603193700002203219700001903241700001903260700002103279700002103300700002403321700002403345700002003369700002003389710006503409710007403474856003603548 2015 eng d a1460-208300aAssociation of exome sequences with plasma C-reactive protein levels in >9000 participants.0 aAssociation of exome sequences with plasma Creactive protein lev c2015 Jan 15 a559-710 v243 aC-reactive protein (CRP) concentration is a heritable systemic marker of inflammation that is associated with cardiovascular disease risk. Genome-wide association studies have identified CRP-associated common variants associated in ∼25 genes. Our aims were to apply exome sequencing to (1) assess whether the candidate loci contain rare coding variants associated with CRP levels and (2) perform an exome-wide search for rare variants in novel genes associated with CRP levels. We exome-sequenced 6050 European-Americans (EAs) and 3109 African-Americans (AAs) from the NHLBI-ESP and the CHARGE consortia, and performed association tests of sequence data with measured CRP levels. In single-variant tests across candidate loci, a novel rare (minor allele frequency = 0.16%) CRP-coding variant (rs77832441-A; p.Thr59Met) was associated with 53% lower mean CRP levels (P = 2.9 × 10(-6)). We replicated the association of rs77832441 in an exome array analysis of 11 414 EAs (P = 3.0 × 10(-15)). Despite a strong effect on CRP levels, rs77832441 was not associated with inflammation-related phenotypes including coronary heart disease. We also found evidence for an AA-specific association of APOE-ε2 rs7214 with higher CRP levels. At the exome-wide significance level (P < 5.0 × 10(-8)), we confirmed associations for reported common variants of HNF1A, CRP, IL6R and TOMM40-APOE. In gene-based tests, a burden of rare/lower frequency variation in CRP in EAs (P ≤ 6.8 × 10(-4)) and in retinoic acid receptor-related orphan receptor α (RORA) in AAs (P = 1.7 × 10(-3)) were associated with CRP levels at the candidate gene level (P < 2.0 × 10(-3)). This inquiry did not elucidate novel genes, but instead demonstrated that variants distributed across the allele frequency spectrum within candidate genes contribute to CRP levels.
10aAdult10aAfrican Americans10aC-Reactive Protein10aCardiovascular Diseases10aCohort Studies10aEuropean Continental Ancestry Group10aExome10aFemale10aGene Frequency10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHepatocyte Nuclear Factor 1-alpha10aHumans10aMale10aPlasma10aPolymorphism, Single Nucleotide10aReceptors, Interleukin-610aRisk Factors1 aSchick, Ursula, M1 aAuer, Paul, L1 aBis, Joshua, C1 aLin, Honghuang1 aWei, Peng1 aPankratz, Nathan1 aLange, Leslie, A1 aBrody, Jennifer1 aStitziel, Nathan, O1 aKim, Daniel, S1 aCarlson, Christopher, S1 aFornage, Myriam1 aHaessler, Jeffery1 aHsu, Li1 aJackson, Rebecca, D1 aKooperberg, Charles1 aLeal, Suzanne, M1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aTracy, Russell1 aArdissino, Diego1 aShah, Svati1 aWiller, Cristen1 aLoos, Ruth1 aMelander, Olle1 aMcPherson, Ruth1 aHovingh, Kees1 aReilly, Muredach1 aWatkins, Hugh1 aGirelli, Domenico1 aFontanillas, Pierre1 aChasman, Daniel, I1 aGabriel, Stacey, B1 aGibbs, Richard1 aNickerson, Deborah, A1 aKathiresan, Sekar1 aPeters, Ulrike1 aDupuis, Josée1 aWilson, James, G1 aRich, Stephen, S1 aMorrison, Alanna, C1 aBenjamin, Emelia, J1 aGross, Myron, D1 aReiner, Alex, P1 aCohorts for Heart and Aging Research in Genomic Epidemiology1 aNational Heart, Lung, and Blood Institute GO Exome Sequencing Project uhttps://chs-nhlbi.org/node/659706191nas a2201513 4500008004100000022001400041245010300055210006900158260001500227300001000242490000800252520194100260653001602201653001702217653001202234653002202246653002502268653002102293653002802314653001002342653001102352653003802363653002502401653001702426653001102443653000902454653001602463653001302479653002602492653005302518653001902571653001802590653001802608100001202626700002402638700001802662700002902680700001802709700002802727700001702755700002002772700001502792700001202807700002002819700002102839700002102860700002002881700001802901700002202919700002302941700002302964700002202987700002003009700002803029700002103057700001703078700002403095700002803119700001803147700002303165700002203188700002403210700002203234700001903256700002203275700001903297700001803316700002903334700001503363700002203378700002003400700002003420700002203440700001503462700002303477700001603500700001903516700001703535700001703552700002903569700001903598700002003617700002103637700002203658700002303680700002003703700001903723700002203742700001203764700002103776700002003797700002403817700002003841700002503861700002103886700002103907700002403928700002203952700002503974700002103999700002404020700002104044700001904065700002004084700002204104700002204126700002004148700002004168700002804188700002404216700002404240700002104264700002004285700002504305700002404330700002004354700002604374700002504400700001804425700002604443700002104469700002304490700003004513700002104543700002004564700002204584710003504606856003604641 2015 eng d a1476-468700aExome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction.0 aExome sequencing identifies rare LDLR and APOA5 alleles conferri c2015 Feb 5 a102-60 v5183 aMyocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
10aAge Factors10aAge of Onset10aAlleles10aApolipoproteins A10aCase-Control Studies10aCholesterol, LDL10aCoronary Artery Disease10aExome10aFemale10aGenetic Predisposition to Disease10aGenetics, Population10aHeterozygote10aHumans10aMale10aMiddle Aged10aMutation10aMyocardial Infarction10aNational Heart, Lung, and Blood Institute (U.S.)10aReceptors, LDL10aTriglycerides10aUnited States1 aDo, Ron1 aStitziel, Nathan, O1 aWon, Hong-Hee1 aJørgensen, Anders, Berg1 aDuga, Stefano1 aMerlini, Pier, Angelica1 aKiezun, Adam1 aFarrall, Martin1 aGoel, Anuj1 aZuk, Or1 aGuella, Illaria1 aAsselta, Rosanna1 aLange, Leslie, A1 aPeloso, Gina, M1 aAuer, Paul, L1 aGirelli, Domenico1 aMartinelli, Nicola1 aFarlow, Deborah, N1 aDePristo, Mark, A1 aRoberts, Robert1 aStewart, Alexander, F R1 aSaleheen, Danish1 aDanesh, John1 aEpstein, Stephen, E1 aSivapalaratnam, Suthesh1 aHovingh, Kees1 aKastelein, John, J1 aSamani, Nilesh, J1 aSchunkert, Heribert1 aErdmann, Jeanette1 aShah, Svati, H1 aKraus, William, E1 aDavies, Robert1 aNikpay, Majid1 aJohansen, Christopher, T1 aWang, Jian1 aHegele, Robert, A1 aHechter, Eliana1 aMärz, Winfried1 aKleber, Marcus, E1 aHuang, Jie1 aJohnson, Andrew, D1 aLi, Mingyao1 aBurke, Greg, L1 aGross, Myron1 aLiu, Yongmei1 aAssimes, Themistocles, L1 aHeiss, Gerardo1 aLange, Ethan, M1 aFolsom, Aaron, R1 aTaylor, Herman, A1 aOlivieri, Oliviero1 aHamsten, Anders1 aClarke, Robert1 aReilly, Dermot, F1 aYin, Wu1 aRivas, Manuel, A1 aDonnelly, Peter1 aRossouw, Jacques, E1 aPsaty, Bruce, M1 aHerrington, David, M1 aWilson, James, G1 aRich, Stephen, S1 aBamshad, Michael, J1 aTracy, Russell, P1 aCupples, Adrienne, L1 aRader, Daniel, J1 aReilly, Muredach, P1 aSpertus, John, A1 aCresci, Sharon1 aHartiala, Jaana1 aTang, W, H Wilson1 aHazen, Stanley, L1 aAllayee, Hooman1 aReiner, Alex, P1 aCarlson, Christopher, S1 aKooperberg, Charles1 aJackson, Rebecca, D1 aBoerwinkle, Eric1 aLander, Eric, S1 aSchwartz, Stephen, M1 aSiscovick, David, S1 aMcPherson, Ruth1 aTybjaerg-Hansen, Anne1 aAbecasis, Goncalo, R1 aWatkins, Hugh1 aNickerson, Deborah, A1 aArdissino, Diego1 aSunyaev, Shamil, R1 aO'Donnell, Christopher, J1 aAltshuler, David1 aGabriel, Stacey1 aKathiresan, Sekar1 aNHLBI Exome Sequencing Project uhttps://chs-nhlbi.org/node/669103753nas a2200601 4500008004100000022001400041245011800055210006900173260001300242300001100255490000700266520199300273653002202266653002502288653001902313653003802332653003402370653001102404653003602415653001702451653001102468100001902479700002002498700002002518700002202538700001802560700001602578700001902594700002302613700002102636700002102657700002302678700002202701700002302723700002302746700002202769700001702791700001602808700002002824700001702844700002202861700002102883700001802904700002002922700002502942700002002967700002402987700002203011700002503033700002003058710003703078856003603115 2015 eng d a1524-462800aMeta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans.0 aMetaAnalysis of GenomeWide Association Studies Identifies Geneti c2015 Aug a2063-80 v463 aBACKGROUND AND PURPOSE: The majority of genome-wide association studies (GWAS) of stroke have focused on European-ancestry populations; however, none has been conducted in African Americans, despite the disproportionately high burden of stroke in this population. The Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) was established to identify stroke susceptibility loci in minority populations.
METHODS: Using METAL, we conducted meta-analyses of GWAS in 14 746 African Americans (1365 ischemic and 1592 total stroke cases) from COMPASS, and tested genetic variants with P<10(-6) for validation in METASTROKE, a consortium of ischemic stroke genetic studies in European-ancestry populations. We also evaluated stroke loci previously identified in European-ancestry populations.
RESULTS: The 15q21.3 locus linked with lipid levels and hypertension was associated with total stroke (rs4471613; P=3.9×10(-8)) in African Americans. Nominal associations (P<10(-6)) for total or ischemic stroke were observed for 18 variants in or near genes implicated in cell cycle/mRNA presplicing (PTPRG, CDC5L), platelet function (HPS4), blood-brain barrier permeability (CLDN17), immune response (ELTD1, WDFY4, and IL1F10-IL1RN), and histone modification (HDAC9). Two of these loci achieved nominal significance in METASTROKE: 5q35.2 (P=0.03), and 1p31.1 (P=0.018). Four of 7 previously reported ischemic stroke loci (PITX2, HDAC9, CDKN2A/CDKN2B, and ZFHX3) were nominally associated (P<0.05) with stroke in COMPASS.
CONCLUSIONS: We identified a novel genetic variant associated with total stroke in African Americans and found that ischemic stroke loci identified in European-ancestry populations may also be relevant for African Americans. Our findings support investigation of diverse populations to identify and characterize genetic risk factors, and the importance of shared genetic risk across populations.
10aAfrican Americans10aCase-Control Studies10aCohort Studies10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aPolymorphism, Single Nucleotide10aRisk Factors10aStroke1 aCarty, Cara, L1 aKeene, Keith, L1 aCheng, Yu-Ching1 aMeschia, James, F1 aChen, Wei-Min1 aNalls, Mike1 aBis, Joshua, C1 aKittner, Steven, J1 aRich, Stephen, S1 aTajuddin, Salman1 aZonderman, Alan, B1 aEvans, Michele, K1 aLangefeld, Carl, D1 aGottesman, Rebecca1 aMosley, Thomas, H1 aShahar, Eyal1 aWoo, Daniel1 aYaffe, Kristine1 aLiu, Yongmei1 aSale, Michèle, M1 aDichgans, Martin1 aMalik, Rainer1 aLongstreth, W T1 aMitchell, Braxton, D1 aPsaty, Bruce, M1 aKooperberg, Charles1 aReiner, Alexander1 aWorrall, Bradford, B1 aFornage, Myriam1 aCOMPASS and METASTROKE Consortia uhttps://chs-nhlbi.org/node/681204841nas a2200685 4500008004100000022001400041245011900055210006900174260001300243300001000256490000700266520281800273653000903091653001903100653001003119653001103129653003803140653002203178653003403200653001103234653000903245653001603254653002003270653005303290653002103343653002403364653002803388653001103416653001803427100001803445700001603463700002203479700002503501700002003526700002003546700002403566700002403590700002803614700001903642700001803661700002503679700002403704700002003728700001603748700001203764700002403776700002003800700001903820700002903839700002103868700002103889700002203910700002503932700002503957700002603982700001904008700002104027710007104048856003604119 2015 eng d a2168-615700aRare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project.0 aRare and Coding Region Genetic Variants Associated With Risk of c2015 Jul a781-80 v723 aIMPORTANCE: Stroke is the second leading cause of death and the third leading cause of years of life lost. Genetic factors contribute to stroke prevalence, and candidate gene and genome-wide association studies (GWAS) have identified variants associated with ischemic stroke risk. These variants often have small effects without obvious biological significance. Exome sequencing may discover predicted protein-altering variants with a potentially large effect on ischemic stroke risk.
OBJECTIVE: To investigate the contribution of rare and common genetic variants to ischemic stroke risk by targeting the protein-coding regions of the human genome.
DESIGN, SETTING, AND PARTICIPANTS: The National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP) analyzed approximately 6000 participants from numerous cohorts of European and African ancestry. For discovery, 365 cases of ischemic stroke (small-vessel and large-vessel subtypes) and 809 European ancestry controls were sequenced; for replication, 47 affected sibpairs concordant for stroke subtype and an African American case-control series were sequenced, with 1672 cases and 4509 European ancestry controls genotyped. The ESP's exome sequencing and genotyping started on January 1, 2010, and continued through June 30, 2012. Analyses were conducted on the full data set between July 12, 2012, and July 13, 2013.
MAIN OUTCOMES AND MEASURES: Discovery of new variants or genes contributing to ischemic stroke risk and subtype (primary analysis) and determination of support for protein-coding variants contributing to risk in previously published candidate genes (secondary analysis).
RESULTS: We identified 2 novel genes associated with an increased risk of ischemic stroke: a protein-coding variant in PDE4DIP (rs1778155; odds ratio, 2.15; P = 2.63 × 10(-8)) with an intracellular signal transduction mechanism and in ACOT4 (rs35724886; odds ratio, 2.04; P = 1.24 × 10(-7)) with a fatty acid metabolism; confirmation of PDE4DIP was observed in affected sibpair families with large-vessel stroke subtype and in African Americans. Replication of protein-coding variants in candidate genes was observed for 2 previously reported GWAS associations: ZFHX3 (cardioembolic stroke) and ABCA1 (large-vessel stroke).
CONCLUSIONS AND RELEVANCE: Exome sequencing discovered 2 novel genes and mechanisms, PDE4DIP and ACOT4, associated with increased risk for ischemic stroke. In addition, ZFHX3 and ABCA1 were discovered to have protein-coding variants associated with ischemic stroke. These results suggest that genetic variation in novel pathways contributes to ischemic stroke risk and serves as a target for prediction, prevention, and therapy.
10aAged10aBrain Ischemia10aExome10aFemale10aGenetic Predisposition to Disease10aGenetic Variation10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aMuscle Proteins10aNational Heart, Lung, and Blood Institute (U.S.)10aNuclear Proteins10aOpen Reading Frames10aPalmitoyl-CoA Hydrolase10aStroke10aUnited States1 aAuer, Paul, L1 aNalls, Mike1 aMeschia, James, F1 aWorrall, Bradford, B1 aLongstreth, W T1 aSeshadri, Sudha1 aKooperberg, Charles1 aBurger, Kathleen, M1 aCarlson, Christopher, S1 aCarty, Cara, L1 aChen, Wei-Min1 aCupples, Adrienne, L1 aDeStefano, Anita, L1 aFornage, Myriam1 aHardy, John1 aHsu, Li1 aJackson, Rebecca, D1 aJarvik, Gail, P1 aKim, Daniel, S1 aLakshminarayan, Kamakshi1 aLange, Leslie, A1 aManichaikul, Ani1 aQuinlan, Aaron, R1 aSingleton, Andrew, B1 aThornton, Timothy, A1 aNickerson, Deborah, A1 aPeters, Ulrike1 aRich, Stephen, S1 aNational Heart, Lung, and Blood Institute Exome Sequencing Project uhttps://chs-nhlbi.org/node/684904476nas a2201081 4500008004100000022001400041245011400055210006900169260001600238300001100254490000800265520141200273653001901685653001501704653001601719653001501735653001901750653003201769653002201801653001101823653002601834653003601860653002301896653002601919100002501945700002201970700002401992700002502016700002002041700001802061700002302079700002302102700002002125700001702145700001502162700002502177700003002202700001902232700002102251700002002272700002502292700001802317700002202335700001502357700002002372700002102392700001902413700001802432700002602450700001902476700001502495700002002510700002202530700002802552700002202580700001302602700001802615700001702633700002602650700002102676700002102697700002302718700002402741700001902765700002402784700002402808700002102832700001902853700002402872700002502896700002002921700002202941700002102963700001602984700002303000700002003023700002003043700002403063700001703087700001803104700002003122700002003142700001803162700002103180700002103201700002203222700002203244700001903266700002003285700003003305700002303335856003603358 2015 eng d a1528-002000aRare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF.0 aRare and lowfrequency variants and their association with plasma c2015 Sep 10 ae19-290 v1263 aFibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.
10aCohort Studies10aFactor VII10aFactor VIII10aFibrinogen10aGene Frequency10aGenetic Association Studies10aGenetic Variation10aHumans10aNerve Tissue Proteins10aPolymorphism, Single Nucleotide10aPotassium Channels10avon Willebrand Factor1 aHuffman, Jennifer, E1 ade Vries, Paul, S1 aMorrison, Alanna, C1 aSabater-Lleal, Maria1 aKacprowski, Tim1 aAuer, Paul, L1 aBrody, Jennifer, A1 aChasman, Daniel, I1 aChen, Ming-Huei1 aGuo, Xiuqing1 aLin, Li-An1 aMarioni, Riccardo, E1 aMüller-Nurasyid, Martina1 aYanek, Lisa, R1 aPankratz, Nathan1 aGrove, Megan, L1 ade Maat, Moniek, P M1 aCushman, Mary1 aWiggins, Kerri, L1 aQi, Lihong1 aSennblad, Bengt1 aHarris, Sarah, E1 aPolasek, Ozren1 aRiess, Helene1 aRivadeneira, Fernando1 aRose, Lynda, M1 aGoel, Anuj1 aTaylor, Kent, D1 aTeumer, Alexander1 aUitterlinden, André, G1 aVaidya, Dhananjay1 aYao, Jie1 aTang, Weihong1 aLevy, Daniel1 aWaldenberger, Melanie1 aBecker, Diane, M1 aFolsom, Aaron, R1 aGiulianini, Franco1 aGreinacher, Andreas1 aHofman, Albert1 aHuang, Chiang-Ching1 aKooperberg, Charles1 aSilveira, Angela1 aStarr, John, M1 aStrauch, Konstantin1 aStrawbridge, Rona, J1 aWright, Alan, F1 aMcKnight, Barbara1 aFranco, Oscar, H1 aZakai, Neil1 aMathias, Rasika, A1 aPsaty, Bruce, M1 aRidker, Paul, M1 aTofler, Geoffrey, H1 aVölker, Uwe1 aWatkins, Hugh1 aFornage, Myriam1 aHamsten, Anders1 aDeary, Ian, J1 aBoerwinkle, Eric1 aKoenig, Wolfgang1 aRotter, Jerome, I1 aHayward, Caroline1 aDehghan, Abbas1 aReiner, Alex, P1 aO'Donnell, Christopher, J1 aSmith, Nicholas, L uhttps://chs-nhlbi.org/node/678804937nas a2201345 4500008004100000022001400041245012400055210006900179260001300248300001200261490000700273520113500280100001601415700001901431700002301450700002301473700002301496700001901519700001801538700002401556700001801580700001801598700001701616700001901633700002001652700002201672700002301694700001901717700001901736700001801755700001901773700001601792700001401808700002601822700001501848700002601863700001601889700001301905700001301918700001901931700002201950700002001972700002101992700002002013700001402033700001902047700001802066700002402084700002202108700001902130700002402149700002002173700001202193700002702205700002202232700002002254700002402274700002802298700002402326700002102350700002402371700002102395700002202416700002802438700002102466700002702487700003002514700002002544700001502564700002402579700002002603700001702623700002302640700001902663700001902682700002202701700002202723700001802745700002202763700001902785700001902804700001402823700001802837700001402855700002102869700002302890700002802913700001702941700001902958700001902977700001702996700002003013700002103033700002403054700002503078700002303103700002303126700002103149700002603170700002203196700002003218700002003238700002003258700002003278700002903298700001703327700002303344710002603367710002303393710002603416710002503442710006603467710002203533856003603555 2016 eng d a1546-171800aMeta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci.0 aMetaanalysis identifies common and rare variants influencing blo c2016 Oct a1162-700 v483 aMeta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.
1 aLiu, Chunyu1 aKraja, Aldi, T1 aSmith, Jennifer, A1 aBrody, Jennifer, A1 aFranceschini, Nora1 aBis, Joshua, C1 aRice, Kenneth1 aMorrison, Alanna, C1 aLu, Yingchang1 aWeiss, Stefan1 aGuo, Xiuqing1 aPalmas, Walter1 aMartin, Lisa, W1 aChen, Yii-Der Ida1 aSurendran, Praveen1 aDrenos, Fotios1 aCook, James, P1 aAuer, Paul, L1 aChu, Audrey, Y1 aGiri, Ayush1 aZhao, Wei1 aJakobsdottir, Johanna1 aLin, Li-An1 aStafford, Jeanette, M1 aAmin, Najaf1 aMei, Hao1 aYao, Jie1 aVoorman, Arend1 aLarson, Martin, G1 aGrove, Megan, L1 aSmith, Albert, V1 aHwang, Shih-Jen1 aChen, Han1 aHuan, Tianxiao1 aKosova, Gulum1 aStitziel, Nathan, O1 aKathiresan, Sekar1 aSamani, Nilesh1 aSchunkert, Heribert1 aDeloukas, Panos1 aLi, Man1 aFuchsberger, Christian1 aPattaro, Cristian1 aGorski, Mathias1 aKooperberg, Charles1 aPapanicolaou, George, J1 aRossouw, Jacques, E1 aFaul, Jessica, D1 aKardia, Sharon, L R1 aBouchard, Claude1 aRaffel, Leslie, J1 aUitterlinden, André, G1 aFranco, Oscar, H1 aVasan, Ramachandran, S1 aO'Donnell, Christopher, J1 aTaylor, Kent, D1 aLiu, Kiang1 aBottinger, Erwin, P1 aGottesman, Omri1 aDaw, Warwick1 aGiulianini, Franco1 aGanesh, Santhi1 aSalfati, Elias1 aHarris, Tamara, B1 aLauner, Lenore, J1 aDörr, Marcus1 aFelix, Stephan, B1 aRettig, Rainer1 aVölzke, Henry1 aKim, Eric1 aLee, Wen-Jane1 aLee, I-Te1 aSheu, Wayne, H-H1 aTsosie, Krystal, S1 aEdwards, Digna, R Velez1 aLiu, Yongmei1 aCorrea, Adolfo1 aWeir, David, R1 aVölker, Uwe1 aRidker, Paul, M1 aBoerwinkle, Eric1 aGudnason, Vilmundur1 aReiner, Alexander, P1 aDuijn, Cornelia, M1 aBorecki, Ingrid, B1 aEdwards, Todd, L1 aChakravarti, Aravinda1 aRotter, Jerome, I1 aPsaty, Bruce, M1 aLoos, Ruth, J F1 aFornage, Myriam1 aEhret, Georg, B1 aNewton-Cheh, Christopher1 aLevy, Daniel1 aChasman, Daniel, I1 aCHD Exome+ Consortium1 aExomeBP Consortium1 aGoT2DGenes Consortium1 aT2D-GENES Consortium1 aMyocardial Infarction Genetics and CARDIoGRAM Exome Consortia1 aCKDGen Consortium uhttps://chs-nhlbi.org/node/726405818nas a2201705 4500008004100000022001400041245009600055210006900151260001600220300001100236490000700247520107200254100002201326700002301348700002501371700002001396700002501416700002201441700001801463700002201481700002501503700002001528700002301548700002001571700003001591700001901621700002301640700002201663700001701685700001901702700001801721700001901739700001901758700002801777700001601805700002401821700002001845700002401865700002001889700002301909700001801932700001701950700001901967700002701986700001802013700001902031700001702050700001502067700001602082700002102098700002302119700001602142700002202158700002502180700002102205700001802226700002002244700002502264700001302289700002002302700002402322700001802346700002002364700002302384700002302407700002102430700002502451700002402476700001602500700003202516700002002548700002102568700002202589700002402611700002002635700002102655700002502676700001902701700002002720700002802740700001902768700001902787700001702806700002602823700001802849700002202867700001502889700002002904700002702924700001502951700002002966700002102986700001903007700002303026700001903049700002303068700001703091700002003108700002003128700002603148700002203174700002003196700001803216700002103234700002003255700002303275700001703298700001903315700002803334700002003362700001903382700002103401700001903422700001603441700002903457700002103486700002403507700002003531700002003551700002303571700001903594700001803613700002103631700002103652700001903673700002003692700002103712700002003733700002403753700002103777700001903798700002303817700002203840700002103862700001903883700001803902700002003920700002103940700002003961700003003981700002304011700002304034700001904057856003604076 2016 eng d a1460-208300aA meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration.0 ametaanalysis of 120 246 individuals identifies 18 new loci for f c2016 Jan 15 a358-700 v253 aGenome-wide association studies have previously identified 23 genetic loci associated with circulating fibrinogen concentration. These studies used HapMap imputation and did not examine the X-chromosome. 1000 Genomes imputation provides better coverage of uncommon variants, and includes indels. We conducted a genome-wide association analysis of 34 studies imputed to the 1000 Genomes Project reference panel and including ∼120 000 participants of European ancestry (95 806 participants with data on the X-chromosome). Approximately 10.7 million single-nucleotide polymorphisms and 1.2 million indels were examined. We identified 41 genome-wide significant fibrinogen loci; of which, 18 were newly identified. There were no genome-wide significant signals on the X-chromosome. The lead variants of five significant loci were indels. We further identified six additional independent signals, including three rare variants, at two previously characterized loci: FGB and IRF1. Together the 41 loci explain 3% of the variance in plasma fibrinogen concentration.
1 ade Vries, Paul, S1 aChasman, Daniel, I1 aSabater-Lleal, Maria1 aChen, Ming-Huei1 aHuffman, Jennifer, E1 aSteri, Maristella1 aTang, Weihong1 aTeumer, Alexander1 aMarioni, Riccardo, E1 aGrossmann, Vera1 aHottenga, Jouke, J1 aTrompet, Stella1 aMüller-Nurasyid, Martina1 aZhao, Jing Hua1 aBrody, Jennifer, A1 aKleber, Marcus, E1 aGuo, Xiuqing1 aWang, Jie, Jin1 aAuer, Paul, L1 aAttia, John, R1 aYanek, Lisa, R1 aAhluwalia, Tarunveer, S1 aLahti, Jari1 aVenturini, Cristina1 aTanaka, Toshiko1 aBielak, Lawrence, F1 aJoshi, Peter, K1 aRocanin-Arjo, Ares1 aKolcic, Ivana1 aNavarro, Pau1 aRose, Lynda, M1 aOldmeadow, Christopher1 aRiess, Helene1 aMazur, Johanna1 aBasu, Saonli1 aGoel, Anuj1 aYang, Qiong1 aGhanbari, Mohsen1 aWillemsen, Gonneke1 aRumley, Ann1 aFiorillo, Edoardo1 ade Craen, Anton, J M1 aGrotevendt, Anne1 aScott, Robert1 aTaylor, Kent, D1 aDelgado, Graciela, E1 aYao, Jie1 aKifley, Annette1 aKooperberg, Charles1 aQayyum, Rehan1 aLopez, Lorna, M1 aBerentzen, Tina, L1 aRäikkönen, Katri1 aMangino, Massimo1 aBandinelli, Stefania1 aPeyser, Patricia, A1 aWild, Sarah1 aTrégouët, David-Alexandre1 aWright, Alan, F1 aMarten, Jonathan1 aZemunik, Tatijana1 aMorrison, Alanna, C1 aSennblad, Bengt1 aTofler, Geoffrey1 ade Maat, Moniek, P M1 aGeus, Eco, J C1 aLowe, Gordon, D1 aZoledziewska, Magdalena1 aSattar, Naveed1 aBinder, Harald1 aVölker, Uwe1 aWaldenberger, Melanie1 aKhaw, Kay-Tee1 aMcKnight, Barbara1 aHuang, Jie1 aJenny, Nancy, S1 aHolliday, Elizabeth, G1 aQi, Lihong1 aMcevoy, Mark, G1 aBecker, Diane, M1 aStarr, John, M1 aSarin, Antti-Pekka1 aHysi, Pirro, G1 aHernandez, Dena, G1 aJhun, Min, A1 aCampbell, Harry1 aHamsten, Anders1 aRivadeneira, Fernando1 aMcArdle, Wendy, L1 aSlagboom, Eline1 aZeller, Tanja1 aKoenig, Wolfgang1 aPsaty, Bruce, M1 aHaritunians, Talin1 aLiu, Jingmin1 aPalotie, Aarno1 aUitterlinden, André, G1 aStott, David, J1 aHofman, Albert1 aFranco, Oscar, H1 aPolasek, Ozren1 aRudan, Igor1 aMorange, Pierre-Emmanuel1 aWilson, James, F1 aKardia, Sharon, L R1 aFerrucci, Luigi1 aSpector, Tim, D1 aEriksson, Johan, G1 aHansen, Torben1 aDeary, Ian, J1 aBecker, Lewis, C1 aScott, Rodney, J1 aMitchell, Paul1 aMärz, Winfried1 aWareham, Nick, J1 aPeters, Annette1 aGreinacher, Andreas1 aWild, Philipp, S1 aJukema, Wouter1 aBoomsma, Dorret, I1 aHayward, Caroline1 aCucca, Francesco1 aTracy, Russell1 aWatkins, Hugh1 aReiner, Alex, P1 aFolsom, Aaron, R1 aRidker, Paul, M1 aO'Donnell, Christopher, J1 aSmith, Nicholas, L1 aStrachan, David, P1 aDehghan, Abbas uhttps://chs-nhlbi.org/node/693606988nas a2201993 4500008004100000022001400041245011600055210006900171260001600240520137500256100001201631700001301643700001801656700002201674700002201696700002501718700001801743700002701761700002001788700002801808700001901836700002001855700002101875700001801896700001601914700002801930700001901958700002501977700002302002700002302025700002302048700002502071700001902096700002102115700002102136700002202157700002102179700002302200700001502223700001802238700001902256700002102275700001702296700001702313700001602330700002002346700002802366700001802394700001902412700002002431700001702451700001802468700001802486700002202504700002102526700002102547700002902568700002302597700002202620700001702642700002202659700003202681700002102713700002302734700002102757700003102778700001402809700002202823700001902845700001602864700002102880700002102901700002302922700002302945700002402968700001902992700002103011700002303032700002103055700002003076700002403096700001803120700001703138700002003155700001803175700002003193700002403213700002103237700002103258700002503279700002203304700001603326700002103342700001703363700002203380700002303402700002003425700001803445700002403463700002203487700002203509700001903531700001903550700001703569700002803586700002403614700002303638700002503661700002003686700002403706700002103730700002403751700002203775700002203797700002303819700002203842700001703864700002103881700002103902700001703923700002003940700001803960700002503978700001904003700002104022700001904043700002004062700002104082700002504103700001804128700001904146700002004165700001904185700001904204700002004223700002904243700002004272700001104292700002304303700002004326700001904346700002004365700002604385700002404411700001904435700002104454700002004475700002404495700002104519700002304540700002804563700001804591700002304609700001704632700001904649700002604668700001904694700001904713700001804732700002304750700002104773700002304794700002304817700001904840700001904859710003904878710004104917856003604958 2016 eng d a1533-345000aSOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function.0 aSOS2 and ACP1 Loci Identified through LargeScale Exome Chip Anal c2016 Dec 053 aGenome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium (nStage1: 111,666; nStage2: 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea (PPM1J, EDEM3, ACP1, SPEG, EYA4, CYP1A1, and ATXN2L; PStage1<3.7×10(-7)), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 (P=5.4×10(-8) by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2-knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.
1 aLi, Man1 aLi, Yong1 aWeeks, Olivia1 aMijatovic, Vladan1 aTeumer, Alexander1 aHuffman, Jennifer, E1 aTromp, Gerard1 aFuchsberger, Christian1 aGorski, Mathias1 aLyytikäinen, Leo-Pekka1 aNutile, Teresa1 aSedaghat, Sanaz1 aSorice, Rossella1 aTin, Adrienne1 aYang, Qiong1 aAhluwalia, Tarunveer, S1 aArking, Dan, E1 aBihlmeyer, Nathan, A1 aBöger, Carsten, A1 aCarroll, Robert, J1 aChasman, Daniel, I1 aCornelis, Marilyn, C1 aDehghan, Abbas1 aFaul, Jessica, D1 aFeitosa, Mary, F1 aGambaro, Giovanni1 aGasparini, Paolo1 aGiulianini, Franco1 aHeid, Iris1 aHuang, Jinyan1 aImboden, Medea1 aJackson, Anne, U1 aJeff, Janina1 aJhun, Min, A1 aKatz, Ronit1 aKifley, Annette1 aKilpeläinen, Tuomas, O1 aKumar, Ashish1 aLaakso, Markku1 aLi-Gao, Ruifang1 aLohman, Kurt1 aLu, Yingchang1 aMägi, Reedik1 aMalerba, Giovanni1 aMihailov, Evelin1 aMohlke, Karen, L1 aMook-Kanamori, Dennis, O1 aRobino, Antonietta1 aRuderfer, Douglas1 aSalvi, Erika1 aSchick, Ursula, M1 aSchulz, Christina-Alexandra1 aSmith, Albert, V1 aSmith, Jennifer, A1 aTraglia, Michela1 aYerges-Armstrong, Laura, M1 aZhao, Wei1 aGoodarzi, Mark, O1 aKraja, Aldi, T1 aLiu, Chunyu1 aWessel, Jennifer1 aBoerwinkle, Eric1 aBorecki, Ingrid, B1 aBork-Jensen, Jette1 aBottinger, Erwin, P1 aBraga, Daniele1 aBrandslund, Ivan1 aBrody, Jennifer, A1 aCampbell, Archie1 aCarey, David, J1 aChristensen, Cramer1 aCoresh, Josef1 aCrook, Errol1 aCurhan, Gary, C1 aCusi, Daniele1 ade Boer, Ian, H1 ade Vries, Aiko, P J1 aDenny, Joshua, C1 aDevuyst, Olivier1 aDreisbach, Albert, W1 aEndlich, Karlhans1 aEsko, Tõnu1 aFranco, Oscar, H1 aFulop, Tibor1 aGerhard, Glenn, S1 aGlümer, Charlotte1 aGottesman, Omri1 aGrarup, Niels1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aHayward, Caroline1 aHocking, Lynne1 aHofman, Albert1 aHu, Frank, B1 aHusemoen, Lise, Lotte N1 aJackson, Rebecca, D1 aJørgensen, Torben1 aJørgensen, Marit, E1 aKähönen, Mika1 aKardia, Sharon, L R1 aKönig, Wolfgang1 aKooperberg, Charles1 aKriebel, Jennifer1 aLauner, Lenore, J1 aLauritzen, Torsten1 aLehtimäki, Terho1 aLevy, Daniel1 aLinksted, Pamela1 aLinneberg, Allan1 aLiu, Yongmei1 aLoos, Ruth, J F1 aLupo, Antonio1 aMeisinger, Christine1 aMelander, Olle1 aMetspalu, Andres1 aMitchell, Paul1 aNauck, Matthias1 aNürnberg, Peter1 aOrho-Melander, Marju1 aParsa, Afshin1 aPedersen, Oluf1 aPeters, Annette1 aPeters, Ulrike1 aPolasek, Ozren1 aPorteous, David1 aProbst-Hensch, Nicole, M1 aPsaty, Bruce, M1 aQi, Lu1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRettig, Rainer1 aRidker, Paul, M1 aRivadeneira, Fernando1 aRossouw, Jacques, E1 aSchmidt, Frank1 aSiscovick, David1 aSoranzo, Nicole1 aStrauch, Konstantin1 aToniolo, Daniela1 aTurner, Stephen, T1 aUitterlinden, André, G1 aUlivi, Sheila1 aVelayutham, Dinesh1 aVölker, Uwe1 aVölzke, Henry1 aWaldenberger, Melanie1 aWang, Jie, Jin1 aWeir, David, R1 aWitte, Daniel1 aKuivaniemi, Helena1 aFox, Caroline, S1 aFranceschini, Nora1 aGoessling, Wolfram1 aKöttgen, Anna1 aChu, Audrey, Y1 aCHARGE Glycemic-T2D Working Group,1 aCHARGE Blood Pressure Working Group, uhttps://chs-nhlbi.org/node/725506088nas a2201561 4500008004100000022001400041245007200055210006900127260001600196520173100212100002801943700002101971700002401992700001802016700002002034700002202054700002502076700001602101700001802117700001802135700001802153700002002171700002002191700001502211700002302226700003002249700001902279700001302298700002102311700002802332700002002360700002402380700002002404700001902424700001802443700002102461700002102482700002102503700001702524700002202541700001902563700001902582700002002601700002502621700002302646700002202669700002402691700002102715700002402736700002202760700002202782700001702804700002302821700001902844700002202863700002302885700001902908700002002927700002002947700002402967700001802991700002203009700001203031700001303043700002103056700001503077700002503092700002103117700002203138700002103160700002203181700002703203700001703230700002503247700002003272700002303292700001803315700002003333700001503353700002303368700002603391700002203417700001603439700001903455700001703474700002203491700002403513700002403537700002203561700002603583700002003609700002103629700002403650700002103674700001803695700002403713700001703737700002603754700001603780700002803796700001903824700001903843700002103862700002003883700002303903700002403926700001903950700002703969700002203996700002204018700002404040700001804064700002204082700001904104700002204123700002304145700002304168700001804191700002904209700002004238700001904258700002204277700001804299700002404317700002204341700001904363700002404382700001504406700002204421700002304443700002404466856003604490 2017 eng d a1460-208300aDiscovery of novel heart rate-associated loci using the Exome Chip.0 aDiscovery of novel heart rateassociated loci using the Exome Chi c2017 Apr 033 aBackground Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. GWAS analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation.Aim To discover new genetic loci associated with heart rate from Exome Chip meta-analyses.Methods Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104,452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134,251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods.Results We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2, SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long range regulatory chromatin interactions in heart tissue (SCD, SLF2, MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants.Conclusion Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies.
1 avan den Berg, Marten, E1 aWarren, Helen, R1 aCabrera, Claudia, P1 aVerweij, Niek1 aMifsud, Borbala1 aHaessler, Jeffrey1 aBihlmeyer, Nathan, A1 aFu, Yi-Ping1 aWeiss, Stefan1 aLin, Henry, J1 aGrarup, Niels1 aLi-Gao, Ruifang1 aPistis, Giorgio1 aShah, Nabi1 aBrody, Jennifer, A1 aMüller-Nurasyid, Martina1 aLin, Honghuang1 aMei, Hao1 aSmith, Albert, V1 aLyytikäinen, Leo-Pekka1 aHall, Leanne, M1 avan Setten, Jessica1 aTrompet, Stella1 aPrins, Bram, P1 aIsaacs, Aaron1 aRadmanesh, Farid1 aMarten, Jonathan1 aEntwistle, Aiman1 aKors, Jan, A1 aSilva, Claudia, T1 aAlonso, Alvaro1 aBis, Joshua, C1 ade Boer, Rudolf1 ade Haan, Hugoline, G1 ade Mutsert, Renée1 aDedoussis, George1 aDominiczak, Anna, F1 aDoney, Alex, S F1 aEllinor, Patrick, T1 aEppinga, Ruben, N1 aFelix, Stephan, B1 aGuo, Xiuqing1 aHagemeijer, Yanick1 aHansen, Torben1 aHarris, Tamara, B1 aHeckbert, Susan, R1 aHuang, Paul, L1 aHwang, Shih-Jen1 aKähönen, Mika1 aKanters, Jørgen, K1 aKolcic, Ivana1 aLauner, Lenore, J1 aLi, Man1 aYao, Jie1 aLinneberg, Allan1 aLiu, Simin1 aMacfarlane, Peter, W1 aMangino, Massimo1 aMorris, Andrew, D1 aMulas, Antonella1 aMurray, Alison, D1 aNelson, Christopher, P1 aOrrù, Marco1 aPadmanabhan, Sandosh1 aPeters, Annette1 aPorteous, David, J1 aPoulter, Neil1 aPsaty, Bruce, M1 aQi, Lihong1 aRaitakari, Olli, T1 aRivadeneira, Fernando1 aRoselli, Carolina1 aRudan, Igor1 aSattar, Naveed1 aSever, Peter1 aSinner, Moritz, F1 aSoliman, Elsayed, Z1 aSpector, Timothy, D1 aStanton, Alice, V1 aStirrups, Kathleen, E1 aTaylor, Kent, D1 aTobin, Martin, D1 aUitterlinden, Andre1 aVaartjes, Ilonca1 aHoes, Arno, W1 avan der Meer, Peter1 aVölker, Uwe1 aWaldenberger, Melanie1 aXie, Zhijun1 aZoledziewska, Magdalena1 aTinker, Andrew1 aPolasek, Ozren1 aRosand, Jonathan1 aJamshidi, Yalda1 aDuijn, Cornelia, M1 aZeggini, Eleftheria1 aJukema, Wouter1 aAsselbergs, Folkert, W1 aSamani, Nilesh, J1 aLehtimäki, Terho1 aGudnason, Vilmundur1 aWilson, James1 aLubitz, Steven, A1 aKääb, Stefan1 aSotoodehnia, Nona1 aCaulfield, Mark, J1 aPalmer, Colin, N A1 aSanna, Serena1 aMook-Kanamori, Dennis, O1 aDeloukas, Panos1 aPedersen, Oluf1 aRotter, Jerome, I1 aDörr, Marcus1 aO'Donnell, Chris, J1 aHayward, Caroline1 aArking, Dan, E1 aKooperberg, Charles1 aHarst, Pim1 aEijgelsheim, Mark1 aStricker, Bruno, H1 aMunroe, Patricia, B uhttps://chs-nhlbi.org/node/736309668nas a2203061 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2017 eng d a1546-171800aExome-wide association study of plasma lipids in >300,000 individuals.0 aExomewide association study of plasma lipids in 300000 individua c2017 Dec a1758-17660 v493 aWe screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.
10aCoronary Artery Disease10aDiabetes Mellitus, Type 210aExome10aGenetic Association Studies10aGenetic Predisposition to Disease10aGenetic Variation10aGenotype10aHumans10aLipids10aMacular Degeneration10aPhenotype10aRisk Factors1 aLiu, Dajiang, J1 aPeloso, Gina, M1 aYu, Haojie1 aButterworth, Adam, S1 aWang, Xiao1 aMahajan, Anubha1 aSaleheen, Danish1 aEmdin, Connor1 aAlam, Dewan1 aAlves, Alexessander, Couto1 aAmouyel, Philippe1 aDi Angelantonio, Emanuele1 aArveiler, Dominique1 aAssimes, Themistocles, L1 aAuer, Paul, L1 aBaber, Usman1 aBallantyne, Christie, M1 aBang, Lia, E1 aBenn, Marianne1 aBis, Joshua, C1 aBoehnke, Michael1 aBoerwinkle, Eric1 aBork-Jensen, Jette1 aBottinger, Erwin, P1 aBrandslund, Ivan1 aBrown, Morris1 aBusonero, Fabio1 aCaulfield, Mark, J1 aChambers, John, C1 aChasman, Daniel, I1 aChen, Eugene1 aChen, Yii-Der Ida1 aChowdhury, Raj1 aChristensen, Cramer1 aChu, Audrey, Y1 aConnell, John, M1 aCucca, Francesco1 aCupples, Adrienne, L1 aDamrauer, Scott, M1 aDavies, Gail1 aDeary, Ian, J1 aDedoussis, George1 aDenny, Joshua, C1 aDominiczak, Anna1 aDubé, Marie-Pierre1 aEbeling, Tapani1 aEiriksdottir, Gudny1 aEsko, Tõnu1 aFarmaki, Aliki-Eleni1 aFeitosa, Mary, F1 aFerrario, Marco1 aFerrieres, Jean1 aFord, Ian1 aFornage, Myriam1 aFranks, Paul, W1 aFrayling, Timothy, M1 aFrikke-Schmidt, Ruth1 aFritsche, Lars, G1 aFrossard, Philippe1 aFuster, Valentin1 aGanesh, Santhi, K1 aGao, Wei1 aGarcia, Melissa, E1 aGieger, Christian1 aGiulianini, Franco1 aGoodarzi, Mark, O1 aGrallert, Harald1 aGrarup, Niels1 aGroop, Leif1 aGrove, Megan, L1 aGudnason, Vilmundur1 aHansen, Torben1 aHarris, Tamara, B1 aHayward, Caroline1 aHirschhorn, Joel, N1 aHolmen, Oddgeir, L1 aHuffman, Jennifer1 aHuo, Yong1 aHveem, Kristian1 aJabeen, Sehrish1 aJackson, Anne, U1 aJakobsdottir, Johanna1 aJarvelin, Marjo-Riitta1 aJensen, Gorm, B1 aJørgensen, Marit, E1 aJukema, Wouter1 aJustesen, Johanne, M1 aKamstrup, Pia, R1 aKanoni, Stavroula1 aKarpe, Fredrik1 aKee, Frank1 aKhera, Amit, V1 aKlarin, Derek1 aKoistinen, Heikki, A1 aKooner, Jaspal, S1 aKooperberg, Charles1 aKuulasmaa, Kari1 aKuusisto, Johanna1 aLaakso, Markku1 aLakka, Timo1 aLangenberg, Claudia1 aLangsted, Anne1 aLauner, Lenore, J1 aLauritzen, Torsten1 aLiewald, David, C M1 aLin, Li, An1 aLinneberg, Allan1 aLoos, Ruth, J F1 aLu, Yingchang1 aLu, Xiangfeng1 aMägi, Reedik1 aMälarstig, Anders1 aManichaikul, Ani1 aManning, Alisa, K1 aMäntyselkä, Pekka1 aMarouli, Eirini1 aMasca, Nicholas, G D1 aMaschio, Andrea1 aMeigs, James, B1 aMelander, Olle1 aMetspalu, Andres1 aMorris, Andrew, P1 aMorrison, Alanna, C1 aMulas, Antonella1 aMüller-Nurasyid, Martina1 aMunroe, Patricia, B1 aNeville, Matt, J1 aNielsen, Jonas, B1 aNielsen, Sune, F1 aNordestgaard, Børge, G1 aOrdovas, Jose, M1 aMehran, Roxana1 aO'Donnell, Christoper, J1 aOrho-Melander, Marju1 aMolony, Cliona, M1 aMuntendam, Pieter1 aPadmanabhan, Sandosh1 aPalmer, Colin, N A1 aPasko, Dorota1 aPatel, Aniruddh, P1 aPedersen, Oluf1 aPerola, Markus1 aPeters, Annette1 aPisinger, Charlotta1 aPistis, Giorgio1 aPolasek, Ozren1 aPoulter, Neil1 aPsaty, Bruce, M1 aRader, Daniel, J1 aRasheed, Asif1 aRauramaa, Rainer1 aReilly, Dermot, F1 aReiner, Alex, P1 aRenstrom, Frida1 aRich, Stephen, S1 aRidker, Paul, M1 aRioux, John, D1 aRobertson, Neil, R1 aRoden, Dan, M1 aRotter, Jerome, I1 aRudan, Igor1 aSalomaa, Veikko1 aSamani, Nilesh, J1 aSanna, Serena1 aSattar, Naveed1 aSchmidt, Ellen, M1 aScott, Robert, A1 aSever, Peter1 aSevilla, Raquel, S1 aShaffer, Christian, M1 aSim, Xueling1 aSivapalaratnam, Suthesh1 aSmall, Kerrin, S1 aSmith, Albert, V1 aSmith, Blair, H1 aSomayajula, Sangeetha1 aSoutham, Lorraine1 aSpector, Timothy, D1 aSpeliotes, Elizabeth, K1 aStarr, John, M1 aStirrups, Kathleen, E1 aStitziel, Nathan1 aStrauch, Konstantin1 aStringham, Heather, M1 aSurendran, Praveen1 aTada, Hayato1 aTall, Alan, R1 aTang, Hua1 aTardif, Jean-Claude1 aTaylor, Kent, D1 aTrompet, Stella1 aTsao, Philip, S1 aTuomilehto, Jaakko1 aTybjaerg-Hansen, Anne1 avan Zuydam, Natalie, R1 aVarbo, Anette1 aVarga, Tibor, V1 aVirtamo, Jarmo1 aWaldenberger, Melanie1 aWang, Nan1 aWareham, Nick, J1 aWarren, Helen, R1 aWeeke, Peter, E1 aWeinstock, Joshua1 aWessel, Jennifer1 aWilson, James, G1 aWilson, Peter, W F1 aXu, Ming1 aYaghootkar, Hanieh1 aYoung, Robin1 aZeggini, Eleftheria1 aZhang, He1 aZheng, Neil, S1 aZhang, Weihua1 aZhang, Yan1 aZhou, Wei1 aZhou, Yanhua1 aZoledziewska, Magdalena1 aHowson, Joanna, M M1 aDanesh, John1 aMcCarthy, Mark, I1 aCowan, Chad, A1 aAbecasis, Goncalo1 aDeloukas, Panos1 aMusunuru, Kiran1 aWiller, Cristen, J1 aKathiresan, Sekar1 aCharge Diabetes Working Group1 aEPIC-InterAct Consortium1 aEPIC-CVD Consortium1 aGOLD Consortium1 aVA Million Veteran Program uhttps://chs-nhlbi.org/node/757303442nas a2200469 4500008004100000022001400041245018400055210006900239260001300308300001200321490000700333520199400340100002202334700002502356700002402381700002502405700002002430700001702450700002402467700002002491700002602511700001302537700002302550700002002573700002702593700001902620700002202639700001902661700002102680700002302701700002002724700002102744700002202765700001702787700002102804700001902825700002702844700002202871700002402893700001902917856003602936 2017 eng d a1556-387100aFine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations.0 aFine mapping of QT interval regions in global populations refine c2017 Apr a572-5800 v143 aBACKGROUND: The electrocardiographically measured QT interval (QT) is heritable and its prolongation is an established risk factor for several cardiovascular diseases. Yet, most QT genetic studies have been performed in European ancestral populations, possibly reducing their global relevance.
