02787nas a2200649 4500008004100000022001400041245009900055210006900154260001600223300000900239490000800248520092400256653002201180653001201202653004001214653002501254653001001279653001101289653001901300653003201319653003801351653002201389653001801411653004201429653001101471653000901482653003601491653002201527653002301549100002401572700002301596700002501619700001601644700002101660700001801681700001601699700001201715700001801727700001301745700002001758700001901778700002101797700002001818700002001838700002201858700002101880700002601901700002101927700002001948700002601968700002401994700002002018710001302038710001502051710003502066856003602101 2012 eng d a1095-920300aEvolution and functional impact of rare coding variation from deep sequencing of human exomes.0 aEvolution and functional impact of rare coding variation from de c2012 Jul 06 a64-90 v3373 a
As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.
10aAfrican Americans10aDisease10aEuropean Continental Ancestry Group10aEvolution, Molecular10aExome10aFemale10aGene Frequency10aGenetic Association Studies10aGenetic Predisposition to Disease10aGenetic Variation10aGenome, Human10aHigh-Throughput Nucleotide Sequencing10aHumans10aMale10aPolymorphism, Single Nucleotide10aPopulation Growth10aSelection, Genetic1 aTennessen, Jacob, A1 aBigham, Abigail, W1 aO'Connor, Timothy, D1 aFu, Wenqing1 aKenny, Eimear, E1 aGravel, Simon1 aMcGee, Sean1 aDo, Ron1 aLiu, Xiaoming1 aJun, Goo1 aKang, Hyun, Min1 aJordan, Daniel1 aLeal, Suzanne, M1 aGabriel, Stacey1 aRieder, Mark, J1 aAbecasis, Goncalo1 aAltshuler, David1 aNickerson, Deborah, A1 aBoerwinkle, Eric1 aSunyaev, Shamil1 aBustamante, Carlos, D1 aBamshad, Michael, J1 aAkey, Joshua, M1 aBroad GO1 aSeattle GO1 aNHLBI Exome Sequencing Project uhttps://chs-nhlbi.org/node/138703560nas a2200709 4500008004100000022001400041245008800055210006900143260000900212300001100221490000600232520160600238653001001844653001201854653002101866653001901887653003401906653001001940653001101950653001901961653001301980653001301993653001002006653001102016653000902027653004402036653003602080653001602116653001602132653002702148100002002175700001302195700002402208700002302232700001902255700002002274700001702294700002302311700002502334700002002359700002402379700002202403700002202425700001902447700002202466700001702488700001702505700001902522700002002541700002002561700002102581700002602602700002402628700002102652700002402673700002302697700002102720700003002741700002202771700002102793856003602814 2013 eng d a1932-620300aBest practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium.0 aBest practices and joint calling of the HumanExome BeadChip the c2013 ae680950 v83 aGenotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.
10aAging10aAlleles10aCluster Analysis10aCohort Studies10aContinental Population Groups10aExome10aFemale10aGene Frequency10aGenomics10aGenotype10aHeart10aHumans10aMale10aOligonucleotide Array Sequence Analysis10aPolymorphism, Single Nucleotide10aSample Size10aSelf Report10aSequence Analysis, DNA1 aGrove, Megan, L1 aYu, Bing1 aCochran, Barbara, J1 aHaritunians, Talin1 aBis, Joshua, C1 aTaylor, Kent, D1 aHansen, Mark1 aBorecki, Ingrid, B1 aCupples, Adrienne, L1 aFornage, Myriam1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aKathiresan, Sekar1 aKraaij, Robert1 aLauner, Lenore, J1 aLevy, Daniel1 aLiu, Yongmei1 aMosley, Thomas1 aPeloso, Gina, M1 aPsaty, Bruce, M1 aRich, Stephen, S1 aRivadeneira, Fernando1 aSiscovick, David, S1 aSmith, Albert, V1 aUitterlinden, Andre1 aDuijn, Cornelia, M1 aWilson, James, G1 aO'Donnell, Christopher, J1 aRotter, Jerome, I1 aBoerwinkle, Eric uhttps://chs-nhlbi.org/node/606703380nas a2200565 4500008004100000022001400041245015900055210006900214260001300283300001100296490000600307520168100313653001501994653001002009653000902019653002802028653003102056653001402087653001002101653001102111653002602122653002002148653001702168653001802185653001102203653000902214653001602223653002002239653002302259653001502282653001302297653002002310653002702330653001602357100001902373700001802392700002402410700001702434700002002451700002102471700001702492700002202509700002002531700002402551700001802575700002602593700002402619710013502643856003602778 2013 eng d a1942-326800aExome sequencing and genome-wide linkage analysis in 17 families illustrate the complex contribution of TTN truncating variants to dilated cardiomyopathy.0 aExome sequencing and genomewide linkage analysis in 17 families c2013 Apr a144-530 v63 aBACKGROUND- Familial dilated cardiomyopathy (DCM) is a genetically heterogeneous disease with >30 known genes. TTN truncating variants were recently implicated in a candidate gene study to cause 25% of familial and 18% of sporadic DCM cases. METHODS AND RESULTS- We used an unbiased genome-wide approach using both linkage analysis and variant filtering across the exome sequences of 48 individuals affected with DCM from 17 families to identify genetic cause. Linkage analysis ranked the TTN region as falling under the second highest genome-wide multipoint linkage peak, multipoint logarithm of odds, 1.59. We identified 6 TTN truncating variants carried by individuals affected with DCM in 7 of 17 DCM families (logarithm of odds, 2.99); 2 of these 7 families also had novel missense variants that segregated with disease. Two additional novel truncating TTN variants did not segregate with DCM. Nucleotide diversity at the TTN locus, including missense variants, was comparable with 5 other known DCM genes. The average number of missense variants in the exome sequences from the DCM cases or the ≈5400 cases from the Exome Sequencing Project was ≈23 per individual. The average number of TTN truncating variants in the Exome Sequencing Project was 0.014 per individual. We also identified a region (chr9q21.11-q22.31) with no known DCM genes with a maximum heterogeneity logarithm of odds score of 1.74. CONCLUSIONS- These data suggest that TTN truncating variants contribute to DCM cause. However, the lack of segregation of all identified TTN truncating variants illustrates the challenge of determining variant pathogenicity even with full exome sequencing.
10aAdolescent10aAdult10aAged10aCardiomyopathy, Dilated10aChromosomes, Human, Pair 910aConnectin10aExome10aFemale10aGenetic Heterogeneity10aGenetic Linkage10aGenetic Loci10aGenome, Human10aHumans10aMale10aMiddle Aged10aMuscle Proteins10aMutation, Missense10aOdds Ratio10aPedigree10aProtein Kinases10aSequence Analysis, DNA10aYoung Adult1 aNorton, Nadine1 aLi, Duanxiang1 aRampersaud, Evadnie1 aMorales, Ana1 aMartin, Eden, R1 aZuchner, Stephan1 aGuo, Shengru1 aGonzalez, Michael1 aHedges, Dale, J1 aRobertson, Peggy, D1 aKrumm, Niklas1 aNickerson, Deborah, A1 aHershberger, Ray, E1 aNational Heart, Lung, and Blood Institute GO Exome Sequencing Project and the Exome Sequencing Project Family Studies Project Team uhttps://chs-nhlbi.org/node/613805734nas a2201333 4500008004100000022001400041245007800055210006900133260001500202300001000217490000800227520196900235653003902204653002502243653002102268653004002289653001002329653001302339653001702352653001102369653001002380653001302390653001702403653002702420653001802447110010402465700001702569700002002586700001802606700002302624700002402647700002102671700001802692700002202710700001402732700001802746700002002764700002302784700002202807700001202829700001302841700001402854700002002868700001602888700001502904700002002919700001802939700002802957700002102985700002203006700002303028700002303051700001203074700001903086700002503105700002103130700002003151700002303171700001803194700002303212700002903235700002303264700002303287700001903310700002003329700001903349700001903368700002203387700002403409700002403433700002303457700002203480700001703502700002203519700002003541700001903561700001903580700002003599700001903619700002603638700002003664700002403684700003003708700002003738700002803758700002203786700002103808700001903829700001803848700002503866700002103891700002003912700002003932700002303952700002203975700002203997700002204019700002004041700002404061700002104085700002404106700002104130700002204151700001604173700002104189700002004210700002604230700002004256700002504276700002004301700002104321700002204342856003604364 2014 eng d a1533-440600aLoss-of-function mutations in APOC3, triglycerides, and coronary disease.0 aLossoffunction mutations in APOC3 triglycerides and coronary dis c2014 Jul 3 a22-310 v3713 aBACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype.
METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons.
RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)).
CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).
