%0 Journal Article %J Exp Gerontol %D 2009 %T Inflammation and stress-related candidate genes, plasma interleukin-6 levels, and longevity in older adults. %A Walston, Jeremy D %A Matteini, Amy M %A Nievergelt, Caroline %A Lange, Leslie A %A Fallin, Dani M %A Barzilai, Nir %A Ziv, Elad %A Pawlikowska, Ludmila %A Kwok, Pui %A Cummings, Steve R %A Kooperberg, Charles %A LaCroix, Andrea %A Tracy, Russell P %A Atzmon, Gil %A Lange, Ethan M %A Reiner, Alex P %K Aged %K Aged, 80 and over %K Aging %K Cardiovascular Diseases %K Case-Control Studies %K Female %K Genetic Variation %K Genotype %K Humans %K Inflammation %K Interleukin-6 %K Longevity %K Male %K Phenotype %K Poly (ADP-Ribose) Polymerase-1 %K Poly(ADP-ribose) Polymerases %K Risk Factors %X

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.

%B Exp Gerontol %V 44 %P 350-5 %8 2009 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/19249341?dopt=Abstract %R 10.1016/j.exger.2009.02.004 %0 Journal Article %J Circ Cardiovasc Genet %D 2011 %T Association of genetic variants and incident coronary heart disease in multiethnic cohorts: the PAGE study. %A Franceschini, Nora %A Carty, Cara %A Bůzková, Petra %A Reiner, Alex P %A Garrett, Tiana %A Lin, Yi %A Vöckler, Jens-S %A Hindorff, Lucia A %A Cole, Shelley A %A Boerwinkle, Eric %A Lin, Dan-Yu %A Bookman, Ebony %A Best, Lyle G %A Bella, Jonathan N %A Eaton, Charles %A Greenland, Philip %A Jenny, Nancy %A North, Kari E %A Taverna, Darin %A Young, Alicia M %A Deelman, Ewa %A Kooperberg, Charles %A Psaty, Bruce %A Heiss, Gerardo %K Aged %K Aged, 80 and over %K Continental Population Groups %K Coronary Disease %K Female %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Prospective Studies %X

BACKGROUND: 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.

%B Circ Cardiovasc Genet %V 4 %P 661-72 %8 2011 Dec %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/22042884?dopt=Abstract %R 10.1161/CIRCGENETICS.111.960096 %0 Journal Article %J PLoS Genet %D 2011 %T Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study. %A Dumitrescu, Logan %A Carty, Cara L %A Taylor, Kira %A Schumacher, Fredrick R %A Hindorff, Lucia A %A Ambite, José L %A Anderson, Garnet %A Best, Lyle G %A Brown-Gentry, Kristin %A Bůzková, Petra %A Carlson, Christopher S %A Cochran, Barbara %A Cole, Shelley A %A Devereux, Richard B %A Duggan, Dave %A Eaton, Charles B %A Fornage, Myriam %A Franceschini, Nora %A Haessler, Jeff %A Howard, Barbara V %A Johnson, Karen C %A Laston, Sandra %A Kolonel, Laurence N %A Lee, Elisa T %A MacCluer, Jean W %A Manolio, Teri A %A Pendergrass, Sarah A %A Quibrera, Miguel %A Shohet, Ralph V %A Wilkens, Lynne R %A Haiman, Christopher A %A Le Marchand, Loïc %A Buyske, Steven %A Kooperberg, Charles %A North, Kari E %A Crawford, Dana C %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Continental Population Groups %K Female %K Gene Frequency %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Lipid Metabolism %K Lipoproteins, HDL %K Lipoproteins, LDL %K Male %K Middle Aged %K Molecular Epidemiology %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Risk Factors %K Triglycerides %K Young Adult %X

For 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.

%B PLoS Genet %V 7 %P e1002138 %8 2011 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/21738485?dopt=Abstract %R 10.1371/journal.pgen.1002138 %0 Journal Article %J Am J Epidemiol %D 2011 %T The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study. %A Matise, Tara C %A Ambite, Jose Luis %A Buyske, Steven %A Carlson, Christopher S %A Cole, Shelley A %A Crawford, Dana C %A Haiman, Christopher A %A Heiss, Gerardo %A Kooperberg, Charles %A Marchand, Loic Le %A Manolio, Teri A %A North, Kari E %A Peters, Ulrike %A Ritchie, Marylyn D %A Hindorff, Lucia A %A Haines, Jonathan L %K Epidemiologic Methods %K Epidemiologic Research Design %K Ethnic Groups %K Genetic Association Studies %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Interinstitutional Relations %K Multifactorial Inheritance %K National Human Genome Research Institute (U.S.) %K Phenotype %K Pilot Projects %K Research Design %K Risk Factors %K United States %X

Genetic 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.

%B Am J Epidemiol %V 174 %P 849-59 %8 2011 Oct 01 %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/21836165?dopt=Abstract %R 10.1093/aje/kwr160 %0 Journal Article %J PLoS Genet %D 2011 %T A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. %A Avery, Christy L %A He, Qianchuan %A North, Kari E %A Ambite, José L %A Boerwinkle, Eric %A Fornage, Myriam %A Hindorff, Lucia A %A Kooperberg, Charles %A Meigs, James B %A Pankow, James S %A Pendergrass, Sarah A %A Psaty, Bruce M %A Ritchie, Marylyn D %A Rotter, Jerome I %A Taylor, Kent D %A Wilkens, Lynne R %A Heiss, Gerardo %A Lin, Dan Yu %K African Americans %K Apolipoprotein C-I %K Blood Glucose %K Dyslipidemias %K European Continental Ancestry Group %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genome, Human %K Humans %K Metabolic Syndrome %K Obesity, Abdominal %K Phenotype %K Phospholipase C gamma %K Polymorphism, Single Nucleotide %K Quantitative Trait, Heritable %K Ubiquitin-Protein Ligases %K Vascular Diseases %X

Despite 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.

%B PLoS Genet %V 7 %P e1002322 %8 2011 Oct %G eng %N 10 %1 http://www.ncbi.nlm.nih.gov/pubmed/22022282?dopt=Abstract %R 10.1371/journal.pgen.1002322 %0 Journal Article %J Circ Cardiovasc Genet %D 2012 %T Associations 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. %A Carty, Cara L %A Bůzková, Petra %A Fornage, Myriam %A Franceschini, Nora %A Cole, Shelley %A Heiss, Gerardo %A Hindorff, Lucia A %A Howard, Barbara V %A Mann, Sue %A Martin, Lisa W %A Zhang, Ying %A Matise, Tara C %A Prentice, Ross %A Reiner, Alexander P %A Kooperberg, Charles %K Aged %K Aged, 80 and over %K Cardiovascular Diseases %K Cholesterol, HDL %K Cholesterol, LDL %K European Continental Ancestry Group %K Female %K Genetics, Population %K Genome-Wide Association Study %K Genomics %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Factors %K Stroke %K Triglycerides %X

BACKGROUND: 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.

%B Circ Cardiovasc Genet %V 5 %P 210-6 %8 2012 Apr 01 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/22403240?dopt=Abstract %R 10.1161/CIRCGENETICS.111.962191 %0 Journal Article %J PLoS One %D 2012 %T Evaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study. %A Buyske, Steven %A Wu, Ying %A Carty, Cara L %A Cheng, Iona %A Assimes, Themistocles L %A Dumitrescu, Logan %A Hindorff, Lucia A %A Mitchell, Sabrina %A Ambite, Jose Luis %A Boerwinkle, Eric %A Bůzková, Petra %A Carlson, Chris S %A Cochran, Barbara %A Duggan, David %A Eaton, Charles B %A Fesinmeyer, Megan D %A Franceschini, Nora %A Haessler, Jeffrey %A Jenny, Nancy %A Kang, Hyun Min %A Kooperberg, Charles %A Lin, Yi %A Le Marchand, Loïc %A Matise, Tara C %A Robinson, Jennifer G %A Rodriguez, Carlos %A Schumacher, Fredrick R %A Voight, Benjamin F %A Young, Alicia %A Manolio, Teri A %A Mohlke, Karen L %A Haiman, Christopher A %A Peters, Ulrike %A Crawford, Dana C %A North, Kari E %K African Americans %K Cardiovascular Diseases %K Cholesterol Ester Transfer Proteins %K Cholesterol, HDL %K Cholesterol, LDL %K Chromosomes, Human %K Cohort Studies %K Gene Frequency %K Genome-Wide Association Study %K Genotype %K Humans %K Metabolic Diseases %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %X

The 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.

%B PLoS One %V 7 %P e35651 %8 2012 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/22539988?dopt=Abstract %R 10.1371/journal.pone.0035651 %0 Journal Article %J PLoS Genet %D 2012 %T Fine-mapping and initial characterization of QT interval loci in African Americans. %A Avery, Christy L %A Sethupathy, Praveen %A Buyske, Steven %A He, Qianchuan %A Lin, Dan-Yu %A Arking, Dan E %A Carty, Cara L %A Duggan, David %A Fesinmeyer, Megan D %A Hindorff, Lucia A %A Jeff, Janina M %A Klein, Liviu %A Patton, Kristen K %A Peters, Ulrike %A Shohet, Ralph V %A Sotoodehnia, Nona %A Young, Alicia M %A Kooperberg, Charles %A Haiman, Christopher A %A Mohlke, Karen L %A Whitsel, Eric A %A North, Kari E %K African Americans %K Aged %K Computational Biology %K Electrocardiography %K European Continental Ancestry Group %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Male %K Metagenomics %K Middle Aged %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Quantitative Trait, Heritable %K Risk Factors %K Tachycardia %K United States %X

The 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.

%B PLoS Genet %V 8 %P e1002870 %8 2012 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/22912591?dopt=Abstract %R 10.1371/journal.pgen.1002870 %0 Journal Article %J Nat Genet %D 2012 %T Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. %A Estrada, Karol %A Styrkarsdottir, Unnur %A Evangelou, Evangelos %A Hsu, Yi-Hsiang %A Duncan, Emma L %A Ntzani, Evangelia E %A Oei, Ling %A Albagha, Omar M E %A Amin, Najaf %A Kemp, John P %A Koller, Daniel L %A Li, Guo %A Liu, Ching-Ti %A Minster, Ryan L %A Moayyeri, Alireza %A Vandenput, Liesbeth %A Willner, Dana %A Xiao, Su-Mei %A Yerges-Armstrong, Laura M %A Zheng, Hou-Feng %A Alonso, Nerea %A Eriksson, Joel %A Kammerer, Candace M %A Kaptoge, Stephen K %A Leo, Paul J %A Thorleifsson, Gudmar %A Wilson, Scott G %A Wilson, James F %A Aalto, Ville %A Alen, Markku %A Aragaki, Aaron K %A Aspelund, Thor %A Center, Jacqueline R %A Dailiana, Zoe %A Duggan, David J %A Garcia, Melissa %A García-Giralt, Natalia %A Giroux, Sylvie %A Hallmans, Göran %A Hocking, Lynne J %A Husted, Lise Bjerre %A Jameson, Karen A %A Khusainova, Rita %A Kim, Ghi Su %A Kooperberg, Charles %A Koromila, Theodora %A Kruk, Marcin %A Laaksonen, Marika %A LaCroix, Andrea Z %A Lee, Seung Hun %A Leung, Ping C %A Lewis, Joshua R %A Masi, Laura %A Mencej-Bedrac, Simona %A Nguyen, Tuan V %A Nogues, Xavier %A Patel, Millan S %A Prezelj, Janez %A Rose, Lynda M %A Scollen, Serena %A Siggeirsdottir, Kristin %A Smith, Albert V %A Svensson, Olle %A Trompet, Stella %A Trummer, Olivia %A van Schoor, Natasja M %A Woo, Jean %A Zhu, Kun %A Balcells, Susana %A Brandi, Maria Luisa %A Buckley, Brendan M %A Cheng, Sulin %A Christiansen, Claus %A Cooper, Cyrus %A Dedoussis, George %A Ford, Ian %A Frost, Morten %A Goltzman, David %A González-Macías, Jesús %A Kähönen, Mika %A Karlsson, Magnus %A Khusnutdinova, Elza %A Koh, Jung-Min %A Kollia, Panagoula %A Langdahl, Bente Lomholt %A Leslie, William D %A Lips, Paul %A Ljunggren, Osten %A Lorenc, Roman S %A Marc, Janja %A Mellström, Dan %A Obermayer-Pietsch, Barbara %A Olmos, José M %A Pettersson-Kymmer, Ulrika %A Reid, David M %A Riancho, José A %A Ridker, Paul M %A Rousseau, François %A Slagboom, P Eline %A Tang, Nelson L S %A Urreizti, Roser %A Van Hul, Wim %A Viikari, Jorma %A Zarrabeitia, María T %A Aulchenko, Yurii S %A Castano-Betancourt, Martha %A Grundberg, Elin %A Herrera, Lizbeth %A Ingvarsson, Thorvaldur %A Johannsdottir, Hrefna %A Kwan, Tony %A Li, Rui %A Luben, Robert %A Medina-Gómez, Carolina %A Palsson, Stefan Th %A Reppe, Sjur %A Rotter, Jerome I %A Sigurdsson, Gunnar %A van Meurs, Joyce B J %A Verlaan, Dominique %A Williams, Frances M K %A Wood, Andrew R %A Zhou, Yanhua %A Gautvik, Kaare M %A Pastinen, Tomi %A Raychaudhuri, Soumya %A Cauley, Jane A %A Chasman, Daniel I %A Clark, Graeme R %A Cummings, Steven R %A Danoy, Patrick %A Dennison, Elaine M %A Eastell, Richard %A Eisman, John A %A Gudnason, Vilmundur %A Hofman, Albert %A Jackson, Rebecca D %A Jones, Graeme %A Jukema, J Wouter %A Khaw, Kay-Tee %A Lehtimäki, Terho %A Liu, Yongmei %A Lorentzon, Mattias %A McCloskey, Eugene %A Mitchell, Braxton D %A Nandakumar, Kannabiran %A Nicholson, Geoffrey C %A Oostra, Ben A %A Peacock, Munro %A Pols, Huibert A P %A Prince, Richard L %A Raitakari, Olli %A Reid, Ian R %A Robbins, John %A Sambrook, Philip N %A Sham, Pak Chung %A Shuldiner, Alan R %A Tylavsky, Frances A %A van Duijn, Cornelia M %A Wareham, Nick J %A Cupples, L Adrienne %A Econs, Michael J %A Evans, David M %A Harris, Tamara B %A Kung, Annie Wai Chee %A Psaty, Bruce M %A Reeve, Jonathan %A Spector, Timothy D %A Streeten, Elizabeth A %A Zillikens, M Carola %A Thorsteinsdottir, Unnur %A Ohlsson, Claes %A Karasik, David %A Richards, J Brent %A Brown, Matthew A %A Stefansson, Kari %A Uitterlinden, André G %A Ralston, Stuart H %A Ioannidis, John P A %A Kiel, Douglas P %A Rivadeneira, Fernando %K Bone Density %K Computational Biology %K European Continental Ancestry Group %K Extracellular Matrix Proteins %K Female %K Femur Neck %K Fractures, Bone %K Gene Expression Profiling %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Glycoproteins %K Humans %K Intercellular Signaling Peptides and Proteins %K Low Density Lipoprotein Receptor-Related Protein-5 %K Lumbar Vertebrae %K Male %K Mitochondrial Membrane Transport Proteins %K Osteoporosis %K Phosphoproteins %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Risk Factors %K Spectrin %X

Bone 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.

%B Nat Genet %V 44 %P 491-501 %8 2012 Apr 15 %G eng %N 5 %R 10.1038/ng.2249 %0 Journal Article %J Am J Hum Genet %D 2013 %T Fine Mapping and Identification of BMI Loci in African Americans. %A Gong, Jian %A Schumacher, Fredrick %A Lim, Unhee %A Hindorff, Lucia A %A Haessler, Jeff %A Buyske, Steven %A Carlson, Christopher S %A Rosse, Stephanie %A Bůzková, Petra %A Fornage, Myriam %A Gross, Myron %A Pankratz, Nathan %A Pankow, James S %A Schreiner, Pamela J %A Cooper, Richard %A Ehret, Georg %A Gu, C Charles %A Houston, Denise %A Irvin, Marguerite R %A Jackson, Rebecca %A Kuller, Lew %A Henderson, Brian %A Cheng, Iona %A Wilkens, Lynne %A Leppert, Mark %A Lewis, Cora E %A Li, Rongling %A Nguyen, Khanh-Dung H %A Goodloe, Robert %A Farber-Eger, Eric %A Boston, Jonathan %A Dilks, Holli H %A Ritchie, Marylyn D %A Fowke, Jay %A Pooler, Loreall %A Graff, Misa %A Fernandez-Rhodes, Lindsay %A Cochrane, Barbara %A Boerwinkle, Eric %A Kooperberg, Charles %A Matise, Tara C %A Le Marchand, Loïc %A Crawford, Dana C %A Haiman, Christopher A %A North, Kari E %A Peters, Ulrike %K Adult %K African Americans %K Aged %K Aged, 80 and over %K Body Mass Index %K Female %K Genetic Loci %K Genetic Predisposition to Disease %K Genome, Human %K Genome-Wide Association Study %K Genotype %K Humans %K Linkage Disequilibrium %K Male %K Middle Aged %K Obesity %K Polymorphism, Single Nucleotide %K Young Adult %X

Genome-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.

%B Am J Hum Genet %V 93 %P 661-71 %8 2013 Oct 3 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/24094743?dopt=Abstract %R 10.1016/j.ajhg.2013.08.012 %0 Journal Article %J PLoS Genet %D 2013 %T Genome-wide association of body fat distribution in African ancestry populations suggests new loci. %A Liu, Ching-Ti %A Monda, Keri L %A Taylor, Kira C %A Lange, Leslie %A Demerath, Ellen W %A Palmas, Walter %A Wojczynski, Mary K %A Ellis, Jaclyn C %A Vitolins, Mara Z %A Liu, Simin %A Papanicolaou, George J %A Irvin, Marguerite R %A Xue, Luting %A Griffin, Paula J %A Nalls, Michael A %A Adeyemo, Adebowale %A Liu, Jiankang %A Li, Guo %A Ruiz-Narvaez, Edward A %A Chen, Wei-Min %A Chen, Fang %A Henderson, Brian E %A Millikan, Robert C %A Ambrosone, Christine B %A Strom, Sara S %A Guo, Xiuqing %A Andrews, Jeanette S %A Sun, Yan V %A Mosley, Thomas H %A Yanek, Lisa R %A Shriner, Daniel %A Haritunians, Talin %A Rotter, Jerome I %A Speliotes, Elizabeth K %A Smith, Megan %A Rosenberg, Lynn %A Mychaleckyj, Josyf %A Nayak, Uma %A Spruill, Ida %A Garvey, W Timothy %A Pettaway, Curtis %A Nyante, Sarah %A Bandera, Elisa V %A Britton, Angela F %A Zonderman, Alan B %A Rasmussen-Torvik, Laura J %A Chen, Yii-Der Ida %A Ding, Jingzhong %A Lohman, Kurt %A Kritchevsky, Stephen B %A Zhao, Wei %A Peyser, Patricia A %A Kardia, Sharon L R %A Kabagambe, Edmond %A Broeckel, Ulrich %A Chen, Guanjie %A Zhou, Jie %A Wassertheil-Smoller, Sylvia %A Neuhouser, Marian L %A Rampersaud, Evadnie %A Psaty, Bruce %A Kooperberg, Charles %A Manson, JoAnn E %A Kuller, Lewis H %A Ochs-Balcom, Heather M %A Johnson, Karen C %A Sucheston, Lara %A Ordovas, Jose M %A Palmer, Julie R %A Haiman, Christopher A %A McKnight, Barbara %A Howard, Barbara V %A Becker, Diane M %A Bielak, Lawrence F %A Liu, Yongmei %A Allison, Matthew A %A Grant, Struan F A %A Burke, Gregory L %A Patel, Sanjay R %A Schreiner, Pamela J %A Borecki, Ingrid B %A Evans, Michele K %A Taylor, Herman %A Sale, Michèle M %A Howard, Virginia %A Carlson, Christopher S %A Rotimi, Charles N %A Cushman, Mary %A Harris, Tamara B %A Reiner, Alexander P %A Cupples, L Adrienne %A North, Kari E %A Fox, Caroline S %K Adiposity %K African Continental Ancestry Group %K Body Fat Distribution %K European Continental Ancestry Group %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Obesity %K Polymorphism, Single Nucleotide %K Waist-Hip Ratio %X

Central 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.

%B PLoS Genet %V 9 %P e1003681 %8 2013 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/23966867?dopt=Abstract %R 10.1371/journal.pgen.1003681 %0 Journal Article %J BMC Genet %D 2013 %T Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study. %A Taylor, Kira C %A Carty, Cara L %A Dumitrescu, Logan %A Bůzková, Petra %A Cole, Shelley A %A Hindorff, Lucia %A Schumacher, Fred R %A Wilkens, Lynne R %A Shohet, Ralph V %A Quibrera, P Miguel %A Johnson, Karen C %A Henderson, Brian E %A Haessler, Jeff %A Franceschini, Nora %A Eaton, Charles B %A Duggan, David J %A Cochran, Barbara %A Cheng, Iona %A Carlson, Chris S %A Brown-Gentry, Kristin %A Anderson, Garnet %A Ambite, Jose Luis %A Haiman, Christopher %A Le Marchand, Loïc %A Kooperberg, Charles %A Crawford, Dana C %A Buyske, Steven %A North, Kari E %A Fornage, Myriam %K Female %K Genetic Heterogeneity %K Genome, Human %K Genome-Wide Association Study %K Humans %K Lipids %K Male %K Polymorphism, Single Nucleotide %K Population Groups %X

BACKGROUND: 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.

%B BMC Genet %V 14 %P 33 %8 2013 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/23634756?dopt=Abstract %R 10.1186/1471-2156-14-33 %0 Journal Article %J Nat Genet %D 2013 %T A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. %A Monda, Keri L %A Chen, Gary K %A Taylor, Kira C %A Palmer, Cameron %A Edwards, Todd L %A Lange, Leslie A %A Ng, Maggie C Y %A Adeyemo, Adebowale A %A Allison, Matthew A %A Bielak, Lawrence F %A Chen, Guanjie %A Graff, Mariaelisa %A Irvin, Marguerite R %A Rhie, Suhn K %A Li, Guo %A Liu, Yongmei %A Liu, Youfang %A Lu, Yingchang %A Nalls, Michael A %A Sun, Yan V %A Wojczynski, Mary K %A Yanek, Lisa R %A Aldrich, Melinda C %A Ademola, Adeyinka %A Amos, Christopher I %A Bandera, Elisa V %A Bock, Cathryn H %A Britton, Angela %A Broeckel, Ulrich %A Cai, Quiyin %A Caporaso, Neil E %A Carlson, Chris S %A Carpten, John %A Casey, Graham %A Chen, Wei-Min %A Chen, Fang %A Chen, Yii-der I %A Chiang, Charleston W K %A Coetzee, Gerhard A %A Demerath, Ellen %A Deming-Halverson, Sandra L %A Driver, Ryan W %A Dubbert, Patricia %A Feitosa, Mary F %A Feng, Ye %A Freedman, Barry I %A Gillanders, Elizabeth M %A Gottesman, Omri %A Guo, Xiuqing %A Haritunians, Talin %A Harris, Tamara %A Harris, Curtis C %A Hennis, Anselm J M %A Hernandez, Dena G %A McNeill, Lorna H %A Howard, Timothy D %A Howard, Barbara V %A Howard, Virginia J %A Johnson, Karen C %A Kang, Sun J %A Keating, Brendan J %A Kolb, Suzanne %A Kuller, Lewis H %A Kutlar, Abdullah %A Langefeld, Carl D %A Lettre, Guillaume %A Lohman, Kurt %A Lotay, Vaneet %A Lyon, Helen %A Manson, JoAnn E %A Maixner, William %A Meng, Yan A %A Monroe, Kristine R %A Morhason-Bello, Imran %A Murphy, Adam B %A Mychaleckyj, Josyf C %A Nadukuru, Rajiv %A Nathanson, Katherine L %A Nayak, Uma %A N'diaye, Amidou %A Nemesure, Barbara %A Wu, Suh-Yuh %A Leske, M Cristina %A Neslund-Dudas, Christine %A Neuhouser, Marian %A Nyante, Sarah %A Ochs-Balcom, Heather %A Ogunniyi, Adesola %A Ogundiran, Temidayo O %A Ojengbede, Oladosu %A Olopade, Olufunmilayo I %A Palmer, Julie R %A Ruiz-Narvaez, Edward A %A Palmer, Nicholette D %A Press, Michael F %A Rampersaud, Evandine %A Rasmussen-Torvik, Laura J %A Rodriguez-Gil, Jorge L %A Salako, Babatunde %A Schadt, Eric E %A Schwartz, Ann G %A Shriner, Daniel A %A Siscovick, David %A Smith, Shad B %A Wassertheil-Smoller, Sylvia %A Speliotes, Elizabeth K %A Spitz, Margaret R %A Sucheston, Lara %A Taylor, Herman %A Tayo, Bamidele O %A Tucker, Margaret A %A Van Den Berg, David J %A Edwards, Digna R Velez %A Wang, Zhaoming %A Wiencke, John K %A Winkler, Thomas W %A Witte, John S %A Wrensch, Margaret %A Wu, Xifeng %A Yang, James J %A Levin, Albert M %A Young, Taylor R %A Zakai, Neil A %A Cushman, Mary %A Zanetti, Krista A %A Zhao, Jing Hua %A Zhao, Wei %A Zheng, Yonglan %A Zhou, Jie %A Ziegler, Regina G %A Zmuda, Joseph M %A Fernandes, Jyotika K %A Gilkeson, Gary S %A Kamen, Diane L %A Hunt, Kelly J %A Spruill, Ida J %A Ambrosone, Christine B %A Ambs, Stefan %A Arnett, Donna K %A Atwood, Larry %A Becker, Diane M %A Berndt, Sonja I %A Bernstein, Leslie %A Blot, William J %A Borecki, Ingrid B %A Bottinger, Erwin P %A Bowden, Donald W %A Burke, Gregory %A Chanock, Stephen J %A Cooper, Richard S %A Ding, Jingzhong %A Duggan, David %A Evans, Michele K %A Fox, Caroline %A Garvey, W Timothy %A Bradfield, Jonathan P %A Hakonarson, Hakon %A Grant, Struan F A %A Hsing, Ann %A Chu, Lisa %A Hu, Jennifer J %A Huo, Dezheng %A Ingles, Sue A %A John, Esther M %A Jordan, Joanne M %A Kabagambe, Edmond K %A Kardia, Sharon L R %A Kittles, Rick A %A Goodman, Phyllis J %A Klein, Eric A %A Kolonel, Laurence N %A Le Marchand, Loïc %A Liu, Simin %A McKnight, Barbara %A Millikan, Robert C %A Mosley, Thomas H %A Padhukasahasram, Badri %A Williams, L Keoki %A Patel, Sanjay R %A Peters, Ulrike %A Pettaway, Curtis A %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Rotimi, Charles N %A Rybicki, Benjamin A %A Sale, Michèle M %A Schreiner, Pamela J %A Signorello, Lisa B %A Singleton, Andrew B %A Stanford, Janet L %A Strom, Sara S %A Thun, Michael J %A Vitolins, Mara %A Zheng, Wei %A Moore, Jason H %A Williams, Scott M %A Ketkar, Shamika %A Zhu, Xiaofeng %A Zonderman, Alan B %A Kooperberg, Charles %A Papanicolaou, George J %A Henderson, Brian E %A Reiner, Alex P %A Hirschhorn, Joel N %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %K African Americans %K Body Mass Index %K Case-Control Studies %K Gene Frequency %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Obesity %K Polymorphism, Single Nucleotide %X

Genome-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.

%B Nat Genet %V 45 %P 690-6 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23583978?dopt=Abstract %R 10.1038/ng.2608 %0 Journal Article %J Hum Genet %D 2013 %T No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population. %A Dumitrescu, Logan %A Carty, Cara L %A Franceschini, Nora %A Hindorff, Lucia A %A Cole, Shelley A %A Bůzková, Petra %A Schumacher, Fredrick R %A Eaton, Charles B %A Goodloe, Robert J %A Duggan, David J %A Haessler, Jeff %A Cochran, Barbara %A Henderson, Brian E %A Cheng, Iona %A Johnson, Karen C %A Carlson, Chris S %A Love, Shelly-Anne %A Brown-Gentry, Kristin %A Nato, Alejandro Q %A Quibrera, Miguel %A Shohet, Ralph V %A Ambite, Jose Luis %A Wilkens, Lynne R %A Le Marchand, Loïc %A Haiman, Christopher A %A Buyske, Steven %A Kooperberg, Charles %A North, Kari E %A Fornage, Myriam %A Crawford, Dana C %K Cholesterol, HDL %K Cholesterol, LDL %K Cohort Studies %K Ethnic Groups %K Female %K Gene Frequency %K Gene-Environment Interaction %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Lipid Metabolism %K Male %K Polymorphism, Single Nucleotide %K Prevalence %K Smoking %K Triglycerides %K Young Adult %X

Genome-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.

%B Hum Genet %V 132 %P 1427-31 %8 2013 Dec %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/24100633?dopt=Abstract %R 10.1007/s00439-013-1375-3 %0 Journal Article %J Ann Hum Genet %D 2013 %T Post-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. %A Dumitrescu, Logan %A Carty, Cara L %A Franceschini, Nora %A Hindorff, Lucia A %A Cole, Shelley A %A Bůzková, Petra %A Schumacher, Fredrick R %A Eaton, Charles B %A Goodloe, Robert J %A Duggan, David J %A Haessler, Jeff %A Cochran, Barbara %A Henderson, Brian E %A Cheng, Iona %A Johnson, Karen C %A Carlson, Chris S %A Love, Shelly-Ann %A Brown-Gentry, Kristin %A Nato, Alejandro Q %A Quibrera, Miguel %A Anderson, Garnet %A Shohet, Ralph V %A Ambite, Jose Luis %A Wilkens, Lynne R %A Marchand, Loic Le %A Haiman, Christopher A %A Buyske, Steven %A Kooperberg, Charles %A North, Kari E %A Fornage, Myriam %A Crawford, Dana C %K Adult %K Aged %K European Continental Ancestry Group %K Female %K Genetic Association Studies %K Genome-Wide Association Study %K Humans %K Lipids %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Quantitative Trait, Heritable %K Risk Factors %X

Numerous 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.

%B Ann Hum Genet %V 77 %P 416-25 %8 2013 Sep %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/23808484?dopt=Abstract %R 10.1111/ahg.12027 %0 Journal Article %J PLoS Genet %D 2013 %T A 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. %A Peters, Ulrike %A North, Kari E %A Sethupathy, Praveen %A Buyske, Steve %A Haessler, Jeff %A Jiao, Shuo %A Fesinmeyer, Megan D %A Jackson, Rebecca D %A Kuller, Lew H %A Rajkovic, Aleksandar %A Lim, Unhee %A Cheng, Iona %A Schumacher, Fred %A Wilkens, Lynne %A Li, Rongling %A Monda, Keri %A Ehret, Georg %A Nguyen, Khanh-Dung H %A Cooper, Richard %A Lewis, Cora E %A Leppert, Mark %A Irvin, Marguerite R %A Gu, C Charles %A Houston, Denise %A Bůzková, Petra %A Ritchie, Marylyn %A Matise, Tara C %A Le Marchand, Loïc %A Hindorff, Lucia A %A Crawford, Dana C %A Haiman, Christopher A %A Kooperberg, Charles %K Adaptor Proteins, Signal Transducing %K Adult %K African Americans %K Aged %K Aged, 80 and over %K Alleles %K Body Mass Index %K Chromosome Mapping %K Continental Population Groups %K European Continental Ancestry Group %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Male %K Metagenomics %K Middle Aged %K Obesity %K Proteins %X

Genetic 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.

%B PLoS Genet %V 9 %P e1003171 %8 2013 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/23341774?dopt=Abstract %R 10.1371/journal.pgen.1003171 %0 Journal Article %J PLoS Genet %D 2013 %T Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained. %A Wu, Ying %A Waite, Lindsay L %A Jackson, Anne U %A Sheu, Wayne H-H %A Buyske, Steven %A Absher, Devin %A Arnett, Donna K %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Carty, Cara L %A Cheng, Iona %A Cochran, Barbara %A Croteau-Chonka, Damien C %A Dumitrescu, Logan %A Eaton, Charles B %A Franceschini, Nora %A Guo, Xiuqing %A Henderson, Brian E %A Hindorff, Lucia A %A Kim, Eric %A Kinnunen, Leena %A Komulainen, Pirjo %A Lee, Wen-Jane %A Le Marchand, Loïc %A Lin, Yi %A Lindström, Jaana %A Lingaas-Holmen, Oddgeir %A Mitchell, Sabrina L %A Narisu, Narisu %A Robinson, Jennifer G %A Schumacher, Fred %A Stančáková, Alena %A Sundvall, Jouko %A Sung, Yun-Ju %A Swift, Amy J %A Wang, Wen-Chang %A Wilkens, Lynne %A Wilsgaard, Tom %A Young, Alicia M %A Adair, Linda S %A Ballantyne, Christie M %A Bůzková, Petra %A Chakravarti, Aravinda %A Collins, Francis S %A Duggan, David %A Feranil, Alan B %A Ho, Low-Tone %A Hung, Yi-Jen %A Hunt, Steven C %A Hveem, Kristian %A Juang, Jyh-Ming J %A Kesäniemi, Antero Y %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo A %A Lee, I-Te %A Leppert, Mark F %A Matise, Tara C %A Moilanen, Leena %A Njølstad, Inger %A Peters, Ulrike %A Quertermous, Thomas %A Rauramaa, Rainer %A Rotter, Jerome I %A Saramies, Jouko %A Tuomilehto, Jaakko %A Uusitupa, Matti %A Wang, Tzung-Dau %A Boehnke, Michael %A Haiman, Christopher A %A Chen, Yii-der I %A Kooperberg, Charles %A Assimes, Themistocles L %A Crawford, Dana C %A Hsiung, Chao A %A North, Kari E %A Mohlke, Karen L %K African Americans %K Apolipoproteins A %K Cholesterol, HDL %K Cholesterol, LDL %K European Continental Ancestry Group %K Genome-Wide Association Study %K Humans %K Lipoproteins, HDL %K Lipoproteins, LDL %K Proprotein Convertases %K Serine Endopeptidases %K Triglycerides %X

Genome-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.

%B PLoS Genet %V 9 %P e1003379 %8 2013 Mar %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/23555291?dopt=Abstract %R 10.1371/journal.pgen.1003379 %0 Journal Article %J BMJ %D 2014 %T Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data. %A Holmes, Michael V %A Dale, Caroline E %A Zuccolo, Luisa %A Silverwood, Richard J %A Guo, Yiran %A Ye, Zheng %A Prieto-Merino, David %A Dehghan, Abbas %A Trompet, Stella %A Wong, Andrew %A Cavadino, Alana %A Drogan, Dagmar %A Padmanabhan, Sandosh %A Li, Shanshan %A Yesupriya, Ajay %A Leusink, Maarten %A Sundström, Johan %A Hubacek, Jaroslav A %A Pikhart, Hynek %A Swerdlow, Daniel I %A Panayiotou, Andrie G %A Borinskaya, Svetlana A %A Finan, Chris %A Shah, Sonia %A Kuchenbaecker, Karoline B %A Shah, Tina %A Engmann, Jorgen %A Folkersen, Lasse %A Eriksson, Per %A Ricceri, Fulvio %A Melander, Olle %A Sacerdote, Carlotta %A Gamble, Dale M %A Rayaprolu, Sruti %A Ross, Owen A %A McLachlan, Stela %A Vikhireva, Olga %A Sluijs, Ivonne %A Scott, Robert A %A Adamkova, Vera %A Flicker, Leon %A Bockxmeer, Frank M van %A Power, Christine %A Marques-Vidal, Pedro %A Meade, Tom %A Marmot, Michael G %A Ferro, Jose M %A Paulos-Pinheiro, Sofia %A Humphries, Steve E %A Talmud, Philippa J %A Mateo Leach, Irene %A Verweij, Niek %A Linneberg, Allan %A Skaaby, Tea %A Doevendans, Pieter A %A Cramer, Maarten J %A van der Harst, Pim %A Klungel, Olaf H %A Dowling, Nicole F %A Dominiczak, Anna F %A Kumari, Meena %A Nicolaides, Andrew N %A Weikert, Cornelia %A Boeing, Heiner %A Ebrahim, Shah %A Gaunt, Tom R %A Price, Jackie F %A Lannfelt, Lars %A Peasey, Anne %A Kubinova, Ruzena %A Pajak, Andrzej %A Malyutina, Sofia %A Voevoda, Mikhail I %A Tamosiunas, Abdonas %A Maitland-van der Zee, Anke H %A Norman, Paul E %A Hankey, Graeme J %A Bergmann, Manuela M %A Hofman, Albert %A Franco, Oscar H %A Cooper, Jackie %A Palmen, Jutta %A Spiering, Wilko %A de Jong, Pim A %A Kuh, Diana %A Hardy, Rebecca %A Uitterlinden, André G %A Ikram, M Arfan %A Ford, Ian %A Hyppönen, Elina %A Almeida, Osvaldo P %A Wareham, Nicholas J %A Khaw, Kay-Tee %A Hamsten, Anders %A Husemoen, Lise Lotte N %A Tjønneland, Anne %A Tolstrup, Janne S %A Rimm, Eric %A Beulens, Joline W J %A Verschuren, W M Monique %A Onland-Moret, N Charlotte %A Hofker, Marten H %A Wannamethee, S Goya %A Whincup, Peter H %A Morris, Richard %A Vicente, Astrid M %A Watkins, Hugh %A Farrall, Martin %A Jukema, J Wouter %A Meschia, James %A Cupples, L Adrienne %A Sharp, Stephen J %A Fornage, Myriam %A Kooperberg, Charles %A LaCroix, Andrea Z %A Dai, James Y %A Lanktree, Matthew B %A Siscovick, David S %A Jorgenson, Eric %A Spring, Bonnie %A Coresh, Josef %A Li, Yun R %A Buxbaum, Sarah G %A Schreiner, Pamela J %A Ellison, R Curtis %A Tsai, Michael Y %A Patel, Sanjay R %A Redline, Susan %A Johnson, Andrew D %A Hoogeveen, Ron C %A Hakonarson, Hakon %A Rotter, Jerome I %A Boerwinkle, Eric %A de Bakker, Paul I W %A Kivimaki, Mika %A Asselbergs, Folkert W %A Sattar, Naveed %A Lawlor, Debbie A %A Whittaker, John %A Davey Smith, George %A Mukamal, Kenneth %A Psaty, Bruce M %A Wilson, James G %A Lange, Leslie A %A Hamidovic, Ajna %A Hingorani, Aroon D %A Nordestgaard, Børge G %A Bobak, Martin %A Leon, David A %A Langenberg, Claudia %A Palmer, Tom M %A Reiner, Alex P %A Keating, Brendan J %A Dudbridge, Frank %A Casas, Juan P %K Adult %K Aged %K Alcohol Dehydrogenase %K Alcohol Drinking %K Biomarkers %K Coronary Disease %K Female %K Genetic Markers %K Genotype %K Humans %K Male %K Mendelian Randomization Analysis %K Middle Aged %K Models, Statistical %K Polymorphism, Single Nucleotide %K Stroke %X

OBJECTIVE: 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.