OBJECTIVE: To leverage diversity and improve biological insight, we fine mapped 16 of the 35 previously identified QT loci (46%) in populations of African American (n = 12,410) and Hispanic/Latino (n = 14,837) ancestry.
METHODS: Racial/ethnic-specific multiple linear regression analyses adjusted for heart rate and clinical covariates were examined separately and in combination after inverse-variance weighted trans-ethnic meta-analysis.
RESULTS: The 16 fine-mapped QT loci included on the Illumina Metabochip represented 21 independent signals, of which 16 (76%) were significantly (P-value≤9.1×10(-5)) associated with QT. Through sequential conditional analysis we also identified three trans-ethnic novel SNPs at ATP1B1, SCN5A-SCN10A, and KCNQ1 and three Hispanic/Latino-specific novel SNPs at NOS1AP and SCN5A-SCN10A (two novel SNPs) with evidence of associations with QT independent of previous identified GWAS lead SNPs. Linkage disequilibrium patterns helped to narrow the region likely to contain the functional variants at several loci, including NOS1AP, USP50-TRPM7, and PRKCA, although intervals surrounding SLC35F1-PLN and CNOT1 remained broad in size (>100 kb). Finally, bioinformatics-based functional characterization suggested a regulatory function in cardiac tissues for the majority of independent signals that generalized and the novel SNPs.
CONCLUSION: Our findings suggest that a majority of identified SNPs implicate gene regulatory dysfunction in QT prolongation, that the same loci influence variation in QT across global populations, and that additional, novel, population-specific QT signals exist.
1 aAvery, Christy, L1 aWassel, Christina, L1 aRichard, Melissa, A1 aHighland, Heather, M1 aBien, Stephanie1 aZubair, Niha1 aSoliman, Elsayed, Z1 aFornage, Myriam1 aBielinski, Suzette, J1 aTao, Ran1 aSeyerle, Amanda, A1 aShah, Sanjiv, J1 aLloyd-Jones, Donald, M1 aBuyske, Steven1 aRotter, Jerome, I1 aPost, Wendy, S1 aRich, Stephen, S1 aHindorff, Lucia, A1 aJeff, Janina, M1 aShohet, Ralph, V1 aSotoodehnia, Nona1 aLin, Dan, Yu1 aWhitsel, Eric, A1 aPeters, Ulrike1 aHaiman, Christopher, A1 aCrawford, Dana, C1 aKooperberg, Charles1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/746306994nas a2202101 4500008004100000022001400041245009900055210006900154260001600223300001000239490000600249520104500255100001901300700001901319700002301338700002201361700001701383700001601400700002801416700002201444700001901466700001801485700002201503700002701525700002201552700002301574700001901597700002001616700001801636700002201654700002301676700002201699700002001721700002801741700002801769700002201797700002001819700002701839700003001866700001901896700001701915700002201932700002201954700001801976700001701994700002102011700002702032700002202059700002302081700002202104700001902126700001702145700001802162700002002180700002202200700002502222700002102247700001802268700002102286700002002307700002302327700002202350700002702372700002102399700002102420700002402441700001902465700002102484700002002505700002102525700001902546700002502565700001902590700002602609700002602635700002102661700001902682700002402701700002002725700002602745700001902771700002102790700002002811700002402831700001702855700001802872700002402890700002102914700002202935700001302957700001202970700001902982700002403001700001803025700002503043700002203068700002003090700002203110700003903132700002103171700001803192700002203210700001903232700001803251700002003269700001703289700001903306700002403325700001703349700002003366700002003386700002003406700002303426700002703449700002203476700002103498700002203519700002303541700002403564700002203588700002103610700002203631700002303653700003203676700002403708700002203732700002003754700002803774700002403802700002003826700002203846700002503868700002203893700002803915700002403943700001803967700002603985700002404011700002304035700001704058700002004075700002304095700001804118700002204136700002304158700001504181700002104196700002004217700002704237700001904264700002004283700001904303700002404322700001504346700002204361700001504383700002804398700002404426700002904450700002004479700002504499700002204524700002204546700001904568700002204587700001704609700002304626700002204649700002604671700002704697700002704724700002304751700002104774700002204795700002004817700001904837856003604856 2017 eng d a2041-172300aGenetic loci associated with heart rate variability and their effects on cardiac disease risk.0 aGenetic loci associated with heart rate variability and their ef c2017 Jun 14 a158050 v83 aReduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.741 aNolte, Ilja, M1 aMunoz, Loretto1 aTragante, Vinicius1 aAmare, Azmeraw, T1 aJansen, Rick1 aVaez, Ahmad1 avon der Heyde, Benedikt1 aAvery, Christy, L1 aBis, Joshua, C1 aDierckx, Bram1 avan Dongen, Jenny1 aGogarten, Stephanie, M1 aGoyette, Philippe1 aHernesniemi, Jussi1 aHuikari, Ville1 aHwang, Shih-Jen1 aJaju, Deepali1 aKerr, Kathleen, F1 aKluttig, Alexander1 aKrijthe, Bouwe, P1 aKumar, Jitender1 avan der Laan, Sander, W1 aLyytikäinen, Leo-Pekka1 aMaihofer, Adam, X1 aMinassian, Arpi1 avan der Most, Peter, J1 aMüller-Nurasyid, Martina1 aNivard, Michel1 aSalvi, Erika1 aStewart, James, D1 aThayer, Julian, F1 aVerweij, Niek1 aWong, Andrew1 aZabaneh, Delilah1 aZafarmand, Mohammad, H1 aAbdellaoui, Abdel1 aAlbarwani, Sulayma1 aAlbert, Christine1 aAlonso, Alvaro1 aAshar, Foram1 aAuvinen, Juha1 aAxelsson, Tomas1 aBaker, Dewleen, G1 ade Bakker, Paul, I W1 aBarcella, Matteo1 aBayoumi, Riad1 aBieringa, Rob, J1 aBoomsma, Dorret1 aBoucher, Gabrielle1 aBritton, Annie, R1 aChristophersen, Ingrid1 aDietrich, Andrea1 aEhret, George, B1 aEllinor, Patrick, T1 aEskola, Markku1 aFelix, Janine, F1 aFloras, John, S1 aFranco, Oscar, H1 aFriberg, Peter1 aGademan, Maaike, G J1 aGeyer, Mark, A1 aGiedraitis, Vilmantas1 aHartman, Catharina, A1 aHemerich, Daiane1 aHofman, Albert1 aHottenga, Jouke-Jan1 aHuikuri, Heikki1 aHutri-Kähönen, Nina1 aJouven, Xavier1 aJunttila, Juhani1 aJuonala, Markus1 aKiviniemi, Antti, M1 aKors, Jan, A1 aKumari, Meena1 aKuznetsova, Tatiana1 aLaurie, Cathy, C1 aLefrandt, Joop, D1 aLi, Yong1 aLi, Yun1 aLiao, Duanping1 aLimacher, Marian, C1 aLin, Henry, J1 aLindgren, Cecilia, M1 aLubitz, Steven, A1 aMahajan, Anubha1 aMcKnight, Barbara1 aSchwabedissen, Henriette, Meyer Zu1 aMilaneschi, Yuri1 aMononen, Nina1 aMorris, Andrew, P1 aNalls, Mike, A1 aNavis, Gerjan1 aNeijts, Melanie1 aNikus, Kjell1 aNorth, Kari, E1 aO'Connor, Daniel, T1 aOrmel, Johan1 aPerz, Siegfried1 aPeters, Annette1 aPsaty, Bruce, M1 aRaitakari, Olli, T1 aRisbrough, Victoria, B1 aSinner, Moritz, F1 aSiscovick, David1 aSmit, Johannes, H1 aSmith, Nicholas, L1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aStaessen, Jan, A1 aStein, Phyllis, K1 aStilp, Adrienne, M1 aStolarz-Skrzypek, Katarzyna1 aStrauch, Konstantin1 aSundström, Johan1 aSwenne, Cees, A1 aSyvänen, Ann-Christine1 aTardif, Jean-Claude1 aTaylor, Kent, D1 aTeumer, Alexander1 aThornton, Timothy, A1 aTinker, Lesley, E1 aUitterlinden, André, G1 avan Setten, Jessica1 aVoss, Andreas1 aWaldenberger, Melanie1 aWilhelmsen, Kirk, C1 aWillemsen, Gonneke1 aWong, Quenna1 aZhang, Zhu-Ming1 aZonderman, Alan, B1 aCusi, Daniele1 aEvans, Michele, K1 aGreiser, Halina, K1 aHarst, Pim1 aHassan, Mohammad1 aIngelsson, Erik1 aJarvelin, Marjo-Riitta1 aKääb, Stefan1 aKähönen, Mika1 aKivimaki, Mika1 aKooperberg, Charles1 aKuh, Diana1 aLehtimäki, Terho1 aLind, Lars1 aNievergelt, Caroline, M1 aO'Donnell, Chris, J1 aOldehinkel, Albertine, J1 aPenninx, Brenda1 aReiner, Alexander, P1 aRiese, Harriëtte1 avan Roon, Arie, M1 aRioux, John, D1 aRotter, Jerome, I1 aSofer, Tamar1 aStricker, Bruno, H1 aTiemeier, Henning1 aVrijkotte, Tanja, G M1 aAsselbergs, Folkert, W1 aBrundel, Bianca, J J M1 aHeckbert, Susan, R1 aWhitsel, Eric, A1 aHoed, Marcel, den1 aSnieder, Harold1 aGeus, Eco, J C uhttps://chs-nhlbi.org/node/757904812nas a2201345 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2017 eng d a1537-660500aGenome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis.0 aGenomewide Transethnic Metaanalysis Identifies Seven Genetic Loc c2017 Jan 05 a51-630 v1003 aGenome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.
1 avan Rooij, Frank, J A1 aQayyum, Rehan1 aSmith, Albert, V1 aZhou, Yi1 aTrompet, Stella1 aTanaka, Toshiko1 aKeller, Margaux, F1 aChang, Li-Ching1 aSchmidt, Helena1 aYang, Min-Lee1 aChen, Ming-Huei1 aHayes, James1 aJohnson, Andrew, D1 aYanek, Lisa, R1 aMueller, Christian1 aLange, Leslie1 aFloyd, James, S1 aGhanbari, Mohsen1 aZonderman, Alan, B1 aJukema, Wouter1 aHofman, Albert1 aDuijn, Cornelia, M1 aDesch, Karl, C1 aSaba, Yasaman1 aOzel, Ayse, B1 aSnively, Beverly, M1 aWu, Jer-Yuarn1 aSchmidt, Reinhold1 aFornage, Myriam1 aKlein, Robert, J1 aFox, Caroline, S1 aMatsuda, Koichi1 aKamatani, Naoyuki1 aWild, Philipp, S1 aStott, David, J1 aFord, Ian1 aSlagboom, Eline1 aYang, Jaden1 aChu, Audrey, Y1 aLambert, Amy, J1 aUitterlinden, André, G1 aFranco, Oscar, H1 aHofer, Edith1 aGinsburg, David1 aHu, Bella1 aKeating, Brendan1 aSchick, Ursula, M1 aBrody, Jennifer, A1 aLi, Jun, Z1 aChen, Zhao1 aZeller, Tanja1 aGuralnik, Jack, M1 aChasman, Daniel, I1 aPeters, Luanne, L1 aKubo, Michiaki1 aBecker, Diane, M1 aLi, Jin1 aEiriksdottir, Gudny1 aRotter, Jerome, I1 aLevy, Daniel1 aGrossmann, Vera1 aPatel, Kushang, V1 aChen, Chien-Hsiun1 aRidker, Paul, M1 aTang, Hua1 aLauner, Lenore, J1 aRice, Kenneth, M1 aLi-Gao, Ruifang1 aFerrucci, Luigi1 aEvans, Michelle, K1 aChoudhuri, Avik1 aTrompouki, Eirini1 aAbraham, Brian, J1 aYang, Song1 aTakahashi, Atsushi1 aKamatani, Yoichiro1 aKooperberg, Charles1 aHarris, Tamara, B1 aJee, Sun, Ha1 aCoresh, Josef1 aTsai, Fuu-Jen1 aLongo, Dan, L1 aChen, Yuan-Tsong1 aFelix, Janine, F1 aYang, Qiong1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aBecker, Lewis, C1 aMook-Kanamori, Dennis, O1 aWilson, James, G1 aGudnason, Vilmundur1 aO'Donnell, Christopher, J1 aDehghan, Abbas1 aCupples, Adrienne, L1 aNalls, Michael, A1 aMorris, Andrew, P1 aOkada, Yukinori1 aReiner, Alexander, P1 aZon, Leonard, I1 aGanesh, Santhi, K1 aBioBank Japan Project uhttps://chs-nhlbi.org/node/736406999nas a2202113 4500008004100000022001400041245011100055210006900166260001300235300001200248490000700260520104100267100003001308700002201338700002201360700001701382700002301399700001801422700001901440700001901459700002101478700002501499700001801524700002201542700001501564700001801579700002501597700001801622700002001640700003001660700001801690700002301708700002601731700001801757700002001775700002201795700002301817700002301840700002201863700002801885700002101913700001801934700002801952700001701980700001901997700002602016700002702042700001302069700002102082700001802103700002202121700002202143700001802165700002202183700001502205700002102220700001902241700001602260700002302276700002302299700002002322700001602342700002502358700002102383700002302404700002602427700001802453700002302471700001902494700002302513700002602536700001902562700002002581700002002601700002002621700002202641700002202663700002202685700002402707700002502731700002202756700002002778700002602798700002002824700001902844700002102863700002002884700001802904700002302922700002002945700002002965700001502985700002103000700001803021700002403039700002303063700002503086700001903111700001503130700001903145700002203164700001403186700002003200700002203220700001703242700002203259700002503281700001203306700002103318700001803339700001903357700001803376700002903394700002003423700002103443700002503464700002003489700002203509700002703531700002303558700001703581700002503598700002003623700001803643700002103661700002203682700001903704700002903723700002303752700002503775700003203800700001903832700001903851700002203870700002403892700002803916700001903944700002103963700001703984700002404001700002204025700001804047700001704065700002104082700002004103700002404123700001904147700002004166700001904186700001704205700002104222700001504243700002304258700002204281700002304303700001904326700002204345700002204367700002004389700002204409700002304431700001904454700002204473700002404495700001904519700001804538700001904556700002304575700002304598700002404621700002204645700002404667700002204691700002404713710003804737710005304775710002104828856003604849 2017 eng d a1546-171800aLarge-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation.0 aLargescale analyses of common and rare variants identify 12 new c2017 Jun a946-9520 v493 aAtrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery.
1 aChristophersen, Ingrid, E1 aRienstra, Michiel1 aRoselli, Carolina1 aYin, Xiaoyan1 aGeelhoed, Bastiaan1 aBarnard, John1 aLin, Honghuang1 aArking, Dan, E1 aSmith, Albert, V1 aAlbert, Christine, M1 aChaffin, Mark1 aTucker, Nathan, R1 aLi, Molong1 aKlarin, Derek1 aBihlmeyer, Nathan, A1 aLow, Siew-Kee1 aWeeke, Peter, E1 aMüller-Nurasyid, Martina1 aSmith, Gustav1 aBrody, Jennifer, A1 aNiemeijer, Maartje, N1 aDörr, Marcus1 aTrompet, Stella1 aHuffman, Jennifer1 aGustafsson, Stefan1 aSchurmann, Claudia1 aKleber, Marcus, E1 aLyytikäinen, Leo-Pekka1 aSeppälä, Ilkka1 aMalik, Rainer1 aHorimoto, Andrea, R V R1 aPerez, Marco1 aSinisalo, Juha1 aAeschbacher, Stefanie1 aThériault, Sébastien1 aYao, Jie1 aRadmanesh, Farid1 aWeiss, Stefan1 aTeumer, Alexander1 aChoi, Seung, Hoan1 aWeng, Lu-Chen1 aClauss, Sebastian1 aDeo, Rajat1 aRader, Daniel, J1 aShah, Svati, H1 aSun, Albert1 aHopewell, Jemma, C1 aDebette, Stephanie1 aChauhan, Ganesh1 aYang, Qiong1 aWorrall, Bradford, B1 aParé, Guillaume1 aKamatani, Yoichiro1 aHagemeijer, Yanick, P1 aVerweij, Niek1 aSiland, Joylene, E1 aKubo, Michiaki1 aSmith, Jonathan, D1 aVan Wagoner, David, R1 aBis, Joshua, C1 aPerz, Siegfried1 aPsaty, Bruce, M1 aRidker, Paul, M1 aMagnani, Jared, W1 aHarris, Tamara, B1 aLauner, Lenore, J1 aShoemaker, Benjamin1 aPadmanabhan, Sandosh1 aHaessler, Jeffrey1 aBartz, Traci, M1 aWaldenberger, Melanie1 aLichtner, Peter1 aArendt, Marina1 aKrieger, Jose, E1 aKähönen, Mika1 aRisch, Lorenz1 aMansur, Alfredo, J1 aPeters, Annette1 aSmith, Blair, H1 aLind, Lars1 aScott, Stuart, A1 aLu, Yingchang1 aBottinger, Erwin, B1 aHernesniemi, Jussi1 aLindgren, Cecilia, M1 aWong, Jorge, A1 aHuang, Jie1 aEskola, Markku1 aMorris, Andrew, P1 aFord, Ian1 aReiner, Alex, P1 aDelgado, Graciela1 aChen, Lin, Y1 aChen, Yii-Der Ida1 aSandhu, Roopinder, K1 aLi, Man1 aBoerwinkle, Eric1 aEisele, Lewin1 aLannfelt, Lars1 aRost, Natalia1 aAnderson, Christopher, D1 aTaylor, Kent, D1 aCampbell, Archie1 aMagnusson, Patrik, K1 aPorteous, David1 aHocking, Lynne, J1 aVlachopoulou, Efthymia1 aPedersen, Nancy, L1 aNikus, Kjell1 aOrho-Melander, Marju1 aHamsten, Anders1 aHeeringa, Jan1 aDenny, Joshua, C1 aKriebel, Jennifer1 aDarbar, Dawood1 aNewton-Cheh, Christopher1 aShaffer, Christian1 aMacfarlane, Peter, W1 aHeilmann-Heimbach, Stefanie1 aAlmgren, Peter1 aHuang, Paul, L1 aSotoodehnia, Nona1 aSoliman, Elsayed, Z1 aUitterlinden, André, G1 aHofman, Albert1 aFranco, Oscar, H1 aVölker, Uwe1 aJöckel, Karl-Heinz1 aSinner, Moritz, F1 aLin, Henry, J1 aGuo, Xiuqing1 aDichgans, Martin1 aIngelsson, Erik1 aKooperberg, Charles1 aMelander, Olle1 aLoos, Ruth, J F1 aLaurikka, Jari1 aConen, David1 aRosand, Jonathan1 aHarst, Pim1 aLokki, Marja-Liisa1 aKathiresan, Sekar1 aPereira, Alexandre1 aJukema, Wouter1 aHayward, Caroline1 aRotter, Jerome, I1 aMärz, Winfried1 aLehtimäki, Terho1 aStricker, Bruno, H1 aChung, Mina, K1 aFelix, Stephan, B1 aGudnason, Vilmundur1 aAlonso, Alvaro1 aRoden, Dan, M1 aKääb, Stefan1 aChasman, Daniel, I1 aHeckbert, Susan, R1 aBenjamin, Emelia, J1 aTanaka, Toshihiro1 aLunetta, Kathryn, L1 aLubitz, Steven, A1 aEllinor, Patrick, T1 aMETASTROKE Consortium of the ISGC1 aNeurology Working Group of the CHARGE Consortium1 aAFGen Consortium uhttps://chs-nhlbi.org/node/739602588nas a2200289 4500008004100000022001400041245008400055210006900139260001300208300001200221490000700233520174600240100002401986700002402010700002402034700002502058700001902083700002002102700001602122700001702138700002402155700002002179700002402199700001602223700002302239856003602262 2017 eng d a1873-681500aLeisure-time physical activity and leukocyte telomere length among older women.0 aLeisuretime physical activity and leukocyte telomere length amon c2017 Sep a141-1470 v953 aBACKGROUND: Shortened leukocyte telomere length (LTL), a purported marker of cellular aging, is associated with morbidity and mortality. However, the association of physical activity, a modifiable lifestyle behavior, with LTL has not been adequately studied among older adults.
METHODS: In this cross-sectional study, we examined associations of various intensity levels of leisure-time physical activity with LTL among 1476 older white and African American women from the Women's Health Initiative Objective Physical Activity and Cardiovascular Health study. Self-reported physical activity was assessed by questionnaire, and LTL was measured by Southern blot. The association between physical activity and LTL was evaluated using multiple linear regression models adjusted for demographic characteristics, lifestyle behaviors, and health-related variables.
RESULTS: Women were on average aged 79.2 (standard deviation 6.7) years old. In the final model adjusted for age, race/ethnicity, education, marital status, smoking, alcohol, body mass index, a history of chronic diseases, and hormone therapy use, LTL was on average 110 (95% confidence interval, 20-190) base pairs longer among women in the highest (≥17.00MET-hours/week) compared with the lowest (<1.25MET-hours/week) level of total leisure-time physical activity (P for trend=0.02). Higher levels of moderate-to-vigorous physical activity (P for trend=0.04) and faster walking speed (P for trend=0.03) were also associated with longer LTL in the fully-adjusted models.
CONCLUSION: Older women participating in greater amounts of total leisure-time physical activity and moderate-to-vigorous physical activity had longer LTL.
1 aShadyab, Aladdin, H1 aLamonte, Michael, J1 aKooperberg, Charles1 aReiner, Alexander, P1 aCarty, Cara, L1 aManini, Todd, M1 aHou, Lifang1 aDi, Chongzhi1 aMacera, Caroline, A1 aGallo, Linda, C1 aShaffer, Richard, A1 aJain, Sonia1 aLaCroix, Andrea, Z uhttps://chs-nhlbi.org/node/758607019nas a2201849 4500008004100000022001400041245009300055210006900148260001300217490000700230520169900237100001901936700001901955700002101974700002301995700001602018700002502034700002202059700001802081700001902099700001702118700002602135700001602161700003002177700002302207700002102230700002502251700002002276700002102296700002302317700001602340700002302356700002002379700001702399700002102416700002302437700002202460700001402482700002502496700002902521700002402550700002102574700001802595700001702613700002502630700001802655700001802673700002002691700002202711700002502733700001302758700002002771700002402791700002502815700001902840700001902859700002102878700002702899700001902926700001402945700002402959700002302983700002203006700002503028700002603053700002303079700002203102700002103124700002003145700001803165700002603183700001703209700001803226700002303244700002403267700001203291700002103303700002103324700002203345700002103367700002703388700002303415700001803438700002203456700002003478700002403498700001803522700001903540700002103559700001603580700002003596700002303616700002003639700002203659700001603681700002103697700001903718700002203737700001703759700002003776700002303796700002703819700002403846700001903870700002203889700001903911700002403930700001503954700002003969700001903989700002204008700001904030700002104049700002204070700002304092700001904115700001904134700002104153700002504174700002004199700002004219700002204239700001604261700002004277700002204297700002004319700001604339700002604355700001904381700001504400700002404415700002304439700002604462700002404488700002504512700002104537700002304558700002104581700002404602700002104626700002504647700001704672700002704689700002004716700002004736700002304756700002304779700001804802700002504820700001704845700002904862700002404891700002404915710004304939710015104982856003605133 2017 eng d a1942-326800aNew Blood Pressure-Associated Loci Identified in Meta-Analyses of 475 000 Individuals.0 aNew Blood PressureAssociated Loci Identified in MetaAnalyses of c2017 Oct0 v103 aBACKGROUND: Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association.
METHODS AND RESULTS: Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5×10-8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant.
CONCLUSIONS: We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.
1 aKraja, Aldi, T1 aCook, James, P1 aWarren, Helen, R1 aSurendran, Praveen1 aLiu, Chunyu1 aEvangelou, Evangelos1 aManning, Alisa, K1 aGrarup, Niels1 aDrenos, Fotios1 aSim, Xueling1 aSmith, Albert, Vernon1 aAmin, Najaf1 aBlakemore, Alexandra, I F1 aBork-Jensen, Jette1 aBrandslund, Ivan1 aFarmaki, Aliki-Eleni1 aFava, Cristiano1 aFerreira, Teresa1 aHerzig, Karl-Heinz1 aGiri, Ayush1 aGiulianini, Franco1 aGrove, Megan, L1 aGuo, Xiuqing1 aHarris, Sarah, E1 aHave, Christian, T1 aHavulinna, Aki, S1 aZhang, He1 aJørgensen, Marit, E1 aKäräjämäki, AnneMari1 aKooperberg, Charles1 aLinneberg, Allan1 aLittle, Louis1 aLiu, Yongmei1 aBonnycastle, Lori, L1 aLu, Yingchang1 aMägi, Reedik1 aMahajan, Anubha1 aMalerba, Giovanni1 aMarioni, Riccardo, E1 aMei, Hao1 aMenni, Cristina1 aMorrison, Alanna, C1 aPadmanabhan, Sandosh1 aPalmas, Walter1 aPoveda, Alaitz1 aRauramaa, Rainer1 aRayner, Nigel, William1 aRiaz, Muhammad1 aRice, Ken1 aRichard, Melissa, A1 aSmith, Jennifer, A1 aSoutham, Lorraine1 aStančáková, Alena1 aStirrups, Kathleen, E1 aTragante, Vinicius1 aTuomi, Tiinamaija1 aTzoulaki, Ioanna1 aVarga, Tibor, V1 aWeiss, Stefan1 aYiorkas, Andrianos, M1 aYoung, Robin1 aZhang, Weihua1 aBarnes, Michael, R1 aCabrera, Claudia, P1 aGao, He1 aBoehnke, Michael1 aBoerwinkle, Eric1 aChambers, John, C1 aConnell, John, M1 aChristensen, Cramer, K1 ade Boer, Rudolf, A1 aDeary, Ian, J1 aDedoussis, George1 aDeloukas, Panos1 aDominiczak, Anna, F1 aDörr, Marcus1 aJoehanes, Roby1 aEdwards, Todd, L1 aEsko, Tõnu1 aFornage, Myriam1 aFranceschini, Nora1 aFranks, Paul, W1 aGambaro, Giovanni1 aGroop, Leif1 aHallmans, Göran1 aHansen, Torben1 aHayward, Caroline1 aHeikki, Oksa1 aIngelsson, Erik1 aTuomilehto, Jaakko1 aJarvelin, Marjo-Riitta1 aKardia, Sharon, L R1 aKarpe, Fredrik1 aKooner, Jaspal, S1 aLakka, Timo, A1 aLangenberg, Claudia1 aLind, Lars1 aLoos, Ruth, J F1 aLaakso, Markku1 aMcCarthy, Mark, I1 aMelander, Olle1 aMohlke, Karen, L1 aMorris, Andrew, P1 aPalmer, Colin, N A1 aPedersen, Oluf1 aPolasek, Ozren1 aPoulter, Neil, R1 aProvince, Michael, A1 aPsaty, Bruce, M1 aRidker, Paul, M1 aRotter, Jerome, I1 aRudan, Igor1 aSalomaa, Veikko1 aSamani, Nilesh, J1 aSever, Peter, J1 aSkaaby, Tea1 aStafford, Jeanette, M1 aStarr, John, M1 aHarst, Pim1 avan der Meer, Peter1 aDuijn, Cornelia, M1 aVergnaud, Anne-Claire1 aGudnason, Vilmundur1 aWareham, Nicholas, J1 aWilson, James, G1 aWiller, Cristen, J1 aWitte, Daniel, R1 aZeggini, Eleftheria1 aSaleheen, Danish1 aButterworth, Adam, S1 aDanesh, John1 aAsselbergs, Folkert, W1 aWain, Louise, V1 aEhret, Georg, B1 aChasman, Daniel, I1 aCaulfield, Mark, J1 aElliott, Paul1 aLindgren, Cecilia, M1 aLevy, Daniel1 aNewton-Cheh, Christopher1 aMunroe, Patricia, B1 aHowson, Joanna, M M1 aUnderstanding Society Scientific Group1 aCHARGE EXOME BP, CHD Exome+, Exome BP, GoT2D:T2DGenes Consortia, The UK Biobank Cardio-Metabolic Traits Consortium Blood Pressure Working Group† uhttps://chs-nhlbi.org/node/756905167nas a2201273 4500008004100000022001400041245013800055210006900193260001300262300001300275490000700288520164300295653002201938653001201960653004901972653001902021653001402040653002502054653001102079653001702090653003402107653001102141653001702152653000902169653002202178653000902200653003102209653003602240100002002276700001502296700002802311700002202339700002102361700002302382700001802405700002302423700001802446700001902464700002102483700002402504700001702528700001502545700001802560700002302578700001502601700002202616700002102638700001602659700002402675700002002699700001402719700001402733700002002747700002302767700001702790700001702807700002302824700002502847700002402872700001702896700001802913700002202931700002402953700002002977700002202997700001303019700001403032700002403046700001803070700002103088700002003109700001803129700002103147700002203168700001903190700001703209700002803226700002003254700002103274700001803295700001903313700002103332700002403353700001503377700001603392700002003408700002403428700002303452700002103475700002103496700001703517700002003534700002003554700001903574700002403593700002103617700001603638700002103654700001903675700002303694700001403717700002203731700002003753700001703773700002603790700001803816700002303834856003603857 2017 eng d a1553-740400aSingle-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.0 aSingletrait and multitrait genomewide association analyses ident c2017 May ae10067280 v133 aHypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.
10aAfrican Americans10aAnimals10aBasic Helix-Loop-Helix Transcription Factors10aBlood Pressure10aCadherins10aCase-Control Studies10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aHypertension10aMale10aMembrane Proteins10aMice10aMultifactorial Inheritance10aPolymorphism, Single Nucleotide1 aLiang, Jingjing1 aLe, Thu, H1 aEdwards, Digna, R Velez1 aTayo, Bamidele, O1 aGaulton, Kyle, J1 aSmith, Jennifer, A1 aLu, Yingchang1 aJensen, Richard, A1 aChen, Guanjie1 aYanek, Lisa, R1 aSchwander, Karen1 aTajuddin, Salman, M1 aSofer, Tamar1 aKim, Wonji1 aKayima, James1 aMcKenzie, Colin, A1 aFox, Ervin1 aNalls, Michael, A1 aYoung, Hunter, J1 aSun, Yan, V1 aLane, Jacqueline, M1 aCechova, Sylvia1 aZhou, Jie1 aTang, Hua1 aFornage, Myriam1 aMusani, Solomon, K1 aWang, Heming1 aLee, Juyoung1 aAdeyemo, Adebowale1 aDreisbach, Albert, W1 aForrester, Terrence1 aChu, Pei-Lun1 aCappola, Anne1 aEvans, Michele, K1 aMorrison, Alanna, C1 aMartin, Lisa, W1 aWiggins, Kerri, L1 aHui, Qin1 aZhao, Wei1 aJackson, Rebecca, D1 aWare, Erin, B1 aFaul, Jessica, D1 aReiner, Alex, P1 aBray, Michael1 aDenny, Joshua, C1 aMosley, Thomas, H1 aPalmas, Walter1 aGuo, Xiuqing1 aPapanicolaou, George, J1 aPenman, Alan, D1 aPolak, Joseph, F1 aRice, Kenneth1 aTaylor, Ken, D1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aLiu, Kiang1 aRisch, Neil1 aHunt, Steven, C1 aKooperberg, Charles1 aZonderman, Alan, B1 aLaurie, Cathy, C1 aBecker, Diane, M1 aCai, Jianwen1 aLoos, Ruth, J F1 aPsaty, Bruce, M1 aWeir, David, R1 aKardia, Sharon, L R1 aArnett, Donna, K1 aWon, Sungho1 aEdwards, Todd, L1 aRedline, Susan1 aCooper, Richard, S1 aRao, D, C1 aRotter, Jerome, I1 aRotimi, Charles1 aLevy, Daniel1 aChakravarti, Aravinda1 aZhu, Xiaofeng1 aFranceschini, Nora uhttps://chs-nhlbi.org/node/757204643nas a2200985 4500008004100000022001400041245023800055210006900293260001300362300001200375490000800387520178500395653002002180653001802200653002502218653001102243653001202254100003002266700001502296700002202311700002302333700002202356700002802378700001602406700002502422700002202447700002102469700002002490700002402510700001902534700001702553700002002570700002102590700001302611700001802624700002702642700002102669700002202690700002002712700001602732700001702748700002602765700001902791700001802810700002502828700001502853700002702868700002302895700002502918700001902943700001802962700002402980700002003004700002103024700001703045700001803062700001403080700001703094700001803111700001603129700002003145700001403165700001603179700002003195700002403215700002303239700002203262700002603284700002003310700002203330700001903352700002103371700002103392700002403413700002003437700002503457700002503482700001703507700002003524700001903544700002003563700001903583700001903602856003603621 2017 eng d a1432-120300aTrans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci.0 aTransethnic finemapping of genetic loci for body mass index in t c2017 Jun a771-8000 v1363 aMost body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m(2)) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.
10aBody Mass Index10aEthnic Groups10aGenetics, Population10aHumans10aObesity1 aFernandez-Rhodes, Lindsay1 aGong, Jian1 aHaessler, Jeffrey1 aFranceschini, Nora1 aGraff, Mariaelisa1 aNishimura, Katherine, K1 aWang, Yujie1 aHighland, Heather, M1 aYoneyama, Sachiko1 aBush, William, S1 aGoodloe, Robert1 aRitchie, Marylyn, D1 aCrawford, Dana1 aGross, Myron1 aFornage, Myriam1 aBůzková, Petra1 aTao, Ran1 aIsasi, Carmen1 aAvilés-Santa, Larissa1 aDaviglus, Martha1 aMackey, Rachel, H1 aHouston, Denise1 aGu, Charles1 aEhret, Georg1 aNguyen, Khanh-Dung, H1 aLewis, Cora, E1 aLeppert, Mark1 aIrvin, Marguerite, R1 aLim, Unhee1 aHaiman, Christopher, A1 aLe Marchand, Loïc1 aSchumacher, Fredrick1 aWilkens, Lynne1 aLu, Yingchang1 aBottinger, Erwin, P1 aLoos, Ruth, J L1 aSheu, Wayne, H-H1 aGuo, Xiuqing1 aLee, Wen-Jane1 aHai, Yang1 aHung, Yi-Jen1 aAbsher, Devin1 aWu, I-Chien1 aTaylor, Kent, D1 aLee, I-Te1 aLiu, Yeheng1 aWang, Tzung-Dau1 aQuertermous, Thomas1 aJuang, Jyh-Ming, J1 aRotter, Jerome, I1 aAssimes, Themistocles1 aHsiung, Chao, A1 aChen, Yii-Der Ida1 aPrentice, Ross1 aKuller, Lewis, H1 aManson, JoAnn, E1 aKooperberg, Charles1 aSmokowski, Paul1 aRobinson, Whitney, R1 aGordon-Larsen, Penny1 aLi, Rongling1 aHindorff, Lucia1 aBuyske, Steven1 aMatise, Tara, C1 aPeters, Ulrike1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/746505196nas a2201345 4500008004100000022001400041245009400055210006900149260001300218300001200231490000700243520143500250100001901685700002401704700002101728700002501749700002101774700002301795700002101818700001701839700001801856700003001874700002001904700001801924700001801942700002001960700002801980700002102008700001802029700001902047700002202066700002802088700001302116700002202129700002202151700001202173700001902185700002402204700002102228700001902249700001802268700002402286700002002310700001702330700002202347700002202369700001902391700002102410700002402431700001702455700001602472700001902488700002202507700002702529700002402556700002202580700002402602700002002626700002602646700002202672700002302694700001902717700002102736700001602757700002302773700002402796700001302820700001702833700002002850700002202870700002202892700002902914700002002943700002602963700002402989700002203013700002503035700002003060700001903080700002203099700001803121700001703139700002103156700002403177700002103201700001703222700002003239700002303259700002403282700001903306700002403325700002003349700002303369700002403392700002103416700002203437700001903459700001903478700001903497700001503516700002303531700001903554700002303573700002203596700001803618700002003636700002703656700002403683700002203707700002103729700002403750700002203774700001803796856003603814 2018 eng d a2574-830000aCommon and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval.0 aCommon and Rare Coding Genetic Variation Underlying the Electroc c2018 May ae0020370 v113 aBACKGROUND: Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability.
METHODS: We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval.
RESULTS: We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction (<1.2×10), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at (=5.9×10) and (=1.1×10) were associated with PR interval. locus also was implicated in the common variant analysis, whereas was a novel locus.
CONCLUSIONS: We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health.
1 aLin, Honghuang1 avan Setten, Jessica1 aSmith, Albert, V1 aBihlmeyer, Nathan, A1 aWarren, Helen, R1 aBrody, Jennifer, A1 aRadmanesh, Farid1 aHall, Leanne1 aGrarup, Niels1 aMüller-Nurasyid, Martina1 aBoutin, Thibaud1 aVerweij, Niek1 aLin, Henry, J1 aLi-Gao, Ruifang1 avan den Berg, Marten, E1 aMarten, Jonathan1 aWeiss, Stefan1 aPrins, Bram, P1 aHaessler, Jeffrey1 aLyytikäinen, Leo-Pekka1 aMei, Hao1 aHarris, Tamara, B1 aLauner, Lenore, J1 aLi, Man1 aAlonso, Alvaro1 aSoliman, Elsayed, Z1 aConnell, John, M1 aHuang, Paul, L1 aWeng, Lu-Chen1 aJameson, Heather, S1 aHucker, William1 aHanley, Alan1 aTucker, Nathan, R1 aChen, Yii-Der Ida1 aBis, Joshua, C1 aRice, Kenneth, M1 aSitlani, Colleen, M1 aKors, Jan, A1 aXie, Zhijun1 aWen, Chengping1 aMagnani, Jared, W1 aNelson, Christopher, P1 aKanters, Jørgen, K1 aSinner, Moritz, F1 aStrauch, Konstantin1 aPeters, Annette1 aWaldenberger, Melanie1 aMeitinger, Thomas1 aBork-Jensen, Jette1 aPedersen, Oluf1 aLinneberg, Allan1 aRudan, Igor1 ade Boer, Rudolf, A1 avan der Meer, Peter1 aYao, Jie1 aGuo, Xiuqing1 aTaylor, Kent, D1 aSotoodehnia, Nona1 aRotter, Jerome, I1 aMook-Kanamori, Dennis, O1 aTrompet, Stella1 aRivadeneira, Fernando1 aUitterlinden, Andre1 aEijgelsheim, Mark1 aPadmanabhan, Sandosh1 aSmith, Blair, H1 aVölzke, Henry1 aFelix, Stephan, B1 aHomuth, Georg1 aVölker, Uwe1 aMangino, Massimo1 aSpector, Timothy, D1 aBots, Michiel, L1 aPerez, Marco1 aKähönen, Mika1 aRaitakari, Olli, T1 aGudnason, Vilmundur1 aArking, Dan, E1 aMunroe, Patricia, B1 aPsaty, Bruce, M1 aDuijn, Cornelia, M1 aBenjamin, Emelia, J1 aRosand, Jonathan1 aSamani, Nilesh, J1 aHansen, Torben1 aKääb, Stefan1 aPolasek, Ozren1 aHarst, Pim1 aHeckbert, Susan, R1 aJukema, Wouter1 aStricker, Bruno, H1 aHayward, Caroline1 aDörr, Marcus1 aJamshidi, Yalda1 aAsselbergs, Folkert, W1 aKooperberg, Charles1 aLehtimäki, Terho1 aWilson, James, G1 aEllinor, Patrick, T1 aLubitz, Steven, A1 aIsaacs, Aaron uhttps://chs-nhlbi.org/node/780103689nas a2200553 4500008004100000022001400041245023400055210006900289260001600358300001400374490000700388520195100395100002602346700002102372700001602393700002202409700002002431700001902451700001902470700002502489700002202514700002802536700002302564700002902587700001902616700002102635700001802656700001302674700001902687700002502706700002402731700003002755700001902785700002102804700002102825700001802846700002302864700001602887700002202903700002302925700002002948700001902968700001902987700002703006700001903033700002303052700002403075856003603099 2018 eng d a1460-208300aDiscovery, fine-mapping, and conditional analyses of genetic variants associated with C-reactive protein in multiethnic populations using the Metabochip in the Population Architecture using Genomics and Epidemiology (PAGE) study.0 aDiscovery finemapping and conditional analyses of genetic varian c2018 Aug 15 a2940-29530 v273 aC-reactive protein (CRP) is a circulating biomarker indicative of systemic inflammation. We aimed to evaluate genetic associations with CRP levels among non-European-ancestry populations through discovery, fine-mapping and conditional analyses. A total of 30 503 non-European-ancestry participants from 6 studies participating in the Population Architecture using Genomics and Epidemiology study had serum high-sensitivity CRP measurements and ∼200 000 single nucleotide polymorphisms (SNPs) genotyped on the Metabochip. We evaluated the association between each SNP and log-transformed CRP levels using multivariate linear regression, with additive genetic models adjusted for age, sex, the first four principal components of genetic ancestry, and study-specific factors. Differential linkage disequilibrium patterns between race/ethnicity groups were used to fine-map regions associated with CRP levels. Conditional analyses evaluated for multiple independent signals within genetic regions. One hundred and sixty-three unique variants in 12 loci in overall or race/ethnicity-stratified Metabochip-wide scans reached a Bonferroni-corrected P-value <2.5E-7. Three loci have no (HACL1, OLFML2B) or only limited (PLA2G6) previous associations with CRP levels. Six loci had different top hits in race/ethnicity-specific versus overall analyses. Fine-mapping refined the signal in six loci, particularly in HNF1A. Conditional analyses provided evidence for secondary signals in LEPR, IL1RN and HNF1A, and for multiple independent signals in CRP and APOE. We identified novel variants and loci associated with CRP levels, generalized known CRP associations to a multiethnic study population, refined association signals at several loci and found evidence for multiple independent signals at several well-known loci. This study demonstrates the benefit of conducting inclusive genetic association studies in large multiethnic populations.
1 aKocarnik, Jonathan, M1 aRichard, Melissa1 aGraff, Misa1 aHaessler, Jeffrey1 aBien, Stephanie1 aCarlson, Chris1 aCarty, Cara, L1 aReiner, Alexander, P1 aAvery, Christy, L1 aBallantyne, Christie, M1 aLaCroix, Andrea, Z1 aAssimes, Themistocles, L1 aBarbalic, Maja1 aPankratz, Nathan1 aTang, Weihong1 aTao, Ran1 aChen, Dongquan1 aTalavera, Gregory, A1 aDaviglus, Martha, L1 aChirinos-Medina, Diana, A1 aPereira, Rocio1 aNishimura, Katie1 aBůzková, Petra1 aBest, Lyle, G1 aAmbite, Jose, Luis1 aCheng, Iona1 aCrawford, Dana, C1 aHindorff, Lucia, A1 aFornage, Myriam1 aHeiss, Gerardo1 aNorth, Kari, E1 aHaiman, Christopher, A1 aPeters, Ulrike1 aLe Marchand, Loïc1 aKooperberg, Charles uhttps://chs-nhlbi.org/node/779805658nas a2201489 4500008004100000022001400041245010600055210006900161260001500230300000700245490000700252520146500259100001901724700002101743700002301764700002701787700001901814700002501833700002501858700002301883700002501906700002901931700002201960700002301982700001702005700001702022700001802039700002202057700002002079700002102099700001802120700002002138700001902158700001802177700002802195700002102223700001302244700003002257700001902287700002502306700002102331700001902352700002302371700002002394700002402414700002102438700001802459700002102477700001802498700001902516700002002535700002102555700002302576700002402599700002202623700002402645700001702669700002202686700002202708700002202730700002302752700001902775700001702794700002002811700001702831700002202848700002202870700001202892700002102904700002702925700001902952700001702971700002002988700001903008700002003027700002303047700002103070700002203091700002203113700002403135700002003159700002403179700002803203700001903231700002003250700002403270700002103294700002403315700001703339700001903356700002603375700002103401700001603422700002703438700001803465700002303483700002103506700002803527700002403555700001903579700001903598700002403617700002403641700002203665700001803687700002203705700002903727700002403756700003203780700002103812700001603833700002203849700002403871700002003895700001603915700002303931700001803954700002203972700002003994700001504014700002104029700002404050700001904074700001904093700002004112856003604132 2018 eng d a1474-760X00aExome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6.0 aExomechip metaanalysis identifies novel loci associated with car c2018 07 17 a870 v193 aBACKGROUND: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear.
RESULTS: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction.
CONCLUSIONS: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.
1 aPrins, Bram, P1 aMead, Timothy, J1 aBrody, Jennifer, A1 aSveinbjornsson, Gardar1 aNtalla, Ioanna1 aBihlmeyer, Nathan, A1 avan den Berg, Marten1 aBork-Jensen, Jette1 aCappellani, Stefania1 aVan Duijvenboden, Stefan1 aKlena, Nikolai, T1 aGabriel, George, C1 aLiu, Xiaoqin1 aGulec, Cagri1 aGrarup, Niels1 aHaessler, Jeffrey1 aHall, Leanne, M1 aIorio, Annamaria1 aIsaacs, Aaron1 aLi-Gao, Ruifang1 aLin, Honghuang1 aLiu, Ching-Ti1 aLyytikäinen, Leo-Pekka1 aMarten, Jonathan1 aMei, Hao1 aMüller-Nurasyid, Martina1 aOrini, Michele1 aPadmanabhan, Sandosh1 aRadmanesh, Farid1 aRamirez, Julia1 aRobino, Antonietta1 aSchwartz, Molly1 avan Setten, Jessica1 aSmith, Albert, V1 aVerweij, Niek1 aWarren, Helen, R1 aWeiss, Stefan1 aAlonso, Alvaro1 aArnar, David, O1 aBots, Michiel, L1 ade Boer, Rudolf, A1 aDominiczak, Anna, F1 aEijgelsheim, Mark1 aEllinor, Patrick, T1 aGuo, Xiuqing1 aFelix, Stephan, B1 aHarris, Tamara, B1 aHayward, Caroline1 aHeckbert, Susan, R1 aHuang, Paul, L1 aJukema, J, W1 aKähönen, Mika1 aKors, Jan, A1 aLambiase, Pier, D1 aLauner, Lenore, J1 aLi, Man1 aLinneberg, Allan1 aNelson, Christopher, P1 aPedersen, Oluf1 aPerez, Marco1 aPeters, Annette1 aPolasek, Ozren1 aPsaty, Bruce, M1 aRaitakari, Olli, T1 aRice, Kenneth, M1 aRotter, Jerome, I1 aSinner, Moritz, F1 aSoliman, Elsayed, Z1 aSpector, Tim, D1 aStrauch, Konstantin1 aThorsteinsdottir, Unnur1 aTinker, Andrew1 aTrompet, Stella1 aUitterlinden, Andre1 aVaartjes, Ilonca1 avan der Meer, Peter1 aVölker, Uwe1 aVölzke, Henry1 aWaldenberger, Melanie1 aWilson, James, G1 aXie, Zhijun1 aAsselbergs, Folkert, W1 aDörr, Marcus1 aDuijn, Cornelia, M1 aGasparini, Paolo1 aGudbjartsson, Daniel, F1 aGudnason, Vilmundur1 aHansen, Torben1 aKääb, Stefan1 aKanters, Jørgen, K1 aKooperberg, Charles1 aLehtimäki, Terho1 aLin, Henry, J1 aLubitz, Steven, A1 aMook-Kanamori, Dennis, O1 aConti, Francesco, J1 aNewton-Cheh, Christopher, H1 aRosand, Jonathan1 aRudan, Igor1 aSamani, Nilesh, J1 aSinagra, Gianfranco1 aSmith, Blair, H1 aHolm, Hilma1 aStricker, Bruno, H1 aUlivi, Sheila1 aSotoodehnia, Nona1 aApte, Suneel, S1 aHarst, Pim1 aStefansson, Kari1 aMunroe, Patricia, B1 aArking, Dan, E1 aLo, Cecilia, W1 aJamshidi, Yalda uhttps://chs-nhlbi.org/node/780905298nas a2201333 4500008004100000022001400041245011200055210006900167260001300236300001200249490000700261520154600268100002501814700002301839700002601862700002101888700001901909700001801928700001801946700002101964700002101985700002002006700001802026700001302044700003002057700002502087700001802112700001702130700001302147700002002160700002502180700001802205700001902223700002402242700002202266700002802288700001202316700001902328700002402347700001902371700001602390700002202406700002002428700002302448700002202471700002502493700002102518700001902539700001602558700002402574700001702598700002102615700002202636700002702658700002102685700002302706700001902729700001902748700002102767700002202788700002002810700002602830700002202856700002002878700001802898700001602916700002302932700002402955700001802979700002002997700002303017700002003040700001903060700001803079700002503097700002603122700002403148700001703172700001803189700001903207700002203226700002103248700002403269700002103293700001703314700002303331700002003354700001803374700002403392700002403416700002203440700002303462700003203485700002203517700002103539700002203560700002403582700002103606700001903627700001903646700001503665700002303680700002203703700002903725700002203754700001803776700002003794700002703814700002403841700002203865700001903887700002203906856003603928 2018 eng d a2574-830000aExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals.0 aExomeChipWide Analysis of 95 626 Individuals Identifies 10 Novel c2018 Jan ae0017580 v113 aBACKGROUND: QT interval, measured through a standard ECG, captures the time it takes for the cardiac ventricles to depolarize and repolarize. JT interval is the component of the QT interval that reflects ventricular repolarization alone. Prolonged QT interval has been linked to higher risk of sudden cardiac arrest.