10aAfrican Continental Ancestry Group10aApolipoprotein C-III10aCoronary Disease10aEuropean Continental Ancestry Group10aExome10aGenotype10aHeterozygote10aHumans10aLiver10aMutation10aRisk Factors10aSequence Analysis, DNA10aTriglycerides1 aTG and HDL Working Group of the Exome Sequencing Project, National Heart, Lung, and Blood Institute1 aCrosby, Jacy1 aPeloso, Gina, M1 aAuer, Paul, L1 aCrosslin, David, R1 aStitziel, Nathan, O1 aLange, Leslie, A1 aLu, Yingchang1 aTang, Zheng-Zheng1 aZhang, He1 aHindy, George1 aMasca, Nicholas1 aStirrups, Kathleen1 aKanoni, Stavroula1 aDo, Ron1 aJun, Goo1 aHu, Youna1 aKang, Hyun, Min1 aXue, Chenyi1 aGoel, Anuj1 aFarrall, Martin1 aDuga, Stefano1 aMerlini, Pier, Angelica1 aAsselta, Rosanna1 aGirelli, Domenico1 aOlivieri, Oliviero1 aMartinelli, Nicola1 aYin, Wu1 aReilly, Dermot1 aSpeliotes, Elizabeth1 aFox, Caroline, S1 aHveem, Kristian1 aHolmen, Oddgeir, L1 aNikpay, Majid1 aFarlow, Deborah, N1 aAssimes, Themistocles, L1 aFranceschini, Nora1 aRobinson, Jennifer1 aNorth, Kari, E1 aMartin, Lisa, W1 aDePristo, Mark1 aGupta, Namrata1 aEscher, Stefan, A1 aJansson, Jan-Håkan1 aVan Zuydam, Natalie1 aPalmer, Colin, N A1 aWareham, Nicholas1 aKoch, Werner1 aMeitinger, Thomas1 aPeters, Annette1 aLieb, Wolfgang1 aErbel, Raimund1 aKönig, Inke, R1 aKruppa, Jochen1 aDegenhardt, Franziska1 aGottesman, Omri1 aBottinger, Erwin, P1 aO'Donnell, Christopher, J1 aPsaty, Bruce, M1 aBallantyne, Christie, M1 aAbecasis, Goncalo1 aOrdovas, Jose, M1 aMelander, Olle1 aWatkins, Hugh1 aOrho-Melander, Marju1 aArdissino, Diego1 aLoos, Ruth, J F1 aMcPherson, Ruth1 aWiller, Cristen, J1 aErdmann, Jeanette1 aHall, Alistair, S1 aSamani, Nilesh, J1 aDeloukas, Panos1 aSchunkert, Heribert1 aWilson, James, G1 aKooperberg, Charles1 aRich, Stephen, S1 aTracy, Russell, P1 aLin, Dan-Yu1 aAltshuler, David1 aGabriel, Stacey1 aNickerson, Deborah, A1 aJarvik, Gail, P1 aCupples, Adrienne, L1 aReiner, Alex, P1 aBoerwinkle, Eric1 aKathiresan, Sekar uhttps://chs-nhlbi.org/node/660503736nas a2200577 4500008004100000022001400041245014100055210006900196260001300265490000600278520210100284653001002385653000902395653002802404653001802432653001002450653001102460653001302471653001102484653001802495653002002513653000902533653002502542653001602567653004002583653004002623653001202663653001502675653003602690653001402726653001702740653002702757100002402784700001102808700001802819700001902837700002502856700002102881700002002902700002102922700001902943700001702962700002002979700002202999700001903021700002003040700002303060700001803083700002103101856003603122 2014 eng d a2047-998000aA low-frequency variant in MAPK14 provides mechanistic evidence of a link with myeloperoxidase: a prognostic cardiovascular risk marker.0 alowfrequency variant in MAPK14 provides mechanistic evidence of c2014 Aug0 v33 aBACKGROUND: Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen-activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow-up genotyping or imputation in participants well-phenotyped for cardiovascular and metabolic traits.
METHODS AND RESULTS: Investigation of genetic variation in MAPK11 and MAPK14 genes using additive genetic models in linear or logistic regression with cardiovascular, metabolic, and biomarker phenotypes highlighted an association of RS2859144 in MAPK14 with myeloperoxidase in a dyslipidemic population (Genetic Epidemiology of Metabolic Syndrome Study), P=2.3×10(-6)). This variant (or proxy) was consistently associated with myeloperoxidase in the Framingham Heart Study and Cardiovascular Health Study studies (replication meta-P=0.003), leading to a meta-P value of 9.96×10(-7) in the 3 dyslipidemic groups. The variant or its proxy was then profiled in additional population-based cohorts (up to a total of 58 930 subjects) including Cohorte Lausannoise, Ely, Fenland, European Prospective Investigation of Cancer, London Life Sciences Prospective Population Study, and the Genetics of Obesity Associations study obesity case-control for up to 40 cardiovascular and metabolic traits. Overall analysis identified the same single nucleotide polymorphisms to be nominally associated consistently with glomerular filtration rate (P=0.002) and risk of obesity (body mass index ≥30 kg/m(2), P=0.004).
CONCLUSIONS: As myeloperoxidase is a prognostic marker of coronary events, the MAPK14 variant may provide a mechanistic link between p38 map kinase and these events, providing information consistent with current indication of Losmapimod for acute coronary syndrome. If replicated, the association with glomerular filtration rate, along with previous biological findings, also provides support for kidney diseases as alternative indications.
10aAdult10aAged10aCardiovascular Diseases10aDyslipidemias10aExome10aFemale10aGenotype10aHumans10aLinear Models10aLogistic Models10aMale10aMetabolic Syndrome X10aMiddle Aged10aMitogen-Activated Protein Kinase 1110aMitogen-Activated Protein Kinase 1410aObesity10aPeroxidase10aPolymorphism, Single Nucleotide10aPrognosis10aRisk Factors10aSequence Analysis, DNA1 aWaterworth, Dawn, M1 aLi, Li1 aScott, Robert1 aWarren, Liling1 aGillson, Christopher1 aAponte, Jennifer1 aSarov-Blat, Lea1 aSprecher, Dennis1 aDupuis, Josée1 aReiner, Alex1 aPsaty, Bruce, M1 aTracy, Russell, P1 aLin, Honghuang1 aMcPherson, Ruth1 aChissoe, Stephanie1 aWareham, Nick1 aEhm, Margaret, G uhttps://chs-nhlbi.org/node/661003227nas a2200505 4500008004100000022001400041245012600055210006900181260001600250300001200266490000700278520166100285653003501946653002301981653004002004653001002044653001102054653003202065653002102097653002602118100002002144700002002164700002302184700002402207700002902231700001802260700002502278700001902303700002602322700002302348700001702371700002202388700002202410700002002432700002402452700002502476700003002501700002502531700002102556700002002577700002402597700002602621710003802647856003602685 2014 eng d a1460-208300aQuantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset.0 aQuantifying rare deleterious variation in 12 human cytochrome P4 c2014 Apr 15 a1957-630 v233 aThe study of genetic influences on drug response and efficacy ('pharmacogenetics') has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6-11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.
10aCytochrome P-450 Enzyme System10aDatabases, Genetic10aEuropean Continental Ancestry Group10aExome10aHumans10aPharmaceutical Preparations10aPharmacogenetics10aPolymorphism, Genetic1 aGordon, Adam, S1 aTabor, Holly, K1 aJohnson, Andrew, D1 aSnively, Beverly, M1 aAssimes, Themistocles, L1 aAuer, Paul, L1 aIoannidis, John, P A1 aPeters, Ulrike1 aRobinson, Jennifer, G1 aSucheston, Lara, E1 aWang, Danxin1 aSotoodehnia, Nona1 aRotter, Jerome, I1 aPsaty, Bruce, M1 aJackson, Rebecca, D1 aHerrington, David, M1 aO'Donnell, Christopher, J1 aReiner, Alexander, P1 aRich, Stephen, S1 aRieder, Mark, J1 aBamshad, Michael, J1 aNickerson, Deborah, A1 aNHLBI GO Exome Sequencing Project uhttps://chs-nhlbi.org/node/656505955nas a2201657 4500008004100000022001400041245011000055210006900165260001600234300001100250490000700261520138800268653001001656653000901666653002201675653002101697653001901718653001801737653001001755653001101765653002201776653001901798653001701817653003401834653001301868653001101881653001101892653000901903653001601912653001401928653003601942653002801978653002702006653001902033653002702052653002602079100002102105700001402126700001402140700001602154700002202170700002202192700001702214700002002231700002102251700002102272700001302293700002002306700001702326700001502343700001702358700002002375700001402395700002702409700001802436700002202454700001602476700001902492700001702511700002102528700002302549700002002572700001802592700002202610700001802632700001502650700001202665700001702677700001502694700001802709700001902727700001902746700001902765700002502784700002602809700002102835700002502856700002102881700001902902700002502921700001702946700002502963700001202988700002303000700002003023700002603043700002903069700002303098700002803121700001803149700002003167700002303187700002103210700001903231700001803250700002803268700001903296700002403315700002303339700002803362700001703390700002203407700002203429700002403451700002403475700002003499700002303519700002203542700001603564700001703580700002403597700002003621700001803641700002003659700002103679700001603700700001903716700002203735700002803757700002303785700003003808700001903838700001903857700002503876700002103901700002003922700002103942700002203963700001603985700002004001700002504021700002404046700002104070700002604091700002504117700002104142700002204163700002304185710005304208856003604261 2014 eng d a1537-660500aWhole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.0 aWholeexome sequencing identifies rare and lowfrequency coding va c2014 Feb 06 a233-450 v943 aElevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.