%B BMJ %V 349 %P g4164 %8 2014 Jul 10 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/25011450?dopt=Abstract %R 10.1136/bmj.g4164 %0 Journal Article %J Am J Hum Genet %D 2014 %T Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. %A Peloso, Gina M %A Auer, Paul L %A Bis, Joshua C %A Voorman, Arend %A Morrison, Alanna C %A Stitziel, Nathan O %A Brody, Jennifer A %A Khetarpal, Sumeet A %A Crosby, Jacy R %A Fornage, Myriam %A Isaacs, Aaron %A Jakobsdottir, Johanna %A Feitosa, Mary F %A Davies, Gail %A Huffman, Jennifer E %A Manichaikul, Ani %A Davis, Brian %A Lohman, Kurt %A Joon, Aron Y %A Smith, Albert V %A Grove, Megan L %A Zanoni, Paolo %A Redon, Valeska %A Demissie, Serkalem %A Lawson, Kim %A Peters, Ulrike %A Carlson, Christopher %A Jackson, Rebecca D %A Ryckman, Kelli K %A Mackey, Rachel H %A Robinson, Jennifer G %A Siscovick, David S %A Schreiner, Pamela J %A Mychaleckyj, Josyf C %A Pankow, James S %A Hofman, Albert %A Uitterlinden, André G %A Harris, Tamara B %A Taylor, Kent D %A Stafford, Jeanette M %A Reynolds, Lindsay M %A Marioni, Riccardo E %A Dehghan, Abbas %A Franco, Oscar H %A Patel, Aniruddh P %A Lu, Yingchang %A Hindy, George %A Gottesman, Omri %A Bottinger, Erwin P %A Melander, Olle %A Orho-Melander, Marju %A Loos, Ruth J F %A Duga, Stefano %A Merlini, Piera Angelica %A Farrall, Martin %A Goel, Anuj %A Asselta, Rosanna %A Girelli, Domenico %A Martinelli, Nicola %A Shah, Svati H %A Kraus, William E %A Li, Mingyao %A Rader, Daniel J %A Reilly, Muredach P %A McPherson, Ruth %A Watkins, Hugh %A Ardissino, Diego %A Zhang, Qunyuan %A Wang, Judy %A Tsai, Michael Y %A Taylor, Herman A %A Correa, Adolfo %A Griswold, Michael E %A Lange, Leslie A %A Starr, John M %A Rudan, Igor %A Eiriksdottir, Gudny %A Launer, Lenore J %A Ordovas, Jose M %A Levy, Daniel %A Chen, Y-D Ida %A Reiner, Alexander P %A Hayward, Caroline %A Polasek, Ozren %A Deary, Ian J %A Borecki, Ingrid B %A Liu, Yongmei %A Gudnason, Vilmundur %A Wilson, James G %A van Duijn, Cornelia M %A Kooperberg, Charles %A Rich, Stephen S %A Psaty, Bruce M %A Rotter, Jerome I %A O'Donnell, Christopher J %A Rice, Kenneth %A Boerwinkle, Eric %A Kathiresan, Sekar %A Cupples, L Adrienne %K 1-Alkyl-2-acetylglycerophosphocholine Esterase %K Adult %K African Continental Ancestry Group %K Aged %K Alleles %K Animals %K Cholesterol, HDL %K Cholesterol, LDL %K Cohort Studies %K Coronary Disease %K European Continental Ancestry Group %K Female %K Gene Frequency %K Genetic Association Studies %K Genetic Code %K Genetic Variation %K Humans %K Linear Models %K Male %K Mice %K Mice, Inbred C57BL %K Microtubule-Associated Proteins %K Middle Aged %K Phenotype %K Sequence Analysis, DNA %K Subtilisins %K Triglycerides %X

Low-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.

%B Am J Hum Genet %V 94 %P 223-32 %8 2014 Feb 06 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24507774?dopt=Abstract %R 10.1016/j.ajhg.2014.01.009 %0 Journal Article %J Epidemiology %D 2014 %T Evidence of heterogeneity by race/ethnicity in genetic determinants of QT interval. %A Seyerle, Amanda A %A Young, Alicia M %A Jeff, Janina M %A Melton, Phillip E %A Jorgensen, Neal W %A Lin, Yi %A Carty, Cara L %A Deelman, Ewa %A Heckbert, Susan R %A Hindorff, Lucia A %A Jackson, Rebecca D %A Martin, Lisa W %A Okin, Peter M %A Perez, Marco V %A Psaty, Bruce M %A Soliman, Elsayed Z %A Whitsel, Eric A %A North, Kari E %A Laston, Sandra %A Kooperberg, Charles %A Avery, Christy L %K Aged %K Continental Population Groups %K Electrocardiography %K Female %K Genetic Predisposition to Disease %K Haplotypes %K Humans %K Long QT Syndrome %K Male %K Middle Aged %K Phenotype %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Quantitative Trait, Heritable %K Risk Factors %X

BACKGROUND: 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.

%B Epidemiology %V 25 %P 790-8 %8 2014 Nov %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/25166880?dopt=Abstract %R 10.1097/EDE.0000000000000168 %0 Journal Article %J N Engl J Med %D 2014 %T Loss-of-function mutations in APOC3, triglycerides, and coronary disease. %A Crosby, Jacy %A Peloso, Gina M %A Auer, Paul L %A Crosslin, David R %A Stitziel, Nathan O %A Lange, Leslie A %A Lu, Yingchang %A Tang, Zheng-Zheng %A Zhang, He %A Hindy, George %A Masca, Nicholas %A Stirrups, Kathleen %A Kanoni, Stavroula %A Do, Ron %A Jun, Goo %A Hu, Youna %A Kang, Hyun Min %A Xue, Chenyi %A Goel, Anuj %A Farrall, Martin %A Duga, Stefano %A Merlini, Pier Angelica %A Asselta, Rosanna %A Girelli, Domenico %A Olivieri, Oliviero %A Martinelli, Nicola %A Yin, Wu %A Reilly, Dermot %A Speliotes, Elizabeth %A Fox, Caroline S %A Hveem, Kristian %A Holmen, Oddgeir L %A Nikpay, Majid %A Farlow, Deborah N %A Assimes, Themistocles L %A Franceschini, Nora %A Robinson, Jennifer %A North, Kari E %A Martin, Lisa W %A DePristo, Mark %A Gupta, Namrata %A Escher, Stefan A %A Jansson, Jan-Håkan %A Van Zuydam, Natalie %A Palmer, Colin N A %A Wareham, Nicholas %A Koch, Werner %A Meitinger, Thomas %A Peters, Annette %A Lieb, Wolfgang %A Erbel, Raimund %A König, Inke R %A Kruppa, Jochen %A Degenhardt, Franziska %A Gottesman, Omri %A Bottinger, Erwin P %A O'Donnell, Christopher J %A Psaty, Bruce M %A Ballantyne, Christie M %A Abecasis, Goncalo %A Ordovas, Jose M %A Melander, Olle %A Watkins, Hugh %A Orho-Melander, Marju %A Ardissino, Diego %A Loos, Ruth J F %A McPherson, Ruth %A Willer, Cristen J %A Erdmann, Jeanette %A Hall, Alistair S %A Samani, Nilesh J %A Deloukas, Panos %A Schunkert, Heribert %A Wilson, James G %A Kooperberg, Charles %A Rich, Stephen S %A Tracy, Russell P %A Lin, Dan-Yu %A Altshuler, David %A Gabriel, Stacey %A Nickerson, Deborah A %A Jarvik, Gail P %A Cupples, L Adrienne %A Reiner, Alex P %A Boerwinkle, Eric %A Kathiresan, Sekar %K African Continental Ancestry Group %K Apolipoprotein C-III %K Coronary Disease %K European Continental Ancestry Group %K Exome %K Genotype %K Heterozygote %K Humans %K Liver %K Mutation %K Risk Factors %K Sequence Analysis, DNA %K Triglycerides %X

BACKGROUND: 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.).

%B N Engl J Med %V 371 %P 22-31 %8 2014 Jul 3 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/24941081?dopt=Abstract %R 10.1056/NEJMoa1307095 %0 Journal Article %J Hum Mol Genet %D 2014 %T Meta-analysis of loci associated with age at natural menopause in African-American women. %A Chen, Christina T L %A Liu, Ching-Ti %A Chen, Gary K %A Andrews, Jeanette S %A Arnold, Alice M %A Dreyfus, Jill %A Franceschini, Nora %A Garcia, Melissa E %A Kerr, Kathleen F %A Li, Guo %A Lohman, Kurt K %A Musani, Solomon K %A Nalls, Michael A %A Raffel, Leslie J %A Smith, Jennifer %A Ambrosone, Christine B %A Bandera, Elisa V %A Bernstein, Leslie %A Britton, Angela %A Brzyski, Robert G %A Cappola, Anne %A Carlson, Christopher S %A Couper, David %A Deming, Sandra L %A Goodarzi, Mark O %A Heiss, Gerardo %A John, Esther M %A Lu, Xiaoning %A Le Marchand, Loïc %A Marciante, Kristin %A McKnight, Barbara %A Millikan, Robert %A Nock, Nora L %A Olshan, Andrew F %A Press, Michael F %A Vaiyda, Dhananjay %A Woods, Nancy F %A Taylor, Herman A %A Zhao, Wei %A Zheng, Wei %A Evans, Michele K %A Harris, Tamara B %A Henderson, Brian E %A Kardia, Sharon L R %A Kooperberg, Charles %A Liu, Yongmei %A Mosley, Thomas H %A Psaty, Bruce %A Wellons, Melissa %A Windham, Beverly G %A Zonderman, Alan B %A Cupples, L Adrienne %A Demerath, Ellen W %A Haiman, Christopher %A Murabito, Joanne M %A Rajkovic, Aleksandar %K African Americans %K Age Factors %K Chromosomes, Human %K European Continental Ancestry Group %K Female %K Genetic Loci %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Menopause %K United States %X

Age 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.

%B Hum Mol Genet %V 23 %P 3327-42 %8 2014 Jun 15 %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/24493794?dopt=Abstract %R 10.1093/hmg/ddu041 %0 Journal Article %J Hum Mol Genet %D 2014 %T Trans-ethnic meta-analysis of white blood cell phenotypes. %A Keller, Margaux F %A Reiner, Alexander P %A Okada, Yukinori %A van Rooij, Frank J A %A Johnson, Andrew D %A Chen, Ming-Huei %A Smith, Albert V %A Morris, Andrew P %A Tanaka, Toshiko %A Ferrucci, Luigi %A Zonderman, Alan B %A Lettre, Guillaume %A Harris, Tamara %A Garcia, Melissa %A Bandinelli, Stefania %A Qayyum, Rehan %A Yanek, Lisa R %A Becker, Diane M %A Becker, Lewis C %A Kooperberg, Charles %A Keating, Brendan %A Reis, Jared %A Tang, Hua %A Boerwinkle, Eric %A Kamatani, Yoichiro %A Matsuda, Koichi %A Kamatani, Naoyuki %A Nakamura, Yusuke %A Kubo, Michiaki %A Liu, Simin %A Dehghan, Abbas %A Felix, Janine F %A Hofman, Albert %A Uitterlinden, André G %A van Duijn, Cornelia M %A Franco, Oscar H %A Longo, Dan L %A Singleton, Andrew B %A Psaty, Bruce M %A Evans, Michelle K %A Cupples, L Adrienne %A Rotter, Jerome I %A O'Donnell, Christopher J %A Takahashi, Atsushi %A Wilson, James G %A Ganesh, Santhi K %A Nalls, Mike A %K African Americans %K Asian Continental Ancestry Group %K Bayes Theorem %K European Continental Ancestry Group %K Genome, Human %K Genome-Wide Association Study %K Genotype %K Humans %K Leukocyte Count %K Leukocytes %K Linkage Disequilibrium %K Phenotype %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %X

White 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.

%B Hum Mol Genet %V 23 %P 6944-60 %8 2014 Dec 20 %G eng %N 25 %1 http://www.ncbi.nlm.nih.gov/pubmed/25096241?dopt=Abstract %R 10.1093/hmg/ddu401 %0 Journal Article %J Am J Hum Genet %D 2014 %T Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. %A Lange, Leslie A %A Hu, Youna %A Zhang, He %A Xue, Chenyi %A Schmidt, Ellen M %A Tang, Zheng-Zheng %A Bizon, Chris %A Lange, Ethan M %A Smith, Joshua D %A Turner, Emily H %A Jun, Goo %A Kang, Hyun Min %A Peloso, Gina %A Auer, Paul %A Li, Kuo-Ping %A Flannick, Jason %A Zhang, Ji %A Fuchsberger, Christian %A Gaulton, Kyle %A Lindgren, Cecilia %A Locke, Adam %A Manning, Alisa %A Sim, Xueling %A Rivas, Manuel A %A Holmen, Oddgeir L %A Gottesman, Omri %A Lu, Yingchang %A Ruderfer, Douglas %A Stahl, Eli A %A Duan, Qing %A Li, Yun %A Durda, Peter %A Jiao, Shuo %A Isaacs, Aaron %A Hofman, Albert %A Bis, Joshua C %A Correa, Adolfo %A Griswold, Michael E %A Jakobsdottir, Johanna %A Smith, Albert V %A Schreiner, Pamela J %A Feitosa, Mary F %A Zhang, Qunyuan %A Huffman, Jennifer E %A Crosby, Jacy %A Wassel, Christina L %A Do, Ron %A Franceschini, Nora %A Martin, Lisa W %A Robinson, Jennifer G %A Assimes, Themistocles L %A Crosslin, David R %A Rosenthal, Elisabeth A %A Tsai, Michael %A Rieder, Mark J %A Farlow, Deborah N %A Folsom, Aaron R %A Lumley, Thomas %A Fox, Ervin R %A Carlson, Christopher S %A Peters, Ulrike %A Jackson, Rebecca D %A van Duijn, Cornelia M %A Uitterlinden, André G %A Levy, Daniel %A Rotter, Jerome I %A Taylor, Herman A %A Gudnason, Vilmundur %A Siscovick, David S %A Fornage, Myriam %A Borecki, Ingrid B %A Hayward, Caroline %A Rudan, Igor %A Chen, Y Eugene %A Bottinger, Erwin P %A Loos, Ruth J F %A Sætrom, Pål %A Hveem, Kristian %A Boehnke, Michael %A Groop, Leif %A McCarthy, Mark %A Meitinger, Thomas %A Ballantyne, Christie M %A Gabriel, Stacey B %A O'Donnell, Christopher J %A Post, Wendy S %A North, Kari E %A Reiner, Alexander P %A Boerwinkle, Eric %A Psaty, Bruce M %A Altshuler, David %A Kathiresan, Sekar %A Lin, Dan-Yu %A Jarvik, Gail P %A Cupples, L Adrienne %A Kooperberg, Charles %A Wilson, James G %A Nickerson, Deborah A %A Abecasis, Goncalo R %A Rich, Stephen S %A Tracy, Russell P %A Willer, Cristen J %K Adult %K Aged %K Apolipoproteins E %K Cholesterol, LDL %K Cohort Studies %K Dyslipidemias %K Exome %K Female %K Follow-Up Studies %K Gene Frequency %K Genetic Code %K Genome-Wide Association Study %K Genotype %K Humans %K Lipase %K Male %K Middle Aged %K Phenotype %K Polymorphism, Single Nucleotide %K Proprotein Convertase 9 %K Proprotein Convertases %K Receptors, LDL %K Sequence Analysis, DNA %K Serine Endopeptidases %X

Elevated 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.

%B Am J Hum Genet %V 94 %P 233-45 %8 2014 Feb 06 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24507775?dopt=Abstract %R 10.1016/j.ajhg.2014.01.010 %0 Journal Article %J Hum Mol Genet %D 2015 %T Association of exome sequences with plasma C-reactive protein levels in >9000 participants. %A Schick, Ursula M %A Auer, Paul L %A Bis, Joshua C %A Lin, Honghuang %A Wei, Peng %A Pankratz, Nathan %A Lange, Leslie A %A Brody, Jennifer %A Stitziel, Nathan O %A Kim, Daniel S %A Carlson, Christopher S %A Fornage, Myriam %A Haessler, Jeffery %A Hsu, Li %A Jackson, Rebecca D %A Kooperberg, Charles %A Leal, Suzanne M %A Psaty, Bruce M %A Boerwinkle, Eric %A Tracy, Russell %A Ardissino, Diego %A Shah, Svati %A Willer, Cristen %A Loos, Ruth %A Melander, Olle %A McPherson, Ruth %A Hovingh, Kees %A Reilly, Muredach %A Watkins, Hugh %A Girelli, Domenico %A Fontanillas, Pierre %A Chasman, Daniel I %A Gabriel, Stacey B %A Gibbs, Richard %A Nickerson, Deborah A %A Kathiresan, Sekar %A Peters, Ulrike %A Dupuis, Josée %A Wilson, James G %A Rich, Stephen S %A Morrison, Alanna C %A Benjamin, Emelia J %A Gross, Myron D %A Reiner, Alex P %K Adult %K African Americans %K C-Reactive Protein %K Cardiovascular Diseases %K Cohort Studies %K European Continental Ancestry Group %K Exome %K Female %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Hepatocyte Nuclear Factor 1-alpha %K Humans %K Male %K Plasma %K Polymorphism, Single Nucleotide %K Receptors, Interleukin-6 %K Risk Factors %X

C-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.

%B Hum Mol Genet %V 24 %P 559-71 %8 2015 Jan 15 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/25187575?dopt=Abstract %R 10.1093/hmg/ddu450 %0 Journal Article %J Nature %D 2015 %T Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. %A Do, Ron %A Stitziel, Nathan O %A Won, Hong-Hee %A Jørgensen, Anders Berg %A Duga, Stefano %A Angelica Merlini, Pier %A Kiezun, Adam %A Farrall, Martin %A Goel, Anuj %A Zuk, Or %A Guella, Illaria %A Asselta, Rosanna %A Lange, Leslie A %A Peloso, Gina M %A Auer, Paul L %A Girelli, Domenico %A Martinelli, Nicola %A Farlow, Deborah N %A DePristo, Mark A %A Roberts, Robert %A Stewart, Alexander F R %A Saleheen, Danish %A Danesh, John %A Epstein, Stephen E %A Sivapalaratnam, Suthesh %A Hovingh, G Kees %A Kastelein, John J %A Samani, Nilesh J %A Schunkert, Heribert %A Erdmann, Jeanette %A Shah, Svati H %A Kraus, William E %A Davies, Robert %A Nikpay, Majid %A Johansen, Christopher T %A Wang, Jian %A Hegele, Robert A %A Hechter, Eliana %A März, Winfried %A Kleber, Marcus E %A Huang, Jie %A Johnson, Andrew D %A Li, Mingyao %A Burke, Greg L %A Gross, Myron %A Liu, Yongmei %A Assimes, Themistocles L %A Heiss, Gerardo %A Lange, Ethan M %A Folsom, Aaron R %A Taylor, Herman A %A Olivieri, Oliviero %A Hamsten, Anders %A Clarke, Robert %A Reilly, Dermot F %A Yin, Wu %A Rivas, Manuel A %A Donnelly, Peter %A Rossouw, Jacques E %A Psaty, Bruce M %A Herrington, David M %A Wilson, James G %A Rich, Stephen S %A Bamshad, Michael J %A Tracy, Russell P %A Cupples, L Adrienne %A Rader, Daniel J %A Reilly, Muredach P %A Spertus, John A %A Cresci, Sharon %A Hartiala, Jaana %A Tang, W H Wilson %A Hazen, Stanley L %A Allayee, Hooman %A Reiner, Alex P %A Carlson, Christopher S %A Kooperberg, Charles %A Jackson, Rebecca D %A Boerwinkle, Eric %A Lander, Eric S %A Schwartz, Stephen M %A Siscovick, David S %A McPherson, Ruth %A Tybjaerg-Hansen, Anne %A Abecasis, Goncalo R %A Watkins, Hugh %A Nickerson, Deborah A %A Ardissino, Diego %A Sunyaev, Shamil R %A O'Donnell, Christopher J %A Altshuler, David %A Gabriel, Stacey %A Kathiresan, Sekar %K Age Factors %K Age of Onset %K Alleles %K Apolipoproteins A %K Case-Control Studies %K Cholesterol, LDL %K Coronary Artery Disease %K Exome %K Female %K Genetic Predisposition to Disease %K Genetics, Population %K Heterozygote %K Humans %K Male %K Middle Aged %K Mutation %K Myocardial Infarction %K National Heart, Lung, and Blood Institute (U.S.) %K Receptors, LDL %K Triglycerides %K United States %X

Myocardial 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.

%B Nature %V 518 %P 102-6 %8 2015 Feb 5 %G eng %N 7537 %1 http://www.ncbi.nlm.nih.gov/pubmed/25487149?dopt=Abstract %R 10.1038/nature13917 %0 Journal Article %J Stroke %D 2015 %T Meta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans. %A Carty, Cara L %A Keene, Keith L %A Cheng, Yu-Ching %A Meschia, James F %A Chen, Wei-Min %A Nalls, Mike %A Bis, Joshua C %A Kittner, Steven J %A Rich, Stephen S %A Tajuddin, Salman %A Zonderman, Alan B %A Evans, Michele K %A Langefeld, Carl D %A Gottesman, Rebecca %A Mosley, Thomas H %A Shahar, Eyal %A Woo, Daniel %A Yaffe, Kristine %A Liu, Yongmei %A Sale, Michèle M %A Dichgans, Martin %A Malik, Rainer %A Longstreth, W T %A Mitchell, Braxton D %A Psaty, Bruce M %A Kooperberg, Charles %A Reiner, Alexander %A Worrall, Bradford B %A Fornage, Myriam %K African Americans %K Case-Control Studies %K Cohort Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %K Stroke %X

BACKGROUND 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.

%B Stroke %V 46 %P 2063-8 %8 2015 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/26089329?dopt=Abstract %R 10.1161/STROKEAHA.115.009044 %0 Journal Article %J JAMA Neurol %D 2015 %T Rare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project. %A Auer, Paul L %A Nalls, Mike %A Meschia, James F %A Worrall, Bradford B %A Longstreth, W T %A Seshadri, Sudha %A Kooperberg, Charles %A Burger, Kathleen M %A Carlson, Christopher S %A Carty, Cara L %A Chen, Wei-Min %A Cupples, L Adrienne %A DeStefano, Anita L %A Fornage, Myriam %A Hardy, John %A Hsu, Li %A Jackson, Rebecca D %A Jarvik, Gail P %A Kim, Daniel S %A Lakshminarayan, Kamakshi %A Lange, Leslie A %A Manichaikul, Ani %A Quinlan, Aaron R %A Singleton, Andrew B %A Thornton, Timothy A %A Nickerson, Deborah A %A Peters, Ulrike %A Rich, Stephen S %K Aged %K Brain Ischemia %K Exome %K Female %K Genetic Predisposition to Disease %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Muscle Proteins %K National Heart, Lung, and Blood Institute (U.S.) %K Nuclear Proteins %K Open Reading Frames %K Palmitoyl-CoA Hydrolase %K Stroke %K United States %X

IMPORTANCE: 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.

%B JAMA Neurol %V 72 %P 781-8 %8 2015 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/25961151?dopt=Abstract %R 10.1001/jamaneurol.2015.0582 %0 Journal Article %J Blood %D 2015 %T Rare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF. %A Huffman, Jennifer E %A de Vries, Paul S %A Morrison, Alanna C %A Sabater-Lleal, Maria %A Kacprowski, Tim %A Auer, Paul L %A Brody, Jennifer A %A Chasman, Daniel I %A Chen, Ming-Huei %A Guo, Xiuqing %A Lin, Li-An %A Marioni, Riccardo E %A Müller-Nurasyid, Martina %A Yanek, Lisa R %A Pankratz, Nathan %A Grove, Megan L %A de Maat, Moniek P M %A Cushman, Mary %A Wiggins, Kerri L %A Qi, Lihong %A Sennblad, Bengt %A Harris, Sarah E %A Polasek, Ozren %A Riess, Helene %A Rivadeneira, Fernando %A Rose, Lynda M %A Goel, Anuj %A Taylor, Kent D %A Teumer, Alexander %A Uitterlinden, André G %A Vaidya, Dhananjay %A Yao, Jie %A Tang, Weihong %A Levy, Daniel %A Waldenberger, Melanie %A Becker, Diane M %A Folsom, Aaron R %A Giulianini, Franco %A Greinacher, Andreas %A Hofman, Albert %A Huang, Chiang-Ching %A Kooperberg, Charles %A Silveira, Angela %A Starr, John M %A Strauch, Konstantin %A Strawbridge, Rona J %A Wright, Alan F %A McKnight, Barbara %A Franco, Oscar H %A Zakai, Neil %A Mathias, Rasika A %A Psaty, Bruce M %A Ridker, Paul M %A Tofler, Geoffrey H %A Völker, Uwe %A Watkins, Hugh %A Fornage, Myriam %A Hamsten, Anders %A Deary, Ian J %A Boerwinkle, Eric %A Koenig, Wolfgang %A Rotter, Jerome I %A Hayward, Caroline %A Dehghan, Abbas %A Reiner, Alex P %A O'Donnell, Christopher J %A Smith, Nicholas L %K Cohort Studies %K Factor VII %K Factor VIII %K Fibrinogen %K Gene Frequency %K Genetic Association Studies %K Genetic Variation %K Humans %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Potassium Channels %K von Willebrand Factor %X

Fibrinogen, 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.

%B Blood %V 126 %P e19-29 %8 2015 Sep 10 %G eng %N 11 %1 http://www.ncbi.nlm.nih.gov/pubmed/26105150?dopt=Abstract %R 10.1182/blood-2015-02-624551 %0 Journal Article %J Nat Genet %D 2016 %T Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. %A Liu, Chunyu %A Kraja, Aldi T %A Smith, Jennifer A %A Brody, Jennifer A %A Franceschini, Nora %A Bis, Joshua C %A Rice, Kenneth %A Morrison, Alanna C %A Lu, Yingchang %A Weiss, Stefan %A Guo, Xiuqing %A Palmas, Walter %A Martin, Lisa W %A Chen, Yii-Der Ida %A Surendran, Praveen %A Drenos, Fotios %A Cook, James P %A Auer, Paul L %A Chu, Audrey Y %A Giri, Ayush %A Zhao, Wei %A Jakobsdottir, Johanna %A Lin, Li-An %A Stafford, Jeanette M %A Amin, Najaf %A Mei, Hao %A Yao, Jie %A Voorman, Arend %A Larson, Martin G %A Grove, Megan L %A Smith, Albert V %A Hwang, Shih-Jen %A Chen, Han %A Huan, Tianxiao %A Kosova, Gulum %A Stitziel, Nathan O %A Kathiresan, Sekar %A Samani, Nilesh %A Schunkert, Heribert %A Deloukas, Panos %A Li, Man %A Fuchsberger, Christian %A Pattaro, Cristian %A Gorski, Mathias %A Kooperberg, Charles %A Papanicolaou, George J %A Rossouw, Jacques E %A Faul, Jessica D %A Kardia, Sharon L R %A Bouchard, Claude %A Raffel, Leslie J %A Uitterlinden, André G %A Franco, Oscar H %A Vasan, Ramachandran S %A O'Donnell, Christopher J %A Taylor, Kent D %A Liu, Kiang %A Bottinger, Erwin P %A Gottesman, Omri %A Daw, E Warwick %A Giulianini, Franco %A Ganesh, Santhi %A Salfati, Elias %A Harris, Tamara B %A Launer, Lenore J %A Dörr, Marcus %A Felix, Stephan B %A Rettig, Rainer %A Völzke, Henry %A Kim, Eric %A Lee, Wen-Jane %A Lee, I-Te %A Sheu, Wayne H-H %A Tsosie, Krystal S %A Edwards, Digna R Velez %A Liu, Yongmei %A Correa, Adolfo %A Weir, David R %A Völker, Uwe %A Ridker, Paul M %A Boerwinkle, Eric %A Gudnason, Vilmundur %A Reiner, Alexander P %A van Duijn, Cornelia M %A Borecki, Ingrid B %A Edwards, Todd L %A Chakravarti, Aravinda %A Rotter, Jerome I %A Psaty, Bruce M %A Loos, Ruth J F %A Fornage, Myriam %A Ehret, Georg B %A Newton-Cheh, Christopher %A Levy, Daniel %A Chasman, Daniel I %X

Meta-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.

%B Nat Genet %V 48 %P 1162-70 %8 2016 Oct %G eng %N 10 %R 10.1038/ng.3660 %0 Journal Article %J Hum Mol Genet %D 2016 %T A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration. %A de Vries, Paul S %A Chasman, Daniel I %A Sabater-Lleal, Maria %A Chen, Ming-Huei %A Huffman, Jennifer E %A Steri, Maristella %A Tang, Weihong %A Teumer, Alexander %A Marioni, Riccardo E %A Grossmann, Vera %A Hottenga, Jouke J %A Trompet, Stella %A Müller-Nurasyid, Martina %A Zhao, Jing Hua %A Brody, Jennifer A %A Kleber, Marcus E %A Guo, Xiuqing %A Wang, Jie Jin %A Auer, Paul L %A Attia, John R %A Yanek, Lisa R %A Ahluwalia, Tarunveer S %A Lahti, Jari %A Venturini, Cristina %A Tanaka, Toshiko %A Bielak, Lawrence F %A Joshi, Peter K %A Rocanin-Arjo, Ares %A Kolcic, Ivana %A Navarro, Pau %A Rose, Lynda M %A Oldmeadow, Christopher %A Riess, Helene %A Mazur, Johanna %A Basu, Saonli %A Goel, Anuj %A Yang, Qiong %A Ghanbari, Mohsen %A Willemsen, Gonneke %A Rumley, Ann %A Fiorillo, Edoardo %A de Craen, Anton J M %A Grotevendt, Anne %A Scott, Robert %A Taylor, Kent D %A Delgado, Graciela E %A Yao, Jie %A Kifley, Annette %A Kooperberg, Charles %A Qayyum, Rehan %A Lopez, Lorna M %A Berentzen, Tina L %A Räikkönen, Katri %A Mangino, Massimo %A Bandinelli, Stefania %A Peyser, Patricia A %A Wild, Sarah %A Trégouët, David-Alexandre %A Wright, Alan F %A Marten, Jonathan %A Zemunik, Tatijana %A Morrison, Alanna C %A Sennblad, Bengt %A Tofler, Geoffrey %A de Maat, Moniek P M %A de Geus, Eco J C %A Lowe, Gordon D %A Zoledziewska, Magdalena %A Sattar, Naveed %A Binder, Harald %A Völker, Uwe %A Waldenberger, Melanie %A Khaw, Kay-Tee %A McKnight, Barbara %A Huang, Jie %A Jenny, Nancy S %A Holliday, Elizabeth G %A Qi, Lihong %A Mcevoy, Mark G %A Becker, Diane M %A Starr, John M %A Sarin, Antti-Pekka %A Hysi, Pirro G %A Hernandez, Dena G %A Jhun, Min A %A Campbell, Harry %A Hamsten, Anders %A Rivadeneira, Fernando %A McArdle, Wendy L %A Slagboom, P Eline %A Zeller, Tanja %A Koenig, Wolfgang %A Psaty, Bruce M %A Haritunians, Talin %A Liu, Jingmin %A Palotie, Aarno %A Uitterlinden, André G %A Stott, David J %A Hofman, Albert %A Franco, Oscar H %A Polasek, Ozren %A Rudan, Igor %A Morange, Pierre-Emmanuel %A Wilson, James F %A Kardia, Sharon L R %A Ferrucci, Luigi %A Spector, Tim D %A Eriksson, Johan G %A Hansen, Torben %A Deary, Ian J %A Becker, Lewis C %A Scott, Rodney J %A Mitchell, Paul %A März, Winfried %A Wareham, Nick J %A Peters, Annette %A Greinacher, Andreas %A Wild, Philipp S %A Jukema, J Wouter %A Boomsma, Dorret I %A Hayward, Caroline %A Cucca, Francesco %A Tracy, Russell %A Watkins, Hugh %A Reiner, Alex P %A Folsom, Aaron R %A Ridker, Paul M %A O'Donnell, Christopher J %A Smith, Nicholas L %A Strachan, David P %A Dehghan, Abbas %X

Genome-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.

%B Hum Mol Genet %V 25 %P 358-70 %8 2016 Jan 15 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/26561523?dopt=Abstract %R 10.1093/hmg/ddv454 %0 Journal Article %J J Am Soc Nephrol %D 2016 %T SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. %A Li, Man %A Li, Yong %A Weeks, Olivia %A Mijatovic, Vladan %A Teumer, Alexander %A Huffman, Jennifer E %A Tromp, Gerard %A Fuchsberger, Christian %A Gorski, Mathias %A Lyytikäinen, Leo-Pekka %A Nutile, Teresa %A Sedaghat, Sanaz %A Sorice, Rossella %A Tin, Adrienne %A Yang, Qiong %A Ahluwalia, Tarunveer S %A Arking, Dan E %A Bihlmeyer, Nathan A %A Böger, Carsten A %A Carroll, Robert J %A Chasman, Daniel I %A Cornelis, Marilyn C %A Dehghan, Abbas %A Faul, Jessica D %A Feitosa, Mary F %A Gambaro, Giovanni %A Gasparini, Paolo %A Giulianini, Franco %A Heid, Iris %A Huang, Jinyan %A Imboden, Medea %A Jackson, Anne U %A Jeff, Janina %A Jhun, Min A %A Katz, Ronit %A Kifley, Annette %A Kilpeläinen, Tuomas O %A Kumar, Ashish %A Laakso, Markku %A Li-Gao, Ruifang %A Lohman, Kurt %A Lu, Yingchang %A Mägi, Reedik %A Malerba, Giovanni %A Mihailov, Evelin %A Mohlke, Karen L %A Mook-Kanamori, Dennis O %A Robino, Antonietta %A Ruderfer, Douglas %A Salvi, Erika %A Schick, Ursula M %A Schulz, Christina-Alexandra %A Smith, Albert V %A Smith, Jennifer A %A Traglia, Michela %A Yerges-Armstrong, Laura M %A Zhao, Wei %A Goodarzi, Mark O %A Kraja, Aldi T %A Liu, Chunyu %A Wessel, Jennifer %A Boerwinkle, Eric %A Borecki, Ingrid B %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Braga, Daniele %A Brandslund, Ivan %A Brody, Jennifer A %A Campbell, Archie %A Carey, David J %A Christensen, Cramer %A Coresh, Josef %A Crook, Errol %A Curhan, Gary C %A Cusi, Daniele %A de Boer, Ian H %A de Vries, Aiko P J %A Denny, Joshua C %A Devuyst, Olivier %A Dreisbach, Albert W %A Endlich, Karlhans %A Esko, Tõnu %A Franco, Oscar H %A Fulop, Tibor %A Gerhard, Glenn S %A Glümer, Charlotte %A Gottesman, Omri %A Grarup, Niels %A Gudnason, Vilmundur %A Harris, Tamara B %A Hayward, Caroline %A Hocking, Lynne %A Hofman, Albert %A Hu, Frank B %A Husemoen, Lise Lotte N %A Jackson, Rebecca D %A Jørgensen, Torben %A Jørgensen, Marit E %A Kähönen, Mika %A Kardia, Sharon L R %A König, Wolfgang %A Kooperberg, Charles %A Kriebel, Jennifer %A Launer, Lenore J %A Lauritzen, Torsten %A Lehtimäki, Terho %A Levy, Daniel %A Linksted, Pamela %A Linneberg, Allan %A Liu, Yongmei %A Loos, Ruth J F %A Lupo, Antonio %A Meisinger, Christine %A Melander, Olle %A Metspalu, Andres %A Mitchell, Paul %A Nauck, Matthias %A Nürnberg, Peter %A Orho-Melander, Marju %A Parsa, Afshin %A Pedersen, Oluf %A Peters, Annette %A Peters, Ulrike %A Polasek, Ozren %A Porteous, David %A Probst-Hensch, Nicole M %A Psaty, Bruce M %A Qi, Lu %A Raitakari, Olli T %A Reiner, Alex P %A Rettig, Rainer %A Ridker, Paul M %A Rivadeneira, Fernando %A Rossouw, Jacques E %A Schmidt, Frank %A Siscovick, David %A Soranzo, Nicole %A Strauch, Konstantin %A Toniolo, Daniela %A Turner, Stephen T %A Uitterlinden, André G %A Ulivi, Sheila %A Velayutham, Dinesh %A Völker, Uwe %A Völzke, Henry %A Waldenberger, Melanie %A Wang, Jie Jin %A Weir, David R %A Witte, Daniel %A Kuivaniemi, Helena %A Fox, Caroline S %A Franceschini, Nora %A Goessling, Wolfram %A Köttgen, Anna %A Chu, Audrey Y %X

Genome-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.