METHODS AND RESULTS: We performed an ExomeChip-wide analysis for both QT and JT intervals, including 209 449 variants, both common and rare, in 17 341 genes from the Illumina Infinium HumanExome BeadChip. We identified 10 loci that modulate QT and JT interval duration that have not been previously reported in the literature using single-variant statistical models in a meta-analysis of 95 626 individuals from 23 cohorts (comprised 83 884 European ancestry individuals, 9610 blacks, 1382 Hispanics, and 750 Asians). This brings the total number of ventricular repolarization associated loci to 45. In addition, our approach of using coding variants has highlighted the role of 17 specific genes for involvement in ventricular repolarization, 7 of which are in novel loci.
CONCLUSIONS: Our analyses show a role for myocyte internal structure and interconnections in modulating QT interval duration, adding to previous known roles of potassium, sodium, and calcium ion regulation, as well as autonomic control. We anticipate that these discoveries will open new paths to the goal of making novel remedies for the prevention of lethal ventricular arrhythmias and sudden cardiac arrest.
1 aBihlmeyer, Nathan, A1 aBrody, Jennifer, A1 aSmith, Albert, Vernon1 aWarren, Helen, R1 aLin, Honghuang1 aIsaacs, Aaron1 aLiu, Ching-Ti1 aMarten, Jonathan1 aRadmanesh, Farid1 aHall, Leanne, M1 aGrarup, Niels1 aMei, Hao1 aMüller-Nurasyid, Martina1 aHuffman, Jennifer, E1 aVerweij, Niek1 aGuo, Xiuqing1 aYao, Jie1 aLi-Gao, Ruifang1 avan den Berg, Marten1 aWeiss, Stefan1 aPrins, Bram, P1 avan Setten, Jessica1 aHaessler, Jeffrey1 aLyytikäinen, Leo-Pekka1 aLi, Man1 aAlonso, Alvaro1 aSoliman, Elsayed, Z1 aBis, Joshua, C1 aAustin, Tom1 aChen, Yii-Der Ida1 aPsaty, Bruce, M1 aHarrris, Tamara, B1 aLauner, Lenore, J1 aPadmanabhan, Sandosh1 aDominiczak, Anna1 aHuang, Paul, L1 aXie, Zhijun1 aEllinor, Patrick, T1 aKors, Jan, A1 aCampbell, Archie1 aMurray, Alison, D1 aNelson, Christopher, P1 aTobin, Martin, D1 aBork-Jensen, Jette1 aHansen, Torben1 aPedersen, Oluf1 aLinneberg, Allan1 aSinner, Moritz, F1 aPeters, Annette1 aWaldenberger, Melanie1 aMeitinger, Thomas1 aPerz, Siegfried1 aKolcic, Ivana1 aRudan, Igor1 ade Boer, Rudolf, A1 avan der Meer, Peter1 aLin, Henry, J1 aTaylor, Kent, D1 ade Mutsert, Renée1 aTrompet, Stella1 aJukema, Wouter1 aMaan, Arie, C1 aStricker, Bruno, H C1 aRivadeneira, Fernando1 aUitterlinden, Andre1 aVölker, Uwe1 aHomuth, Georg1 aVölzke, Henry1 aFelix, Stephan, B1 aMangino, Massimo1 aSpector, Timothy, D1 aBots, Michiel, L1 aPerez, Marco1 aRaitakari, Olli, T1 aKähönen, Mika1 aMononen, Nina1 aGudnason, Vilmundur1 aMunroe, Patricia, B1 aLubitz, Steven, A1 aDuijn, Cornelia, M1 aNewton-Cheh, Christopher, H1 aHayward, Caroline1 aRosand, Jonathan1 aSamani, Nilesh, J1 aKanters, Jørgen, K1 aWilson, James, G1 aKääb, Stefan1 aPolasek, Ozren1 aHarst, Pim1 aHeckbert, Susan, R1 aRotter, Jerome, I1 aMook-Kanamori, Dennis, O1 aEijgelsheim, Mark1 aDörr, Marcus1 aJamshidi, Yalda1 aAsselbergs, Folkert, W1 aKooperberg, Charles1 aLehtimäki, Terho1 aArking, Dan, E1 aSotoodehnia, Nona uhttps://chs-nhlbi.org/node/778402961nas a2200325 4500008004100000022001400041245012600055210006900181260001600250520195800266100002402224700002302248700002202271700002302293700001302316700002502329700002202354700001802376700002002394700002302414700002002437700002202457700001602479700001902495700002002514700001902534700002402553700002202577856003602599 2018 eng d a1096-865200aGeneralization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study.0 aGeneralization and fine mapping of red blood cell trait genetic c2018 Jun 153 aRed blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs through fine-mapping. Here, we report the first fine-mapping of six correlated (Pearson's r range: |0.04 - 0.92|) RBC traits in up to 19,036 African Americans and 19,562 Hispanic/Latinos participants of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Trans-ethnic meta-analysis of race/ethnic- and study-specific estimates for approximately 11,000 SNPs flanking 13 previously identified association signals as well as 150,000 additional array-wide SNPs was performed using inverse-variance meta-analysis after adjusting for study and clinical covariates. Approximately half of previously reported index SNP-RBC trait associations generalized to the trans-ethnic study population (p<1.7x10 ); previously unreported independent association signals within the ABO region reinforce the potential for multiple functional variants affecting the same locus. Trans-ethnic fine-mapping did not reveal additional signals at the HFE locus independent of the known functional variants. Finally, we identified a potential novel association in the Hispanic/Latino study population at the HECTD4/RPL6 locus for RBC count (p=1.9x10 ). The identification of a previously unknown association, generalization of a large proportion of known association signals, and refinement of known association signals all exemplify the benefits of genetic studies in diverse populations. This article is protected by copyright. All rights reserved.
1 aHodonsky, Chani, Jo1 aSchurmann, Claudia1 aSchick, Ursula, M1 aKocarnik, Jonathan1 aTao, Ran1 avan Rooij, Frank, Ja1 aWassel, Christina1 aBuyske, Steve1 aFornage, Myriam1 aHindorff, Lucia, A1 aFloyd, James, S1 aGanesh, Santhi, K1 aLin, Dan-Yu1 aNorth, Kari, E1 aReiner, Alex, P1 aLoos, Ruth, Jf1 aKooperberg, Charles1 aAvery, Christy, L uhttps://chs-nhlbi.org/node/779311426nas a2203589 4500008004100000022001400041245015500055210006900210260001600279300001200295490000800307520141100315100002001726700001601746700001601762700002701778700002201805700001901827700002701846700002001873700001801893700001901911700001301930700002101943700001901964700001901983700001502002700001202017700001902029700001802048700002002066700002102086700002502107700001802132700001602150700002002166700001802186700002102204700001502225700001802240700002102258700002002279700002202299700002102321700002302342700001802365700002702383700002802410700002702438700001802465700001902483700001902502700002102521700001902542700001602561700002602577700002002603700002202623700001802645700001602663700001902679700002202698700001802720700001302738700002102751700002602772700002402798700002002822700002502842700002102867700001902888700002202907700001802929700002102947700002002968700002302988700001303011700001903024700001603043700001803059700002403077700001703101700002003118700002303138700002703161700002803188700001503216700002503231700001403256700002203270700002203292700001903314700001703333700001703350700001503367700001603382700001803398700002003416700001903436700002503455700002003480700001703500700002003517700001903537700001803556700002303574700002303597700001903620700002303639700002703662700002803689700002403717700002503741700002603766700001703792700002203809700002303831700002003854700002003874700002303894700002303917700002203940700001803962700002503980700001704005700002004022700002204042700002204064700002204086700002004108700001904128700002104147700002504168700002704193700001904220700002404239700002304263700002004286700002004306700002204326700002104348700001904369700002204388700002004410700002604430700001904456700002404475700002704499700002004526700002404546700002604570700001904596700002004615700002004635700002004655700001704675700002204692700002404714700001704738700002204755700002204777700002204799700002004821700002404841700002204865700003004887700002404917700002604941700002504967700002104992700001505013700002305028700002005051700002405071700002005095700002105115700002805136700002005164700002805184700001905212700002405231700001905255700002205274700002305296700001905319700002205338700001905360700002105379700002205400700002105422700002105443700002005464700001805484700002505502700001905527700002105546700001505567700001505582700002205597700002005619700002405639700002105663700002405684700001805708700002405726700002505750700002605775700002405801700002205825700002105847700001705868700002005885700002305905700002005928700002105948700002305969700002405992700002306016700002306039700002306062700001906085700002406104700002106128700002706149700001906176700002006195700002006215700001806235700002806253700002006281700002406301700001106325700002106336700002306357700002206380700002006402700002106422700002306443700001906466700002006485700001706505700002306522700002106545700002706566700002106593700002506614700001706639700002206656700001906678700002006697700002506717700002906742700002006771700002106791700002606812700002506838700002206863700002006885700001806905700001806923700002406941700001506965700001906980700002206999700001907021700002207040700002207062700002307084700002107107700002407128700002307152700002207175700001907197700001507216700002107231700002007252700002007272700002007292700002407312700002007336700002407356700002207380700002007402700002207422700001907444700002107463700002707484700002007511700001707531700001907548700001707567700002107584700002407605700002307629700001907652700002007671700001907691700002507710710002707735710003807762856003607800 2018 eng d a1537-660500aGenome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders.0 aGenome Analyses of 200000 Individuals Identify 58 Loci for Chron c2018 Nov 01 a691-7060 v1033 aC-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.
1 aLigthart, Symen1 aVaez, Ahmad1 aVõsa, Urmo1 aStathopoulou, Maria, G1 ade Vries, Paul, S1 aPrins, Bram, P1 avan der Most, Peter, J1 aTanaka, Toshiko1 aNaderi, Elnaz1 aRose, Lynda, M1 aWu, Ying1 aKarlsson, Robert1 aBarbalic, Maja1 aLin, Honghuang1 aPool, Rene1 aZhu, Gu1 aMace, Aurelien1 aSidore, Carlo1 aTrompet, Stella1 aMangino, Massimo1 aSabater-Lleal, Maria1 aKemp, John, P1 aAbbasi, Ali1 aKacprowski, Tim1 aVerweij, Niek1 aSmith, Albert, V1 aHuang, Tao1 aMarzi, Carola1 aFeitosa, Mary, F1 aLohman, Kurt, K1 aKleber, Marcus, E1 aMilaneschi, Yuri1 aMueller, Christian1 aHuq, Mahmudul1 aVlachopoulou, Efthymia1 aLyytikäinen, Leo-Pekka1 aOldmeadow, Christopher1 aDeelen, Joris1 aPerola, Markus1 aZhao, Jing Hua1 aFeenstra, Bjarke1 aAmini, Marzyeh1 aLahti, Jari1 aSchraut, Katharina, E1 aFornage, Myriam1 aSuktitipat, Bhoom1 aChen, Wei-Min1 aLi, Xiaohui1 aNutile, Teresa1 aMalerba, Giovanni1 aLuan, Jian'an1 aBak, Tom1 aSchork, Nicholas1 aM, Fabiola, del Greco1 aThiering, Elisabeth1 aMahajan, Anubha1 aMarioni, Riccardo, E1 aMihailov, Evelin1 aEriksson, Joel1 aOzel, Ayse, Bilge1 aZhang, Weihua1 aNethander, Maria1 aCheng, Yu-Ching1 aAslibekyan, Stella1 aAng, Wei1 aGandin, Ilaria1 aYengo, Loic1 aPortas, Laura1 aKooperberg, Charles1 aHofer, Edith1 aRajan, Kumar, B1 aSchurmann, Claudia1 aHollander, Wouter, den1 aAhluwalia, Tarunveer, S1 aZhao, Jing1 aDraisma, Harmen, H M1 aFord, Ian1 aTimpson, Nicholas1 aTeumer, Alexander1 aHuang, Hongyan1 aWahl, Simone1 aLiu, Yongmei1 aHuang, Jie1 aUh, Hae-Won1 aGeller, Frank1 aJoshi, Peter, K1 aYanek, Lisa, R1 aTrabetti, Elisabetta1 aLehne, Benjamin1 aVozzi, Diego1 aVerbanck, Marie1 aBiino, Ginevra1 aSaba, Yasaman1 aMeulenbelt, Ingrid1 aO'Connell, Jeff, R1 aLaakso, Markku1 aGiulianini, Franco1 aMagnusson, Patrik, K E1 aBallantyne, Christie, M1 aHottenga, Jouke Jan1 aMontgomery, Grant, W1 aRivadineira, Fernando1 aRueedi, Rico1 aSteri, Maristella1 aHerzig, Karl-Heinz1 aStott, David, J1 aMenni, Cristina1 aFrånberg, Mattias1 aSt Pourcain, Beate1 aFelix, Stephan, B1 aPers, Tune, H1 aBakker, Stephan, J L1 aKraft, Peter1 aPeters, Annette1 aVaidya, Dhananjay1 aDelgado, Graciela1 aSmit, Johannes, H1 aGroßmann, Vera1 aSinisalo, Juha1 aSeppälä, Ilkka1 aWilliams, Stephen, R1 aHolliday, Elizabeth, G1 aMoed, Matthijs1 aLangenberg, Claudia1 aRäikkönen, Katri1 aDing, Jingzhong1 aCampbell, Harry1 aSale, Michèle, M1 aChen, Yii-der, I1 aJames, Alan, L1 aRuggiero, Daniela1 aSoranzo, Nicole1 aHartman, Catharina, A1 aSmith, Erin, N1 aBerenson, Gerald, S1 aFuchsberger, Christian1 aHernandez, Dena1 aTiesler, Carla, M T1 aGiedraitis, Vilmantas1 aLiewald, David1 aFischer, Krista1 aMellström, Dan1 aLarsson, Anders1 aWang, Yunmei1 aScott, William, R1 aLorentzon, Matthias1 aBeilby, John1 aRyan, Kathleen, A1 aPennell, Craig, E1 aVuckovic, Dragana1 aBalkau, Beverly1 aConcas, Maria, Pina1 aSchmidt, Reinhold1 ade Leon, Carlos, F Mendes1 aBottinger, Erwin, P1 aKloppenburg, Margreet1 aPaternoster, Lavinia1 aBoehnke, Michael1 aMusk, A, W1 aWillemsen, Gonneke1 aEvans, David, M1 aMadden, Pamela, A F1 aKähönen, Mika1 aKutalik, Zoltán1 aZoledziewska, Magdalena1 aKarhunen, Ville1 aKritchevsky, Stephen, B1 aSattar, Naveed1 aLachance, Genevieve1 aClarke, Robert1 aHarris, Tamara, B1 aRaitakari, Olli, T1 aAttia, John, R1 avan Heemst, Diana1 aKajantie, Eero1 aSorice, Rossella1 aGambaro, Giovanni1 aScott, Robert, A1 aHicks, Andrew, A1 aFerrucci, Luigi1 aStandl, Marie1 aLindgren, Cecilia, M1 aStarr, John, M1 aKarlsson, Magnus1 aLind, Lars1 aLi, Jun, Z1 aChambers, John, C1 aMori, Trevor, A1 ade Geus, Eco, J C N1 aHeath, Andrew, C1 aMartin, Nicholas, G1 aAuvinen, Juha1 aBuckley, Brendan, M1 ade Craen, Anton, J M1 aWaldenberger, Melanie1 aStrauch, Konstantin1 aMeitinger, Thomas1 aScott, Rodney, J1 aMcEvoy, Mark1 aBeekman, Marian1 aBombieri, Cristina1 aRidker, Paul, M1 aMohlke, Karen, L1 aPedersen, Nancy, L1 aMorrison, Alanna, C1 aBoomsma, Dorret, I1 aWhitfield, John, B1 aStrachan, David, P1 aHofman, Albert1 aVollenweider, Peter1 aCucca, Francesco1 aJarvelin, Marjo-Riitta1 aJukema, Wouter1 aSpector, Tim, D1 aHamsten, Anders1 aZeller, Tanja1 aUitterlinden, André, G1 aNauck, Matthias1 aGudnason, Vilmundur1 aQi, Lu1 aGrallert, Harald1 aBorecki, Ingrid, B1 aRotter, Jerome, I1 aMärz, Winfried1 aWild, Philipp, S1 aLokki, Marja-Liisa1 aBoyle, Michael1 aSalomaa, Veikko1 aMelbye, Mads1 aEriksson, Johan, G1 aWilson, James, F1 aPenninx, Brenda, W J H1 aBecker, Diane, M1 aWorrall, Bradford, B1 aGibson, Greg1 aKrauss, Ronald, M1 aCiullo, Marina1 aZaza, Gianluigi1 aWareham, Nicholas, J1 aOldehinkel, Albertine, J1 aPalmer, Lyle, J1 aMurray, Sarah, S1 aPramstaller, Peter, P1 aBandinelli, Stefania1 aHeinrich, Joachim1 aIngelsson, Erik1 aDeary, Ian, J1 aMägi, Reedik1 aVandenput, Liesbeth1 aHarst, Pim1 aDesch, Karl, C1 aKooner, Jaspal, S1 aOhlsson, Claes1 aHayward, Caroline1 aLehtimäki, Terho1 aShuldiner, Alan, R1 aArnett, Donna, K1 aBeilin, Lawrence, J1 aRobino, Antonietta1 aFroguel, Philippe1 aPirastu, Mario1 aJess, Tine1 aKoenig, Wolfgang1 aLoos, Ruth, J F1 aEvans, Denis, A1 aSchmidt, Helena1 aSmith, George Davey1 aSlagboom, Eline1 aEiriksdottir, Gudny1 aMorris, Andrew, P1 aPsaty, Bruce, M1 aTracy, Russell, P1 aNolte, Ilja, M1 aBoerwinkle, Eric1 aVisvikis-Siest, Sophie1 aReiner, Alex, P1 aGross, Myron1 aBis, Joshua, C1 aFranke, Lude1 aFranco, Oscar, H1 aBenjamin, Emelia, J1 aChasman, Daniel, I1 aDupuis, Josée1 aSnieder, Harold1 aDehghan, Abbas1 aAlizadeh, Behrooz, Z1 aLifeLines Cohort Study1 aCHARGE Inflammation Working Group uhttps://chs-nhlbi.org/node/792012060nas a2203745 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2018 eng d a1537-660500aA Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.0 aLargeScale Multiancestry Genomewide Study Accounting for Smoking c2018 Mar 01 a375-4000 v1023 aGenome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).
1 aSung, Yun, J1 aWinkler, Thomas, W1 aFuentes, Lisa, de Las1 aBentley, Amy, R1 aBrown, Michael, R1 aKraja, Aldi, T1 aSchwander, Karen1 aNtalla, Ioanna1 aGuo, Xiuqing1 aFranceschini, Nora1 aLu, Yingchang1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aMarten, Jonathan1 aMusani, Solomon, K1 aLi, Changwei1 aFeitosa, Mary, F1 aKilpeläinen, Tuomas, O1 aRichard, Melissa, A1 aNoordam, Raymond1 aAslibekyan, Stella1 aAschard, Hugues1 aBartz, Traci, M1 aDorajoo, Rajkumar1 aLiu, Yongmei1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, Vernon1 aTajuddin, Salman, M1 aTayo, Bamidele, O1 aWarren, Helen, R1 aZhao, Wei1 aZhou, Yanhua1 aMatoba, Nana1 aSofer, Tamar1 aAlver, Maris1 aAmini, Marzyeh1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aGandin, Ilaria1 aGao, Chuan1 aGiulianini, Franco1 aGoel, Anuj1 aHarris, Sarah, E1 aHartwig, Fernando, Pires1 aHorimoto, Andrea, R V R1 aHsu, Fang-Chi1 aJackson, Anne, U1 aKähönen, Mika1 aKasturiratne, Anuradhani1 aKuhnel, Brigitte1 aLeander, Karin1 aLee, Wen-Jane1 aLin, Keng-Hung1 aLuan, Jian, 'an1 aMcKenzie, Colin, A1 aMeian, He1 aNelson, Christopher, P1 aRauramaa, Rainer1 aSchupf, Nicole1 aScott, Robert, A1 aSheu, Wayne, H H1 aStančáková, Alena1 aTakeuchi, Fumihiko1 avan der Most, Peter, J1 aVarga, Tibor, V1 aWang, Heming1 aWang, Yajuan1 aWare, Erin, B1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAfaq, Saima1 aAlfred, Tamuno1 aAmin, Najaf1 aArking, Dan1 aAung, Tin1 aBarr, Graham1 aBielak, Lawrence, F1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aBraund, Peter, S1 aBrody, Jennifer, A1 aBroeckel, Ulrich1 aCabrera, Claudia, P1 aCade, Brian1 aCaizheng, Yu1 aCampbell, Archie1 aCanouil, Mickaël1 aChakravarti, Aravinda1 aChauhan, Ganesh1 aChristensen, Kaare1 aCocca, Massimiliano1 aCollins, Francis, S1 aConnell, John, M1 ade Mutsert, Renée1 ade Silva, Janaka1 aDebette, Stephanie1 aDörr, Marcus1 aDuan, Qing1 aEaton, Charles, B1 aEhret, Georg1 aEvangelou, Evangelos1 aFaul, Jessica, D1 aFisher, Virginia, A1 aForouhi, Nita, G1 aFranco, Oscar, H1 aFriedlander, Yechiel1 aGao, He1 aGigante, Bruna1 aGraff, Misa1 aGu, Charles1 aGu, Dongfeng1 aGupta, Preeti1 aHagenaars, Saskia, P1 aHarris, Tamara, B1 aHe, Jiang1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHofman, Albert1 aHoward, Barbara, V1 aHunt, Steven1 aIrvin, Marguerite, R1 aJia, Yucheng1 aJoehanes, Roby1 aJustice, Anne, E1 aKatsuya, Tomohiro1 aKaufman, Joel1 aKerrison, Nicola, D1 aKhor, Chiea, Chuen1 aKoh, Woon-Puay1 aKoistinen, Heikki, A1 aKomulainen, Pirjo1 aKooperberg, Charles1 aKrieger, Jose, E1 aKubo, Michiaki1 aKuusisto, Johanna1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLewis, Cora, E1 aLi, Yize1 aLim, Sing, Hui1 aLin, Shiow1 aLiu, Ching-Ti1 aLiu, Jianjun1 aLiu, Jingmin1 aLiu, Kiang1 aLiu, Yeheng1 aLoh, Marie1 aLohman, Kurt, K1 aLong, Jirong1 aLouie, Tin1 aMägi, Reedik1 aMahajan, Anubha1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilani, Lili1 aMomozawa, Yukihide1 aMorris, Andrew, P1 aMosley, Thomas, H1 aMunson, Peter1 aMurray, Alison, D1 aNalls, Mike, A1 aNasri, Ubaydah1 aNorris, Jill, M1 aNorth, Kari1 aOgunniyi, Adesola1 aPadmanabhan, Sandosh1 aPalmas, Walter, R1 aPalmer, Nicholette, D1 aPankow, James, S1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aRaitakari, Olli, T1 aRenstrom, Frida1 aRice, Treva, K1 aRidker, Paul, M1 aRobino, Antonietta1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRudan, Igor1 aSabanayagam, Charumathi1 aSalako, Babatunde, L1 aSandow, Kevin1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aScott, William, R1 aSeshadri, Sudha1 aSever, Peter1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aTang, Hua1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aUitterlinden, André, G1 aWaldenberger, Melanie1 aWang, Lihua1 aWang, Ya, X1 aBin Wei, Wen1 aWilliams, Christine1 aWilson, Gregory1 aWojczynski, Mary, K1 aYao, Jie1 aYuan, Jian-Min1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aChen, Yii-Der Ida1 ade Faire, Ulf1 aDeary, Ian, J1 aEsko, Tõnu1 aFarrall, Martin1 aForrester, Terrence1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aHorta, Bernardo, Lessa1 aHung, Yi-Jen1 aJonas, Jost, B1 aKato, Norihiro1 aKooner, Jaspal, S1 aLaakso, Markku1 aLehtimäki, Terho1 aLiang, Kae-Woei1 aMagnusson, Patrik, K E1 aNewman, Anne, B1 aOldehinkel, Albertine, J1 aPereira, Alexandre, C1 aRedline, Susan1 aRettig, Rainer1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aWu, Tangchun1 aZheng, Wei1 aKamatani, Yoichiro1 aLaurie, Cathy, C1 aBouchard, Claude1 aCooper, Richard, S1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon, L R1 aKritchevsky, Stephen, B1 aLevy, Daniel1 aO'Connell, Jeff, R1 aPsaty, Bruce, M1 avan Dam, Rob, M1 aSims, Mario1 aArnett, Donna, K1 aMook-Kanamori, Dennis, O1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aFornage, Myriam1 aRotimi, Charles, N1 aProvince, Michael, A1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aLoos, Ruth, J F1 aReiner, Alex, P1 aRotter, Jerome, I1 aZhu, Xiaofeng1 aBierut, Laura, J1 aGauderman, James1 aCaulfield, Mark, J1 aElliott, Paul1 aRice, Kenneth1 aMunroe, Patricia, B1 aMorrison, Alanna, C1 aCupples, Adrienne, L1 aRao, Dabeeru, C1 aChasman, Daniel, I1 aCHARGE Neurology Working Group1 aCOGENT-Kidney Consortium1 aGIANT Consortium1 aLifeLines Cohort Study uhttps://chs-nhlbi.org/node/768616401nas a2205425 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2018 eng d a1546-171800aMultiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.0 aMultiancestry genomewide association study of 520000 subjects id c2018 Apr a524-5370 v503 aStroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
1 aMalik, Rainer1 aChauhan, Ganesh1 aTraylor, Matthew1 aSargurupremraj, Muralidharan1 aOkada, Yukinori1 aMishra, Aniket1 aRutten-Jacobs, Loes1 aGiese, Anne-Katrin1 avan der Laan, Sander, W1 aGretarsdottir, Solveig1 aAnderson, Christopher, D1 aChong, Michael1 aAdams, Hieab, H H1 aAgo, Tetsuro1 aAlmgren, Peter1 aAmouyel, Philippe1 aAy, Hakan1 aBartz, Traci, M1 aBenavente, Oscar, R1 aBevan, Steve1 aBoncoraglio, Giorgio, B1 aBrown, Robert, D1 aButterworth, Adam, S1 aCarrera, Caty1 aCarty, Cara, L1 aChasman, Daniel, I1 aChen, Wei-Min1 aCole, John, W1 aCorrea, Adolfo1 aCotlarciuc, Ioana1 aCruchaga, Carlos1 aDanesh, John1 ade Bakker, Paul, I W1 aDeStefano, Anita, L1 aHoed, Marcel, den1 aDuan, Qing1 aEngelter, Stefan, T1 aFalcone, Guido, J1 aGottesman, Rebecca, F1 aGrewal, Raji, P1 aGudnason, Vilmundur1 aGustafsson, Stefan1 aHaessler, Jeffrey1 aHarris, Tamara, B1 aHassan, Ahamad1 aHavulinna, Aki, S1 aHeckbert, Susan, R1 aHolliday, Elizabeth, G1 aHoward, George1 aHsu, Fang-Chi1 aHyacinth, Hyacinth, I1 aIkram, Arfan, M1 aIngelsson, Erik1 aIrvin, Marguerite, R1 aJian, Xueqiu1 aJimenez-Conde, Jordi1 aJohnson, Julie, A1 aJukema, Wouter1 aKanai, Masahiro1 aKeene, Keith, L1 aKissela, Brett, M1 aKleindorfer, Dawn, O1 aKooperberg, Charles1 aKubo, Michiaki1 aLange, Leslie, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLee, Jin-Moo1 aLemmens, Robin1 aLeys, Didier1 aLewis, Cathryn, M1 aLin, Wei-Yu1 aLindgren, Arne, G1 aLorentzen, Erik1 aMagnusson, Patrik, K1 aMaguire, Jane1 aManichaikul, Ani1 aMcArdle, Patrick, F1 aMeschia, James, F1 aMitchell, Braxton, D1 aMosley, Thomas, H1 aNalls, Michael, A1 aNinomiya, Toshiharu1 aO'Donnell, Martin, J1 aPsaty, Bruce, M1 aPulit, Sara, L1 aRannikmae, Kristiina1 aReiner, Alexander, P1 aRexrode, Kathryn, M1 aRice, Kenneth1 aRich, Stephen, S1 aRidker, Paul, M1 aRost, Natalia, S1 aRothwell, Peter, M1 aRotter, Jerome, I1 aRundek, Tatjana1 aSacco, Ralph, L1 aSakaue, Saori1 aSale, Michèle, M1 aSalomaa, Veikko1 aSapkota, Bishwa, R1 aSchmidt, Reinhold1 aSchmidt, Carsten, O1 aSchminke, Ulf1 aSharma, Pankaj1 aSlowik, Agnieszka1 aSudlow, Cathie, L M1 aTanislav, Christian1 aTatlisumak, Turgut1 aTaylor, Kent, D1 aThijs, Vincent, N S1 aThorleifsson, Gudmar1 aThorsteinsdottir, Unnur1 aTiedt, Steffen1 aTrompet, Stella1 aTzourio, Christophe1 aDuijn, Cornelia, M1 aWalters, Matthew1 aWareham, Nicholas, J1 aWassertheil-Smoller, Sylvia1 aWilson, James, G1 aWiggins, Kerri, L1 aYang, Qiong1 aYusuf, Salim1 aBis, Joshua, C1 aPastinen, Tomi1 aRuusalepp, Arno1 aSchadt, Eric, E1 aKoplev, Simon1 aBjörkegren, Johan, L M1 aCodoni, Veronica1 aCivelek, Mete1 aSmith, Nicholas, L1 aTrégouët, David, A1 aChristophersen, Ingrid, E1 aRoselli, Carolina1 aLubitz, Steven, A1 aEllinor, Patrick, T1 aTai, Shyong, E1 aKooner, Jaspal, S1 aKato, Norihiro1 aHe, Jiang1 aHarst, Pim1 aElliott, Paul1 aChambers, John, C1 aTakeuchi, Fumihiko1 aJohnson, Andrew, D1 aSanghera, Dharambir, K1 aMelander, Olle1 aJern, Christina1 aStrbian, Daniel1 aFernandez-Cadenas, Israel1 aLongstreth, W T1 aRolfs, Arndt1 aHata, Jun1 aWoo, Daniel1 aRosand, Jonathan1 aParé, Guillaume1 aHopewell, Jemma, C1 aSaleheen, Danish1 aStefansson, Kari1 aWorrall, Bradford, B1 aKittner, Steven, J1 aSeshadri, Sudha1 aFornage, Myriam1 aMarkus, Hugh, S1 aHowson, Joanna, M M1 aKamatani, Yoichiro1 aDebette, Stephanie1 aDichgans, Martin1 aMalik, Rainer1 aChauhan, Ganesh1 aTraylor, Matthew1 aSargurupremraj, Muralidharan1 aOkada, Yukinori1 aMishra, Aniket1 aRutten-Jacobs, Loes1 aGiese, Anne-Katrin1 avan der Laan, Sander, W1 aGretarsdottir, Solveig1 aAnderson, Christopher, D1 aChong, Michael1 aAdams, Hieab, H H1 aAgo, Tetsuro1 aAlmgren, Peter1 aAmouyel, Philippe1 aAy, Hakan1 aBartz, Traci, M1 aBenavente, Oscar, R1 aBevan, Steve1 aBoncoraglio, Giorgio, B1 aBrown, Robert, D1 aButterworth, Adam, S1 aCarrera, Caty1 aCarty, Cara, L1 aChasman, Daniel, I1 aChen, Wei-Min1 aCole, John, W1 aCorrea, Adolfo1 aCotlarciuc, Ioana1 aCruchaga, Carlos1 aDanesh, John1 ade Bakker, Paul, I W1 aDeStefano, Anita, L1 aHoed, Marcel, den1 aDuan, Qing1 aEngelter, Stefan, T1 aFalcone, Guido, J1 aGottesman, Rebecca, F1 aGrewal, Raji, P1 aGudnason, Vilmundur1 aGustafsson, Stefan1 aHaessler, Jeffrey1 aHarris, Tamara, B1 aHassan, Ahamad1 aHavulinna, Aki, S1 aHeckbert, Susan, R1 aHolliday, Elizabeth, G1 aHoward, George1 aHsu, Fang-Chi1 aHyacinth, Hyacinth, I1 aIkram, Arfan, M1 aIngelsson, Erik1 aIrvin, Marguerite, R1 aJian, Xueqiu1 aJimenez-Conde, Jordi1 aJohnson, Julie, A1 aJukema, Wouter1 aKanai, Masahiro1 aKeene, Keith, L1 aKissela, Brett, M1 aKleindorfer, Dawn, O1 aKooperberg, Charles1 aKubo, Michiaki1 aLange, Leslie, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLee, Jin-Moo1 aLemmens, Robin1 aLeys, Didier1 aLewis, Cathryn, M1 aLin, Wei-Yu1 aLindgren, Arne, G1 aLorentzen, Erik1 aMagnusson, Patrik, K1 aMaguire, Jane1 aManichaikul, Ani1 aMcArdle, Patrick, F1 aMeschia, James, F1 aMitchell, Braxton, D1 aMosley, Thomas, H1 aNalls, Michael, A1 aNinomiya, Toshiharu1 aO'Donnell, Martin, J1 aPsaty, Bruce, M1 aPulit, Sara, L1 aRannikmae, Kristiina1 aReiner, Alexander, P1 aRexrode, Kathryn, M1 aRice, Kenneth1 aRich, Stephen, S1 aRidker, Paul, M1 aRost, Natalia, S1 aRothwell, Peter, M1 aRotter, Jerome, I1 aRundek, Tatjana1 aSacco, Ralph, L1 aSakaue, Saori1 aSale, Michèle, M1 aSalomaa, Veikko1 aSapkota, Bishwa, R1 aSchmidt, Reinhold1 aSchmidt, Carsten, O1 aSchminke, Ulf1 aSharma, Pankaj1 aSlowik, Agnieszka1 aSudlow, Cathie, L M1 aTanislav, Christian1 aTatlisumak, Turgut1 aTaylor, Kent, D1 aThijs, Vincent, N S1 aThorleifsson, Gudmar1 aThorsteinsdottir, Unnur1 aTiedt, Steffen1 aTrompet, Stella1 aTzourio, Christophe1 aDuijn, Cornelia, M1 aWalters, Matthew1 aWareham, Nicholas, J1 aWassertheil-Smoller, Sylvia1 aWilson, James, G1 aWiggins, Kerri, L1 aYang, Qiong1 aYusuf, Salim1 aAmin, Najaf1 aAparicio, Hugo, S1 aArnett, Donna, K1 aAttia, John1 aBeiser, Alexa, S1 aBerr, Claudine1 aBuring, Julie, E1 aBustamante, Mariana1 aCaso, Valeria1 aCheng, Yu-Ching1 aChoi, Seung, Hoan1 aChowhan, Ayesha1 aCullell, Natalia1 aDartigues, Jean-François1 aDelavaran, Hossein1 aDelgado, Pilar1 aDörr, Marcus1 aEngström, Gunnar1 aFord, Ian1 aGurpreet, Wander, S1 aHamsten, Anders1 aHeitsch, Laura1 aHozawa, Atsushi1 aIbanez, Laura1 aIlinca, Andreea1 aIngelsson, Martin1 aIwasaki, Motoki1 aJackson, Rebecca, D1 aJood, Katarina1 aJousilahti, Pekka1 aKaffashian, Sara1 aKalra, Lalit1 aKamouchi, Masahiro1 aKitazono, Takanari1 aKjartansson, Olafur1 aKloss, Manja1 aKoudstaal, Peter, J1 aKrupinski, Jerzy1 aLabovitz, Daniel, L1 aLaurie, Cathy, C1 aLevi, Christopher, R1 aLi, Linxin1 aLind, Lars1 aLindgren, Cecilia, M1 aLioutas, Vasileios1 aLiu, Yong, Mei1 aLopez, Oscar, L1 aMakoto, Hirata1 aMartinez-Majander, Nicolas1 aMatsuda, Koichi1 aMinegishi, Naoko1 aMontaner, Joan1 aMorris, Andrew, P1 aMuiño, Elena1 aMüller-Nurasyid, Martina1 aNorrving, Bo1 aOgishima, Soichi1 aParati, Eugenio, A1 aPeddareddygari, Leema, Reddy1 aPedersen, Nancy, L1 aPera, Joanna1 aPerola, Markus1 aPezzini, Alessandro1 aPileggi, Silvana1 aRabionet, Raquel1 aRiba-Llena, Iolanda1 aRibasés, Marta1 aRomero, Jose, R1 aRoquer, Jaume1 aRudd, Anthony, G1 aSarin, Antti-Pekka1 aSarju, Ralhan1 aSarnowski, Chloe1 aSasaki, Makoto1 aSatizabal, Claudia, L1 aSatoh, Mamoru1 aSattar, Naveed1 aSawada, Norie1 aSibolt, Gerli1 aSigurdsson, Ásgeir1 aSmith, Albert1 aSobue, Kenji1 aSoriano-Tárraga, Carolina1 aStanne, Tara1 aStine, Colin1 aStott, David, J1 aStrauch, Konstantin1 aTakai, Takako1 aTanaka, Hideo1 aTanno, Kozo1 aTeumer, Alexander1 aTomppo, Liisa1 aTorres-Aguila, Nuria, P1 aTouze, Emmanuel1 aTsugane, Shoichiro1 aUitterlinden, André, G1 aValdimarsson, Einar, M1 avan der Lee, Sven, J1 aVölzke, Henry1 aWakai, Kenji1 aWeir, David1 aWilliams, Stephen, R1 aWolfe, Charles, D A1 aWong, Quenna1 aXu, Huichun1 aYamaji, Taiki1 aSanghera, Dharambir, K1 aMelander, Olle1 aJern, Christina1 aStrbian, Daniel1 aFernandez-Cadenas, Israel1 aLongstreth, W T1 aRolfs, Arndt1 aHata, Jun1 aWoo, Daniel1 aRosand, Jonathan1 aParé, Guillaume1 aHopewell, Jemma, C1 aSaleheen, Danish1 aStefansson, Kari1 aWorrall, Bradford, B1 aKittner, Steven, J1 aSeshadri, Sudha1 aFornage, Myriam1 aMarkus, Hugh, S1 aHowson, Joanna, M M1 aKamatani, Yoichiro1 aDebette, Stephanie1 aDichgans, Martin1 aAFGen Consortium1 aCohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium1 aInternational Genomics of Blood Pressure (iGEN-BP) Consortium1 aINVENT Consortium1 aSTARNET1 aBioBank Japan Cooperative Hospital Group1 aCOMPASS Consortium1 aEPIC-CVD Consortium1 aEPIC-InterAct Consortium1 aInternational Stroke Genetics Consortium (ISGC)1 aMETASTROKE Consortium1 aNeurology Working Group of the CHARGE Consortium1 aNINDS Stroke Genetics Network (SiGN)1 aUK Young Lacunar DNA Study1 aMEGASTROKE Consortium1 aMEGASTROKE Consortium: uhttps://chs-nhlbi.org/node/768311027nas a2203421 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2018 eng d a1932-620300aNovel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.0 aNovel genetic associations for blood pressure identified via gen c2018 ae01981660 v133 aHeavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
1 aFeitosa, Mary, F1 aKraja, Aldi, T1 aChasman, Daniel, I1 aSung, Yun, J1 aWinkler, Thomas, W1 aNtalla, Ioanna1 aGuo, Xiuqing1 aFranceschini, Nora1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aMarten, Jonathan1 aMusani, Solomon, K1 aLi, Changwei1 aBentley, Amy, R1 aBrown, Michael, R1 aSchwander, Karen1 aRichard, Melissa, A1 aNoordam, Raymond1 aAschard, Hugues1 aBartz, Traci, M1 aBielak, Lawrence, F1 aDorajoo, Rajkumar1 aFisher, Virginia1 aHartwig, Fernando, P1 aHorimoto, Andrea, R V R1 aLohman, Kurt, K1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, V1 aTajuddin, Salman, M1 aWojczynski, Mary, K1 aAlver, Maris1 aBoissel, Mathilde1 aCai, Qiuyin1 aCampbell, Archie1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aGao, Chuan1 aGoel, Anuj1 aHagemeijer, Yanick1 aHarris, Sarah, E1 aHe, Meian1 aHsu, Fang-Chi1 aJackson, Anne, U1 aKähönen, Mika1 aKasturiratne, Anuradhani1 aKomulainen, Pirjo1 aKuhnel, Brigitte1 aLaguzzi, Federica1 aLuan, Jian'an1 aMatoba, Nana1 aNolte, Ilja, M1 aPadmanabhan, Sandosh1 aRiaz, Muhammad1 aRueedi, Rico1 aRobino, Antonietta1 aSaid, Abdullah1 aScott, Robert, A1 aSofer, Tamar1 aStančáková, Alena1 aTakeuchi, Fumihiko1 aTayo, Bamidele, O1 avan der Most, Peter, J1 aVarga, Tibor, V1 aVitart, Veronique1 aWang, Yajuan1 aWare, Erin, B1 aWarren, Helen, R1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAfaq, Saima1 aAmin, Najaf1 aAmini, Marzyeh1 aArking, Dan, E1 aAung, Tin1 aBoerwinkle, Eric1 aBorecki, Ingrid1 aBroeckel, Ulrich1 aBrown, Morris1 aBrumat, Marco1 aBurke, Gregory, L1 aCanouil, Mickaël1 aChakravarti, Aravinda1 aCharumathi, Sabanayagam1 aChen, Yii-Der, Ida1 aConnell, John, M1 aCorrea, Adolfo1 aFuentes, Lisa, de Las1 ade Mutsert, Renée1 ade Silva, Janaka1 aDeng, Xuan1 aDing, Jingzhong1 aDuan, Qing1 aEaton, Charles, B1 aEhret, Georg1 aEppinga, Ruben, N1 aEvangelou, Evangelos1 aFaul, Jessica, D1 aFelix, Stephan, B1 aForouhi, Nita, G1 aForrester, Terrence1 aFranco, Oscar, H1 aFriedlander, Yechiel1 aGandin, Ilaria1 aGao, He1 aGhanbari, Mohsen1 aGigante, Bruna1 aGu, Charles1 aGu, Dongfeng1 aHagenaars, Saskia, P1 aHallmans, Göran1 aHarris, Tamara, B1 aHe, Jiang1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHoward, Barbara, V1 aIkram, Arfan, M1 aJohn, Ulrich1 aKatsuya, Tomohiro1 aKhor, Chiea, Chuen1 aKilpeläinen, Tuomas, O1 aKoh, Woon-Puay1 aKrieger, Jose, E1 aKritchevsky, Stephen, B1 aKubo, Michiaki1 aKuusisto, Johanna1 aLakka, Timo, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLewis, Cora, E1 aLi, Yize1 aLin, Shiow1 aLiu, Jianjun1 aLiu, Jingmin1 aLoh, Marie1 aLouie, Tin1 aMägi, Reedik1 aMcKenzie, Colin, A1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMilani, Lili1 aMohlke, Karen, L1 aMomozawa, Yukihide1 aNalls, Mike, A1 aNelson, Christopher, P1 aSotoodehnia, Nona1 aNorris, Jill, M1 aO'Connell, Jeff, R1 aPalmer, Nicholette, D1 aPerls, Thomas1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPoulter, Neil1 aRaffel, Leslie, J1 aRaitakari, Olli, T1 aRoll, Kathryn1 aRose, Lynda, M1 aRosendaal, Frits, R1 aRotter, Jerome, I1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aSchupf, Nicole1 aScott, William, R1 aSever, Peter, S1 aShi, Yuan1 aSidney, Stephen1 aSims, Mario1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aStringham, Heather, M1 aTan, Nicholas, Y Q1 aTang, Hua1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aTurner, Stephen, T1 aUitterlinden, André, G1 aVollenweider, Peter1 aWaldenberger, Melanie1 aWang, Lihua1 aWang, Ya, Xing1 aBin Wei, Wen1 aWilliams, Christine1 aYao, Jie1 aYu, Caizheng1 aYuan, Jian-Min1 aZhao, Wei1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aDeary, Ian, J1 aEsko, Tõnu1 aFarrall, Martin1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aJonas, Jost, Bruno1 aKamatani, Yoichiro1 aKato, Norihiro1 aKooner, Jaspal, S1 aKutalik, Zoltán1 aLaakso, Markku1 aLaurie, Cathy, C1 aLeander, Karin1 aLehtimäki, Terho1 aStudy, Lifelines, Cohort1 aMagnusson, Patrik, K E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aPolasek, Ozren1 aPorteous, David, J1 aRauramaa, Rainer1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aWu, Tangchun1 aZheng, Wei1 aBouchard, Claude1 aChristensen, Kaare1 aEvans, Michele, K1 aGudnason, Vilmundur1 aHorta, Bernardo, L1 aKardia, Sharon, L R1 aLiu, Yongmei1 aPereira, Alexandre, C1 aPsaty, Bruce, M1 aRidker, Paul, M1 avan Dam, Rob, M1 aGauderman, James1 aZhu, Xiaofeng1 aMook-Kanamori, Dennis, O1 aFornage, Myriam1 aRotimi, Charles, N1 aCupples, Adrienne, L1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aKooperberg, Charles1 aPalmas, Walter1 aRice, Kenneth1 aMorrison, Alanna, C1 aElliott, Paul1 aCaulfield, Mark, J1 aMunroe, Patricia, B1 aRao, Dabeeru, C1 aProvince, Michael, A1 aLevy, Daniel1 aInterAct Consortium uhttps://chs-nhlbi.org/node/779204216nas a2200841 4500008004100000022001400041245011700055210006900172260001600241300001400257490000800271520173700279100002102016700001302037700001902050700002002069700003002089700002302119700002302142700002002165700002202185700002102207700002302228700001902251700002002270700002202290700002002312700002202332700002102354700002402375700002502399700002102424700002402445700002202469700002302491700002302514700001902537700002302556700002302579700002302602700001802625700002202643700002502665700002502690700002102715700002102736700002302757700001702780700002102797700002502818700002602843700002702869700002402896700001502920700002202935700001702957700002402974700002402998700001803022700002003040700001803060700002403078700002003102700002003122700002903142700002303171700002503194700003203219700002303251710002803274710003603302856003603338 2019 eng d a1528-002000aGenomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism.0 aGenomic and transcriptomic association studies identify 16 novel c2019 Nov 07 a1645-16570 v1343 aVenous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. We meta-analyzed GWAS data from 18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes.