10aAdult10aAged10aApolipoproteins E10aCholesterol, LDL10aCohort Studies10aDyslipidemias10aExome10aFemale10aFollow-Up Studies10aGene Frequency10aGenetic Code10aGenome-Wide Association Study10aGenotype10aHumans10aLipase10aMale10aMiddle Aged10aPhenotype10aPolymorphism, Single Nucleotide10aProprotein Convertase 910aProprotein Convertases10aReceptors, LDL10aSequence Analysis, DNA10aSerine Endopeptidases1 aLange, Leslie, A1 aHu, Youna1 aZhang, He1 aXue, Chenyi1 aSchmidt, Ellen, M1 aTang, Zheng-Zheng1 aBizon, Chris1 aLange, Ethan, M1 aSmith, Joshua, D1 aTurner, Emily, H1 aJun, Goo1 aKang, Hyun, Min1 aPeloso, Gina1 aAuer, Paul1 aLi, Kuo-Ping1 aFlannick, Jason1 aZhang, Ji1 aFuchsberger, Christian1 aGaulton, Kyle1 aLindgren, Cecilia1 aLocke, Adam1 aManning, Alisa1 aSim, Xueling1 aRivas, Manuel, A1 aHolmen, Oddgeir, L1 aGottesman, Omri1 aLu, Yingchang1 aRuderfer, Douglas1 aStahl, Eli, A1 aDuan, Qing1 aLi, Yun1 aDurda, Peter1 aJiao, Shuo1 aIsaacs, Aaron1 aHofman, Albert1 aBis, Joshua, C1 aCorrea, Adolfo1 aGriswold, Michael, E1 aJakobsdottir, Johanna1 aSmith, Albert, V1 aSchreiner, Pamela, J1 aFeitosa, Mary, F1 aZhang, Qunyuan1 aHuffman, Jennifer, E1 aCrosby, Jacy1 aWassel, Christina, L1 aDo, Ron1 aFranceschini, Nora1 aMartin, Lisa, W1 aRobinson, Jennifer, G1 aAssimes, Themistocles, L1 aCrosslin, David, R1 aRosenthal, Elisabeth, A1 aTsai, Michael1 aRieder, Mark, J1 aFarlow, Deborah, N1 aFolsom, Aaron, R1 aLumley, Thomas1 aFox, Ervin, R1 aCarlson, Christopher, S1 aPeters, Ulrike1 aJackson, Rebecca, D1 aDuijn, Cornelia, M1 aUitterlinden, André, G1 aLevy, Daniel1 aRotter, Jerome, I1 aTaylor, Herman, A1 aGudnason, Vilmundur1 aSiscovick, David, S1 aFornage, Myriam1 aBorecki, Ingrid, B1 aHayward, Caroline1 aRudan, Igor1 aChen, Eugene1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aSætrom, Pål1 aHveem, Kristian1 aBoehnke, Michael1 aGroop, Leif1 aMcCarthy, Mark1 aMeitinger, Thomas1 aBallantyne, Christie, M1 aGabriel, Stacey, B1 aO'Donnell, Christopher, J1 aPost, Wendy, S1 aNorth, Kari, E1 aReiner, Alexander, P1 aBoerwinkle, Eric1 aPsaty, Bruce, M1 aAltshuler, David1 aKathiresan, Sekar1 aLin, Dan-Yu1 aJarvik, Gail, P1 aCupples, Adrienne, L1 aKooperberg, Charles1 aWilson, James, G1 aNickerson, Deborah, A1 aAbecasis, Goncalo, R1 aRich, Stephen, S1 aTracy, Russell, P1 aWiller, Cristen, J1 aNHLBI Grand Opportunity Exome Sequencing Project uhttps://chs-nhlbi.org/node/657704486nas a2200901 4500008004100000022001400041245009600055210006900151260001600220300001100236490000700247520184700254653001002101653002202111653002302133653002802156653001902184653004002203653001002243653001102253653001902264653003802283653003402321653003802355653001102393653000902404653001102413653003602424653002902460653001702489100002202506700001802528700001902546700001902565700001402584700002102598700002102619700002002640700002402660700001902684700002802703700002002731700002202751700001202773700002402785700002402809700002102833700002002854700002102874700001902895700002102914700001602935700002002951700001502971700001902986700002003005700001803025700002103043700001803064700002203082700002403104700002303128700002303151700001903174700002603193700002203219700001903241700001903260700002103279700002103300700002403321700002403345700002003369700002003389710006503409710007403474856003603548 2015 eng d a1460-208300aAssociation of exome sequences with plasma C-reactive protein levels in >9000 participants.0 aAssociation of exome sequences with plasma Creactive protein lev c2015 Jan 15 a559-710 v243 aC-reactive protein (CRP) concentration is a heritable systemic marker of inflammation that is associated with cardiovascular disease risk. Genome-wide association studies have identified CRP-associated common variants associated in ∼25 genes. Our aims were to apply exome sequencing to (1) assess whether the candidate loci contain rare coding variants associated with CRP levels and (2) perform an exome-wide search for rare variants in novel genes associated with CRP levels. We exome-sequenced 6050 European-Americans (EAs) and 3109 African-Americans (AAs) from the NHLBI-ESP and the CHARGE consortia, and performed association tests of sequence data with measured CRP levels. In single-variant tests across candidate loci, a novel rare (minor allele frequency = 0.16%) CRP-coding variant (rs77832441-A; p.Thr59Met) was associated with 53% lower mean CRP levels (P = 2.9 × 10(-6)). We replicated the association of rs77832441 in an exome array analysis of 11 414 EAs (P = 3.0 × 10(-15)). Despite a strong effect on CRP levels, rs77832441 was not associated with inflammation-related phenotypes including coronary heart disease. We also found evidence for an AA-specific association of APOE-ε2 rs7214 with higher CRP levels. At the exome-wide significance level (P < 5.0 × 10(-8)), we confirmed associations for reported common variants of HNF1A, CRP, IL6R and TOMM40-APOE. In gene-based tests, a burden of rare/lower frequency variation in CRP in EAs (P ≤ 6.8 × 10(-4)) and in retinoic acid receptor-related orphan receptor α (RORA) in AAs (P = 1.7 × 10(-3)) were associated with CRP levels at the candidate gene level (P < 2.0 × 10(-3)). This inquiry did not elucidate novel genes, but instead demonstrated that variants distributed across the allele frequency spectrum within candidate genes contribute to CRP levels.