%B J Am Soc Nephrol %8 2016 Dec 05 %G eng %R 10.1681/ASN.2016020131 %0 Journal Article %J Hum Mol Genet %D 2017 %T Discovery of novel heart rate-associated loci using the Exome Chip. %A van den Berg, Marten E %A Warren, Helen R %A Cabrera, Claudia P %A Verweij, Niek %A Mifsud, Borbala %A Haessler, Jeffrey %A Bihlmeyer, Nathan A %A Fu, Yi-Ping %A Weiss, Stefan %A Lin, Henry J %A Grarup, Niels %A Li-Gao, Ruifang %A Pistis, Giorgio %A Shah, Nabi %A Brody, Jennifer A %A Müller-Nurasyid, Martina %A Lin, Honghuang %A Mei, Hao %A Smith, Albert V %A Lyytikäinen, Leo-Pekka %A Hall, Leanne M %A van Setten, Jessica %A Trompet, Stella %A Prins, Bram P %A Isaacs, Aaron %A Radmanesh, Farid %A Marten, Jonathan %A Entwistle, Aiman %A Kors, Jan A %A Silva, Claudia T %A Alonso, Alvaro %A Bis, Joshua C %A de Boer, Rudolf %A de Haan, Hugoline G %A de Mutsert, Renée %A Dedoussis, George %A Dominiczak, Anna F %A Doney, Alex S F %A Ellinor, Patrick T %A Eppinga, Ruben N %A Felix, Stephan B %A Guo, Xiuqing %A Hagemeijer, Yanick %A Hansen, Torben %A Harris, Tamara B %A Heckbert, Susan R %A Huang, Paul L %A Hwang, Shih-Jen %A Kähönen, Mika %A Kanters, Jørgen K %A Kolcic, Ivana %A Launer, Lenore J %A Li, Man %A Yao, Jie %A Linneberg, Allan %A Liu, Simin %A Macfarlane, Peter W %A Mangino, Massimo %A Morris, Andrew D %A Mulas, Antonella %A Murray, Alison D %A Nelson, Christopher P %A Orrù, Marco %A Padmanabhan, Sandosh %A Peters, Annette %A Porteous, David J %A Poulter, Neil %A Psaty, Bruce M %A Qi, Lihong %A Raitakari, Olli T %A Rivadeneira, Fernando %A Roselli, Carolina %A Rudan, Igor %A Sattar, Naveed %A Sever, Peter %A Sinner, Moritz F %A Soliman, Elsayed Z %A Spector, Timothy D %A Stanton, Alice V %A Stirrups, Kathleen E %A Taylor, Kent D %A Tobin, Martin D %A Uitterlinden, Andre %A Vaartjes, Ilonca %A Hoes, Arno W %A van der Meer, Peter %A Völker, Uwe %A Waldenberger, Melanie %A Xie, Zhijun %A Zoledziewska, Magdalena %A Tinker, Andrew %A Polasek, Ozren %A Rosand, Jonathan %A Jamshidi, Yalda %A van Duijn, Cornelia M %A Zeggini, Eleftheria %A Wouter Jukema, J %A Asselbergs, Folkert W %A Samani, Nilesh J %A Lehtimäki, Terho %A Gudnason, Vilmundur %A Wilson, James %A Lubitz, Steven A %A Kääb, Stefan %A Sotoodehnia, Nona %A Caulfield, Mark J %A Palmer, Colin N A %A Sanna, Serena %A Mook-Kanamori, Dennis O %A Deloukas, Panos %A Pedersen, Oluf %A Rotter, Jerome I %A Dörr, Marcus %A O'Donnell, Chris J %A Hayward, Caroline %A Arking, Dan E %A Kooperberg, Charles %A van der Harst, Pim %A Eijgelsheim, Mark %A Stricker, Bruno H %A Munroe, Patricia B %X

Background 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.

%B Hum Mol Genet %8 2017 Apr 03 %G eng %R 10.1093/hmg/ddx113 %0 Journal Article %J Nat Genet %D 2017 %T Exome-wide association study of plasma lipids in >300,000 individuals. %A Liu, Dajiang J %A Peloso, Gina M %A Yu, Haojie %A Butterworth, Adam S %A Wang, Xiao %A Mahajan, Anubha %A Saleheen, Danish %A Emdin, Connor %A Alam, Dewan %A Alves, Alexessander Couto %A Amouyel, Philippe %A Di Angelantonio, Emanuele %A Arveiler, Dominique %A Assimes, Themistocles L %A Auer, Paul L %A Baber, Usman %A Ballantyne, Christie M %A Bang, Lia E %A Benn, Marianne %A Bis, Joshua C %A Boehnke, Michael %A Boerwinkle, Eric %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brandslund, Ivan %A Brown, Morris %A Busonero, Fabio %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Y Eugene %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Connell, John M %A Cucca, Francesco %A Cupples, L Adrienne %A Damrauer, Scott M %A Davies, Gail %A Deary, Ian J %A Dedoussis, George %A Denny, Joshua C %A Dominiczak, Anna %A Dubé, Marie-Pierre %A Ebeling, Tapani %A Eiriksdottir, Gudny %A Esko, Tõnu %A Farmaki, Aliki-Eleni %A Feitosa, Mary F %A Ferrario, Marco %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Frayling, Timothy M %A Frikke-Schmidt, Ruth %A Fritsche, Lars G %A Frossard, Philippe %A Fuster, Valentin %A Ganesh, Santhi K %A Gao, Wei %A Garcia, Melissa E %A Gieger, Christian %A Giulianini, Franco %A Goodarzi, Mark O %A Grallert, Harald %A Grarup, Niels %A Groop, Leif %A Grove, Megan L %A Gudnason, Vilmundur %A Hansen, Torben %A Harris, Tamara B %A Hayward, Caroline %A Hirschhorn, Joel N %A Holmen, Oddgeir L %A Huffman, Jennifer %A Huo, Yong %A Hveem, Kristian %A Jabeen, Sehrish %A Jackson, Anne U %A Jakobsdottir, Johanna %A Jarvelin, Marjo-Riitta %A Jensen, Gorm B %A Jørgensen, Marit E %A Jukema, J Wouter %A Justesen, Johanne M %A Kamstrup, Pia R %A Kanoni, Stavroula %A Karpe, Fredrik %A Kee, Frank %A Khera, Amit V %A Klarin, Derek %A Koistinen, Heikki A %A Kooner, Jaspal S %A Kooperberg, Charles %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo %A Langenberg, Claudia %A Langsted, Anne %A Launer, Lenore J %A Lauritzen, Torsten %A Liewald, David C M %A Lin, Li An %A Linneberg, Allan %A Loos, Ruth J F %A Lu, Yingchang %A Lu, Xiangfeng %A Mägi, Reedik %A Mälarstig, Anders %A Manichaikul, Ani %A Manning, Alisa K %A Mäntyselkä, Pekka %A Marouli, Eirini %A Masca, Nicholas G D %A Maschio, Andrea %A Meigs, James B %A Melander, Olle %A Metspalu, Andres %A Morris, Andrew P %A Morrison, Alanna C %A Mulas, Antonella %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Neville, Matt J %A Nielsen, Jonas B %A Nielsen, Sune F %A Nordestgaard, Børge G %A Ordovas, Jose M %A Mehran, Roxana %A O'Donnell, Christoper J %A Orho-Melander, Marju %A Molony, Cliona M %A Muntendam, Pieter %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Pasko, Dorota %A Patel, Aniruddh P %A Pedersen, Oluf %A Perola, Markus %A Peters, Annette %A Pisinger, Charlotta %A Pistis, Giorgio %A Polasek, Ozren %A Poulter, Neil %A Psaty, Bruce M %A Rader, Daniel J %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Reiner, Alex P %A Renstrom, Frida %A Rich, Stephen S %A Ridker, Paul M %A Rioux, John D %A Robertson, Neil R %A Roden, Dan M %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sanna, Serena %A Sattar, Naveed %A Schmidt, Ellen M %A Scott, Robert A %A Sever, Peter %A Sevilla, Raquel S %A Shaffer, Christian M %A Sim, Xueling %A Sivapalaratnam, Suthesh %A Small, Kerrin S %A Smith, Albert V %A Smith, Blair H %A Somayajula, Sangeetha %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stirrups, Kathleen E %A Stitziel, Nathan %A Strauch, Konstantin %A Stringham, Heather M %A Surendran, Praveen %A Tada, Hayato %A Tall, Alan R %A Tang, Hua %A Tardif, Jean-Claude %A Taylor, Kent D %A Trompet, Stella %A Tsao, Philip S %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A van Zuydam, Natalie R %A Varbo, Anette %A Varga, Tibor V %A Virtamo, Jarmo %A Waldenberger, Melanie %A Wang, Nan %A Wareham, Nick J %A Warren, Helen R %A Weeke, Peter E %A Weinstock, Joshua %A Wessel, Jennifer %A Wilson, James G %A Wilson, Peter W F %A Xu, Ming %A Yaghootkar, Hanieh %A Young, Robin %A Zeggini, Eleftheria %A Zhang, He %A Zheng, Neil S %A Zhang, Weihua %A Zhang, Yan %A Zhou, Wei %A Zhou, Yanhua %A Zoledziewska, Magdalena %A Howson, Joanna M M %A Danesh, John %A McCarthy, Mark I %A Cowan, Chad A %A Abecasis, Goncalo %A Deloukas, Panos %A Musunuru, Kiran %A Willer, Cristen J %A Kathiresan, Sekar %K Coronary Artery Disease %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genetic Variation %K Genotype %K Humans %K Lipids %K Macular Degeneration %K Phenotype %K Risk Factors %X

We 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.

%B Nat Genet %V 49 %P 1758-1766 %8 2017 Dec %G eng %N 12 %R 10.1038/ng.3977 %0 Journal Article %J Heart Rhythm %D 2017 %T Fine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations. %A Avery, Christy L %A Wassel, Christina L %A Richard, Melissa A %A Highland, Heather M %A Bien, Stephanie %A Zubair, Niha %A Soliman, Elsayed Z %A Fornage, Myriam %A Bielinski, Suzette J %A Tao, Ran %A Seyerle, Amanda A %A Shah, Sanjiv J %A Lloyd-Jones, Donald M %A Buyske, Steven %A Rotter, Jerome I %A Post, Wendy S %A Rich, Stephen S %A Hindorff, Lucia A %A Jeff, Janina M %A Shohet, Ralph V %A Sotoodehnia, Nona %A Lin, Dan Yu %A Whitsel, Eric A %A Peters, Ulrike %A Haiman, Christopher A %A Crawford, Dana C %A Kooperberg, Charles %A North, Kari E %X

BACKGROUND: 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.

%B Heart Rhythm %V 14 %P 572-580 %8 2017 Apr %G eng %N 4 %R 10.1016/j.hrthm.2016.12.021 %0 Journal Article %J Nat Commun %D 2017 %T Genetic loci associated with heart rate variability and their effects on cardiac disease risk. %A Nolte, Ilja M %A Munoz, M Loretto %A Tragante, Vinicius %A Amare, Azmeraw T %A Jansen, Rick %A Vaez, Ahmad %A von der Heyde, Benedikt %A Avery, Christy L %A Bis, Joshua C %A Dierckx, Bram %A van Dongen, Jenny %A Gogarten, Stephanie M %A Goyette, Philippe %A Hernesniemi, Jussi %A Huikari, Ville %A Hwang, Shih-Jen %A Jaju, Deepali %A Kerr, Kathleen F %A Kluttig, Alexander %A Krijthe, Bouwe P %A Kumar, Jitender %A van der Laan, Sander W %A Lyytikäinen, Leo-Pekka %A Maihofer, Adam X %A Minassian, Arpi %A van der Most, Peter J %A Müller-Nurasyid, Martina %A Nivard, Michel %A Salvi, Erika %A Stewart, James D %A Thayer, Julian F %A Verweij, Niek %A Wong, Andrew %A Zabaneh, Delilah %A Zafarmand, Mohammad H %A Abdellaoui, Abdel %A Albarwani, Sulayma %A Albert, Christine %A Alonso, Alvaro %A Ashar, Foram %A Auvinen, Juha %A Axelsson, Tomas %A Baker, Dewleen G %A de Bakker, Paul I W %A Barcella, Matteo %A Bayoumi, Riad %A Bieringa, Rob J %A Boomsma, Dorret %A Boucher, Gabrielle %A Britton, Annie R %A Christophersen, Ingrid %A Dietrich, Andrea %A Ehret, George B %A Ellinor, Patrick T %A Eskola, Markku %A Felix, Janine F %A Floras, John S %A Franco, Oscar H %A Friberg, Peter %A Gademan, Maaike G J %A Geyer, Mark A %A Giedraitis, Vilmantas %A Hartman, Catharina A %A Hemerich, Daiane %A Hofman, Albert %A Hottenga, Jouke-Jan %A Huikuri, Heikki %A Hutri-Kähönen, Nina %A Jouven, Xavier %A Junttila, Juhani %A Juonala, Markus %A Kiviniemi, Antti M %A Kors, Jan A %A Kumari, Meena %A Kuznetsova, Tatiana %A Laurie, Cathy C %A Lefrandt, Joop D %A Li, Yong %A Li, Yun %A Liao, Duanping %A Limacher, Marian C %A Lin, Henry J %A Lindgren, Cecilia M %A Lubitz, Steven A %A Mahajan, Anubha %A McKnight, Barbara %A Zu Schwabedissen, Henriette Meyer %A Milaneschi, Yuri %A Mononen, Nina %A Morris, Andrew P %A Nalls, Mike A %A Navis, Gerjan %A Neijts, Melanie %A Nikus, Kjell %A North, Kari E %A O'Connor, Daniel T %A Ormel, Johan %A Perz, Siegfried %A Peters, Annette %A Psaty, Bruce M %A Raitakari, Olli T %A Risbrough, Victoria B %A Sinner, Moritz F %A Siscovick, David %A Smit, Johannes H %A Smith, Nicholas L %A Soliman, Elsayed Z %A Sotoodehnia, Nona %A Staessen, Jan A %A Stein, Phyllis K %A Stilp, Adrienne M %A Stolarz-Skrzypek, Katarzyna %A Strauch, Konstantin %A Sundström, Johan %A Swenne, Cees A %A Syvänen, Ann-Christine %A Tardif, Jean-Claude %A Taylor, Kent D %A Teumer, Alexander %A Thornton, Timothy A %A Tinker, Lesley E %A Uitterlinden, André G %A van Setten, Jessica %A Voss, Andreas %A Waldenberger, Melanie %A Wilhelmsen, Kirk C %A Willemsen, Gonneke %A Wong, Quenna %A Zhang, Zhu-Ming %A Zonderman, Alan B %A Cusi, Daniele %A Evans, Michele K %A Greiser, Halina K %A van der Harst, Pim %A Hassan, Mohammad %A Ingelsson, Erik %A Jarvelin, Marjo-Riitta %A Kääb, Stefan %A Kähönen, Mika %A Kivimaki, Mika %A Kooperberg, Charles %A Kuh, Diana %A Lehtimäki, Terho %A Lind, Lars %A Nievergelt, Caroline M %A O'Donnell, Chris J %A Oldehinkel, Albertine J %A Penninx, Brenda %A Reiner, Alexander P %A Riese, Harriëtte %A van Roon, Arie M %A Rioux, John D %A Rotter, Jerome I %A Sofer, Tamar %A Stricker, Bruno H %A Tiemeier, Henning %A Vrijkotte, Tanja G M %A Asselbergs, Folkert W %A Brundel, Bianca J J M %A Heckbert, Susan R %A Whitsel, Eric A %A den Hoed, Marcel %A Snieder, Harold %A de Geus, Eco J C %X

Reduced 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 (-0.74 %B Nat Commun %V 8 %P 15805 %8 2017 Jun 14 %G eng %R 10.1038/ncomms15805 %0 Journal Article %J Am J Hum Genet %D 2017 %T Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis. %A van Rooij, Frank J A %A Qayyum, Rehan %A Smith, Albert V %A Zhou, Yi %A Trompet, Stella %A Tanaka, Toshiko %A Keller, Margaux F %A Chang, Li-Ching %A Schmidt, Helena %A Yang, Min-Lee %A Chen, Ming-Huei %A Hayes, James %A Johnson, Andrew D %A Yanek, Lisa R %A Mueller, Christian %A Lange, Leslie %A Floyd, James S %A Ghanbari, Mohsen %A Zonderman, Alan B %A Jukema, J Wouter %A Hofman, Albert %A van Duijn, Cornelia M %A Desch, Karl C %A Saba, Yasaman %A Ozel, Ayse B %A Snively, Beverly M %A Wu, Jer-Yuarn %A Schmidt, Reinhold %A Fornage, Myriam %A Klein, Robert J %A Fox, Caroline S %A Matsuda, Koichi %A Kamatani, Naoyuki %A Wild, Philipp S %A Stott, David J %A Ford, Ian %A Slagboom, P Eline %A Yang, Jaden %A Chu, Audrey Y %A Lambert, Amy J %A Uitterlinden, André G %A Franco, Oscar H %A Hofer, Edith %A Ginsburg, David %A Hu, Bella %A Keating, Brendan %A Schick, Ursula M %A Brody, Jennifer A %A Li, Jun Z %A Chen, Zhao %A Zeller, Tanja %A Guralnik, Jack M %A Chasman, Daniel I %A Peters, Luanne L %A Kubo, Michiaki %A Becker, Diane M %A Li, Jin %A Eiriksdottir, Gudny %A Rotter, Jerome I %A Levy, Daniel %A Grossmann, Vera %A Patel, Kushang V %A Chen, Chien-Hsiun %A Ridker, Paul M %A Tang, Hua %A Launer, Lenore J %A Rice, Kenneth M %A Li-Gao, Ruifang %A Ferrucci, Luigi %A Evans, Michelle K %A Choudhuri, Avik %A Trompouki, Eirini %A Abraham, Brian J %A Yang, Song %A Takahashi, Atsushi %A Kamatani, Yoichiro %A Kooperberg, Charles %A Harris, Tamara B %A Jee, Sun Ha %A Coresh, Josef %A Tsai, Fuu-Jen %A Longo, Dan L %A Chen, Yuan-Tsong %A Felix, Janine F %A Yang, Qiong %A Psaty, Bruce M %A Boerwinkle, Eric %A Becker, Lewis C %A Mook-Kanamori, Dennis O %A Wilson, James G %A Gudnason, Vilmundur %A O'Donnell, Christopher J %A Dehghan, Abbas %A Cupples, L Adrienne %A Nalls, Michael A %A Morris, Andrew P %A Okada, Yukinori %A Reiner, Alexander P %A Zon, Leonard I %A Ganesh, Santhi K %X

Genome-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.

%B Am J Hum Genet %V 100 %P 51-63 %8 2017 Jan 05 %G eng %N 1 %R 10.1016/j.ajhg.2016.11.016 %0 Journal Article %J Nat Genet %D 2017 %T Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation. %A Christophersen, Ingrid E %A Rienstra, Michiel %A Roselli, Carolina %A Yin, Xiaoyan %A Geelhoed, Bastiaan %A Barnard, John %A Lin, Honghuang %A Arking, Dan E %A Smith, Albert V %A Albert, Christine M %A Chaffin, Mark %A Tucker, Nathan R %A Li, Molong %A Klarin, Derek %A Bihlmeyer, Nathan A %A Low, Siew-Kee %A Weeke, Peter E %A Müller-Nurasyid, Martina %A Smith, J Gustav %A Brody, Jennifer A %A Niemeijer, Maartje N %A Dörr, Marcus %A Trompet, Stella %A Huffman, Jennifer %A Gustafsson, Stefan %A Schurmann, Claudia %A Kleber, Marcus E %A Lyytikäinen, Leo-Pekka %A Seppälä, Ilkka %A Malik, Rainer %A Horimoto, Andrea R V R %A Perez, Marco %A Sinisalo, Juha %A Aeschbacher, Stefanie %A Thériault, Sébastien %A Yao, Jie %A Radmanesh, Farid %A Weiss, Stefan %A Teumer, Alexander %A Choi, Seung Hoan %A Weng, Lu-Chen %A Clauss, Sebastian %A Deo, Rajat %A Rader, Daniel J %A Shah, Svati H %A Sun, Albert %A Hopewell, Jemma C %A Debette, Stephanie %A Chauhan, Ganesh %A Yang, Qiong %A Worrall, Bradford B %A Paré, Guillaume %A Kamatani, Yoichiro %A Hagemeijer, Yanick P %A Verweij, Niek %A Siland, Joylene E %A Kubo, Michiaki %A Smith, Jonathan D %A Van Wagoner, David R %A Bis, Joshua C %A Perz, Siegfried %A Psaty, Bruce M %A Ridker, Paul M %A Magnani, Jared W %A Harris, Tamara B %A Launer, Lenore J %A Shoemaker, M Benjamin %A Padmanabhan, Sandosh %A Haessler, Jeffrey %A Bartz, Traci M %A Waldenberger, Melanie %A Lichtner, Peter %A Arendt, Marina %A Krieger, Jose E %A Kähönen, Mika %A Risch, Lorenz %A Mansur, Alfredo J %A Peters, Annette %A Smith, Blair H %A Lind, Lars %A Scott, Stuart A %A Lu, Yingchang %A Bottinger, Erwin B %A Hernesniemi, Jussi %A Lindgren, Cecilia M %A Wong, Jorge A %A Huang, Jie %A Eskola, Markku %A Morris, Andrew P %A Ford, Ian %A Reiner, Alex P %A Delgado, Graciela %A Chen, Lin Y %A Chen, Yii-Der Ida %A Sandhu, Roopinder K %A Li, Man %A Boerwinkle, Eric %A Eisele, Lewin %A Lannfelt, Lars %A Rost, Natalia %A Anderson, Christopher D %A Taylor, Kent D %A Campbell, Archie %A Magnusson, Patrik K %A Porteous, David %A Hocking, Lynne J %A Vlachopoulou, Efthymia %A Pedersen, Nancy L %A Nikus, Kjell %A Orho-Melander, Marju %A Hamsten, Anders %A Heeringa, Jan %A Denny, Joshua C %A Kriebel, Jennifer %A Darbar, Dawood %A Newton-Cheh, Christopher %A Shaffer, Christian %A Macfarlane, Peter W %A Heilmann-Heimbach, Stefanie %A Almgren, Peter %A Huang, Paul L %A Sotoodehnia, Nona %A Soliman, Elsayed Z %A Uitterlinden, André G %A Hofman, Albert %A Franco, Oscar H %A Völker, Uwe %A Jöckel, Karl-Heinz %A Sinner, Moritz F %A Lin, Henry J %A Guo, Xiuqing %A Dichgans, Martin %A Ingelsson, Erik %A Kooperberg, Charles %A Melander, Olle %A Loos, Ruth J F %A Laurikka, Jari %A Conen, David %A Rosand, Jonathan %A van der Harst, Pim %A Lokki, Marja-Liisa %A Kathiresan, Sekar %A Pereira, Alexandre %A Jukema, J Wouter %A Hayward, Caroline %A Rotter, Jerome I %A März, Winfried %A Lehtimäki, Terho %A Stricker, Bruno H %A Chung, Mina K %A Felix, Stephan B %A Gudnason, Vilmundur %A Alonso, Alvaro %A Roden, Dan M %A Kääb, Stefan %A Chasman, Daniel I %A Heckbert, Susan R %A Benjamin, Emelia J %A Tanaka, Toshihiro %A Lunetta, Kathryn L %A Lubitz, Steven A %A Ellinor, Patrick T %X

Atrial 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.

%B Nat Genet %V 49 %P 946-952 %8 2017 Jun %G eng %N 6 %R 10.1038/ng.3843 %0 Journal Article %J Exp Gerontol %D 2017 %T Leisure-time physical activity and leukocyte telomere length among older women. %A Shadyab, Aladdin H %A Lamonte, Michael J %A Kooperberg, Charles %A Reiner, Alexander P %A Carty, Cara L %A Manini, Todd M %A Hou, Lifang %A Di, Chongzhi %A Macera, Caroline A %A Gallo, Linda C %A Shaffer, Richard A %A Jain, Sonia %A LaCroix, Andrea Z %X

BACKGROUND: 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.

%B Exp Gerontol %V 95 %P 141-147 %8 2017 Sep %G eng %R 10.1016/j.exger.2017.05.019 %0 Journal Article %J Circ Cardiovasc Genet %D 2017 %T New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475 000 Individuals. %A Kraja, Aldi T %A Cook, James P %A Warren, Helen R %A Surendran, Praveen %A Liu, Chunyu %A Evangelou, Evangelos %A Manning, Alisa K %A Grarup, Niels %A Drenos, Fotios %A Sim, Xueling %A Smith, Albert Vernon %A Amin, Najaf %A Blakemore, Alexandra I F %A Bork-Jensen, Jette %A Brandslund, Ivan %A Farmaki, Aliki-Eleni %A Fava, Cristiano %A Ferreira, Teresa %A Herzig, Karl-Heinz %A Giri, Ayush %A Giulianini, Franco %A Grove, Megan L %A Guo, Xiuqing %A Harris, Sarah E %A Have, Christian T %A Havulinna, Aki S %A Zhang, He %A Jørgensen, Marit E %A Käräjämäki, AnneMari %A Kooperberg, Charles %A Linneberg, Allan %A Little, Louis %A Liu, Yongmei %A Bonnycastle, Lori L %A Lu, Yingchang %A Mägi, Reedik %A Mahajan, Anubha %A Malerba, Giovanni %A Marioni, Riccardo E %A Mei, Hao %A Menni, Cristina %A Morrison, Alanna C %A Padmanabhan, Sandosh %A Palmas, Walter %A Poveda, Alaitz %A Rauramaa, Rainer %A Rayner, Nigel William %A Riaz, Muhammad %A Rice, Ken %A Richard, Melissa A %A Smith, Jennifer A %A Southam, Lorraine %A Stančáková, Alena %A Stirrups, Kathleen E %A Tragante, Vinicius %A Tuomi, Tiinamaija %A Tzoulaki, Ioanna %A Varga, Tibor V %A Weiss, Stefan %A Yiorkas, Andrianos M %A Young, Robin %A Zhang, Weihua %A Barnes, Michael R %A Cabrera, Claudia P %A Gao, He %A Boehnke, Michael %A Boerwinkle, Eric %A Chambers, John C %A Connell, John M %A Christensen, Cramer K %A de Boer, Rudolf A %A Deary, Ian J %A Dedoussis, George %A Deloukas, Panos %A Dominiczak, Anna F %A Dörr, Marcus %A Joehanes, Roby %A Edwards, Todd L %A Esko, Tõnu %A Fornage, Myriam %A Franceschini, Nora %A Franks, Paul W %A Gambaro, Giovanni %A Groop, Leif %A Hallmans, Göran %A Hansen, Torben %A Hayward, Caroline %A Heikki, Oksa %A Ingelsson, Erik %A Tuomilehto, Jaakko %A Jarvelin, Marjo-Riitta %A Kardia, Sharon L R %A Karpe, Fredrik %A Kooner, Jaspal S %A Lakka, Timo A %A Langenberg, Claudia %A Lind, Lars %A Loos, Ruth J F %A Laakso, Markku %A McCarthy, Mark I %A Melander, Olle %A Mohlke, Karen L %A Morris, Andrew P %A Palmer, Colin N A %A Pedersen, Oluf %A Polasek, Ozren %A Poulter, Neil R %A Province, Michael A %A Psaty, Bruce M %A Ridker, Paul M %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sever, Peter J %A Skaaby, Tea %A Stafford, Jeanette M %A Starr, John M %A van der Harst, Pim %A van der Meer, Peter %A van Duijn, Cornelia M %A Vergnaud, Anne-Claire %A Gudnason, Vilmundur %A Wareham, Nicholas J %A Wilson, James G %A Willer, Cristen J %A Witte, Daniel R %A Zeggini, Eleftheria %A Saleheen, Danish %A Butterworth, Adam S %A Danesh, John %A Asselbergs, Folkert W %A Wain, Louise V %A Ehret, Georg B %A Chasman, Daniel I %A Caulfield, Mark J %A Elliott, Paul %A Lindgren, Cecilia M %A Levy, Daniel %A Newton-Cheh, Christopher %A Munroe, Patricia B %A Howson, Joanna M M %X

BACKGROUND: 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.

%B Circ Cardiovasc Genet %V 10 %8 2017 Oct %G eng %N 5 %R 10.1161/CIRCGENETICS.117.001778 %0 Journal Article %J PLoS Genet %D 2017 %T Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. %A Liang, Jingjing %A Le, Thu H %A Edwards, Digna R Velez %A Tayo, Bamidele O %A Gaulton, Kyle J %A Smith, Jennifer A %A Lu, Yingchang %A Jensen, Richard A %A Chen, Guanjie %A Yanek, Lisa R %A Schwander, Karen %A Tajuddin, Salman M %A Sofer, Tamar %A Kim, Wonji %A Kayima, James %A McKenzie, Colin A %A Fox, Ervin %A Nalls, Michael A %A Young, J Hunter %A Sun, Yan V %A Lane, Jacqueline M %A Cechova, Sylvia %A Zhou, Jie %A Tang, Hua %A Fornage, Myriam %A Musani, Solomon K %A Wang, Heming %A Lee, Juyoung %A Adeyemo, Adebowale %A Dreisbach, Albert W %A Forrester, Terrence %A Chu, Pei-Lun %A Cappola, Anne %A Evans, Michele K %A Morrison, Alanna C %A Martin, Lisa W %A Wiggins, Kerri L %A Hui, Qin %A Zhao, Wei %A Jackson, Rebecca D %A Ware, Erin B %A Faul, Jessica D %A Reiner, Alex P %A Bray, Michael %A Denny, Joshua C %A Mosley, Thomas H %A Palmas, Walter %A Guo, Xiuqing %A Papanicolaou, George J %A Penman, Alan D %A Polak, Joseph F %A Rice, Kenneth %A Taylor, Ken D %A Boerwinkle, Eric %A Bottinger, Erwin P %A Liu, Kiang %A Risch, Neil %A Hunt, Steven C %A Kooperberg, Charles %A Zonderman, Alan B %A Laurie, Cathy C %A Becker, Diane M %A Cai, Jianwen %A Loos, Ruth J F %A Psaty, Bruce M %A Weir, David R %A Kardia, Sharon L R %A Arnett, Donna K %A Won, Sungho %A Edwards, Todd L %A Redline, Susan %A Cooper, Richard S %A Rao, D C %A Rotter, Jerome I %A Rotimi, Charles %A Levy, Daniel %A Chakravarti, Aravinda %A Zhu, Xiaofeng %A Franceschini, Nora %K African Americans %K Animals %K Basic Helix-Loop-Helix Transcription Factors %K Blood Pressure %K Cadherins %K Case-Control Studies %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Hypertension %K Male %K Membrane Proteins %K Mice %K Multifactorial Inheritance %K Polymorphism, Single Nucleotide %X

Hypertension 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.

%B PLoS Genet %V 13 %P e1006728 %8 2017 May %G eng %N 5 %R 10.1371/journal.pgen.1006728 %0 Journal Article %J Hum Genet %D 2017 %T Trans-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. %A Fernandez-Rhodes, Lindsay %A Gong, Jian %A Haessler, Jeffrey %A Franceschini, Nora %A Graff, Mariaelisa %A Nishimura, Katherine K %A Wang, Yujie %A Highland, Heather M %A Yoneyama, Sachiko %A Bush, William S %A Goodloe, Robert %A Ritchie, Marylyn D %A Crawford, Dana %A Gross, Myron %A Fornage, Myriam %A Bůzková, Petra %A Tao, Ran %A Isasi, Carmen %A Avilés-Santa, Larissa %A Daviglus, Martha %A Mackey, Rachel H %A Houston, Denise %A Gu, C Charles %A Ehret, Georg %A Nguyen, Khanh-Dung H %A Lewis, Cora E %A Leppert, Mark %A Irvin, Marguerite R %A Lim, Unhee %A Haiman, Christopher A %A Le Marchand, Loïc %A Schumacher, Fredrick %A Wilkens, Lynne %A Lu, Yingchang %A Bottinger, Erwin P %A Loos, Ruth J L %A Sheu, Wayne H-H %A Guo, Xiuqing %A Lee, Wen-Jane %A Hai, Yang %A Hung, Yi-Jen %A Absher, Devin %A Wu, I-Chien %A Taylor, Kent D %A Lee, I-Te %A Liu, Yeheng %A Wang, Tzung-Dau %A Quertermous, Thomas %A Juang, Jyh-Ming J %A Rotter, Jerome I %A Assimes, Themistocles %A Hsiung, Chao A %A Chen, Yii-Der Ida %A Prentice, Ross %A Kuller, Lewis H %A Manson, JoAnn E %A Kooperberg, Charles %A Smokowski, Paul %A Robinson, Whitney R %A Gordon-Larsen, Penny %A Li, Rongling %A Hindorff, Lucia %A Buyske, Steven %A Matise, Tara C %A Peters, Ulrike %A North, Kari E %K Body Mass Index %K Ethnic Groups %K Genetics, Population %K Humans %K Obesity %X

Most 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.

%B Hum Genet %V 136 %P 771-800 %8 2017 Jun %G eng %N 6 %R 10.1007/s00439-017-1787-6 %0 Journal Article %J Circ Genom Precis Med %D 2018 %T Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval. %A Lin, Honghuang %A van Setten, Jessica %A Smith, Albert V %A Bihlmeyer, Nathan A %A Warren, Helen R %A Brody, Jennifer A %A Radmanesh, Farid %A Hall, Leanne %A Grarup, Niels %A Müller-Nurasyid, Martina %A Boutin, Thibaud %A Verweij, Niek %A Lin, Henry J %A Li-Gao, Ruifang %A van den Berg, Marten E %A Marten, Jonathan %A Weiss, Stefan %A Prins, Bram P %A Haessler, Jeffrey %A Lyytikäinen, Leo-Pekka %A Mei, Hao %A Harris, Tamara B %A Launer, Lenore J %A Li, Man %A Alonso, Alvaro %A Soliman, Elsayed Z %A Connell, John M %A Huang, Paul L %A Weng, Lu-Chen %A Jameson, Heather S %A Hucker, William %A Hanley, Alan %A Tucker, Nathan R %A Chen, Yii-Der Ida %A Bis, Joshua C %A Rice, Kenneth M %A Sitlani, Colleen M %A Kors, Jan A %A Xie, Zhijun %A Wen, Chengping %A Magnani, Jared W %A Nelson, Christopher P %A Kanters, Jørgen K %A Sinner, Moritz F %A Strauch, Konstantin %A Peters, Annette %A Waldenberger, Melanie %A Meitinger, Thomas %A Bork-Jensen, Jette %A Pedersen, Oluf %A Linneberg, Allan %A Rudan, Igor %A de Boer, Rudolf A %A van der Meer, Peter %A Yao, Jie %A Guo, Xiuqing %A Taylor, Kent D %A Sotoodehnia, Nona %A Rotter, Jerome I %A Mook-Kanamori, Dennis O %A Trompet, Stella %A Rivadeneira, Fernando %A Uitterlinden, Andre %A Eijgelsheim, Mark %A Padmanabhan, Sandosh %A Smith, Blair H %A Völzke, Henry %A Felix, Stephan B %A Homuth, Georg %A Völker, Uwe %A Mangino, Massimo %A Spector, Timothy D %A Bots, Michiel L %A Perez, Marco %A Kähönen, Mika %A Raitakari, Olli T %A Gudnason, Vilmundur %A Arking, Dan E %A Munroe, Patricia B %A Psaty, Bruce M %A van Duijn, Cornelia M %A Benjamin, Emelia J %A Rosand, Jonathan %A Samani, Nilesh J %A Hansen, Torben %A Kääb, Stefan %A Polasek, Ozren %A van der Harst, Pim %A Heckbert, Susan R %A Jukema, J Wouter %A Stricker, Bruno H %A Hayward, Caroline %A Dörr, Marcus %A Jamshidi, Yalda %A Asselbergs, Folkert W %A Kooperberg, Charles %A Lehtimäki, Terho %A Wilson, James G %A Ellinor, Patrick T %A Lubitz, Steven A %A Isaacs, Aaron %X

BACKGROUND: 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.

%B Circ Genom Precis Med %V 11 %P e002037 %8 2018 May %G eng %N 5 %R 10.1161/CIRCGEN.117.002037 %0 Journal Article %J Hum Mol Genet %D 2018 %T Discovery, 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. %A Kocarnik, Jonathan M %A Richard, Melissa %A Graff, Misa %A Haessler, Jeffrey %A Bien, Stephanie %A Carlson, Chris %A Carty, Cara L %A Reiner, Alexander P %A Avery, Christy L %A Ballantyne, Christie M %A LaCroix, Andrea Z %A Assimes, Themistocles L %A Barbalic, Maja %A Pankratz, Nathan %A Tang, Weihong %A Tao, Ran %A Chen, Dongquan %A Talavera, Gregory A %A Daviglus, Martha L %A Chirinos-Medina, Diana A %A Pereira, Rocio %A Nishimura, Katie %A Bůzková, Petra %A Best, Lyle G %A Ambite, Jose Luis %A Cheng, Iona %A Crawford, Dana C %A Hindorff, Lucia A %A Fornage, Myriam %A Heiss, Gerardo %A North, Kari E %A Haiman, Christopher A %A Peters, Ulrike %A Le Marchand, Loïc %A Kooperberg, Charles %X

C-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.