1 aLindström, Sara1 aWang, Lu1 aSmith, Erin, N1 aGordon, William1 aVlieg, Astrid, van Hylcka1 ade Andrade, Mariza1 aBrody, Jennifer, A1 aPattee, Jack, W1 aHaessler, Jeffrey1 aBrumpton, Ben, M1 aChasman, Daniel, I1 aSuchon, Pierre1 aChen, Ming-Huei1 aTurman, Constance1 aGermain, Marine1 aWiggins, Kerri, L1 aMacDonald, James1 aBraekkan, Sigrid, K1 aArmasu, Sebastian, M1 aPankratz, Nathan1 aJackson, Rebecca, D1 aNielsen, Jonas, B1 aGiulianini, Franco1 aPuurunen, Marja, K1 aIbrahim, Manal1 aHeckbert, Susan, R1 aDamrauer, Scott, M1 aNatarajan, Pradeep1 aKlarin, Derek1 ade Vries, Paul, S1 aSabater-Lleal, Maria1 aHuffman, Jennifer, E1 aBammler, Theo, K1 aFrazer, Kelly, A1 aMcCauley, Bryan, M1 aTaylor, Kent1 aPankow, James, S1 aReiner, Alexander, P1 aGabrielsen, Maiken, E1 aDeleuze, Jean-Francois1 aO'Donnell, Chris, J1 aKim, Jihye1 aMcKnight, Barbara1 aKraft, Peter1 aHansen, John-Bjarne1 aRosendaal, Frits, R1 aHeit, John, A1 aPsaty, Bruce, M1 aTang, Weihong1 aKooperberg, Charles1 aHveem, Kristian1 aRidker, Paul, M1 aMorange, Pierre-Emmanuel1 aJohnson, Andrew, D1 aKabrhel, Christopher1 aTrégouët, David-Alexandre1 aSmith, Nicholas, L1 aMillion Veteran Program1 aCHARGE Hemostasis Working Group uhttps://chs-nhlbi.org/node/820004013nas a2200685 4500008004100000022001400041245016200055210006900217260001600286300001200302490000800314520192200322100002102244700001702265700002302282700001502305700002202320700002002342700001702362700001602379700001702395700001802412700001202430700002302442700002202465700002302487700002502510700001702535700001802552700001902570700002602589700002002615700002402635700002202659700002102681700002002702700002202722700002102744700001902765700002402784700002002808700002302828700002502851700002502876700002502901700002702926700001902953700002402972700002102996700002203017700002103039700002203060700001903082700002003101710003403121710003603155710003603191710006403227856003603291 2019 eng d a1537-660500aImpact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.0 aImpact of Rare and Common Genetic Variants on Diabetes Diagnosis c2019 Oct 03 a706-7180 v1053 aHemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
1 aSarnowski, Chloe1 aLeong, Aaron1 aRaffield, Laura, M1 aWu, Peitao1 ade Vries, Paul, S1 aDiCorpo, Daniel1 aGuo, Xiuqing1 aXu, Huichun1 aLiu, Yongmei1 aZheng, Xiuwen1 aHu, Yao1 aBrody, Jennifer, A1 aGoodarzi, Mark, O1 aHidalgo, Bertha, A1 aHighland, Heather, M1 aJain, Deepti1 aLiu, Ching-Ti1 aNaik, Rakhi, P1 aO'Connell, Jeffrey, R1 aPerry, James, A1 aPorneala, Bianca, C1 aSelvin, Elizabeth1 aWessel, Jennifer1 aPsaty, Bruce, M1 aCurran, Joanne, E1 aPeralta, Juan, M1 aBlangero, John1 aKooperberg, Charles1 aMathias, Rasika1 aJohnson, Andrew, D1 aReiner, Alexander, P1 aMitchell, Braxton, D1 aCupples, Adrienne, L1 aVasan, Ramachandran, S1 aCorrea, Adolfo1 aMorrison, Alanna, C1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aRich, Stephen, S1 aManning, Alisa, K1 aDupuis, Josée1 aMeigs, James, B1 aTOPMed Diabetes Working Group1 aTOPMed Hematology Working Group1 aTOPMed Hemostasis Working Group1 aNational Heart, Lung, and Blood Institute TOPMed Consortium uhttps://chs-nhlbi.org/node/820502918nas a2200589 4500008004100000022001400041245006600055210006200121260001600183520123400199100002101433700002301454700002201477700002001499700002001519700001901539700002001558700002001578700002001598700002101618700002101639700001701660700001701677700001801694700001901712700002601731700001801757700002101775700002401796700002201820700002701842700002901869700001901898700002101917700002001938700002201958700001701980700002501997700002302022700002402045700001702069700002402086700001802110700002302128700002902151700002502180700001702205700002302222700002502245710002202270856003602292 2019 eng d a1098-227200aA large-scale exome array analysis of venous thromboembolism.0 alargescale exome array analysis of venous thromboembolism c2019 Jan 193 aAlthough recent Genome-Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome-wide search for low-frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta-analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene-based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene-based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low-frequency and rare variants associated with VTE risk.
1 aLindström, Sara1 aBrody, Jennifer, A1 aTurman, Constance1 aGermain, Marine1 aBartz, Traci, M1 aSmith, Erin, N1 aChen, Ming-Huei1 aPuurunen, Marja1 aChasman, Daniel1 aHassler, Jeffrey1 aPankratz, Nathan1 aBasu, Saonli1 aGuan, Weihua1 aGyorgy, Beata1 aIbrahim, Manal1 aEmpana, Jean-Philippe1 aOlaso, Robert1 aJackson, Rebecca1 aBraekkan, Sigrid, K1 aMcKnight, Barbara1 aDeleuze, Jean-Francois1 aO'Donnell, Cristopher, J1 aJouven, Xavier1 aFrazer, Kelly, A1 aPsaty, Bruce, M1 aWiggins, Kerri, L1 aTaylor, Kent1 aReiner, Alexander, P1 aHeckbert, Susan, R1 aKooperberg, Charles1 aRidker, Paul1 aHansen, John-Bjarne1 aTang, Weihong1 aJohnson, Andrew, D1 aMorange, Pierre-Emmanuel1 aTrégouët, David, A1 aKraft, Peter1 aSmith, Nicholas, L1 aKabrhel, Christopher1 aINVENT Consortium uhttps://chs-nhlbi.org/node/797910550nas a2203325 4500008004100000022001400041245010600055210006900161260001600230520134200246100002201588700002201610700002001632700001701652700002301669700001901692700002101711700001901732700001701751700002301768700002001791700001701811700002001828700002501848700002301873700001701896700002101913700002401934700002101958700002001979700002001999700002402019700001502043700002202058700002002080700002202100700002002122700002102142700002402163700002502187700002202212700001702234700002202251700002002273700001302293700001902306700001902325700001502344700001502359700002302374700002102397700002502418700001402443700002802457700001802485700002102503700002902524700002202553700002102575700002202596700001902618700001802637700002802655700001702683700001902700700001902719700001902738700001902757700002102776700001702797700002502814700002302839700002202862700002702884700002002911700001702931700001802948700001702966700001902983700001803002700001903020700001603039700001603055700001903071700001903090700001403109700002503123700002103148700002103169700002103190700002203211700002803233700002203261700002103283700001803304700002603322700002303348700002103371700002003392700002403412700001503436700002203451700002203473700002103495700002103516700002403537700002103561700002503582700002103607700002303628700001903651700002003670700001603690700002203706700002003728700002003748700001903768700002103787700002303808700002003831700002103851700001903872700002303891700002503914700002203939700002303961700002803984700001904012700002504031700001804056700002404074700002104098700002604119700001904145700002204164700001904186700002304205700002404228700002204252700002004274700002404294700001304318700002004331700001704351700001504368700001504383700001504398700001804413700002404431700002304455700002204478700002104500700002104521700001704542700002104559700002204580700002404602700001904626700002004645700002704665700002204692700002304714700002604737700001704763700002304780700002004803700002404823700001904847700001804866700002204884700002304906700002004929700001904949700002104968700002304989700002605012700001905038700001605057700002405073700002505097700002205122700001705144700001405161700002005175700001605195700002005211700002305231700002005254700001905274700002405293700001805317700002005335700001905355700002105374700002805395700002205423700002205445700002605467700001605493700001605509700001405525700001705539700002405556700002005580700002405600700001305624700001305637700001705650700001905667700001405686700002305700700002105723700002105744700002205765700002205787700001805809700001605827700002005843700002005863700002305883700002205906700002105928700002205949700002305971700002305994700001906017700002206036700001906058700001906077700002206096700002706118700002006145700002606165700002106191700002206212700001706234700001706251700001506268700002606283700001906309700002506328700001806353700001906371700003006390700001506420700001806435700001906453700002106472700002206493700002406515700001806539700001706557700002006574700002006594700002006614700002406634700001806658700002306676700002906699700002006728700002106748700001806769700002206787700002306809700001906832700002006851700001706871700002206888700002106910700002506931700002406956700001806980700002306998700002507021700002007046700002407066710002407090710007407114856003607188 2019 eng d a1476-625600aMulti-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions.0 aMultiAncestry GenomeWide Association Study of Lipid Levels Incor c2019 Jan 293 aAn individual's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multi-ancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in Stage 1 (genome-wide discovery) and 66 studies in Stage 2 (focused follow-up), for a total of 394,584 individuals from five ancestry groups. Genetic main and interaction effects were jointly assessed by a 2 degrees of freedom (DF) test, and a 1 DF test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in Stage 1 and were evaluated in Stage 2, followed by combined analyses of Stage 1 and Stage 2. In the combined analysis of Stage 1 and Stage 2, 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2 DF tests, of which 18 were novel. No genome-wide significant associations were found testing the interaction effect alone. The novel loci included several genes (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models.
1 ade Vries, Paul, S1 aBrown, Michael, R1 aBentley, Amy, R1 aSung, Yun, J1 aWinkler, Thomas, W1 aNtalla, Ioanna1 aSchwander, Karen1 aKraja, Aldi, T1 aGuo, Xiuqing1 aFranceschini, Nora1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aHuffman, Jennifer, E1 aMusani, Solomon, K1 aLi, Changwei1 aFeitosa, Mary, F1 aRichard, Melissa, A1 aNoordam, Raymond1 aAschard, Hugues1 aBartz, Traci, M1 aBielak, Lawrence, F1 aDeng, Xuan1 aDorajoo, Rajkumar1 aLohman, Kurt, K1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, V1 aTajuddin, Salman, M1 aEvangelou, Evangelos1 aGraff, Mariaelisa1 aAlver, Maris1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aGandin, Ilaria1 aGao, Chuan1 aGoel, Anuj1 aHagemeijer, Yanick1 aHarris, Sarah, E1 aHartwig, Fernando, P1 aHe, Meian1 aHorimoto, Andrea, R V R1 aHsu, Fang-Chi1 aJackson, Anne, U1 aKasturiratne, Anuradhani1 aKomulainen, Pirjo1 aKuhnel, Brigitte1 aLaguzzi, Federica1 aLee, Joseph, H1 aLuan, Jian'an1 aLyytikäinen, Leo-Pekka1 aMatoba, Nana1 aNolte, Ilja, M1 aPietzner, Maik1 aRiaz, Muhammad1 aSaid, Abdullah1 aScott, Robert, A1 aSofer, Tamar1 aStančáková, Alena1 aTakeuchi, Fumihiko1 aTayo, Bamidele, O1 avan der Most, Peter, J1 aVarga, Tibor, V1 aWang, Yajuan1 aWare, Erin, B1 aWen, Wanqing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAfaq, Saima1 aAmin, Najaf1 aAmini, Marzyeh1 aArking, Dan, E1 aAung, Tin1 aBallantyne, Christie1 aBoerwinkle, Eric1 aBroeckel, Ulrich1 aCampbell, Archie1 aCanouil, Mickaël1 aCharumathi, Sabanayagam1 aChen, Yii-Der Ida1 aConnell, John, M1 ade Faire, Ulf1 aFuentes, Lisa, de Las1 ade Mutsert, Renée1 ade Silva, Janaka1 aDing, Jingzhong1 aDominiczak, Anna, F1 aDuan, Qing1 aEaton, Charles, B1 aEppinga, Ruben, N1 aFaul, Jessica, D1 aFisher, Virginia1 aForrester, Terrence1 aFranco, Oscar, H1 aFriedlander, Yechiel1 aGhanbari, Mohsen1 aGiulianini, Franco1 aGrabe, Hans, J1 aGrove, Megan, L1 aGu, Charles1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHixson, James, E1 aHoward, Barbara, V1 aIkram, Arfan, M1 aJacobs, David, R1 aJohnson, Craig1 aJonas, Jost, Bruno1 aKammerer, Candace, M1 aKatsuya, Tomohiro1 aKhor, Chiea, Chuen1 aKilpeläinen, Tuomas, O1 aKoh, Woon-Puay1 aKoistinen, Heikki, A1 aKolcic, Ivana1 aKooperberg, Charles1 aKrieger, Jose, E1 aKritchevsky, Steve, B1 aKubo, Michiaki1 aKuusisto, Johanna1 aLakka, Timo, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLemaitre, Rozenn, N1 aLi, Yize1 aLiang, Jingjing1 aLiu, Jianjun1 aLiu, Kiang1 aLoh, Marie1 aLouie, Tin1 aMägi, Reedik1 aManichaikul, Ani, W1 aMcKenzie, Colin, A1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMilani, Lili1 aMohlke, Karen, L1 aMosley, Thomas, H1 aMukamal, Kenneth, J1 aNalls, Mike, A1 aNauck, Matthias1 aNelson, Christopher, P1 aSotoodehnia, Nona1 aO'Connell, Jeff, R1 aPalmer, Nicholette, D1 aPazoki, Raha1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aPoulter, Neil1 aRaffel, Leslie, J1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRice, Treva, K1 aRich, Stephen, S1 aRobino, Antonietta1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRudan, Igor1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aScott, William, R1 aSever, Peter1 aShi, Yuan1 aSidney, Stephen1 aSims, Mario1 aSmith, Blair, H1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aTan, Nicholas1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aUitterlinden, André, G1 avan Heemst, Diana1 aVuckovic, Dragana1 aWaldenberger, Melanie1 aWang, Lihua1 aWang, Yujie1 aWang, Zhe1 aBin Wei, Wen1 aWilliams, Christine1 aWilson, Gregory1 aWojczynski, Mary, K1 aYao, Jie1 aYu, Bing1 aYu, Caizheng1 aYuan, Jian-Min1 aZhao, Wei1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aDeary, Ian, J1 aEsko, Tõnu1 aFarrall, Martin1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aHorta, Bernardo, L1 aKamatani, Yoichiro1 aKato, Norihiro1 aKooner, Jaspal, S1 aLaakso, Markku1 aLeander, Karin1 aLehtimäki, Terho1 aMagnusson, Patrik, K E1 aPenninx, Brenda1 aPereira, Alexandre, C1 aRauramaa, Rainer1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWang, Ya, Xing1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aZheng, Wei1 aElliott, Paul1 aNorth, Kari, E1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aLiu, Ching-Ti1 aLiu, Yongmei1 aPsaty, Bruce, M1 aRidker, Paul, M1 avan Dam, Rob, M1 aKardia, Sharon, L R1 aZhu, Xiaofeng1 aRotimi, Charles, N1 aMook-Kanamori, Dennis, O1 aFornage, Myriam1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aLiu, Jingmin1 aRotter, Jerome, I1 aGauderman, James1 aProvince, Michael, A1 aMunroe, Patricia, B1 aRice, Kenneth1 aChasman, Daniel, I1 aCupples, Adrienne, L1 aRao, Dabeeru, C1 aMorrison, Alanna, C1 aInterAct Consortium1 aLifelines Cohort, Groningen, The Netherlands (Lifelines Cohort Study) uhttps://chs-nhlbi.org/node/797011178nas a2203793 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2019 eng d a1546-171800aMulti-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids.0 aMultiancestry genomewide genesmoking interaction study of 387272 c2019 Apr a636-6480 v513 aThe concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
1 aBentley, Amy, R1 aSung, Yun, J1 aBrown, Michael, R1 aWinkler, Thomas, W1 aKraja, Aldi, T1 aNtalla, Ioanna1 aSchwander, Karen1 aChasman, Daniel, I1 aLim, Elise1 aDeng, Xuan1 aGuo, Xiuqing1 aLiu, Jingmin1 aLu, Yingchang1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aHuffman, Jennifer, E1 aMusani, Solomon, K1 aLi, Changwei1 aFeitosa, Mary, F1 aRichard, Melissa, A1 aNoordam, Raymond1 aBaker, Jenna1 aChen, Guanjie1 aAschard, Hugues1 aBartz, Traci, M1 aDing, Jingzhong1 aDorajoo, Rajkumar1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, V1 aTajuddin, Salman, M1 aZhao, Wei1 aGraff, Mariaelisa1 aAlver, Maris1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aEvangelou, Evangelos1 aGao, Chuan1 aGoel, Anuj1 aHagemeijer, Yanick1 aHarris, Sarah, E1 aHartwig, Fernando, P1 aHe, Meian1 aHorimoto, Andrea, R V R1 aHsu, Fang-Chi1 aHung, Yi-Jen1 aJackson, Anne, U1 aKasturiratne, Anuradhani1 aKomulainen, Pirjo1 aKuhnel, Brigitte1 aLeander, Karin1 aLin, Keng-Hung1 aLuan, Jian'an1 aLyytikäinen, Leo-Pekka1 aMatoba, Nana1 aNolte, Ilja, M1 aPietzner, Maik1 aPrins, Bram1 aRiaz, Muhammad1 aRobino, Antonietta1 aSaid, Abdullah1 aSchupf, Nicole1 aScott, Robert, A1 aSofer, Tamar1 aStančáková, Alena1 aTakeuchi, Fumihiko1 aTayo, Bamidele, O1 avan der Most, Peter, J1 aVarga, Tibor, V1 aWang, Tzung-Dau1 aWang, Yajuan1 aWare, Erin, B1 aWen, Wanqing1 aXiang, Yong-Bing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAdeyemo, Adebowale1 aAfaq, Saima1 aAmin, Najaf1 aAmini, Marzyeh1 aArking, Dan, E1 aArzumanyan, Zorayr1 aAung, Tin1 aBallantyne, Christie1 aBarr, Graham1 aBielak, Lawrence, F1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aBroeckel, Ulrich1 aBrown, Morris1 aCade, Brian, E1 aCampbell, Archie1 aCanouil, Mickaël1 aCharumathi, Sabanayagam1 aChen, Yii-Der Ida1 aChristensen, Kaare1 aConcas, Maria, Pina1 aConnell, John, M1 aFuentes, Lisa, de Las1 ade Silva, Janaka1 ade Vries, Paul, S1 aDoumatey, Ayo1 aDuan, Qing1 aEaton, Charles, B1 aEppinga, Ruben, N1 aFaul, Jessica, D1 aFloyd, James, S1 aForouhi, Nita, G1 aForrester, Terrence1 aFriedlander, Yechiel1 aGandin, Ilaria1 aGao, He1 aGhanbari, Mohsen1 aGharib, Sina, A1 aGigante, Bruna1 aGiulianini, Franco1 aGrabe, Hans, J1 aGu, Charles1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHixson, James, E1 aIkram, Arfan, M1 aJia, Yucheng1 aJoehanes, Roby1 aJohnson, Craig1 aJonas, Jost, Bruno1 aJustice, Anne, E1 aKatsuya, Tomohiro1 aKhor, Chiea, Chuen1 aKilpeläinen, Tuomas, O1 aKoh, Woon-Puay1 aKolcic, Ivana1 aKooperberg, Charles1 aKrieger, Jose, E1 aKritchevsky, Stephen, B1 aKubo, Michiaki1 aKuusisto, Johanna1 aLakka, Timo, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLewis, Cora, E1 aLi, Yize1 aLiang, Jingjing1 aLin, Shiow1 aLiu, Ching-Ti1 aLiu, Jianjun1 aLiu, Kiang1 aLoh, Marie1 aLohman, Kurt, K1 aLouie, Tin1 aLuzzi, Anna1 aMägi, Reedik1 aMahajan, Anubha1 aManichaikul, Ani, W1 aMcKenzie, Colin, A1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMilani, Lili1 aMohlke, Karen, L1 aMomozawa, Yukihide1 aMorris, Andrew, P1 aMurray, Alison, D1 aNalls, Mike, A1 aNauck, Matthias1 aNelson, Christopher, P1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPapanicolau, George, J1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aPoulter, Neil1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRenstrom, Frida1 aRice, Treva, K1 aRich, Stephen, S1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRosendaal, Frits, R1 aRudan, Igor1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aScott, William, R1 aSever, Peter1 aShi, Yuan1 aSidney, Stephen1 aSims, Mario1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aStringham, Heather, M1 aTan, Nicholas, Y Q1 aTang, Hua1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aTiemeier, Henning1 aTurner, Stephen, T1 aUitterlinden, André, G1 avan Heemst, Diana1 aWaldenberger, Melanie1 aWang, Heming1 aWang, Lan1 aWang, Lihua1 aBin Wei, Wen1 aWilliams, Christine, A1 aWilson, Gregory1 aWojczynski, Mary, K1 aYao, Jie1 aYoung, Kristin1 aYu, Caizheng1 aYuan, Jian-Min1 aZhou, Jie1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aCooper, Richard, S1 ade Faire, Ulf1 aDeary, Ian, J1 aElliott, Paul1 aEsko, Tõnu1 aFarrall, Martin1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aHorta, Bernardo, L1 aJuang, Jyh-Ming, Jimmy1 aKamatani, Yoichiro1 aKammerer, Candace, M1 aKato, Norihiro1 aKooner, Jaspal, S1 aLaakso, Markku1 aLaurie, Cathy, C1 aLee, I-Te1 aLehtimäki, Terho1 aMagnusson, Patrik, K E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aPereira, Alexandre, C1 aRauramaa, Rainer1 aRedline, Susan1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWang, Jun-Sing1 aWang, Ya, Xing1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aWu, Tangchun1 aZeggini, Eleftheria1 aZheng, Wei1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon, L R1 aLiu, Yongmei1 aPsaty, Bruce, M1 aRidker, Paul, M1 avan Dam, Rob, M1 aMook-Kanamori, Dennis, O1 aFornage, Myriam1 aProvince, Michael, A1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aLoos, Ruth, J F1 aFranceschini, Nora1 aRotter, Jerome, I1 aZhu, Xiaofeng1 aBierut, Laura, J1 aGauderman, James1 aRice, Kenneth1 aMunroe, Patricia, B1 aMorrison, Alanna, C1 aRao, Dabeeru, C1 aRotimi, Charles, N1 aCupples, Adrienne, L1 aCOGENT-Kidney Consortium1 aEPIC-InterAct Consortium1 aUnderstanding Society Scientific Group1 aLifelines Cohort uhttps://chs-nhlbi.org/node/800506391nas a2201909 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2019 eng d a2041-172300aMulti-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.0 aMultiancestry sleepbySNP interaction analysis in 126926 individu c2019 Nov 12 a51210 v103 aBoth short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
1 aNoordam, Raymond1 aBos, Maxime, M1 aWang, Heming1 aWinkler, Thomas, W1 aBentley, Amy, R1 aKilpeläinen, Tuomas, O1 ade Vries, Paul, S1 aSung, Yun, Ju1 aSchwander, Karen1 aCade, Brian, E1 aManning, Alisa1 aAschard, Hugues1 aBrown, Michael, R1 aChen, Han1 aFranceschini, Nora1 aMusani, Solomon, K1 aRichard, Melissa1 aVojinovic, Dina1 aAslibekyan, Stella1 aBartz, Traci, M1 aFuentes, Lisa, de Las1 aFeitosa, Mary1 aHorimoto, Andrea, R1 aIlkov, Marjan1 aKho, Minjung1 aKraja, Aldi1 aLi, Changwei1 aLim, Elise1 aLiu, Yongmei1 aMook-Kanamori, Dennis, O1 aRankinen, Tuomo1 aTajuddin, Salman, M1 avan der Spek, Ashley1 aWang, Zhe1 aMarten, Jonathan1 aLaville, Vincent1 aAlver, Maris1 aEvangelou, Evangelos1 aGraff, Maria, E1 aHe, Meian1 aKuhnel, Brigitte1 aLyytikäinen, Leo-Pekka1 aMarques-Vidal, Pedro1 aNolte, Ilja, M1 aPalmer, Nicholette, D1 aRauramaa, Rainer1 aShu, Xiao-Ou1 aSnieder, Harold1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aAdolfo, Correa1 aBallantyne, Christie1 aBielak, Larry1 aBiermasz, Nienke, R1 aBoerwinkle, Eric1 aDimou, Niki1 aEiriksdottir, Gudny1 aGao, Chuan1 aGharib, Sina, A1 aGottlieb, Daniel, J1 aHaba-Rubio, José1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeinzer, Raphael1 aHixson, James, E1 aHomuth, Georg1 aIkram, Arfan, M1 aKomulainen, Pirjo1 aKrieger, Jose, E1 aLee, Jiwon1 aLiu, Jingmin1 aLohman, Kurt, K1 aLuik, Annemarie, I1 aMägi, Reedik1 aMartin, Lisa, W1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aNalls, Mike, A1 aO'Connell, Jeff1 aPeters, Annette1 aPeyser, Patricia1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRensen, Patrick, C N1 aRice, Treva, K1 aRich, Stephen, S1 aRoenneberg, Till1 aRotter, Jerome, I1 aSchreiner, Pamela, J1 aShikany, James1 aSidney, Stephen, S1 aSims, Mario1 aSitlani, Colleen, M1 aSofer, Tamar1 aStrauch, Konstantin1 aSwertz, Morris, A1 aTaylor, Kent, D1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aVölzke, Henry1 aWaldenberger, Melanie1 aWallance, Robert, B1 aDijk, Ko Willems1 aYu, Caizheng1 aZonderman, Alan, B1 aBecker, Diane, M1 aElliott, Paul1 aEsko, Tõnu1 aGieger, Christian1 aGrabe, Hans, J1 aLakka, Timo, A1 aLehtimäki, Terho1 aNorth, Kari, E1 aPenninx, Brenda, W J H1 aVollenweider, Peter1 aWagenknecht, Lynne, E1 aWu, Tangchun1 aXiang, Yong-Bing1 aZheng, Wei1 aArnett, Donna, K1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon1 aKelly, Tanika, N1 aKritchevsky, Stephen, B1 aLoos, Ruth, J F1 aPereira, Alexandre, C1 aProvince, Mike1 aPsaty, Bruce, M1 aRotimi, Charles1 aZhu, Xiaofeng1 aAmin, Najaf1 aCupples, Adrienne, L1 aFornage, Myriam1 aFox, Ervin, F1 aGuo, Xiuqing1 aGauderman, James1 aRice, Kenneth1 aKooperberg, Charles1 aMunroe, Patricia, B1 aLiu, Ching-Ti1 aMorrison, Alanna, C1 aRao, Dabeeru, C1 avan Heemst, Diana1 aRedline, Susan uhttps://chs-nhlbi.org/node/820202929nas a2200289 4500008004100000022001400041245011200055210006900167260001600236300001200252490000600264520204600270100002602316700002002342700002302362700002002385700001902405700002402424700002502448700002002473700001702493700002802510700002302538700002402561700001802585856003602603 2020 eng d a2574-380500aAssociation of Leukocyte Telomere Length With Mortality Among Adult Participants in 3 Longitudinal Studies.0 aAssociation of Leukocyte Telomere Length With Mortality Among Ad c2020 Feb 05 ae2000230 v33 aImportance: Leukocyte telomere length (LTL) is a trait associated with risk of cardiovascular disease and cancer, the 2 major disease categories that largely define longevity in the United States. However, it remains unclear whether LTL is associated with the human life span.
Objective: To examine whether LTL is associated with the life span of contemporary humans.
Design, Setting, and Participants: This cohort study included 3259 adults of European ancestry from the Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), and Women's Health Initiative (WHI). Leukocyte telomere length was measured in 1992 and 1997 in the CHS, from 1995 to 1998 in the FHS, and from 1993 to 1998 in the WHI. Data analysis was conducted from February 2017 to December 2019.
Main Outcomes and Measures: Death and LTL, measured by Southern blots of the terminal restriction fragments, were the main outcomes. Cause of death was adjudicated by end point committees.
Results: The analyzed sample included 3259 participants (2342 [71.9%] women), with a median (range) age of 69.0 (50.0-98.0) years at blood collection. The median (range) follow-up until death was 10.9 (0.2-23.0) years in CHS, 19.7 (3.4-23.0) years in FHS, and 16.6 (0.5-20.0) years in WHI. During follow-up, there were 1525 deaths (482 [31.6%] of cardiovascular disease; 373 [24.5%] of cancer, and 670 [43.9%] of other or unknown causes). Short LTL, expressed in residual LTL, was associated with increased mortality risk. Overall, the hazard ratio for all-cause mortality for a 1-kilobase decrease in LTL was 1.34 (95% CI, 1.21-1.47). This association was stronger for noncancer causes of death (cardiovascular death: hazard ratio, 1.28; 95% CI, 1.08-1.52; cancer: hazard ratio, 1.13; 95% CI, 0.93-1.36; and other causes: hazard ratio, 1.53; 95% CI, 1.32-1.77).
Conclusions and Relevance: The results of this study indicate that LTL is associated with a natural life span limit in contemporary humans.
1 aArbeev, Konstantin, G1 aVerhulst, Simon1 aSteenstrup, Troels1 aKark, Jeremy, D1 aBagley, Olivia1 aKooperberg, Charles1 aReiner, Alexander, P1 aHwang, Shih-Jen1 aLevy, Daniel1 aFitzpatrick, Annette, L1 aChristensen, Kaare1 aYashin, Anatoliy, I1 aAviv, Abraham uhttps://chs-nhlbi.org/node/828206570nas a2201753 4500008004100000022001400041245007100055210006900126260001200195300001200207490000800219520164100227100002301868700002501891700002601916700002201942700001701964700002401981700002002005700001902025700002602044700001902070700001602089700002002105700002902125700002702154700001602181700002202197700002002219700002002239700002502259700002402284700001902308700002002327700001902347700002002366700002402386700002002410700002602430700002702456700002502483700002402508700001402532700002202546700002302568700002102591700002302612700001902635700002302654700001702677700002302694700001802717700002102735700001902756700002302775700002502798700002202823700002402845700002402869700001902893700002702912700001902939700001702958700002202975700001902997700002103016700001903037700002203056700001903078700001903097700002003116700002203136700002203158700002503180700001903205700002103224700002303245700002103268700002303289700002303312700002203335700001903357700001803376700002203394700002103416700002203437700002103459700002103480700002003501700001903521700002003540700002203560700001803582700002203600700002003622700001703642700001703659700001603676700001503692700002703707700002303734700001703757700002403774700002103798700002003819700002103839700002403860700002503884700002403909700002303933700002503956700002303981700002104004700001904025700002004044700001904064700002804083700001804111700002104129700002104150700002304171700001804194700002004212700002304232700001804255700002404273700002104297700002504318700002104343700001704364700001704381700001804398700002104416700002204437700002104459700001704480700002204497700002004519700002304539700002304562700002504585700002404610700002204634700002304656700002204679700002304701710005604724856003604780 2020 eng d a1476-468700aInherited causes of clonal haematopoiesis in 97,691 whole genomes.0 aInherited causes of clonal haematopoiesis in 97691 whole genomes c2020 10 a763-7680 v5863 aAge is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.
1 aBick, Alexander, G1 aWeinstock, Joshua, S1 aNandakumar, Satish, K1 aFulco, Charles, P1 aBao, Erik, L1 aZekavat, Seyedeh, M1 aSzeto, Mindy, D1 aLiao, Xiaotian1 aLeventhal, Matthew, J1 aNasser, Joseph1 aChang, Kyle1 aLaurie, Cecelia1 aBurugula, Bala, Bharathi1 aGibson, Christopher, J1 aLin, Amy, E1 aTaub, Margaret, A1 aAguet, Francois1 aArdlie, Kristin1 aMitchell, Braxton, D1 aBarnes, Kathleen, C1 aMoscati, Arden1 aFornage, Myriam1 aRedline, Susan1 aPsaty, Bruce, M1 aSilverman, Edwin, K1 aWeiss, Scott, T1 aPalmer, Nicholette, D1 aVasan, Ramachandran, S1 aBurchard, Esteban, G1 aKardia, Sharon, L R1 aHe, Jiang1 aKaplan, Robert, C1 aSmith, Nicholas, L1 aArnett, Donna, K1 aSchwartz, David, A1 aCorrea, Adolfo1 ade Andrade, Mariza1 aGuo, Xiuqing1 aKonkle, Barbara, A1 aCuster, Brian1 aPeralta, Juan, M1 aGui, Hongsheng1 aMeyers, Deborah, A1 aMcGarvey, Stephen, T1 aChen, Ida Yii-Der1 aShoemaker, Benjamin1 aPeyser, Patricia, A1 aBroome, Jai, G1 aGogarten, Stephanie, M1 aWang, Fei, Fei1 aWong, Quenna1 aMontasser, May, E1 aDaya, Michelle1 aKenny, Eimear, E1 aNorth, Kari, E1 aLauner, Lenore, J1 aCade, Brian, E1 aBis, Joshua, C1 aCho, Michael, H1 aLasky-Su, Jessica1 aBowden, Donald, W1 aCupples, Adrienne, L1 aC Y Mak, Angel1 aBecker, Lewis, C1 aSmith, Jennifer, A1 aKelly, Tanika, N1 aAslibekyan, Stella1 aHeckbert, Susan, R1 aTiwari, Hemant, K1 aYang, Ivana, V1 aHeit, John, A1 aLubitz, Steven, A1 aJohnsen, Jill, M1 aCurran, Joanne, E1 aWenzel, Sally, E1 aWeeks, Daniel, E1 aRao, Dabeeru, C1 aDarbar, Dawood1 aMoon, Jee-Young1 aTracy, Russell, P1 aButh, Erin, J1 aRafaels, Nicholas1 aLoos, Ruth, J F1 aDurda, Peter1 aLiu, Yongmei1 aHou, Lifang1 aLee, Jiwon1 aKachroo, Priyadarshini1 aFreedman, Barry, I1 aLevy, Daniel1 aBielak, Lawrence, F1 aHixson, James, E1 aFloyd, James, S1 aWhitsel, Eric, A1 aEllinor, Patrick, T1 aIrvin, Marguerite, R1 aFingerlin, Tasha, E1 aRaffield, Laura, M1 aArmasu, Sebastian, M1 aWheeler, Marsha, M1 aSabino, Ester, C1 aBlangero, John1 aWilliams, Keoki1 aLevy, Bruce, D1 aSheu, Wayne, Huey-Herng1 aRoden, Dan, M1 aBoerwinkle, Eric1 aManson, JoAnn, E1 aMathias, Rasika, A1 aDesai, Pinkal1 aTaylor, Kent, D1 aJohnson, Andrew, D1 aAuer, Paul, L1 aKooperberg, Charles1 aLaurie, Cathy, C1 aBlackwell, Thomas, W1 aSmith, Albert, V1 aZhao, Hongyu1 aLange, Ethan1 aLange, Leslie1 aRich, Stephen, S1 aRotter, Jerome, I1 aWilson, James, G1 aScheet, Paul1 aKitzman, Jacob, O1 aLander, Eric, S1 aEngreitz, Jesse, M1 aEbert, Benjamin, L1 aReiner, Alexander, P1 aJaiswal, Siddhartha1 aAbecasis, Goncalo1 aSankaran, Vijay, G1 aKathiresan, Sekar1 aNatarajan, Pradeep1 aNHLBI Trans-Omics for Precision Medicine Consortium uhttps://chs-nhlbi.org/node/862107958nas a2202377 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2020 eng d a2041-172300aMulti-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.0 aMultiancestry GWAS of the electrocardiographic PR interval ident c2020 May 21 a25420 v113 aThe electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
1 aNtalla, Ioanna1 aWeng, Lu-Chen1 aCartwright, James, H1 aHall, Amelia, Weber1 aSveinbjornsson, Gardar1 aTucker, Nathan, R1 aChoi, Seung, Hoan1 aChaffin, Mark, D1 aRoselli, Carolina1 aBarnes, Michael, R1 aMifsud, Borbala1 aWarren, Helen, R1 aHayward, Caroline1 aMarten, Jonathan1 aCranley, James, J1 aConcas, Maria, Pina1 aGasparini, Paolo1 aBoutin, Thibaud1 aKolcic, Ivana1 aPolasek, Ozren1 aRudan, Igor1 aAraujo, Nathalia, M1 aLima-Costa, Maria, Fernanda1 aRibeiro, Antonio, Luiz P1 aSouza, Renan, P1 aTarazona-Santos, Eduardo1 aGiedraitis, Vilmantas1 aIngelsson, Erik1 aMahajan, Anubha1 aMorris, Andrew, P1 aM, Fabiola, del Greco1 aFoco, Luisa1 aGögele, Martin1 aHicks, Andrew, A1 aCook, James, P1 aLind, Lars1 aLindgren, Cecilia, M1 aSundström, Johan1 aNelson, Christopher, P1 aRiaz, Muhammad, B1 aSamani, Nilesh, J1 aSinagra, Gianfranco1 aUlivi, Sheila1 aKähönen, Mika1 aMishra, Pashupati, P1 aMononen, Nina1 aNikus, Kjell1 aCaulfield, Mark, J1 aDominiczak, Anna1 aPadmanabhan, Sandosh1 aMontasser, May, E1 aO'Connell, Jeff, R1 aRyan, Kathleen1 aShuldiner, Alan, R1 aAeschbacher, Stefanie1 aConen, David1 aRisch, Lorenz1 aThériault, Sébastien1 aHutri-Kähönen, Nina1 aLehtimäki, Terho1 aLyytikäinen, Leo-Pekka1 aRaitakari, Olli, T1 aBarnes, Catriona, L K1 aCampbell, Harry1 aJoshi, Peter, K1 aWilson, James, F1 aIsaacs, Aaron1 aKors, Jan, A1 aDuijn, Cornelia, M1 aHuang, Paul, L1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aLauner, Lenore, J1 aSmith, Albert, V1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aNadkarni, Girish, N1 aPreuss, Michael, H1 aCorrea, Adolfo1 aMei, Hao1 aWilson, James1 aMeitinger, Thomas1 aMüller-Nurasyid, Martina1 aPeters, Annette1 aWaldenberger, Melanie1 aMangino, Massimo1 aSpector, Timothy, D1 aRienstra, Michiel1 avan de Vegte, Yordi, J1 aHarst, Pim1 aVerweij, Niek1 aKääb, Stefan1 aSchramm, Katharina1 aSinner, Moritz, F1 aStrauch, Konstantin1 aCutler, Michael, J1 aFatkin, Diane1 aLondon, Barry1 aOlesen, Morten1 aRoden, Dan, M1 aShoemaker, Benjamin1 aSmith, Gustav1 aBiggs, Mary, L1 aBis, Joshua, C1 aBrody, Jennifer, A1 aPsaty, Bruce, M1 aRice, Kenneth1 aSotoodehnia, Nona1 aDe Grandi, Alessandro1 aFuchsberger, Christian1 aPattaro, Cristian1 aPramstaller, Peter, P1 aFord, Ian1 aJukema, Wouter1 aMacfarlane, Peter, W1 aTrompet, Stella1 aDörr, Marcus1 aFelix, Stephan, B1 aVölker, Uwe1 aWeiss, Stefan1 aHavulinna, Aki, S1 aJula, Antti1 aSääksjärvi, Katri1 aSalomaa, Veikko1 aGuo, Xiuqing1 aHeckbert, Susan, R1 aLin, Henry, J1 aRotter, Jerome, I1 aTaylor, Kent, D1 aYao, Jie1 ade Mutsert, Renée1 aMaan, Arie, C1 aMook-Kanamori, Dennis, O1 aNoordam, Raymond1 aCucca, Francesco1 aDing, Jun1 aLakatta, Edward, G1 aQian, Yong1 aTarasov, Kirill, V1 aLevy, Daniel1 aLin, Honghuang1 aNewton-Cheh, Christopher, H1 aLunetta, Kathryn, L1 aMurray, Alison, D1 aPorteous, David, J1 aSmith, Blair, H1 aStricker, Bruno, H1 aUitterlinden, Andre1 avan den Berg, Marten, E1 aHaessler, Jeffrey1 aJackson, Rebecca, D1 aKooperberg, Charles1 aPeters, Ulrike1 aReiner, Alexander, P1 aWhitsel, Eric, A1 aAlonso, Alvaro1 aArking, Dan, E1 aBoerwinkle, Eric1 aEhret, Georg, B1 aSoliman, Elsayed, Z1 aAvery, Christy, L1 aGogarten, Stephanie, M1 aKerr, Kathleen, F1 aLaurie, Cathy, C1 aSeyerle, Amanda, A1 aStilp, Adrienne1 aAssa, Solmaz1 aSaid, Abdullah1 avan der Ende, Yldau1 aLambiase, Pier, D1 aOrini, Michele1 aRamirez, Julia1 aVan Duijvenboden, Stefan1 aArnar, David, O1 aGudbjartsson, Daniel, F1 aHolm, Hilma1 aSulem, Patrick1 aThorleifsson, Gudmar1 aThorolfsdottir, Rosa, B1 aThorsteinsdottir, Unnur1 aBenjamin, Emelia, J1 aTinker, Andrew1 aStefansson, Kari1 aEllinor, Patrick, T1 aJamshidi, Yalda1 aLubitz, Steven, A1 aMunroe, Patricia, B uhttps://chs-nhlbi.org/node/836803741nas a2200625 4500008004100000022001400041245009700055210006900152260001300221300001200234490000700246520194400253100001402197700001402211700002002225700002402245700002302269700002102292700002302313700001702336700001502353700002102368700002402389700001702413700001602430700002502446700002202471700002202493700001502515700002402530700002002554700002002574700002102594700002502615700002002640700002402660700002302684700002602707700001302733700001402746700002002760700002402780700002402804700001802828700002902846700002502875700002002900700001902920700002002939700002202959700002102981700002403002710005303026856003603079 2020 eng d a2574-830000aRole of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.0 aRole of Rare and LowFrequency Variants in GeneAlcohol Interactio c2020 Aug ae0027720 v133 aBACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.
METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.
RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .
CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.
1 aWang, Zhe1 aChen, Han1 aBartz, Traci, M1 aBielak, Lawrence, F1 aChasman, Daniel, I1 aFeitosa, Mary, F1 aFranceschini, Nora1 aGuo, Xiuqing1 aLim, Elise1 aNoordam, Raymond1 aRichard, Melissa, A1 aWang, Heming1 aCade, Brian1 aCupples, Adrienne, L1 ade Vries, Paul, S1 aGiulanini, Franco1 aLee, Jiwon1 aLemaitre, Rozenn, N1 aMartin, Lisa, W1 aReiner, Alex, P1 aRich, Stephen, S1 aSchreiner, Pamela, J1 aSidney, Stephen1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 avan Dijk, Ko, Willems1 aYao, Jie1 aZhao, Wei1 aFornage, Myriam1 aKardia, Sharon, L R1 aKooperberg, Charles1 aLiu, Ching-Ti1 aMook-Kanamori, Dennis, O1 aProvince, Michael, A1 aPsaty, Bruce, M1 aRedline, Susan1 aRidker, Paul, M1 aRotter, Jerome, I1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aCHARGE Gene-Lifestyle Interactions Working Group uhttps://chs-nhlbi.org/node/840703306nas a2200565 4500008004100000022001400041245014400055210006900199260001600268490000600284520159100290100001701881700001501898700002501913700001701938700002301955700002701978700002402005700001702029700001202046700002402058700002202082700002702104700002502131700002402156700002002180700002002200700001402220700002602234700001502260700002402275700002002299700002002319700002202339700002002361700002102381700001702402700002102419700002402440700002102464700002302485700002102508700002002529700001902549700002302568700002102591700002702612710006502639856003602704 2021 eng d a2666-247700aBinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.0 aBinomiRare A robust test for association of a rare genetic varia c2021 Jul 080 v23 aWhole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.