10aAdult10aAfrican Americans10aC-Reactive Protein10aCardiovascular Diseases10aCohort Studies10aEuropean Continental Ancestry Group10aExome10aFemale10aGene Frequency10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHepatocyte Nuclear Factor 1-alpha10aHumans10aMale10aPlasma10aPolymorphism, Single Nucleotide10aReceptors, Interleukin-610aRisk Factors1 aSchick, Ursula, M1 aAuer, Paul, L1 aBis, Joshua, C1 aLin, Honghuang1 aWei, Peng1 aPankratz, Nathan1 aLange, Leslie, A1 aBrody, Jennifer1 aStitziel, Nathan, O1 aKim, Daniel, S1 aCarlson, Christopher, S1 aFornage, Myriam1 aHaessler, Jeffery1 aHsu, Li1 aJackson, Rebecca, D1 aKooperberg, Charles1 aLeal, Suzanne, M1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aTracy, Russell1 aArdissino, Diego1 aShah, Svati1 aWiller, Cristen1 aLoos, Ruth1 aMelander, Olle1 aMcPherson, Ruth1 aHovingh, Kees1 aReilly, Muredach1 aWatkins, Hugh1 aGirelli, Domenico1 aFontanillas, Pierre1 aChasman, Daniel, I1 aGabriel, Stacey, B1 aGibbs, Richard1 aNickerson, Deborah, A1 aKathiresan, Sekar1 aPeters, Ulrike1 aDupuis, Josée1 aWilson, James, G1 aRich, Stephen, S1 aMorrison, Alanna, C1 aBenjamin, Emelia, J1 aGross, Myron, D1 aReiner, Alex, P1 aCohorts for Heart and Aging Research in Genomic Epidemiology1 aNational Heart, Lung, and Blood Institute GO Exome Sequencing Project uhttps://chs-nhlbi.org/node/659706191nas a2201513 4500008004100000022001400041245010300055210006900158260001500227300001000242490000800252520194100260653001602201653001702217653001202234653002202246653002502268653002102293653002802314653001002342653001102352653003802363653002502401653001702426653001102443653000902454653001602463653001302479653002602492653005302518653001902571653001802590653001802608100001202626700002402638700001802662700002902680700001802709700002802727700001702755700002002772700001502792700001202807700002002819700002102839700002102860700002002881700001802901700002202919700002302941700002302964700002202987700002003009700002803029700002103057700001703078700002403095700002803119700001803147700002303165700002203188700002403210700002203234700001903256700002203275700001903297700001803316700002903334700001503363700002203378700002003400700002003420700002203440700001503462700002303477700001603500700001903516700001703535700001703552700002903569700001903598700002003617700002103637700002203658700002303680700002003703700001903723700002203742700001203764700002103776700002003797700002403817700002003841700002503861700002103886700002103907700002403928700002203952700002503974700002103999700002404020700002104044700001904065700002004084700002204104700002204126700002004148700002004168700002804188700002404216700002404240700002104264700002004285700002504305700002404330700002004354700002604374700002504400700001804425700002604443700002104469700002304490700003004513700002104543700002004564700002204584710003504606856003604641 2015 eng d a1476-468700aExome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction.0 aExome sequencing identifies rare LDLR and APOA5 alleles conferri c2015 Feb 5 a102-60 v5183 aMyocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
10aAge Factors10aAge of Onset10aAlleles10aApolipoproteins A10aCase-Control Studies10aCholesterol, LDL10aCoronary Artery Disease10aExome10aFemale10aGenetic Predisposition to Disease10aGenetics, Population10aHeterozygote10aHumans10aMale10aMiddle Aged10aMutation10aMyocardial Infarction10aNational Heart, Lung, and Blood Institute (U.S.)10aReceptors, LDL10aTriglycerides10aUnited States1 aDo, Ron1 aStitziel, Nathan, O1 aWon, Hong-Hee1 aJørgensen, Anders, Berg1 aDuga, Stefano1 aMerlini, Pier, Angelica1 aKiezun, Adam1 aFarrall, Martin1 aGoel, Anuj1 aZuk, Or1 aGuella, Illaria1 aAsselta, Rosanna1 aLange, Leslie, A1 aPeloso, Gina, M1 aAuer, Paul, L1 aGirelli, Domenico1 aMartinelli, Nicola1 aFarlow, Deborah, N1 aDePristo, Mark, A1 aRoberts, Robert1 aStewart, Alexander, F R1 aSaleheen, Danish1 aDanesh, John1 aEpstein, Stephen, E1 aSivapalaratnam, Suthesh1 aHovingh, Kees1 aKastelein, John, J1 aSamani, Nilesh, J1 aSchunkert, Heribert1 aErdmann, Jeanette1 aShah, Svati, H1 aKraus, William, E1 aDavies, Robert1 aNikpay, Majid1 aJohansen, Christopher, T1 aWang, Jian1 aHegele, Robert, A1 aHechter, Eliana1 aMärz, Winfried1 aKleber, Marcus, E1 aHuang, Jie1 aJohnson, Andrew, D1 aLi, Mingyao1 aBurke, Greg, L1 aGross, Myron1 aLiu, Yongmei1 aAssimes, Themistocles, L1 aHeiss, Gerardo1 aLange, Ethan, M1 aFolsom, Aaron, R1 aTaylor, Herman, A1 aOlivieri, Oliviero1 aHamsten, Anders1 aClarke, Robert1 aReilly, Dermot, F1 aYin, Wu1 aRivas, Manuel, A1 aDonnelly, Peter1 aRossouw, Jacques, E1 aPsaty, Bruce, M1 aHerrington, David, M1 aWilson, James, G1 aRich, Stephen, S1 aBamshad, Michael, J1 aTracy, Russell, P1 aCupples, Adrienne, L1 aRader, Daniel, J1 aReilly, Muredach, P1 aSpertus, John, A1 aCresci, Sharon1 aHartiala, Jaana1 aTang, W, H Wilson1 aHazen, Stanley, L1 aAllayee, Hooman1 aReiner, Alex, P1 aCarlson, Christopher, S1 aKooperberg, Charles1 aJackson, Rebecca, D1 aBoerwinkle, Eric1 aLander, Eric, S1 aSchwartz, Stephen, M1 aSiscovick, David, S1 aMcPherson, Ruth1 aTybjaerg-Hansen, Anne1 aAbecasis, Goncalo, R1 aWatkins, Hugh1 aNickerson, Deborah, A1 aArdissino, Diego1 aSunyaev, Shamil, R1 aO'Donnell, Christopher, J1 aAltshuler, David1 aGabriel, Stacey1 aKathiresan, Sekar1 aNHLBI Exome Sequencing Project uhttps://chs-nhlbi.org/node/669109013nas a2202797 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2015 eng d a2041-172300aLow-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility.0 aLowfrequency and rare exome chip variants associate with fasting c2015 a58970 v63 aFasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
10aAfrican Continental Ancestry Group10aBlood Glucose10aDiabetes Mellitus, Type 210aEuropean Continental Ancestry Group10aExome10aFasting10aGenetic Association Studies10aGenetic Loci10aGenetic Predisposition to Disease10aGenetic Variation10aGlucagon-Like Peptide-1 Receptor10aGlucose-6-Phosphatase10aHumans10aInsulin10aMutation Rate10aOligonucleotide Array Sequence Analysis10aPolymorphism, Single Nucleotide1 aWessel, Jennifer1 aChu, Audrey, Y1 aWillems, Sara, M1 aWang, Shuai1 aYaghootkar, Hanieh1 aBrody, Jennifer, A1 aDauriz, Marco1 aHivert, Marie-France1 aRaghavan, Sridharan1 aLipovich, Leonard1 aHidalgo, Bertha1 aFox, Keolu1 aHuffman, Jennifer, E1 aAn, Ping1 aLu, Yingchang1 aRasmussen-Torvik, Laura, J1 aGrarup, Niels1 aEhm, Margaret, G1 aLi, Li1 aBaldridge, Abigail, S1 aStančáková, Alena1 aAbrol, Ravinder1 aBesse, Céline1 aBoland, Anne1 aBork-Jensen, Jette1 aFornage, Myriam1 aFreitag, Daniel, F1 aGarcia, Melissa, E1 aGuo, Xiuqing1 aHara, Kazuo1 aIsaacs, Aaron1 aJakobsdottir, Johanna1 aLange, Leslie, A1 aLayton, Jill, C1 aLi, Man1 aZhao, Jing, Hua1 aMeidtner, Karina1 aMorrison, Alanna, C1 aNalls, Mike, A1 aPeters, Marjolein, J1 aSabater-Lleal, Maria1 aSchurmann, Claudia1 aSilveira, Angela1 aSmith, Albert, V1 aSoutham, Lorraine1 aStoiber, Marcus, H1 aStrawbridge, Rona, J1 aTaylor, Kent, D1 aVarga, Tibor, V1 aAllin, Kristine, H1 aAmin, Najaf1 aAponte, Jennifer, L1 aAung, Tin1 aBarbieri, Caterina1 aBihlmeyer, Nathan, A1 aBoehnke, Michael1 aBombieri, Cristina1 aBowden, Donald, W1 aBurns, Sean, M1 aChen, Yuning1 aChen, Yii-DerI1 aCheng, Ching-Yu1 aCorrea, Adolfo1 aCzajkowski, Jacek1 aDehghan, Abbas1 aEhret, Georg, B1 aEiriksdottir, Gudny1 aEscher, Stefan, A1 aFarmaki, Aliki-Eleni1 aFrånberg, Mattias1 aGambaro, Giovanni1 aGiulianini, Franco1 aGoddard, William, A1 aGoel, Anuj1 aGottesman, Omri1 aGrove, Megan, L1 aGustafsson, Stefan1 aHai, Yang1 aHallmans, Göran1 aHeo, Jiyoung1 aHoffmann, Per1 aIkram, Mohammad, K1 aJensen, Richard, A1 aJørgensen, Marit, E1 aJørgensen, Torben1 aKaraleftheri, Maria1 aKhor, Chiea, C1 aKirkpatrick, Andrea1 aKraja, Aldi, T1 aKuusisto, Johanna1 aLange, Ethan, M1 aLee, I, T1 aLee, Wen-Jane1 aLeong, Aaron1 aLiao, Jiemin1 aLiu, Chunyu1 aLiu, Yongmei1 aLindgren, Cecilia, M1 aLinneberg, Allan1 aMalerba, Giovanni1 aMamakou, Vasiliki1 aMarouli, Eirini1 aMaruthur, Nisa, M1 aMatchan, Angela1 aMcKean-Cowdin, Roberta1 aMcLeod, Olga1 aMetcalf, Ginger, A1 aMohlke, Karen, L1 aMuzny, Donna, M1 aNtalla, Ioanna1 aPalmer, Nicholette, D1 aPasko, Dorota1 aPeter, Andreas1 aRayner, Nigel, W1 aRenstrom, Frida1 aRice, Ken1 aSala, Cinzia, F1 aSennblad, Bengt1 aSerafetinidis, Ioannis1 aSmith, Jennifer, A1 aSoranzo, Nicole1 aSpeliotes, Elizabeth, K1 aStahl, Eli, A1 aStirrups, Kathleen1 aTentolouris, Nikos1 aThanopoulou, Anastasia1 aTorres, Mina1 aTraglia, Michela1 aTsafantakis, Emmanouil1 aJavad, Sundas1 aYanek, Lisa, R1 aZengini, Eleni1 aBecker, Diane, M1 aBis, Joshua, C1 aBrown, James, B1 aCupples, Adrienne, L1 aHansen, Torben1 aIngelsson, Erik1 aKarter, Andrew, J1 aLorenzo, Carlos1 aMathias, Rasika, A1 aNorris, Jill, M1 aPeloso, Gina, M1 aSheu, Wayne, H-H1 aToniolo, Daniela1 aVaidya, Dhananjay1 aVarma, Rohit1 aWagenknecht, Lynne, E1 aBoeing, Heiner1 aBottinger, Erwin, P1 aDedoussis, George1 aDeloukas, Panos1 