%B Hum Mol Genet %V 27 %P 2940-2953 %8 2018 Aug 15 %G eng %N 16 %R 10.1093/hmg/ddy211 %0 Journal Article %J Genome Biol %D 2018 %T Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6. %A Prins, Bram P %A Mead, Timothy J %A Brody, Jennifer A %A Sveinbjornsson, Gardar %A Ntalla, Ioanna %A Bihlmeyer, Nathan A %A van den Berg, Marten %A Bork-Jensen, Jette %A Cappellani, Stefania %A Van Duijvenboden, Stefan %A Klena, Nikolai T %A Gabriel, George C %A Liu, Xiaoqin %A Gulec, Cagri %A Grarup, Niels %A Haessler, Jeffrey %A Hall, Leanne M %A Iorio, Annamaria %A Isaacs, Aaron %A Li-Gao, Ruifang %A Lin, Honghuang %A Liu, Ching-Ti %A Lyytikäinen, Leo-Pekka %A Marten, Jonathan %A Mei, Hao %A Müller-Nurasyid, Martina %A Orini, Michele %A Padmanabhan, Sandosh %A Radmanesh, Farid %A Ramirez, Julia %A Robino, Antonietta %A Schwartz, Molly %A van Setten, Jessica %A Smith, Albert V %A Verweij, Niek %A Warren, Helen R %A Weiss, Stefan %A Alonso, Alvaro %A Arnar, David O %A Bots, Michiel L %A de Boer, Rudolf A %A Dominiczak, Anna F %A Eijgelsheim, Mark %A Ellinor, Patrick T %A Guo, Xiuqing %A Felix, Stephan B %A Harris, Tamara B %A Hayward, Caroline %A Heckbert, Susan R %A Huang, Paul L %A Jukema, J W %A Kähönen, Mika %A Kors, Jan A %A Lambiase, Pier D %A Launer, Lenore J %A Li, Man %A Linneberg, Allan %A Nelson, Christopher P %A Pedersen, Oluf %A Perez, Marco %A Peters, Annette %A Polasek, Ozren %A Psaty, Bruce M %A Raitakari, Olli T %A Rice, Kenneth M %A Rotter, Jerome I %A Sinner, Moritz F %A Soliman, Elsayed Z %A Spector, Tim D %A Strauch, Konstantin %A Thorsteinsdottir, Unnur %A Tinker, Andrew %A Trompet, Stella %A Uitterlinden, Andre %A Vaartjes, Ilonca %A van der Meer, Peter %A Völker, Uwe %A Völzke, Henry %A Waldenberger, Melanie %A Wilson, James G %A Xie, Zhijun %A Asselbergs, Folkert W %A Dörr, Marcus %A van Duijn, Cornelia M %A Gasparini, Paolo %A Gudbjartsson, Daniel F %A Gudnason, Vilmundur %A Hansen, Torben %A Kääb, Stefan %A Kanters, Jørgen K %A Kooperberg, Charles %A Lehtimäki, Terho %A Lin, Henry J %A Lubitz, Steven A %A Mook-Kanamori, Dennis O %A Conti, Francesco J %A Newton-Cheh, Christopher H %A Rosand, Jonathan %A Rudan, Igor %A Samani, Nilesh J %A Sinagra, Gianfranco %A Smith, Blair H %A Holm, Hilma %A Stricker, Bruno H %A Ulivi, Sheila %A Sotoodehnia, Nona %A Apte, Suneel S %A van der Harst, Pim %A Stefansson, Kari %A Munroe, Patricia B %A Arking, Dan E %A Lo, Cecilia W %A Jamshidi, Yalda %X

BACKGROUND: 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.

%B Genome Biol %V 19 %P 87 %8 2018 07 17 %G eng %N 1 %R 10.1186/s13059-018-1457-6 %0 Journal Article %J Circ Genom Precis Med %D 2018 %T ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals. %A Bihlmeyer, Nathan A %A Brody, Jennifer A %A Smith, Albert Vernon %A Warren, Helen R %A Lin, Honghuang %A Isaacs, Aaron %A Liu, Ching-Ti %A Marten, Jonathan %A Radmanesh, Farid %A Hall, Leanne M %A Grarup, Niels %A Mei, Hao %A Müller-Nurasyid, Martina %A Huffman, Jennifer E %A Verweij, Niek %A Guo, Xiuqing %A Yao, Jie %A Li-Gao, Ruifang %A van den Berg, Marten %A Weiss, Stefan %A Prins, Bram P %A van Setten, Jessica %A Haessler, Jeffrey %A Lyytikäinen, Leo-Pekka %A Li, Man %A Alonso, Alvaro %A Soliman, Elsayed Z %A Bis, Joshua C %A Austin, Tom %A Chen, Yii-Der Ida %A Psaty, Bruce M %A Harrris, Tamara B %A Launer, Lenore J %A Padmanabhan, Sandosh %A Dominiczak, Anna %A Huang, Paul L %A Xie, Zhijun %A Ellinor, Patrick T %A Kors, Jan A %A Campbell, Archie %A Murray, Alison D %A Nelson, Christopher P %A Tobin, Martin D %A Bork-Jensen, Jette %A Hansen, Torben %A Pedersen, Oluf %A Linneberg, Allan %A Sinner, Moritz F %A Peters, Annette %A Waldenberger, Melanie %A Meitinger, Thomas %A Perz, Siegfried %A Kolcic, Ivana %A Rudan, Igor %A de Boer, Rudolf A %A van der Meer, Peter %A Lin, Henry J %A Taylor, Kent D %A de Mutsert, Renée %A Trompet, Stella %A Jukema, J Wouter %A Maan, Arie C %A Stricker, Bruno H C %A Rivadeneira, Fernando %A Uitterlinden, Andre %A Völker, Uwe %A Homuth, Georg %A Völzke, Henry %A Felix, Stephan B %A Mangino, Massimo %A Spector, Timothy D %A Bots, Michiel L %A Perez, Marco %A Raitakari, Olli T %A Kähönen, Mika %A Mononen, Nina %A Gudnason, Vilmundur %A Munroe, Patricia B %A Lubitz, Steven A %A van Duijn, Cornelia M %A Newton-Cheh, Christopher H %A Hayward, Caroline %A Rosand, Jonathan %A Samani, Nilesh J %A Kanters, Jørgen K %A Wilson, James G %A Kääb, Stefan %A Polasek, Ozren %A van der Harst, Pim %A Heckbert, Susan R %A Rotter, Jerome I %A Mook-Kanamori, Dennis O %A Eijgelsheim, Mark %A Dörr, Marcus %A Jamshidi, Yalda %A Asselbergs, Folkert W %A Kooperberg, Charles %A Lehtimäki, Terho %A Arking, Dan E %A Sotoodehnia, Nona %X

BACKGROUND: 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.

%B Circ Genom Precis Med %V 11 %P e001758 %8 2018 Jan %G eng %N 1 %R 10.1161/CIRCGEN.117.001758 %0 Journal Article %J Am J Hematol %D 2018 %T Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study. %A Jo Hodonsky, Chani %A Schurmann, Claudia %A Schick, Ursula M %A Kocarnik, Jonathan %A Tao, Ran %A van Rooij, Frank Ja %A Wassel, Christina %A Buyske, Steve %A Fornage, Myriam %A Hindorff, Lucia A %A Floyd, James S %A Ganesh, Santhi K %A Lin, Dan-Yu %A North, Kari E %A Reiner, Alex P %A Loos, Ruth Jf %A Kooperberg, Charles %A Avery, Christy L %X

Red 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.

%B Am J Hematol %8 2018 Jun 15 %G eng %R 10.1002/ajh.25161 %0 Journal Article %J Am J Hum Genet %D 2018 %T Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. %A Ligthart, Symen %A Vaez, Ahmad %A Võsa, Urmo %A Stathopoulou, Maria G %A de Vries, Paul S %A Prins, Bram P %A van der Most, Peter J %A Tanaka, Toshiko %A Naderi, Elnaz %A Rose, Lynda M %A Wu, Ying %A Karlsson, Robert %A Barbalic, Maja %A Lin, Honghuang %A Pool, Rene %A Zhu, Gu %A Mace, Aurelien %A Sidore, Carlo %A Trompet, Stella %A Mangino, Massimo %A Sabater-Lleal, Maria %A Kemp, John P %A Abbasi, Ali %A Kacprowski, Tim %A Verweij, Niek %A Smith, Albert V %A Huang, Tao %A Marzi, Carola %A Feitosa, Mary F %A Lohman, Kurt K %A Kleber, Marcus E %A Milaneschi, Yuri %A Mueller, Christian %A Huq, Mahmudul %A Vlachopoulou, Efthymia %A Lyytikäinen, Leo-Pekka %A Oldmeadow, Christopher %A Deelen, Joris %A Perola, Markus %A Zhao, Jing Hua %A Feenstra, Bjarke %A Amini, Marzyeh %A Lahti, Jari %A Schraut, Katharina E %A Fornage, Myriam %A Suktitipat, Bhoom %A Chen, Wei-Min %A Li, Xiaohui %A Nutile, Teresa %A Malerba, Giovanni %A Luan, Jian'an %A Bak, Tom %A Schork, Nicholas %A del Greco M, Fabiola %A Thiering, Elisabeth %A Mahajan, Anubha %A Marioni, Riccardo E %A Mihailov, Evelin %A Eriksson, Joel %A Ozel, Ayse Bilge %A Zhang, Weihua %A Nethander, Maria %A Cheng, Yu-Ching %A Aslibekyan, Stella %A Ang, Wei %A Gandin, Ilaria %A Yengo, Loic %A Portas, Laura %A Kooperberg, Charles %A Hofer, Edith %A Rajan, Kumar B %A Schurmann, Claudia %A den Hollander, Wouter %A Ahluwalia, Tarunveer S %A Zhao, Jing %A Draisma, Harmen H M %A Ford, Ian %A Timpson, Nicholas %A Teumer, Alexander %A Huang, Hongyan %A Wahl, Simone %A Liu, Yongmei %A Huang, Jie %A Uh, Hae-Won %A Geller, Frank %A Joshi, Peter K %A Yanek, Lisa R %A Trabetti, Elisabetta %A Lehne, Benjamin %A Vozzi, Diego %A Verbanck, Marie %A Biino, Ginevra %A Saba, Yasaman %A Meulenbelt, Ingrid %A O'Connell, Jeff R %A Laakso, Markku %A Giulianini, Franco %A Magnusson, Patrik K E %A Ballantyne, Christie M %A Hottenga, Jouke Jan %A Montgomery, Grant W %A Rivadineira, Fernando %A Rueedi, Rico %A Steri, Maristella %A Herzig, Karl-Heinz %A Stott, David J %A Menni, Cristina %A Frånberg, Mattias %A St Pourcain, Beate %A Felix, Stephan B %A Pers, Tune H %A Bakker, Stephan J L %A Kraft, Peter %A Peters, Annette %A Vaidya, Dhananjay %A Delgado, Graciela %A Smit, Johannes H %A Großmann, Vera %A Sinisalo, Juha %A Seppälä, Ilkka %A Williams, Stephen R %A Holliday, Elizabeth G %A Moed, Matthijs %A Langenberg, Claudia %A Räikkönen, Katri %A Ding, Jingzhong %A Campbell, Harry %A Sale, Michèle M %A Chen, Yii-der I %A James, Alan L %A Ruggiero, Daniela %A Soranzo, Nicole %A Hartman, Catharina A %A Smith, Erin N %A Berenson, Gerald S %A Fuchsberger, Christian %A Hernandez, Dena %A Tiesler, Carla M T %A Giedraitis, Vilmantas %A Liewald, David %A Fischer, Krista %A Mellström, Dan %A Larsson, Anders %A Wang, Yunmei %A Scott, William R %A Lorentzon, Matthias %A Beilby, John %A Ryan, Kathleen A %A Pennell, Craig E %A Vuckovic, Dragana %A Balkau, Beverly %A Concas, Maria Pina %A Schmidt, Reinhold %A Mendes de Leon, Carlos F %A Bottinger, Erwin P %A Kloppenburg, Margreet %A Paternoster, Lavinia %A Boehnke, Michael %A Musk, A W %A Willemsen, Gonneke %A Evans, David M %A Madden, Pamela A F %A Kähönen, Mika %A Kutalik, Zoltán %A Zoledziewska, Magdalena %A Karhunen, Ville %A Kritchevsky, Stephen B %A Sattar, Naveed %A Lachance, Genevieve %A Clarke, Robert %A Harris, Tamara B %A Raitakari, Olli T %A Attia, John R %A van Heemst, Diana %A Kajantie, Eero %A Sorice, Rossella %A Gambaro, Giovanni %A Scott, Robert A %A Hicks, Andrew A %A Ferrucci, Luigi %A Standl, Marie %A Lindgren, Cecilia M %A Starr, John M %A Karlsson, Magnus %A Lind, Lars %A Li, Jun Z %A Chambers, John C %A Mori, Trevor A %A de Geus, Eco J C N %A Heath, Andrew C %A Martin, Nicholas G %A Auvinen, Juha %A Buckley, Brendan M %A de Craen, Anton J M %A Waldenberger, Melanie %A Strauch, Konstantin %A Meitinger, Thomas %A Scott, Rodney J %A McEvoy, Mark %A Beekman, Marian %A Bombieri, Cristina %A Ridker, Paul M %A Mohlke, Karen L %A Pedersen, Nancy L %A Morrison, Alanna C %A Boomsma, Dorret I %A Whitfield, John B %A Strachan, David P %A Hofman, Albert %A Vollenweider, Peter %A Cucca, Francesco %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Spector, Tim D %A Hamsten, Anders %A Zeller, Tanja %A Uitterlinden, André G %A Nauck, Matthias %A Gudnason, Vilmundur %A Qi, Lu %A Grallert, Harald %A Borecki, Ingrid B %A Rotter, Jerome I %A März, Winfried %A Wild, Philipp S %A Lokki, Marja-Liisa %A Boyle, Michael %A Salomaa, Veikko %A Melbye, Mads %A Eriksson, Johan G %A Wilson, James F %A Penninx, Brenda W J H %A Becker, Diane M %A Worrall, Bradford B %A Gibson, Greg %A Krauss, Ronald M %A Ciullo, Marina %A Zaza, Gianluigi %A Wareham, Nicholas J %A Oldehinkel, Albertine J %A Palmer, Lyle J %A Murray, Sarah S %A Pramstaller, Peter P %A Bandinelli, Stefania %A Heinrich, Joachim %A Ingelsson, Erik %A Deary, Ian J %A Mägi, Reedik %A Vandenput, Liesbeth %A van der Harst, Pim %A Desch, Karl C %A Kooner, Jaspal S %A Ohlsson, Claes %A Hayward, Caroline %A Lehtimäki, Terho %A Shuldiner, Alan R %A Arnett, Donna K %A Beilin, Lawrence J %A Robino, Antonietta %A Froguel, Philippe %A Pirastu, Mario %A Jess, Tine %A Koenig, Wolfgang %A Loos, Ruth J F %A Evans, Denis A %A Schmidt, Helena %A Smith, George Davey %A Slagboom, P Eline %A Eiriksdottir, Gudny %A Morris, Andrew P %A Psaty, Bruce M %A Tracy, Russell P %A Nolte, Ilja M %A Boerwinkle, Eric %A Visvikis-Siest, Sophie %A Reiner, Alex P %A Gross, Myron %A Bis, Joshua C %A Franke, Lude %A Franco, Oscar H %A Benjamin, Emelia J %A Chasman, Daniel I %A Dupuis, Josée %A Snieder, Harold %A Dehghan, Abbas %A Alizadeh, Behrooz Z %X

C-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.

%B Am J Hum Genet %V 103 %P 691-706 %8 2018 Nov 01 %G eng %N 5 %R 10.1016/j.ajhg.2018.09.009 %0 Journal Article %J Am J Hum Genet %D 2018 %T A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. %A Sung, Yun J %A Winkler, Thomas W %A de Las Fuentes, Lisa %A Bentley, Amy R %A Brown, Michael R %A Kraja, Aldi T %A Schwander, Karen %A Ntalla, Ioanna %A Guo, Xiuqing %A Franceschini, Nora %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Marten, Jonathan %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Kilpeläinen, Tuomas O %A Richard, Melissa A %A Noordam, Raymond %A Aslibekyan, Stella %A Aschard, Hugues %A Bartz, Traci M %A Dorajoo, Rajkumar %A Liu, Yongmei %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert Vernon %A Tajuddin, Salman M %A Tayo, Bamidele O %A Warren, Helen R %A Zhao, Wei %A Zhou, Yanhua %A Matoba, Nana %A Sofer, Tamar %A Alver, Maris %A Amini, Marzyeh %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Giulianini, Franco %A Goel, Anuj %A Harris, Sarah E %A Hartwig, Fernando Pires %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kähönen, Mika %A Kasturiratne, Anuradhani %A Kuhnel, Brigitte %A Leander, Karin %A Lee, Wen-Jane %A Lin, Keng-Hung %A 'an Luan, Jian %A McKenzie, Colin A %A Meian, He %A Nelson, Christopher P %A Rauramaa, Rainer %A Schupf, Nicole %A Scott, Robert A %A Sheu, Wayne H H %A Stančáková, Alena %A Takeuchi, Fumihiko %A van der Most, Peter J %A Varga, Tibor V %A Wang, Heming %A Wang, Yajuan %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Alfred, Tamuno %A Amin, Najaf %A Arking, Dan %A Aung, Tin %A Barr, R Graham %A Bielak, Lawrence F %A Boerwinkle, Eric %A Bottinger, Erwin P %A Braund, Peter S %A Brody, Jennifer A %A Broeckel, Ulrich %A Cabrera, Claudia P %A Cade, Brian %A Caizheng, Yu %A Campbell, Archie %A Canouil, Mickaël %A Chakravarti, Aravinda %A Chauhan, Ganesh %A Christensen, Kaare %A Cocca, Massimiliano %A Collins, Francis S %A Connell, John M %A de Mutsert, Renée %A de Silva, H Janaka %A Debette, Stephanie %A Dörr, Marcus %A Duan, Qing %A Eaton, Charles B %A Ehret, Georg %A Evangelou, Evangelos %A Faul, Jessica D %A Fisher, Virginia A %A Forouhi, Nita G %A Franco, Oscar H %A Friedlander, Yechiel %A Gao, He %A Gigante, Bruna %A Graff, Misa %A Gu, C Charles %A Gu, Dongfeng %A Gupta, Preeti %A Hagenaars, Saskia P %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hofman, Albert %A Howard, Barbara V %A Hunt, Steven %A Irvin, Marguerite R %A Jia, Yucheng %A Joehanes, Roby %A Justice, Anne E %A Katsuya, Tomohiro %A Kaufman, Joel %A Kerrison, Nicola D %A Khor, Chiea Chuen %A Koh, Woon-Puay %A Koistinen, Heikki A %A Komulainen, Pirjo %A Kooperberg, Charles %A Krieger, Jose E %A Kubo, Michiaki %A Kuusisto, Johanna %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Lim, Sing Hui %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Jingmin %A Liu, Kiang %A Liu, Yeheng %A Loh, Marie %A Lohman, Kurt K %A Long, Jirong %A Louie, Tin %A Mägi, Reedik %A Mahajan, Anubha %A Meitinger, Thomas %A Metspalu, Andres %A Milani, Lili %A Momozawa, Yukihide %A Morris, Andrew P %A Mosley, Thomas H %A Munson, Peter %A Murray, Alison D %A Nalls, Mike A %A Nasri, Ubaydah %A Norris, Jill M %A North, Kari %A Ogunniyi, Adesola %A Padmanabhan, Sandosh %A Palmas, Walter R %A Palmer, Nicholette D %A Pankow, James S %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Raitakari, Olli T %A Renstrom, Frida %A Rice, Treva K %A Ridker, Paul M %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Sabanayagam, Charumathi %A Salako, Babatunde L %A Sandow, Kevin %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Seshadri, Sudha %A Sever, Peter %A Sitlani, Colleen M %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya X %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yuan, Jian-Min %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Chen, Yii-Der Ida %A de Faire, Ulf %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Forrester, Terrence %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo Lessa %A Hung, Yi-Jen %A Jonas, Jost B %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Lehtimäki, Terho %A Liang, Kae-Woei %A Magnusson, Patrik K E %A Newman, Anne B %A Oldehinkel, Albertine J %A Pereira, Alexandre C %A Redline, Susan %A Rettig, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zheng, Wei %A Kamatani, Yoichiro %A Laurie, Cathy C %A Bouchard, Claude %A Cooper, Richard S %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Kritchevsky, Stephen B %A Levy, Daniel %A O'Connell, Jeff R %A Psaty, Bruce M %A van Dam, Rob M %A Sims, Mario %A Arnett, Donna K %A Mook-Kanamori, Dennis O %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A Fornage, Myriam %A Rotimi, Charles N %A Province, Michael A %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Reiner, Alex P %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Caulfield, Mark J %A Elliott, Paul %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Cupples, L Adrienne %A Rao, Dabeeru C %A Chasman, Daniel I %X

Genome-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).

%B Am J Hum Genet %V 102 %P 375-400 %8 2018 Mar 01 %G eng %N 3 %R 10.1016/j.ajhg.2018.01.015 %0 Journal Article %J Nat Genet %D 2018 %T Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. %A Malik, Rainer %A Chauhan, Ganesh %A Traylor, Matthew %A Sargurupremraj, Muralidharan %A Okada, Yukinori %A Mishra, Aniket %A Rutten-Jacobs, Loes %A Giese, Anne-Katrin %A van der Laan, Sander W %A Gretarsdottir, Solveig %A Anderson, Christopher D %A Chong, Michael %A Adams, Hieab H H %A Ago, Tetsuro %A Almgren, Peter %A Amouyel, Philippe %A Ay, Hakan %A Bartz, Traci M %A Benavente, Oscar R %A Bevan, Steve %A Boncoraglio, Giorgio B %A Brown, Robert D %A Butterworth, Adam S %A Carrera, Caty %A Carty, Cara L %A Chasman, Daniel I %A Chen, Wei-Min %A Cole, John W %A Correa, Adolfo %A Cotlarciuc, Ioana %A Cruchaga, Carlos %A Danesh, John %A de Bakker, Paul I W %A DeStefano, Anita L %A den Hoed, Marcel %A Duan, Qing %A Engelter, Stefan T %A Falcone, Guido J %A Gottesman, Rebecca F %A Grewal, Raji P %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeffrey %A Harris, Tamara B %A Hassan, Ahamad %A Havulinna, Aki S %A Heckbert, Susan R %A Holliday, Elizabeth G %A Howard, George %A Hsu, Fang-Chi %A Hyacinth, Hyacinth I %A Ikram, M Arfan %A Ingelsson, Erik %A Irvin, Marguerite R %A Jian, Xueqiu %A Jimenez-Conde, Jordi %A Johnson, Julie A %A Jukema, J Wouter %A Kanai, Masahiro %A Keene, Keith L %A Kissela, Brett M %A Kleindorfer, Dawn O %A Kooperberg, Charles %A Kubo, Michiaki %A Lange, Leslie A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lee, Jin-Moo %A Lemmens, Robin %A Leys, Didier %A Lewis, Cathryn M %A Lin, Wei-Yu %A Lindgren, Arne G %A Lorentzen, Erik %A Magnusson, Patrik K %A Maguire, Jane %A Manichaikul, Ani %A McArdle, Patrick F %A Meschia, James F %A Mitchell, Braxton D %A Mosley, Thomas H %A Nalls, Michael A %A Ninomiya, Toshiharu %A O'Donnell, Martin J %A Psaty, Bruce M %A Pulit, Sara L %A Rannikmae, Kristiina %A Reiner, Alexander P %A Rexrode, Kathryn M %A Rice, Kenneth %A Rich, Stephen S %A Ridker, Paul M %A Rost, Natalia S %A Rothwell, Peter M %A Rotter, Jerome I %A Rundek, Tatjana %A Sacco, Ralph L %A Sakaue, Saori %A Sale, Michèle M %A Salomaa, Veikko %A Sapkota, Bishwa R %A Schmidt, Reinhold %A Schmidt, Carsten O %A Schminke, Ulf %A Sharma, Pankaj %A Slowik, Agnieszka %A Sudlow, Cathie L M %A Tanislav, Christian %A Tatlisumak, Turgut %A Taylor, Kent D %A Thijs, Vincent N S %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tiedt, Steffen %A Trompet, Stella %A Tzourio, Christophe %A van Duijn, Cornelia M %A Walters, Matthew %A Wareham, Nicholas J %A Wassertheil-Smoller, Sylvia %A Wilson, James G %A Wiggins, Kerri L %A Yang, Qiong %A Yusuf, Salim %A Bis, Joshua C %A Pastinen, Tomi %A Ruusalepp, Arno %A Schadt, Eric E %A Koplev, Simon %A Björkegren, Johan L M %A Codoni, Veronica %A Civelek, Mete %A Smith, Nicholas L %A Trégouët, David A %A Christophersen, Ingrid E %A Roselli, Carolina %A Lubitz, Steven A %A Ellinor, Patrick T %A Tai, E Shyong %A Kooner, Jaspal S %A Kato, Norihiro %A He, Jiang %A van der Harst, Pim %A Elliott, Paul %A Chambers, John C %A Takeuchi, Fumihiko %A Johnson, Andrew D %A Sanghera, Dharambir K %A Melander, Olle %A Jern, Christina %A Strbian, Daniel %A Fernandez-Cadenas, Israel %A Longstreth, W T %A Rolfs, Arndt %A Hata, Jun %A Woo, Daniel %A Rosand, Jonathan %A Paré, Guillaume %A Hopewell, Jemma C %A Saleheen, Danish %A Stefansson, Kari %A Worrall, Bradford B %A Kittner, Steven J %A Seshadri, Sudha %A Fornage, Myriam %A Markus, Hugh S %A Howson, Joanna M M %A Kamatani, Yoichiro %A Debette, Stephanie %A Dichgans, Martin %A Malik, Rainer %A Chauhan, Ganesh %A Traylor, Matthew %A Sargurupremraj, Muralidharan %A Okada, Yukinori %A Mishra, Aniket %A Rutten-Jacobs, Loes %A Giese, Anne-Katrin %A van der Laan, Sander W %A Gretarsdottir, Solveig %A Anderson, Christopher D %A Chong, Michael %A Adams, Hieab H H %A Ago, Tetsuro %A Almgren, Peter %A Amouyel, Philippe %A Ay, Hakan %A Bartz, Traci M %A Benavente, Oscar R %A Bevan, Steve %A Boncoraglio, Giorgio B %A Brown, Robert D %A Butterworth, Adam S %A Carrera, Caty %A Carty, Cara L %A Chasman, Daniel I %A Chen, Wei-Min %A Cole, John W %A Correa, Adolfo %A Cotlarciuc, Ioana %A Cruchaga, Carlos %A Danesh, John %A de Bakker, Paul I W %A DeStefano, Anita L %A Hoed, Marcel den %A Duan, Qing %A Engelter, Stefan T %A Falcone, Guido J %A Gottesman, Rebecca F %A Grewal, Raji P %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeffrey %A Harris, Tamara B %A Hassan, Ahamad %A Havulinna, Aki S %A Heckbert, Susan R %A Holliday, Elizabeth G %A Howard, George %A Hsu, Fang-Chi %A Hyacinth, Hyacinth I %A Ikram, M Arfan %A Ingelsson, Erik %A Irvin, Marguerite R %A Jian, Xueqiu %A Jimenez-Conde, Jordi %A Johnson, Julie A %A Jukema, J Wouter %A Kanai, Masahiro %A Keene, Keith L %A Kissela, Brett M %A Kleindorfer, Dawn O %A Kooperberg, Charles %A Kubo, Michiaki %A Lange, Leslie A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lee, Jin-Moo %A Lemmens, Robin %A Leys, Didier %A Lewis, Cathryn M %A Lin, Wei-Yu %A Lindgren, Arne G %A Lorentzen, Erik %A Magnusson, Patrik K %A Maguire, Jane %A Manichaikul, Ani %A McArdle, Patrick F %A Meschia, James F %A Mitchell, Braxton D %A Mosley, Thomas H %A Nalls, Michael A %A Ninomiya, Toshiharu %A O'Donnell, Martin J %A Psaty, Bruce M %A Pulit, Sara L %A Rannikmae, Kristiina %A Reiner, Alexander P %A Rexrode, Kathryn M %A Rice, Kenneth %A Rich, Stephen S %A Ridker, Paul M %A Rost, Natalia S %A Rothwell, Peter M %A Rotter, Jerome I %A Rundek, Tatjana %A Sacco, Ralph L %A Sakaue, Saori %A Sale, Michèle M %A Salomaa, Veikko %A Sapkota, Bishwa R %A Schmidt, Reinhold %A Schmidt, Carsten O %A Schminke, Ulf %A Sharma, Pankaj %A Slowik, Agnieszka %A Sudlow, Cathie L M %A Tanislav, Christian %A Tatlisumak, Turgut %A Taylor, Kent D %A Thijs, Vincent N S %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tiedt, Steffen %A Trompet, Stella %A Tzourio, Christophe %A van Duijn, Cornelia M %A Walters, Matthew %A Wareham, Nicholas J %A Wassertheil-Smoller, Sylvia %A Wilson, James G %A Wiggins, Kerri L %A Yang, Qiong %A Yusuf, Salim %A Amin, Najaf %A Aparicio, Hugo S %A Arnett, Donna K %A Attia, John %A Beiser, Alexa S %A Berr, Claudine %A Buring, Julie E %A Bustamante, Mariana %A Caso, Valeria %A Cheng, Yu-Ching %A Choi, Seung Hoan %A Chowhan, Ayesha %A Cullell, Natalia %A Dartigues, Jean-François %A Delavaran, Hossein %A Delgado, Pilar %A Dörr, Marcus %A Engström, Gunnar %A Ford, Ian %A Gurpreet, Wander S %A Hamsten, Anders %A Heitsch, Laura %A Hozawa, Atsushi %A Ibanez, Laura %A Ilinca, Andreea %A Ingelsson, Martin %A Iwasaki, Motoki %A Jackson, Rebecca D %A Jood, Katarina %A Jousilahti, Pekka %A Kaffashian, Sara %A Kalra, Lalit %A Kamouchi, Masahiro %A Kitazono, Takanari %A Kjartansson, Olafur %A Kloss, Manja %A Koudstaal, Peter J %A Krupinski, Jerzy %A Labovitz, Daniel L %A Laurie, Cathy C %A Levi, Christopher R %A Li, Linxin %A Lind, Lars %A Lindgren, Cecilia M %A Lioutas, Vasileios %A Liu, Yong Mei %A Lopez, Oscar L %A Makoto, Hirata %A Martinez-Majander, Nicolas %A Matsuda, Koichi %A Minegishi, Naoko %A Montaner, Joan %A Morris, Andrew P %A Muiño, Elena %A Müller-Nurasyid, Martina %A Norrving, Bo %A Ogishima, Soichi %A Parati, Eugenio A %A Peddareddygari, Leema Reddy %A Pedersen, Nancy L %A Pera, Joanna %A Perola, Markus %A Pezzini, Alessandro %A Pileggi, Silvana %A Rabionet, Raquel %A Riba-Llena, Iolanda %A Ribasés, Marta %A Romero, Jose R %A Roquer, Jaume %A Rudd, Anthony G %A Sarin, Antti-Pekka %A Sarju, Ralhan %A Sarnowski, Chloe %A Sasaki, Makoto %A Satizabal, Claudia L %A Satoh, Mamoru %A Sattar, Naveed %A Sawada, Norie %A Sibolt, Gerli %A Sigurdsson, Ásgeir %A Smith, Albert %A Sobue, Kenji %A Soriano-Tárraga, Carolina %A Stanne, Tara %A Stine, O Colin %A Stott, David J %A Strauch, Konstantin %A Takai, Takako %A Tanaka, Hideo %A Tanno, Kozo %A Teumer, Alexander %A Tomppo, Liisa %A Torres-Aguila, Nuria P %A Touze, Emmanuel %A Tsugane, Shoichiro %A Uitterlinden, André G %A Valdimarsson, Einar M %A van der Lee, Sven J %A Völzke, Henry %A Wakai, Kenji %A Weir, David %A Williams, Stephen R %A Wolfe, Charles D A %A Wong, Quenna %A Xu, Huichun %A Yamaji, Taiki %A Sanghera, Dharambir K %A Melander, Olle %A Jern, Christina %A Strbian, Daniel %A Fernandez-Cadenas, Israel %A Longstreth, W T %A Rolfs, Arndt %A Hata, Jun %A Woo, Daniel %A Rosand, Jonathan %A Paré, Guillaume %A Hopewell, Jemma C %A Saleheen, Danish %A Stefansson, Kari %A Worrall, Bradford B %A Kittner, Steven J %A Seshadri, Sudha %A Fornage, Myriam %A Markus, Hugh S %A Howson, Joanna M M %A Kamatani, Yoichiro %A Debette, Stephanie %A Dichgans, Martin %X

Stroke 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.

%B Nat Genet %V 50 %P 524-537 %8 2018 Apr %G eng %N 4 %R 10.1038/s41588-018-0058-3 %0 Journal Article %J PLoS One %D 2018 %T Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. %A Feitosa, Mary F %A Kraja, Aldi T %A Chasman, Daniel I %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Marten, Jonathan %A Musani, Solomon K %A Li, Changwei %A Bentley, Amy R %A Brown, Michael R %A Schwander, Karen %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Dorajoo, Rajkumar %A Fisher, Virginia %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Wojczynski, Mary K %A Alver, Maris %A Boissel, Mathilde %A Cai, Qiuyin %A Campbell, Archie %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A He, Meian %A Hsu, Fang-Chi %A Jackson, Anne U %A Kähönen, Mika %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Laguzzi, Federica %A Luan, Jian'an %A Matoba, Nana %A Nolte, Ilja M %A Padmanabhan, Sandosh %A Riaz, Muhammad %A Rueedi, Rico %A Robino, Antonietta %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Vitart, Veronique %A Wang, Yajuan %A Ware, Erin B %A Warren, Helen R %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Boerwinkle, Eric %A Borecki, Ingrid %A Broeckel, Ulrich %A Brown, Morris %A Brumat, Marco %A Burke, Gregory L %A Canouil, Mickaël %A Chakravarti, Aravinda %A Charumathi, Sabanayagam %A Ida Chen, Yii-Der %A Connell, John M %A Correa, Adolfo %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Deng, Xuan %A Ding, Jingzhong %A Duan, Qing %A Eaton, Charles B %A Ehret, Georg %A Eppinga, Ruben N %A Evangelou, Evangelos %A Faul, Jessica D %A Felix, Stephan B %A Forouhi, Nita G %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gigante, Bruna %A Gu, C Charles %A Gu, Dongfeng %A Hagenaars, Saskia P %A Hallmans, Göran %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Howard, Barbara V %A Ikram, M Arfan %A John, Ulrich %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Lin, Shiow %A Liu, Jianjun %A Liu, Jingmin %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Nalls, Mike A %A Nelson, Christopher P %A Sotoodehnia, Nona %A Norris, Jill M %A O'Connell, Jeff R %A Palmer, Nicholette D %A Perls, Thomas %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Roll, Kathryn %A Rose, Lynda M %A Rosendaal, Frits R %A Rotter, Jerome I %A Schmidt, Carsten O %A Schreiner, Pamela J %A Schupf, Nicole %A Scott, William R %A Sever, Peter S %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Sitlani, Colleen M %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Turner, Stephen T %A Uitterlinden, André G %A Vollenweider, Peter %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya Xing %A Wei, Wen Bin %A Williams, Christine %A Yao, Jie %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Jonas, Jost Bruno %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Kutalik, Zoltán %A Laakso, Markku %A Laurie, Cathy C %A Leander, Karin %A Lehtimäki, Terho %A Study, Lifelines Cohort %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Polasek, Ozren %A Porteous, David J %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zheng, Wei %A Bouchard, Claude %A Christensen, Kaare %A Evans, Michele K %A Gudnason, Vilmundur %A Horta, Bernardo L %A Kardia, Sharon L R %A Liu, Yongmei %A Pereira, Alexandre C %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Gauderman, W James %A Zhu, Xiaofeng %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Rotimi, Charles N %A Cupples, L Adrienne %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Kooperberg, Charles %A Palmas, Walter %A Rice, Kenneth %A Morrison, Alanna C %A Elliott, Paul %A Caulfield, Mark J %A Munroe, Patricia B %A Rao, Dabeeru C %A Province, Michael A %A Levy, Daniel %X

Heavy 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.

%B PLoS One %V 13 %P e0198166 %8 2018 %G eng %N 6 %R 10.1371/journal.pone.0198166 %0 Journal Article %J Blood %D 2019 %T Genomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism. %A Lindström, Sara %A Wang, Lu %A Smith, Erin N %A Gordon, William %A van Hylckama Vlieg, Astrid %A de Andrade, Mariza %A Brody, Jennifer A %A Pattee, Jack W %A Haessler, Jeffrey %A Brumpton, Ben M %A Chasman, Daniel I %A Suchon, Pierre %A Chen, Ming-Huei %A Turman, Constance %A Germain, Marine %A Wiggins, Kerri L %A MacDonald, James %A Braekkan, Sigrid K %A Armasu, Sebastian M %A Pankratz, Nathan %A Jackson, Rebecca D %A Nielsen, Jonas B %A Giulianini, Franco %A Puurunen, Marja K %A Ibrahim, Manal %A Heckbert, Susan R %A Damrauer, Scott M %A Natarajan, Pradeep %A Klarin, Derek %A de Vries, Paul S %A Sabater-Lleal, Maria %A Huffman, Jennifer E %A Bammler, Theo K %A Frazer, Kelly A %A McCauley, Bryan M %A Taylor, Kent %A Pankow, James S %A Reiner, Alexander P %A Gabrielsen, Maiken E %A Deleuze, Jean-Francois %A O'Donnell, Chris J %A Kim, Jihye %A McKnight, Barbara %A Kraft, Peter %A Hansen, John-Bjarne %A Rosendaal, Frits R %A Heit, John A %A Psaty, Bruce M %A Tang, Weihong %A Kooperberg, Charles %A Hveem, Kristian %A Ridker, Paul M %A Morange, Pierre-Emmanuel %A Johnson, Andrew D %A Kabrhel, Christopher %A Trégouët, David-Alexandre %A Smith, Nicholas L %X

Venous 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.