1 aSofer, Tamar1 aLee, Jiwon1 aKurniansyah, Nuzulul1 aJain, Deepti1 aLaurie, Cecelia, A1 aGogarten, Stephanie, M1 aConomos, Matthew, P1 aHeavner, Ben1 aHu, Yao1 aKooperberg, Charles1 aHaessler, Jeffrey1 aVasan, Ramachandran, S1 aCupples, Adrienne, L1 aCoombes, Brandon, J1 aSeyerle, Amanda1 aGharib, Sina, A1 aChen, Han1 aO'Connell, Jeffrey, R1 aZhang, Man1 aGottlieb, Daniel, J1 aPsaty, Bruce, M1 aLongstreth, W T1 aRotter, Jerome, I1 aTaylor, Kent, D1 aRich, Stephen, S1 aGuo, Xiuqing1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aPankow, James, S1 aJohnson, Andrew, D1 aPankratz, Nathan1 aReiner, Alex, P1 aRedline, Susan1 aSmith, Nicholas, L1 aRice, Kenneth, M1 aSchifano, Elizabeth, D1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883805153nas a2201369 4500008004100000022001400041245011700055210006900172260001500241300000900256490000700265520124400272100002301516700001901539700002101558700002701579700002001606700002201626700001901648700002601667700002601693700002001719700002001739700002301759700003001782700001901812700002301831700002901854700002801883700002401911700001901935700001901954700001201973700002401985700002102009700001702030700002502047700001902072700001802091700001502109700002402124700002002148700002002168700002202188700002002210700001702230700002602247700002602273700002102299700002402320700002302344700001802367700001902385700002102404700001902425700002102444700002202465700002102487700002102508700001902529700002102548700002202569700002002591700002102611700002002632700001902652700002202671700001802693700002202711700002402733700002002757700002302777700002002800700001802820700002202838700001402860700002002874700002002894700002202914700002402936700001802960700001702978700002402995700002103019700001803040700002403058700002003082700002203102700002303124700003003147700002503177700002503202700002603227700001903253700001903272700002103291700002003312700001403332700001903346700002503365700001703390700001903407700002103426700002203447700002703469700002203496700002503518700002203543700002403565700002103589700002003610700002003630700002003650710006503670710001203735856003603747 2021 eng d a2041-172300aChromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.0 aChromosome Xq23 is associated with lower atherogenic lipid conce c2021 04 12 a21820 v123 aAutosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
1 aNatarajan, Pradeep1 aPampana, Akhil1 aGraham, Sarah, E1 aRuotsalainen, Sanni, E1 aPerry, James, A1 ade Vries, Paul, S1 aBroome, Jai, G1 aPirruccello, James, P1 aHonigberg, Michael, C1 aAragam, Krishna1 aWolford, Brooke1 aBrody, Jennifer, A1 aAntonacci-Fulton, Lucinda1 aArden, Moscati1 aAslibekyan, Stella1 aAssimes, Themistocles, L1 aBallantyne, Christie, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aDo, Ron1 aDoddapaneni, Harsha1 aEmery, Leslie, S1 aHung, Yi-Jen1 aIrvin, Marguerite, R1 aKhan, Alyna, T1 aLange, Leslie1 aLee, Jiwon1 aLemaitre, Rozenn, N1 aMartin, Lisa, W1 aMetcalf, Ginger1 aMontasser, May, E1 aMoon, Jee-Young1 aMuzny, Donna1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aStilp, Adrienne, M1 aTsai, Michael1 aWang, Fei, Fei1 aWeeks, Daniel, E1 aYanek, Lisa, R1 aWilson, James, G1 aAbecasis, Goncalo1 aArnett, Donna, K1 aBecker, Lewis, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aChoi, Won, Jung1 aCorrea, Adolfo1 aCurran, Joanne, E1 aDaly, Mark, J1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aFornage, Myriam1 aFreedman, Barry, I1 aGabriel, Stacey1 aGermer, Soren1 aGibbs, Richard, A1 aHe, Jiang1 aHveem, Kristian1 aJarvik, Gail, P1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKenny, Eimear1 aKim, Ryan, W1 aKooperberg, Charles1 aLaurie, Cathy, C1 aLee, Seonwook1 aLloyd-Jones, Don, M1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aMathias, Rasika, A1 aMartinez, Karine, A Viaud1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aNickerson, Deborah, A1 aNorth, Kari, E1 aPalotie, Aarno1 aPark, Cheol, Joo1 aPsaty, Bruce, M1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSmith, Albert, V1 aTracy, Russell, P1 aVasan, Ramachandran, S1 aKathiresan, Sekar1 aCupples, Adrienne, L1 aRotter, Jerome, I1 aMorrison, Alanna, C1 aRich, Stephen, S1 aRipatti, Samuli1 aWiller, Cristen1 aPeloso, Gina, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aFinnGen uhttps://chs-nhlbi.org/node/871109591nas a2202833 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2021 eng d a1537-660500aDiscovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.0 aDiscovery and finemapping of height loci via highdensity imputat c2021 Apr 01 a564-5820 v1083 aAlthough many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
1 aGraff, Mariaelisa1 aJustice, Anne, E1 aYoung, Kristin, L1 aMarouli, Eirini1 aZhang, Xinruo1 aFine, Rebecca, S1 aLim, Elise1 aBuchanan, Victoria1 aRand, Kristin1 aFeitosa, Mary, F1 aWojczynski, Mary, K1 aYanek, Lisa, R1 aShao, Yaming1 aRohde, Rebecca1 aAdeyemo, Adebowale, A1 aAldrich, Melinda, C1 aAllison, Matthew, A1 aAmbrosone, Christine, B1 aAmbs, Stefan1 aAmos, Christopher1 aArnett, Donna, K1 aAtwood, Larry1 aBandera, Elisa, V1 aBartz, Traci1 aBecker, Diane, M1 aBerndt, Sonja, I1 aBernstein, Leslie1 aBielak, Lawrence, F1 aBlot, William, J1 aBottinger, Erwin, P1 aBowden, Donald, W1 aBradfield, Jonathan, P1 aBrody, Jennifer, A1 aBroeckel, Ulrich1 aBurke, Gregory1 aCade, Brian, E1 aCai, Qiuyin1 aCaporaso, Neil1 aCarlson, Chris1 aCarpten, John1 aCasey, Graham1 aChanock, Stephen, J1 aChen, Guanjie1 aChen, Minhui1 aChen, Yii-der, I1 aChen, Wei-Min1 aChesi, Alessandra1 aChiang, Charleston, W K1 aChu, Lisa1 aCoetzee, Gerry, A1 aConti, David, V1 aCooper, Richard, S1 aCushman, Mary1 aDemerath, Ellen1 aDeming, Sandra, L1 aDimitrov, Latchezar1 aDing, Jingzhong1 aDiver, Ryan1 aDuan, Qing1 aEvans, Michele, K1 aFalusi, Adeyinka, G1 aFaul, Jessica, D1 aFornage, Myriam1 aFox, Caroline1 aFreedman, Barry, I1 aGarcia, Melissa1 aGillanders, Elizabeth, M1 aGoodman, Phyllis1 aGottesman, Omri1 aGrant, Struan, F A1 aGuo, Xiuqing1 aHakonarson, Hakon1 aHaritunians, Talin1 aHarris, Tamara, B1 aHarris, Curtis, C1 aHenderson, Brian, E1 aHennis, Anselm1 aHernandez, Dena, G1 aHirschhorn, Joel, N1 aMcNeill, Lorna, Haughton1 aHoward, Timothy, D1 aHoward, Barbara1 aHsing, Ann, W1 aHsu, Yu-Han, H1 aHu, Jennifer, J1 aHuff, Chad, D1 aHuo, Dezheng1 aIngles, Sue, A1 aIrvin, Marguerite, R1 aJohn, Esther, M1 aJohnson, Karen, C1 aJordan, Joanne, M1 aKabagambe, Edmond, K1 aKang, Sun, J1 aKardia, Sharon, L1 aKeating, Brendan, J1 aKittles, Rick, A1 aKlein, Eric, A1 aKolb, Suzanne1 aKolonel, Laurence, N1 aKooperberg, Charles1 aKuller, Lewis1 aKutlar, Abdullah1 aLange, Leslie1 aLangefeld, Carl, D1 aLe Marchand, Loïc1 aLeonard, Hampton1 aLettre, Guillaume1 aLevin, Albert, M1 aLi, Yun1 aLi, Jin1 aLiu, Yongmei1 aLiu, Youfang1 aLiu, Simin1 aLohman, Kurt1 aLotay, Vaneet1 aLu, Yingchang1 aMaixner, William1 aManson, JoAnn, E1 aMcKnight, Barbara1 aMeng, Yan1 aMonda, Keri, L1 aMonroe, Kris1 aMoore, Jason, H1 aMosley, Thomas, H1 aMudgal, Poorva1 aMurphy, Adam, B1 aNadukuru, Raj1 aNalls, Mike, A1 aNathanson, Katherine, L1 aNayak, Uma1 aN'diaye, Amidou1 aNemesure, Barbara1 aNeslund-Dudas, Christine1 aNeuhouser, Marian, L1 aNyante, Sarah1 aOchs-Balcom, Heather1 aOgundiran, Temidayo, O1 aOgunniyi, Adesola1 aOjengbede, Oladosu1 aOkut, Hayrettin1 aOlopade, Olufunmilayo, I1 aOlshan, Andrew1 aPadhukasahasram, Badri1 aPalmer, Julie1 aPalmer, Cameron, D1 aPalmer, Nicholette, D1 aPapanicolaou, George1 aPatel, Sanjay, R1 aPettaway, Curtis, A1 aPeyser, Patricia, A1 aPress, Michael, F1 aRao, D, C1 aRasmussen-Torvik, Laura, J1 aRedline, Susan1 aReiner, Alex, P1 aRhie, Suhn, K1 aRodriguez-Gil, Jorge, L1 aRotimi, Charles, N1 aRotter, Jerome, I1 aRuiz-Narvaez, Edward, A1 aRybicki, Benjamin, A1 aSalako, Babatunde1 aSale, Michèle, M1 aSanderson, Maureen1 aSchadt, Eric1 aSchreiner, Pamela, J1 aSchurmann, Claudia1 aSchwartz, Ann, G1 aShriner, Daniel, A1 aSignorello, Lisa, B1 aSingleton, Andrew, B1 aSiscovick, David, S1 aSmith, Jennifer, A1 aSmith, Shad1 aSpeliotes, Elizabeth1 aSpitz, Margaret1 aStanford, Janet, L1 aStevens, Victoria, L1 aStram, Alex1 aStrom, Sara, S1 aSucheston, Lara1 aSun, Yan, V1 aTajuddin, Salman, M1 aTaylor, Herman1 aTaylor, Kira1 aTayo, Bamidele, O1 aThun, Michael, J1 aTucker, Margaret, A1 aVaidya, Dhananjay1 aVan Den Berg, David, J1 aVedantam, Sailaja1 aVitolins, Mara1 aWang, Zhaoming1 aWare, Erin, B1 aWassertheil-Smoller, Sylvia1 aWeir, David, R1 aWiencke, John, K1 aWilliams, Scott, M1 aWilliams, Keoki1 aWilson, James, G1 aWitte, John, S1 aWrensch, Margaret1 aWu, Xifeng1 aYao, Jie1 aZakai, Neil1 aZanetti, Krista1 aZemel, Babette, S1 aZhao, Wei1 aZhao, Jing Hua1 aZheng, Wei1 aZhi, Degui1 aZhou, Jie1 aZhu, Xiaofeng1 aZiegler, Regina, G1 aZmuda, Joe1 aZonderman, Alan, B1 aPsaty, Bruce, M1 aBorecki, Ingrid, B1 aCupples, Adrienne, L1 aLiu, Ching-Ti1 aHaiman, Christopher, A1 aLoos, Ruth1 aC Y Ng, Maggie1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/870511212nas a2203445 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2021 eng d a1476-468700aGenetic insights into biological mechanisms governing human ovarian ageing.0 aGenetic insights into biological mechanisms governing human ovar c2021 Aug a393-3970 v5963 aReproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
1 aRuth, Katherine, S1 aDay, Felix, R1 aHussain, Jazib1 aMartínez-Marchal, Ana1 aAiken, Catherine, E1 aAzad, Ajuna1 aThompson, Deborah, J1 aKnoblochova, Lucie1 aAbe, Hironori1 aTarry-Adkins, Jane, L1 aGonzalez, Javier, Martin1 aFontanillas, Pierre1 aClaringbould, Annique1 aBakker, Olivier, B1 aSulem, Patrick1 aWalters, Robin, G1 aTerao, Chikashi1 aTuron, Sandra1 aHorikoshi, Momoko1 aLin, Kuang1 aOnland-Moret, Charlotte, N1 aSankar, Aditya1 aHertz, Emil, Peter Thra1 aTimshel, Pascal, N1 aShukla, Vallari1 aBorup, Rehannah1 aOlsen, Kristina, W1 aAguilera, Paula1 aFerrer-Roda, Mònica1 aHuang, Yan1 aStankovic, Stasa1 aTimmers, Paul, R H J1 aAhearn, Thomas, U1 aAlizadeh, Behrooz, Z1 aNaderi, Elnaz1 aAndrulis, Irene, L1 aArnold, Alice, M1 aAronson, Kristan, J1 aAugustinsson, Annelie1 aBandinelli, Stefania1 aBarbieri, Caterina, M1 aBeaumont, Robin, N1 aBecher, Heiko1 aBeckmann, Matthias, W1 aBenonisdottir, Stefania1 aBergmann, Sven1 aBochud, Murielle1 aBoerwinkle, Eric1 aBojesen, Stig, E1 aBolla, Manjeet, K1 aBoomsma, Dorret, I1 aBowker, Nicholas1 aBrody, Jennifer, A1 aBroer, Linda1 aBuring, Julie, E1 aCampbell, Archie1 aCampbell, Harry1 aCastelao, Jose, E1 aCatamo, Eulalia1 aChanock, Stephen, J1 aChenevix-Trench, Georgia1 aCiullo, Marina1 aCorre, Tanguy1 aCouch, Fergus, J1 aCox, Angela1 aCrisponi, Laura1 aCross, Simon, S1 aCucca, Francesco1 aCzene, Kamila1 aSmith, George Davey1 ade Geus, Eco, J C N1 ade Mutsert, Renée1 aDe Vivo, Immaculata1 aDemerath, Ellen, W1 aDennis, Joe1 aDunning, Alison, M1 aDwek, Miriam1 aEriksson, Mikael1 aEsko, Tõnu1 aFasching, Peter, A1 aFaul, Jessica, D1 aFerrucci, Luigi1 aFranceschini, Nora1 aFrayling, Timothy, M1 aGago-Dominguez, Manuela1 aMezzavilla, Massimo1 aGarcía-Closas, Montserrat1 aGieger, Christian1 aGiles, Graham, G1 aGrallert, Harald1 aGudbjartsson, Daniel, F1 aGudnason, Vilmundur1 aGuénel, Pascal1 aHaiman, Christopher, A1 aHåkansson, Niclas1 aHall, Per1 aHayward, Caroline1 aHe, Chunyan1 aHe, Wei1 aHeiss, Gerardo1 aHøffding, Miya, K1 aHopper, John, L1 aHottenga, Jouke, J1 aHu, Frank1 aHunter, David1 aIkram, Mohammad, A1 aJackson, Rebecca, D1 aJoaquim, Micaella, D R1 aJohn, Esther, M1 aJoshi, Peter, K1 aKarasik, David1 aKardia, Sharon, L R1 aKartsonaki, Christiana1 aKarlsson, Robert1 aKitahara, Cari, M1 aKolcic, Ivana1 aKooperberg, Charles1 aKraft, Peter1 aKurian, Allison, W1 aKutalik, Zoltán1 aLa Bianca, Martina1 aLachance, Genevieve1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLaven, Joop, S E1 aLawlor, Deborah, A1 aLe Marchand, Loïc1 aLi, Jingmei1 aLindblom, Annika1 aLindström, Sara1 aLindstrom, Tricia1 aLinet, Martha1 aLiu, Yongmei1 aLiu, Simin1 aLuan, Jian'an1 aMägi, Reedik1 aMagnusson, Patrik, K E1 aMangino, Massimo1 aMannermaa, Arto1 aMarco, Brumat1 aMarten, Jonathan1 aMartin, Nicholas, G1 aMbarek, Hamdi1 aMcKnight, Barbara1 aMedland, Sarah, E1 aMeisinger, Christa1 aMeitinger, Thomas1 aMenni, Cristina1 aMetspalu, Andres1 aMilani, Lili1 aMilne, Roger, L1 aMontgomery, Grant, W1 aMook-Kanamori, Dennis, O1 aMulas, Antonella1 aMulligan, Anna, M1 aMurray, Alison1 aNalls, Mike, A1 aNewman, Anne1 aNoordam, Raymond1 aNutile, Teresa1 aNyholt, Dale, R1 aOlshan, Andrew, F1 aOlsson, Håkan1 aPainter, Jodie, N1 aPatel, Alpa, V1 aPedersen, Nancy, L1 aPerjakova, Natalia1 aPeters, Annette1 aPeters, Ulrike1 aPharoah, Paul, D P1 aPolasek, Ozren1 aPorcu, Eleonora1 aPsaty, Bruce, M1 aRahman, Iffat1 aRennert, Gad1 aRennert, Hedy, S1 aRidker, Paul, M1 aRing, Susan, M1 aRobino, Antonietta1 aRose, Lynda, M1 aRosendaal, Frits, R1 aRossouw, Jacques1 aRudan, Igor1 aRueedi, Rico1 aRuggiero, Daniela1 aSala, Cinzia, F1 aSaloustros, Emmanouil1 aSandler, Dale, P1 aSanna, Serena1 aSawyer, Elinor, J1 aSarnowski, Chloe1 aSchlessinger, David1 aSchmidt, Marjanka, K1 aSchoemaker, Minouk, J1 aSchraut, Katharina, E1 aScott, Christopher1 aShekari, Saleh1 aShrikhande, Amruta1 aSmith, Albert, V1 aSmith, Blair, H1 aSmith, Jennifer, A1 aSorice, Rossella1 aSouthey, Melissa, C1 aSpector, Tim, D1 aSpinelli, John, J1 aStampfer, Meir1 aStöckl, Doris1 avan Meurs, Joyce, B J1 aStrauch, Konstantin1 aStyrkarsdottir, Unnur1 aSwerdlow, Anthony, J1 aTanaka, Toshiko1 aTeras, Lauren, R1 aTeumer, Alexander1 aÞorsteinsdottir, Unnur1 aTimpson, Nicholas, J1 aToniolo, Daniela1 aTraglia, Michela1 aTroester, Melissa, A1 aTruong, Thérèse1 aTyrrell, Jessica1 aUitterlinden, André, G1 aUlivi, Sheila1 aVachon, Celine, M1 aVitart, Veronique1 aVölker, Uwe1 aVollenweider, Peter1 aVölzke, Henry1 aWang, Qin1 aWareham, Nicholas, J1 aWeinberg, Clarice, R1 aWeir, David, R1 aWilcox, Amber, N1 aDijk, Ko Willems1 aWillemsen, Gonneke1 aWilson, James, F1 aWolffenbuttel, Bruce, H R1 aWolk, Alicja1 aWood, Andrew, R1 aZhao, Wei1 aZygmunt, Marek1 aChen, Zhengming1 aLi, Liming1 aFranke, Lude1 aBurgess, Stephen1 aDeelen, Patrick1 aPers, Tune, H1 aGrøndahl, Marie, Louise1 aAndersen, Claus, Yding1 aPujol, Anna1 aLopez-Contreras, Andres, J1 aDaniel, Jeremy, A1 aStefansson, Kari1 aChang-Claude, Jenny1 aSchouw, Yvonne, T1 aLunetta, Kathryn, L1 aChasman, Daniel, I1 aEaston, Douglas, F1 aVisser, Jenny, A1 aOzanne, Susan, E1 aNamekawa, Satoshi, H1 aSolc, Petr1 aMurabito, Joanne, M1 aOng, Ken, K1 aHoffmann, Eva, R1 aMurray, Anna1 aRoig, Ignasi1 aPerry, John, R B1 aBiobank-based Integrative Omics Study (BIOS) Consortium1 aeQTLGen Consortium1 aBioBank Japan Project1 aChina Kadoorie Biobank Collaborative Group1 akConFab Investigators1 aLifeLines Cohort Study1 aInterAct Consortium1 a23andMe Research Team uhttps://chs-nhlbi.org/node/883503417nas a2200493 4500008004100000022001400041245018000055210006900235260000900304300001300313490000700326520180900333100002102142700001402163700001902177700003202196700001802228700002502246700002202271700001902293700002102312700002502333700002002358700002702378700002502405700001702430700002002447700002402467700002102491700002502512700002402537700002602561700002002587700001802607700002102625700002702646700001802673700002102691700002402712700002402736710005302760710007402813856003602887 2021 eng d a1932-620300aIdentification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program.0 aIdentification of novel and rare variants associated with handgr c2021 ae02536110 v163 aHandgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.
1 aSarnowski, Chloe1 aChen, Han1 aBiggs, Mary, L1 aWassertheil-Smoller, Sylvia1 aBressler, Jan1 aIrvin, Marguerite, R1 aRyan, Kathleen, A1 aKarasik, David1 aArnett, Donna, K1 aCupples, Adrienne, L1 aFardo, David, W1 aGogarten, Stephanie, M1 aHeavner, Benjamin, D1 aJain, Deepti1 aKang, Hyun, Min1 aKooperberg, Charles1 aMainous, Arch, G1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aO'Connell, Jeffrey, R1 aPsaty, Bruce, M1 aRice, Kenneth1 aSmith, Albert, V1 aVasan, Ramachandran, S1 aWindham, Gwen1 aKiel, Douglas, P1 aMurabito, Joanne, M1 aLunetta, Kathryn, L1 aTOPMed Longevity and Healthy Aging Working Group1 afrom the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883606260nas a2201741 4500008004100000022001400041245015100055210006900206260001600275490000600291520132000297100001601617700002101633700002301654700001801677700002301695700002101718700002001739700001701759700002801776700002001804700002001824700002001844700002401864700002201888700002601910700002501936700002801961700001701989700002202006700002102028700002102049700002102070700002102091700002802112700001902140700002102159700002702180700001602207700001802223700001802241700001702259700001902276700001902295700002102314700001502335700002102350700002102371700002602392700002202418700002502440700002502465700002602490700002302516700002202539700002502561700002202586700001802608700002102626700002202647700002002669700002502689700001602714700002202730700002802752700002002780700002002800700001802820700001902838700002302857700002202880700002202902700002102924700001702945700001702962700001702979700002302996700002003019700002203039700002103061700002303082700002203105700002003127700002403147700002603171700002203197700002003219700001803239700002603257700002403283700002903307700002503336700002203361700002203383700001703405700002003422700001603442700002303458700002203481700002403503700001903527700001703546700002803563700002303591700002603614700001803640700001803658700002003676700001503696700001303711700001803724700001403742700001803756700002303774700002103797700001803818700002203836700001903858700002203877700001903899700002903918700002703947700002003974700001803994700001904012700001504031700002204046700002104068700002404089700002304113700001804136700002904154700002404183700002604207700002004233700001604253700001804269700002404287700001704311700001804328700002204346700002404368700002304392700002004415700002004435710002704455856003604482 2021 eng d a2666-247700aMulti-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits.0 aMultiAncestry Genomewide Association Study Accounting for GenePs c2021 Jan 140 v23 aPsychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (), synaptic function and neurotransmission (), as well as genes previously implicated in neuropsychiatric or stress-related disorders (). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.
1 aSun, Daokun1 aRichard, Melissa1 aMusani, Solomon, K1 aSung, Yun, Ju1 aWinkler, Thomas, W1 aSchwander, Karen1 aChai, Jin, Fang1 aGuo, Xiuqing1 aKilpeläinen, Tuomas, O1 aVojinovic, Dina1 aAschard, Hugues1 aBartz, Traci, M1 aBielak, Lawrence, F1 aBrown, Michael, R1 aChitrala, Kumaraswamy1 aHartwig, Fernando, P1 aHorimoto, Andrea, R V R1 aLiu, Yongmei1 aManning, Alisa, K1 aNoordam, Raymond1 aSmith, Albert, V1 aHarris, Sarah, E1 aKuhnel, Brigitte1 aLyytikäinen, Leo-Pekka1 aNolte, Ilja, M1 aRauramaa, Rainer1 avan der Most, Peter, J1 aWang, Rujia1 aWare, Erin, B1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aArking, Dan, E1 aArnett, Donna, K1 aBarac, Ana1 aBoerwinkle, Eric1 aBroeckel, Ulrich1 aChakravarti, Aravinda1 aChen, Yii-Der Ida1 aCupples, Adrienne, L1 aDavigulus, Martha, L1 aFuentes, Lisa, de Las1 ade Mutsert, Renée1 ade Vries, Paul, S1 aDelaney, Joseph, A C1 aRoux, Ana, V Diez1 aDörr, Marcus1 aFaul, Jessica, D1 aFretts, Amanda, M1 aGallo, Linda, C1 aGrabe, Hans, Jörgen1 aGu, Charles1 aHarris, Tamara, B1 aHartman, Catharina, C A1 aHeikkinen, Sami1 aIkram, Arfan, M1 aIsasi, Carmen1 aJohnson, Craig1 aJonas, Jost, Bruno1 aKaplan, Robert, C1 aKomulainen, Pirjo1 aKrieger, Jose, E1 aLevy, Daniel1 aLiu, Jianjun1 aLohman, Kurt1 aLuik, Annemarie, I1 aMartin, Lisa, W1 aMeitinger, Thomas1 aMilaneschi, Yuri1 aO'Connell, Jeff, R1 aPalmas, Walter, R1 aPeters, Annette1 aPeyser, Patricia, A1 aPulkki-Råback, Laura1 aRaffel, Leslie, J1 aReiner, Alex, P1 aRice, Kenneth1 aRobinson, Jennifer, G1 aRosendaal, Frits, R1 aSchmidt, Carsten, Oliver1 aSchreiner, Pamela, J1 aSchwettmann, Lars1 aShikany, James, M1 aShu, Xiao-Ou1 aSidney, Stephen1 aSims, Mario1 aSmith, Jennifer, A1 aSotoodehnia, Nona1 aStrauch, Konstantin1 aTai, Shyong, E1 aTaylor, Kent1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aWaldenberger, Melanie1 aWee, Hwee-Lin1 aBin Wei, Wen-1 aWilson, Gregory1 aXuan, Deng1 aYao, Jie1 aZeng, Donglin1 aZhao, Wei1 aZhu, Xiaofeng1 aZonderman, Alan, B1 aBecker, Diane, M1 aDeary, Ian, J1 aGieger, Christian1 aLakka, Timo, A1 aLehtimäki, Terho1 aNorth, Kari, E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aSnieder, Harold1 aWang, Ya-Xing1 aWeir, David, R1 aZheng, Wei1 aEvans, Michele, K1 aGauderman, James1 aGudnason, Vilmundur1 aHorta, Bernardo, L1 aLiu, Ching-Ti1 aMook-Kanamori, Dennis, O1 aMorrison, Alanna, C1 aPereira, Alexandre, C1 aPsaty, Bruce, M1 aAmin, Najaf1 aFox, Ervin, R1 aKooperberg, Charles1 aSim, Xueling1 aBierut, Laura1 aRotter, Jerome, I1 aKardia, Sharon, L R1 aFranceschini, Nora1 aRao, Dabeeru, C1 aFornage, Myriam1 aLifeLines Cohort Study uhttps://chs-nhlbi.org/node/900506233nas a2201609 4500008004100000022001400041245009500055210006900150260001600219520178500235100001702020700002102037700001902058700002102077700002302098700001502121700001802136700002002154700002202174700002002196700002802216700001802244700002202262700002402284700002102308700002002329700002002349700001502369700002502384700001702409700003102426700002002457700002302477700002302500700002102523700001702544700002002561700002102581700002702602700001902629700002402648700002602672700002102698700001802719700001702737700001902754700002802773700002002801700002402821700002202845700002202867700001902889700001402908700002102922700002102943700002502964700002002989700002203009700001803031700002203049700002003071700001903091700002303110700002003133700002803153700001603181700001503197700001703212700001403229700002003243700002303263700001903286700001603305700002003321700001703341700002103358700001903379700001303398700001703411700002203428700002403450700002903474700002003503700001503523700002303538700002403561700002203585700002003607700001803627700001703645700002103662700001903683700002103702700001603723700001503739700002603754700002003780700002403800700002203824700002103846700001703867700001803884700001703902700002203919700002203941700002003963700002603983700002204009700001904031700001504050700002004065700002204085700002404107700002404131700002604155700002004181700002004201700002304221700001804244700002104262700002204283700002104305700001804326700002404344700001804368700001904386700001604405700001904421700001804440700002004458700002704478700002104505700002004526700001904546700002204565856003604587 2021 eng d a1476-557800aMulti-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.0 aMultiancestry genomewide genesleep interactions identify novel l c2021 Apr 153 aLong and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
1 aWang, Heming1 aNoordam, Raymond1 aCade, Brian, E1 aSchwander, Karen1 aWinkler, Thomas, W1 aLee, Jiwon1 aSung, Yun, Ju1 aBentley, Amy, R1 aManning, Alisa, K1 aAschard, Hugues1 aKilpeläinen, Tuomas, O1 aIlkov, Marjan1 aBrown, Michael, R1 aHorimoto, Andrea, R1 aRichard, Melissa1 aBartz, Traci, M1 aVojinovic, Dina1 aLim, Elise1 aNierenberg, Jovia, L1 aLiu, Yongmei1 aChitrala, Kumaraswamynaidu1 aRankinen, Tuomo1 aMusani, Solomon, K1 aFranceschini, Nora1 aRauramaa, Rainer1 aAlver, Maris1 aZee, Phyllis, C1 aHarris, Sarah, E1 avan der Most, Peter, J1 aNolte, Ilja, M1 aMunroe, Patricia, B1 aPalmer, Nicholette, D1 aKuhnel, Brigitte1 aWeiss, Stefan1 aWen, Wanqing1 aHall, Kelly, A1 aLyytikäinen, Leo-Pekka1 aO'Connell, Jeff1 aEiriksdottir, Gudny1 aLauner, Lenore, J1 ade Vries, Paul, S1 aArking, Dan, E1 aChen, Han1 aBoerwinkle, Eric1 aKrieger, Jose, E1 aSchreiner, Pamela, J1 aSidney, Stephen1 aShikany, James, M1 aRice, Kenneth1 aChen, Yii-Der Ida1 aGharib, Sina, A1 aBis, Joshua, C1 aLuik, Annemarie, I1 aIkram, Arfan, M1 aUitterlinden, André, G1 aAmin, Najaf1 aXu, Hanfei1 aLevy, Daniel1 aHe, Jiang1 aLohman, Kurt, K1 aZonderman, Alan, B1 aRice, Treva, K1 aSims, Mario1 aWilson, Gregory1 aSofer, Tamar1 aRich, Stephen, S1 aPalmas, Walter1 aYao, Jie1 aGuo, Xiuqing1 aRotter, Jerome, I1 aBiermasz, Nienke, R1 aMook-Kanamori, Dennis, O1 aMartin, Lisa, W1 aBarac, Ana1 aWallace, Robert, B1 aGottlieb, Daniel, J1 aKomulainen, Pirjo1 aHeikkinen, Sami1 aMägi, Reedik1 aMilani, Lili1 aMetspalu, Andres1 aStarr, John, M1 aMilaneschi, Yuri1 aWaken, R, J1 aGao, Chuan1 aWaldenberger, Melanie1 aPeters, Annette1 aStrauch, Konstantin1 aMeitinger, Thomas1 aRoenneberg, Till1 aVölker, Uwe1 aDörr, Marcus1 aShu, Xiao-Ou1 aMukherjee, Sutapa1 aHillman, David, R1 aKähönen, Mika1 aWagenknecht, Lynne, E1 aGieger, Christian1 aGrabe, Hans, J1 aZheng, Wei1 aPalmer, Lyle, J1 aLehtimäki, Terho1 aGudnason, Vilmundur1 aMorrison, Alanna, C1 aPereira, Alexandre, C1 aFornage, Myriam1 aPsaty, Bruce, M1 aDuijn, Cornelia, M1 aLiu, Ching-Ti1 aKelly, Tanika, N1 aEvans, Michele, K1 aBouchard, Claude1 aFox, Ervin, R1 aKooperberg, Charles1 aZhu, Xiaofeng1 aLakka, Timo, A1 aEsko, Tõnu1 aNorth, Kari, E1 aDeary, Ian, J1 aSnieder, Harold1 aPenninx, Brenda, W J H1 aGauderman, James1 aRao, Dabeeru, C1 aRedline, Susan1 avan Heemst, Diana uhttps://chs-nhlbi.org/node/871408483nas a2202413 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2021 eng d a1476-468700aSequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.0 aSequencing of 53831 diverse genomes from the NHLBI TOPMed Progra c2021 02 a290-2990 v5903 aThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
1 aTaliun, Daniel1 aHarris, Daniel, N1 aKessler, Michael, D1 aCarlson, Jedidiah1 aSzpiech, Zachary, A1 aTorres, Raul1 aTaliun, Sarah, A Gagliano1 aCorvelo, André1 aGogarten, Stephanie, M1 aKang, Hyun, Min1 aPitsillides, Achilleas, N1 aLeFaive, Jonathon1 aLee, Seung-Been1 aTian, Xiaowen1 aBrowning, Brian, L1 aDas, Sayantan1 aEmde, Anne-Katrin1 aClarke, Wayne, E1 aLoesch, Douglas, P1 aShetty, Amol, C1 aBlackwell, Thomas, W1 aSmith, Albert, V1 aWong, Quenna1 aLiu, Xiaoming1 aConomos, Matthew, P1 aBobo, Dean, M1 aAguet, Francois1 aAlbert, Christine1 aAlonso, Alvaro1 aArdlie, Kristin, G1 aArking, Dan, E1 aAslibekyan, Stella1 aAuer, Paul, L1 aBarnard, John1 aBarr, Graham1 aBarwick, Lucas1 aBecker, Lewis, C1 aBeer, Rebecca, L1 aBenjamin, Emelia, J1 aBielak, Lawrence, F1 aBlangero, John1 aBoehnke, Michael1 aBowden, Donald, W1 aBrody, Jennifer, A1 aBurchard, Esteban, G1 aCade, Brian, E1 aCasella, James, F1 aChalazan, Brandon1 aChasman, Daniel, I1 aChen, Yii-Der Ida1 aCho, Michael, H1 aChoi, Seung, Hoan1 aChung, Mina, K1 aClish, Clary, B1 aCorrea, Adolfo1 aCurran, Joanne, E1 aCuster, Brian1 aDarbar, Dawood1 aDaya, Michelle1 ade Andrade, Mariza1 aDeMeo, Dawn, L1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aEng, Celeste1 aFatkin, Diane1 aFingerlin, Tasha1 aForer, Lukas1 aFornage, Myriam1 aFranceschini, Nora1 aFuchsberger, Christian1 aFullerton, Stephanie, M1 aGermer, Soren1 aGladwin, Mark, T1 aGottlieb, Daniel, J1 aGuo, Xiuqing1 aHall, Michael, E1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHeckbert, Susan, R1 aIrvin, Marguerite, R1 aJohnsen, Jill, M1 aJohnson, Andrew, D1 aKaplan, Robert1 aKardia, Sharon, L R1 aKelly, Tanika1 aKelly, Shannon1 aKenny, Eimear, E1 aKiel, Douglas, P1 aKlemmer, Robert1 aKonkle, Barbara, A1 aKooperberg, Charles1 aKöttgen, Anna1 aLange, Leslie, A1 aLasky-Su, Jessica1 aLevy, Daniel1 aLin, Xihong1 aLin, Keng-Han1 aLiu, Chunyu1 aLoos, Ruth, J F1 aGarman, Lori1 aGerszten, Robert1 aLubitz, Steven, A1 aLunetta, Kathryn, L1 aC Y Mak, Angel1 aManichaikul, Ani1 aManning, Alisa, K1 aMathias, Rasika, A1 aMcManus, David, D1 aMcGarvey, Stephen, T1 aMeigs, James, B1 aMeyers, Deborah, A1 aMikulla, Julie, L1 aMinear, Mollie, A1 aMitchell, Braxton, D1 aMohanty, Sanghamitra1 aMontasser, May, E1 aMontgomery, Courtney1 aMorrison, Alanna, C1 aMurabito, Joanne, M1 aNatale, Andrea1 aNatarajan, Pradeep1 aNelson, Sarah, C1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPankratz, Nathan1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aPleiness, Jacob1 aPost, Wendy, S1 aPsaty, Bruce, M1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRoden, Dan1 aRotter, Jerome, I1 aRuczinski, Ingo1 aSarnowski, Chloe1 aSchoenherr, Sebastian1 aSchwartz, David, A1 aSeo, Jeong-Sun1 aSeshadri, Sudha1 aSheehan, Vivien, A1 aSheu, Wayne, H1 aShoemaker, Benjamin1 aSmith, Nicholas, L1 aSmith, Jennifer, A1 aSotoodehnia, Nona1 aStilp, Adrienne, M1 aTang, Weihong1 aTaylor, Kent, D1 aTelen, Marilyn1 aThornton, Timothy, A1 aTracy, Russell, P1 aVan Den Berg, David, J1 aVasan, Ramachandran, S1 aViaud-Martinez, Karine, A1 aVrieze, Scott1 aWeeks, Daniel, E1 aWeir, Bruce, S1 aWeiss, Scott, T1 aWeng, Lu-Chen1 aWiller, Cristen, J1 aZhang, Yingze1 aZhao, Xutong1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBoerwinkle, Eric1 aGabriel, Stacey1 aGibbs, Richard1 aRice, Kenneth, M1 aRich, Stephen, S1 aSilverman, Edwin, K1 aQasba, Pankaj1 aGan, Weiniu1 aPapanicolaou, George, J1 aNickerson, Deborah, A1 aBrowning, Sharon, R1 aZody, Michael, C1 aZöllner, Sebastian1 aWilson, James, G1 aCupples, Adrienne, L1 aLaurie, Cathy, C1 aJaquish, Cashell, E1 aHernandez, Ryan, D1 aO'Connor, Timothy, D1 aAbecasis, Goncalo, R1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/866603856nas a2200673 4500008004100000022001400041245008300055210006900138260001500207300001000222490000700232520192100239653000902160653002502169653002402194653001502218653002502233653001102258653001802269653001102287653001902298653000902317653001602326653001302342653003202355653002802387653002302415653001702438653001802455653003402473653002702507100001302534700002102547700002302568700002902591700002602620700001902646700002202665700002102687700001802708700001902726700002402745700001802769700002202787700002202809700002602831700002302857700002002880700002102900700002102921700002402942700002302966700002802989700002003017700002303037700002203060710006403082856003603146 2021 eng d a1558-359700aSupplemental Association of Clonal Hematopoiesis With Incident Heart Failure.0 aSupplemental Association of Clonal Hematopoiesis With Incident H c2021 07 06 a42-520 v783 aBACKGROUND: Age-related clonal hematopoiesis of indeterminate potential (CHIP), defined as clonally expanded leukemogenic sequence variations (particularly in DNMT3A, TET2, ASXL1, and JAK2) in asymptomatic individuals, is associated with cardiovascular events, including recurrent heart failure (HF).
OBJECTIVES: This study sought to evaluate whether CHIP is associated with incident HF.
METHODS: CHIP status was obtained from whole exome or genome sequencing of blood DNA in participants without prevalent HF or hematological malignancy from 5 cohorts. Cox proportional hazards models were performed within each cohort, adjusting for demographic and clinical risk factors, followed by fixed-effect meta-analyses. Large CHIP clones (defined as variant allele frequency >10%), HF with or without baseline coronary heart disease, and left ventricular ejection fraction were evaluated in secondary analyses.
RESULTS: Of 56,597 individuals (59% women, mean age 58 years at baseline), 3,406 (6%) had CHIP, and 4,694 developed HF (8.3%) over up to 20 years of follow-up. CHIP was prospectively associated with a 25% increased risk of HF in meta-analysis (hazard ratio: 1.25; 95% confidence interval: 1.13-1.38) with consistent associations across cohorts. ASXL1, TET2, and JAK2 sequence variations were each associated with an increased risk of HF, whereas DNMT3A sequence variations were not associated with HF. Secondary analyses suggested large CHIP was associated with a greater risk of HF (hazard ratio: 1.29; 95% confidence interval: 1.15-1.44), and the associations for CHIP on HF with and without prior coronary heart disease were homogenous. ASXL1 sequence variations were associated with reduced left ventricular ejection fraction.
CONCLUSIONS: CHIP, particularly sequence variations in ASXL1, TET2, and JAK2, represents a new risk factor for HF.
10aAged10aClonal Hematopoiesis10aCorrelation of Data10aDemography10aDNA-Binding Proteins10aFemale10aHeart Failure10aHumans10aJanus Kinase 210aMale10aMiddle Aged10aMutation10aProportional Hazards Models10aProto-Oncogene Proteins10aRepressor Proteins10aRisk Factors10aStroke Volume10aVentricular Dysfunction, Left10aWhole Exome Sequencing1 aYu, Bing1 aRoberts, Mary, B1 aRaffield, Laura, M1 aZekavat, Seyedeh, Maryam1 aNguyen, Ngoc, Quynh H1 aBiggs, Mary, L1 aBrown, Michael, R1 aGriffin, Gabriel1 aDesai, Pinkal1 aCorrea, Adolfo1 aMorrison, Alanna, C1 aShah, Amil, M1 aNiroula, Abhishek1 aUddin, Md, Mesbah1 aHonigberg, Michael, C1 aEbert, Benjamin, L1 aPsaty, Bruce, M1 aWhitsel, Eric, A1 aManson, JoAnn, E1 aKooperberg, Charles1 aBick, Alexander, G1 aBallantyne, Christie, M1 aReiner, Alex, P1 aNatarajan, Pradeep1 aEaton, Charles, B1 aNational Heart, Lung, and Blood Institute TOPMed Consortium uhttps://chs-nhlbi.org/node/883904296nas a2200973 4500008004100000022001400041245010700055210006900162260001600231520147300247100002301720700002101743700001901764700001801783700001901801700002301820700001901843700001701862700001901879700003001898700002601928700002801954700002801982700002102010700001702031700002202048700002302070700002202093700002202115700002102137700002402158700002302182700002002205700002402225700002002249700002102269700002302290700002402313700002402337700001902361700001902380700002002399700001902419700002502438700002302463700002402486700002002510700002302530700001602553700002202569700002002591700002002611700001702631700002202648700001802670700002402688700002402712700002302736700002402759700001902783700001502802700002302817700002502840700002502865700002202890700002402912700001902936700002602955700002602981700002103007700002103028700002203049700002303071700002003094700002703114700002103141700002003162700002103182700001903203700002003222700002303242700002103265856003603286 2021 eng d a1476-625600aA System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.0 aSystem for Phenotype Harmonization in the NHLBI TransOmics for P c2021 Apr 163 aGenotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.
1 aStilp, Adrienne, M1 aEmery, Leslie, S1 aBroome, Jai, G1 aButh, Erin, J1 aKhan, Alyna, T1 aLaurie, Cecelia, A1 aWang, Fei, Fei1 aWong, Quenna1 aChen, Dongquan1 aD'Augustine, Catherine, M1 aHeard-Costa, Nancy, L1 aHohensee, Chancellor, R1 aJohnson, William, Craig1 aJuarez, Lucia, D1 aLiu, Jingmin1 aMutalik, Karen, M1 aRaffield, Laura, M1 aWiggins, Kerri, L1 ade Vries, Paul, S1 aKelly, Tanika, N1 aKooperberg, Charles1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aReiner, Alex, P1 aArnett, Donna, K1 aAslibekyan, Stella1 aBarnes, Kathleen, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aChen, Ming-Huei1 aCorrea, Adolfo1 aCupples, Adrienne, L1 ade Andrade, Mariza1 aEllinor, Patrick, T1 aFornage, Myriam1 aFranceschini, Nora1 aGan, Weiniu1 aGanesh, Santhi, K1 aGraffelman, Jan1 aGrove, Megan, L1 aGuo, Xiuqing1 aHawley, Nicola, L1 aHsu, Wan-Ling1 aJackson, Rebecca, D1 aJaquish, Cashell, E1 aJohnson, Andrew, D1 aKardia, Sharon, L R1 aKelly, Shannon1 aLee, Jiwon1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNorth, Kari, E1 aNouraie, Seyed, Mehdi1 aOelsner, Elizabeth, C1 aPankratz, Nathan1 aRich, Stephen, S1 aRotter, Jerome, I1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aWeeks, Daniel, E1 aWeiss, Scott, T1 aWilson, Carla, G1 aYanek, Lisa, R1 aPsaty, Bruce, M1 aHeckbert, Susan, R1 aLaurie, Cathy, C uhttps://chs-nhlbi.org/node/871304364nas a2200997 4500008004100000022001400041245016200055210006900217260001300286300001100299490000700310520151100317100002001828700002201848700002301870700002301893700002301916700002601939700002501965700002001990700002102010700002602031700001702057700002502074700002202099700001702121700001702138700002002155700002002175700002302195700001702218700002102235700001802256700001802274700001902292700001202311700001802323700001502341700002302356700002802379700001802407700002002425700002002445700002102465700002302486700002002509700002102529700002302550700001802573700002202591700002302613700002202636700001802658700002002676700002302696700002302719700001902742700002002761700001402781700002002795700002202815700002002837700002102857700002102878700001702899700002402916700001902940700002502959700001402984700002302998700002403021700002303045700002503068700002603093700002103119700002703140700002203167700001703189700002103206700001903227700002103246700001603267700002403283700002303307856003603330 2021 eng d a2352-396400aWhole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.0 aWhole genome sequence analyses of eGFR in 23732 people represent c2021 Jan a1031570 v633 aBACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.
METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.
FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.
INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.
1 aLin, Bridget, M1 aGrinde, Kelsey, E1 aBrody, Jennifer, A1 aBreeze, Charles, E1 aRaffield, Laura, M1 aMychaleckyj, Josyf, C1 aThornton, Timothy, A1 aPerry, James, A1 aBaier, Leslie, J1 aFuentes, Lisa, de Las1 aGuo, Xiuqing1 aHeavner, Benjamin, D1 aHanson, Robert, L1 aHung, Yi-Jen1 aQian, Huijun1 aHsiung, Chao, A1 aHwang, Shih-Jen1 aIrvin, Margaret, R1 aJain, Deepti1 aKelly, Tanika, N1 aKobes, Sayuko1 aLange, Leslie1 aLash, James, P1 aLi, Yun1 aLiu, Xiaoming1 aMi, Xuenan1 aMusani, Solomon, K1 aPapanicolaou, George, J1 aParsa, Afshin1 aReiner, Alex, P1 aSalimi, Shabnam1 aSheu, Wayne, H-H1 aShuldiner, Alan, R1 aTaylor, Kent, D1 aSmith, Albert, V1 aSmith, Jennifer, A1 aTin, Adrienne1 aVaidya, Dhananjay1 aWallace, Robert, B1 aYamamoto, Kenichi1 aSakaue, Saori1 aMatsuda, Koichi1 aKamatani, Yoichiro1 aMomozawa, Yukihide1 aYanek, Lisa, R1 aYoung, Betsi, A1 aZhao, Wei1 aOkada, Yukinori1 aAbecasis, Gonzalo1 aPsaty, Bruce, M1 aArnett, Donna, K1 aBoerwinkle, Eric1 aCai, Jianwen1 aDer Chen, Ida, Yii-1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aHe, Jiang1 aKardia, Sharon, Lr1 aKooperberg, Charles1 aMathias, Rasika, A1 aMitchell, Braxton, D1 aNickerson, Deborah, A1 aTurner, Steve, T1 aVasan, Ramachandran, S1 aRotter, Jerome, I1 aLevy, Daniel1 aKramer, Holly, J1 aKöttgen, Anna1 aRich, Stephen, S1 aLin, Dan-Yu1 aBrowning, Sharon, R1 aFranceschini, Nora uhttps://chs-nhlbi.org/node/866404419nas a2200925 4500008004100000022001400041245011400055210006900169260001600238520175700254100002002011700001202031700001402043700001702057700001602074700002002090700002102110700002002131700002302151700002502174700002302199700001902222700002002241700001902261700002002280700002302300700002002323700002102343700002002364700002302384700001902407700001402426700002002440700001902460700002502479700001802504700002002522700002102542700001902563700002102582700002502603700002002628700001902648700002202667700002002689700002002709700002002729700001602749700002002765700002402785700002102809700002702830700002002857700001502877700002502892700002402917700002202941700001902963700002602982700002103008700002003029700002703049700002103076700002203097700002103119700002303140700001403163700002203177700002403199700002303223700002303246700001203269700001803281700002203299700002503321700002303346700002303369710006503392856003603457 2021 eng d a1460-208300aWhole genome sequence analysis of platelet traits in the NHLBI trans-omics for precision medicine initiative.0 aWhole genome sequence analysis of platelet traits in the NHLBI t c2021 Sep 063 aPlatelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing from NHLBI's Trans-Omics for Precision Medicine Initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several GWAS identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of whole genome sequencing in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.
1 aLittle, Amarise1 aHu, Yao1 aSun, Quan1 aJain, Deepti1 aBroome, Jai1 aChen, Ming-Huei1 aThibord, Florian1 aMcHugh, Caitlin1 aSurendran, Praveen1 aBlackwell, Thomas, W1 aBrody, Jennifer, A1 aBhan, Arunoday1 aChami, Nathalie1 aVries, Paul, S1 aEkunwe, Lynette1 aHeard-Costa, Nancy1 aHobbs, Brian, D1 aManichaikul, Ani1 aMoon, Jee-Young1 aPreuss, Michael, H1 aRyan, Kathleen1 aWang, Zhe1 aWheeler, Marsha1 aYanek, Lisa, R1 aAbecasis, Goncalo, R1 aAlmasy, Laura1 aBeaty, Terri, H1 aBecker, Lewis, C1 aBlangero, John1 aBoerwinkle, Eric1 aButterworth, Adam, S1 aChoquet, Helene1 aCorrea, Adolfo1 aCurran, Joanne, E1 aFaraday, Nauder1 aFornage, Myriam1 aGlahn, David, C1 aHou, Lifang1 aJorgenson, Eric1 aKooperberg, Charles1 aLewis, Joshua, P1 aLloyd-Jones, Donald, M1 aLoos, Ruth, J F1 aMin, Nancy1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aNickerson, Debbie1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPankratz, Nathan1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aRich, Stephen, S1 aRotter, Jerome, I1 aSmith, Albert, V1 aSmith, Nicholas, L1 aTang, Hua1 aTracy, Russell, P1 aConomos, Matthew, P1 aLaurie, Cecelia, A1 aMathias, Rasika, A1 aLi, Yun1 aAuer, Paul, L1 aThornton, Timothy1 aReiner, Alexander, P1 aJohnson, Andrew, D1 aRaffield, Laura, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/891305743nas a2201309 4500008004100000022001400041245011800055210006900173260001500242300001200257490000800269520205100277653001002328653000902338653003202347653002202379653001702401653001102418653001702429653002202446653003402468653001702502653001102519653000902530653001602539653005302555653001402608653002002622653003102642653001802673100001202691700002302703700002302726700001702749700001702766700001802783700001502801700003602816700002302852700002002875700001902895700002002914700001302934700001702947700001602964700002002980700002203000700002003022700001403042700002303056700002303079700002503102700002003127700001903147700002803166700002303194700001403217700002003231700002303251700001503274700002003289700002103309700001803330700002003348700002203368700001803390700001803408700002103426700002003447700002203467700002003489700002703509700002703536700002303563700001903586700002103605700002103626700002103647700002503668700001603693700002603709700002403735700002003759700001903779700001903798700001903817700002003836700002003856700002403876700002303900700002903923700001403952700002003966700002003986700002504006700002204031700002104053700002504074700002304099700001804122700001204140700002304152700002204175700002104197700002104218700002304239700002104262700002404283700002504307710006504332856003604397 2021 eng d a1537-660500aWhole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program.0 aWholegenome sequencing association analysis of quantitative red c2021 05 06 a874-8930 v1083 aWhole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.
10aAdult10aAged10aChromosomes, Human, Pair 1610aDatasets as Topic10aErythrocytes10aFemale10aGene Editing10aGenetic Variation10aGenome-Wide Association Study10aHEK293 Cells10aHumans10aMale10aMiddle Aged10aNational Heart, Lung, and Blood Institute (U.S.)10aPhenotype10aQuality Control10aReproducibility of Results10aUnited States1 aHu, Yao1 aStilp, Adrienne, M1 aMcHugh, Caitlin, P1 aRao, Shuquan1 aJain, Deepti1 aZheng, Xiuwen1 aLane, John1 ade Bellefon, Sébastian, Méric1 aRaffield, Laura, M1 aChen, Ming-Huei1 aYanek, Lisa, R1 aWheeler, Marsha1 aYao, Yao1 aRen, Chunyan1 aBroome, Jai1 aMoon, Jee-Young1 ade Vries, Paul, S1 aHobbs, Brian, D1 aSun, Quan1 aSurendran, Praveen1 aBrody, Jennifer, A1 aBlackwell, Thomas, W1 aChoquet, Helene1 aRyan, Kathleen1 aDuggirala, Ravindranath1 aHeard-Costa, Nancy1 aWang, Zhe1 aChami, Nathalie1 aPreuss, Michael, H1 aMin, Nancy1 aEkunwe, Lynette1 aLange, Leslie, A1 aCushman, Mary1 aFaraday, Nauder1 aCurran, Joanne, E1 aAlmasy, Laura1 aKundu, Kousik1 aSmith, Albert, V1 aGabriel, Stacey1 aRotter, Jerome, I1 aFornage, Myriam1 aLloyd-Jones, Donald, M1 aVasan, Ramachandran, S1 aSmith, Nicholas, L1 aNorth, Kari, E1 aBoerwinkle, Eric1 aBecker, Lewis, C1 aLewis, Joshua, P1 aAbecasis, Goncalo, R1 aHou, Lifang1 aO'Connell, Jeffrey, R1 aMorrison, Alanna, C1 aBeaty, Terri, H1 aKaplan, Robert1 aCorrea, Adolfo1 aBlangero, John1 aJorgenson, Eric1 aPsaty, Bruce, M1 aKooperberg, Charles1 aWalton, Russell, T1 aKleinstiver, Benjamin, P1 aTang, Hua1 aLoos, Ruth, J F1 aSoranzo, Nicole1 aButterworth, Adam, S1 aNickerson, Debbie1 aRich, Stephen, S1 aMitchell, Braxton, D1 aJohnson, Andrew, D1 aAuer, Paul, L1 aLi, Yun1 aMathias, Rasika, A1 aLettre, Guillaume1 aPankratz, Nathan1 aLaurie, Cathy, C1 aLaurie, Cecelia, A1 aBauer, Daniel, E1 aConomos, Matthew, P1 aReiner, Alexander, P1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/877905763nas a2201477 4500008004100000022001400041245012500055210006900180260001500249300001400264490000800278520153200286653001101818653001501829653002301844653003801867653001801905653003401923653001101957653001501968653005301983653001402036653003602050653001402086653001302100653004302113653002802156653001902184653001802203653002802221100002402249700002302273700002102296700002302317700002902340700002502369700002302394700001602417700002002433700002002453700002402473700001502497700002202512700001902534700002002553700002002573700002302593700002502616700002002641700001802661700001702679700002102696700002802717700001502745700002002760700002302780700002002803700001902823700002102842700001402863700002302877700002202900700002002922700001402942700002002956700001902976700001502995700002503010700001803035700002403053700002003077700002103097700001903118700002103137700002503158700001903183700002003202700002003222700001903242700001503261700001903276700002003295700002003315700002403335700001603359700002303375700002003398700001903418700002403437700001803461700002303479700002203502700002103524700001703545700001203562700002703574700002003601700002103621700002303642700002503665700002403690700001503714700002603729700002303755700001903778700002603797700002203823700002103845700002003866700002003886700002103906700002003927700002203947700002403969700002303993700001404016700002204030700002504052700002704077700001404104700002304118700002504141700001804166710006504184856003604249 2021 eng d a1537-660500aWhole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program.0 aWholegenome sequencing in diverse subjects identifies genetic co c2021 10 07 a1836-18510 v1083 aMany common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.