aFerrannini, Ele1 aFranco, Oscar, H1 aFranks, Paul, W1 aGibbs, Richard, A1 aGudnason, Vilmundur1 aHamsten, Anders1 aHarris, Tamara, B1 aHattersley, Andrew, T1 aHayward, Caroline1 aHofman, Albert1 aJansson, Jan-Håkan1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLevy, Daniel1 aOostra, Ben, A1 aO'Donnell, Christopher, J1 aO'Rahilly, Stephen1 aPadmanabhan, Sandosh1 aPankow, James, S1 aPolasek, Ozren1 aProvince, Michael, A1 aRich, Stephen, S1 aRidker, Paul, M1 aRudan, Igor1 aSchulze, Matthias, B1 aSmith, Blair, H1 aUitterlinden, André, G1 aWalker, Mark1 aWatkins, Hugh1 aWong, Tien, Y1 aZeggini, Eleftheria1 aLaakso, Markku1 aBorecki, Ingrid, B1 aChasman, Daniel, I1 aPedersen, Oluf1 aPsaty, Bruce, M1 aTai, Shyong, E1 aDuijn, Cornelia, M1 aWareham, Nicholas, J1 aWaterworth, Dawn, M1 aBoerwinkle, Eric1 aKao, Linda, W H1 aFlorez, Jose, C1 aLoos, Ruth, J F1 aWilson, James, G1 aFrayling, Timothy, M1 aSiscovick, David, S1 aDupuis, Josée1 aRotter, Jerome, I1 aMeigs, James, B1 aScott, Robert, A1 aGoodarzi, Mark, O1 aEPIC-InterAct Consortium uhttps://chs-nhlbi.org/node/668604841nas a2200685 4500008004100000022001400041245011900055210006900174260001300243300001000256490000700266520281800273653000903091653001903100653001003119653001103129653003803140653002203178653003403200653001103234653000903245653001603254653002003270653005303290653002103343653002403364653002803388653001103416653001803427100001803445700001603463700002203479700002503501700002003526700002003546700002403566700002403590700002803614700001903642700001803661700002503679700002403704700002003728700001603748700001203764700002403776700002003800700001903820700002903839700002103868700002103889700002203910700002503932700002503957700002603982700001904008700002104027710007104048856003604119 2015 eng d a2168-615700aRare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project.0 aRare and Coding Region Genetic Variants Associated With Risk of c2015 Jul a781-80 v723 aIMPORTANCE: Stroke is the second leading cause of death and the third leading cause of years of life lost. Genetic factors contribute to stroke prevalence, and candidate gene and genome-wide association studies (GWAS) have identified variants associated with ischemic stroke risk. These variants often have small effects without obvious biological significance. Exome sequencing may discover predicted protein-altering variants with a potentially large effect on ischemic stroke risk.
OBJECTIVE: To investigate the contribution of rare and common genetic variants to ischemic stroke risk by targeting the protein-coding regions of the human genome.
DESIGN, SETTING, AND PARTICIPANTS: The National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP) analyzed approximately 6000 participants from numerous cohorts of European and African ancestry. For discovery, 365 cases of ischemic stroke (small-vessel and large-vessel subtypes) and 809 European ancestry controls were sequenced; for replication, 47 affected sibpairs concordant for stroke subtype and an African American case-control series were sequenced, with 1672 cases and 4509 European ancestry controls genotyped. The ESP's exome sequencing and genotyping started on January 1, 2010, and continued through June 30, 2012. Analyses were conducted on the full data set between July 12, 2012, and July 13, 2013.
MAIN OUTCOMES AND MEASURES: Discovery of new variants or genes contributing to ischemic stroke risk and subtype (primary analysis) and determination of support for protein-coding variants contributing to risk in previously published candidate genes (secondary analysis).
RESULTS: We identified 2 novel genes associated with an increased risk of ischemic stroke: a protein-coding variant in PDE4DIP (rs1778155; odds ratio, 2.15; P = 2.63 × 10(-8)) with an intracellular signal transduction mechanism and in ACOT4 (rs35724886; odds ratio, 2.04; P = 1.24 × 10(-7)) with a fatty acid metabolism; confirmation of PDE4DIP was observed in affected sibpair families with large-vessel stroke subtype and in African Americans. Replication of protein-coding variants in candidate genes was observed for 2 previously reported GWAS associations: ZFHX3 (cardioembolic stroke) and ABCA1 (large-vessel stroke).
CONCLUSIONS AND RELEVANCE: Exome sequencing discovered 2 novel genes and mechanisms, PDE4DIP and ACOT4, associated with increased risk for ischemic stroke. In addition, ZFHX3 and ABCA1 were discovered to have protein-coding variants associated with ischemic stroke. These results suggest that genetic variation in novel pathways contributes to ischemic stroke risk and serves as a target for prediction, prevention, and therapy.
10aAged10aBrain Ischemia10aExome10aFemale10aGenetic Predisposition to Disease10aGenetic Variation10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aMuscle Proteins10aNational Heart, Lung, and Blood Institute (U.S.)10aNuclear Proteins10aOpen Reading Frames10aPalmitoyl-CoA Hydrolase10aStroke10aUnited States1 aAuer, Paul, L1 aNalls, Mike1 aMeschia, James, F1 aWorrall, Bradford, B1 aLongstreth, W T1 aSeshadri, Sudha1 aKooperberg, Charles1 aBurger, Kathleen, M1 aCarlson, Christopher, S1 aCarty, Cara, L1 aChen, Wei-Min1 aCupples, Adrienne, L1 aDeStefano, Anita, L1 aFornage, Myriam1 aHardy, John1 aHsu, Li1 aJackson, Rebecca, D1 aJarvik, Gail, P1 aKim, Daniel, S1 aLakshminarayan, Kamakshi1 aLange, Leslie, A1 aManichaikul, Ani1 aQuinlan, Aaron, R1 aSingleton, Andrew, B1 aThornton, Timothy, A1 aNickerson, Deborah, A1 aPeters, Ulrike1 aRich, Stephen, S1 aNational Heart, Lung, and Blood Institute Exome Sequencing Project uhttps://chs-nhlbi.org/node/684909668nas a2203061 4500008004100000022001400041245007500055210006900130260001300199300001400212490000700226520116500233653002801398653003001426653001001456653003201466653003801498653002201536653001301558653001101571653001101582653002501593653001401618653001701632100002001649700002001669700001501689700002501704700001501729700002001744700002101764700001801785700001601803700003101819700002201850700003001872700002401902700002901926700001801955700001701973700002801990700001702018700001902035700001902054700002102073700002102094700002302115700002402138700002102162700001802183700002002201700002302221700002202244700002302266700001702289700002202306700001902328700002402347700001902371700002102390700002102411700002502432700002302457700001702480700001802497700002202515700002102537700002102558700002402579700002002603700002402623700001602647700002502663700002102688700002002709700002002729700001402749700002002763700002002783700002502803700002502828700002202853700002302875700002102898700002202919700001302941700002302954700002202977700002302999700002203022700002103044700001803065700001603083700002003099700002403119700001903143700002203162700002203184700002403206700002303230700002203253700001403275700002003289700002003309700002103329700002603350700002703376700002003403700002503423700001903448700002503467700002103492700002203513700001903535700001503554700001903569700001803588700002503606700002203631700002403653700002003677700002203697700001903719700001603738700002403754700001903778700002203797700002303819700002403842700001603866700002103882700002003903700001803923700001803941700001803959700002303977700002104000700002204021700002404043700002004067700002504087700002004112700002004132700001904152700002104171700002204192700002404214700002104238700003004259700002404289700002104313700002204334700002104356700002804377700002104405700001904426700002904445700002504474700002204499700002204521700002504543700002304568700001804591700002304609700001904632700001904651700002004670700002404690700002004714700001904734700001804753700002004771700002104791700001804812700002104830700002204851700002004873700002004893700002104913700002004934700001904954700002304973700001804996700002205014700001605036700002005052700002205072700001805094700001905112700002205131700002105153700001705174700002305191700002605214700001705240700002805257700002105285700002105306700002005327700002605347700002205373700002405395700002805419700001905447700002605466700002105492700002405513700002605537700002305563700001705586700001805603700001405621700002405635700002005659700002005679700002005699700002305719700002605742700002705768700001805795700002005813700001905833700002605852700001405878700002105892700002105913700002005934700002205954700002105976700002105997700002306018700001306041700002306054700001706077700002406094700001406118700001906132700001806151700001506169700001406184700001706198700002806215700002406243700001706267700002206284700001906306700002206325700002006347700002006367700002306387700002206410710003406432710002906466710002406495710002006519710003106539856003606570 2017 eng d a1546-171800aExome-wide association study of plasma lipids in >300,000 individuals.0 aExomewide association study of plasma lipids in 300000 individua c2017 Dec a1758-17660 v493 aWe screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.