%B Blood %V 134 %P 1645-1657 %8 2019 Nov 07 %G eng %N 19 %R 10.1182/blood.2019000435 %0 Journal Article %J Am J Hum Genet %D 2019 %T Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. %A Sarnowski, Chloe %A Leong, Aaron %A Raffield, Laura M %A Wu, Peitao %A de Vries, Paul S %A DiCorpo, Daniel %A Guo, Xiuqing %A Xu, Huichun %A Liu, Yongmei %A Zheng, Xiuwen %A Hu, Yao %A Brody, Jennifer A %A Goodarzi, Mark O %A Hidalgo, Bertha A %A Highland, Heather M %A Jain, Deepti %A Liu, Ching-Ti %A Naik, Rakhi P %A O'Connell, Jeffrey R %A Perry, James A %A Porneala, Bianca C %A Selvin, Elizabeth %A Wessel, Jennifer %A Psaty, Bruce M %A Curran, Joanne E %A Peralta, Juan M %A Blangero, John %A Kooperberg, Charles %A Mathias, Rasika %A Johnson, Andrew D %A Reiner, Alexander P %A Mitchell, Braxton D %A Cupples, L Adrienne %A Vasan, Ramachandran S %A Correa, Adolfo %A Morrison, Alanna C %A Boerwinkle, Eric %A Rotter, Jerome I %A Rich, Stephen S %A Manning, Alisa K %A Dupuis, Josée %A Meigs, James B %X

Hemoglobin 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.

%B Am J Hum Genet %V 105 %P 706-718 %8 2019 Oct 03 %G eng %N 4 %R 10.1016/j.ajhg.2019.08.010 %0 Journal Article %J Genet Epidemiol %D 2019 %T A large-scale exome array analysis of venous thromboembolism. %A Lindström, Sara %A Brody, Jennifer A %A Turman, Constance %A Germain, Marine %A Bartz, Traci M %A Smith, Erin N %A Chen, Ming-Huei %A Puurunen, Marja %A Chasman, Daniel %A Hassler, Jeffrey %A Pankratz, Nathan %A Basu, Saonli %A Guan, Weihua %A Gyorgy, Beata %A Ibrahim, Manal %A Empana, Jean-Philippe %A Olaso, Robert %A Jackson, Rebecca %A Braekkan, Sigrid K %A McKnight, Barbara %A Deleuze, Jean-Francois %A O'Donnell, Cristopher J %A Jouven, Xavier %A Frazer, Kelly A %A Psaty, Bruce M %A Wiggins, Kerri L %A Taylor, Kent %A Reiner, Alexander P %A Heckbert, Susan R %A Kooperberg, Charles %A Ridker, Paul %A Hansen, John-Bjarne %A Tang, Weihong %A Johnson, Andrew D %A Morange, Pierre-Emmanuel %A Trégouët, David A %A Kraft, Peter %A Smith, Nicholas L %A Kabrhel, Christopher %X

Although 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.

%B Genet Epidemiol %8 2019 Jan 19 %G eng %R 10.1002/gepi.22187 %0 Journal Article %J Am J Epidemiol %D 2019 %T Multi-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. %A de Vries, Paul S %A Brown, Michael R %A Bentley, Amy R %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Schwander, Karen %A Kraja, Aldi T %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Deng, Xuan %A Dorajoo, Rajkumar %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Evangelou, Evangelos %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Laguzzi, Federica %A Lee, Joseph H %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Riaz, Muhammad %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Ballantyne, Christie %A Boerwinkle, Eric %A Broeckel, Ulrich %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Connell, John M %A de Faire, Ulf %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Ding, Jingzhong %A Dominiczak, Anna F %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Fisher, Virginia %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Ghanbari, Mohsen %A Giulianini, Franco %A Grabe, Hans J %A Grove, Megan L %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Howard, Barbara V %A Ikram, M Arfan %A Jacobs, David R %A Johnson, Craig %A Jonas, Jost Bruno %A Kammerer, Candace M %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Koistinen, Heikki A %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Steve B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lemaitre, Rozenn N %A Li, Yize %A Liang, Jingjing %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Mosley, Thomas H %A Mukamal, Kenneth J %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A Sotoodehnia, Nona %A O'Connell, Jeff R %A Palmer, Nicholette D %A Pazoki, Raha %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Reiner, Alex P %A Rice, Treva K %A Rich, Stephen S %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Blair H %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tan, Nicholas %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A van Heemst, Diana %A Vuckovic, Dragana %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Yujie %A Wang, Zhe %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yu, Bing %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Penninx, Brenda %A Pereira, Alexandre C %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Zheng, Wei %A Elliott, Paul %A North, Kari E %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Liu, Ching-Ti %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Kardia, Sharon L R %A Zhu, Xiaofeng %A Rotimi, Charles N %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Liu, Jingmin %A Rotter, Jerome I %A Gauderman, W James %A Province, Michael A %A Munroe, Patricia B %A Rice, Kenneth %A Chasman, Daniel I %A Cupples, L Adrienne %A Rao, Dabeeru C %A Morrison, Alanna C %X

An 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.

%B Am J Epidemiol %8 2019 Jan 29 %G eng %R 10.1093/aje/kwz005 %0 Journal Article %J Nat Genet %D 2019 %T Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. %A Bentley, Amy R %A Sung, Yun J %A Brown, Michael R %A Winkler, Thomas W %A Kraja, Aldi T %A Ntalla, Ioanna %A Schwander, Karen %A Chasman, Daniel I %A Lim, Elise %A Deng, Xuan %A Guo, Xiuqing %A Liu, Jingmin %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Baker, Jenna %A Chen, Guanjie %A Aschard, Hugues %A Bartz, Traci M %A Ding, Jingzhong %A Dorajoo, Rajkumar %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Zhao, Wei %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Evangelou, Evangelos %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Hung, Yi-Jen %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Leander, Karin %A Lin, Keng-Hung %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Prins, Bram %A Riaz, Muhammad %A Robino, Antonietta %A Said, M Abdullah %A Schupf, Nicole %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Tzung-Dau %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Xiang, Yong-Bing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Adeyemo, Adebowale %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Arzumanyan, Zorayr %A Aung, Tin %A Ballantyne, Christie %A Barr, R Graham %A Bielak, Lawrence F %A Boerwinkle, Eric %A Bottinger, Erwin P %A Broeckel, Ulrich %A Brown, Morris %A Cade, Brian E %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Christensen, Kaare %A Concas, Maria Pina %A Connell, John M %A de Las Fuentes, Lisa %A de Silva, H Janaka %A de Vries, Paul S %A Doumatey, Ayo %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Floyd, James S %A Forouhi, Nita G %A Forrester, Terrence %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gharib, Sina A %A Gigante, Bruna %A Giulianini, Franco %A Grabe, Hans J %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Ikram, M Arfan %A Jia, Yucheng %A Joehanes, Roby %A Johnson, Craig %A Jonas, Jost Bruno %A Justice, Anne E %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Liang, Jingjing %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Lohman, Kurt K %A Louie, Tin %A Luzzi, Anna %A Mägi, Reedik %A Mahajan, Anubha %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Morris, Andrew P %A Murray, Alison D %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Papanicolau, George J %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raitakari, Olli T %A Reiner, Alex P %A Renstrom, Frida %A Rice, Treva K %A Rich, Stephen S %A Robinson, Jennifer G %A Rose, Lynda M %A Rosendaal, Frits R %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Tiemeier, Henning %A Turner, Stephen T %A Uitterlinden, André G %A van Heemst, Diana %A Waldenberger, Melanie %A Wang, Heming %A Wang, Lan %A Wang, Lihua %A Wei, Wen Bin %A Williams, Christine A %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Young, Kristin %A Yu, Caizheng %A Yuan, Jian-Min %A Zhou, Jie %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Cooper, Richard S %A de Faire, Ulf %A Deary, Ian J %A Elliott, Paul %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Juang, Jyh-Ming Jimmy %A Kamatani, Yoichiro %A Kammerer, Candace M %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Laurie, Cathy C %A Lee, I-Te %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Pereira, Alexandre C %A Rauramaa, Rainer %A Redline, Susan %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Jun-Sing %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zeggini, Eleftheria %A Zheng, Wei %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Province, Michael A %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Franceschini, Nora %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Rao, Dabeeru C %A Rotimi, Charles N %A Cupples, L Adrienne %X

The 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.

%B Nat Genet %V 51 %P 636-648 %8 2019 Apr %G eng %N 4 %R 10.1038/s41588-019-0378-y %0 Journal Article %J Nat Commun %D 2019 %T Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. %A Noordam, Raymond %A Bos, Maxime M %A Wang, Heming %A Winkler, Thomas W %A Bentley, Amy R %A Kilpeläinen, Tuomas O %A de Vries, Paul S %A Sung, Yun Ju %A Schwander, Karen %A Cade, Brian E %A Manning, Alisa %A Aschard, Hugues %A Brown, Michael R %A Chen, Han %A Franceschini, Nora %A Musani, Solomon K %A Richard, Melissa %A Vojinovic, Dina %A Aslibekyan, Stella %A Bartz, Traci M %A de Las Fuentes, Lisa %A Feitosa, Mary %A Horimoto, Andrea R %A Ilkov, Marjan %A Kho, Minjung %A Kraja, Aldi %A Li, Changwei %A Lim, Elise %A Liu, Yongmei %A Mook-Kanamori, Dennis O %A Rankinen, Tuomo %A Tajuddin, Salman M %A van der Spek, Ashley %A Wang, Zhe %A Marten, Jonathan %A Laville, Vincent %A Alver, Maris %A Evangelou, Evangelos %A Graff, Maria E %A He, Meian %A Kuhnel, Brigitte %A Lyytikäinen, Leo-Pekka %A Marques-Vidal, Pedro %A Nolte, Ilja M %A Palmer, Nicholette D %A Rauramaa, Rainer %A Shu, Xiao-Ou %A Snieder, Harold %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Adolfo, Correa %A Ballantyne, Christie %A Bielak, Larry %A Biermasz, Nienke R %A Boerwinkle, Eric %A Dimou, Niki %A Eiriksdottir, Gudny %A Gao, Chuan %A Gharib, Sina A %A Gottlieb, Daniel J %A Haba-Rubio, José %A Harris, Tamara B %A Heikkinen, Sami %A Heinzer, Raphael %A Hixson, James E %A Homuth, Georg %A Ikram, M Arfan %A Komulainen, Pirjo %A Krieger, Jose E %A Lee, Jiwon %A Liu, Jingmin %A Lohman, Kurt K %A Luik, Annemarie I %A Mägi, Reedik %A Martin, Lisa W %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Nalls, Mike A %A O'Connell, Jeff %A Peters, Annette %A Peyser, Patricia %A Raitakari, Olli T %A Reiner, Alex P %A Rensen, Patrick C N %A Rice, Treva K %A Rich, Stephen S %A Roenneberg, Till %A Rotter, Jerome I %A Schreiner, Pamela J %A Shikany, James %A Sidney, Stephen S %A Sims, Mario %A Sitlani, Colleen M %A Sofer, Tamar %A Strauch, Konstantin %A Swertz, Morris A %A Taylor, Kent D %A Uitterlinden, André G %A van Duijn, Cornelia M %A Völzke, Henry %A Waldenberger, Melanie %A Wallance, Robert B %A van Dijk, Ko Willems %A Yu, Caizheng %A Zonderman, Alan B %A Becker, Diane M %A Elliott, Paul %A Esko, Tõnu %A Gieger, Christian %A Grabe, Hans J %A Lakka, Timo A %A Lehtimäki, Terho %A North, Kari E %A Penninx, Brenda W J H %A Vollenweider, Peter %A Wagenknecht, Lynne E %A Wu, Tangchun %A Xiang, Yong-Bing %A Zheng, Wei %A Arnett, Donna K %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon %A Kelly, Tanika N %A Kritchevsky, Stephen B %A Loos, Ruth J F %A Pereira, Alexandre C %A Province, Mike %A Psaty, Bruce M %A Rotimi, Charles %A Zhu, Xiaofeng %A Amin, Najaf %A Cupples, L Adrienne %A Fornage, Myriam %A Fox, Ervin F %A Guo, Xiuqing %A Gauderman, W James %A Rice, Kenneth %A Kooperberg, Charles %A Munroe, Patricia B %A Liu, Ching-Ti %A Morrison, Alanna C %A Rao, Dabeeru C %A van Heemst, Diana %A Redline, Susan %X

Both 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.

%B Nat Commun %V 10 %P 5121 %8 2019 Nov 12 %G eng %N 1 %R 10.1038/s41467-019-12958-0 %0 Journal Article %J JAMA Netw Open %D 2020 %T Association of Leukocyte Telomere Length With Mortality Among Adult Participants in 3 Longitudinal Studies. %A Arbeev, Konstantin G %A Verhulst, Simon %A Steenstrup, Troels %A Kark, Jeremy D %A Bagley, Olivia %A Kooperberg, Charles %A Reiner, Alexander P %A Hwang, Shih-Jen %A Levy, Daniel %A Fitzpatrick, Annette L %A Christensen, Kaare %A Yashin, Anatoliy I %A Aviv, Abraham %X

Importance: 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.

%B JAMA Netw Open %V 3 %P e200023 %8 2020 Feb 05 %G eng %N 2 %R 10.1001/jamanetworkopen.2020.0023 %0 Journal Article %J Nature %D 2020 %T Inherited causes of clonal haematopoiesis in 97,691 whole genomes. %A Bick, Alexander G %A Weinstock, Joshua S %A Nandakumar, Satish K %A Fulco, Charles P %A Bao, Erik L %A Zekavat, Seyedeh M %A Szeto, Mindy D %A Liao, Xiaotian %A Leventhal, Matthew J %A Nasser, Joseph %A Chang, Kyle %A Laurie, Cecelia %A Burugula, Bala Bharathi %A Gibson, Christopher J %A Lin, Amy E %A Taub, Margaret A %A Aguet, Francois %A Ardlie, Kristin %A Mitchell, Braxton D %A Barnes, Kathleen C %A Moscati, Arden %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Silverman, Edwin K %A Weiss, Scott T %A Palmer, Nicholette D %A Vasan, Ramachandran S %A Burchard, Esteban G %A Kardia, Sharon L R %A He, Jiang %A Kaplan, Robert C %A Smith, Nicholas L %A Arnett, Donna K %A Schwartz, David A %A Correa, Adolfo %A de Andrade, Mariza %A Guo, Xiuqing %A Konkle, Barbara A %A Custer, Brian %A Peralta, Juan M %A Gui, Hongsheng %A Meyers, Deborah A %A McGarvey, Stephen T %A Chen, Ida Yii-Der %A Shoemaker, M Benjamin %A Peyser, Patricia A %A Broome, Jai G %A Gogarten, Stephanie M %A Wang, Fei Fei %A Wong, Quenna %A Montasser, May E %A Daya, Michelle %A Kenny, Eimear E %A North, Kari E %A Launer, Lenore J %A Cade, Brian E %A Bis, Joshua C %A Cho, Michael H %A Lasky-Su, Jessica %A Bowden, Donald W %A Cupples, L Adrienne %A Mak, Angel C Y %A Becker, Lewis C %A Smith, Jennifer A %A Kelly, Tanika N %A Aslibekyan, Stella %A Heckbert, Susan R %A Tiwari, Hemant K %A Yang, Ivana V %A Heit, John A %A Lubitz, Steven A %A Johnsen, Jill M %A Curran, Joanne E %A Wenzel, Sally E %A Weeks, Daniel E %A Rao, Dabeeru C %A Darbar, Dawood %A Moon, Jee-Young %A Tracy, Russell P %A Buth, Erin J %A Rafaels, Nicholas %A Loos, Ruth J F %A Durda, Peter %A Liu, Yongmei %A Hou, Lifang %A Lee, Jiwon %A Kachroo, Priyadarshini %A Freedman, Barry I %A Levy, Daniel %A Bielak, Lawrence F %A Hixson, James E %A Floyd, James S %A Whitsel, Eric A %A Ellinor, Patrick T %A Irvin, Marguerite R %A Fingerlin, Tasha E %A Raffield, Laura M %A Armasu, Sebastian M %A Wheeler, Marsha M %A Sabino, Ester C %A Blangero, John %A Williams, L Keoki %A Levy, Bruce D %A Sheu, Wayne Huey-Herng %A Roden, Dan M %A Boerwinkle, Eric %A Manson, JoAnn E %A Mathias, Rasika A %A Desai, Pinkal %A Taylor, Kent D %A Johnson, Andrew D %A Auer, Paul L %A Kooperberg, Charles %A Laurie, Cathy C %A Blackwell, Thomas W %A Smith, Albert V %A Zhao, Hongyu %A Lange, Ethan %A Lange, Leslie %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Scheet, Paul %A Kitzman, Jacob O %A Lander, Eric S %A Engreitz, Jesse M %A Ebert, Benjamin L %A Reiner, Alexander P %A Jaiswal, Siddhartha %A Abecasis, Goncalo %A Sankaran, Vijay G %A Kathiresan, Sekar %A Natarajan, Pradeep %X

Age 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.

%B Nature %V 586 %P 763-768 %8 2020 10 %G eng %N 7831 %R 10.1038/s41586-020-2819-2 %0 Journal Article %J Nat Commun %D 2020 %T Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction. %A Ntalla, Ioanna %A Weng, Lu-Chen %A Cartwright, James H %A Hall, Amelia Weber %A Sveinbjornsson, Gardar %A Tucker, Nathan R %A Choi, Seung Hoan %A Chaffin, Mark D %A Roselli, Carolina %A Barnes, Michael R %A Mifsud, Borbala %A Warren, Helen R %A Hayward, Caroline %A Marten, Jonathan %A Cranley, James J %A Concas, Maria Pina %A Gasparini, Paolo %A Boutin, Thibaud %A Kolcic, Ivana %A Polasek, Ozren %A Rudan, Igor %A Araujo, Nathalia M %A Lima-Costa, Maria Fernanda %A Ribeiro, Antonio Luiz P %A Souza, Renan P %A Tarazona-Santos, Eduardo %A Giedraitis, Vilmantas %A Ingelsson, Erik %A Mahajan, Anubha %A Morris, Andrew P %A del Greco M, Fabiola %A Foco, Luisa %A Gögele, Martin %A Hicks, Andrew A %A Cook, James P %A Lind, Lars %A Lindgren, Cecilia M %A Sundström, Johan %A Nelson, Christopher P %A Riaz, Muhammad B %A Samani, Nilesh J %A Sinagra, Gianfranco %A Ulivi, Sheila %A Kähönen, Mika %A Mishra, Pashupati P %A Mononen, Nina %A Nikus, Kjell %A Caulfield, Mark J %A Dominiczak, Anna %A Padmanabhan, Sandosh %A Montasser, May E %A O'Connell, Jeff R %A Ryan, Kathleen %A Shuldiner, Alan R %A Aeschbacher, Stefanie %A Conen, David %A Risch, Lorenz %A Thériault, Sébastien %A Hutri-Kähönen, Nina %A Lehtimäki, Terho %A Lyytikäinen, Leo-Pekka %A Raitakari, Olli T %A Barnes, Catriona L K %A Campbell, Harry %A Joshi, Peter K %A Wilson, James F %A Isaacs, Aaron %A Kors, Jan A %A van Duijn, Cornelia M %A Huang, Paul L %A Gudnason, Vilmundur %A Harris, Tamara B %A Launer, Lenore J %A Smith, Albert V %A Bottinger, Erwin P %A Loos, Ruth J F %A Nadkarni, Girish N %A Preuss, Michael H %A Correa, Adolfo %A Mei, Hao %A Wilson, James %A Meitinger, Thomas %A Müller-Nurasyid, Martina %A Peters, Annette %A Waldenberger, Melanie %A Mangino, Massimo %A Spector, Timothy D %A Rienstra, Michiel %A van de Vegte, Yordi J %A van der Harst, Pim %A Verweij, Niek %A Kääb, Stefan %A Schramm, Katharina %A Sinner, Moritz F %A Strauch, Konstantin %A Cutler, Michael J %A Fatkin, Diane %A London, Barry %A Olesen, Morten %A Roden, Dan M %A Benjamin Shoemaker, M %A Gustav Smith, J %A Biggs, Mary L %A Bis, Joshua C %A Brody, Jennifer A %A Psaty, Bruce M %A Rice, Kenneth %A Sotoodehnia, Nona %A De Grandi, Alessandro %A Fuchsberger, Christian %A Pattaro, Cristian %A Pramstaller, Peter P %A Ford, Ian %A Wouter Jukema, J %A Macfarlane, Peter W %A Trompet, Stella %A Dörr, Marcus %A Felix, Stephan B %A Völker, Uwe %A Weiss, Stefan %A Havulinna, Aki S %A Jula, Antti %A Sääksjärvi, Katri %A Salomaa, Veikko %A Guo, Xiuqing %A Heckbert, Susan R %A Lin, Henry J %A Rotter, Jerome I %A Taylor, Kent D %A Yao, Jie %A de Mutsert, Renée %A Maan, Arie C %A Mook-Kanamori, Dennis O %A Noordam, Raymond %A Cucca, Francesco %A Ding, Jun %A Lakatta, Edward G %A Qian, Yong %A Tarasov, Kirill V %A Levy, Daniel %A Lin, Honghuang %A Newton-Cheh, Christopher H %A Lunetta, Kathryn L %A Murray, Alison D %A Porteous, David J %A Smith, Blair H %A Stricker, Bruno H %A Uitterlinden, Andre %A van den Berg, Marten E %A Haessler, Jeffrey %A Jackson, Rebecca D %A Kooperberg, Charles %A Peters, Ulrike %A Reiner, Alexander P %A Whitsel, Eric A %A Alonso, Alvaro %A Arking, Dan E %A Boerwinkle, Eric %A Ehret, Georg B %A Soliman, Elsayed Z %A Avery, Christy L %A Gogarten, Stephanie M %A Kerr, Kathleen F %A Laurie, Cathy C %A Seyerle, Amanda A %A Stilp, Adrienne %A Assa, Solmaz %A Abdullah Said, M %A Yldau van der Ende, M %A Lambiase, Pier D %A Orini, Michele %A Ramirez, Julia %A Van Duijvenboden, Stefan %A Arnar, David O %A Gudbjartsson, Daniel F %A Holm, Hilma %A Sulem, Patrick %A Thorleifsson, Gudmar %A Thorolfsdottir, Rosa B %A Thorsteinsdottir, Unnur %A Benjamin, Emelia J %A Tinker, Andrew %A Stefansson, Kari %A Ellinor, Patrick T %A Jamshidi, Yalda %A Lubitz, Steven A %A Munroe, Patricia B %X

The 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.

%B Nat Commun %V 11 %P 2542 %8 2020 May 21 %G eng %N 1 %R 10.1038/s41467-020-15706-x %0 Journal Article %J Circ Genom Precis Med %D 2020 %T Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels. %A Wang, Zhe %A Chen, Han %A Bartz, Traci M %A Bielak, Lawrence F %A Chasman, Daniel I %A Feitosa, Mary F %A Franceschini, Nora %A Guo, Xiuqing %A Lim, Elise %A Noordam, Raymond %A Richard, Melissa A %A Wang, Heming %A Cade, Brian %A Cupples, L Adrienne %A de Vries, Paul S %A Giulanini, Franco %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Reiner, Alex P %A Rich, Stephen S %A Schreiner, Pamela J %A Sidney, Stephen %A Sitlani, Colleen M %A Smith, Jennifer A %A Willems van Dijk, Ko %A Yao, Jie %A Zhao, Wei %A Fornage, Myriam %A Kardia, Sharon L R %A Kooperberg, Charles %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Province, Michael A %A Psaty, Bruce M %A Redline, Susan %A Ridker, Paul M %A Rotter, Jerome I %A Boerwinkle, Eric %A Morrison, Alanna C %X

BACKGROUND: 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.

%B Circ Genom Precis Med %V 13 %P e002772 %8 2020 Aug %G eng %N 4 %R 10.1161/CIRCGEN.119.002772 %0 Journal Article %J HGG Adv %D 2021 %T BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion. %A Sofer, Tamar %A Lee, Jiwon %A Kurniansyah, Nuzulul %A Jain, Deepti %A Laurie, Cecelia A %A Gogarten, Stephanie M %A Conomos, Matthew P %A Heavner, Ben %A Hu, Yao %A Kooperberg, Charles %A Haessler, Jeffrey %A Vasan, Ramachandran S %A Cupples, L Adrienne %A Coombes, Brandon J %A Seyerle, Amanda %A Gharib, Sina A %A Chen, Han %A O'Connell, Jeffrey R %A Zhang, Man %A Gottlieb, Daniel J %A Psaty, Bruce M %A Longstreth, W T %A Rotter, Jerome I %A Taylor, Kent D %A Rich, Stephen S %A Guo, Xiuqing %A Boerwinkle, Eric %A Morrison, Alanna C %A Pankow, James S %A Johnson, Andrew D %A Pankratz, Nathan %A Reiner, Alex P %A Redline, Susan %A Smith, Nicholas L %A Rice, Kenneth M %A Schifano, Elizabeth D %X

Whole-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.

%B HGG Adv %V 2 %8 2021 Jul 08 %G eng %N 3 %R 10.1016/j.xhgg.2021.100040 %0 Journal Article %J Nat Commun %D 2021 %T Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. %A Natarajan, Pradeep %A Pampana, Akhil %A Graham, Sarah E %A Ruotsalainen, Sanni E %A Perry, James A %A de Vries, Paul S %A Broome, Jai G %A Pirruccello, James P %A Honigberg, Michael C %A Aragam, Krishna %A Wolford, Brooke %A Brody, Jennifer A %A Antonacci-Fulton, Lucinda %A Arden, Moscati %A Aslibekyan, Stella %A Assimes, Themistocles L %A Ballantyne, Christie M %A Bielak, Lawrence F %A Bis, Joshua C %A Cade, Brian E %A Do, Ron %A Doddapaneni, Harsha %A Emery, Leslie S %A Hung, Yi-Jen %A Irvin, Marguerite R %A Khan, Alyna T %A Lange, Leslie %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Metcalf, Ginger %A Montasser, May E %A Moon, Jee-Young %A Muzny, Donna %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peralta, Juan M %A Peyser, Patricia A %A Stilp, Adrienne M %A Tsai, Michael %A Wang, Fei Fei %A Weeks, Daniel E %A Yanek, Lisa R %A Wilson, James G %A Abecasis, Goncalo %A Arnett, Donna K %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Chang, Yi-Cheng %A Chen, Yii-der I %A Choi, Won Jung %A Correa, Adolfo %A Curran, Joanne E %A Daly, Mark J %A Dutcher, Susan K %A Ellinor, Patrick T %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard A %A He, Jiang %A Hveem, Kristian %A Jarvik, Gail P %A Kaplan, Robert C %A Kardia, Sharon L R %A Kenny, Eimear %A Kim, Ryan W %A Kooperberg, Charles %A Laurie, Cathy C %A Lee, Seonwook %A Lloyd-Jones, Don M %A Loos, Ruth J F %A Lubitz, Steven A %A Mathias, Rasika A %A Martinez, Karine A Viaud %A McGarvey, Stephen T %A Mitchell, Braxton D %A Nickerson, Deborah A %A North, Kari E %A Palotie, Aarno %A Park, Cheol Joo %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Seo, Daekwan %A Seo, Jeong-Sun %A Smith, Albert V %A Tracy, Russell P %A Vasan, Ramachandran S %A Kathiresan, Sekar %A Cupples, L Adrienne %A Rotter, Jerome I %A Morrison, Alanna C %A Rich, Stephen S %A Ripatti, Samuli %A Willer, Cristen %A Peloso, Gina M %X

Autosomal 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.

%B Nat Commun %V 12 %P 2182 %8 2021 04 12 %G eng %N 1 %R 10.1038/s41467-021-22339-1 %0 Journal Article %J Am J Hum Genet %D 2021 %T Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. %A Graff, Mariaelisa %A Justice, Anne E %A Young, Kristin L %A Marouli, Eirini %A Zhang, Xinruo %A Fine, Rebecca S %A Lim, Elise %A Buchanan, Victoria %A Rand, Kristin %A Feitosa, Mary F %A Wojczynski, Mary K %A Yanek, Lisa R %A Shao, Yaming %A Rohde, Rebecca %A Adeyemo, Adebowale A %A Aldrich, Melinda C %A Allison, Matthew A %A Ambrosone, Christine B %A Ambs, Stefan %A Amos, Christopher %A Arnett, Donna K %A Atwood, Larry %A Bandera, Elisa V %A Bartz, Traci %A Becker, Diane M %A Berndt, Sonja I %A Bernstein, Leslie %A Bielak, Lawrence F %A Blot, William J %A Bottinger, Erwin P %A Bowden, Donald W %A Bradfield, Jonathan P %A Brody, Jennifer A %A Broeckel, Ulrich %A Burke, Gregory %A Cade, Brian E %A Cai, Qiuyin %A Caporaso, Neil %A Carlson, Chris %A Carpten, John %A Casey, Graham %A Chanock, Stephen J %A Chen, Guanjie %A Chen, Minhui %A Chen, Yii-der I %A Chen, Wei-Min %A Chesi, Alessandra %A Chiang, Charleston W K %A Chu, Lisa %A Coetzee, Gerry A %A Conti, David V %A Cooper, Richard S %A Cushman, Mary %A Demerath, Ellen %A Deming, Sandra L %A Dimitrov, Latchezar %A Ding, Jingzhong %A Diver, W Ryan %A Duan, Qing %A Evans, Michele K %A Falusi, Adeyinka G %A Faul, Jessica D %A Fornage, Myriam %A Fox, Caroline %A Freedman, Barry I %A Garcia, Melissa %A Gillanders, Elizabeth M %A Goodman, Phyllis %A Gottesman, Omri %A Grant, Struan F A %A Guo, Xiuqing %A Hakonarson, Hakon %A Haritunians, Talin %A Harris, Tamara B %A Harris, Curtis C %A Henderson, Brian E %A Hennis, Anselm %A Hernandez, Dena G %A Hirschhorn, Joel N %A McNeill, Lorna Haughton %A Howard, Timothy D %A Howard, Barbara %A Hsing, Ann W %A Hsu, Yu-Han H %A Hu, Jennifer J %A Huff, Chad D %A Huo, Dezheng %A Ingles, Sue A %A Irvin, Marguerite R %A John, Esther M %A Johnson, Karen C %A Jordan, Joanne M %A Kabagambe, Edmond K %A Kang, Sun J %A Kardia, Sharon L %A Keating, Brendan J %A Kittles, Rick A %A Klein, Eric A %A Kolb, Suzanne %A Kolonel, Laurence N %A Kooperberg, Charles %A Kuller, Lewis %A Kutlar, Abdullah %A Lange, Leslie %A Langefeld, Carl D %A Le Marchand, Loïc %A Leonard, Hampton %A Lettre, Guillaume %A Levin, Albert M %A Li, Yun %A Li, Jin %A Liu, Yongmei %A Liu, Youfang %A Liu, Simin %A Lohman, Kurt %A Lotay, Vaneet %A Lu, Yingchang %A Maixner, William %A Manson, JoAnn E %A McKnight, Barbara %A Meng, Yan %A Monda, Keri L %A Monroe, Kris %A Moore, Jason H %A Mosley, Thomas H %A Mudgal, Poorva %A Murphy, Adam B %A Nadukuru, Rajiv %A Nalls, Mike A %A Nathanson, Katherine L %A Nayak, Uma %A N'diaye, Amidou %A Nemesure, Barbara %A Neslund-Dudas, Christine %A Neuhouser, Marian L %A Nyante, Sarah %A Ochs-Balcom, Heather %A Ogundiran, Temidayo O %A Ogunniyi, Adesola %A Ojengbede, Oladosu %A Okut, Hayrettin %A Olopade, Olufunmilayo I %A Olshan, Andrew %A Padhukasahasram, Badri %A Palmer, Julie %A Palmer, Cameron D %A Palmer, Nicholette D %A Papanicolaou, George %A Patel, Sanjay R %A Pettaway, Curtis A %A Peyser, Patricia A %A Press, Michael F %A Rao, D C %A Rasmussen-Torvik, Laura J %A Redline, Susan %A Reiner, Alex P %A Rhie, Suhn K %A Rodriguez-Gil, Jorge L %A Rotimi, Charles N %A Rotter, Jerome I %A Ruiz-Narvaez, Edward A %A Rybicki, Benjamin A %A Salako, Babatunde %A Sale, Michèle M %A Sanderson, Maureen %A Schadt, Eric %A Schreiner, Pamela J %A Schurmann, Claudia %A Schwartz, Ann G %A Shriner, Daniel A %A Signorello, Lisa B %A Singleton, Andrew B %A Siscovick, David S %A Smith, Jennifer A %A Smith, Shad %A Speliotes, Elizabeth %A Spitz, Margaret %A Stanford, Janet L %A Stevens, Victoria L %A Stram, Alex %A Strom, Sara S %A Sucheston, Lara %A Sun, Yan V %A Tajuddin, Salman M %A Taylor, Herman %A Taylor, Kira %A Tayo, Bamidele O %A Thun, Michael J %A Tucker, Margaret A %A Vaidya, Dhananjay %A Van Den Berg, David J %A Vedantam, Sailaja %A Vitolins, Mara %A Wang, Zhaoming %A Ware, Erin B %A Wassertheil-Smoller, Sylvia %A Weir, David R %A Wiencke, John K %A Williams, Scott M %A Williams, L Keoki %A Wilson, James G %A Witte, John S %A Wrensch, Margaret %A Wu, Xifeng %A Yao, Jie %A Zakai, Neil %A Zanetti, Krista %A Zemel, Babette S %A Zhao, Wei %A Zhao, Jing Hua %A Zheng, Wei %A Zhi, Degui %A Zhou, Jie %A Zhu, Xiaofeng %A Ziegler, Regina G %A Zmuda, Joe %A Zonderman, Alan B %A Psaty, Bruce M %A Borecki, Ingrid B %A Cupples, L Adrienne %A Liu, Ching-Ti %A Haiman, Christopher A %A Loos, Ruth %A Ng, Maggie C Y %A North, Kari E %X

Although 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.

%B Am J Hum Genet %V 108 %P 564-582 %8 2021 Apr 01 %G eng %N 4 %R 10.1016/j.ajhg.2021.02.011 %0 Journal Article %J Nature %D 2021 %T Genetic insights into biological mechanisms governing human ovarian ageing. %A Ruth, Katherine S %A Day, Felix R %A Hussain, Jazib %A Martínez-Marchal, Ana %A Aiken, Catherine E %A Azad, Ajuna %A Thompson, Deborah J %A Knoblochova, Lucie %A Abe, Hironori %A Tarry-Adkins, Jane L %A Gonzalez, Javier Martin %A Fontanillas, Pierre %A Claringbould, Annique %A Bakker, Olivier B %A Sulem, Patrick %A Walters, Robin G %A Terao, Chikashi %A Turon, Sandra %A Horikoshi, Momoko %A Lin, Kuang %A Onland-Moret, N Charlotte %A Sankar, Aditya %A Hertz, Emil Peter Thrane %A Timshel, Pascal N %A Shukla, Vallari %A Borup, Rehannah %A Olsen, Kristina W %A Aguilera, Paula %A Ferrer-Roda, Mònica %A Huang, Yan %A Stankovic, Stasa %A Timmers, Paul R H J %A Ahearn, Thomas U %A Alizadeh, Behrooz Z %A Naderi, Elnaz %A Andrulis, Irene L %A Arnold, Alice M %A Aronson, Kristan J %A Augustinsson, Annelie %A Bandinelli, Stefania %A Barbieri, Caterina M %A Beaumont, Robin N %A Becher, Heiko %A Beckmann, Matthias W %A Benonisdottir, Stefania %A Bergmann, Sven %A Bochud, Murielle %A Boerwinkle, Eric %A Bojesen, Stig E %A Bolla, Manjeet K %A Boomsma, Dorret I %A Bowker, Nicholas %A Brody, Jennifer A %A Broer, Linda %A Buring, Julie E %A Campbell, Archie %A Campbell, Harry %A Castelao, Jose E %A Catamo, Eulalia %A Chanock, Stephen J %A Chenevix-Trench, Georgia %A Ciullo, Marina %A Corre, Tanguy %A Couch, Fergus J %A Cox, Angela %A Crisponi, Laura %A Cross, Simon S %A Cucca, Francesco %A Czene, Kamila %A Smith, George Davey %A de Geus, Eco J C N %A de Mutsert, Renée %A De Vivo, Immaculata %A Demerath, Ellen W %A Dennis, Joe %A Dunning, Alison M %A Dwek, Miriam %A Eriksson, Mikael %A Esko, Tõnu %A Fasching, Peter A %A Faul, Jessica D %A Ferrucci, Luigi %A Franceschini, Nora %A Frayling, Timothy M %A Gago-Dominguez, Manuela %A Mezzavilla, Massimo %A García-Closas, Montserrat %A Gieger, Christian %A Giles, Graham G %A Grallert, Harald %A Gudbjartsson, Daniel F %A Gudnason, Vilmundur %A Guénel, Pascal %A Haiman, Christopher A %A Håkansson, Niclas %A Hall, Per %A Hayward, Caroline %A He, Chunyan %A He, Wei %A Heiss, Gerardo %A Høffding, Miya K %A Hopper, John L %A Hottenga, Jouke J %A Hu, Frank %A Hunter, David %A Ikram, Mohammad A %A Jackson, Rebecca D %A Joaquim, Micaella D R %A John, Esther M %A Joshi, Peter K %A Karasik, David %A Kardia, Sharon L R %A Kartsonaki, Christiana %A Karlsson, Robert %A Kitahara, Cari M %A Kolcic, Ivana %A Kooperberg, Charles %A Kraft, Peter %A Kurian, Allison W %A Kutalik, Zoltán %A La Bianca, Martina %A Lachance, Genevieve %A Langenberg, Claudia %A Launer, Lenore J %A Laven, Joop S E %A Lawlor, Deborah A %A Le Marchand, Loïc %A Li, Jingmei %A Lindblom, Annika %A Lindström, Sara %A Lindstrom, Tricia %A Linet, Martha %A Liu, Yongmei %A Liu, Simin %A Luan, Jian'an %A Mägi, Reedik %A Magnusson, Patrik K E %A Mangino, Massimo %A Mannermaa, Arto %A Marco, Brumat %A Marten, Jonathan %A Martin, Nicholas G %A Mbarek, Hamdi %A McKnight, Barbara %A Medland, Sarah E %A Meisinger, Christa %A Meitinger, Thomas %A Menni, Cristina %A Metspalu, Andres %A Milani, Lili %A Milne, Roger L %A Montgomery, Grant W %A Mook-Kanamori, Dennis O %A Mulas, Antonella %A Mulligan, Anna M %A Murray, Alison %A Nalls, Mike A %A Newman, Anne %A Noordam, Raymond %A Nutile, Teresa %A Nyholt, Dale R %A Olshan, Andrew F %A Olsson, Håkan %A Painter, Jodie N %A Patel, Alpa V %A Pedersen, Nancy L %A Perjakova, Natalia %A Peters, Annette %A Peters, Ulrike %A Pharoah, Paul D P %A Polasek, Ozren %A Porcu, Eleonora %A Psaty, Bruce M %A Rahman, Iffat %A Rennert, Gad %A Rennert, Hedy S %A Ridker, Paul M %A Ring, Susan M %A Robino, Antonietta %A Rose, Lynda M %A Rosendaal, Frits R %A Rossouw, Jacques %A Rudan, Igor %A Rueedi, Rico %A Ruggiero, Daniela %A Sala, Cinzia F %A Saloustros, Emmanouil %A Sandler, Dale P %A Sanna, Serena %A Sawyer, Elinor J %A Sarnowski, Chloe %A Schlessinger, David %A Schmidt, Marjanka K %A Schoemaker, Minouk J %A Schraut, Katharina E %A Scott, Christopher %A Shekari, Saleh %A Shrikhande, Amruta %A Smith, Albert V %A Smith, Blair H %A Smith, Jennifer A %A Sorice, Rossella %A Southey, Melissa C %A Spector, Tim D %A Spinelli, John J %A Stampfer, Meir %A Stöckl, Doris %A van Meurs, Joyce B J %A Strauch, Konstantin %A Styrkarsdottir, Unnur %A Swerdlow, Anthony J %A Tanaka, Toshiko %A Teras, Lauren R %A Teumer, Alexander %A Þorsteinsdottir, Unnur %A Timpson, Nicholas J %A Toniolo, Daniela %A Traglia, Michela %A Troester, Melissa A %A Truong, Thérèse %A Tyrrell, Jessica %A Uitterlinden, André G %A Ulivi, Sheila %A Vachon, Celine M %A Vitart, Veronique %A Völker, Uwe %A Vollenweider, Peter %A Völzke, Henry %A Wang, Qin %A Wareham, Nicholas J %A Weinberg, Clarice R %A Weir, David R %A Wilcox, Amber N %A van Dijk, Ko Willems %A Willemsen, Gonneke %A Wilson, James F %A Wolffenbuttel, Bruce H R %A Wolk, Alicja %A Wood, Andrew R %A Zhao, Wei %A Zygmunt, Marek %A Chen, Zhengming %A Li, Liming %A Franke, Lude %A Burgess, Stephen %A Deelen, Patrick %A Pers, Tune H %A Grøndahl, Marie Louise %A Andersen, Claus Yding %A Pujol, Anna %A Lopez-Contreras, Andres J %A Daniel, Jeremy A %A Stefansson, Kari %A Chang-Claude, Jenny %A van der Schouw, Yvonne T %A Lunetta, Kathryn L %A Chasman, Daniel I %A Easton, Douglas F %A Visser, Jenny A %A Ozanne, Susan E %A Namekawa, Satoshi H %A Solc, Petr %A Murabito, Joanne M %A Ong, Ken K %A Hoffmann, Eva R %A Murray, Anna %A Roig, Ignasi %A Perry, John R B %X

Reproductive 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.