10aAsthma10aBiomarkers10aDermatitis, Atopic10aGenetic Predisposition to Disease10aGenome, Human10aGenome-Wide Association Study10aHumans10aLeukocytes10aNational Heart, Lung, and Blood Institute (U.S.)10aPhenotype10aPolymorphism, Single Nucleotide10aPrognosis10aProteome10aPulmonary Disease, Chronic Obstructive10aQuantitative Trait Loci10aUnited Kingdom10aUnited States10aWhole Genome Sequencing1 aMikhaylova, Anna, V1 aMcHugh, Caitlin, P1 aPolfus, Linda, M1 aRaffield, Laura, M1 aBoorgula, Meher, Preethi1 aBlackwell, Thomas, W1 aBrody, Jennifer, A1 aBroome, Jai1 aChami, Nathalie1 aChen, Ming-Huei1 aConomos, Matthew, P1 aCox, Corey1 aCurran, Joanne, E1 aDaya, Michelle1 aEkunwe, Lynette1 aGlahn, David, C1 aHeard-Costa, Nancy1 aHighland, Heather, M1 aHobbs, Brian, D1 aIlboudo, Yann1 aJain, Deepti1 aLange, Leslie, A1 aMiller-Fleming, Tyne, W1 aMin, Nancy1 aMoon, Jee-Young1 aPreuss, Michael, H1 aRosen, Jonathon1 aRyan, Kathleen1 aSmith, Albert, V1 aSun, Quan1 aSurendran, Praveen1 ade Vries, Paul, S1 aWalter, Klaudia1 aWang, Zhe1 aWheeler, Marsha1 aYanek, Lisa, R1 aZhong, Xue1 aAbecasis, Goncalo, R1 aAlmasy, Laura1 aBarnes, Kathleen, C1 aBeaty, Terri, H1 aBecker, Lewis, C1 aBlangero, John1 aBoerwinkle, Eric1 aButterworth, Adam, S1 aChavan, Sameer1 aCho, Michael, H1 aChoquet, Helene1 aCorrea, Adolfo1 aCox, Nancy1 aDeMeo, Dawn, L1 aFaraday, Nauder1 aFornage, Myriam1 aGerszten, Robert, E1 aHou, Lifang1 aJohnson, Andrew, D1 aJorgenson, Eric1 aKaplan, Robert1 aKooperberg, Charles1 aKundu, Kousik1 aLaurie, Cecelia, A1 aLettre, Guillaume1 aLewis, Joshua, P1 aLi, Bingshan1 aLi, Yun1 aLloyd-Jones, Donald, M1 aLoos, Ruth, J F1 aManichaikul, Ani1 aMeyers, Deborah, A1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aNgo, Debby1 aNickerson, Deborah, A1 aNongmaithem, Suraj1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aOrtega, Victor, E1 aPankratz, Nathan1 aPerry, James, A1 aPsaty, Bruce, M1 aRich, Stephen, S1 aSoranzo, Nicole1 aRotter, Jerome, I1 aSilverman, Edwin, K1 aSmith, Nicholas, L1 aTang, Hua1 aTracy, Russell, P1 aThornton, Timothy, A1 aVasan, Ramachandran, S1 aZein, Joe1 aMathias, Rasika, A1 aReiner, Alexander, P1 aAuer, Paul, L1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/891403404nas a2200757 4500008004100000022001400041245011100055210006900166260001300235300001200248490000700260520115000267100002601417700001701443700001701460700002501477700002401502700002201526700002701548700002501575700002001600700002401620700001801644700002501662700001501687700002301702700001901725700002701744700002101771700002401792700002101816700002201837700002601859700001901885700002301904700002401927700002801951700001901979700002001998700002002018700002302038700002402061700002702085700002302112700002002135700002102155700002202176700002302198700001902221700001702240700002002257700002302277700002302300700002502323700002402348700002102372700001902393700002102412700001902433700001602452700001502468700002302483710003902506710006502545856003602610 2022 eng d a1546-171800aAssessing the contribution of rare variants to complex trait heritability from whole-genome sequence data.0 aAssessing the contribution of rare variants to complex trait her c2022 Mar a263-2730 v543 aAnalyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.
1 aWainschtein, Pierrick1 aJain, Deepti1 aZheng, Zhili1 aCupples, Adrienne, L1 aShadyab, Aladdin, H1 aMcKnight, Barbara1 aShoemaker, Benjamin, M1 aMitchell, Braxton, D1 aPsaty, Bruce, M1 aKooperberg, Charles1 aLiu, Ching-Ti1 aAlbert, Christine, M1 aRoden, Dan1 aChasman, Daniel, I1 aDarbar, Dawood1 aLloyd-Jones, Donald, M1 aArnett, Donna, K1 aRegan, Elizabeth, A1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aO'Connell, Jeffrey, R1 aYanek, Lisa, R1 ade Andrade, Mariza1 aAllison, Matthew, A1 aMcDonald, Merry-Lynn, N1 aChung, Mina, K1 aFornage, Myriam1 aChami, Nathalie1 aSmith, Nicholas, L1 aEllinor, Patrick, T1 aVasan, Ramachandran, S1 aMathias, Rasika, A1 aLoos, Ruth, J F1 aRich, Stephen, S1 aLubitz, Steven, A1 aHeckbert, Susan, R1 aRedline, Susan1 aGuo, Xiuqing1 aChen, Y, -D Ida1 aLaurie, Cecelia, A1 aHernandez, Ryan, D1 aMcGarvey, Stephen, T1 aGoddard, Michael, E1 aLaurie, Cathy, C1 aNorth, Kari, E1 aLange, Leslie, A1 aWeir, Bruce, S1 aYengo, Loic1 aYang, Jian1 aVisscher, Peter, M1 aTOPMed Anthropometry Working Group1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/904203135nas a2200529 4500008004100000022001400041245006700055210006600122260001300188300001200201490000700213520159100220100002401811700002401835700002201859700002001881700002001901700002201921700002301943700002201966700001301988700002402001700002102025700002402046700002002070700002702090700001902117700002102136700002202157700002202179700001902201700002002220700002002240700002202260700002402282700002102306700002802327700002402355700002302379700002402402700002102426700002102447700002302468700002502491710005302516856003602569 2022 eng d a1524-462800aClonal Hematopoiesis Is Associated With Higher Risk of Stroke.0 aClonal Hematopoiesis Is Associated With Higher Risk of Stroke c2022 Mar a788-7970 v533 aBACKGROUND AND PURPOSE: Clonal hematopoiesis of indeterminate potential (CHIP) is a novel age-related risk factor for cardiovascular disease-related morbidity and mortality. The association of CHIP with risk of incident ischemic stroke was reported previously in an exploratory analysis including a small number of incident stroke cases without replication and lack of stroke subphenotyping. The purpose of this study was to discover whether CHIP is a risk factor for ischemic or hemorrhagic stroke.
METHODS: We utilized plasma genome sequence data of blood DNA to identify CHIP in 78 752 individuals from 8 prospective cohorts and biobanks. We then assessed the association of CHIP and commonly mutated individual CHIP driver genes (, , and ) with any stroke, ischemic stroke, and hemorrhagic stroke.
RESULTS: CHIP was associated with an increased risk of total stroke (hazard ratio, 1.14 [95% CI, 1.03-1.27]; =0.01) after adjustment for age, sex, and race. We observed associations with CHIP with risk of hemorrhagic stroke (hazard ratio, 1.24 [95% CI, 1.01-1.51]; =0.04) and with small vessel ischemic stroke subtypes. In gene-specific association results, showed the strongest association with total stroke and ischemic stroke, whereas and were each associated with increased risk of hemorrhagic stroke.
CONCLUSIONS: CHIP is associated with an increased risk of stroke, particularly with hemorrhagic and small vessel ischemic stroke. Future studies clarifying the relationship between CHIP and subtypes of stroke are needed.
1 aBhattacharya, Romit1 aZekavat, Seyedeh, M1 aHaessler, Jeffrey1 aFornage, Myriam1 aRaffield, Laura1 aUddin, Md, Mesbah1 aBick, Alexander, G1 aNiroula, Abhishek1 aYu, Bing1 aGibson, Christopher1 aGriffin, Gabriel1 aMorrison, Alanna, C1 aPsaty, Bruce, M1 aLongstreth, William, T1 aBis, Joshua, C1 aRich, Stephen, S1 aRotter, Jerome, I1 aTracy, Russell, P1 aCorrea, Adolfo1 aSeshadri, Sudha1 aJohnson, Andrew1 aCollins, Jason, M1 aHayden, Kathleen, M1 aMadsen, Tracy, E1 aBallantyne, Christie, M1 aJaiswal, Siddhartha1 aEbert, Benjamin, L1 aKooperberg, Charles1 aManson, JoAnn, E1 aWhitsel, Eric, A1 aNatarajan, Pradeep1 aReiner, Alexander, P1 aNHLBI Trans-Omics for Precision Medicine Program uhttps://chs-nhlbi.org/node/898606322nas a2201285 4500008004100000022001400041245007900055210006900134260001600203300001400219490000800233520251800241653003802759653003402797653001302831653001102844653003602855653002802891653001502919653002702934100002102961700001802982700002303000700002003023700002203043700002303065700002003088700002003108700002403128700002603152700001803178700002503196700001503221700002303236700002203259700002403281700002203305700002903327700002303356700002003379700002403399700002403423700002003447700001803467700001903485700002003504700001903524700002203543700001403565700003003579700002003609700002303629700002303652700002203675700001703697700002603714700002003740700002203760700001203782700002503794700001403819700001403833700002403847700002403871700002103895700002203916700002303938700002403961700002203985700001804007700002204025700002004047700002004067700002304087700002504110700001804135700002104153700001904174700001804193700002604211700002004237700002304257700002504280700002104305700002504326700002204351700002004373700003004393700002704423700001704450700002104467700002004488700002004508700002604528700002104554700001904575700002104594700001704615700001804632700002404650700002404674700002904698700002504727700003204752700002304784700002304807700002304830710014704853856003605000 2022 eng d a1524-453900aCross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.0 aCrossAncestry Investigation of Venous Thromboembolism Genomic Pr c2022 Oct 18 a1225-12420 v1463 aBACKGROUND: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources.
METHODS: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations.
RESULTS: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis.
CONCLUSIONS: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.
10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenomics10aHumans10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aThrombosis10aVenous Thromboembolism1 aThibord, Florian1 aKlarin, Derek1 aBrody, Jennifer, A1 aChen, Ming-Huei1 aLevin, Michael, G1 aChasman, Daniel, I1 aGoode, Ellen, L1 aHveem, Kristian1 aTeder-Laving, Maris1 aMartinez-Perez, Angel1 aAïssi, Dylan1 aDaian-Bacq, Delphine1 aIto, Kaoru1 aNatarajan, Pradeep1 aLutsey, Pamela, L1 aNadkarni, Girish, N1 ade Vries, Paul, S1 aCuellar-Partida, Gabriel1 aWolford, Brooke, N1 aPattee, Jack, W1 aKooperberg, Charles1 aBraekkan, Sigrid, K1 aLi-Gao, Ruifang1 aSaut, Noémie1 aSept, Corriene1 aGermain, Marine1 aJudy, Renae, L1 aWiggins, Kerri, L1 aKo, Darae1 aO'Donnell, Christopher, J1 aTaylor, Kent, D1 aGiulianini, Franco1 ade Andrade, Mariza1 aNøst, Therese, H1 aBoland, Anne1 aEmpana, Jean-Philippe1 aKoyama, Satoshi1 aGilliland, Thomas1 aDo, Ron1 aHuffman, Jennifer, E1 aWang, Xin1 aZhou, Wei1 aSoria, Jose, Manuel1 aSouto, Juan, Carlos1 aPankratz, Nathan1 aHaessler, Jeffery1 aHindberg, Kristian1 aRosendaal, Frits, R1 aTurman, Constance1 aOlaso, Robert1 aKember, Rachel, L1 aBartz, Traci, M1 aLynch, Julie, A1 aHeckbert, Susan, R1 aArmasu, Sebastian, M1 aBrumpton, Ben1 aSmadja, David, M1 aJouven, Xavier1 aKomuro, Issei1 aClapham, Katharine, R1 aLoos, Ruth, J F1 aWiller, Cristen, J1 aSabater-Lleal, Maria1 aPankow, James, S1 aReiner, Alexander, P1 aMorelli, Vania, M1 aRidker, Paul, M1 aVlieg, Astrid, van Hylcka1 aDeleuze, Jean-Francois1 aKraft, Peter1 aRader, Daniel, J1 aLee, Kyung, Min1 aPsaty, Bruce, M1 aSkogholt, Anne, Heidi1 aEmmerich, Joseph1 aSuchon, Pierre1 aRich, Stephen, S1 aVy, Ha, My T1 aTang, Weihong1 aJackson, Rebecca, D1 aHansen, John-Bjarne1 aMorange, Pierre-Emmanuel1 aKabrhel, Christopher1 aTrégouët, David-Alexandre1 aDamrauer, Scott, M1 aJohnson, Andrew, D1 aSmith, Nicholas, L1 aGlobal Biobank Meta-Analysis Initiative; Estonian Biobank Research Team; 23andMe Research Team; Biobank Japan; CHARGE Hemostasis Working Group uhttps://chs-nhlbi.org/node/919403248nas a2200733 4500008004100000022001400041245010400055210006900159260001500228300000900243490000700252520109600259653002701355653001901382653001101401653002101412653001401433100002501447700002401472700002201496700002101518700002101539700002501560700001801585700002001603700002001623700001701643700002901660700002601689700002001715700001901735700002401754700002101778700002301799700001901822700002501841700001901866700002901885700002201914700002301936700002101959700002401980700001802004700002002022700002502042700002402067700001602091700002002107700001902127700002102146700002102167700002202188700002202210700002402232700002202256700002002278700002202298700002302320700002402343700002402367700002202391710006502413856003602478 2022 eng d a2041-172300aEndophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes.0 aEndophenotype effect sizes support variant pathogenicity in mono c2022 08 30 a51060 v133 aAccurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P < 0.001 for each trait) and discriminate pathogenic from non-pathogenic variants (area under the curve 0.82-0.84 across endophenotypes). An effect size threshold of ≥ 0.5 times the endophenotype standard deviation nominates up to 35% of rare variants of uncertain significance or not in ClinVar in disease susceptibility genes with pathogenic potential. We propose that variant associations with quantitative endophenotypes for monogenic diseases can provide evidence supporting pathogenicity.
10aDisease Susceptibility10aEndophenotypes10aHumans10aLong QT Syndrome10aVirulence1 aHalford, Jennifer, L1 aMorrill, Valerie, N1 aChoi, Seung, Hoan1 aJurgens, Sean, J1 aMelloni, Giorgio1 aMarston, Nicholas, A1 aWeng, Lu-Chen1 aNauffal, Victor1 aHall, Amelia, W1 aGunn, Sophia1 aAustin-Tse, Christina, A1 aPirruccello, James, P1 aKhurshid, Shaan1 aRehm, Heidi, L1 aBenjamin, Emelia, J1 aBoerwinkle, Eric1 aBrody, Jennifer, A1 aCorrea, Adolfo1 aFornwalt, Brandon, K1 aGupta, Namrata1 aHaggerty, Christopher, M1 aHarris, Stephanie1 aHeckbert, Susan, R1 aHong, Charles, C1 aKooperberg, Charles1 aLin, Henry, J1 aLoos, Ruth, J F1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aPost, Wendy1 aPsaty, Bruce, M1 aRedline, Susan1 aRice, Kenneth, M1 aRich, Stephen, S1 aRotter, Jerome, I1 aSchnatz, Peter, F1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aWong, Eugene, K1 aSabatine, Marc, S1 aRuff, Christian, T1 aLunetta, Kathryn, L1 aEllinor, Patrick, T1 aLubitz, Steven, A1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/916704304nas a2201045 4500008004100000022001400041245011400055210006900169260001300238300001400251490000700265520128500272653002201557653001101579653003401590653001101624653001401635653002801649100001401677700001401691700001701705700002201722700003201744700002401776700001801800700001501818700001401833700001401847700001601861700002101877700001801898700002401916700001901940700002501959700001901984700002102003700002202024700002302046700001902069700002402088700001902112700002502131700002202156700002202178700002802200700002302228700002302251700002502274700001702299700002102316700002402337700001902361700002102380700002002401700002102421700002202442700002002464700002302484700002002507700002502527700002202552700002402574700001702598700002602615700002602641700002402667700002002691700002302711700001902734700002502753700003402778700002102812700002102833700002302854700002002877700002202897700002702919700002102946700002102967700001902988700001403007700002203021700002303043700002303066700002003089700001603109710006503125710003203190856003603222 2022 eng d a1548-710500aA framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.0 aframework for detecting noncoding rarevariant associations of la c2022 Dec a1599-16110 v193 aLarge-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.
10aGenetic Variation10aGenome10aGenome-Wide Association Study10aHumans10aPhenotype10aWhole Genome Sequencing1 aLi, Zilin1 aLi, Xihao1 aZhou, Hufeng1 aGaynor, Sheila, M1 aSelvaraj, Margaret, Sunitha1 aArapoglou, Theodore1 aQuick, Corbin1 aLiu, Yaowu1 aChen, Han1 aSun, Ryan1 aDey, Rounak1 aArnett, Donna, K1 aAuer, Paul, L1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlackwell, Thomas, W1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aConomos, Matthew, P1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 ade Vries, Paul, S1 aDuggirala, Ravindranath1 aFranceschini, Nora1 aFreedman, Barry, I1 aGöring, Harald, H H1 aGuo, Xiuqing1 aKalyani, Rita, R1 aKooperberg, Charles1 aKral, Brian, G1 aLange, Leslie, A1 aLin, Bridget, M1 aManichaikul, Ani1 aManning, Alisa, K1 aMartin, Lisa, W1 aMathias, Rasika, A1 aMeigs, James, B1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aRedline, Susan1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aRice, Kenneth, M1 aRich, Stephen, S1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aTaub, Margaret, A1 aVasan, Ramachandran, S1 aWeeks, Daniel, E1 aWilson, James, G1 aYanek, Lisa, R1 aZhao, Wei1 aRotter, Jerome, I1 aWiller, Cristen, J1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aLin, Xihong1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/925305976nas a2201393 4500008004100000022001400041245013400055210006900189260001600258300003400274520189200308100002102200700001402221700001702235700002202252700003002274700002502304700002502329700001502354700002302369700002302392700001702415700002002432700002202452700001302474700001902487700002402506700001902530700001802549700002302567700001902590700002602609700001602635700002302651700002402674700002102698700002902719700002202748700001602770700001902786700001802805700002102823700001802844700002602862700002202888700002102910700001802931700001602949700002002965700001902985700001803004700002403022700002503046700002203071700002103093700002203114700001703136700001703153700002003170700002103190700003303211700002403244700001703268700002203285700003403307700002503341700002203366700002103388700002103409700001903430700002203449700002003471700001903491700001403510700002503524700002103549700002503570700001703595700001403612700002303626700001803649700001703667700002203684700002103706700002203727700002403749700002103773700001903794700002203813700002103835700001903856700002603875700002103901700002003922700001903942700001903961700002503980700002004005700002304025700002404048700002204072700002304094700001404117700002004131700002004151700002004171700001904191700002104210700002204231700002404253700002104277700002504298700001804323700001704341700002104358700002404379710014304403856003604546 2022 eng d a1524-456300aInsights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension.0 aInsights From a LargeScale WholeGenome Sequencing Study of Systo c2022 Jun 02 a101161HYPERTENSIONAHA122193243 aBACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.
METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.
RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5×10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99×10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18×10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28×10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1×10 and <1×10, respectively).
DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
1 aKelly, Tanika, N1 aSun, Xiao1 aHe, Karen, Y1 aBrown, Michael, R1 aTaliun, Sarah, A Gagliano1 aHellwege, Jacklyn, N1 aIrvin, Marguerite, R1 aMi, Xuenan1 aBrody, Jennifer, A1 aFranceschini, Nora1 aGuo, Xiuqing1 aHwang, Shih-Jen1 ade Vries, Paul, S1 aGao, Yan1 aMoscati, Arden1 aNadkarni, Girish, N1 aYanek, Lisa, R1 aElfassy, Tali1 aSmith, Jennifer, A1 aChung, Ren-Hua1 aBeitelshees, Amber, L1 aPatki, Amit1 aAslibekyan, Stella1 aBlobner, Brandon, M1 aPeralta, Juan, M1 aAssimes, Themistocles, L1 aPalmas, Walter, R1 aLiu, Chunyu1 aBress, Adam, P1 aHuang, Zhijie1 aBecker, Lewis, C1 aHwa, Chii-Min1 aO'Connell, Jeffrey, R1 aCarlson, Jenna, C1 aWarren, Helen, R1 aDas, Sayantan1 aGiri, Ayush1 aMartin, Lisa, W1 aJohnson, Craig1 aFox, Ervin, R1 aBottinger, Erwin, P1 aRazavi, Alexander, C1 aVaidya, Dhananjay1 aChuang, Lee-Ming1 aChang, Yen-Pei, C1 aNaseri, Take1 aJain, Deepti1 aKang, Hyun, Min1 aHung, Adriana, M1 aSrinivasasainagendra, Vinodh1 aSnively, Beverly, M1 aGu, Dongfeng1 aMontasser, May, E1 aReupena, Muagututi'a, Sefuiva1 aHeavner, Benjamin, D1 aLeFaive, Jonathon1 aHixson, James, E1 aRice, Kenneth, M1 aWang, Fei, Fei1 aNielsen, Jonas, B1 aHuang, Jianfeng1 aKhan, Alyna, T1 aZhou, Wei1 aNierenberg, Jovia, L1 aLaurie, Cathy, C1 aArmstrong, Nicole, D1 aShi, Mengyao1 aPan, Yang1 aStilp, Adrienne, M1 aEmery, Leslie1 aWong, Quenna1 aHawley, Nicola, L1 aMinster, Ryan, L1 aCurran, Joanne, E1 aMunroe, Patricia, B1 aWeeks, Daniel, E1 aNorth, Kari, E1 aTracy, Russell, P1 aKenny, Eimear, E1 aShimbo, Daichi1 aChakravarti, Aravinda1 aRich, Stephen, S1 aReiner, Alex, P1 aBlangero, John1 aRedline, Susan1 aMitchell, Braxton, D1 aRao, Dabeeru, C1 aChen, Yii-Der, Ida1 aKardia, Sharon, L R1 aKaplan, Robert, C1 aMathias, Rasika, A1 aHe, Jiang1 aPsaty, Bruce, M1 aFornage, Myriam1 aLoos, Ruth, J F1 aCorrea, Adolfo1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aKooperberg, Charles1 aEdwards, Todd, L1 aAbecasis, Goncalo, R1 aZhu, Xiaofeng1 aLevy, Daniel1 aArnett, Donna, K1 aMorrison, Alanna, C1 aNHLBI Trans-Omics for Precision Medicine TOPMed) Consortium, The Samoan Obesity, Lifestyle, and Genetic Adaptations Study (OLaGA) Group† uhttps://chs-nhlbi.org/node/909905087nas a2201237 4500008004100000022001400041245010900055210006900164260001200233300001400245490000700259520156200266653002801828653003801856653003401894653001101928653003601939653001701975100002701992700001502019700002402034700002002058700002302078700001602101700002002117700001802137700001402155700001802169700001802187700002402205700002002229700002102249700002302270700001802293700002202311700002802333700002502361700002302386700002202409700002202431700002302453700002002476700001502496700001802511700001602529700001902545700002402564700002202588700002002610700001202630700002002642700002502662700001902687700002202706700002202728700002702750700002302777700002202800700001902822700002102841700001702862700002102879700001602900700002002916700002302936700002102959700002002980700002003000700002003020700001903040700002403059700001503083700002403098700002303122700002203145700002403167700002203191700001603213700001903229700002203248700002503270700002203295700002103317700002103338700002103359700001503380700002103395700002303416700002503439700002403464700002103488700002003509700002003529700002303549700002303572700001403595700001603609700002003625700003003645700002903675710003003704710003303734710001803767710002803785856003603813 2022 eng d a1546-170X00aLarge-scale genome-wide association study of coronary artery disease in genetically diverse populations.0 aLargescale genomewide association study of coronary artery disea c2022 08 a1679-16920 v283 aWe report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.
10aCoronary Artery Disease10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aPolymorphism, Single Nucleotide10aRisk Factors1 aTcheandjieu, Catherine1 aZhu, Xiang1 aHilliard, Austin, T1 aClarke, Shoa, L1 aNapolioni, Valerio1 aMa, Shining1 aLee, Kyung, Min1 aFang, Huaying1 aChen, Fei1 aLu, Yingchang1 aTsao, Noah, L1 aRaghavan, Sridharan1 aKoyama, Satoshi1 aGorman, Bryan, R1 aVujkovic, Marijana1 aKlarin, Derek1 aLevin, Michael, G1 aSinnott-Armstrong, Nasa1 aWojcik, Genevieve, L1 aPlomondon, Mary, E1 aMaddox, Thomas, M1 aWaldo, Stephen, W1 aBick, Alexander, G1 aPyarajan, Saiju1 aHuang, Jie1 aSong, Rebecca1 aHo, Yuk-Lam1 aBuyske, Steven1 aKooperberg, Charles1 aHaessler, Jeffrey1 aLoos, Ruth, J F1 aDo, Ron1 aVerbanck, Marie1 aChaudhary, Kumardeep1 aNorth, Kari, E1 aAvery, Christy, L1 aGraff, Mariaelisa1 aHaiman, Christopher, A1 aLe Marchand, Loïc1 aWilkens, Lynne, R1 aBis, Joshua, C1 aLeonard, Hampton1 aShen, Botong1 aLange, Leslie, A1 aGiri, Ayush1 aDikilitas, Ozan1 aKullo, Iftikhar, J1 aStanaway, Ian, B1 aJarvik, Gail, P1 aGordon, Adam, S1 aHebbring, Scott1 aNamjou, Bahram1 aKaufman, Kenneth, M1 aIto, Kaoru1 aIshigaki, Kazuyoshi1 aKamatani, Yoichiro1 aVerma, Shefali, S1 aRitchie, Marylyn, D1 aKember, Rachel, L1 aBaras, Aris1 aLotta, Luca, A1 aKathiresan, Sekar1 aHauser, Elizabeth, R1 aMiller, Donald, R1 aLee, Jennifer, S1 aSaleheen, Danish1 aReaven, Peter, D1 aCho, Kelly1 aGaziano, Michael1 aNatarajan, Pradeep1 aHuffman, Jennifer, E1 aVoight, Benjamin, F1 aRader, Daniel, J1 aChang, Kyong-Mi1 aLynch, Julie, A1 aDamrauer, Scott, M1 aWilson, Peter, W F1 aTang, Hua1 aSun, Yan, V1 aTsao, Philip, S1 aO'Donnell, Christopher, J1 aAssimes, Themistocles, L1 aRegeneron Genetics Center1 aCARDIoGRAMplusC4D Consortium1 aBiobank Japan1 aMillion Veteran Program uhttps://chs-nhlbi.org/node/917603474nas a2200565 4500008004100000022001400041245008100055210006900136260001600205520182300221100002002044700002402064700002102088700002202109700002002131700001802151700002502169700002602194700002902220700002502249700002002274700001902294700001902313700002402332700002102356700001602377700001902393700002502412700002302437700002402460700001802484700002002502700002102522700001902543700002502562700002502587700002402612700002002636700001902656700001902675700001902694700002102713700002202734700002402756700002202780700002402802700002402826700002202850856003602872 2022 eng d a1524-453900aMonogenic and Polygenic Contributions to QTc Prolongation in the Population.0 aMonogenic and Polygenic Contributions to QTc Prolongation in the c2022 Apr 073 a Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variation to the QT interval in the population. We performed a genome wide association study (GWAS) of the QTc in 84,630 United Kingdom Biobank (UKB) participants and created a polygenic risk score (PRS). Among 26,976 participants with whole genome sequencing and electrocardiogram data in the Trans-Omics for Precision Medicine (TOPMed) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed. Fifty-four independent loci were identified by GWAS in the UKB. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS comprising 1,110,494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/ = 1.4 ms, 95% CI 1.3 -1.5; p-value=1.1×10). Carriers of putative pathogenic rare variants had longer QTc than non-carriers (ΔQTc=10.9 ms [7.4-14.4]). 23.7% of individuals with QTc>480 ms carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS). QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.
1 aNauffal, Victor1 aMorrill, Valerie, N1 aJurgens, Sean, J1 aChoi, Seung, Hoan1 aHall, Amelia, W1 aWeng, Lu-Chen1 aHalford, Jennifer, L1 aAustin-Tse, Christina1 aHaggerty, Christopher, M1 aHarris, Stephanie, L1 aWong, Eugene, K1 aAlonso, Alvaro1 aArking, Dan, E1 aBenjamin, Emelia, J1 aBoerwinkle, Eric1 aMin, Yuan-I1 aCorrea, Adolfo1 aFornwalt, Brandon, K1 aHeckbert, Susan, R1 aKooperberg, Charles1 aLin, Henry, J1 aLoos, Ruth, J F1 aRice, Kenneth, M1 aGupta, Namrata1 aBlackwell, Thomas, W1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aPsaty, Bruce, M1 aPost, Wendy, S1 aRedline, Susan1 aRehm, Heidi, L1 aRich, Stephen, S1 aRotter, Jerome, I1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aLunetta, Kathryn, L1 aEllinor, Patrick, T1 aLubitz, Steven, A uhttps://chs-nhlbi.org/node/903813363nas a2204429 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2022 eng d a1546-171800aMulti-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.0 aMultiancestry genetic study of type 2 diabetes highlights the po c2022 May a560-5720 v543 aWe assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
10aDiabetes Mellitus, Type 210aEthnicity10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aPolymorphism, Single Nucleotide10aRisk Factors1 aMahajan, Anubha1 aSpracklen, Cassandra, N1 aZhang, Weihua1 aC Y Ng, Maggie1 aPetty, Lauren, E1 aKitajima, Hidetoshi1 aYu, Grace, Z1 aRüeger, Sina1 aSpeidel, Leo1 aKim, Young, Jin1 aHorikoshi, Momoko1 aMercader, Josep, M1 aTaliun, Daniel1 aMoon, Sanghoon1 aKwak, Soo-Heon1 aRobertson, Neil, R1 aRayner, Nigel, W1 aLoh, Marie1 aKim, Bong-Jo1 aChiou, Joshua1 aMiguel-Escalada, Irene1 aParolo, Pietro, Della Brio1 aLin, Kuang1 aBragg, Fiona1 aPreuss, Michael, H1 aTakeuchi, Fumihiko1 aNano, Jana1 aGuo, Xiuqing1 aLamri, Amel1 aNakatochi, Masahiro1 aScott, Robert, A1 aLee, Jung-Jin1 aHuerta-Chagoya, Alicia1 aGraff, Mariaelisa1 aChai, Jin-Fang1 aParra, Esteban, J1 aYao, Jie1 aBielak, Lawrence, F1 aTabara, Yasuharu1 aHai, Yang1 aSteinthorsdottir, Valgerdur1 aCook, James, P1 aKals, Mart1 aGrarup, Niels1 aSchmidt, Ellen, M1 aPan, Ian1 aSofer, Tamar1 aWuttke, Matthias1 aSarnowski, Chloe1 aGieger, Christian1 aNousome, Darryl1 aTrompet, Stella1 aLong, Jirong1 aSun, Meng1 aTong, Lin1 aChen, Wei-Min1 aAhmad, Meraj1 aNoordam, Raymond1 aJ Y Lim, Victor1 aTam, Claudia, H T1 aJoo, Yoonjung, Yoonie1 aChen, Chien-Hsiun1 aRaffield, Laura, M1 aLecoeur, Cécile1 aPrins, Bram, Peter1 aNicolas, Aude1 aYanek, Lisa, R1 aChen, Guanjie1 aJensen, Richard, A1 aTajuddin, Salman1 aKabagambe, Edmond, K1 aAn, Ping1 aXiang, Anny, H1 aChoi, Hyeok, Sun1 aCade, Brian, E1 aTan, Jingyi1 aFlanagan, Jack1 aAbaitua, Fernando1 aAdair, Linda, S1 aAdeyemo, Adebowale1 aAguilar-Salinas, Carlos, A1 aAkiyama, Masato1 aAnand, Sonia, S1 aBertoni, Alain1 aBian, Zheng1 aBork-Jensen, Jette1 aBrandslund, Ivan1 aBrody, Jennifer, A1 aBrummett, Chad, M1 aBuchanan, Thomas, A1 aCanouil, Mickaël1 aChan, Juliana, C N1 aChang, Li-Ching1 aChee, Miao-Li1 aChen, Ji1 aChen, Shyh-Huei1 aChen, Yuan-Tsong1 aChen, Zhengming1 aChuang, Lee-Ming1 aCushman, Mary1 aDas, Swapan, K1 ade Silva, Janaka1 aDedoussis, George1 aDimitrov, Latchezar1 aDoumatey, Ayo, P1 aDu, Shufa1 aDuan, Qing1 aEckardt, Kai-Uwe1 aEmery, Leslie, S1 aEvans, Daniel, S1 aEvans, Michele, K1 aFischer, Krista1 aFloyd, James, S1 aFord, Ian1 aFornage, Myriam1 aFranco, Oscar, H1 aFrayling, Timothy, M1 aFreedman, Barry, I1 aFuchsberger, Christian1 aGenter, Pauline1 aGerstein, Hertzel, C1 aGiedraitis, Vilmantas1 aGonzález-Villalpando, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGoodarzi, Mark, O1 aGordon-Larsen, Penny1 aGorkin, David1 aGross, Myron1 aGuo, Yu1 aHackinger, Sophie1 aHan, Sohee1 aHattersley, Andrew, T1 aHerder, Christian1 aHoward, Annie-Green1 aHsueh, Willa1 aHuang, Mengna1 aHuang, Wei1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aHwu, Chii-Min1 aIchihara, Sahoko1 aIkram, Mohammad, Arfan1 aIngelsson, Martin1 aIslam, Md, Tariqul1 aIsono, Masato1 aJang, Hye-Mi1 aJasmine, Farzana1 aJiang, Guozhi1 aJonas, Jost, B1 aJørgensen, Marit, E1 aJørgensen, Torben1 aKamatani, Yoichiro1 aKandeel, Fouad, R1 aKasturiratne, Anuradhani1 aKatsuya, Tomohiro1 aKaur, Varinderpal1 aKawaguchi, Takahisa1 aKeaton, Jacob, M1 aKho, Abel, N1 aKhor, Chiea-Chuen1 aKibriya, Muhammad, G1 aKim, Duk-Hwan1 aKohara, Katsuhiko1 aKriebel, Jennifer1 aKronenberg, Florian1 aKuusisto, Johanna1 aLäll, Kristi1 aLange, Leslie, A1 aLee, Myung-Shik1 aLee, Nanette, R1 aLeong, Aaron1 aLi, Liming1 aLi, Yun1 aLi-Gao, Ruifang1 aLigthart, Symen1 aLindgren, Cecilia, M1 aLinneberg, Allan1 aLiu, Ching-Ti1 aLiu, Jianjun1 aLocke, Adam, E1 aLouie, Tin1 aLuan, Jian'an1 aLuk, Andrea, O1 aLuo, Xi1 aLv, Jun1 aLyssenko, Valeriya1 aMamakou, Vasiliki1 aMani, Radha, K1 aMeitinger, Thomas1 aMetspalu, Andres1 aMorris, Andrew, D1 aNadkarni, Girish, N1 aNadler, Jerry, L1 aNalls, Michael, A1 aNayak, Uma1 aNongmaithem, Suraj, S1 aNtalla, Ioanna1 aOkada, Yukinori1 aOrozco, Lorena1 aPatel, Sanjay, R1 aPereira, Mark, A1 aPeters, Annette1 aPirie, Fraser, J1 aPorneala, Bianca1 aPrasad, Gauri1 aPreissl, Sebastian1 aRasmussen-Torvik, Laura, J1 aReiner, Alexander, P1 aRoden, Michael1 aRohde, Rebecca1 aRoll, Kathryn1 aSabanayagam, Charumathi1 aSander, Maike1 aSandow, Kevin1 aSattar, Naveed1 aSchönherr, Sebastian1 aSchurmann, Claudia1 aShahriar, Mohammad1 aShi, Jinxiu1 aShin, Dong, Mun1 aShriner, Daniel1 aSmith, Jennifer, A1 aSo, Wing, Yee1 aStančáková, Alena1 aStilp, Adrienne, M1 aStrauch, Konstantin1 aSuzuki, Ken1 aTakahashi, Atsushi1 aTaylor, Kent, D1 aThorand, Barbara1 aThorleifsson, Gudmar1 aThorsteinsdottir, Unnur1 aTomlinson, Brian1 aTorres, Jason, M1 aTsai, Fuu-Jen1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 aValladares-Salgado, Adan1 avan Dam, Rob, M1 avan Klinken, Jan, B1 aVarma, Rohit1 aVujkovic, Marijana1 aWacher-Rodarte, Niels1 aWheeler, Eleanor1 aWhitsel, Eric, A1 aWickremasinghe, Ananda, R1 aDijk, Ko Willems1 aWitte, Daniel, R1 aYajnik, Chittaranjan, S1 aYamamoto, Ken1 aYamauchi, Toshimasa1 aYengo, Loic1 aYoon, Kyungheon1 aYu, Canqing1 aYuan, Jian-Min1 aYusuf, Salim1 aZhang, Liang1 aZheng, Wei1 aRaffel, Leslie, J1 aIgase, Michiya1 aIpp, Eli1 aRedline, Susan1 aCho, Yoon Shin1 aLind, Lars1 aProvince, Michael, A1 aHanis, Craig, L1 aPeyser, Patricia, A1 aIngelsson, Erik1 aZonderman, Alan, B1 aPsaty, Bruce, M1 aWang, Ya-Xing1 aRotimi, Charles, N1 aBecker, Diane, M1 aMatsuda, Fumihiko1 aLiu, Yongmei1 aZeggini, Eleftheria1 aYokota, Mitsuhiro1 aRich, Stephen, S1 aKooperberg, Charles1 aPankow, James, S1 aEngert, James, C1 aChen, Yii-Der Ida1 aFroguel, Philippe1 aWilson, James, G1 aSheu, Wayne, H H1 aKardia, Sharon, L R1 aWu, Jer-Yuarn1 aHayes, Geoffrey1 aMa, Ronald, C W1 aWong, Tien-Yin1 aGroop, Leif1 aMook-Kanamori, Dennis, O1 aChandak, Giriraj, R1 aCollins, Francis, S1 aBharadwaj, Dwaipayan1 aParé, Guillaume1 aSale, Michèle, M1 aAhsan, Habibul1 aMotala, Ayesha, A1 aShu, Xiao-Ou1 aPark, Kyong-Soo1 aJukema, Wouter1 aCruz, Miguel1 aMcKean-Cowdin, Roberta1 aGrallert, Harald1 aCheng, Ching-Yu1 aBottinger, Erwin, P1 aDehghan, Abbas1 aTai, E-Shyong1 aDupuis, Josée1 aKato, Norihiro1 aLaakso, Markku1 aKöttgen, Anna1 aKoh, Woon-Puay1 aPalmer, Colin, N A1 aLiu, Simin1 aAbecasis, Goncalo1 aKooner, Jaspal, S1 aLoos, Ruth, J F1 aNorth, Kari, E1 aHaiman, Christopher, A1 aFlorez, Jose, C1 aSaleheen, Danish1 aHansen, Torben1 aPedersen, Oluf1 aMägi, Reedik1 aLangenberg, Claudia1 aWareham, Nicholas, J1 aMaeda, Shiro1 aKadowaki, Takashi1 aLee, Juyoung1 aMillwood, Iona, Y1 aWalters, Robin, G1 aStefansson, Kari1 aMyers, Simon, R1 aFerrer, Jorge1 aGaulton, Kyle, J1 aMeigs, James, B1 aMohlke, Karen, L1 aGloyn, Anna, L1 aBowden, Donald, W1 aBelow, Jennifer, E1 aChambers, John, C1 aSim, Xueling1 aBoehnke, Michael1 aRotter, Jerome, I1 aMcCarthy, Mark, I1 aMorris, Andrew, P1 aFinnGen1 aeMERGE Consortium uhttps://chs-nhlbi.org/node/910403010nas a2200697 4500008004100000022001400041245012100055210006900176260001600245300000900261490000700270520097500277653001001252653003001262653003801292653003401330653001101364653001701375653003101392653001501423653001701438100002501455700002401480700002101504700001801525700002201543700001901565700001701584700001901601700002001620700001801640700002201658700001301680700001901693700002301712700001301735700002401748700002201772700001401794700002001808700001501828700003201843700002101875700002701896700002101923700002001944700001901964700001901983700002402002700002002026700002202046700002002068700002202088700002102110700002402131700002302155700001702178700001702195710006402212856003602276 2022 eng d a2041-172300aA multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.0 amultiethnic polygenic risk score is associated with hypertension c2022 Jun 21 a35490 v133 aIn a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.