10aCoronary Artery Disease10aDiabetes Mellitus, Type 210aExome10aGenetic Association Studies10aGenetic Predisposition to Disease10aGenetic Variation10aGenotype10aHumans10aLipids10aMacular Degeneration10aPhenotype10aRisk Factors1 aLiu, Dajiang, J1 aPeloso, Gina, M1 aYu, Haojie1 aButterworth, Adam, S1 aWang, Xiao1 aMahajan, Anubha1 aSaleheen, Danish1 aEmdin, Connor1 aAlam, Dewan1 aAlves, Alexessander, Couto1 aAmouyel, Philippe1 aDi Angelantonio, Emanuele1 aArveiler, Dominique1 aAssimes, Themistocles, L1 aAuer, Paul, L1 aBaber, Usman1 aBallantyne, Christie, M1 aBang, Lia, E1 aBenn, Marianne1 aBis, Joshua, C1 aBoehnke, Michael1 aBoerwinkle, Eric1 aBork-Jensen, Jette1 aBottinger, Erwin, P1 aBrandslund, Ivan1 aBrown, Morris1 aBusonero, Fabio1 aCaulfield, Mark, J1 aChambers, John, C1 aChasman, Daniel, I1 aChen, Eugene1 aChen, Yii-Der Ida1 aChowdhury, Raj1 aChristensen, Cramer1 aChu, Audrey, Y1 aConnell, John, M1 aCucca, Francesco1 aCupples, Adrienne, L1 aDamrauer, Scott, M1 aDavies, Gail1 aDeary, Ian, J1 aDedoussis, George1 aDenny, Joshua, C1 aDominiczak, Anna1 aDubé, Marie-Pierre1 aEbeling, Tapani1 aEiriksdottir, Gudny1 aEsko, Tõnu1 aFarmaki, Aliki-Eleni1 aFeitosa, Mary, F1 aFerrario, Marco1 aFerrieres, Jean1 aFord, Ian1 aFornage, Myriam1 aFranks, Paul, W1 aFrayling, Timothy, M1 aFrikke-Schmidt, Ruth1 aFritsche, Lars, G1 aFrossard, Philippe1 aFuster, Valentin1 aGanesh, Santhi, K1 aGao, Wei1 aGarcia, Melissa, E1 aGieger, Christian1 aGiulianini, Franco1 aGoodarzi, Mark, O1 aGrallert, Harald1 aGrarup, Niels1 aGroop, Leif1 aGrove, Megan, L1 aGudnason, Vilmundur1 aHansen, Torben1 aHarris, Tamara, B1 aHayward, Caroline1 aHirschhorn, Joel, N1 aHolmen, Oddgeir, L1 aHuffman, Jennifer1 aHuo, Yong1 aHveem, Kristian1 aJabeen, Sehrish1 aJackson, Anne, U1 aJakobsdottir, Johanna1 aJarvelin, Marjo-Riitta1 aJensen, Gorm, B1 aJørgensen, Marit, E1 aJukema, Wouter1 aJustesen, Johanne, M1 aKamstrup, Pia, R1 aKanoni, Stavroula1 aKarpe, Fredrik1 aKee, Frank1 aKhera, Amit, V1 aKlarin, Derek1 aKoistinen, Heikki, A1 aKooner, Jaspal, S1 aKooperberg, Charles1 aKuulasmaa, Kari1 aKuusisto, Johanna1 aLaakso, Markku1 aLakka, Timo1 aLangenberg, Claudia1 aLangsted, Anne1 aLauner, Lenore, J1 aLauritzen, Torsten1 aLiewald, David, C M1 aLin, Li, An1 aLinneberg, Allan1 aLoos, Ruth, J F1 aLu, Yingchang1 aLu, Xiangfeng1 aMägi, Reedik1 aMälarstig, Anders1 aManichaikul, Ani1 aManning, Alisa, K1 aMäntyselkä, Pekka1 aMarouli, Eirini1 aMasca, Nicholas, G D1 aMaschio, Andrea1 aMeigs, James, B1 aMelander, Olle1 aMetspalu, Andres1 aMorris, Andrew, P1 aMorrison, Alanna, C1 aMulas, Antonella1 aMüller-Nurasyid, Martina1 aMunroe, Patricia, B1 aNeville, Matt, J1 aNielsen, Jonas, B1 aNielsen, Sune, F1 aNordestgaard, Børge, G1 aOrdovas, Jose, M1 aMehran, Roxana1 aO'Donnell, Christoper, J1 aOrho-Melander, Marju1 aMolony, Cliona, M1 aMuntendam, Pieter1 aPadmanabhan, Sandosh1 aPalmer, Colin, N A1 aPasko, Dorota1 aPatel, Aniruddh, P1 aPedersen, Oluf1 aPerola, Markus1 aPeters, Annette1 aPisinger, Charlotta1 aPistis, Giorgio1 aPolasek, Ozren1 aPoulter, Neil1 aPsaty, Bruce, M1 aRader, Daniel, J1 aRasheed, Asif1 aRauramaa, Rainer1 aReilly, Dermot, F1 aReiner, Alex, P1 aRenstrom, Frida1 aRich, Stephen, S1 aRidker, Paul, M1 aRioux, John, D1 aRobertson, Neil, R1 aRoden, Dan, M1 aRotter, Jerome, I1 aRudan, Igor1 aSalomaa, Veikko1 aSamani, Nilesh, J1 aSanna, Serena1 aSattar, Naveed1 aSchmidt, Ellen, M1 aScott, Robert, A1 aSever, Peter1 aSevilla, Raquel, S1 aShaffer, Christian, M1 aSim, Xueling1 aSivapalaratnam, Suthesh1 aSmall, Kerrin, S1 aSmith, Albert, V1 aSmith, Blair, H1 aSomayajula, Sangeetha1 aSoutham, Lorraine1 aSpector, Timothy, D1 aSpeliotes, Elizabeth, K1 aStarr, John, M1 aStirrups, Kathleen, E1 aStitziel, Nathan1 aStrauch, Konstantin1 aStringham, Heather, M1 aSurendran, Praveen1 aTada, Hayato1 aTall, Alan, R1 aTang, Hua1 aTardif, Jean-Claude1 aTaylor, Kent, D1 aTrompet, Stella1 aTsao, Philip, S1 aTuomilehto, Jaakko1 aTybjaerg-Hansen, Anne1 avan Zuydam, Natalie, R1 aVarbo, Anette1 aVarga, Tibor, V1 aVirtamo, Jarmo1 aWaldenberger, Melanie1 aWang, Nan1 aWareham, Nick, J1 aWarren, Helen, R1 aWeeke, Peter, E1 aWeinstock, Joshua1 aWessel, Jennifer1 aWilson, James, G1 aWilson, Peter, W F1 aXu, Ming1 aYaghootkar, Hanieh1 aYoung, Robin1 aZeggini, Eleftheria1 aZhang, He1 aZheng, Neil, S1 aZhang, Weihua1 aZhang, Yan1 aZhou, Wei1 aZhou, Yanhua1 aZoledziewska, Magdalena1 aHowson, Joanna, M M1 aDanesh, John1 aMcCarthy, Mark, I1 aCowan, Chad, A1 aAbecasis, Goncalo1 aDeloukas, Panos1 aMusunuru, Kiran1 aWiller, Cristen, J1 aKathiresan, Sekar1 aCharge Diabetes Working Group1 aEPIC-InterAct Consortium1 aEPIC-CVD Consortium1 aGOLD Consortium1 aVA Million Veteran Program uhttps://chs-nhlbi.org/node/757317687nas a2205785 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2017 eng d a1546-171800aRare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease.0 aRare coding variants in PLCG2 ABI3 and TREM2 implicate microglia c2017 Sep a1373-13840 v493 aWe identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.