%B Nature %V 596 %P 393-397 %8 2021 Aug %G eng %N 7872 %R 10.1038/s41586-021-03779-7 %0 Journal Article %J PLoS One %D 2021 %T Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program. %A Sarnowski, Chloe %A Chen, Han %A Biggs, Mary L %A Wassertheil-Smoller, Sylvia %A Bressler, Jan %A Irvin, Marguerite R %A Ryan, Kathleen A %A Karasik, David %A Arnett, Donna K %A Cupples, L Adrienne %A Fardo, David W %A Gogarten, Stephanie M %A Heavner, Benjamin D %A Jain, Deepti %A Kang, Hyun Min %A Kooperberg, Charles %A Mainous, Arch G %A Mitchell, Braxton D %A Morrison, Alanna C %A O'Connell, Jeffrey R %A Psaty, Bruce M %A Rice, Kenneth %A Smith, Albert V %A Vasan, Ramachandran S %A Windham, B Gwen %A Kiel, Douglas P %A Murabito, Joanne M %A Lunetta, Kathryn L %X

Handgrip 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.

%B PLoS One %V 16 %P e0253611 %8 2021 %G eng %N 7 %R 10.1371/journal.pone.0253611 %0 Journal Article %J HGG Adv %D 2021 %T Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. %A Sun, Daokun %A Richard, Melissa %A Musani, Solomon K %A Sung, Yun Ju %A Winkler, Thomas W %A Schwander, Karen %A Chai, Jin Fang %A Guo, Xiuqing %A Kilpeläinen, Tuomas O %A Vojinovic, Dina %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Brown, Michael R %A Chitrala, Kumaraswamy %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Liu, Yongmei %A Manning, Alisa K %A Noordam, Raymond %A Smith, Albert V %A Harris, Sarah E %A Kuhnel, Brigitte %A Lyytikäinen, Leo-Pekka %A Nolte, Ilja M %A Rauramaa, Rainer %A van der Most, Peter J %A Wang, Rujia %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Arking, Dan E %A Arnett, Donna K %A Barac, Ana %A Boerwinkle, Eric %A Broeckel, Ulrich %A Chakravarti, Aravinda %A Chen, Yii-Der Ida %A Cupples, L Adrienne %A Davigulus, Martha L %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Vries, Paul S %A Delaney, Joseph A C %A Roux, Ana V Diez %A Dörr, Marcus %A Faul, Jessica D %A Fretts, Amanda M %A Gallo, Linda C %A Grabe, Hans Jörgen %A Gu, C Charles %A Harris, Tamara B %A Hartman, Catharina C A %A Heikkinen, Sami %A Ikram, M Arfan %A Isasi, Carmen %A Johnson, W Craig %A Jonas, Jost Bruno %A Kaplan, Robert C %A Komulainen, Pirjo %A Krieger, Jose E %A Levy, Daniel %A Liu, Jianjun %A Lohman, Kurt %A Luik, Annemarie I %A Martin, Lisa W %A Meitinger, Thomas %A Milaneschi, Yuri %A O'Connell, Jeff R %A Palmas, Walter R %A Peters, Annette %A Peyser, Patricia A %A Pulkki-Råback, Laura %A Raffel, Leslie J %A Reiner, Alex P %A Rice, Kenneth %A Robinson, Jennifer G %A Rosendaal, Frits R %A Schmidt, Carsten Oliver %A Schreiner, Pamela J %A Schwettmann, Lars %A Shikany, James M %A Shu, Xiao-Ou %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Sotoodehnia, Nona %A Strauch, Konstantin %A Tai, E Shyong %A Taylor, Kent %A Uitterlinden, André G %A van Duijn, Cornelia M %A Waldenberger, Melanie %A Wee, Hwee-Lin %A Wei, Wen-Bin %A Wilson, Gregory %A Xuan, Deng %A Yao, Jie %A Zeng, Donglin %A Zhao, Wei %A Zhu, Xiaofeng %A Zonderman, Alan B %A Becker, Diane M %A Deary, Ian J %A Gieger, Christian %A Lakka, Timo A %A Lehtimäki, Terho %A North, Kari E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Snieder, Harold %A Wang, Ya-Xing %A Weir, David R %A Zheng, Wei %A Evans, Michele K %A Gauderman, W James %A Gudnason, Vilmundur %A Horta, Bernardo L %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Morrison, Alanna C %A Pereira, Alexandre C %A Psaty, Bruce M %A Amin, Najaf %A Fox, Ervin R %A Kooperberg, Charles %A Sim, Xueling %A Bierut, Laura %A Rotter, Jerome I %A Kardia, Sharon L R %A Franceschini, Nora %A Rao, Dabeeru C %A Fornage, Myriam %X

Psychological 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.

%B HGG Adv %V 2 %8 2021 Jan 14 %G eng %N 1 %R 10.1016/j.xhgg.2020.100013 %0 Journal Article %J Mol Psychiatry %D 2021 %T Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. %A Wang, Heming %A Noordam, Raymond %A Cade, Brian E %A Schwander, Karen %A Winkler, Thomas W %A Lee, Jiwon %A Sung, Yun Ju %A Bentley, Amy R %A Manning, Alisa K %A Aschard, Hugues %A Kilpeläinen, Tuomas O %A Ilkov, Marjan %A Brown, Michael R %A Horimoto, Andrea R %A Richard, Melissa %A Bartz, Traci M %A Vojinovic, Dina %A Lim, Elise %A Nierenberg, Jovia L %A Liu, Yongmei %A Chitrala, Kumaraswamynaidu %A Rankinen, Tuomo %A Musani, Solomon K %A Franceschini, Nora %A Rauramaa, Rainer %A Alver, Maris %A Zee, Phyllis C %A Harris, Sarah E %A van der Most, Peter J %A Nolte, Ilja M %A Munroe, Patricia B %A Palmer, Nicholette D %A Kuhnel, Brigitte %A Weiss, Stefan %A Wen, Wanqing %A Hall, Kelly A %A Lyytikäinen, Leo-Pekka %A O'Connell, Jeff %A Eiriksdottir, Gudny %A Launer, Lenore J %A de Vries, Paul S %A Arking, Dan E %A Chen, Han %A Boerwinkle, Eric %A Krieger, Jose E %A Schreiner, Pamela J %A Sidney, Stephen %A Shikany, James M %A Rice, Kenneth %A Chen, Yii-Der Ida %A Gharib, Sina A %A Bis, Joshua C %A Luik, Annemarie I %A Ikram, M Arfan %A Uitterlinden, André G %A Amin, Najaf %A Xu, Hanfei %A Levy, Daniel %A He, Jiang %A Lohman, Kurt K %A Zonderman, Alan B %A Rice, Treva K %A Sims, Mario %A Wilson, Gregory %A Sofer, Tamar %A Rich, Stephen S %A Palmas, Walter %A Yao, Jie %A Guo, Xiuqing %A Rotter, Jerome I %A Biermasz, Nienke R %A Mook-Kanamori, Dennis O %A Martin, Lisa W %A Barac, Ana %A Wallace, Robert B %A Gottlieb, Daniel J %A Komulainen, Pirjo %A Heikkinen, Sami %A Mägi, Reedik %A Milani, Lili %A Metspalu, Andres %A Starr, John M %A Milaneschi, Yuri %A Waken, R J %A Gao, Chuan %A Waldenberger, Melanie %A Peters, Annette %A Strauch, Konstantin %A Meitinger, Thomas %A Roenneberg, Till %A Völker, Uwe %A Dörr, Marcus %A Shu, Xiao-Ou %A Mukherjee, Sutapa %A Hillman, David R %A Kähönen, Mika %A Wagenknecht, Lynne E %A Gieger, Christian %A Grabe, Hans J %A Zheng, Wei %A Palmer, Lyle J %A Lehtimäki, Terho %A Gudnason, Vilmundur %A Morrison, Alanna C %A Pereira, Alexandre C %A Fornage, Myriam %A Psaty, Bruce M %A van Duijn, Cornelia M %A Liu, Ching-Ti %A Kelly, Tanika N %A Evans, Michele K %A Bouchard, Claude %A Fox, Ervin R %A Kooperberg, Charles %A Zhu, Xiaofeng %A Lakka, Timo A %A Esko, Tõnu %A North, Kari E %A Deary, Ian J %A Snieder, Harold %A Penninx, Brenda W J H %A Gauderman, W James %A Rao, Dabeeru C %A Redline, Susan %A van Heemst, Diana %X

Long 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.

%B Mol Psychiatry %8 2021 Apr 15 %G eng %R 10.1038/s41380-021-01087-0 %0 Journal Article %J Nature %D 2021 %T Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. %A Taliun, Daniel %A Harris, Daniel N %A Kessler, Michael D %A Carlson, Jedidiah %A Szpiech, Zachary A %A Torres, Raul %A Taliun, Sarah A Gagliano %A Corvelo, André %A Gogarten, Stephanie M %A Kang, Hyun Min %A Pitsillides, Achilleas N %A LeFaive, Jonathon %A Lee, Seung-Been %A Tian, Xiaowen %A Browning, Brian L %A Das, Sayantan %A Emde, Anne-Katrin %A Clarke, Wayne E %A Loesch, Douglas P %A Shetty, Amol C %A Blackwell, Thomas W %A Smith, Albert V %A Wong, Quenna %A Liu, Xiaoming %A Conomos, Matthew P %A Bobo, Dean M %A Aguet, Francois %A Albert, Christine %A Alonso, Alvaro %A Ardlie, Kristin G %A Arking, Dan E %A Aslibekyan, Stella %A Auer, Paul L %A Barnard, John %A Barr, R Graham %A Barwick, Lucas %A Becker, Lewis C %A Beer, Rebecca L %A Benjamin, Emelia J %A Bielak, Lawrence F %A Blangero, John %A Boehnke, Michael %A Bowden, Donald W %A Brody, Jennifer A %A Burchard, Esteban G %A Cade, Brian E %A Casella, James F %A Chalazan, Brandon %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Cho, Michael H %A Choi, Seung Hoan %A Chung, Mina K %A Clish, Clary B %A Correa, Adolfo %A Curran, Joanne E %A Custer, Brian %A Darbar, Dawood %A Daya, Michelle %A de Andrade, Mariza %A DeMeo, Dawn L %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Eng, Celeste %A Fatkin, Diane %A Fingerlin, Tasha %A Forer, Lukas %A Fornage, Myriam %A Franceschini, Nora %A Fuchsberger, Christian %A Fullerton, Stephanie M %A Germer, Soren %A Gladwin, Mark T %A Gottlieb, Daniel J %A Guo, Xiuqing %A Hall, Michael E %A He, Jiang %A Heard-Costa, Nancy L %A Heckbert, Susan R %A Irvin, Marguerite R %A Johnsen, Jill M %A Johnson, Andrew D %A Kaplan, Robert %A Kardia, Sharon L R %A Kelly, Tanika %A Kelly, Shannon %A Kenny, Eimear E %A Kiel, Douglas P %A Klemmer, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Köttgen, Anna %A Lange, Leslie A %A Lasky-Su, Jessica %A Levy, Daniel %A Lin, Xihong %A Lin, Keng-Han %A Liu, Chunyu %A Loos, Ruth J F %A Garman, Lori %A Gerszten, Robert %A Lubitz, Steven A %A Lunetta, Kathryn L %A Mak, Angel C Y %A Manichaikul, Ani %A Manning, Alisa K %A Mathias, Rasika A %A McManus, David D %A McGarvey, Stephen T %A Meigs, James B %A Meyers, Deborah A %A Mikulla, Julie L %A Minear, Mollie A %A Mitchell, Braxton D %A Mohanty, Sanghamitra %A Montasser, May E %A Montgomery, Courtney %A Morrison, Alanna C %A Murabito, Joanne M %A Natale, Andrea %A Natarajan, Pradeep %A Nelson, Sarah C %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Pankratz, Nathan %A Peloso, Gina M %A Peyser, Patricia A %A Pleiness, Jacob %A Post, Wendy S %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Roden, Dan %A Rotter, Jerome I %A Ruczinski, Ingo %A Sarnowski, Chloe %A Schoenherr, Sebastian %A Schwartz, David A %A Seo, Jeong-Sun %A Seshadri, Sudha %A Sheehan, Vivien A %A Sheu, Wayne H %A Shoemaker, M Benjamin %A Smith, Nicholas L %A Smith, Jennifer A %A Sotoodehnia, Nona %A Stilp, Adrienne M %A Tang, Weihong %A Taylor, Kent D %A Telen, Marilyn %A Thornton, Timothy A %A Tracy, Russell P %A Van Den Berg, David J %A Vasan, Ramachandran S %A Viaud-Martinez, Karine A %A Vrieze, Scott %A Weeks, Daniel E %A Weir, Bruce S %A Weiss, Scott T %A Weng, Lu-Chen %A Willer, Cristen J %A Zhang, Yingze %A Zhao, Xutong %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Boerwinkle, Eric %A Gabriel, Stacey %A Gibbs, Richard %A Rice, Kenneth M %A Rich, Stephen S %A Silverman, Edwin K %A Qasba, Pankaj %A Gan, Weiniu %A Papanicolaou, George J %A Nickerson, Deborah A %A Browning, Sharon R %A Zody, Michael C %A Zöllner, Sebastian %A Wilson, James G %A Cupples, L Adrienne %A Laurie, Cathy C %A Jaquish, Cashell E %A Hernandez, Ryan D %A O'Connor, Timothy D %A Abecasis, Goncalo R %X

The 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%.

%B Nature %V 590 %P 290-299 %8 2021 02 %G eng %N 7845 %R 10.1038/s41586-021-03205-y %0 Journal Article %J J Am Coll Cardiol %D 2021 %T Supplemental Association of Clonal Hematopoiesis With Incident Heart Failure. %A Yu, Bing %A Roberts, Mary B %A Raffield, Laura M %A Zekavat, Seyedeh Maryam %A Nguyen, Ngoc Quynh H %A Biggs, Mary L %A Brown, Michael R %A Griffin, Gabriel %A Desai, Pinkal %A Correa, Adolfo %A Morrison, Alanna C %A Shah, Amil M %A Niroula, Abhishek %A Uddin, Md Mesbah %A Honigberg, Michael C %A Ebert, Benjamin L %A Psaty, Bruce M %A Whitsel, Eric A %A Manson, JoAnn E %A Kooperberg, Charles %A Bick, Alexander G %A Ballantyne, Christie M %A Reiner, Alex P %A Natarajan, Pradeep %A Eaton, Charles B %K Aged %K Clonal Hematopoiesis %K Correlation of Data %K Demography %K DNA-Binding Proteins %K Female %K Heart Failure %K Humans %K Janus Kinase 2 %K Male %K Middle Aged %K Mutation %K Proportional Hazards Models %K Proto-Oncogene Proteins %K Repressor Proteins %K Risk Factors %K Stroke Volume %K Ventricular Dysfunction, Left %K Whole Exome Sequencing %X

BACKGROUND: 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.

%B J Am Coll Cardiol %V 78 %P 42-52 %8 2021 07 06 %G eng %N 1 %R 10.1016/j.jacc.2021.04.085 %0 Journal Article %J Am J Epidemiol %D 2021 %T A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. %A Stilp, Adrienne M %A Emery, Leslie S %A Broome, Jai G %A Buth, Erin J %A Khan, Alyna T %A Laurie, Cecelia A %A Wang, Fei Fei %A Wong, Quenna %A Chen, Dongquan %A D'Augustine, Catherine M %A Heard-Costa, Nancy L %A Hohensee, Chancellor R %A Johnson, William Craig %A Juarez, Lucia D %A Liu, Jingmin %A Mutalik, Karen M %A Raffield, Laura M %A Wiggins, Kerri L %A de Vries, Paul S %A Kelly, Tanika N %A Kooperberg, Charles %A Natarajan, Pradeep %A Peloso, Gina M %A Peyser, Patricia A %A Reiner, Alex P %A Arnett, Donna K %A Aslibekyan, Stella %A Barnes, Kathleen C %A Bielak, Lawrence F %A Bis, Joshua C %A Cade, Brian E %A Chen, Ming-Huei %A Correa, Adolfo %A Cupples, L Adrienne %A de Andrade, Mariza %A Ellinor, Patrick T %A Fornage, Myriam %A Franceschini, Nora %A Gan, Weiniu %A Ganesh, Santhi K %A Graffelman, Jan %A Grove, Megan L %A Guo, Xiuqing %A Hawley, Nicola L %A Hsu, Wan-Ling %A Jackson, Rebecca D %A Jaquish, Cashell E %A Johnson, Andrew D %A Kardia, Sharon L R %A Kelly, Shannon %A Lee, Jiwon %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A North, Kari E %A Nouraie, Seyed Mehdi %A Oelsner, Elizabeth C %A Pankratz, Nathan %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Jennifer A %A Taylor, Kent D %A Vasan, Ramachandran S %A Weeks, Daniel E %A Weiss, Scott T %A Wilson, Carla G %A Yanek, Lisa R %A Psaty, Bruce M %A Heckbert, Susan R %A Laurie, Cathy C %X

Genotype-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.

%B Am J Epidemiol %8 2021 Apr 16 %G eng %R 10.1093/aje/kwab115 %0 Journal Article %J EBioMedicine %D 2021 %T Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium. %A Lin, Bridget M %A Grinde, Kelsey E %A Brody, Jennifer A %A Breeze, Charles E %A Raffield, Laura M %A Mychaleckyj, Josyf C %A Thornton, Timothy A %A Perry, James A %A Baier, Leslie J %A de Las Fuentes, Lisa %A Guo, Xiuqing %A Heavner, Benjamin D %A Hanson, Robert L %A Hung, Yi-Jen %A Qian, Huijun %A Hsiung, Chao A %A Hwang, Shih-Jen %A Irvin, Margaret R %A Jain, Deepti %A Kelly, Tanika N %A Kobes, Sayuko %A Lange, Leslie %A Lash, James P %A Li, Yun %A Liu, Xiaoming %A Mi, Xuenan %A Musani, Solomon K %A Papanicolaou, George J %A Parsa, Afshin %A Reiner, Alex P %A Salimi, Shabnam %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Taylor, Kent D %A Smith, Albert V %A Smith, Jennifer A %A Tin, Adrienne %A Vaidya, Dhananjay %A Wallace, Robert B %A Yamamoto, Kenichi %A Sakaue, Saori %A Matsuda, Koichi %A Kamatani, Yoichiro %A Momozawa, Yukihide %A Yanek, Lisa R %A Young, Betsi A %A Zhao, Wei %A Okada, Yukinori %A Abecasis, Gonzalo %A Psaty, Bruce M %A Arnett, Donna K %A Boerwinkle, Eric %A Cai, Jianwen %A Yii-Der Chen, Ida %A Correa, Adolfo %A Cupples, L Adrienne %A He, Jiang %A Kardia, Sharon Lr %A Kooperberg, Charles %A Mathias, Rasika A %A Mitchell, Braxton D %A Nickerson, Deborah A %A Turner, Steve T %A Vasan, Ramachandran S %A Rotter, Jerome I %A Levy, Daniel %A Kramer, Holly J %A Köttgen, Anna %A Rich, Stephen S %A Lin, Dan-Yu %A Browning, Sharon R %A Franceschini, Nora %X

BACKGROUND: 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.

%B EBioMedicine %V 63 %P 103157 %8 2021 Jan %G eng %R 10.1016/j.ebiom.2020.103157 %0 Journal Article %J Hum Mol Genet %D 2021 %T Whole genome sequence analysis of platelet traits in the NHLBI trans-omics for precision medicine initiative. %A Little, Amarise %A Hu, Yao %A Sun, Quan %A Jain, Deepti %A Broome, Jai %A Chen, Ming-Huei %A Thibord, Florian %A McHugh, Caitlin %A Surendran, Praveen %A Blackwell, Thomas W %A Brody, Jennifer A %A Bhan, Arunoday %A Chami, Nathalie %A Vries, Paul S %A Ekunwe, Lynette %A Heard-Costa, Nancy %A Hobbs, Brian D %A Manichaikul, Ani %A Moon, Jee-Young %A Preuss, Michael H %A Ryan, Kathleen %A Wang, Zhe %A Wheeler, Marsha %A Yanek, Lisa R %A Abecasis, Goncalo R %A Almasy, Laura %A Beaty, Terri H %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Butterworth, Adam S %A Choquet, Helene %A Correa, Adolfo %A Curran, Joanne E %A Faraday, Nauder %A Fornage, Myriam %A Glahn, David C %A Hou, Lifang %A Jorgenson, Eric %A Kooperberg, Charles %A Lewis, Joshua P %A Lloyd-Jones, Donald M %A Loos, Ruth J F %A Min, Nancy %A Mitchell, Braxton D %A Morrison, Alanna C %A Nickerson, Debbie %A North, Kari E %A O'Connell, Jeffrey R %A Pankratz, Nathan %A Psaty, Bruce M %A Vasan, Ramachandran S %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Albert V %A Smith, Nicholas L %A Tang, Hua %A Tracy, Russell P %A Conomos, Matthew P %A Laurie, Cecelia A %A Mathias, Rasika A %A Li, Yun %A Auer, Paul L %A Thornton, Timothy %A Reiner, Alexander P %A Johnson, Andrew D %A Raffield, Laura M %X

Platelets 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.

%B Hum Mol Genet %8 2021 Sep 06 %G eng %R 10.1093/hmg/ddab252 %0 Journal Article %J Am J Hum Genet %D 2021 %T Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program. %A Hu, Yao %A Stilp, Adrienne M %A McHugh, Caitlin P %A Rao, Shuquan %A Jain, Deepti %A Zheng, Xiuwen %A Lane, John %A Méric de Bellefon, Sébastian %A Raffield, Laura M %A Chen, Ming-Huei %A Yanek, Lisa R %A Wheeler, Marsha %A Yao, Yao %A Ren, Chunyan %A Broome, Jai %A Moon, Jee-Young %A de Vries, Paul S %A Hobbs, Brian D %A Sun, Quan %A Surendran, Praveen %A Brody, Jennifer A %A Blackwell, Thomas W %A Choquet, Helene %A Ryan, Kathleen %A Duggirala, Ravindranath %A Heard-Costa, Nancy %A Wang, Zhe %A Chami, Nathalie %A Preuss, Michael H %A Min, Nancy %A Ekunwe, Lynette %A Lange, Leslie A %A Cushman, Mary %A Faraday, Nauder %A Curran, Joanne E %A Almasy, Laura %A Kundu, Kousik %A Smith, Albert V %A Gabriel, Stacey %A Rotter, Jerome I %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Vasan, Ramachandran S %A Smith, Nicholas L %A North, Kari E %A Boerwinkle, Eric %A Becker, Lewis C %A Lewis, Joshua P %A Abecasis, Goncalo R %A Hou, Lifang %A O'Connell, Jeffrey R %A Morrison, Alanna C %A Beaty, Terri H %A Kaplan, Robert %A Correa, Adolfo %A Blangero, John %A Jorgenson, Eric %A Psaty, Bruce M %A Kooperberg, Charles %A Walton, Russell T %A Kleinstiver, Benjamin P %A Tang, Hua %A Loos, Ruth J F %A Soranzo, Nicole %A Butterworth, Adam S %A Nickerson, Debbie %A Rich, Stephen S %A Mitchell, Braxton D %A Johnson, Andrew D %A Auer, Paul L %A Li, Yun %A Mathias, Rasika A %A Lettre, Guillaume %A Pankratz, Nathan %A Laurie, Cathy C %A Laurie, Cecelia A %A Bauer, Daniel E %A Conomos, Matthew P %A Reiner, Alexander P %K Adult %K Aged %K Chromosomes, Human, Pair 16 %K Datasets as Topic %K Erythrocytes %K Female %K Gene Editing %K Genetic Variation %K Genome-Wide Association Study %K HEK293 Cells %K Humans %K Male %K Middle Aged %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Quality Control %K Reproducibility of Results %K United States %X

Whole-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.

%B Am J Hum Genet %V 108 %P 874-893 %8 2021 05 06 %G eng %N 5 %R 10.1016/j.ajhg.2021.04.003 %0 Journal Article %J Am J Hum Genet %D 2021 %T Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program. %A Mikhaylova, Anna V %A McHugh, Caitlin P %A Polfus, Linda M %A Raffield, Laura M %A Boorgula, Meher Preethi %A Blackwell, Thomas W %A Brody, Jennifer A %A Broome, Jai %A Chami, Nathalie %A Chen, Ming-Huei %A Conomos, Matthew P %A Cox, Corey %A Curran, Joanne E %A Daya, Michelle %A Ekunwe, Lynette %A Glahn, David C %A Heard-Costa, Nancy %A Highland, Heather M %A Hobbs, Brian D %A Ilboudo, Yann %A Jain, Deepti %A Lange, Leslie A %A Miller-Fleming, Tyne W %A Min, Nancy %A Moon, Jee-Young %A Preuss, Michael H %A Rosen, Jonathon %A Ryan, Kathleen %A Smith, Albert V %A Sun, Quan %A Surendran, Praveen %A de Vries, Paul S %A Walter, Klaudia %A Wang, Zhe %A Wheeler, Marsha %A Yanek, Lisa R %A Zhong, Xue %A Abecasis, Goncalo R %A Almasy, Laura %A Barnes, Kathleen C %A Beaty, Terri H %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Butterworth, Adam S %A Chavan, Sameer %A Cho, Michael H %A Choquet, Helene %A Correa, Adolfo %A Cox, Nancy %A DeMeo, Dawn L %A Faraday, Nauder %A Fornage, Myriam %A Gerszten, Robert E %A Hou, Lifang %A Johnson, Andrew D %A Jorgenson, Eric %A Kaplan, Robert %A Kooperberg, Charles %A Kundu, Kousik %A Laurie, Cecelia A %A Lettre, Guillaume %A Lewis, Joshua P %A Li, Bingshan %A Li, Yun %A Lloyd-Jones, Donald M %A Loos, Ruth J F %A Manichaikul, Ani %A Meyers, Deborah A %A Mitchell, Braxton D %A Morrison, Alanna C %A Ngo, Debby %A Nickerson, Deborah A %A Nongmaithem, Suraj %A North, Kari E %A O'Connell, Jeffrey R %A Ortega, Victor E %A Pankratz, Nathan %A Perry, James A %A Psaty, Bruce M %A Rich, Stephen S %A Soranzo, Nicole %A Rotter, Jerome I %A Silverman, Edwin K %A Smith, Nicholas L %A Tang, Hua %A Tracy, Russell P %A Thornton, Timothy A %A Vasan, Ramachandran S %A Zein, Joe %A Mathias, Rasika A %A Reiner, Alexander P %A Auer, Paul L %K Asthma %K Biomarkers %K Dermatitis, Atopic %K Genetic Predisposition to Disease %K Genome, Human %K Genome-Wide Association Study %K Humans %K Leukocytes %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Polymorphism, Single Nucleotide %K Prognosis %K Proteome %K Pulmonary Disease, Chronic Obstructive %K Quantitative Trait Loci %K United Kingdom %K United States %K Whole Genome Sequencing %X

Many 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.

%B Am J Hum Genet %V 108 %P 1836-1851 %8 2021 10 07 %G eng %N 10 %R 10.1016/j.ajhg.2021.08.007 %0 Journal Article %J Nat Genet %D 2022 %T Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. %A Wainschtein, Pierrick %A Jain, Deepti %A Zheng, Zhili %A Cupples, L Adrienne %A Shadyab, Aladdin H %A McKnight, Barbara %A Shoemaker, Benjamin M %A Mitchell, Braxton D %A Psaty, Bruce M %A Kooperberg, Charles %A Liu, Ching-Ti %A Albert, Christine M %A Roden, Dan %A Chasman, Daniel I %A Darbar, Dawood %A Lloyd-Jones, Donald M %A Arnett, Donna K %A Regan, Elizabeth A %A Boerwinkle, Eric %A Rotter, Jerome I %A O'Connell, Jeffrey R %A Yanek, Lisa R %A de Andrade, Mariza %A Allison, Matthew A %A McDonald, Merry-Lynn N %A Chung, Mina K %A Fornage, Myriam %A Chami, Nathalie %A Smith, Nicholas L %A Ellinor, Patrick T %A Vasan, Ramachandran S %A Mathias, Rasika A %A Loos, Ruth J F %A Rich, Stephen S %A Lubitz, Steven A %A Heckbert, Susan R %A Redline, Susan %A Guo, Xiuqing %A Chen, Y -D Ida %A Laurie, Cecelia A %A Hernandez, Ryan D %A McGarvey, Stephen T %A Goddard, Michael E %A Laurie, Cathy C %A North, Kari E %A Lange, Leslie A %A Weir, Bruce S %A Yengo, Loic %A Yang, Jian %A Visscher, Peter M %X

Analyses 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.

%B Nat Genet %V 54 %P 263-273 %8 2022 Mar %G eng %N 3 %R 10.1038/s41588-021-00997-7 %0 Journal Article %J Stroke %D 2022 %T Clonal Hematopoiesis Is Associated With Higher Risk of Stroke. %A Bhattacharya, Romit %A Zekavat, Seyedeh M %A Haessler, Jeffrey %A Fornage, Myriam %A Raffield, Laura %A Uddin, Md Mesbah %A Bick, Alexander G %A Niroula, Abhishek %A Yu, Bing %A Gibson, Christopher %A Griffin, Gabriel %A Morrison, Alanna C %A Psaty, Bruce M %A Longstreth, William T %A Bis, Joshua C %A Rich, Stephen S %A Rotter, Jerome I %A Tracy, Russell P %A Correa, Adolfo %A Seshadri, Sudha %A Johnson, Andrew %A Collins, Jason M %A Hayden, Kathleen M %A Madsen, Tracy E %A Ballantyne, Christie M %A Jaiswal, Siddhartha %A Ebert, Benjamin L %A Kooperberg, Charles %A Manson, JoAnn E %A Whitsel, Eric A %A Natarajan, Pradeep %A Reiner, Alexander P %X

BACKGROUND 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.

%B Stroke %V 53 %P 788-797 %8 2022 Mar %G eng %N 3 %R 10.1161/STROKEAHA.121.037388 %0 Journal Article %J Circulation %D 2022 %T Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors. %A Thibord, Florian %A Klarin, Derek %A Brody, Jennifer A %A Chen, Ming-Huei %A Levin, Michael G %A Chasman, Daniel I %A Goode, Ellen L %A Hveem, Kristian %A Teder-Laving, Maris %A Martinez-Perez, Angel %A Aïssi, Dylan %A Daian-Bacq, Delphine %A Ito, Kaoru %A Natarajan, Pradeep %A Lutsey, Pamela L %A Nadkarni, Girish N %A de Vries, Paul S %A Cuellar-Partida, Gabriel %A Wolford, Brooke N %A Pattee, Jack W %A Kooperberg, Charles %A Braekkan, Sigrid K %A Li-Gao, Ruifang %A Saut, Noémie %A Sept, Corriene %A Germain, Marine %A Judy, Renae L %A Wiggins, Kerri L %A Ko, Darae %A O'Donnell, Christopher J %A Taylor, Kent D %A Giulianini, Franco %A de Andrade, Mariza %A Nøst, Therese H %A Boland, Anne %A Empana, Jean-Philippe %A Koyama, Satoshi %A Gilliland, Thomas %A Do, Ron %A Huffman, Jennifer E %A Wang, Xin %A Zhou, Wei %A Manuel Soria, Jose %A Carlos Souto, Juan %A Pankratz, Nathan %A Haessler, Jeffery %A Hindberg, Kristian %A Rosendaal, Frits R %A Turman, Constance %A Olaso, Robert %A Kember, Rachel L %A Bartz, Traci M %A Lynch, Julie A %A Heckbert, Susan R %A Armasu, Sebastian M %A Brumpton, Ben %A Smadja, David M %A Jouven, Xavier %A Komuro, Issei %A Clapham, Katharine R %A Loos, Ruth J F %A Willer, Cristen J %A Sabater-Lleal, Maria %A Pankow, James S %A Reiner, Alexander P %A Morelli, Vania M %A Ridker, Paul M %A Vlieg, Astrid van Hylckama %A Deleuze, Jean-Francois %A Kraft, Peter %A Rader, Daniel J %A Min Lee, Kyung %A Psaty, Bruce M %A Heidi Skogholt, Anne %A Emmerich, Joseph %A Suchon, Pierre %A Rich, Stephen S %A Vy, Ha My T %A Tang, Weihong %A Jackson, Rebecca D %A Hansen, John-Bjarne %A Morange, Pierre-Emmanuel %A Kabrhel, Christopher %A Trégouët, David-Alexandre %A Damrauer, Scott M %A Johnson, Andrew D %A Smith, Nicholas L %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genomics %K Humans %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Thrombosis %K Venous Thromboembolism %X

BACKGROUND: 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.

%B Circulation %V 146 %P 1225-1242 %8 2022 Oct 18 %G eng %N 16 %R 10.1161/CIRCULATIONAHA.122.059675 %0 Journal Article %J Nat Commun %D 2022 %T Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes. %A Halford, Jennifer L %A Morrill, Valerie N %A Choi, Seung Hoan %A Jurgens, Sean J %A Melloni, Giorgio %A Marston, Nicholas A %A Weng, Lu-Chen %A Nauffal, Victor %A Hall, Amelia W %A Gunn, Sophia %A Austin-Tse, Christina A %A Pirruccello, James P %A Khurshid, Shaan %A Rehm, Heidi L %A Benjamin, Emelia J %A Boerwinkle, Eric %A Brody, Jennifer A %A Correa, Adolfo %A Fornwalt, Brandon K %A Gupta, Namrata %A Haggerty, Christopher M %A Harris, Stephanie %A Heckbert, Susan R %A Hong, Charles C %A Kooperberg, Charles %A Lin, Henry J %A Loos, Ruth J F %A Mitchell, Braxton D %A Morrison, Alanna C %A Post, Wendy %A Psaty, Bruce M %A Redline, Susan %A Rice, Kenneth M %A Rich, Stephen S %A Rotter, Jerome I %A Schnatz, Peter F %A Soliman, Elsayed Z %A Sotoodehnia, Nona %A Wong, Eugene K %A Sabatine, Marc S %A Ruff, Christian T %A Lunetta, Kathryn L %A Ellinor, Patrick T %A Lubitz, Steven A %K Disease Susceptibility %K Endophenotypes %K Humans %K Long QT Syndrome %K Virulence %X

Accurate 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.