10aAdult10aDiabetes Mellitus, Type 210aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aHypertension10aMultifactorial Inheritance10aPrevalence10aRisk Factors1 aKurniansyah, Nuzulul1 aGoodman, Matthew, O1 aKelly, Tanika, N1 aElfassy, Tali1 aWiggins, Kerri, L1 aBis, Joshua, C1 aGuo, Xiuqing1 aPalmas, Walter1 aTaylor, Kent, D1 aLin, Henry, J1 aHaessler, Jeffrey1 aGao, Yan1 aShimbo, Daichi1 aSmith, Jennifer, A1 aYu, Bing1 aFeofanova, Elena, V1 aSmit, Roelof, A J1 aWang, Zhe1 aHwang, Shih-Jen1 aLiu, Simin1 aWassertheil-Smoller, Sylvia1 aManson, JoAnn, E1 aLloyd-Jones, Donald, M1 aRich, Stephen, S1 aLoos, Ruth, J F1 aRedline, Susan1 aCorrea, Adolfo1 aKooperberg, Charles1 aFornage, Myriam1 aKaplan, Robert, C1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aArnett, Donna, K1 aMorrison, Alanna, C1 aFranceschini, Nora1 aLevy, Daniel1 aSofer, Tamar1 aNHLBI Trans-Omics in Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/910008881nas a2202605 4500008004100000022001400041245012200055210006900177260001500246300001000261490000800271520141300279653001201692653001801704653002501722653002601747653002301773653003001796653001001826653003801836653002201874653002501896653003401921653001101955653002101966653001101987653001001998653003402008653003102042653002402073653001402097653003602111100001802147700001902165700002102184700002002205700001802225700003202243700001702275700001702292700003102309700003002340700002102370700002102391700002302412700001602435700002802451700002902479700001802508700002102526700002402547700001902571700001902590700002102609700002502630700002102655700002202676700002102698700002302719700001902742700001902761700001902780700002702799700001702826700002002843700002102863700002002884700002002904700001902924700002902943700002402972700001902996700002503015700002203040700001703062700002203079700002303101700002403124700002803148700002203176700002403198700002103222700002003243700002003263700002303283700002103306700003103327700002803358700001803386700002203404700002203426700002103448700002303469700003903492700002203531700002103553700001803574700001903592700001703611700001903628700001503647700002003662700001903682700001403701700002603715700001703741700002103758700002503779700002603804700002003830700002003850700002403870700001803894700002103912700001903933700001703952700001703969700002003986700002504006700002404031700002204055700002004077700001904097700002104116700001504137700001704152700001804169700002104187700002404208700002104232700001704253700002004270700002204290700002304312700002004335700002804355700003604383700002304419700002504442700002004467700002004487700002204507700001904529700002604548700002304574700001504597700002104612700002204633700002004655700002904675700002404704700002004728700002104748700002204769700002604791700002504817700001904842700002304861700002604884700002104910700002104931700001904952700002104971700002404992700001905016700002005035700002005055700001405075700001405089700001905103700002505122700003105147700002105178700001905199700002405218700002305242700001705265700001905282700001705301700001605318700002105334700001805355700002305373700001905396700002205415700002005437700001905457700002005476700002105496700002105517700002205538700002305560700002405583700002105607700002005628700002705648700003005675700001905705700001605724700001805740700002105758700002105779700002105800700001905821700001905840700002205859700002105881700002205902700002105924700002205945700002305967700002305990700002306013700001906036700002006055710006106075710006506136710003806201856003606239 2022 eng d a1537-660500aRare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.0 aRare coding variants in 35 genes associate with circulating lipi c2022 01 06 a81-960 v1093 aLarge-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
10aAlleles10aBlood Glucose10aCase-Control Studies10aComputational Biology10aDatabases, Genetic10aDiabetes Mellitus, Type 210aExome10aGenetic Predisposition to Disease10aGenetic Variation10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLipid Metabolism10aLipids10aLiver10aMolecular Sequence Annotation10aMultifactorial Inheritance10aOpen Reading Frames10aPhenotype10aPolymorphism, Single Nucleotide1 aHindy, George1 aDornbos, Peter1 aChaffin, Mark, D1 aLiu, Dajiang, J1 aWang, Minxian1 aSelvaraj, Margaret, Sunitha1 aZhang, David1 aPark, Joseph1 aAguilar-Salinas, Carlos, A1 aAntonacci-Fulton, Lucinda1 aArdissino, Diego1 aArnett, Donna, K1 aAslibekyan, Stella1 aAtzmon, Gil1 aBallantyne, Christie, M1 aBarajas-Olmos, Francisco1 aBarzilai, Nir1 aBecker, Lewis, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBottinger, Erwin1 aBowden, Donald, W1 aBown, Matthew, J1 aBrody, Jennifer, A1 aBroome, Jai, G1 aBurtt, Noel, P1 aCade, Brian, E1 aCenteno-Cruz, Federico1 aChan, Edmund1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aCheng, Ching-Yu1 aChoi, Won, Jung1 aChowdhury, Raj1 aContreras-Cubas, Cecilia1 aCórdova, Emilio, J1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDanesh, John1 ade Vries, Paul, S1 aDeFronzo, Ralph, A1 aDoddapaneni, Harsha1 aDuggirala, Ravindranath1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aFlorez, Jose, C1 aFornage, Myriam1 aFreedman, Barry, I1 aFuster, Valentin1 aGaray-Sevilla, Ma, Eugenia1 aGarcía-Ortiz, Humberto1 aGermer, Soren1 aGibbs, Richard, A1 aGieger, Christian1 aGlaser, Benjamin1 aGonzalez, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGraff, Mariaelisa1 aGraham, Sarah, E1 aGrarup, Niels1 aGroop, Leif, C1 aGuo, Xiuqing1 aGupta, Namrata1 aHan, Sohee1 aHanis, Craig, L1 aHansen, Torben1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aIrvin, Marguerite, R1 aIslas-Andrade, Sergio1 aJarvik, Gail, P1 aKang, Hyun, Min1 aKardia, Sharon, L R1 aKelly, Tanika1 aKenny, Eimear, E1 aKhan, Alyna, T1 aKim, Bong-Jo1 aKim, Ryan, W1 aKim, Young, Jin1 aKoistinen, Heikki, A1 aKooperberg, Charles1 aKuusisto, Johanna1 aKwak, Soo, Heon1 aLaakso, Markku1 aLange, Leslie, A1 aLee, Jiwon1 aLee, Juyoung1 aLee, Seonwook1 aLehman, Donna, M1 aLemaitre, Rozenn, N1 aLinneberg, Allan1 aLiu, Jianjun1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aLyssenko, Valeriya1 aMa, Ronald, C W1 aMartin, Lisa, Warsinger1 aMartínez-Hernández, Angélica1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMcPherson, Ruth1 aMeigs, James, B1 aMeitinger, Thomas1 aMelander, Olle1 aMendoza-Caamal, Elvia1 aMetcalf, Ginger, A1 aMi, Xuenan1 aMohlke, Karen, L1 aMontasser, May, E1 aMoon, Jee-Young1 aMoreno-Macias, Hortensia1 aMorrison, Alanna, C1 aMuzny, Donna, M1 aNelson, Sarah, C1 aNilsson, Peter, M1 aO'Connell, Jeffrey, R1 aOrho-Melander, Marju1 aOrozco, Lorena1 aPalmer, Colin, N A1 aPalmer, Nicholette, D1 aPark, Cheol, Joo1 aPark, Kyong, Soo1 aPedersen, Oluf1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aPost, Wendy, S1 aPreuss, Michael1 aPsaty, Bruce, M1 aQi, Qibin1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRevilla-Monsalve, Cristina1 aRich, Stephen, S1 aSamani, Nilesh1 aSchunkert, Heribert1 aSchurmann, Claudia1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSim, Xueling1 aSladek, Rob1 aSmall, Kerrin, S1 aSo, Wing, Yee1 aStilp, Adrienne, M1 aTai, Shyong, E1 aTam, Claudia, H T1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aThameem, Farook1 aTomlinson, Brian1 aTsai, Michael, Y1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 avan Dam, Rob, M1 aVasan, Ramachandran, S1 aMartinez, Karine, A Viaud1 aWang, Fei, Fei1 aWang, Xuzhi1 aWatkins, Hugh1 aWeeks, Daniel, E1 aWilson, James, G1 aWitte, Daniel, R1 aWong, Tien-Yin1 aYanek, Lisa, R1 aKathiresan, Sekar1 aRader, Daniel, J1 aRotter, Jerome, I1 aBoehnke, Michael1 aMcCarthy, Mark, I1 aWiller, Cristen, J1 aNatarajan, Pradeep1 aFlannick, Jason, A1 aKhera, Amit, V1 aPeloso, Gina, M1 aAMP-T2D-GENES, Myocardial Infarction Genetics Consortium1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aNHLBI TOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/897504507nas a2201189 4500008004100000022001400041245006700055210006600122260001600188520113600204100002201340700001601362700002401378700002101402700002801423700002401451700002101475700001901496700001901515700002401534700002901558700002201587700002301609700001901632700003201651700002101683700001901704700002501723700001801748700002301766700001901789700002301808700002201831700002401853700002001877700002301897700002401920700002001944700002001964700002201984700002302006700002202029700001602051700002002067700002202087700001602109700002102125700002202146700002402168700001902192700001502211700002402226700001702250700002702267700002002294700002402314700002102338700002802359700001902387700001902406700002302425700002802448700001902476700002602495700002602521700002202547700002002569700002402589700002002613700002002633700001602653700002102669700002202690700001902712700002002731700002502751700002102776700002202797700002302819700002402842700002402866700002302890700001802913700002102931700002302952700001802975700002002993700002203013700002703035700002303062700001403085700002203099700001903121700001903140700002103159700002203180700001803202700002003220700002303240700001803263856003603281 2022 eng d a2397-337400aRare genetic variants explain missing heritability in smoking.0 aRare genetic variants explain missing heritability in smoking c2022 Aug 043 aCommon genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
1 aJang, Seon-Kyeong1 aEvans, Luke1 aFialkowski, Allison1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBecker, Diane, M1 aBis, Joshua, C1 aBlangero, John1 aBleecker, Eugene, R1 aBoorgula, Meher, Preethi1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aJenkins, Brenda, W Campbell1 aCarson, April, P1 aChavan, Sameer1 aCupples, Adrienne, L1 aCuster, Brian1 aDamrauer, Scott, M1 aDavid, Sean, P1 ade Andrade, Mariza1 aDinardo, Carla, L1 aFingerlin, Tasha, E1 aFornage, Myriam1 aFreedman, Barry, I1 aGarrett, Melanie, E1 aGharib, Sina, A1 aGlahn, David, C1 aHaessler, Jeffrey1 aHeckbert, Susan, R1 aHokanson, John, E1 aHou, Lifang1 aHwang, Shih-Jen1 aHyman, Matthew, C1 aJudy, Renae1 aJustice, Anne, E1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKelly, Shannon1 aKim, Wonji1 aKooperberg, Charles1 aLevy, Daniel1 aLloyd-Jones, Donald, M1 aLoos, Ruth, J F1 aManichaikul, Ani, W1 aGladwin, Mark, T1 aMartin, Lisa, Warsinger1 aNouraie, Mehdi1 aMelander, Olle1 aMeyers, Deborah, A1 aMontgomery, Courtney, G1 aNorth, Kari, E1 aOelsner, Elizabeth, C1 aPalmer, Nicholette, D1 aPayton, Marinelle1 aPeljto, Anna, L1 aPeyser, Patricia, A1 aPreuss, Michael1 aPsaty, Bruce, M1 aQiao, Dandi1 aRader, Daniel, J1 aRafaels, Nicholas1 aRedline, Susan1 aReed, Robert, M1 aReiner, Alexander, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aSchwartz, David, A1 aShadyab, Aladdin, H1 aSilverman, Edwin, K1 aSmith, Nicholas, L1 aSmith, Gustav1 aSmith, Albert, V1 aSmith, Jennifer, A1 aTang, Weihong1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aVasan, Ramachandran, S1 aGordeuk, Victor, R1 aWang, Zhe1 aWiggins, Kerri, L1 aYanek, Lisa, R1 aYang, Ivana, V1 aYoung, Kendra, A1 aYoung, Kristin, L1 aZhang, Yingze1 aLiu, Dajiang, J1 aKeller, Matthew, C1 aVrieze, Scott uhttps://chs-nhlbi.org/node/916804203nas a2200697 4500008004100000022001400041245011000055210006900165260000900234300001100243490000700254520220700261653001902468653002202487653003402509653001102543653001202554653002802566100001402594700002102608700002002629700002102649700002002670700001902690700001902709700002302728700002002751700001502771700002802786700002402814700002402838700001802862700002702880700002102907700002302928700001902951700002102970700002102991700001903012700001903031700002303050700002303073700001703096700002103113700002103134700002203155700002403177700002203201700001903223700002403242700001903266700002103285700002503306700002303331700002403354700002403378700002503402700002203427700002003449856003603469 2022 eng d a1664-239200aThe Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations.0 aValue of Rare Genetic Variation in the Prediction of Common Obes c2022 a8638930 v133 aPolygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRS) with a rare variant PRS (PRS) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m), obesity (BMI ≥ 30 kg/m), and extreme obesity (BMI ≥ 40 kg/m). We built PRSs and PRSs using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRS explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRS explained 1.49%, and 2.97% and 3.68%, respectively. The PRS was associated with an increased risk of obesity and extreme obesity (OR = 1.37 per SD, = 1.7x10; OR = 1.55 per SD, = 3.8x10), which was attenuated, after adjusting for PRS (OR = 1.08 per SD, = 9.8x10; OR= 1.09 per SD, = 0.02). When PRS and PRS are combined, the increase in explained variance attributed to PRS was small (incremental Nagelkerke R = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS to PRS provided little improvement to the prediction of obesity (PRS AUC = 0.591; PRS AUC = 0.708; PRS AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS provides limited improvement over PRS in the prediction of obesity risk, based on these large populations.
10aGene Frequency10aGenetic Variation10aGenome-Wide Association Study10aHumans10aObesity10aWhole Genome Sequencing1 aWang, Zhe1 aChoi, Shing, Wan1 aChami, Nathalie1 aBoerwinkle, Eric1 aFornage, Myriam1 aRedline, Susan1 aBis, Joshua, C1 aBrody, Jennifer, A1 aPsaty, Bruce, M1 aKim, Wonji1 aMcDonald, Merry-Lynn, N1 aRegan, Elizabeth, A1 aSilverman, Edwin, K1 aLiu, Ching-Ti1 aVasan, Ramachandran, S1 aKalyani, Rita, R1 aMathias, Rasika, A1 aYanek, Lisa, R1 aArnett, Donna, K1 aJustice, Anne, E1 aNorth, Kari, E1 aKaplan, Robert1 aHeckbert, Susan, R1 ade Andrade, Mariza1 aGuo, Xiuqing1 aLange, Leslie, A1 aRich, Stephen, S1 aRotter, Jerome, I1 aEllinor, Patrick, T1 aLubitz, Steven, A1 aBlangero, John1 aShoemaker, Benjamin1 aDarbar, Dawood1 aGladwin, Mark, T1 aAlbert, Christine, M1 aChasman, Daniel, I1 aJackson, Rebecca, D1 aKooperberg, Charles1 aReiner, Alexander, P1 aO'Reilly, Paul, F1 aLoos, Ruth, J F uhttps://chs-nhlbi.org/node/910905141nas a2201381 4500008004100000022001400041245014300055210006900198260001500267300000800282490000600290520117000296653003001466653001201496653001201508653001101520653001201531653005301543653002601596653003601622653002301658653002701681653001801708100002001726700002201746700002201768700002601790700002301816700002501839700001501864700002101879700002501900700001801925700002401943700002201967700002301989700002002012700001702032700002002049700002602069700001902095700002202114700001902136700001702155700001702172700003302189700002102222700001902243700001802262700002602280700002002306700002102326700002302347700002602370700002202396700002402418700002302442700002202465700002002487700002202507700002002529700002502549700002102574700002102595700001802616700001802634700002002652700002102672700002102693700001702714700002102731700003102752700002502783700003402808700002202842700002302864700002102887700001602908700001302924700001402937700002002951700001902971700002102990700001903011700002103030700001903051700002503070700002203095700002803117700001403145700002303159700002403182700001703206700002403223700001503247700002303262700002503285700002503310700002403335700002403359700002003383700001903403700002303422700002003445700002703465700003003492700002003522700002103542700001903563700002103582700002203603700001603625700001903641700002003660700002103680700002203701856003603723 2022 eng d a2399-364200aWhole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program.0 aWhole genome sequence association analysis of fasting glucose an c2022 07 28 a7560 v53 aThe genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.
10aDiabetes Mellitus, Type 210aFasting10aGlucose10aHumans10aInsulin10aNational Heart, Lung, and Blood Institute (U.S.)10aNerve Tissue Proteins10aPolymorphism, Single Nucleotide10aPrecision Medicine10aReceptors, Immunologic10aUnited States1 aDiCorpo, Daniel1 aGaynor, Sheila, M1 aRussell, Emily, M1 aWesterman, Kenneth, E1 aRaffield, Laura, M1 aMajarian, Timothy, D1 aWu, Peitao1 aSarnowski, Chloe1 aHighland, Heather, M1 aJackson, Anne1 aHasbani, Natalie, R1 ade Vries, Paul, S1 aBrody, Jennifer, A1 aHidalgo, Bertha1 aGuo, Xiuqing1 aPerry, James, A1 aO'Connell, Jeffrey, R1 aLent, Samantha1 aMontasser, May, E1 aCade, Brian, E1 aJain, Deepti1 aWang, Heming1 aAlbanus, Ricardo, D'Oliveira1 aVarshney, Arushi1 aYanek, Lisa, R1 aLange, Leslie1 aPalmer, Nicholette, D1 aAlmeida, Marcio1 aPeralta, Juan, M1 aAslibekyan, Stella1 aBaldridge, Abigail, S1 aBertoni, Alain, G1 aBielak, Lawrence, F1 aChen, Chung-Shiuan1 aChen, Yii-Der Ida1 aChoi, Won, Jung1 aGoodarzi, Mark, O1 aFloyd, James, S1 aIrvin, Marguerite, R1 aKalyani, Rita, R1 aKelly, Tanika, N1 aLee, Seonwook1 aLiu, Ching-Ti1 aLoesch, Douglas1 aManson, JoAnn, E1 aMinster, Ryan, L1 aNaseri, Take1 aPankow, James, S1 aRasmussen-Torvik, Laura, J1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aSelvin, Elizabeth1 aSmith, Jennifer, A1 aWeeks, Daniel, E1 aXu, Huichun1 aYao, Jie1 aZhao, Wei1 aParker, Stephen1 aAlonso, Alvaro1 aArnett, Donna, K1 aBlangero, John1 aBoerwinkle, Eric1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDuggirala, Ravindranath1 aHe, Jiang1 aHeckbert, Susan, R1 aKardia, Sharon, L R1 aKim, Ryan, W1 aKooperberg, Charles1 aLiu, Simin1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRedline, Susan1 aShuldiner, Alan, R1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aViaud-Martinez, Karine, A1 aFlorez, Jose, C1 aWilson, James, G1 aSladek, Robert1 aRich, Stephen, S1 aRotter, Jerome, I1 aLin, Xihong1 aDupuis, Josée1 aMeigs, James, B1 aWessel, Jennifer1 aManning, Alisa, K uhttps://chs-nhlbi.org/node/915804169nas a2200757 4500008004100000022001400041245010600055210006900161260001600230520193200246100001402178700001402192700001502206700001802221700001702239700002102256700001702277700002002294700002302314700001802337700001902355700002102374700002302395700002202418700002402440700002602464700001802490700002102508700001702529700002002546700002502566700002302591700001902614700002202633700002202655700002002677700002702697700001602724700002302740700002502763700002402788700002402812700002102836700001902857700002302876700002702899700002102926700001702947700002202964700001902986700002203005700002403027700002503051700002003076700002203096700002203118700002403140700002003164700002103184700001403205700002103219710006503240710004103305710002903346856003603375 2022 eng d a1460-208300aWhole-Exome Sequencing Study Identifies Four Novel Gene Loci Associated with Diabetic Kidney Disease.0 aWholeExome Sequencing Study Identifies Four Novel Gene Loci Asso c2022 Nov 293 aDiabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease (CKD) and diabetes. Our two-stage whole-exome sequencing study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort (CRIC) and Atherosclerosis Risk in Communities (ARIC) studies (stage-1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine (TOPMed) participants (stage-2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex, and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test (SKAT-O) implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds (95% confidence interval: 33.6, 1105) of DKD compared with non-carriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% confidence interval: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.
1 aPan, Yang1 aSun, Xiao1 aMi, Xuenan1 aHuang, Zhijie1 aHsu, Yenchih1 aHixson, James, E1 aMunzy, Donna1 aMetcalf, Ginger1 aFranceschini, Nora1 aTin, Adrienne1 aKöttgen, Anna1 aFrancis, Michael1 aBrody, Jennifer, A1 aKestenbaum, Bryan1 aSitlani, Colleen, M1 aMychaleckyj, Josyf, C1 aKramer, Holly1 aLange, Leslie, A1 aGuo, Xiuqing1 aHwang, Shih-Jen1 aIrvin, Marguerite, R1 aSmith, Jennifer, A1 aYanek, Lisa, R1 aVaidya, Dhananjay1 aChen, Yii-Der Ida1 aFornage, Myriam1 aLloyd-Jones, Donald, M1 aHou, Lifang1 aMathias, Rasika, A1 aMitchell, Braxton, D1 aPeyser, Patricia, A1 aKardia, Sharon, L R1 aArnett, Donna, K1 aCorrea, Adolfo1 aRaffield, Laura, M1 aVasan, Ramachandran, S1 aCupple, Adrienne1 aLevy, Daniel1 aKaplan, Robert, C1 aNorth, Kari, E1 aRotter, Jerome, I1 aKooperberg, Charles1 aReiner, Alexander, P1 aPsaty, Bruce, M1 aTracy, Russell, P1 aGibbs, Richard, A1 aMorrison, Alanna, C1 aFeldman, Harold1 aBoerwinkle, Eric1 aHe, Jiang1 aKelly, Tanika, N1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Kidney Function Working Group1 aCRIC Study Investigators uhttps://chs-nhlbi.org/node/925806073nas a2201597 4500008004100000022001400041245008800055210006900143260001300212300001200225490000800237520158400245653001201829653001201841653002501853653003401878653001801912653002901930653001101959653000901970653001301979653003001992100002502022700002802047700002902075700002202104700001902126700001902145700001702164700001802181700001702199700001302216700002202229700001902251700002602270700002602296700002302322700001902345700002002364700001702384700002202401700003102423700001902454700002302473700002602496700002102522700002102543700002402564700002002588700002102608700002002629700002002649700001602669700002702685700001902712700001902731700002002750700001902770700002302789700002402812700001802836700001602854700002602870700002302896700002202919700002002941700001902961700002702980700001903007700002103026700002403047700002403071700001403095700002203109700001503131700001903146700002303165700002303188700002203211700002103233700002503254700001903279700002303298700001903321700002203340700001903362700002303381700001303404700002303417700002203440700002103462700002203483700002303505700002103528700002303549700001803572700001903590700002203609700002103631700002803652700002203680700001903702700002203721700002003743700001703763700001403780700001603794700002203810700001803832700002303850700001803873700002403891700002403915700001903939700001803958700002203976700002403998700001504022700002104037700001804058700002304076700002304099700002504122700002504147700002104172700001804193700002504211700002304236700002204259700002104281700002504302700002304327700002404350710006504374856003604439 2023 eng d a1476-468700aAberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis.0 aAberrant activation of TCL1A promotes stem cell expansion in clo c2023 Apr a755-7630 v6163 aMutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis. These lesions are precursors for blood cancers, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.
10aAlleles10aAnimals10aClonal Hematopoiesis10aGenome-Wide Association Study10aHematopoiesis10aHematopoietic Stem Cells10aHumans10aMice10aMutation10aPromoter Regions, Genetic1 aWeinstock, Joshua, S1 aGopakumar, Jayakrishnan1 aBurugula, Bala, Bharathi1 aUddin, Md, Mesbah1 aJahn, Nikolaus1 aBelk, Julia, A1 aBouzid, Hind1 aDaniel, Bence1 aMiao, Zhuang1 aLy, Nghi1 aMack, Taralynn, M1 aLuna, Sofia, E1 aProthro, Katherine, P1 aMitchell, Shaneice, R1 aLaurie, Cecelia, A1 aBroome, Jai, G1 aTaylor, Kent, D1 aGuo, Xiuqing1 aSinner, Moritz, F1 avon Falkenhausen, Aenne, S1 aKääb, Stefan1 aShuldiner, Alan, R1 aO'Connell, Jeffrey, R1 aLewis, Joshua, P1 aBoerwinkle, Eric1 aBarnes, Kathleen, C1 aChami, Nathalie1 aKenny, Eimear, E1 aLoos, Ruth, J F1 aFornage, Myriam1 aHou, Lifang1 aLloyd-Jones, Donald, M1 aRedline, Susan1 aCade, Brian, E1 aPsaty, Bruce, M1 aBis, Joshua, C1 aBrody, Jennifer, A1 aSilverman, Edwin, K1 aYun, Jeong, H1 aQiao, Dandi1 aPalmer, Nicholette, D1 aFreedman, Barry, I1 aBowden, Donald, W1 aCho, Michael, H1 aDeMeo, Dawn, L1 aVasan, Ramachandran, S1 aYanek, Lisa, R1 aBecker, Lewis, C1 aKardia, Sharon, L R1 aPeyser, Patricia, A1 aHe, Jiang1 aRienstra, Michiel1 aHarst, Pim1 aKaplan, Robert1 aHeckbert, Susan, R1 aSmith, Nicholas, L1 aWiggins, Kerri, L1 aArnett, Donna, K1 aIrvin, Marguerite, R1 aTiwari, Hemant1 aCutler, Michael, J1 aKnight, Stacey1 aMuhlestein, Brent1 aCorrea, Adolfo1 aRaffield, Laura, M1 aGao, Yan1 ade Andrade, Mariza1 aRotter, Jerome, I1 aRich, Stephen, S1 aTracy, Russell, P1 aKonkle, Barbara, A1 aJohnsen, Jill, M1 aWheeler, Marsha, M1 aSmith, Gustav1 aMelander, Olle1 aNilsson, Peter, M1 aCuster, Brian, S1 aDuggirala, Ravindranath1 aCurran, Joanne, E1 aBlangero, John1 aMcGarvey, Stephen1 aWilliams, Keoki1 aXiao, Shujie1 aYang, Mao1 aGu, Charles1 aChen, Yii-Der Ida1 aLee, Wen-Jane1 aMarcus, Gregory, M1 aKane, John, P1 aPullinger, Clive, R1 aShoemaker, Benjamin1 aDarbar, Dawood1 aRoden, Dan, M1 aAlbert, Christine1 aKooperberg, Charles1 aZhou, Ying1 aManson, JoAnn, E1 aDesai, Pinkal1 aJohnson, Andrew, D1 aMathias, Rasika, A1 aBlackwell, Thomas, W1 aAbecasis, Goncalo, R1 aSmith, Albert, V1 aKang, Hyun, M1 aSatpathy, Ansuman, T1 aNatarajan, Pradeep1 aKitzman, Jacob, O1 aWhitsel, Eric, A1 aReiner, Alexander, P1 aBick, Alexander, G1 aJaiswal, Siddhartha1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/938703922nas a2200673 4500008004100000022001400041245014500055210006900200260001600269300001200285520190200297100001302199700001802212700001902230700001902249700001402268700002202282700002302304700002402327700001402351700002702365700002202392700001702414700002502431700001302456700001702469700001502486700002402501700002102525700002102546700002002567700002402587700002302611700002002634700002102654700002002675700002402695700002302719700002702742700002802769700002002797700001402817700002102831700002202852700001902874700002202893700002402915700001602939700002002955700002102975700001702996700002203013700001903035700002603054700001903080700001603099710009703115856003603212 2023 eng d a2047-998000aAssociation Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk.0 aAssociation Between Whole BloodDerived Mitochondrial DNA Copy Nu c2023 Oct 07 ae0290903 aBackground The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.
1 aLiu, Xue1 aSun, Xianbang1 aZhang, Yuankai1 aJiang, Wenqing1 aLai, Meng1 aWiggins, Kerri, L1 aRaffield, Laura, M1 aBielak, Lawrence, F1 aZhao, Wei1 aPitsillides, Achilleas1 aHaessler, Jeffrey1 aZheng, Yinan1 aBlackwell, Thomas, W1 aYao, Jie1 aGuo, Xiuqing1 aQian, Yong1 aThyagarajan, Bharat1 aPankratz, Nathan1 aRich, Stephen, S1 aTaylor, Kent, D1 aPeyser, Patricia, A1 aHeckbert, Susan, R1 aSeshadri, Sudha1 aBoerwinkle, Eric1 aGrove, Megan, L1 aLarson, Nicholas, B1 aSmith, Jennifer, A1 aVasan, Ramachandran, S1 aFitzpatrick, Annette, L1 aFornage, Myriam1 aDing, Jun1 aCarson, April, P1 aAbecasis, Goncalo1 aDupuis, Josée1 aReiner, Alexander1 aKooperberg, Charles1 aHou, Lifang1 aPsaty, Bruce, M1 aWilson, James, G1 aLevy, Daniel1 aRotter, Jerome, I1 aBis, Joshua, C1 aSatizabal, Claudia, L1 aArking, Dan, E1 aLiu, Chunyu1 aTOPMed mtDNA Working Group in NHLBI Trans‐Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/950204742nas a2200769 4500008004100000245009400041210006900135260001600204520254400220100002502764700001802789700002402807700002102831700002402852700001802876700001602894700002502910700001602935700002202951700001202973700002102985700002003006700002003026700002403046700001903070700002003089700002003109700002103129700002003150700002003170700001603190700001903206700001903225700002303244700002003267700002703287700002603314700002303340700002203363700001903385700001903404700002103423700002403444700002403468700001803492700002103510700002103531700002303552700002103575700001903596700002103615700002003636700001703656700002403673700002203697700001903719700002003738700002503758700001203783700002903795700002403824700002303848700002203871700002203893700002103915856003603936 2023 eng d00aCarriers of rare damaging genetic variants are at lower risk of atherosclerotic disease.0 aCarriers of rare damaging genetic variants are at lower risk of c2023 Aug 163 aBACKGROUND: The CCL2/CCR2 axis governs monocyte trafficking and recruitment to atherosclerotic lesions. Human genetic analyses and population-based studies support an association between circulating CCL2 levels and atherosclerosis. Still, it remains unknown whether pharmacological targeting of CCR2, the main CCL2 receptor, would provide protection against human atherosclerotic disease.
METHODS: In whole-exome sequencing data from 454,775 UK Biobank participants (40-69 years), we identified predicted loss-of-function (LoF) or damaging missense (REVEL score >0.5) variants within the gene. We prioritized variants associated with lower monocyte count (p<0.05) and tested associations with vascular risk factors and risk of atherosclerotic disease over a mean follow-up of 14 years. The results were replicated in a pooled cohort of three independent datasets (TOPMed, deCODE and Penn Medicine BioBank; total n=441,445) and the effect of the most frequent damaging variant was experimentally validated.
RESULTS: A total of 45 predicted LoF or damaging missense variants were identified in the gene, 4 of which were also significantly associated with lower monocyte count, but not with other white blood cell counts. Heterozygous carriers of these variants were at a lower risk of a combined atherosclerosis outcome, showed a lower burden of atherosclerosis across four vascular beds, and were at a lower lifetime risk of coronary artery disease and myocardial infarction. There was no evidence of association with vascular risk factors including LDL-cholesterol, blood pressure, glycemic status, or C-reactive protein. Using a cAMP assay, we found that cells transfected with the most frequent damaging variant (3:46358273:T:A, M249K, 547 carriers, frequency: 0.14%) show a decrease in signaling in response to CCL2. The associations of the M249K variant with myocardial infarction were consistent across cohorts (OR : 0.62 95%CI: 0.39-0.96; OR : 0.64 95%CI: 0.34-1.19; OR : 0.64 95%CI: 0.45-0.90). In a phenome-wide association study, we found no evidence for higher risk of common infections or mortality among carriers of damaging variants.
CONCLUSIONS: Heterozygous carriers of damaging variants have a lower burden of atherosclerosis and lower lifetime risk of myocardial infarction. In conjunction with previous evidence from experimental and epidemiological studies, our findings highlight the translational potential of CCR2-targeting as an atheroprotective approach.
1 aGeorgakis, Marios, K1 aMalik, Rainer1 aHasbani, Natalie, R1 aShakt, Gabrielle1 aMorrison, Alanna, C1 aTsao, Noah, L1 aJudy, Renae1 aMitchell, Braxton, D1 aXu, Huichun1 aMontasser, May, E1 aDo, Ron1 aKenny, Eimear, E1 aLoos, Ruth, J F1 aTerry, James, G1 aCarr, John, Jeffrey1 aBis, Joshua, C1 aPsaty, Bruce, M1 aLongstreth, W T1 aYoung, Kendra, A1 aLutz, Sharon, M1 aCho, Michael, H1 aBroome, Jai1 aKhan, Alyna, T1 aWang, Fei, Fei1 aHeard-Costa, Nancy1 aSeshadri, Sudha1 aVasan, Ramachandran, S1 aPalmer, Nicholette, D1 aFreedman, Barry, I1 aBowden, Donald, W1 aYanek, Lisa, R1 aKral, Brian, G1 aBecker, Lewis, C1 aPeyser, Patricia, A1 aBielak, Lawrence, F1 aAmmous, Farah1 aCarson, April, P1 aHall, Michael, E1 aRaffield, Laura, M1 aRich, Stephen, S1 aPost, Wendy, S1 aTracy, Russel, P1 aTaylor, Kent, D1 aGuo, Xiuqing1 aMahaney, Michael, C1 aCurran, Joanne, E1 aBlangero, John1 aClarke, Shoa, L1 aHaessler, Jeffrey, W1 aHu, Yao1 aAssimes, Themistocles, L1 aKooperberg, Charles1 aDamrauer, Scott, M1 aRotter, Jerome, I1 ade Vries, Paul, S1 aDichgans, Martin uhttps://chs-nhlbi.org/node/947903429nas a2200505 4500008004100000022001400041245009400055210006900149260001600218520189000234100002302124700002202147700002102169700002402190700002602214700002302240700002002263700002102283700001902304700001902323700002502342700001902367700002202386700001702408700002002425700002102445700001502466700002302481700002002504700002102524700002002545700001902565700002102584700001502605700002102620700002702641700002002668700002002688700002402708700002202732700001702754700002102771710009502792856003602887 2023 eng d a1935-554800aClonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk.0 aClonal Hematopoiesis of Indeterminate Potential CHIP and Inciden c2023 Sep 273 aOBJECTIVE: Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D.
RESEARCH DESIGN AND METHODS: CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis.
RESULTS: Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI = 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI = 1.05, 2.08) and ASXL1 (HR 1.76; CI = 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI = 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses.
CONCLUSIONS: CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.
1 aTobias, Deirdre, K1 aManning, Alisa, K1 aWessel, Jennifer1 aRaghavan, Sridharan1 aWesterman, Kenneth, E1 aBick, Alexander, G1 aDiCorpo, Daniel1 aWhitsel, Eric, A1 aCollins, Jason1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aDupuis, Josée1 aGoodarzi, Mark, O1 aGuo, Xiuqing1 aHoward, Barbara1 aLange, Leslie, A1 aLiu, Simin1 aRaffield, Laura, M1 aReiner, Alex, P1 aRich, Stephen, S1 aTaylor, Kent, D1 aTinker, Lesley1 aWilson, James, G1 aWu, Peitao1 aCarson, April, P1 aVasan, Ramachandran, S1 aFornage, Myriam1 aPsaty, Bruce, M1 aKooperberg, Charles1 aRotter, Jerome, I1 aMeigs, James1 aManson, JoAnn, E1 aTOPMed Diabetes Working Group; National Heart, Lung, and Blood Institute TOPMed Consortium uhttps://chs-nhlbi.org/node/950603124nas a2200769 4500008004100000022001400041245010100055210006900156260001600225300000900241490000700250520097600257653001901233653001401252653001101266653003801277653003401315653001101349653000901360653003101369653002201400653001701422100002501439700002401464700001901488700002001507700002101527700001901548700002201567700002501589700001801614700001801632700001701650700001901667700001801686700002001704700001301724700001801737700002301755700002301778700001301801700001501814700003201829700002101861700001801882700002201900700001401922700001601936700002701952700002401979700002002003700002402023700001902047700002002066700002102086700002102107700002102128700002202149700001902171700002502190700002302215700001702238700002202255700002402277700001702301856003602318 2023 eng d a2041-172300aEvaluating the use of blood pressure polygenic risk scores across race/ethnic background groups.0 aEvaluating the use of blood pressure polygenic risk scores acros c2023 Jun 02 a32020 v143 aWe assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.
10aBlood Pressure10aEthnicity10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aMale10aMultifactorial Inheritance10aPopulation Health10aRisk Factors1 aKurniansyah, Nuzulul1 aGoodman, Matthew, O1 aKhan, Alyna, T1 aWang, Jiongming1 aFeofanova, Elena1 aBis, Joshua, C1 aWiggins, Kerri, L1 aHuffman, Jennifer, E1 aKelly, Tanika1 aElfassy, Tali1 aGuo, Xiuqing1 aPalmas, Walter1 aLin, Henry, J1 aHwang, Shih-Jen1 aGao, Yan1 aYoung, Kendra1 aKinney, Gregory, L1 aSmith, Jennifer, A1 aYu, Bing1 aLiu, Simin1 aWassertheil-Smoller, Sylvia1 aManson, JoAnn, E1 aZhu, Xiaofeng1 aChen, Yii-Der Ida1 aLee, I-Te1 aGu, Charles1 aLloyd-Jones, Donald, M1 aZöllner, Sebastian1 aFornage, Myriam1 aKooperberg, Charles1 aCorrea, Adolfo1 aPsaty, Bruce, M1 aArnett, Donna, K1 aIsasi, Carmen, R1 aRich, Stephen, S1 aKaplan, Robert, C1 aRedline, Susan1 aMitchell, Braxton, D1 aFranceschini, Nora1 aLevy, Daniel1 aRotter, Jerome, I1 aMorrison, Alanna, C1 aSofer, Tamar uhttps://chs-nhlbi.org/node/937905138nas a2201357 4500008004100000022001400041245012700055210006900182260001600251300000900267490000700276520124600283653002501529653002701554653001501581653002801596653002401624653003401648653001101682653001701693100002201710700002201732700002601754700001901780700001301799700001801812700002201830700001901852700002001871700002901891700002701920700002401947700001801971700001601989700002202005700001302027700002102040700002002061700001902081700002602100700002402126700001902150700002702169700002002196700002602216700002202242700001902264700002302283700002102306700001902327700001902346700002102365700002702386700002402413700002702437700001502464700002302479700001702502700001902519700002302538700002402561700001702585700003202602700002102634700002502655700002402680700001702704700002302721700002602744700002502770700001802795700002102813700001402834700002402848700002402872700001802896700002902914700001902943700002502962700001802987700002103005700002103026700002203047700001903069700002203088700001703110700002103127700001803148700002203166700001903188700002903207700002803236700002503264700002003289700002203309700002903331700002203360700002303382700001503405700002303420700001803443700002103461700001903482700002203501700001803523700002403541700001803565700002103583700002403604700002203628700002003650700002203670700002803692700002403720856003603744 2023 eng d a2041-172300aGenetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.0 aGenetic architecture of spatial electrical biomarkers for cardia c2023 Mar 14 a14110 v143 aThe 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
10aArrhythmias, Cardiac10aAtrioventricular Block10aBiomarkers10aCardiovascular Diseases10aElectrocardiography10aGenome-Wide Association Study10aHumans10aRisk Factors1 aYoung, William, J1 aHaessler, Jeffrey1 aBenjamins, Jan-Walter1 aRepetto, Linda1 aYao, Jie1 aIsaacs, Aaron1 aHarper, Andrew, R1 aRamirez, Julia1 aGarnier, Sophie1 aVan Duijvenboden, Stefan1 aBaldassari, Antoine, R1 aConcas, Maria, Pina1 aDuong, ThuyVy1 aFoco, Luisa1 aIsaksen, Jonas, L1 aMei, Hao1 aNoordam, Raymond1 aNursyifa, Casia1 aRichmond, Anne1 aSantolalla, Meddly, L1 aSitlani, Colleen, M1 aSoroush, Negin1 aThériault, Sébastien1 aTrompet, Stella1 aAeschbacher, Stefanie1 aAhmadizar, Fariba1 aAlonso, Alvaro1 aBrody, Jennifer, A1 aCampbell, Archie1 aCorrea, Adolfo1 aDarbar, Dawood1 aDe Luca, Antonio1 aDeleuze, Jean-Francois1 aEllervik, Christina1 aFuchsberger, Christian1 aGoel, Anuj1 aGrace, Christopher1 aGuo, Xiuqing1 aHansen, Torben1 aHeckbert, Susan, R1 aJackson, Rebecca, D1 aKors, Jan, A1 aLima-Costa, Maria, Fernanda1 aLinneberg, Allan1 aMacfarlane, Peter, W1 aMorrison, Alanna, C1 aNavarro, Pau1 aPorteous, David, J1 aPramstaller, Peter, P1 aReiner, Alexander, P1 aRisch, Lorenz1 aSchotten, Ulrich1 aShen, Xia1 aSinagra, Gianfranco1 aSoliman, Elsayed, Z1 aStoll, Monika1 aTarazona-Santos, Eduardo1 aTinker, Andrew1 aTrajanoska, Katerina1 aVillard, Eric1 aWarren, Helen, R1 aWhitsel, Eric, A1 aWiggins, Kerri, L1 aArking, Dan, E1 aAvery, Christy, L1 aConen, David1 aGirotto, Giorgia1 aGrarup, Niels1 aHayward, Caroline1 aJukema, Wouter1 aMook-Kanamori, Dennis, O1 aOlesen, Morten, Salling1 aPadmanabhan, Sandosh1 aPsaty, Bruce, M1 aPattaro, Cristian1 aRibeiro, Antonio, Luiz P1 aRotter, Jerome, I1 aStricker, Bruno, H1 aHarst, Pim1 aDuijn, Cornelia, M1 aVerweij, Niek1 aWilson, James, G1 aOrini, Michele1 aCharron, Philippe1 aWatkins, Hugh1 aKooperberg, Charles1 aLin, Henry, J1 aWilson, James, F1 aKanters, Jørgen, K1 aSotoodehnia, Nona1 aMifsud, Borbala1 aLambiase, Pier, D1 aTereshchenko, Larisa, G1 aMunroe, Patricia, B uhttps://chs-nhlbi.org/node/932202705nas a2200505 4500008004100000245011300041210006900154260001600223520116400239100001801403700001801421700002101439700002001460700001901480700002301499700002101522700002001543700002001563700001801583700001901601700002001620700001801640700001901658700002301677700002401700700001701724700002001741700002301761700002501784700001701809700002701826700002101853700002201874700002201896700002101918700002401939700002101963700002601984700002202010700002402032700001902056700002302075710006502098856003602163 2023 eng d00aGenetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants.0 aGenetic control of mRNA splicing as a potential mechanism for in c2023 Jan 313 aExonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.
1 aEinson, Jonah1 aGlinos, Dafni1 aBoerwinkle, Eric1 aCastaldi, Peter1 aDarbar, Dawood1 ade Andrade, Mariza1 aEllinor, Patrick1 aFornage, Myriam1 aGabriel, Stacey1 aGermer, Soren1 aGibbs, Richard1 aHersh, Craig, P1 aJohnsen, Jill1 aKaplan, Robert1 aKonkle, Barbara, A1 aKooperberg, Charles1 aNassir, Rami1 aLoos, Ruth, J F1 aMeyers, Deborah, A1 aMitchell, Braxton, D1 aPsaty, Bruce1 aVasan, Ramachandran, S1 aRich, Stephen, S1 aRienstra, Michael1 aRotter, Jerome, I1 aSaferali, Aabida1 aShoemaker, Benjamin1 aSilverman, Edwin1 aSmith, Albert, Vernon1 aMohammadi, Pejman1 aCastel, Stephane, E1 aIossifov, Ivan1 aLappalainen, Tuuli1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/928604639nas a2201273 4500008004100000022001400041245008500055210006900140260001600209300001300225490000600238520107000244653002301314653001801337653001101355653001601366653001301382653002301395653001401418100002501432700002301457700001901480700002001499700001701519700002301536700002601559700002101585700002101606700002401627700002001651700002101671700002001692700002001712700001901732700001901751700002401770700001901794700002101813700001801834700002001852700002501872700002001897700001901917700002301936700002401959700001801983700001602001700002002017700002202037700001902059700002602078700002302104700002202127700002002149700002702169700002302196700001902219700002102238700001902259700001402278700001902292700002302311700002302334700002202357700002102379700002502400700001902425700001902444700002302463700001302486700002302499700002202522700002102544700002402565700002302589700002102612700002302633700002102656700002802677700002202705700001902727700001902746700001702765700002002782700002302802700001602825700001902841700002202860700001602882700002202898700001802920700002402938700001902962700001502981700002202996700002403018700001803042700002503060700002503085700002103110700001803131700002003149700002303169700002403192700002503216700002303241710006503264856003603329 2023 eng d a2375-254800aThe genetic determinants of recurrent somatic mutations in 43,693 blood genomes.0 agenetic determinants of recurrent somatic mutations in 43693 blo c2023 Apr 28 aeabm49450 v93 aNononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.
10aGerm-Line Mutation10aHematopoiesis10aHumans10aMiddle Aged10aMutation10aMutation, Missense10aPhenotype1 aWeinstock, Joshua, S1 aLaurie, Cecelia, A1 aBroome, Jai, G1 aTaylor, Kent, D1 aGuo, Xiuqing1 aShuldiner, Alan, R1 aO'Connell, Jeffrey, R1 aLewis, Joshua, P1 aBoerwinkle, Eric1 aBarnes, Kathleen, C1 aChami, Nathalie1 aKenny, Eimear, E1 aLoos, Ruth, J F1 aFornage, Myriam1 aRedline, Susan1 aCade, Brian, E1 aGilliland, Frank, D1 aChen, Zhanghua1 aGauderman, James1 aKumar, Rajesh1 aGrammer, Leslie1 aSchleimer, Robert, P1 aPsaty, Bruce, M1 aBis, Joshua, C1 aBrody, Jennifer, A1 aSilverman, Edwin, K1 aYun, Jeong, H1 aQiao, Dandi1 aWeiss, Scott, T1 aLasky-Su, Jessica1 aDeMeo, Dawn, L1 aPalmer, Nicholette, D1 aFreedman, Barry, I1 aBowden, Donald, W1 aCho, Michael, H1 aVasan, Ramachandran, S1 aJohnson, Andrew, D1 aYanek, Lisa, R1 aBecker, Lewis, C1 aKardia, Sharon1 aHe, Jiang1 aKaplan, Robert1 aHeckbert, Susan, R1 aSmith, Nicholas, L1 aWiggins, Kerri, L1 aArnett, Donna, K1 aIrvin, Marguerite, R1 aTiwari, Hemant1 aCorrea, Adolfo1 aRaffield, Laura, M1 aGao, Yan1 ade Andrade, Mariza1 aRotter, Jerome, I1 aRich, Stephen, S1 aManichaikul, Ani, W1 aKonkle, Barbara, A1 aJohnsen, Jill, M1 aWheeler, Marsha, M1 aCuster, Brian, S1 aDuggirala, Ravindranath1 aCurran, Joanne, E1 aBlangero, John1 aGui, Hongsheng1 aXiao, Shujie1 aWilliams, Keoki1 aMeyers, Deborah, A1 aLi, Xingnan1 aOrtega, Victor1 aMcGarvey, Stephen1 aGu, Charles1 aChen, Yii-Der Ida1 aLee, Wen-Jane1 aShoemaker, Benjamin1 aDarbar, Dawood1 aRoden, Dan1 aAlbert, Christine1 aKooperberg, Charles1 aDesai, Pinkal1 aBlackwell, Thomas, W1 aAbecasis, Goncalo, R1 aSmith, Albert, V1 aKang, Hyun, M1 aMathias, Rasika1 aNatarajan, Pradeep1 aJaiswal, Siddhartha1 aReiner, Alexander, P1 aBick, Alexander, G1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/941903534nas a2200649 4500008004100000245010900041210006900150260001600219520168900235100002201924700001601946700002001962700002201982700001402004700002202018700001602040700002202056700002402078700002002102700002202122700001702144700002402161700001802185700002102203700002302224700002402247700001902271700002102290700002002311700001902331700002202350700002002372700001902392700002002411700001702431700001902448700001702467700002502484700002402509700001902533700002302552700001902575700002302594700002002617700002102637700001802658700002002676700002202696700002402718700002102742700002002763700001802783700001402801700001702815700001602832856003602848 2023 eng d00aGenome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.0 aGenomeWide Interaction Analysis with DASH Diet Score Identified c2023 Nov 113 aOBJECTIVE: We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP).
METHODS: We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses.
RESULTS: We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with -expression quantitative trait loci (eQTL) variants (P = 4e-273) and -DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is , the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene at 15q25.1.
CONCLUSION: We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.
1 aGuirette, Melanie1 aLan, Jessie1 aMcKeown, Nicola1 aBrown, Michael, R1 aChen, Han1 ade Vries, Paul, S1 aKim, Hyunju1 aRebholz, Casey, M1 aMorrison, Alanna, C1 aBartz, Traci, M1 aFretts, Amanda, M1 aGuo, Xiuqing1 aLemaitre, Rozenn, N1 aLiu, Ching-Ti1 aNoordam, Raymond1 ade Mutsert, Renée1 aRosendaal, Frits, R1 aWang, Carol, A1 aBeilin, Lawrence1 aMori, Trevor, A1 aOddy, Wendy, H1 aPennell, Craig, E1 aChai, Jin, Fang1 aWhitton, Clare1 avan Dam, Rob, M1 aLiu, Jianjun1 aTai, Shyong, E1 aSim, Xueling1 aNeuhouser, Marian, L1 aKooperberg, Charles1 aTinker, Lesley1 aFranceschini, Nora1 aHuan, Tianxiao1 aWinkler, Thomas, W1 aBentley, Amy, R1 aGauderman, James1 aHeerkens, Luc1 aTanaka, Toshiko1 avan Rooij, Jeroen1 aMunroe, Patricia, B1 aWarren, Helen, R1 aVoortman, Trudy1 aChen, Honglei1 aRao, D, C1 aLevy, Daniel1 aMa, Jiantao uhttps://chs-nhlbi.org/node/958302914nas a2200553 4500008004100000245010000041210006900141260001600210520130500226100002001531700001901551700002001570700002501590700002101615700002401636700002101660700002101681700002401702700002001726700002101746700001601767700002401783700001701807700002401824700001701848700002301865700002301888700002201911700001801933700002001951700001601971700002001987700002002007700001902027700001902046700002002065700002402085700002102109700001902130700001802149700002202167700001402189700001502203700001702218700002302235700001702258710004902275856003602324 2023 eng d00aMachine learning models for blood pressure phenotypes combining multiple polygenic risk scores.0 aMachine learning models for blood pressure phenotypes combining c2023 Dec 143 aWe construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.
1 aHrytsenko, Yana1 aShea, Benjamin1 aElgart, Michael1 aKurniansyah, Nuzulul1 aLyons, Genevieve1 aMorrison, Alanna, C1 aCarson, April, P1 aHaring, Bernhard1 aMitchel, Braxton, D1 aPsaty, Bruce, M1 aJaeger, Byron, C1 aGu, Charles1 aKooperberg, Charles1 aLevy, Daniel1 aLloyd-Jones, Donald1 aChoi, Eunhee1 aBrody, Jennifer, A1 aSmith, Jennifer, A1 aRotter, Jerome, I1 aMoll, Matthew1 aFornage, Myriam1 aSimon, Noah1 aCastaldi, Peter1 aCasanova, Ramon1 aChung, Ren-Hua1 aKaplan, Robert1 aLoos, Ruth, J F1 aKardia, Sharon, L R1 aRich, Stephen, S1 aRedline, Susan1 aKelly, Tanika1 aO'Connor, Timothy1 aZhao, Wei1 aKim, Wonji1 aGuo, Xiuqing1 aChen, Yii, Der Ida1 aSofer, Tamar1 aTrans-Omics in Precision Medicine Consortium uhttps://chs-nhlbi.org/node/958613865nas a2204393 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2023 eng d00aMulti-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.0 aMultiancestry genomewide study in 25 million individuals reveals c2023 Mar 313 aType 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.