10aAdaptor Proteins, Signal Transducing10aAlzheimer Disease10aAmino Acid Sequence10aCase-Control Studies10aExome10aGene Expression Profiling10aGene Frequency10aGenetic Predisposition to Disease10aGenotype10aHumans10aImmunity, Innate10aLinkage Disequilibrium10aMembrane Glycoproteins10aMicroglia10aOdds Ratio10aPhospholipase C gamma10aPolymorphism, Single Nucleotide10aProtein Interaction Maps10aReceptors, Immunologic10aSequence Homology, Amino Acid1 aSims, Rebecca1 avan der Lee, Sven, J1 aNaj, Adam, C1 aBellenguez, Céline1 aBadarinarayan, Nandini1 aJakobsdottir, Johanna1 aKunkle, Brian, W1 aBoland, Anne1 aRaybould, Rachel1 aBis, Joshua, C1 aMartin, Eden, R1 aGrenier-Boley, Benjamin1 aHeilmann-Heimbach, Stefanie1 aChouraki, Vincent1 aKuzma, Amanda, B1 aSleegers, Kristel1 aVronskaya, Maria1 aRuiz, Agustin1 aGraham, Robert, R1 aOlaso, Robert1 aHoffmann, Per1 aGrove, Megan, L1 aVardarajan, Badri, N1 aHiltunen, Mikko1 aNöthen, Markus, M1 aWhite, Charles, C1 aHamilton-Nelson, Kara, L1 aEpelbaum, Jacques1 aMaier, Wolfgang1 aChoi, Seung-Hoan1 aBeecham, Gary, W1 aDulary, Cécile1 aHerms, Stefan1 aSmith, Albert, V1 aFunk, Cory, C1 aDerbois, Céline1 aForstner, Andreas, J1 aAhmad, Shahzad1 aLi, Hongdong1 aBacq, Delphine1 aHarold, Denise1 aSatizabal, Claudia, L1 aValladares, Otto1 aSquassina, Alessio1 aThomas, Rhodri1 aBrody, Jennifer, A1 aQu, Liming1 aSánchez-Juan, Pascual1 aMorgan, Taniesha1 aWolters, Frank, J1 aZhao, Yi1 aGarcia, Florentino, Sanchez1 aDenning, Nicola1 aFornage, Myriam1 aMalamon, John1 aNaranjo, Maria, Candida De1 aMajounie, Elisa1 aMosley, Thomas, H1 aDombroski, Beth1 aWallon, David1 aLupton, Michelle, K1 aDupuis, Josée1 aWhitehead, Patrice1 aFratiglioni, Laura1 aMedway, Christopher1 aJian, Xueqiu1 aMukherjee, Shubhabrata1 aKeller, Lina1 aBrown, Kristelle1 aLin, Honghuang1 aCantwell, Laura, B1 aPanza, Francesco1 aMcGuinness, Bernadette1 aMoreno-Grau, Sonia1 aBurgess, Jeremy, D1 aSolfrizzi, Vincenzo1 aProitsi, Petra1 aAdams, Hieab, H1 aAllen, Mariet1 aSeripa, Davide1 aPastor, Pau1 aCupples, Adrienne, L1 aPrice, Nathan, D1 aHannequin, Didier1 aFrank-García, Ana1 aLevy, Daniel1 aChakrabarty, Paramita1 aCaffarra, Paolo1 aGiegling, Ina1 aBeiser, Alexa, S1 aGiedraitis, Vilmantas1 aHampel, Harald1 aGarcia, Melissa, E1 aWang, Xue1 aLannfelt, Lars1 aMecocci, Patrizia1 aEiriksdottir, Gudny1 aCrane, Paul, K1 aPasquier, Florence1 aBoccardi, Virginia1 aHenández, Isabel1 aBarber, Robert, C1 aScherer, Martin1 aTarraga, Lluis1 aAdams, Perrie, M1 aLeber, Markus1 aChen, Yuning1 aAlbert, Marilyn, S1 aRiedel-Heller, Steffi1 aEmilsson, Valur1 aBeekly, Duane1 aBraae, Anne1 aSchmidt, Reinhold1 aBlacker, Deborah1 aMasullo, Carlo1 aSchmidt, Helena1 aDoody, Rachelle, S1 aSpalletta, Gianfranco1 aJr, W, T Longstre1 aFairchild, Thomas, J1 aBossù, Paola1 aLopez, Oscar, L1 aFrosch, Matthew, P1 aSacchinelli, Eleonora1 aGhetti, Bernardino1 aYang, Qiong1 aHuebinger, Ryan, M1 aJessen, Frank1 aLi, Shuo1 aKamboh, Ilyas1 aMorris, John1 aSotolongo-Grau, Oscar1 aKatz, 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L1 aApostolova, Liana, G1 aArnold, Steven, E1 aAsthana, Sanjay1 aAtwood, Craig, S1 aBaldwin, Clinton, T1 aBarnes, Lisa, L1 aBarral, Sandra1 aBeach, Thomas, G1 aBecker, James, T1 aBigio, Eileen, H1 aBird, Thomas, D1 aBoeve, Bradley, F1 aBowen, James, D1 aBoxer, Adam1 aBurke, James, R1 aBurns, Jeffrey, M1 aBuxbaum, Joseph, D1 aCairns, Nigel, J1 aCao, Chuanhai1 aCarlson, Chris, S1 aCarlsson, Cynthia, M1 aCarney, Regina, M1 aCarrasquillo, Minerva, M1 aCarroll, Steven, L1 aDiaz, Carolina, Ceballos1 aChui, Helena, C1 aClark, David, G1 aCribbs, David, H1 aCrocco, Elizabeth, A1 aDeCarli, Charles1 aDick, Malcolm1 aDuara, Ranjan1 aEvans, Denis, A1 aFaber, Kelley, M1 aFallon, Kenneth, B1 aFardo, David, W1 aFarlow, Martin, R1 aFerris, Steven1 aForoud, Tatiana, M1 aGalasko, Douglas, R1 aGearing, Marla1 aGeschwind, Daniel, H1 aGilbert, John, R1 aGraff-Radford, Neill, R1 aGreen, Robert, C1 aGrowdon, John, H1 aHamilton, Ronald, L1 aHarrell, Lindy, E1 aHonig, Lawrence, S1 aHuentelman, Matthew, J1 aHulette, Christine, M1 aHyman, Bradley, T1 aJarvik, Gail, P1 aAbner, Erin1 aJin, Lee-Way1 aJun, Gyungah1 aKarydas, Anna1 aKaye, Jeffrey, A1 aKim, Ronald1 aKowall, Neil, W1 aKramer, Joel, H1 aLaFerla, Frank, M1 aLah, James, J1 aLeverenz, James, B1 aLevey, Allan, I1 aLi, Ge1 aLieberman, Andrew, P1 aLunetta, Kathryn, L1 aLyketsos, Constantine, G1 aMarson, Daniel, C1 aMartiniuk, Frank1 aMash, Deborah, C1 aMasliah, Eliezer1 aMcCormick, Wayne, C1 aMcCurry, Susan, M1 aMcDavid, Andrew, N1 aMcKee, Ann, C1 aMesulam, Marsel1 aMiller, Bruce, L1 aMiller, Carol, A1 aMiller, Joshua, W1 aMorris, John, C1 aMurrell, Jill, R1 aMyers, Amanda, J1 aO'Bryant, Sid1 aOlichney, John, M1 aPankratz, Vernon, S1 aParisi, Joseph, E1 aPaulson, Henry, L1 aPerry, William1 aPeskind, Elaine1 aPierce, Aimee1 aPoon, Wayne, W1 aPotter, Huntington1 aQuinn, Joseph, F1 aRaj, Ashok1 aRaskind, Murray1 aReisberg, Barry1 aReitz, Christiane1 aRingman, John, M1 aRoberson, Erik, D1 aRogaeva, Ekaterina1 aRosen, Howard, J1 aRosenberg, Roger, N1 aSager, Mark, A1 aSaykin, Andrew, J1 aSchneider, Julie, A1 aSchneider, Lon, S1 aSeeley, William, W1 aSmith, Amanda, G1 aSonnen, Joshua, A1 aSpina, Salvatore1 aStern, Robert, A1 aSwerdlow, Russell, H1 aTanzi, Rudolph, E1 aThornton-Wells, Tricia, A1 aTrojanowski, John, Q1 aTroncoso, Juan, C1 aVan Deerlin, Vivianna, M1 aVan Eldik, Linda, J1 aVinters, Harry, V1 aVonsattel, Jean, Paul1 aWeintraub, Sandra1 aWelsh-Bohmer, Kathleen, A1 aWilhelmsen, Kirk, C1 aWilliamson, Jennifer1 aWingo, Thomas, S1 aWoltjer, Randall, L1 aWright, Clinton, B1 aYu, Chang-En1 aYu, Lei1 aGarzia, Fabienne1 aGolamaully, Feroze1 aSeptier, Gislain1 aEngelborghs, Sebastien1 aVandenberghe, Rik1 aDe Deyn, Peter, P1 aFernadez, Carmen, Muñoz1 aBenito, Yoland, Aladro1 aThonberg, Håkan1 aForsell, Charlotte1 aLilius, Lena1 aKinhult-Ståhlbom, Anne1 aKilander, Lena1 aBrundin, RoseMarie1 aConcari, Letizia1 aHelisalmi, Seppo1 aKoivisto, Anne, Maria1 aHaapasalo, Annakaisa1 aDermecourt, Vincent1 aFiévet, Nathalie1 aHanon, Olivier1 aDufouil, Carole1 