%B Nat Commun %V 13 %P 5106 %8 2022 08 30 %G eng %N 1 %R 10.1038/s41467-022-32009-5 %0 Journal Article %J Nat Methods %D 2022 %T A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. %A Li, Zilin %A Li, Xihao %A Zhou, Hufeng %A Gaynor, Sheila M %A Selvaraj, Margaret Sunitha %A Arapoglou, Theodore %A Quick, Corbin %A Liu, Yaowu %A Chen, Han %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Auer, Paul L %A Bielak, Lawrence F %A Bis, Joshua C %A Blackwell, Thomas W %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Conomos, Matthew P %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A de Vries, Paul S %A Duggirala, Ravindranath %A Franceschini, Nora %A Freedman, Barry I %A Göring, Harald H H %A Guo, Xiuqing %A Kalyani, Rita R %A Kooperberg, Charles %A Kral, Brian G %A Lange, Leslie A %A Lin, Bridget M %A Manichaikul, Ani %A Manning, Alisa K %A Martin, Lisa W %A Mathias, Rasika A %A Meigs, James B %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Rich, Stephen S %A Smith, Jennifer A %A Taylor, Kent D %A Taub, Margaret A %A Vasan, Ramachandran S %A Weeks, Daniel E %A Wilson, James G %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Willer, Cristen J %A Natarajan, Pradeep %A Peloso, Gina M %A Lin, Xihong %K Genetic Variation %K Genome %K Genome-Wide Association Study %K Humans %K Phenotype %K Whole Genome Sequencing %X

Large-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.

%B Nat Methods %V 19 %P 1599-1611 %8 2022 Dec %G eng %N 12 %R 10.1038/s41592-022-01640-x %0 Journal Article %J Hypertension %D 2022 %T Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. %A Kelly, Tanika N %A Sun, Xiao %A He, Karen Y %A Brown, Michael R %A Taliun, Sarah A Gagliano %A Hellwege, Jacklyn N %A Irvin, Marguerite R %A Mi, Xuenan %A Brody, Jennifer A %A Franceschini, Nora %A Guo, Xiuqing %A Hwang, Shih-Jen %A de Vries, Paul S %A Gao, Yan %A Moscati, Arden %A Nadkarni, Girish N %A Yanek, Lisa R %A Elfassy, Tali %A Smith, Jennifer A %A Chung, Ren-Hua %A Beitelshees, Amber L %A Patki, Amit %A Aslibekyan, Stella %A Blobner, Brandon M %A Peralta, Juan M %A Assimes, Themistocles L %A Palmas, Walter R %A Liu, Chunyu %A Bress, Adam P %A Huang, Zhijie %A Becker, Lewis C %A Hwa, Chii-Min %A O'Connell, Jeffrey R %A Carlson, Jenna C %A Warren, Helen R %A Das, Sayantan %A Giri, Ayush %A Martin, Lisa W %A Craig Johnson, W %A Fox, Ervin R %A Bottinger, Erwin P %A Razavi, Alexander C %A Vaidya, Dhananjay %A Chuang, Lee-Ming %A Chang, Yen-Pei C %A Naseri, Take %A Jain, Deepti %A Kang, Hyun Min %A Hung, Adriana M %A Srinivasasainagendra, Vinodh %A Snively, Beverly M %A Gu, Dongfeng %A Montasser, May E %A Reupena, Muagututi'a Sefuiva %A Heavner, Benjamin D %A LeFaive, Jonathon %A Hixson, James E %A Rice, Kenneth M %A Wang, Fei Fei %A Nielsen, Jonas B %A Huang, Jianfeng %A Khan, Alyna T %A Zhou, Wei %A Nierenberg, Jovia L %A Laurie, Cathy C %A Armstrong, Nicole D %A Shi, Mengyao %A Pan, Yang %A Stilp, Adrienne M %A Emery, Leslie %A Wong, Quenna %A Hawley, Nicola L %A Minster, Ryan L %A Curran, Joanne E %A Munroe, Patricia B %A Weeks, Daniel E %A North, Kari E %A Tracy, Russell P %A Kenny, Eimear E %A Shimbo, Daichi %A Chakravarti, Aravinda %A Rich, Stephen S %A Reiner, Alex P %A Blangero, John %A Redline, Susan %A Mitchell, Braxton D %A Rao, Dabeeru C %A Ida Chen, Yii-Der %A Kardia, Sharon L R %A Kaplan, Robert C %A Mathias, Rasika A %A He, Jiang %A Psaty, Bruce M %A Fornage, Myriam %A Loos, Ruth J F %A Correa, Adolfo %A Boerwinkle, Eric %A Rotter, Jerome I %A Kooperberg, Charles %A Edwards, Todd L %A Abecasis, Goncalo R %A Zhu, Xiaofeng %A Levy, Daniel %A Arnett, Donna K %A Morrison, Alanna C %X

BACKGROUND: 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.

%B Hypertension %P 101161HYPERTENSIONAHA12219324 %8 2022 Jun 02 %G eng %R 10.1161/HYPERTENSIONAHA.122.19324 %0 Journal Article %J Nat Med %D 2022 %T Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. %A Tcheandjieu, Catherine %A Zhu, Xiang %A Hilliard, Austin T %A Clarke, Shoa L %A Napolioni, Valerio %A Ma, Shining %A Lee, Kyung Min %A Fang, Huaying %A Chen, Fei %A Lu, Yingchang %A Tsao, Noah L %A Raghavan, Sridharan %A Koyama, Satoshi %A Gorman, Bryan R %A Vujkovic, Marijana %A Klarin, Derek %A Levin, Michael G %A Sinnott-Armstrong, Nasa %A Wojcik, Genevieve L %A Plomondon, Mary E %A Maddox, Thomas M %A Waldo, Stephen W %A Bick, Alexander G %A Pyarajan, Saiju %A Huang, Jie %A Song, Rebecca %A Ho, Yuk-Lam %A Buyske, Steven %A Kooperberg, Charles %A Haessler, Jeffrey %A Loos, Ruth J F %A Do, Ron %A Verbanck, Marie %A Chaudhary, Kumardeep %A North, Kari E %A Avery, Christy L %A Graff, Mariaelisa %A Haiman, Christopher A %A Le Marchand, Loïc %A Wilkens, Lynne R %A Bis, Joshua C %A Leonard, Hampton %A Shen, Botong %A Lange, Leslie A %A Giri, Ayush %A Dikilitas, Ozan %A Kullo, Iftikhar J %A Stanaway, Ian B %A Jarvik, Gail P %A Gordon, Adam S %A Hebbring, Scott %A Namjou, Bahram %A Kaufman, Kenneth M %A Ito, Kaoru %A Ishigaki, Kazuyoshi %A Kamatani, Yoichiro %A Verma, Shefali S %A Ritchie, Marylyn D %A Kember, Rachel L %A Baras, Aris %A Lotta, Luca A %A Kathiresan, Sekar %A Hauser, Elizabeth R %A Miller, Donald R %A Lee, Jennifer S %A Saleheen, Danish %A Reaven, Peter D %A Cho, Kelly %A Gaziano, J Michael %A Natarajan, Pradeep %A Huffman, Jennifer E %A Voight, Benjamin F %A Rader, Daniel J %A Chang, Kyong-Mi %A Lynch, Julie A %A Damrauer, Scott M %A Wilson, Peter W F %A Tang, Hua %A Sun, Yan V %A Tsao, Philip S %A O'Donnell, Christopher J %A Assimes, Themistocles L %K Coronary Artery Disease %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %X

We 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.

%B Nat Med %V 28 %P 1679-1692 %8 2022 08 %G eng %N 8 %R 10.1038/s41591-022-01891-3 %0 Journal Article %J Circulation %D 2022 %T Monogenic and Polygenic Contributions to QTc Prolongation in the Population. %A Nauffal, Victor %A Morrill, Valerie N %A Jurgens, Sean J %A Choi, Seung Hoan %A Hall, Amelia W %A Weng, Lu-Chen %A Halford, Jennifer L %A Austin-Tse, Christina %A Haggerty, Christopher M %A Harris, Stephanie L %A Wong, Eugene K %A Alonso, Alvaro %A Arking, Dan E %A Benjamin, Emelia J %A Boerwinkle, Eric %A Min, Yuan-I %A Correa, Adolfo %A Fornwalt, Brandon K %A Heckbert, Susan R %A Kooperberg, Charles %A Lin, Henry J %A Loos, Ruth J F %A Rice, Kenneth M %A Gupta, Namrata %A Blackwell, Thomas W %A Mitchell, Braxton D %A Morrison, Alanna C %A Psaty, Bruce M %A Post, Wendy S %A Redline, Susan %A Rehm, Heidi L %A Rich, Stephen S %A Rotter, Jerome I %A Soliman, Elsayed Z %A Sotoodehnia, Nona %A Lunetta, Kathryn L %A Ellinor, Patrick T %A Lubitz, Steven A %X

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.

%B Circulation %8 2022 Apr 07 %G eng %R 10.1161/CIRCULATIONAHA.121.057261 %0 Journal Article %J Nat Genet %D 2022 %T Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. %A Mahajan, Anubha %A Spracklen, Cassandra N %A Zhang, Weihua %A Ng, Maggie C Y %A Petty, Lauren E %A Kitajima, Hidetoshi %A Yu, Grace Z %A Rüeger, Sina %A Speidel, Leo %A Kim, Young Jin %A Horikoshi, Momoko %A Mercader, Josep M %A Taliun, Daniel %A Moon, Sanghoon %A Kwak, Soo-Heon %A Robertson, Neil R %A Rayner, Nigel W %A Loh, Marie %A Kim, Bong-Jo %A Chiou, Joshua %A Miguel-Escalada, Irene %A Della Briotta Parolo, Pietro %A Lin, Kuang %A Bragg, Fiona %A Preuss, Michael H %A Takeuchi, Fumihiko %A Nano, Jana %A Guo, Xiuqing %A Lamri, Amel %A Nakatochi, Masahiro %A Scott, Robert A %A Lee, Jung-Jin %A Huerta-Chagoya, Alicia %A Graff, Mariaelisa %A Chai, Jin-Fang %A Parra, Esteban J %A Yao, Jie %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Steinthorsdottir, Valgerdur %A Cook, James P %A Kals, Mart %A Grarup, Niels %A Schmidt, Ellen M %A Pan, Ian %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Ahmad, Meraj %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Lecoeur, Cécile %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Jensen, Richard A %A Tajuddin, Salman %A Kabagambe, Edmond K %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Flanagan, Jack %A Abaitua, Fernando %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Akiyama, Masato %A Anand, Sonia S %A Bertoni, Alain %A Bian, Zheng %A Bork-Jensen, Jette %A Brandslund, Ivan %A Brody, Jennifer A %A Brummett, Chad M %A Buchanan, Thomas A %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Fuchsberger, Christian %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Goodarzi, Mark O %A Gordon-Larsen, Penny %A Gorkin, David %A Gross, Myron %A Guo, Yu %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Marit E %A Jørgensen, Torben %A Kamatani, Yoichiro %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kohara, Katsuhiko %A Kriebel, Jennifer %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lyssenko, Valeriya %A Mamakou, Vasiliki %A Mani, K Radha %A Meitinger, Thomas %A Metspalu, Andres %A Morris, Andrew D %A Nadkarni, Girish N %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Nongmaithem, Suraj S %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Porneala, Bianca %A Prasad, Gauri %A Preissl, Sebastian %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Kathryn %A Sabanayagam, Charumathi %A Sander, Maike %A Sandow, Kevin %A Sattar, Naveed %A Schönherr, Sebastian %A Schurmann, Claudia %A Shahriar, Mohammad %A Shi, Jinxiu %A Shin, Dong Mun %A Shriner, Daniel %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Stilp, Adrienne M %A Strauch, Konstantin %A Suzuki, Ken %A Takahashi, Atsushi %A Taylor, Kent D %A Thorand, Barbara %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Torres, Jason M %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Vujkovic, Marijana %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Whitsel, Eric A %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamauchi, Toshimasa %A Yengo, Loic %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Hanis, Craig L %A Peyser, Patricia A %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Zeggini, Eleftheria %A Yokota, Mitsuhiro %A Rich, Stephen S %A Kooperberg, Charles %A Pankow, James S %A Engert, James C %A Chen, Yii-Der Ida %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Kardia, Sharon L R %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Groop, Leif %A Mook-Kanamori, Dennis O %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Bottinger, Erwin P %A Dehghan, Abbas %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Palmer, Colin N A %A Liu, Simin %A Abecasis, Goncalo %A Kooner, Jaspal S %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %A Florez, Jose C %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Mägi, Reedik %A Langenberg, Claudia %A Wareham, Nicholas J %A Maeda, Shiro %A Kadowaki, Takashi %A Lee, Juyoung %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Myers, Simon R %A Ferrer, Jorge %A Gaulton, Kyle J %A Meigs, James B %A Mohlke, Karen L %A Gloyn, Anna L %A Bowden, Donald W %A Below, Jennifer E %A Chambers, John C %A Sim, Xueling %A Boehnke, Michael %A Rotter, Jerome I %A McCarthy, Mark I %A Morris, Andrew P %K Diabetes Mellitus, Type 2 %K Ethnicity %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %X

We 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.

%B Nat Genet %V 54 %P 560-572 %8 2022 May %G eng %N 5 %R 10.1038/s41588-022-01058-3 %0 Journal Article %J Nat Commun %D 2022 %T A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. %A Kurniansyah, Nuzulul %A Goodman, Matthew O %A Kelly, Tanika N %A Elfassy, Tali %A Wiggins, Kerri L %A Bis, Joshua C %A Guo, Xiuqing %A Palmas, Walter %A Taylor, Kent D %A Lin, Henry J %A Haessler, Jeffrey %A Gao, Yan %A Shimbo, Daichi %A Smith, Jennifer A %A Yu, Bing %A Feofanova, Elena V %A Smit, Roelof A J %A Wang, Zhe %A Hwang, Shih-Jen %A Liu, Simin %A Wassertheil-Smoller, Sylvia %A Manson, JoAnn E %A Lloyd-Jones, Donald M %A Rich, Stephen S %A Loos, Ruth J F %A Redline, Susan %A Correa, Adolfo %A Kooperberg, Charles %A Fornage, Myriam %A Kaplan, Robert C %A Psaty, Bruce M %A Rotter, Jerome I %A Arnett, Donna K %A Morrison, Alanna C %A Franceschini, Nora %A Levy, Daniel %A Sofer, Tamar %K Adult %K Diabetes Mellitus, Type 2 %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Hypertension %K Multifactorial Inheritance %K Prevalence %K Risk Factors %X

In 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.

%B Nat Commun %V 13 %P 3549 %8 2022 Jun 21 %G eng %N 1 %R 10.1038/s41467-022-31080-2 %0 Journal Article %J Am J Hum Genet %D 2022 %T Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. %A Hindy, George %A Dornbos, Peter %A Chaffin, Mark D %A Liu, Dajiang J %A Wang, Minxian %A Selvaraj, Margaret Sunitha %A Zhang, David %A Park, Joseph %A Aguilar-Salinas, Carlos A %A Antonacci-Fulton, Lucinda %A Ardissino, Diego %A Arnett, Donna K %A Aslibekyan, Stella %A Atzmon, Gil %A Ballantyne, Christie M %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Becker, Lewis C %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Bown, Matthew J %A Brody, Jennifer A %A Broome, Jai G %A Burtt, Noel P %A Cade, Brian E %A Centeno-Cruz, Federico %A Chan, Edmund %A Chang, Yi-Cheng %A Chen, Yii-der I %A Cheng, Ching-Yu %A Choi, Won Jung %A Chowdhury, Rajiv %A Contreras-Cubas, Cecilia %A Córdova, Emilio J %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Danesh, John %A de Vries, Paul S %A DeFronzo, Ralph A %A Doddapaneni, Harsha %A Duggirala, Ravindranath %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Florez, Jose C %A Fornage, Myriam %A Freedman, Barry I %A Fuster, Valentin %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Germer, Soren %A Gibbs, Richard A %A Gieger, Christian %A Glaser, Benjamin %A Gonzalez, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Graff, Mariaelisa %A Graham, Sarah E %A Grarup, Niels %A Groop, Leif C %A Guo, Xiuqing %A Gupta, Namrata %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A He, Jiang %A Heard-Costa, Nancy L %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Irvin, Marguerite R %A Islas-Andrade, Sergio %A Jarvik, Gail P %A Kang, Hyun Min %A Kardia, Sharon L R %A Kelly, Tanika %A Kenny, Eimear E %A Khan, Alyna T %A Kim, Bong-Jo %A Kim, Ryan W %A Kim, Young Jin %A Koistinen, Heikki A %A Kooperberg, Charles %A Kuusisto, Johanna %A Kwak, Soo Heon %A Laakso, Markku %A Lange, Leslie A %A Lee, Jiwon %A Lee, Juyoung %A Lee, Seonwook %A Lehman, Donna M %A Lemaitre, Rozenn N %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lubitz, Steven A %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martin, Lisa Warsinger %A Martínez-Hernández, Angélica %A Mathias, Rasika A %A McGarvey, Stephen T %A McPherson, Ruth %A Meigs, James B %A Meitinger, Thomas %A Melander, Olle %A Mendoza-Caamal, Elvia %A Metcalf, Ginger A %A Mi, Xuenan %A Mohlke, Karen L %A Montasser, May E %A Moon, Jee-Young %A Moreno-Macias, Hortensia %A Morrison, Alanna C %A Muzny, Donna M %A Nelson, Sarah C %A Nilsson, Peter M %A O'Connell, Jeffrey R %A Orho-Melander, Marju %A Orozco, Lorena %A Palmer, Colin N A %A Palmer, Nicholette D %A Park, Cheol Joo %A Park, Kyong Soo %A Pedersen, Oluf %A Peralta, Juan M %A Peyser, Patricia A %A Post, Wendy S %A Preuss, Michael %A Psaty, Bruce M %A Qi, Qibin %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Samani, Nilesh %A Schunkert, Heribert %A Schurmann, Claudia %A Seo, Daekwan %A Seo, Jeong-Sun %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Stilp, Adrienne M %A Tai, E Shyong %A Tam, Claudia H T %A Taylor, Kent D %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tsai, Michael Y %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A van Dam, Rob M %A Vasan, Ramachandran S %A Viaud Martinez, Karine A %A Wang, Fei Fei %A Wang, Xuzhi %A Watkins, Hugh %A Weeks, Daniel E %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Yanek, Lisa R %A Kathiresan, Sekar %A Rader, Daniel J %A Rotter, Jerome I %A Boehnke, Michael %A McCarthy, Mark I %A Willer, Cristen J %A Natarajan, Pradeep %A Flannick, Jason A %A Khera, Amit V %A Peloso, Gina M %K Alleles %K Blood Glucose %K Case-Control Studies %K Computational Biology %K Databases, Genetic %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Predisposition to Disease %K Genetic Variation %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Lipid Metabolism %K Lipids %K Liver %K Molecular Sequence Annotation %K Multifactorial Inheritance %K Open Reading Frames %K Phenotype %K Polymorphism, Single Nucleotide %X

Large-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.

%B Am J Hum Genet %V 109 %P 81-96 %8 2022 01 06 %G eng %N 1 %R 10.1016/j.ajhg.2021.11.021 %0 Journal Article %J Nat Hum Behav %D 2022 %T Rare genetic variants explain missing heritability in smoking. %A Jang, Seon-Kyeong %A Evans, Luke %A Fialkowski, Allison %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Becker, Diane M %A Bis, Joshua C %A Blangero, John %A Bleecker, Eugene R %A Boorgula, Meher Preethi %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Jenkins, Brenda W Campbell %A Carson, April P %A Chavan, Sameer %A Cupples, L Adrienne %A Custer, Brian %A Damrauer, Scott M %A David, Sean P %A de Andrade, Mariza %A Dinardo, Carla L %A Fingerlin, Tasha E %A Fornage, Myriam %A Freedman, Barry I %A Garrett, Melanie E %A Gharib, Sina A %A Glahn, David C %A Haessler, Jeffrey %A Heckbert, Susan R %A Hokanson, John E %A Hou, Lifang %A Hwang, Shih-Jen %A Hyman, Matthew C %A Judy, Renae %A Justice, Anne E %A Kaplan, Robert C %A Kardia, Sharon L R %A Kelly, Shannon %A Kim, Wonji %A Kooperberg, Charles %A Levy, Daniel %A Lloyd-Jones, Donald M %A Loos, Ruth J F %A Manichaikul, Ani W %A Gladwin, Mark T %A Martin, Lisa Warsinger %A Nouraie, Mehdi %A Melander, Olle %A Meyers, Deborah A %A Montgomery, Courtney G %A North, Kari E %A Oelsner, Elizabeth C %A Palmer, Nicholette D %A Payton, Marinelle %A Peljto, Anna L %A Peyser, Patricia A %A Preuss, Michael %A Psaty, Bruce M %A Qiao, Dandi %A Rader, Daniel J %A Rafaels, Nicholas %A Redline, Susan %A Reed, Robert M %A Reiner, Alexander P %A Rich, Stephen S %A Rotter, Jerome I %A Schwartz, David A %A Shadyab, Aladdin H %A Silverman, Edwin K %A Smith, Nicholas L %A Smith, J Gustav %A Smith, Albert V %A Smith, Jennifer A %A Tang, Weihong %A Taylor, Kent D %A Telen, Marilyn J %A Vasan, Ramachandran S %A Gordeuk, Victor R %A Wang, Zhe %A Wiggins, Kerri L %A Yanek, Lisa R %A Yang, Ivana V %A Young, Kendra A %A Young, Kristin L %A Zhang, Yingze %A Liu, Dajiang J %A Keller, Matthew C %A Vrieze, Scott %X

Common 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.

%B Nat Hum Behav %8 2022 Aug 04 %G eng %R 10.1038/s41562-022-01408-5 %0 Journal Article %J Front Endocrinol (Lausanne) %D 2022 %T The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. %A Wang, Zhe %A Choi, Shing Wan %A Chami, Nathalie %A Boerwinkle, Eric %A Fornage, Myriam %A Redline, Susan %A Bis, Joshua C %A Brody, Jennifer A %A Psaty, Bruce M %A Kim, Wonji %A McDonald, Merry-Lynn N %A Regan, Elizabeth A %A Silverman, Edwin K %A Liu, Ching-Ti %A Vasan, Ramachandran S %A Kalyani, Rita R %A Mathias, Rasika A %A Yanek, Lisa R %A Arnett, Donna K %A Justice, Anne E %A North, Kari E %A Kaplan, Robert %A Heckbert, Susan R %A de Andrade, Mariza %A Guo, Xiuqing %A Lange, Leslie A %A Rich, Stephen S %A Rotter, Jerome I %A Ellinor, Patrick T %A Lubitz, Steven A %A Blangero, John %A Shoemaker, M Benjamin %A Darbar, Dawood %A Gladwin, Mark T %A Albert, Christine M %A Chasman, Daniel I %A Jackson, Rebecca D %A Kooperberg, Charles %A Reiner, Alexander P %A O'Reilly, Paul F %A Loos, Ruth J F %K Gene Frequency %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Obesity %K Whole Genome Sequencing %X

Polygenic 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.

%B Front Endocrinol (Lausanne) %V 13 %P 863893 %8 2022 %G eng %R 10.3389/fendo.2022.863893 %0 Journal Article %J Commun Biol %D 2022 %T Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. %A DiCorpo, Daniel %A Gaynor, Sheila M %A Russell, Emily M %A Westerman, Kenneth E %A Raffield, Laura M %A Majarian, Timothy D %A Wu, Peitao %A Sarnowski, Chloe %A Highland, Heather M %A Jackson, Anne %A Hasbani, Natalie R %A de Vries, Paul S %A Brody, Jennifer A %A Hidalgo, Bertha %A Guo, Xiuqing %A Perry, James A %A O'Connell, Jeffrey R %A Lent, Samantha %A Montasser, May E %A Cade, Brian E %A Jain, Deepti %A Wang, Heming %A D'Oliveira Albanus, Ricardo %A Varshney, Arushi %A Yanek, Lisa R %A Lange, Leslie %A Palmer, Nicholette D %A Almeida, Marcio %A Peralta, Juan M %A Aslibekyan, Stella %A Baldridge, Abigail S %A Bertoni, Alain G %A Bielak, Lawrence F %A Chen, Chung-Shiuan %A Chen, Yii-Der Ida %A Choi, Won Jung %A Goodarzi, Mark O %A Floyd, James S %A Irvin, Marguerite R %A Kalyani, Rita R %A Kelly, Tanika N %A Lee, Seonwook %A Liu, Ching-Ti %A Loesch, Douglas %A Manson, JoAnn E %A Minster, Ryan L %A Naseri, Take %A Pankow, James S %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Selvin, Elizabeth %A Smith, Jennifer A %A Weeks, Daniel E %A Xu, Huichun %A Yao, Jie %A Zhao, Wei %A Parker, Stephen %A Alonso, Alvaro %A Arnett, Donna K %A Blangero, John %A Boerwinkle, Eric %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Duggirala, Ravindranath %A He, Jiang %A Heckbert, Susan R %A Kardia, Sharon L R %A Kim, Ryan W %A Kooperberg, Charles %A Liu, Simin %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Morrison, Alanna C %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Shuldiner, Alan R %A Taylor, Kent D %A Vasan, Ramachandran S %A Viaud-Martinez, Karine A %A Florez, Jose C %A Wilson, James G %A Sladek, Robert %A Rich, Stephen S %A Rotter, Jerome I %A Lin, Xihong %A Dupuis, Josée %A Meigs, James B %A Wessel, Jennifer %A Manning, Alisa K %K Diabetes Mellitus, Type 2 %K Fasting %K Glucose %K Humans %K Insulin %K National Heart, Lung, and Blood Institute (U.S.) %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Precision Medicine %K Receptors, Immunologic %K United States %X

The 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.

%B Commun Biol %V 5 %P 756 %8 2022 07 28 %G eng %N 1 %R 10.1038/s42003-022-03702-4 %0 Journal Article %J Hum Mol Genet %D 2022 %T Whole-Exome Sequencing Study Identifies Four Novel Gene Loci Associated with Diabetic Kidney Disease. %A Pan, Yang %A Sun, Xiao %A Mi, Xuenan %A Huang, Zhijie %A Hsu, Yenchih %A Hixson, James E %A Munzy, Donna %A Metcalf, Ginger %A Franceschini, Nora %A Tin, Adrienne %A Köttgen, Anna %A Francis, Michael %A Brody, Jennifer A %A Kestenbaum, Bryan %A Sitlani, Colleen M %A Mychaleckyj, Josyf C %A Kramer, Holly %A Lange, Leslie A %A Guo, Xiuqing %A Hwang, Shih-Jen %A Irvin, Marguerite R %A Smith, Jennifer A %A Yanek, Lisa R %A Vaidya, Dhananjay %A Chen, Yii-Der Ida %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Hou, Lifang %A Mathias, Rasika A %A Mitchell, Braxton D %A Peyser, Patricia A %A Kardia, Sharon L R %A Arnett, Donna K %A Correa, Adolfo %A Raffield, Laura M %A Vasan, Ramachandran S %A Cupple, L Adrienne %A Levy, Daniel %A Kaplan, Robert C %A North, Kari E %A Rotter, Jerome I %A Kooperberg, Charles %A Reiner, Alexander P %A Psaty, Bruce M %A Tracy, Russell P %A Gibbs, Richard A %A Morrison, Alanna C %A Feldman, Harold %A Boerwinkle, Eric %A He, Jiang %A Kelly, Tanika N %X

Diabetic 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.

%B Hum Mol Genet %8 2022 Nov 29 %G eng %R 10.1093/hmg/ddac290 %0 Journal Article %J Nature %D 2023 %T Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis. %A Weinstock, Joshua S %A Gopakumar, Jayakrishnan %A Burugula, Bala Bharathi %A Uddin, Md Mesbah %A Jahn, Nikolaus %A Belk, Julia A %A Bouzid, Hind %A Daniel, Bence %A Miao, Zhuang %A Ly, Nghi %A Mack, Taralynn M %A Luna, Sofia E %A Prothro, Katherine P %A Mitchell, Shaneice R %A Laurie, Cecelia A %A Broome, Jai G %A Taylor, Kent D %A Guo, Xiuqing %A Sinner, Moritz F %A von Falkenhausen, Aenne S %A Kääb, Stefan %A Shuldiner, Alan R %A O'Connell, Jeffrey R %A Lewis, Joshua P %A Boerwinkle, Eric %A Barnes, Kathleen C %A Chami, Nathalie %A Kenny, Eimear E %A Loos, Ruth J F %A Fornage, Myriam %A Hou, Lifang %A Lloyd-Jones, Donald M %A Redline, Susan %A Cade, Brian E %A Psaty, Bruce M %A Bis, Joshua C %A Brody, Jennifer A %A Silverman, Edwin K %A Yun, Jeong H %A Qiao, Dandi %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Cho, Michael H %A DeMeo, Dawn L %A Vasan, Ramachandran S %A Yanek, Lisa R %A Becker, Lewis C %A Kardia, Sharon L R %A Peyser, Patricia A %A He, Jiang %A Rienstra, Michiel %A van der Harst, Pim %A Kaplan, Robert %A Heckbert, Susan R %A Smith, Nicholas L %A Wiggins, Kerri L %A Arnett, Donna K %A Irvin, Marguerite R %A Tiwari, Hemant %A Cutler, Michael J %A Knight, Stacey %A Muhlestein, J Brent %A Correa, Adolfo %A Raffield, Laura M %A Gao, Yan %A de Andrade, Mariza %A Rotter, Jerome I %A Rich, Stephen S %A Tracy, Russell P %A Konkle, Barbara A %A Johnsen, Jill M %A Wheeler, Marsha M %A Smith, J Gustav %A Melander, Olle %A Nilsson, Peter M %A Custer, Brian S %A Duggirala, Ravindranath %A Curran, Joanne E %A Blangero, John %A McGarvey, Stephen %A Williams, L Keoki %A Xiao, Shujie %A Yang, Mao %A Gu, C Charles %A Chen, Yii-Der Ida %A Lee, Wen-Jane %A Marcus, Gregory M %A Kane, John P %A Pullinger, Clive R %A Shoemaker, M Benjamin %A Darbar, Dawood %A Roden, Dan M %A Albert, Christine %A Kooperberg, Charles %A Zhou, Ying %A Manson, JoAnn E %A Desai, Pinkal %A Johnson, Andrew D %A Mathias, Rasika A %A Blackwell, Thomas W %A Abecasis, Goncalo R %A Smith, Albert V %A Kang, Hyun M %A Satpathy, Ansuman T %A Natarajan, Pradeep %A Kitzman, Jacob O %A Whitsel, Eric A %A Reiner, Alexander P %A Bick, Alexander G %A Jaiswal, Siddhartha %K Alleles %K Animals %K Clonal Hematopoiesis %K Genome-Wide Association Study %K Hematopoiesis %K Hematopoietic Stem Cells %K Humans %K Mice %K Mutation %K Promoter Regions, Genetic %X

Mutations 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.

%B Nature %V 616 %P 755-763 %8 2023 Apr %G eng %N 7958 %R 10.1038/s41586-023-05806-1 %0 Journal Article %J J Am Heart Assoc %D 2023 %T Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk. %A Liu, Xue %A Sun, Xianbang %A Zhang, Yuankai %A Jiang, Wenqing %A Lai, Meng %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Haessler, Jeffrey %A Zheng, Yinan %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Qian, Yong %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Boerwinkle, Eric %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Carson, April P %A Abecasis, Goncalo %A Dupuis, Josée %A Reiner, Alexander %A Kooperberg, Charles %A Hou, Lifang %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %X

Background 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.

%B J Am Heart Assoc %P e029090 %8 2023 Oct 07 %G eng %R 10.1161/JAHA.122.029090 %0 Journal Article %J medRxiv %D 2023 %T Carriers of rare damaging genetic variants are at lower risk of atherosclerotic disease. %A Georgakis, Marios K %A Malik, Rainer %A Hasbani, Natalie R %A Shakt, Gabrielle %A Morrison, Alanna C %A Tsao, Noah L %A Judy, Renae %A Mitchell, Braxton D %A Xu, Huichun %A Montasser, May E %A Do, Ron %A Kenny, Eimear E %A Loos, Ruth J F %A Terry, James G %A Carr, John Jeffrey %A Bis, Joshua C %A Psaty, Bruce M %A Longstreth, W T %A Young, Kendra A %A Lutz, Sharon M %A Cho, Michael H %A Broome, Jai %A Khan, Alyna T %A Wang, Fei Fei %A Heard-Costa, Nancy %A Seshadri, Sudha %A Vasan, Ramachandran S %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Yanek, Lisa R %A Kral, Brian G %A Becker, Lewis C %A Peyser, Patricia A %A Bielak, Lawrence F %A Ammous, Farah %A Carson, April P %A Hall, Michael E %A Raffield, Laura M %A Rich, Stephen S %A Post, Wendy S %A Tracy, Russel P %A Taylor, Kent D %A Guo, Xiuqing %A Mahaney, Michael C %A Curran, Joanne E %A Blangero, John %A Clarke, Shoa L %A Haessler, Jeffrey W %A Hu, Yao %A Assimes, Themistocles L %A Kooperberg, Charles %A Damrauer, Scott M %A Rotter, Jerome I %A de Vries, Paul S %A Dichgans, Martin %X

BACKGROUND: 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.

%B medRxiv %8 2023 Aug 16 %G eng %R 10.1101/2023.08.14.23294063 %0 Journal Article %J Diabetes Care %D 2023 %T Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk. %A Tobias, Deirdre K %A Manning, Alisa K %A Wessel, Jennifer %A Raghavan, Sridharan %A Westerman, Kenneth E %A Bick, Alexander G %A DiCorpo, Daniel %A Whitsel, Eric A %A Collins, Jason %A Correa, Adolfo %A Cupples, L Adrienne %A Dupuis, Josée %A Goodarzi, Mark O %A Guo, Xiuqing %A Howard, Barbara %A Lange, Leslie A %A Liu, Simin %A Raffield, Laura M %A Reiner, Alex P %A Rich, Stephen S %A Taylor, Kent D %A Tinker, Lesley %A Wilson, James G %A Wu, Peitao %A Carson, April P %A Vasan, Ramachandran S %A Fornage, Myriam %A Psaty, Bruce M %A Kooperberg, Charles %A Rotter, Jerome I %A Meigs, James %A Manson, JoAnn E %X

OBJECTIVE: 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.

%B Diabetes Care %8 2023 Sep 27 %G eng %R 10.2337/dc23-0805 %0 Journal Article %J Nat Commun %D 2023 %T Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. %A Kurniansyah, Nuzulul %A Goodman, Matthew O %A Khan, Alyna T %A Wang, Jiongming %A Feofanova, Elena %A Bis, Joshua C %A Wiggins, Kerri L %A Huffman, Jennifer E %A Kelly, Tanika %A Elfassy, Tali %A Guo, Xiuqing %A Palmas, Walter %A Lin, Henry J %A Hwang, Shih-Jen %A Gao, Yan %A Young, Kendra %A Kinney, Gregory L %A Smith, Jennifer A %A Yu, Bing %A Liu, Simin %A Wassertheil-Smoller, Sylvia %A Manson, JoAnn E %A Zhu, Xiaofeng %A Chen, Yii-Der Ida %A Lee, I-Te %A Gu, C Charles %A Lloyd-Jones, Donald M %A Zöllner, Sebastian %A Fornage, Myriam %A Kooperberg, Charles %A Correa, Adolfo %A Psaty, Bruce M %A Arnett, Donna K %A Isasi, Carmen R %A Rich, Stephen S %A Kaplan, Robert C %A Redline, Susan %A Mitchell, Braxton D %A Franceschini, Nora %A Levy, Daniel %A Rotter, Jerome I %A Morrison, Alanna C %A Sofer, Tamar %K Blood Pressure %K Ethnicity %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Male %K Multifactorial Inheritance %K Population Health %K Risk Factors %X

We 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.

%B Nat Commun %V 14 %P 3202 %8 2023 Jun 02 %G eng %N 1 %R 10.1038/s41467-023-38990-9 %0 Journal Article %J Nat Commun %D 2023 %T Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease. %A Young, William J %A Haessler, Jeffrey %A Benjamins, Jan-Walter %A Repetto, Linda %A Yao, Jie %A Isaacs, Aaron %A Harper, Andrew R %A Ramirez, Julia %A Garnier, Sophie %A Van Duijvenboden, Stefan %A Baldassari, Antoine R %A Concas, Maria Pina %A Duong, ThuyVy %A Foco, Luisa %A Isaksen, Jonas L %A Mei, Hao %A Noordam, Raymond %A Nursyifa, Casia %A Richmond, Anne %A Santolalla, Meddly L %A Sitlani, Colleen M %A Soroush, Negin %A Thériault, Sébastien %A Trompet, Stella %A Aeschbacher, Stefanie %A Ahmadizar, Fariba %A Alonso, Alvaro %A Brody, Jennifer A %A Campbell, Archie %A Correa, Adolfo %A Darbar, Dawood %A De Luca, Antonio %A Deleuze, Jean-Francois %A Ellervik, Christina %A Fuchsberger, Christian %A Goel, Anuj %A Grace, Christopher %A Guo, Xiuqing %A Hansen, Torben %A Heckbert, Susan R %A Jackson, Rebecca D %A Kors, Jan A %A Lima-Costa, Maria Fernanda %A Linneberg, Allan %A Macfarlane, Peter W %A Morrison, Alanna C %A Navarro, Pau %A Porteous, David J %A Pramstaller, Peter P %A Reiner, Alexander P %A Risch, Lorenz %A Schotten, Ulrich %A Shen, Xia %A Sinagra, Gianfranco %A Soliman, Elsayed Z %A Stoll, Monika %A Tarazona-Santos, Eduardo %A Tinker, Andrew %A Trajanoska, Katerina %A Villard, Eric %A Warren, Helen R %A Whitsel, Eric A %A Wiggins, Kerri L %A Arking, Dan E %A Avery, Christy L %A Conen, David %A Girotto, Giorgia %A Grarup, Niels %A Hayward, Caroline %A Jukema, J Wouter %A Mook-Kanamori, Dennis O %A Olesen, Morten Salling %A Padmanabhan, Sandosh %A Psaty, Bruce M %A Pattaro, Cristian %A Ribeiro, Antonio Luiz P %A Rotter, Jerome I %A Stricker, Bruno H %A van der Harst, Pim %A van Duijn, Cornelia M %A Verweij, Niek %A Wilson, James G %A Orini, Michele %A Charron, Philippe %A Watkins, Hugh %A Kooperberg, Charles %A Lin, Henry J %A Wilson, James F %A Kanters, Jørgen K %A Sotoodehnia, Nona %A Mifsud, Borbala %A Lambiase, Pier D %A Tereshchenko, Larisa G %A Munroe, Patricia B %K Arrhythmias, Cardiac %K Atrioventricular Block %K Biomarkers %K Cardiovascular Diseases %K Electrocardiography %K Genome-Wide Association Study %K Humans %K Risk Factors %X

The 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.