1 aSuzuki, Ken1 aHatzikotoulas, Konstantinos1 aSoutham, Lorraine1 aTaylor, Henry, J1 aYin, Xianyong1 aLorenz, Kim, M1 aMandla, Ravi1 aHuerta-Chagoya, Alicia1 aRayner, Nigel, W1 aBocher, Ozvan1 ade, S, V Arruda A1 aSonehara, Kyuto1 aNamba, Shinichi1 aLee, Simon, S K1 aPreuss, Michael, H1 aPetty, Lauren, E1 aSchroeder, Philip1 aVanderwerff, Brett1 aKals, Mart1 aBragg, Fiona1 aLin, Kuang1 aGuo, Xiuqing1 aZhang, Weihua1 aYao, Jie1 aKim, Young, Jin1 aGraff, Mariaelisa1 aTakeuchi, Fumihiko1 aNano, Jana1 aLamri, Amel1 aNakatochi, Masahiro1 aMoon, Sanghoon1 aScott, Robert, A1 aCook, James, P1 aLee, Jung-Jin1 aPan, Ian1 aTaliun, Daniel1 aParra, Esteban, J1 aChai, Jin-Fang1 aBielak, Lawrence, F1 aTabara, Yasuharu1 aHai, Yang1 aThorleifsson, Gudmar1 aGrarup, Niels1 aSofer, Tamar1 aWuttke, Matthias1 aSarnowski, Chloe1 aGieger, Christian1 aNousome, Darryl1 aTrompet, Stella1 aKwak, Soo-Heon1 aLong, Jirong1 aSun, Meng1 aTong, Lin1 aChen, Wei-Min1 aNongmaithem, Suraj, S1 aNoordam, Raymond1 aJ Y Lim, Victor1 aTam, Claudia, H T1 aJoo, Yoonjung, Yoonie1 aChen, Chien-Hsiun1 aRaffield, Laura, M1 aPrins, Bram, Peter1 aNicolas, Aude1 aYanek, Lisa, R1 aChen, Guanjie1 aBrody, Jennifer, A1 aKabagambe, Edmond1 aAn, Ping1 aXiang, Anny, H1 aChoi, Hyeok, Sun1 aCade, Brian, E1 aTan, Jingyi1 aBroadaway, Alaine1 aWilliamson, Alice1 aKamali, Zoha1 aCui, Jinrui1 aAdair, Linda, S1 aAdeyemo, Adebowale1 aAguilar-Salinas, Carlos, A1 aAhluwalia, Tarunveer, S1 aAnand, Sonia, S1 aBertoni, Alain1 aBork-Jensen, Jette1 aBrandslund, Ivan1 aBuchanan, Thomas, A1 aBurant, Charles, F1 aButterworth, Adam, S1 aCanouil, Mickaël1 aChan, Juliana, C N1 aChang, Li-Ching1 aChee, Miao-Li1 aChen, Ji1 aChen, Shyh-Huei1 aChen, Yuan-Tsong1 aChen, Zhengming1 aChuang, Lee-Ming1 aCushman, Mary1 aDanesh, John1 aDas, Swapan, K1 ade Silva, Janaka1 aDedoussis, George1 aDimitrov, Latchezar1 aDoumatey, Ayo, P1 aDu, Shufa1 aDuan, Qing1 aEckardt, Kai-Uwe1 aEmery, Leslie, S1 aEvans, Daniel, S1 aEvans, Michele, K1 aFischer, Krista1 aFloyd, James, S1 aFord, Ian1 aFranco, Oscar, H1 aFrayling, Timothy, M1 aFreedman, Barry, I1 aGenter, Pauline1 aGerstein, Hertzel, C1 aGiedraitis, Vilmantas1 aGonzález-Villalpando, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGordon-Larsen, Penny1 aGross, Myron1 aGuare, Lindsay, A1 aHackinger, Sophie1 aHan, Sohee1 aHattersley, Andrew, T1 aHerder, Christian1 aHorikoshi, Momoko1 aHoward, Annie-Green1 aHsueh, Willa1 aHuang, Mengna1 aHuang, Wei1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aHwu, Chii-Min1 aIchihara, Sahoko1 aIkram, Mohammad, Arfan1 aIngelsson, Martin1 aIslam, Md, Tariqul1 aIsono, Masato1 aJang, Hye-Mi1 aJasmine, Farzana1 aJiang, Guozhi1 aJonas, Jost, B1 aJørgensen, Torben1 aKandeel, Fouad, R1 aKasturiratne, Anuradhani1 aKatsuya, Tomohiro1 aKaur, Varinderpal1 aKawaguchi, Takahisa1 aKeaton, Jacob, M1 aKho, Abel, N1 aKhor, Chiea-Chuen1 aKibriya, Muhammad, G1 aKim, Duk-Hwan1 aKronenberg, Florian1 aKuusisto, Johanna1 aLäll, Kristi1 aLange, Leslie, A1 aLee, Kyung, Min1 aLee, Myung-Shik1 aLee, Nanette, R1 aLeong, Aaron1 aLi, Liming1 aLi, Yun1 aLi-Gao, Ruifang1 aLithgart, Symen1 aLindgren, Cecilia, M1 aLinneberg, Allan1 aLiu, Ching-Ti1 aLiu, Jianjun1 aLocke, Adam, E1 aLouie, Tin1 aLuan, Jian'an1 aLuk, Andrea, O1 aLuo, Xi1 aLv, Jun1 aLynch, Julie, A1 aLyssenko, Valeriya1 aMaeda, Shiro1 aMamakou, Vasiliki1 aMansuri, Sohail, Rafik1 aMatsuda, Koichi1 aMeitinger, Thomas1 aMetspalu, Andres1 aMo, Huan1 aMorris, Andrew, D1 aNadler, Jerry, L1 aNalls, Michael, A1 aNayak, Uma1 aNtalla, Ioanna1 aOkada, Yukinori1 aOrozco, Lorena1 aPatel, Sanjay, R1 aPatil, Snehal1 aPei, Pei1 aPereira, Mark, A1 aPeters, Annette1 aPirie, Fraser, J1 aPolikowsky, Hannah, G1 aPorneala, Bianca1 aPrasad, Gauri1 aRasmussen-Torvik, Laura, J1 aReiner, Alexander, P1 aRoden, Michael1 aRohde, Rebecca1 aRoll, Katheryn1 aSabanayagam, Charumathi1 aSandow, Kevin1 aSankareswaran, Alagu1 aSattar, Naveed1 aSchönherr, Sebastian1 aShahriar, Mohammad1 aShen, Botong1 aShi, Jinxiu1 aShin, Dong, Mun1 aShojima, Nobuhiro1 aSmith, Jennifer, A1 aSo, Wing, Yee1 aStančáková, Alena1 aSteinthorsdottir, Valgerdur1 aStilp, Adrienne, M1 aStrauch, Konstantin1 aTaylor, Kent, D1 aThorand, Barbara1 aThorsteinsdottir, Unnur1 aTomlinson, Brian1 aTran, Tam, C1 aTsai, Fuu-Jen1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 aValladares-Salgado, Adan1 avan Dam, Rob, M1 avan Klinken, Jan, B1 aVarma, Rohit1 aWacher-Rodarte, Niels1 aWheeler, Eleanor1 aWickremasinghe, Ananda, R1 aDijk, Ko Willems1 aWitte, Daniel, R1 aYajnik, Chittaranjan, S1 aYamamoto, Ken1 aYamamoto, Kenichi1 aYoon, Kyungheon1 aYu, Canqing1 aYuan, Jian-Min1 aYusuf, Salim1 aZawistowski, Matthew1 aZhang, Liang1 aZheng, Wei1 aProject, Biobank, Japan1 aBioBank, Penn, Medicine1 aCenter, Regeneron, Genetics1 aConsortium, eMERGE1 aRaffel, Leslie, J1 aIgase, Michiya1 aIpp, Eli1 aRedline, Susan1 aCho, Yoon Shin1 aLind, Lars1 aProvince, Michael, A1 aFornage, Myriam1 aHanis, Craig, L1 aIngelsson, Erik1 aZonderman, Alan, B1 aPsaty, Bruce, M1 aWang, Ya-Xing1 aRotimi, Charles, N1 aBecker, Diane, M1 aMatsuda, Fumihiko1 aLiu, Yongmei1 aYokota, Mitsuhiro1 aKardia, Sharon, L R1 aPeyser, Patricia, A1 aPankow, James, S1 aEngert, James, C1 aBonnefond, Amélie1 aFroguel, Philippe1 aWilson, James, G1 aSheu, Wayne, H H1 aWu, Jer-Yuarn1 aHayes, Geoffrey1 aMa, Ronald, C W1 aWong, Tien-Yin1 aMook-Kanamori, Dennis, O1 aTuomi, Tiinamaija1 aChandak, Giriraj, R1 aCollins, Francis, S1 aBharadwaj, Dwaipayan1 aParé, Guillaume1 aSale, Michèle, M1 aAhsan, Habibul1 aMotala, Ayesha, A1 aShu, Xiao-Ou1 aPark, Kyong-Soo1 aJukema, Wouter1 aCruz, Miguel1 aChen, Yii-Der Ida1 aRich, Stephen, S1 aMcKean-Cowdin, Roberta1 aGrallert, Harald1 aCheng, Ching-Yu1 aGhanbari, Mohsen1 aTai, E-Shyong1 aDupuis, Josée1 aKato, Norihiro1 aLaakso, Markku1 aKöttgen, Anna1 aKoh, Woon-Puay1 aBowden, Donald, W1 aPalmer, Colin, N A1 aKooner, Jaspal, S1 aKooperberg, Charles1 aLiu, Simin1 aNorth, Kari, E1 aSaleheen, Danish1 aHansen, Torben1 aPedersen, Oluf1 aWareham, Nicholas, J1 aLee, Juyoung1 aKim, Bong-Jo1 aMillwood, Iona, Y1 aWalters, Robin, G1 aStefansson, Kari1 aGoodarzi, Mark, O1 aMohlke, Karen, L1 aLangenberg, Claudia1 aHaiman, Christopher, A1 aLoos, Ruth, J F1 aFlorez, Jose, C1 aRader, Daniel, J1 aRitchie, Marylyn, D1 aZöllner, Sebastian1 aMägi, Reedik1 aDenny, Joshua, C1 aYamauchi, Toshimasa1 aKadowaki, Takashi1 aChambers, John, C1 aC Y Ng, Maggie1 aSim, Xueling1 aBelow, Jennifer, E1 aTsao, Philip, S1 aChang, Kyong-Mi1 aMcCarthy, Mark, I1 aMeigs, James, B1 aMahajan, Anubha1 aSpracklen, Cassandra, N1 aMercader, Josep, M1 aBoehnke, Michael1 aRotter, Jerome, I1 aVujkovic, Marijana1 aVoight, Benjamin, F1 aMorris, Andrew, P1 aZeggini, Eleftheria1 aVA Million Veteran Program, AMED GRIFIN Diabetes Initiative Japan1 aInternational Consortium for Blood Pressure (ICBP)1 aMeta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) uhttps://chs-nhlbi.org/node/938504817nas a2201309 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2023 eng d a1546-171800aMulti-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing.0 aMultiancestry transcriptomewide association analyses yield insig c2023 Feb a291-3000 v553 aMost transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.
10aBiology10aDrug Repositioning10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aPolymorphism, Single Nucleotide10aTobacco Use10aTranscriptome1 aChen, Fang1 aWang, Xingyan1 aJang, Seon-Kyeong1 aQuach, Bryan, C1 aWeissenkampen, Dylan1 aKhunsriraksakul, Chachrit1 aYang, Lina1 aSauteraud, Renan1 aAlbert, Christine, M1 aAllred, Nicholette, D D1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBarr, Graham1 aBecker, Diane, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoorgula, Meher, Preethi1 aChasman, Daniel, I1 aChavan, Sameer1 aChen, Yii-der, I1 aChuang, Lee-Ming1 aCorrea, Adolfo1 aCurran, Joanne, E1 aDavid, Sean, P1 aFuentes, Lisa, de Las1 aDeka, Ranjan1 aDuggirala, Ravindranath1 aFaul, Jessica, D1 aGarrett, Melanie, E1 aGharib, Sina, A1 aGuo, Xiuqing1 aHall, Michael, E1 aHawley, Nicola, L1 aHe, Jiang1 aHobbs, Brian, D1 aHokanson, John, E1 aHsiung, Chao, A1 aHwang, Shih-Jen1 aHyde, Thomas, M1 aIrvin, Marguerite, R1 aJaffe, Andrew, E1 aJohnson, Eric, O1 aKaplan, Robert1 aKardia, Sharon, L R1 aKaufman, Joel, D1 aKelly, Tanika, N1 aKleinman, Joel, E1 aKooperberg, Charles1 aLee, I-Te1 aLevy, Daniel1 aLutz, Sharon, M1 aManichaikul, Ani, W1 aMartin, Lisa, W1 aMarx, Olivia1 aMcGarvey, Stephen, T1 aMinster, Ryan, L1 aMoll, Matthew1 aMoussa, Karine, A1 aNaseri, Take1 aNorth, Kari, E1 aOelsner, Elizabeth, C1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRafaels, Nicholas1 aRaffield, Laura, M1 aReupena, Muagututi'a, Sefuiva1 aRich, Stephen, S1 aRotter, Jerome, I1 aSchwartz, David, A1 aShadyab, Aladdin, H1 aSheu, Wayne, H-H1 aSims, Mario1 aSmith, Jennifer, A1 aSun, Xiao1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aWatson, Harold1 aWeeks, Daniel, E1 aWeir, David, R1 aYanek, Lisa, R1 aYoung, Kendra, A1 aYoung, Kristin, L1 aZhao, Wei1 aHancock, Dana, B1 aJiang, Bibo1 aVrieze, Scott1 aLiu, Dajiang, J uhttps://chs-nhlbi.org/node/941203951nas a2200925 4500008004100000022001400041245013100055210006900186260001300255300001200268490000700280520122300287653002101510653003401531653001101565653001401576653002801590100001401618700001801632700001701650700002201667700001501689700001401704700003201718700001401750700001601764700002101780700002401801700001901825700001901844700002101863700002201884700002301906700001901929700001901948700002501967700002201992700002202014700002802036700002302064700002502087700001702112700002202129700002102151700002402172700001902196700002102215700002102236700002002257700002502277700002502302700002202327700002402349700001702373700002602390700002602416700002402442700002002466700002302486700001902509700002502528700003402553700002102587700002102608700002402629700002302653700002002676700002702696700002302723700002102746700001902767700001402786700002202800700002302822700002002845700001402865700001602879710009402895856003602989 2023 eng d a1546-171800aPowerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.0 aPowerful scalable and resourceefficient metaanalysis of rare var c2023 Jan a154-1640 v553 aMeta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.
10aExome Sequencing10aGenome-Wide Association Study10aLipids10aPhenotype10aWhole Genome Sequencing1 aLi, Xihao1 aQuick, Corbin1 aZhou, Hufeng1 aGaynor, Sheila, M1 aLiu, Yaowu1 aChen, Han1 aSelvaraj, Margaret, Sunitha1 aSun, Ryan1 aDey, Rounak1 aArnett, Donna, K1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 ade Vries, Paul, S1 aDuggirala, Ravindranath1 aFreedman, Barry, I1 aGöring, Harald, H H1 aGuo, Xiuqing1 aHaessler, Jeffrey1 aKalyani, Rita, R1 aKooperberg, Charles1 aKral, Brian, G1 aLange, Leslie, A1 aManichaikul, Ani1 aMartin, Lisa, W1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aRedline, Susan1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aRice, Kenneth, M1 aRich, Stephen, S1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aWiller, Cristen, J1 aWilson, James, G1 aYanek, Lisa, R1 aZhao, Wei1 aRotter, Jerome, I1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aLi, Zilin1 aLin, Xihong1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/923904538nas a2200997 4500008004100000245012600041210006900167260001600236520164000252100001701892700003201909700001401941700001401955700002401969700002101993700001902014700001902033700002102052700002202073700001902095700002202114700002102136700002202157700002202179700002202201700002202223700002402245700002002269700002002289700002302309700002002332700001802352700002202370700001702392700001402409700002302423700002102446700001602467700002502483700001902508700002202527700002302549700002102572700001402593700002402607700001902631700001702650700001702667700001602684700002002700700001902720700002402739700002002763700002302783700002102806700002502827700002202852700002402874700002402898700001702922700002602939700002602965700002302991700002003014700002303034700002003057700001903077700002503096700002103121700003403142700002103176700002303197700001803220700002203238700002103260700003003281700001403311700001903325700001403344700002203358700001603380700002303396700002003419710006503439856003603504 2023 eng d00aRare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study.0 aRare variants in long noncoding RNAs are associated with blood l c2023 Jun 293 aLong non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.
1 aWang, Yuxuan1 aSelvaraj, Margaret, Sunitha1 aLi, Xihao1 aLi, Zilin1 aHoldcraft, Jacob, A1 aArnett, Donna, K1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aCade, Brian, E1 aCarlson, Jenna, C1 aCarson, April, P1 aChen, Yii-Der Ida1 aCurran, Joanne, E1 ade Vries, Paul, S1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aFloyd, James, S1 aFornage, Myriam1 aFreedman, Barry, I1 aGabriel, Stacey1 aGermer, Soren1 aGibbs, Richard, A1 aGuo, Xiuqing1 aHe, Jiang1 aHeard-Costa, Nancy1 aHildalgo, Bertha1 aHou, Lifang1 aIrvin, Marguerite, R1 aJoehanes, Roby1 aKaplan, Robert, C1 aKardia, Sharon, Lr1 aKelly, Tanika, N1 aKim, Ryan1 aKooperberg, Charles1 aKral, Brian, G1 aLevy, Daniel1 aLi, Changwei1 aLiu, Chunyu1 aLloyd-Jone, Don1 aLoos, Ruth, Jf1 aMahaney, Michael, C1 aMartin, Lisa, W1 aMathias, Rasika, A1 aMinster, Ryan, L1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aMurabito, Joanne, M1 aNaseri, Take1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPreuss, Michael, H1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aRao, Dabeeru, C1 aRedline, Susan1 aReiner, Alexander, P1 aRich, Stephen, S1 aRuepena, Muagututi'a, Sefuiva1 aSheu, Wayne, H-H1 aSmith, Jennifer, A1 aSmith, Albert1 aTiwari, Hemant, K1 aTsai, Michael, Y1 aViaud-Martinez, Karine, A1 aWang, Zhe1 aYanek, Lisa, R1 aZhao, Wei1 aRotter, Jerome, I1 aLin, Xihong1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/941803992nas a2200925 4500008004100000245012300041210006900164260001600233520132600249100001401575700001401589700003201603700002001635700001701655700001701672700001401689700002201703700001201725700002101737700001901758700001901777700002101796700002201817700002301839700001901862700002101881700002201902700002001924700002201944700002201966700002201988700002002010700002302030700002302053700001602076700002602092700001402118700001602132700001702148700002502165700002202190700002402212700001802236700002102254700002402275700001902299700001702318700002002335700002402355700002002379700002302399700002102422700002502443700002202468700002402490700002602514700002402540700002002564700002302584700001902607700002502626700002102651700002402672700002302696700002002719700001902739700002702758700001402785700001902799700001302818700002102831700002202852700002002874700002302894700001402917700001802931700001602949710006502965856003603030 2023 eng d00aA statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.0 astatistical framework for powerful multitrait rare variant analy c2023 Nov 023 aLarge-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of and an intergenic region on chromosome 1.
1 aLi, Xihao1 aChen, Han1 aSelvaraj, Margaret, Sunitha1 aVan Buren, Eric1 aZhou, Hufeng1 aWang, Yuxuan1 aSun, Ryan1 aMcCaw, Zachary, R1 aYu, Zhi1 aArnett, Donna, K1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aCarson, April, P1 aCarlson, Jenna, C1 aChami, Nathalie1 aChen, Yii-Der Ida1 aCurran, Joanne, E1 ade Vries, Paul, S1 aFornage, Myriam1 aFranceschini, Nora1 aFreedman, Barry, I1 aGu, Charles1 aHeard-Costa, Nancy, L1 aHe, Jiang1 aHou, Lifang1 aHung, Yi-Jen1 aIrvin, Marguerite, R1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKelly, Tanika1 aKonigsberg, Iain1 aKooperberg, Charles1 aKral, Brian, G1 aLi, Changwei1 aLoos, Ruth, J F1 aMahaney, Michael, C1 aMartin, Lisa, W1 aMathias, Rasika, A1 aMinster, Ryan, L1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aPalmer, Nicholette, D1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aRedline, Susan1 aReiner, Alexander, P1 aRich, Stephen, S1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aTiwari, Hemant1 aVasan, Ramachandran, S1 aWang, Zhe1 aYanek, Lisa, R1 aYu, Bing1 aRice, Kenneth, M1 aRotter, Jerome, I1 aPeloso, Gina, M1 aNatarajan, Pradeep1 aLi, Zilin1 aLiu, Zhonghua1 aLin, Xihong1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/954305739nas a2200901 4500008004100000245012500041210006900166260001600235520316300251100002003414700003103434700002303465700002103488700001803509700001503527700002303542700001303565700001703578700002203595700001803617700001803635700002303653700001503676700002203691700001703713700001803730700002503748700001703773700001803790700002103808700001903829700002203848700002003870700001503890700002003905700001603925700002503941700002403966700001903990700002404009700002404033700002504057700002104082700002404103700002404127700002204151700002004173700002104193700002104214700003004235700002004265700002104285700001204306700002104318700001904339700002004358700001904378700002104397700002304418700002104441700001604462700002504478700002104503700002404524700001904548700002204567700002004589700002304609700002304632700002404655700001904679700002104698700002204719700001804741700002204759700002004781856003604801 2023 eng d00aTime-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus.0 aTimetoEvent GenomeWide Association Study for Incident Cardiovasc c2023 Jul 283 aBACKGROUND: Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD.
METHODS: From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D.
RESULTS: A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance ( <5.0×10 ): rs147138607 (intergenic variant between and ) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, =3.6×10 , rs11444867 (intergenic variant near ) with HR 1.89, 95% CI 1.52 - 2.35, =9.9×10 , and rs335407 (intergenic variant between and ) HR 1.25, 95% CI 1.16 - 1.35, =1.5×10 . Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with <0.05, and 5 were significant after Bonferroni correction ( <0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase ( =1.0×10 ).
CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.
CLINICAL PERSPECTIVE: We conducted a large-scale multi-ancestry time-to-event GWAS to identify genetic variants associated with CVD among people with T2D. Three variants were significantly associated with incident CVD in people with T2D: rs147138607 (intergenic variant between and ), rs11444867 (intergenic variant near ), and rs335407 (intergenic variant between and ). A polygenic score composed of known CAD variants identified in the general population was significantly associated with the risk of CVD in people with T2D. There are genetic risk factors specific to T2D that could at least partially explain the excess risk of CVD in people with T2D.In addition, we show that people with T2D have enrichment of known CAD association signals which could also explain the excess risk of CVD.
1 aKwak, Soo, Heon1 aHernandez-Cancela, Ryan, B1 aDiCorpo, Daniel, A1 aCondon, David, E1 aMerino, Jordi1 aWu, Peitao1 aBrody, Jennifer, A1 aYao, Jie1 aGuo, Xiuqing1 aAhmadizar, Fariba1 aMeyer, Mariah1 aSincan, Murat1 aMercader, Josep, M1 aLee, Sujin1 aHaessler, Jeffrey1 aVy, Ha, My T1 aLin, Zhaotong1 aArmstrong, Nicole, D1 aGu, Shaopeng1 aTsao, Noah, L1 aLange, Leslie, A1 aWang, Ningyuan1 aWiggins, Kerri, L1 aTrompet, Stella1 aLiu, Simin1 aLoos, Ruth, J F1 aJudy, Renae1 aSchroeder, Philip, H1 aHasbani, Natalie, R1 aBos, Maxime, M1 aMorrison, Alanna, C1 aJackson, Rebecca, D1 aReiner, Alexander, P1 aManson, JoAnn, E1 aChaudhary, Ninad, S1 aCarmichael, Lynn, K1 aChen, Yii-Der Ida1 aTaylor, Kent, D1 aGhanbari, Mohsen1 avan Meurs, Joyce1 aPitsillides, Achilleas, N1 aPsaty, Bruce, M1 aNoordam, Raymond1 aDo, Ron1 aPark, Kyong, Soo1 aJukema, Wouter1 aKavousi, Maryam1 aCorrea, Adolfo1 aRich, Stephen, S1 aDamrauer, Scott, M1 aHajek, Catherine1 aCho, Nam, H1 aIrvin, Marguerite, R1 aPankow, James, S1 aNadkarni, Girish, N1 aSladek, Robert1 aGoodarzi, Mark, O1 aFlorez, Jose, C1 aChasman, Daniel, I1 aHeckbert, Susan, R1 aKooperberg, Charles1 aDupuis, Josée1 aMalhotra, Rajeev1 ade Vries, Paul, S1 aLiu, Ching-Ti1 aRotter, Jerome, I1 aMeigs, James, B uhttps://chs-nhlbi.org/node/945002774nas a2200397 4500008004100000022001400041245011600055210006900171260001600240300001200256490000600268520162400274100002401898700001501922700002301937700002101960700002401981700002002005700002002025700002102045700001702066700002202083700002402105700001302129700001902142700002002161700001802181700002202199700002002221700002002241700002202261700002102283700001902304700001702323856003602340 2023 eng d a2472-197200aA Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies.0 aType 1 Diabetes Polygenic Score Is Not Associated With Prevalent c2023 Oct 09 abvad1230 v73 aCONTEXT: Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight.
OBJECTIVE: We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.
METHODS: We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D.
RESULTS: The T1D PS was not associated with T2D both in CHARGE ( = .15) and in the MGB Biobank ( = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, = .03) in CHARGE T2D cases but not with other outcomes.
CONCLUSION: In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.
1 aSrinivasan, Shylaja1 aWu, Peitao1 aMercader, Josep, M1 aUdler, Miriam, S1 aPorneala, Bianca, C1 aBartz, Traci, M1 aFloyd, James, S1 aSitlani, Colleen1 aGuo, Xiquing1 aHaessler, Jeffrey1 aKooperberg, Charles1 aLiu, Jun1 aAhmad, Shahzad1 aDuijn, Cornelia1 aLiu, Ching-Ti1 aGoodarzi, Mark, O1 aFlorez, Jose, C1 aMeigs, James, B1 aRotter, Jerome, I1 aRich, Stephen, S1 aDupuis, Josée1 aLeong, Aaron uhttps://chs-nhlbi.org/node/954407212nas a2201753 4500008004100000245012700041210006900168260001600237520220800253100002502461700001902486700001602505700001902521700002302540700001902563700002302582700002102605700001802626700002002644700002402664700002302688700002902711700002302740700002002763700002102783700002102804700002102825700002402846700002202870700001902892700001502911700002102926700002002947700001802967700001902985700002103004700002503025700002603050700002103076700001903097700001903116700002803135700002203163700002203185700001903207700002003226700001803246700001703264700001503281700002003296700002803316700001703344700001703361700002703378700002503405700002003430700002003450700002003470700002403490700001203514700001603526700002003542700002803562700001603590700002103606700001903627700002103646700002703667700002103694700002403715700001603739700002203755700002403777700002503801700001703826700001403843700002103857700002003878700002203898700001903920700002003939700001503959700002003974700002203994700002404016700002004040700001804060700002004078700002704098700001804125700001704143700002104160700001604181700001804197700002404215700002004239700002004259700002604279700001904305700002004324700002304344700002304367700002504390700002004415700003004435700001804465700002304483700001804506700002104524700001904545700002004564700001804584700001904602700002304621700002204644700002004666700001904686700002204705700002004727700001904747700002304766700002104789700002004810700002304830700002504853700002904878700002904907700001904936700002604955700001904981700002205000700002005022700002405042700002005066700001705086700001805103700002105121700001305142700003205155700002305187700002205210700002205232700002505254700002405279700002305303710003105326710006505357856003605422 2023 eng d00aWhole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.0 aWhole genome analysis of plasma fibrinogen reveals populationdif c2023 Jun 123 aUNLABELLED: Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( , and signals contain predicted deleterious missense variants. Two loci, and , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.
KEY POINTS: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.
1 aHuffman, Jennifer, E1 aNicolas, Jayna1 aHahn, Julie1 aHeath, Adam, S1 aRaffield, Laura, M1 aYanek, Lisa, R1 aBrody, Jennifer, A1 aThibord, Florian1 aAlmasy, Laura1 aBartz, Traci, M1 aBielak, Lawrence, F1 aBowler, Russell, P1 aCarrasquilla, Germán, D1 aChasman, Daniel, I1 aChen, Ming-Huei1 aEmmert, David, B1 aGhanbari, Mohsen1 aHaessle, Jeffery1 aHottenga, Jouke-Jan1 aKleber, Marcus, E1 aLe, Ngoc-Quynh1 aLee, Jiwon1 aLewis, Joshua, P1 aLi-Gao, Ruifang1 aLuan, Jian'an1 aMalmberg, Anni1 aMangino, Massimo1 aMarioni, Riccardo, E1 aMartinez-Perez, Angel1 aPankratz, Nathan1 aPolasek, Ozren1 aRichmond, Anne1 aRodriguez, Benjamin, At1 aRotter, Jerome, I1 aSteri, Maristella1 aSuchon, Pierre1 aTrompet, Stella1 aWeiss, Stefan1 aZare, Marjan1 aAuer, Paul1 aCho, Michael, H1 aChristofidou, Paraskevi1 aDavies, Gail1 ade Geus, Eco1 aDeleuze, Jean-Francois1 aDelgado, Graciela, E1 aEkunwe, Lynette1 aFaraday, Nauder1 aGögele, Martin1 aGreinacher, Andreas1 aHe, Gao1 aHoward, Tom1 aJoshi, Peter, K1 aKilpeläinen, Tuomas, O1 aLahti, Jari1 aLinneberg, Allan1 aNaitza, Silvia1 aNoordam, Raymond1 aPaüls-Vergés, Ferran1 aRich, Stephen, S1 aRosendaal, Frits, R1 aRudan, Igor1 aRyan, Kathleen, A1 aSouto, Juan, Carlos1 avan Rooij, Frank, Ja1 aWang, Heming1 aZhao, Wei1 aBecker, Lewis, C1 aBeswick, Andrew1 aBrown, Michael, R1 aCade, Brian, E1 aCampbell, Harry1 aCho, Kelly1 aCrapo, James, D1 aCurran, Joanne, E1 ade Maat, Moniek, Pm1 aDoyle, Margaret1 aElliott, Paul1 aFloyd, James, S1 aFuchsberger, Christian1 aGrarup, Niels1 aGuo, Xiuqing1 aHarris, Sarah, E1 aHou, Lifang1 aKolcic, Ivana1 aKooperberg, Charles1 aMenni, Cristina1 aNauck, Matthias1 aO'Connell, Jeffrey, R1 aOrrù, Valeria1 aPsaty, Bruce, M1 aRäikkönen, Katri1 aSmith, Jennifer, A1 aSoria, José, Manuel1 aStott, David, J1 aVlieg, Astrid, van Hylcka1 aWatkins, Hugh1 aWillemsen, Gonneke1 aWilson, Peter1 aBen-Shlomo, Yoav1 aBlangero, John1 aBoomsma, Dorret1 aCox, Simon, R1 aDehghan, Abbas1 aEriksson, Johan, G1 aFiorillo, Edoardo1 aFornage, Myriam1 aHansen, Torben1 aHayward, Caroline1 aIkram, Arfan, M1 aJukema, Wouter1 aKardia, Sharon, Lr1 aLange, Leslie, A1 aMärz, Winfried1 aMathias, Rasika, A1 aMitchell, Braxton, D1 aMook-Kanamori, Dennis, O1 aMorange, Pierre-Emmanuel1 aPedersen, Oluf1 aPramstaller, Peter, P1 aRedline, Susan1 aReiner, Alexander1 aRidker, Paul, M1 aSilverman, Edwin, K1 aSpector, Tim, D1 aVölker, Uwe1 aWareham, Nick1 aWilson, James, F1 aYao, Jie1 aTrégouët, David-Alexandre1 aJohnson, Andrew, D1 aWolberg, Alisa, S1 ade Vries, Paul, S1 aSabater-Lleal, Maria1 aMorrison, Alanna, C1 aSmith, Nicholas, L1 aVA Million Veteran Program1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/944903549nas a2200541 4500008004100000022001400041245010100055210006900156260001600225300001200241520193400253100002302187700002302210700002402233700001702257700002402274700002002298700002002318700002702338700002402365700001902389700002302408700002402431700002302455700001402478700002102492700002202513700002302535700002402558700002502582700001702607700001802624700002202642700002102664700002302685700002302708700002202731700002102753700002002774700002702794700001402821700002402835700002102859700002302880700002102903710004702924856003602971 2023 eng d a2574-830000aWhole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program.0 aWhole Genome Analysis of Venous Thromboembolism the TransOmics f c2023 Mar 24 ae0035323 aBackground Risk for venous thromboembolism has a strong genetic component. Whole genome sequencingfrom the Trans-Omics for Precision Medicine program allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods The 3793 cases and 7834 controls (11.6% of cases were Black, Hispanic/Latino, or Asian American) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only (odds ratio, 6.2 for carriers of rare variants; =7.4×10) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at (odds ratio, 3.8; =1.6×10), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: became significant (minimum =1.8×10 with the secondary filter), while did not (minimum =4.4×10 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, , became significant (=4.4×10 using all missense variants with minor allele frequency <0.0005). Conclusions Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel locus and to identify additional rare variation associated with venous thromboembolism.
1 aSeyerle, Amanda, A1 aLaurie, Cecelia, A1 aCoombes, Brandon, J1 aJain, Deepti1 aConomos, Matthew, P1 aBrody, Jennifer1 aChen, Ming-Huei1 aGogarten, Stephanie, M1 aBeutel, Kathleen, M1 aGupta, Namrata1 aHeckbert, Susan, R1 aJackson, Rebecca, D1 aJohnson, Andrew, D1 aKo, Darae1 aManson, JoAnn, E1 aMcKnight, Barbara1 aMetcalf, Ginger, A1 aMorrison, Alanna, C1 aReiner, Alexander, P1 aSofer, Tamar1 aTang, Weihong1 aWiggins, Kerri, L1 aBoerwinkle, Eric1 ade Andrade, Mariza1 aGabriel, Stacey, B1 aGibbs, Richard, A1 aLaurie, Cathy, C1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aRice, Ken1 aKooperberg, Charles1 aPankow, James, S1 aSmith, Nicholas, L1 aPankratz, Nathan1 aTrans-Omics for Precision Medicine Program uhttps://chs-nhlbi.org/node/932103713nas a2200661 4500008004100000022001400041245015600055210006900211260000900280300001200289490000700301520176300308100002502071700003302096700001802129700002902147700002602176700002002202700001902222700002302241700001402264700002202278700002002300700002302320700001702343700002502360700001902385700001802404700002402422700002002446700002102466700002602487700002202513700002602535700002002561700001402581700002102595700001402616700001402630700002102644700002102665700002102686700002102707700002402728700002002752700002402772700002702796700002002823700002002843700001902863700002102882700002202903700002302925700002102948700002502969700002102994856003603015 2023 eng d a1664-802100aWhole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program.0 aWhole genome sequence analysis of apparent treatment resistant h c2023 a12782150 v143 a Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data. Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP ( = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg ( = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg ( = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American). One variant in the known HTN locus, , was a top finding in the multi-ethnic analysis ( = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74-0.88)]. This variant was replicated in the Vanderbilt University Medical Center's DNA repository data. Aggregate gene-based signals included the genes and . Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.
1 aArmstrong, Nicole, D1 aSrinivasasainagendra, Vinodh1 aAmmous, Farah1 aAssimes, Themistocles, L1 aBeitelshees, Amber, L1 aBrody, Jennifer1 aCade, Brian, E1 aChen, Yii-Der, Ida1 aChen, Han1 ade Vries, Paul, S1 aFloyd, James, S1 aFranceschini, Nora1 aGuo, Xiuqing1 aHellwege, Jacklyn, N1 aHouse, John, S1 aHwu, Chii-Min1 aKardia, Sharon, L R1 aLange, Ethan, M1 aLange, Leslie, A1 aMcDonough, Caitrin, W1 aMontasser, May, E1 aO'Connell, Jeffrey, R1 aShuey, Megan, M1 aSun, Xiao1 aTanner, Rikki, M1 aWang, Zhe1 aZhao, Wei1 aCarson, April, P1 aEdwards, Todd, L1 aKelly, Tanika, N1 aKenny, Eimear, E1 aKooperberg, Charles1 aLoos, Ruth, J F1 aMorrison, Alanna, C1 aMotsinger-Reif, Alison1 aPsaty, Bruce, M1 aRao, Dabeeru, C1 aRedline, Susan1 aRich, Stephen, S1 aRotter, Jerome, I1 aSmith, Jennifer, A1 aSmith, Albert, V1 aIrvin, Marguerite, R1 aArnett, Donna, K uhttps://chs-nhlbi.org/node/958105493nas a2201573 4500008004100000245011200041210006900153260001600222520100600238100001801244700002301262700002201285700002501307700002001332700001501352700001401367700002001381700002101401700002201422700001401444700001401458700002401472700002101496700002401517700001901541700002901560700002201589700001901611700001801630700002801648700002001676700001901696700001901715700002101734700002401755700001901779700001701798700002801815700001701843700002201860700002301882700002401905700001701929700001801946700002501964700002001989700002102009700001602030700002002046700001602066700001302082700001802095700002402113700001702137700002102154700002402175700002102199700002002220700002002240700001702260700002202277700002802299700002302327700002402350700001702374700002302391700003002414700002602444700002102470700002002491700001902511700002302530700001402553700002402567700002402591700001802615700002802633700002402661700002302685700002202708700002702730700001702757700002102774700002102795700002202816700002202838700002302860700001902883700002302902700001402925700002402939700002102963700002802984700002403012700001903036700002103055700002503076700002103101700002303122700002203145700002203167700002003189700002303209700001403232700002303246700001603269700002503285700002403310700002103334700002503355700001903380700002003399700002303419700002503442700002103467700002203488700002403510700002303534700002003557700002203577700002003599700001803619700002503637700001603662700001603678700002503694700002103719700001803740700002003758700001903778700002103797710006503818856003603883 2023 eng d00aWHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE.0 aWHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES N c2023 Aug 223 aObesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals ( < 5 × 10 ). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the and loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.
1 aZhang, Xinruo1 aBrody, Jennifer, A1 aGraff, Mariaelisa1 aHighland, Heather, M1 aChami, Nathalie1 aXu, Hanfei1 aWang, Zhe1 aFerrier, Kendra1 aChittoor, Geetha1 aJosyula, Navya, S1 aLi, Xihao1 aLi, Zilin1 aAllison, Matthew, A1 aBecker, Diane, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBoorgula, Meher, Preethi1 aBowden, Donald, W1 aBroome, Jai, G1 aButh, Erin, J1 aCarlson, Christopher, S1 aChang, Kyong-Mi1 aChavan, Sameer1 aChiu, Yen-Feng1 aChuang, Lee-Ming1 aConomos, Matthew, P1 aDeMeo, Dawn, L1 aDu, Margaret1 aDuggirala, Ravindranath1 aEng, Celeste1 aFohner, Alison, E1 aFreedman, Barry, I1 aGarrett, Melanie, E1 aGuo, Xiuqing1 aHaiman, Chris1 aHeavner, Benjamin, D1 aHidalgo, Bertha1 aHixson, James, E1 aHo, Yuk-Lam1 aHobbs, Brian, D1 aHu, Donglei1 aHui, Qin1 aHwu, Chii-Min1 aJackson, Rebecca, D1 aJain, Deepti1 aKalyani, Rita, R1 aKardia, Sharon, L R1 aKelly, Tanika, N1 aLange, Ethan, M1 aLeNoir, Michael1 aLi, Changwei1 aLe Marchand, Loic1 aMcDonald, Merry-Lynn, N1 aMcHugh, Caitlin, P1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey1 aO'Donnell, Christopher, J1 aPalmer, Nicholette, D1 aPankow, James, S1 aPerry, James, A1 aPeters, Ulrike1 aPreuss, Michael, H1 aRao, D, C1 aRegan, Elizabeth, A1 aReupena, Sefuiva, M1 aRoden, Dan, M1 aRodriguez-Santana, Jose1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aTiwari, Hemant, K1 aVasan, Ramachandran, S1 aWang, Zeyuan1 aWeeks, Daniel, E1 aWessel, Jennifer1 aWiggins, Kerri, L1 aWilkens, Lynne, R1 aWilson, Peter, W F1 aYanek, Lisa, R1 aYoneda, Zachary, T1 aZhao, Wei1 aZöllner, Sebastian1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBlangero, John1 aBoerwinkle, Eric1 aBurchard, Esteban, G1 aCarson, April, P1 aChasman, Daniel, I1 aChen, Yii-Der Ida1 aCurran, Joanne, E1 aFornage, Myriam1 aGordeuk, Victor, R1 aHe, Jiang1 aHeckbert, Susan, R1 aHou, Lifang1 aIrvin, Marguerite, R1 aKooperberg, Charles1 aMinster, Ryan, L1 aMitchell, Braxton, D1 aNouraie, Mehdi1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aReiner, Alexander, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aShoemaker, Benjamin1 aSmith, Nicholas, L1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aWeiss, Scott, T1 aZhang, Yingze1 aCosta, Nancy, Heard-1 aSun, Yan, V1 aLin, Xihong1 aCupples, Adrienne, L1 aLange, Leslie, A1 aLiu, Ching-Ti1 aLoos, Ruth, J F1 aNorth, Kari, E1 aJustice, Anne, E1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/948403779nas a2200673 4500008004100000245013300041210006900174260001600243520177100259100001902030700002202049700001402071700002002085700002002105700001502125700001902140700002202159700002702181700001402208700002102222700002002243700001902263700002102282700001902303700001702322700002202339700002102361700002202382700002502404700002102429700002002450700002502470700002402495700002202519700001902541700001602560700002302576700002002599700001902619700001502638700002102653700002302674700002202697700002402719700002002743700001902763700001902782700001602801700002002817700002402837700002502861700002302886700001602909700001802925700002302943710006502966710003803031856003603069 2023 eng d00aWhole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.0 aWhole Genome Sequencing Based Analysis of Inflammation Biomarker c2023 Sep 123 aInflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
1 aJiang, Min-Zhi1 aGaynor, Sheila, M1 aLi, Xihao1 aVan Buren, Eric1 aStilp, Adrienne1 aButh, Erin1 aWang, Fei, Fei1 aManansala, Regina1 aGogarten, Stephanie, M1 aLi, Zilin1 aPolfus, Linda, M1 aSalimi, Shabnam1 aBis, Joshua, C1 aPankratz, Nathan1 aYanek, Lisa, R1 aDurda, Peter1 aTracy, Russell, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aMitchell, Braxton, D1 aLewis, Joshua, P1 aPsaty, Bruce, M1 aPratte, Katherine, A1 aSilverman, Edwin, K1 aKaplan, Robert, C1 aAvery, Christy1 aNorth, Kari1 aMathias, Rasika, A1 aFaraday, Nauder1 aLin, Honghuang1 aWang, Biqi1 aCarson, April, P1 aNorwood, Arnita, F1 aGibbs, Richard, A1 aKooperberg, Charles1 aLundin, Jessica1 aPeters, Ulrike1 aDupuis, Josée1 aHou, Lifang1 aFornage, Myriam1 aBenjamin, Emelia, J1 aReiner, Alexander, P1 aBowler, Russell, P1 aLin, Xihong1 aAuer, Paul, L1 aRaffield, Laura, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Inflammation Working Group uhttps://chs-nhlbi.org/node/950014002nas a2204477 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2024 eng d a1476-468700aGenetic drivers of heterogeneity in type 2 diabetes pathophysiology.0 aGenetic drivers of heterogeneity in type 2 diabetes pathophysiol c2024 Feb 193 aType 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
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aNongmaithem, Suraj, S1 aNoordam, Raymond1 aJ Y Lim, Victor1 aTam, Claudia, H T1 aJoo, Yoonjung, Yoonie1 aChen, Chien-Hsiun1 aRaffield, Laura, M1 aPrins, Bram, Peter1 aNicolas, Aude1 aYanek, Lisa, R1 aChen, Guanjie1 aBrody, Jennifer, A1 aKabagambe, Edmond1 aAn, Ping1 aXiang, Anny, H1 aChoi, Hyeok, Sun1 aCade, Brian, E1 aTan, Jingyi1 aBroadaway, Alaine1 aWilliamson, Alice1 aKamali, Zoha1 aCui, Jinrui1 aThangam, Manonanthini1 aAdair, Linda, S1 aAdeyemo, Adebowale1 aAguilar-Salinas, Carlos, A1 aAhluwalia, Tarunveer, S1 aAnand, Sonia, S1 aBertoni, Alain1 aBork-Jensen, Jette1 aBrandslund, Ivan1 aBuchanan, Thomas, A1 aBurant, Charles, F1 aButterworth, Adam, S1 aCanouil, Mickaël1 aChan, Juliana, C N1 aChang, Li-Ching1 aChee, Miao-Li1 aChen, Ji1 aChen, Shyh-Huei1 aChen, Yuan-Tsong1 aChen, Zhengming1 aChuang, Lee-Ming1 aCushman, Mary1 aDanesh, John1 aDas, Swapan, K1 ade Silva, Janaka1 aDedoussis, George1 aDimitrov, Latchezar1 aDoumatey, Ayo, P1 aDu, Shufa1 aDuan, Qing1 aEckardt, Kai-Uwe1 aEmery, Leslie, S1 aEvans, Daniel, S1 aEvans, Michele, K1 aFischer, Krista1 aFloyd, James, S1 aFord, Ian1 aFranco, Oscar, H1 aFrayling, Timothy, M1 aFreedman, Barry, I1 aGenter, Pauline1 aGerstein, Hertzel, C1 aGiedraitis, Vilmantas1 aGonzález-Villalpando, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGordon-Larsen, Penny1 aGross, Myron1 aGuare, Lindsay, A1 aHackinger, Sophie1 aHakaste, Liisa1 aHan, Sohee1 aHattersley, Andrew, T1 aHerder, Christian1 aHorikoshi, Momoko1 aHoward, Annie-Green1 aHsueh, Willa1 aHuang, Mengna1 aHuang, Wei1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aHwu, Chii-Min1 aIchihara, Sahoko1 aIkram, Mohammad, Arfan1 aIngelsson, Martin1 aIslam, Md, Tariqul1 aIsono, Masato1 aJang, Hye-Mi1 aJasmine, Farzana1 aJiang, Guozhi1 aJonas, Jost, B1 aJørgensen, Torben1 aKamanu, Frederick, K1 aKandeel, Fouad, R1 aKasturiratne, Anuradhani1 aKatsuya, Tomohiro1 aKaur, Varinderpal1 aKawaguchi, Takahisa1 aKeaton, Jacob, M1 aKho, Abel, N1 aKhor, Chiea-Chuen1 aKibriya, Muhammad, G1 aKim, 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Kevin1 aSankareswaran, Alagu1 aSattar, Naveed1 aSchönherr, Sebastian1 aShahriar, Mohammad1 aShen, Botong1 aShi, Jinxiu1 aShin, Dong, Mun1 aShojima, Nobuhiro1 aSmith, Jennifer, A1 aSo, Wing, Yee1 aStančáková, Alena1 aSteinthorsdottir, Valgerdur1 aStilp, Adrienne, M1 aStrauch, Konstantin1 aTaylor, Kent, D1 aThorand, Barbara1 aThorsteinsdottir, Unnur1 aTomlinson, Brian1 aTran, Tam, C1 aTsai, Fuu-Jen1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 aValladares-Salgado, Adan1 avan Dam, Rob, M1 avan Klinken, Jan, B1 aVarma, Rohit1 aWacher-Rodarte, Niels1 aWheeler, Eleanor1 aWickremasinghe, Ananda, R1 aDijk, Ko Willems1 aWitte, Daniel, R1 aYajnik, Chittaranjan, S1 aYamamoto, Ken1 aYamamoto, Kenichi1 aYoon, Kyungheon1 aYu, Canqing1 aYuan, Jian-Min1 aYusuf, Salim1 aZawistowski, Matthew1 aZhang, Liang1 aZheng, Wei1 aRaffel, Leslie, J1 aIgase, Michiya1 aIpp, Eli1 aRedline, Susan1 aCho, Yoon Shin1 aLind, Lars1 aProvince, Michael, A1 aFornage, Myriam1 aHanis, Craig, L1 aIngelsson, Erik1 aZonderman, Alan, B1 aPsaty, Bruce, M1 aWang, Ya-Xing1 aRotimi, Charles, N1 aBecker, Diane, M1 aMatsuda, Fumihiko1 aLiu, Yongmei1 aYokota, Mitsuhiro1 aKardia, Sharon, L R1 aPeyser, Patricia, A1 aPankow, James, S1 aEngert, James, C1 aBonnefond, Amélie1 aFroguel, Philippe1 aWilson, James, G1 aSheu, Wayne, H H1 aWu, Jer-Yuarn1 aHayes, Geoffrey1 aMa, Ronald, C W1 aWong, Tien-Yin1 aMook-Kanamori, Dennis, O1 aTuomi, Tiinamaija1 aChandak, Giriraj, R1 aCollins, Francis, S1 aBharadwaj, Dwaipayan1 aParé, Guillaume1 aSale, Michèle, M1 aAhsan, Habibul1 aMotala, Ayesha, A1 aShu, Xiao-Ou1 aPark, Kyong-Soo1 aJukema, Wouter1 aCruz, Miguel1 aChen, Yii-Der Ida1 aRich, Stephen, S1 aMcKean-Cowdin, Roberta1 aGrallert, Harald1 aCheng, Ching-Yu1 aGhanbari, Mohsen1 aTai, E-Shyong1 aDupuis, Josée1 aKato, Norihiro1 aLaakso, Markku1 aKöttgen, Anna1 aKoh, Woon-Puay1 aBowden, Donald, W1 aPalmer, Colin, N A1 aKooner, Jaspal, S1 aKooperberg, Charles1 aLiu, Simin1 aNorth, Kari, E1 aSaleheen, Danish1 aHansen, Torben1 aPedersen, Oluf1 aWareham, Nicholas, J1 aLee, Juyoung1 aKim, Bong-Jo1 aMillwood, Iona, Y1 aWalters, Robin, G1 aStefansson, Kari1 aAhlqvist, Emma1 aGoodarzi, Mark, O1 aMohlke, Karen, L1 aLangenberg, Claudia1 aHaiman, Christopher, A1 aLoos, Ruth, J F1 aFlorez, Jose, C1 aRader, Daniel, J1 aRitchie, Marylyn, D1 aZöllner, Sebastian1 aMägi, Reedik1 aMarston, Nicholas, A1 aRuff, Christian, T1 avan Heel, David, A1 aFiner, Sarah1 aDenny, Joshua, C1 aYamauchi, Toshimasa1 aKadowaki, Takashi1 aChambers, John, C1 aC Y Ng, Maggie1 aSim, Xueling1 aBelow, Jennifer, E1 aTsao, Philip, S1 aChang, Kyong-Mi1 aMcCarthy, Mark, I1 aMeigs, James, B1 aMahajan, Anubha1 aSpracklen, Cassandra, N1 aMercader, Josep, M1 aBoehnke, Michael1 aRotter, Jerome, I1 aVujkovic, Marijana1 aVoight, Benjamin, F1 aMorris, Andrew, P1 aZeggini, Eleftheria1 aVA Million Veteran Program uhttps://chs-nhlbi.org/node/9619