%B Nat Commun %V 14 %P 1411 %8 2023 Mar 14 %G eng %N 1 %R 10.1038/s41467-023-36997-w %0 Journal Article %J bioRxiv %D 2023 %T Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants. %A Einson, Jonah %A Glinos, Dafni %A Boerwinkle, Eric %A Castaldi, Peter %A Darbar, Dawood %A de Andrade, Mariza %A Ellinor, Patrick %A Fornage, Myriam %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard %A Hersh, Craig P %A Johnsen, Jill %A Kaplan, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Nassir, Rami %A Loos, Ruth J F %A Meyers, Deborah A %A Mitchell, Braxton D %A Psaty, Bruce %A Vasan, Ramachandran S %A Rich, Stephen S %A Rienstra, Michael %A Rotter, Jerome I %A Saferali, Aabida %A Shoemaker, M Benjamin %A Silverman, Edwin %A Smith, Albert Vernon %A Mohammadi, Pejman %A Castel, Stephane E %A Iossifov, Ivan %A Lappalainen, Tuuli %X

Exonic 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.

%B bioRxiv %8 2023 Jan 31 %G eng %R 10.1101/2023.01.31.526505 %0 Journal Article %J Sci Adv %D 2023 %T The genetic determinants of recurrent somatic mutations in 43,693 blood genomes. %A Weinstock, Joshua S %A Laurie, Cecelia A %A Broome, Jai G %A Taylor, Kent D %A Guo, Xiuqing %A Shuldiner, Alan R %A O'Connell, Jeffrey R %A Lewis, Joshua P %A Boerwinkle, Eric %A Barnes, Kathleen C %A Chami, Nathalie %A Kenny, Eimear E %A Loos, Ruth J F %A Fornage, Myriam %A Redline, Susan %A Cade, Brian E %A Gilliland, Frank D %A Chen, Zhanghua %A Gauderman, W James %A Kumar, Rajesh %A Grammer, Leslie %A Schleimer, Robert P %A Psaty, Bruce M %A Bis, Joshua C %A Brody, Jennifer A %A Silverman, Edwin K %A Yun, Jeong H %A Qiao, Dandi %A Weiss, Scott T %A Lasky-Su, Jessica %A DeMeo, Dawn L %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Cho, Michael H %A Vasan, Ramachandran S %A Johnson, Andrew D %A Yanek, Lisa R %A Becker, Lewis C %A Kardia, Sharon %A He, Jiang %A Kaplan, Robert %A Heckbert, Susan R %A Smith, Nicholas L %A Wiggins, Kerri L %A Arnett, Donna K %A Irvin, Marguerite R %A Tiwari, Hemant %A Correa, Adolfo %A Raffield, Laura M %A Gao, Yan %A de Andrade, Mariza %A Rotter, Jerome I %A Rich, Stephen S %A Manichaikul, Ani W %A Konkle, Barbara A %A Johnsen, Jill M %A Wheeler, Marsha M %A Custer, Brian S %A Duggirala, Ravindranath %A Curran, Joanne E %A Blangero, John %A Gui, Hongsheng %A Xiao, Shujie %A Williams, L Keoki %A Meyers, Deborah A %A Li, Xingnan %A Ortega, Victor %A McGarvey, Stephen %A Gu, C Charles %A Chen, Yii-Der Ida %A Lee, Wen-Jane %A Shoemaker, M Benjamin %A Darbar, Dawood %A Roden, Dan %A Albert, Christine %A Kooperberg, Charles %A Desai, Pinkal %A Blackwell, Thomas W %A Abecasis, Goncalo R %A Smith, Albert V %A Kang, Hyun M %A Mathias, Rasika %A Natarajan, Pradeep %A Jaiswal, Siddhartha %A Reiner, Alexander P %A Bick, Alexander G %K Germ-Line Mutation %K Hematopoiesis %K Humans %K Middle Aged %K Mutation %K Mutation, Missense %K Phenotype %X

Nononcogenic 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.

%B Sci Adv %V 9 %P eabm4945 %8 2023 Apr 28 %G eng %N 17 %R 10.1126/sciadv.abm4945 %0 Journal Article %J medRxiv %D 2023 %T Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure. %A Guirette, Melanie %A Lan, Jessie %A McKeown, Nicola %A Brown, Michael R %A Chen, Han %A de Vries, Paul S %A Kim, Hyunju %A Rebholz, Casey M %A Morrison, Alanna C %A Bartz, Traci M %A Fretts, Amanda M %A Guo, Xiuqing %A Lemaitre, Rozenn N %A Liu, Ching-Ti %A Noordam, Raymond %A de Mutsert, Renée %A Rosendaal, Frits R %A Wang, Carol A %A Beilin, Lawrence %A Mori, Trevor A %A Oddy, Wendy H %A Pennell, Craig E %A Chai, Jin Fang %A Whitton, Clare %A van Dam, Rob M %A Liu, Jianjun %A Tai, E Shyong %A Sim, Xueling %A Neuhouser, Marian L %A Kooperberg, Charles %A Tinker, Lesley %A Franceschini, Nora %A Huan, Tianxiao %A Winkler, Thomas W %A Bentley, Amy R %A Gauderman, W James %A Heerkens, Luc %A Tanaka, Toshiko %A van Rooij, Jeroen %A Munroe, Patricia B %A Warren, Helen R %A Voortman, Trudy %A Chen, Honglei %A Rao, D C %A Levy, Daniel %A Ma, Jiantao %X

OBJECTIVE: 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.

%B medRxiv %8 2023 Nov 11 %G eng %R 10.1101/2023.11.10.23298402 %0 Journal Article %J medRxiv %D 2023 %T Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores. %A Hrytsenko, Yana %A Shea, Benjamin %A Elgart, Michael %A Kurniansyah, Nuzulul %A Lyons, Genevieve %A Morrison, Alanna C %A Carson, April P %A Haring, Bernhard %A Mitchel, Braxton D %A Psaty, Bruce M %A Jaeger, Byron C %A Gu, C Charles %A Kooperberg, Charles %A Levy, Daniel %A Lloyd-Jones, Donald %A Choi, Eunhee %A Brody, Jennifer A %A Smith, Jennifer A %A Rotter, Jerome I %A Moll, Matthew %A Fornage, Myriam %A Simon, Noah %A Castaldi, Peter %A Casanova, Ramon %A Chung, Ren-Hua %A Kaplan, Robert %A Loos, Ruth J F %A Kardia, Sharon L R %A Rich, Stephen S %A Redline, Susan %A Kelly, Tanika %A O'Connor, Timothy %A Zhao, Wei %A Kim, Wonji %A Guo, Xiuqing %A Der Ida Chen, Yii %A Sofer, Tamar %X

We 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.

%B medRxiv %8 2023 Dec 14 %G eng %R 10.1101/2023.12.13.23299909 %0 Journal Article %J medRxiv %D 2023 %T Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. %A Suzuki, Ken %A Hatzikotoulas, Konstantinos %A Southam, Lorraine %A Taylor, Henry J %A Yin, Xianyong %A Lorenz, Kim M %A Mandla, Ravi %A Huerta-Chagoya, Alicia %A Rayner, Nigel W %A Bocher, Ozvan %A Ana Luiza de, S V Arruda %A Sonehara, Kyuto %A Namba, Shinichi %A Lee, Simon S K %A Preuss, Michael H %A Petty, Lauren E %A Schroeder, Philip %A Vanderwerff, Brett %A Kals, Mart %A Bragg, Fiona %A Lin, Kuang %A Guo, Xiuqing %A Zhang, Weihua %A Yao, Jie %A Kim, Young Jin %A Graff, Mariaelisa %A Takeuchi, Fumihiko %A Nano, Jana %A Lamri, Amel %A Nakatochi, Masahiro %A Moon, Sanghoon %A Scott, Robert A %A Cook, James P %A Lee, Jung-Jin %A Pan, Ian %A Taliun, Daniel %A Parra, Esteban J %A Chai, Jin-Fang %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Thorleifsson, Gudmar %A Grarup, Niels %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Kwak, Soo-Heon %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Nongmaithem, Suraj S %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Brody, Jennifer A %A Kabagambe, Edmond %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Alaine Broadaway, K %A Williamson, Alice %A Kamali, Zoha %A Cui, Jinrui %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Ahluwalia, Tarunveer S %A Anand, Sonia S %A Bertoni, Alain %A Bork-Jensen, Jette %A Brandslund, Ivan %A Buchanan, Thomas A %A Burant, Charles F %A Butterworth, Adam S %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Danesh, John %A Das, Swapan K %A Janaka de Silva, H %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Gordon-Larsen, Penny %A Gross, Myron %A Guare, Lindsay A %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Horikoshi, Momoko %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Torben %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Kyung Min %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Lithgart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lynch, Julie A %A Lyssenko, Valeriya %A Maeda, Shiro %A Mamakou, Vasiliki %A Mansuri, Sohail Rafik %A Matsuda, Koichi %A Meitinger, Thomas %A Metspalu, Andres %A Mo, Huan %A Morris, Andrew D %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Patil, Snehal %A Pei, Pei %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Polikowsky, Hannah G %A Porneala, Bianca %A Prasad, Gauri %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Katheryn %A Sabanayagam, Charumathi %A Sandow, Kevin %A Sankareswaran, Alagu %A Sattar, Naveed %A Schönherr, Sebastian %A Shahriar, Mohammad %A Shen, Botong %A Shi, Jinxiu %A Shin, Dong Mun %A Shojima, Nobuhiro %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Steinthorsdottir, Valgerdur %A Stilp, Adrienne M %A Strauch, Konstantin %A Taylor, Kent D %A Thorand, Barbara %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Tran, Tam C %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamamoto, Kenichi %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zawistowski, Matthew %A Zhang, Liang %A Zheng, Wei %A Project, Biobank Japan %A BioBank, Penn Medicine %A Center, Regeneron Genetics %A Consortium, eMERGE %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Fornage, Myriam %A Hanis, Craig L %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Yokota, Mitsuhiro %A Kardia, Sharon L R %A Peyser, Patricia A %A Pankow, James S %A Engert, James C %A Bonnefond, Amélie %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Wu, Jer-Yuarn %A Geoffrey Hayes, M %A Ma, Ronald C W %A Wong, Tien-Yin %A Mook-Kanamori, Dennis O %A Tuomi, Tiinamaija %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A Chen, Yii-Der Ida %A Rich, Stephen S %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Ghanbari, Mohsen %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Bowden, Donald W %A Palmer, Colin N A %A Kooner, Jaspal S %A Kooperberg, Charles %A Liu, Simin %A North, Kari E %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Wareham, Nicholas J %A Lee, Juyoung %A Kim, Bong-Jo %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Goodarzi, Mark O %A Mohlke, Karen L %A Langenberg, Claudia %A Haiman, Christopher A %A Loos, Ruth J F %A Florez, Jose C %A Rader, Daniel J %A Ritchie, Marylyn D %A Zöllner, Sebastian %A Mägi, Reedik %A Denny, Joshua C %A Yamauchi, Toshimasa %A Kadowaki, Takashi %A Chambers, John C %A Ng, Maggie C Y %A Sim, Xueling %A Below, Jennifer E %A Tsao, Philip S %A Chang, Kyong-Mi %A McCarthy, Mark I %A Meigs, James B %A Mahajan, Anubha %A Spracklen, Cassandra N %A Mercader, Josep M %A Boehnke, Michael %A Rotter, Jerome I %A Vujkovic, Marijana %A Voight, Benjamin F %A Morris, Andrew P %A Zeggini, Eleftheria %X

Type 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.

%B medRxiv %8 2023 Mar 31 %G eng %R 10.1101/2023.03.31.23287839 %0 Journal Article %J Nat Genet %D 2023 %T Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. %A Chen, Fang %A Wang, Xingyan %A Jang, Seon-Kyeong %A Quach, Bryan C %A Weissenkampen, J Dylan %A Khunsriraksakul, Chachrit %A Yang, Lina %A Sauteraud, Renan %A Albert, Christine M %A Allred, Nicholette D D %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Barr, R Graham %A Becker, Diane M %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boorgula, Meher Preethi %A Chasman, Daniel I %A Chavan, Sameer %A Chen, Yii-der I %A Chuang, Lee-Ming %A Correa, Adolfo %A Curran, Joanne E %A David, Sean P %A Fuentes, Lisa de Las %A Deka, Ranjan %A Duggirala, Ravindranath %A Faul, Jessica D %A Garrett, Melanie E %A Gharib, Sina A %A Guo, Xiuqing %A Hall, Michael E %A Hawley, Nicola L %A He, Jiang %A Hobbs, Brian D %A Hokanson, John E %A Hsiung, Chao A %A Hwang, Shih-Jen %A Hyde, Thomas M %A Irvin, Marguerite R %A Jaffe, Andrew E %A Johnson, Eric O %A Kaplan, Robert %A Kardia, Sharon L R %A Kaufman, Joel D %A Kelly, Tanika N %A Kleinman, Joel E %A Kooperberg, Charles %A Lee, I-Te %A Levy, Daniel %A Lutz, Sharon M %A Manichaikul, Ani W %A Martin, Lisa W %A Marx, Olivia %A McGarvey, Stephen T %A Minster, Ryan L %A Moll, Matthew %A Moussa, Karine A %A Naseri, Take %A North, Kari E %A Oelsner, Elizabeth C %A Peralta, Juan M %A Peyser, Patricia A %A Psaty, Bruce M %A Rafaels, Nicholas %A Raffield, Laura M %A Reupena, Muagututi'a Sefuiva %A Rich, Stephen S %A Rotter, Jerome I %A Schwartz, David A %A Shadyab, Aladdin H %A Sheu, Wayne H-H %A Sims, Mario %A Smith, Jennifer A %A Sun, Xiao %A Taylor, Kent D %A Telen, Marilyn J %A Watson, Harold %A Weeks, Daniel E %A Weir, David R %A Yanek, Lisa R %A Young, Kendra A %A Young, Kristin L %A Zhao, Wei %A Hancock, Dana B %A Jiang, Bibo %A Vrieze, Scott %A Liu, Dajiang J %K Biology %K Drug Repositioning %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Tobacco Use %K Transcriptome %X

Most 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.

%B Nat Genet %V 55 %P 291-300 %8 2023 Feb %G eng %N 2 %R 10.1038/s41588-022-01282-x %0 Journal Article %J Nat Genet %D 2023 %T Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. %A Li, Xihao %A Quick, Corbin %A Zhou, Hufeng %A Gaynor, Sheila M %A Liu, Yaowu %A Chen, Han %A Selvaraj, Margaret Sunitha %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A de Vries, Paul S %A Duggirala, Ravindranath %A Freedman, Barry I %A Göring, Harald H H %A Guo, Xiuqing %A Haessler, Jeffrey %A Kalyani, Rita R %A Kooperberg, Charles %A Kral, Brian G %A Lange, Leslie A %A Manichaikul, Ani %A Martin, Lisa W %A McGarvey, Stephen T %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Rich, Stephen S %A Sitlani, Colleen M %A Smith, Jennifer A %A Taylor, Kent D %A Vasan, Ramachandran S %A Willer, Cristen J %A Wilson, James G %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Natarajan, Pradeep %A Peloso, Gina M %A Li, Zilin %A Lin, Xihong %K Exome Sequencing %K Genome-Wide Association Study %K Lipids %K Phenotype %K Whole Genome Sequencing %X

Meta-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.

%B Nat Genet %V 55 %P 154-164 %8 2023 Jan %G eng %N 1 %R 10.1038/s41588-022-01225-6 %0 Journal Article %J medRxiv %D 2023 %T Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. %A Wang, Yuxuan %A Selvaraj, Margaret Sunitha %A Li, Xihao %A Li, Zilin %A Holdcraft, Jacob A %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Cade, Brian E %A Carlson, Jenna C %A Carson, April P %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Dutcher, Susan K %A Ellinor, Patrick T %A Floyd, James S %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard A %A Guo, Xiuqing %A He, Jiang %A Heard-Costa, Nancy %A Hildalgo, Bertha %A Hou, Lifang %A Irvin, Marguerite R %A Joehanes, Roby %A Kaplan, Robert C %A Kardia, Sharon Lr %A Kelly, Tanika N %A Kim, Ryan %A Kooperberg, Charles %A Kral, Brian G %A Levy, Daniel %A Li, Changwei %A Liu, Chunyu %A Lloyd-Jone, Don %A Loos, Ruth Jf %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Murabito, Joanne M %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Preuss, Michael H %A Psaty, Bruce M %A Raffield, Laura M %A Rao, Dabeeru C %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Ruepena, Muagututi'a Sefuiva %A Sheu, Wayne H-H %A Smith, Jennifer A %A Smith, Albert %A Tiwari, Hemant K %A Tsai, Michael Y %A Viaud-Martinez, Karine A %A Wang, Zhe %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Lin, Xihong %A Natarajan, Pradeep %A Peloso, Gina M %X

Long 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.

%B medRxiv %8 2023 Jun 29 %G eng %R 10.1101/2023.06.28.23291966 %0 Journal Article %J bioRxiv %D 2023 %T A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. %A Li, Xihao %A Chen, Han %A Selvaraj, Margaret Sunitha %A Van Buren, Eric %A Zhou, Hufeng %A Wang, Yuxuan %A Sun, Ryan %A McCaw, Zachary R %A Yu, Zhi %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Carson, April P %A Carlson, Jenna C %A Chami, Nathalie %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Fornage, Myriam %A Franceschini, Nora %A Freedman, Barry I %A Gu, Charles %A Heard-Costa, Nancy L %A He, Jiang %A Hou, Lifang %A Hung, Yi-Jen %A Irvin, Marguerite R %A Kaplan, Robert C %A Kardia, Sharon L R %A Kelly, Tanika %A Konigsberg, Iain %A Kooperberg, Charles %A Kral, Brian G %A Li, Changwei %A Loos, Ruth J F %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Sitlani, Colleen M %A Smith, Jennifer A %A Taylor, Kent D %A Tiwari, Hemant %A Vasan, Ramachandran S %A Wang, Zhe %A Yanek, Lisa R %A Yu, Bing %A Rice, Kenneth M %A Rotter, Jerome I %A Peloso, Gina M %A Natarajan, Pradeep %A Li, Zilin %A Liu, Zhonghua %A Lin, Xihong %X

Large-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.

%B bioRxiv %8 2023 Nov 02 %G eng %R 10.1101/2023.10.30.564764 %0 Journal Article %J medRxiv %D 2023 %T Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus. %A Kwak, Soo Heon %A Hernandez-Cancela, Ryan B %A DiCorpo, Daniel A %A Condon, David E %A Merino, Jordi %A Wu, Peitao %A Brody, Jennifer A %A Yao, Jie %A Guo, Xiuqing %A Ahmadizar, Fariba %A Meyer, Mariah %A Sincan, Murat %A Mercader, Josep M %A Lee, Sujin %A Haessler, Jeffrey %A Vy, Ha My T %A Lin, Zhaotong %A Armstrong, Nicole D %A Gu, Shaopeng %A Tsao, Noah L %A Lange, Leslie A %A Wang, Ningyuan %A Wiggins, Kerri L %A Trompet, Stella %A Liu, Simin %A Loos, Ruth J F %A Judy, Renae %A Schroeder, Philip H %A Hasbani, Natalie R %A Bos, Maxime M %A Morrison, Alanna C %A Jackson, Rebecca D %A Reiner, Alexander P %A Manson, JoAnn E %A Chaudhary, Ninad S %A Carmichael, Lynn K %A Chen, Yii-Der Ida %A Taylor, Kent D %A Ghanbari, Mohsen %A van Meurs, Joyce %A Pitsillides, Achilleas N %A Psaty, Bruce M %A Noordam, Raymond %A Do, Ron %A Park, Kyong Soo %A Jukema, J Wouter %A Kavousi, Maryam %A Correa, Adolfo %A Rich, Stephen S %A Damrauer, Scott M %A Hajek, Catherine %A Cho, Nam H %A Irvin, Marguerite R %A Pankow, James S %A Nadkarni, Girish N %A Sladek, Robert %A Goodarzi, Mark O %A Florez, Jose C %A Chasman, Daniel I %A Heckbert, Susan R %A Kooperberg, Charles %A Dupuis, Josée %A Malhotra, Rajeev %A de Vries, Paul S %A Liu, Ching-Ti %A Rotter, Jerome I %A Meigs, James B %X

BACKGROUND: 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.

%B medRxiv %8 2023 Jul 28 %G eng %R 10.1101/2023.07.25.23293180 %0 Journal Article %J J Endocr Soc %D 2023 %T A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies. %A Srinivasan, Shylaja %A Wu, Peitao %A Mercader, Josep M %A Udler, Miriam S %A Porneala, Bianca C %A Bartz, Traci M %A Floyd, James S %A Sitlani, Colleen %A Guo, Xiquing %A Haessler, Jeffrey %A Kooperberg, Charles %A Liu, Jun %A Ahmad, Shahzad %A van Duijn, Cornelia %A Liu, Ching-Ti %A Goodarzi, Mark O %A Florez, Jose C %A Meigs, James B %A Rotter, Jerome I %A Rich, Stephen S %A Dupuis, Josée %A Leong, Aaron %X

CONTEXT: 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.

%B J Endocr Soc %V 7 %P bvad123 %8 2023 Oct 09 %G eng %N 11 %R 10.1210/jendso/bvad123 %0 Journal Article %J medRxiv %D 2023 %T Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles. %A Huffman, Jennifer E %A Nicolas, Jayna %A Hahn, Julie %A Heath, Adam S %A Raffield, Laura M %A Yanek, Lisa R %A Brody, Jennifer A %A Thibord, Florian %A Almasy, Laura %A Bartz, Traci M %A Bielak, Lawrence F %A Bowler, Russell P %A Carrasquilla, Germán D %A Chasman, Daniel I %A Chen, Ming-Huei %A Emmert, David B %A Ghanbari, Mohsen %A Haessle, Jeffery %A Hottenga, Jouke-Jan %A Kleber, Marcus E %A Le, Ngoc-Quynh %A Lee, Jiwon %A Lewis, Joshua P %A Li-Gao, Ruifang %A Luan, Jian'an %A Malmberg, Anni %A Mangino, Massimo %A Marioni, Riccardo E %A Martinez-Perez, Angel %A Pankratz, Nathan %A Polasek, Ozren %A Richmond, Anne %A Rodriguez, Benjamin At %A Rotter, Jerome I %A Steri, Maristella %A Suchon, Pierre %A Trompet, Stella %A Weiss, Stefan %A Zare, Marjan %A Auer, Paul %A Cho, Michael H %A Christofidou, Paraskevi %A Davies, Gail %A de Geus, Eco %A Deleuze, Jean-Francois %A Delgado, Graciela E %A Ekunwe, Lynette %A Faraday, Nauder %A Gögele, Martin %A Greinacher, Andreas %A He, Gao %A Howard, Tom %A Joshi, Peter K %A Kilpeläinen, Tuomas O %A Lahti, Jari %A Linneberg, Allan %A Naitza, Silvia %A Noordam, Raymond %A Paüls-Vergés, Ferran %A Rich, Stephen S %A Rosendaal, Frits R %A Rudan, Igor %A Ryan, Kathleen A %A Souto, Juan Carlos %A van Rooij, Frank Ja %A Wang, Heming %A Zhao, Wei %A Becker, Lewis C %A Beswick, Andrew %A Brown, Michael R %A Cade, Brian E %A Campbell, Harry %A Cho, Kelly %A Crapo, James D %A Curran, Joanne E %A de Maat, Moniek Pm %A Doyle, Margaret %A Elliott, Paul %A Floyd, James S %A Fuchsberger, Christian %A Grarup, Niels %A Guo, Xiuqing %A Harris, Sarah E %A Hou, Lifang %A Kolcic, Ivana %A Kooperberg, Charles %A Menni, Cristina %A Nauck, Matthias %A O'Connell, Jeffrey R %A Orrù, Valeria %A Psaty, Bruce M %A Räikkönen, Katri %A Smith, Jennifer A %A Soria, José Manuel %A Stott, David J %A van Hylckama Vlieg, Astrid %A Watkins, Hugh %A Willemsen, Gonneke %A Wilson, Peter %A Ben-Shlomo, Yoav %A Blangero, John %A Boomsma, Dorret %A Cox, Simon R %A Dehghan, Abbas %A Eriksson, Johan G %A Fiorillo, Edoardo %A Fornage, Myriam %A Hansen, Torben %A Hayward, Caroline %A Ikram, M Arfan %A Jukema, J Wouter %A Kardia, Sharon Lr %A Lange, Leslie A %A März, Winfried %A Mathias, Rasika A %A Mitchell, Braxton D %A Mook-Kanamori, Dennis O %A Morange, Pierre-Emmanuel %A Pedersen, Oluf %A Pramstaller, Peter P %A Redline, Susan %A Reiner, Alexander %A Ridker, Paul M %A Silverman, Edwin K %A Spector, Tim D %A Völker, Uwe %A Wareham, Nick %A Wilson, James F %A Yao, Jie %A Trégouët, David-Alexandre %A Johnson, Andrew D %A Wolberg, Alisa S %A de Vries, Paul S %A Sabater-Lleal, Maria %A Morrison, Alanna C %A Smith, Nicholas L %X

UNLABELLED: 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.

%B medRxiv %8 2023 Jun 12 %G eng %R 10.1101/2023.06.07.23291095 %0 Journal Article %J Circ Genom Precis Med %D 2023 %T Whole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program. %A Seyerle, Amanda A %A Laurie, Cecelia A %A Coombes, Brandon J %A Jain, Deepti %A Conomos, Matthew P %A Brody, Jennifer %A Chen, Ming-Huei %A Gogarten, Stephanie M %A Beutel, Kathleen M %A Gupta, Namrata %A Heckbert, Susan R %A Jackson, Rebecca D %A Johnson, Andrew D %A Ko, Darae %A Manson, JoAnn E %A McKnight, Barbara %A Metcalf, Ginger A %A Morrison, Alanna C %A Reiner, Alexander P %A Sofer, Tamar %A Tang, Weihong %A Wiggins, Kerri L %A Boerwinkle, Eric %A Andrade, Mariza de %A Gabriel, Stacey B %A Gibbs, Richard A %A Laurie, Cathy C %A Psaty, Bruce M %A Vasan, Ramachandran S %A Rice, Ken %A Kooperberg, Charles %A Pankow, James S %A Smith, Nicholas L %A Pankratz, Nathan %X

Background 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.

%B Circ Genom Precis Med %P e003532 %8 2023 Mar 24 %G eng %R 10.1161/CIRCGEN.121.003532 %0 Journal Article %J Front Genet %D 2023 %T Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program. %A Armstrong, Nicole D %A Srinivasasainagendra, Vinodh %A Ammous, Farah %A Assimes, Themistocles L %A Beitelshees, Amber L %A Brody, Jennifer %A Cade, Brian E %A Ida Chen, Yii-Der %A Chen, Han %A de Vries, Paul S %A Floyd, James S %A Franceschini, Nora %A Guo, Xiuqing %A Hellwege, Jacklyn N %A House, John S %A Hwu, Chii-Min %A Kardia, Sharon L R %A Lange, Ethan M %A Lange, Leslie A %A McDonough, Caitrin W %A Montasser, May E %A O'Connell, Jeffrey R %A Shuey, Megan M %A Sun, Xiao %A Tanner, Rikki M %A Wang, Zhe %A Zhao, Wei %A Carson, April P %A Edwards, Todd L %A Kelly, Tanika N %A Kenny, Eimear E %A Kooperberg, Charles %A Loos, Ruth J F %A Morrison, Alanna C %A Motsinger-Reif, Alison %A Psaty, Bruce M %A Rao, Dabeeru C %A Redline, Susan %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Jennifer A %A Smith, Albert V %A Irvin, Marguerite R %A Arnett, Donna K %X

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.

%B Front Genet %V 14 %P 1278215 %8 2023 %G eng %R 10.3389/fgene.2023.1278215 %0 Journal Article %J medRxiv %D 2023 %T WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE. %A Zhang, Xinruo %A Brody, Jennifer A %A Graff, Mariaelisa %A Highland, Heather M %A Chami, Nathalie %A Xu, Hanfei %A Wang, Zhe %A Ferrier, Kendra %A Chittoor, Geetha %A Josyula, Navya S %A Li, Xihao %A Li, Zilin %A Allison, Matthew A %A Becker, Diane M %A Bielak, Lawrence F %A Bis, Joshua C %A Boorgula, Meher Preethi %A Bowden, Donald W %A Broome, Jai G %A Buth, Erin J %A Carlson, Christopher S %A Chang, Kyong-Mi %A Chavan, Sameer %A Chiu, Yen-Feng %A Chuang, Lee-Ming %A Conomos, Matthew P %A DeMeo, Dawn L %A Du, Margaret %A Duggirala, Ravindranath %A Eng, Celeste %A Fohner, Alison E %A Freedman, Barry I %A Garrett, Melanie E %A Guo, Xiuqing %A Haiman, Chris %A Heavner, Benjamin D %A Hidalgo, Bertha %A Hixson, James E %A Ho, Yuk-Lam %A Hobbs, Brian D %A Hu, Donglei %A Hui, Qin %A Hwu, Chii-Min %A Jackson, Rebecca D %A Jain, Deepti %A Kalyani, Rita R %A Kardia, Sharon L R %A Kelly, Tanika N %A Lange, Ethan M %A LeNoir, Michael %A Li, Changwei %A Marchand, Loic Le %A McDonald, Merry-Lynn N %A McHugh, Caitlin P %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey %A O'Donnell, Christopher J %A Palmer, Nicholette D %A Pankow, James S %A Perry, James A %A Peters, Ulrike %A Preuss, Michael H %A Rao, D C %A Regan, Elizabeth A %A Reupena, Sefuiva M %A Roden, Dan M %A Rodriguez-Santana, Jose %A Sitlani, Colleen M %A Smith, Jennifer A %A Tiwari, Hemant K %A Vasan, Ramachandran S %A Wang, Zeyuan %A Weeks, Daniel E %A Wessel, Jennifer %A Wiggins, Kerri L %A Wilkens, Lynne R %A Wilson, Peter W F %A Yanek, Lisa R %A Yoneda, Zachary T %A Zhao, Wei %A Zöllner, Sebastian %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Blangero, John %A Boerwinkle, Eric %A Burchard, Esteban G %A Carson, April P %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Curran, Joanne E %A Fornage, Myriam %A Gordeuk, Victor R %A He, Jiang %A Heckbert, Susan R %A Hou, Lifang %A Irvin, Marguerite R %A Kooperberg, Charles %A Minster, Ryan L %A Mitchell, Braxton D %A Nouraie, Mehdi %A Psaty, Bruce M %A Raffield, Laura M %A Reiner, Alexander P %A Rich, Stephen S %A Rotter, Jerome I %A Shoemaker, M Benjamin %A Smith, Nicholas L %A Taylor, Kent D %A Telen, Marilyn J %A Weiss, Scott T %A Zhang, Yingze %A Costa, Nancy Heard- %A Sun, Yan V %A Lin, Xihong %A Cupples, L Adrienne %A Lange, Leslie A %A Liu, Ching-Ti %A Loos, Ruth J F %A North, Kari E %A Justice, Anne E %X

Obesity 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.

%B medRxiv %8 2023 Aug 22 %G eng %R 10.1101/2023.08.21.23293271 %0 Journal Article %J bioRxiv %D 2023 %T Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. %A Jiang, Min-Zhi %A Gaynor, Sheila M %A Li, Xihao %A Van Buren, Eric %A Stilp, Adrienne %A Buth, Erin %A Wang, Fei Fei %A Manansala, Regina %A Gogarten, Stephanie M %A Li, Zilin %A Polfus, Linda M %A Salimi, Shabnam %A Bis, Joshua C %A Pankratz, Nathan %A Yanek, Lisa R %A Durda, Peter %A Tracy, Russell P %A Rich, Stephen S %A Rotter, Jerome I %A Mitchell, Braxton D %A Lewis, Joshua P %A Psaty, Bruce M %A Pratte, Katherine A %A Silverman, Edwin K %A Kaplan, Robert C %A Avery, Christy %A North, Kari %A Mathias, Rasika A %A Faraday, Nauder %A Lin, Honghuang %A Wang, Biqi %A Carson, April P %A Norwood, Arnita F %A Gibbs, Richard A %A Kooperberg, Charles %A Lundin, Jessica %A Peters, Ulrike %A Dupuis, Josée %A Hou, Lifang %A Fornage, Myriam %A Benjamin, Emelia J %A Reiner, Alexander P %A Bowler, Russell P %A Lin, Xihong %A Auer, Paul L %A Raffield, Laura M %X

Inflammation 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.

%B bioRxiv %8 2023 Sep 12 %G eng %R 10.1101/2023.09.10.555215 %0 Journal Article %J Nature %D 2024 %T Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. %A Suzuki, Ken %A Hatzikotoulas, Konstantinos %A Southam, Lorraine %A Taylor, Henry J %A Yin, Xianyong %A Lorenz, Kim M %A Mandla, Ravi %A Huerta-Chagoya, Alicia %A Melloni, Giorgio E M %A Kanoni, Stavroula %A Rayner, Nigel W %A Bocher, Ozvan %A Arruda, Ana Luiza %A Sonehara, Kyuto %A Namba, Shinichi %A Lee, Simon S K %A Preuss, Michael H %A Petty, Lauren E %A Schroeder, Philip %A Vanderwerff, Brett %A Kals, Mart %A Bragg, Fiona %A Lin, Kuang %A Guo, Xiuqing %A Zhang, Weihua %A Yao, Jie %A Kim, Young Jin %A Graff, Mariaelisa %A Takeuchi, Fumihiko %A Nano, Jana %A Lamri, Amel %A Nakatochi, Masahiro %A Moon, Sanghoon %A Scott, Robert A %A Cook, James P %A Lee, Jung-Jin %A Pan, Ian %A Taliun, Daniel %A Parra, Esteban J %A Chai, Jin-Fang %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Thorleifsson, Gudmar %A Grarup, Niels %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Kwak, Soo-Heon %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Nongmaithem, Suraj S %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Brody, Jennifer A %A Kabagambe, Edmond %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Broadaway, K Alaine %A Williamson, Alice %A Kamali, Zoha %A Cui, Jinrui %A Thangam, Manonanthini %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Ahluwalia, Tarunveer S %A Anand, Sonia S %A Bertoni, Alain %A Bork-Jensen, Jette %A Brandslund, Ivan %A Buchanan, Thomas A %A Burant, Charles F %A Butterworth, Adam S %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Danesh, John %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Gordon-Larsen, Penny %A Gross, Myron %A Guare, Lindsay A %A Hackinger, Sophie %A Hakaste, Liisa %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Horikoshi, Momoko %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Torben %A Kamanu, Frederick K %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Kyung Min %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lynch, Julie A %A Lyssenko, Valeriya %A Maeda, Shiro %A Mamakou, Vasiliki %A Mansuri, Sohail Rafik %A Matsuda, Koichi %A Meitinger, Thomas %A Melander, Olle %A Metspalu, Andres %A Mo, Huan %A Morris, Andrew D %A Moura, Filipe A %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Patil, Snehal %A Pei, Pei %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Polikowsky, Hannah G %A Porneala, Bianca %A Prasad, Gauri %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Katheryn %A Sabanayagam, Charumathi %A Sandow, Kevin %A Sankareswaran, Alagu %A Sattar, Naveed %A Schönherr, Sebastian %A Shahriar, Mohammad %A Shen, Botong %A Shi, Jinxiu %A Shin, Dong Mun %A Shojima, Nobuhiro %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Steinthorsdottir, Valgerdur %A Stilp, Adrienne M %A Strauch, Konstantin %A Taylor, Kent D %A Thorand, Barbara %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Tran, Tam C %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamamoto, Kenichi %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zawistowski, Matthew %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Fornage, Myriam %A Hanis, Craig L %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Yokota, Mitsuhiro %A Kardia, Sharon L R %A Peyser, Patricia A %A Pankow, James S %A Engert, James C %A Bonnefond, Amélie %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Mook-Kanamori, Dennis O %A Tuomi, Tiinamaija %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A Chen, Yii-Der Ida %A Rich, Stephen S %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Ghanbari, Mohsen %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Bowden, Donald W %A Palmer, Colin N A %A Kooner, Jaspal S %A Kooperberg, Charles %A Liu, Simin %A North, Kari E %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Wareham, Nicholas J %A Lee, Juyoung %A Kim, Bong-Jo %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Ahlqvist, Emma %A Goodarzi, Mark O %A Mohlke, Karen L %A Langenberg, Claudia %A Haiman, Christopher A %A Loos, Ruth J F %A Florez, Jose C %A Rader, Daniel J %A Ritchie, Marylyn D %A Zöllner, Sebastian %A Mägi, Reedik %A Marston, Nicholas A %A Ruff, Christian T %A van Heel, David A %A Finer, Sarah %A Denny, Joshua C %A Yamauchi, Toshimasa %A Kadowaki, Takashi %A Chambers, John C %A Ng, Maggie C Y %A Sim, Xueling %A Below, Jennifer E %A Tsao, Philip S %A Chang, Kyong-Mi %A McCarthy, Mark I %A Meigs, James B %A Mahajan, Anubha %A Spracklen, Cassandra N %A Mercader, Josep M %A Boehnke, Michael %A Rotter, Jerome I %A Vujkovic, Marijana %A Voight, Benjamin F %A Morris, Andrew P %A Zeggini, Eleftheria %X

Type 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.

%B Nature %8 2024 Feb 19 %G eng %R 10.1038/s41586-024-07019-6