aBrice, Alexis1 aRitchie, Karen1 aDubois, Bruno1 aHimali, Jayanadra, J1 aKeene, Dirk1 aTschanz, JoAnn1 aFitzpatrick, Annette, L1 aKukull, Walter, A1 aNorton, Maria1 aAspelund, Thor1 aLarson, Eric, B1 aMunger, Ron1 aRotter, Jerome, I1 aLipton, Richard, B1 aBullido, María, J1 aHofman, Albert1 aMontine, Thomas, J1 aCoto, Eliecer1 aBoerwinkle, Eric1 aPetersen, Ronald, C1 aAlvarez, Victoria1 aRivadeneira, Fernando1 aReiman, Eric, M1 aGallo, Maura1 aO'Donnell, Christopher, J1 aReisch, Joan, S1 aBruni, Amalia, Cecilia1 aRoyall, Donald, R1 aDichgans, Martin1 aSano, Mary1 aGalimberti, Daniela1 aSt George-Hyslop, Peter1 aScarpini, Elio1 aTsuang, Debby, W1 aMancuso, Michelangelo1 aBonuccelli, Ubaldo1 aWinslow, Ashley, R1 aDaniele, Antonio1 aWu, Chuang-Kuo1 aPeters, Oliver1 aNacmias, Benedetta1 aRiemenschneider, Matthias1 aHeun, Reinhard1 aBrayne, Carol1 aRubinsztein, David, C1 aBras, Jose1 aGuerreiro, Rita1 aAl-Chalabi, Ammar1 aShaw, Christopher, E1 aCollinge, John1 aMann, David1 aTsolaki, Magda1 aClarimon, Jordi1 aSussams, Rebecca1 aLovestone, Simon1 aO'Donovan, Michael, C1 aOwen, Michael, J1 aBehrens, Timothy, W1 aMead, Simon1 aGoate, Alison, M1 aUitterlinden, André, G1 aHolmes, Clive1 aCruchaga, Carlos1 aIngelsson, Martin1 aBennett, David, A1 aPowell, John1 aGolde, Todd, E1 aGraff, Caroline1 aDe Jager, Philip, L1 aMorgan, Kevin1 aErtekin-Taner, Nilufer1 aCombarros, Onofre1 aPsaty, Bruce, M1 aPassmore, Peter1 aYounkin, Steven, G1 aBerr, Claudine1 aGudnason, Vilmundur1 aRujescu, Dan1 aDickson, Dennis, W1 aDartigues, Jean-François1 aDeStefano, Anita, L1 aOrtega-Cubero, Sara1 aHakonarson, Hakon1 aCampion, Dominique1 aBoada, Merce1 aKauwe, John, Keoni1 aFarrer, Lindsay, A1 aVan Broeckhoven, Christine1 aIkram, Arfan, M1 aJones, Lesley1 aHaines, Jonathan, L1 aTzourio, Christophe1 aLauner, Lenore, J1 aEscott-Price, Valentina1 aMayeux, Richard1 aDeleuze, Jean-Francois1 aAmin, Najaf1 aHolmans, Peter, A1 aPericak-Vance, Margaret, A1 aAmouyel, Philippe1 aDuijn, Cornelia, M1 aRamirez, Alfredo1 aSan Wang, Li-1 aLambert, Jean-Charles1 aSeshadri, Sudha1 aWilliams, Julie1 aSchellenberg, Gerard, D1 aARUK Consortium1 aGERAD/PERADES, CHARGE, ADGC, EADI uhttps://chs-nhlbi.org/node/758703116nas a2200673 4500008004100000022001400041245012500055210006900180260001500249300000900264490000600273520115900279653001001438653003801448653004501486653001101531653002601542653002701568653003101595653003801626653003301664653001401697100001801711700001301729700002301742700001901765700001901784700002501803700001601828700002001844700003001864700001901894700001301913700001901926700002101945700002001966700001701986700001302003700001902016700002102035700002402056700001902080700001302099700002802112700001902140700001602159700002202175700002102197700001902218700002202237700002302259700002102282700002002303700002102323700002102344700002202365700001902387856003602406 2018 eng d a2041-172300aLarge-scale whole-exome sequencing association studies identify rare functional variants influencing serum urate levels.0 aLargescale wholeexome sequencing association studies identify ra c2018 10 12 a42280 v93 aElevated serum urate levels can cause gout, an excruciating disease with suboptimal treatment. Previous GWAS identified common variants with modest effects on serum urate. Here we report large-scale whole-exome sequencing association studies of serum urate and kidney function among ≤19,517 European ancestry and African-American individuals. We identify aggregate associations of low-frequency damaging variants in the urate transporters SLC22A12 (URAT1; p = 1.3 × 10) and SLC2A9 (p = 4.5 × 10). Gout risk in rare SLC22A12 variant carriers is halved (OR = 0.5, p = 4.9 × 10). Selected rare variants in SLC22A12 are validated in transport studies, confirming three as loss-of-function (R325W, R405C, and T467M) and illustrating the therapeutic potential of the new URAT1-blocker lesinurad. In SLC2A9, mapping of rare variants of large effects onto the predicted protein structure reveals new residues that may affect urate binding. These findings provide new insights into the genetic architecture of serum urate, and highlight molecular targets in SLC22A12 and SLC2A9 for lowering serum urate and preventing gout.
10aExome10aGenetic Predisposition to Disease10aGlucose Transport Proteins, Facilitative10aHumans10aKidney Function Tests10aMeta-Analysis as Topic10aOrganic Anion Transporters10aOrganic Cation Transport Proteins10aProtein Structure, Secondary10aUric Acid1 aTin, Adrienne1 aLi, Yong1 aBrody, Jennifer, A1 aNutile, Teresa1 aChu, Audrey, Y1 aHuffman, Jennifer, E1 aYang, Qiong1 aChen, Ming-Huei1 aRobinson-Cohen, Cassianne1 aMace, Aurelien1 aLiu, Jun1 aDemirkan, Ayse1 aSorice, Rossella1 aSedaghat, Sanaz1 aSwen, Melody1 aYu, Bing1 aGhasemi, Sahar1 aTeumer, Alexanda1 aVollenweider, Peter1 aCiullo, Marina1 aLi, Meng1 aUitterlinden, André, G1 aKraaij, Robert1 aAmin, Najaf1 avan Rooij, Jeroen1 aKutalik, Zoltán1 aDehghan, Abbas1 aMcKnight, Barbara1 aDuijn, Cornelia, M1 aMorrison, Alanna1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aFox, Caroline, S1 aWoodward, Owen, M1 aKöttgen, Anna uhttps://chs-nhlbi.org/node/792806377nas a2201849 4500008004100000022001400041245011300055210006900168260001500237300000900252490000700261520114200268653001001410653003701420653001501457653003001472653001801502653001001520653003801530653001301568653001101581653003101592653001501623653002001638100002301658700002401681700001601705700002001721700001701741700002001758700002001778700001801798700001601816700001901832700001901851700002001870700002101890700001901911700002401930700001501954700003101969700001602000700002902016700001802045700001902063700002102082700002502103700002102128700002202149700002702171700002202198700002002220700001702240700001802257700002002275700001902295700002902314700002102343700001902364700002302383700002802406700001902434700003102453700002802484700002202512700002102534700003602555700002402591700001802615700001602633700001702649700002402666700001502690700002002705700001902725700002602744700002402770700003202794700002102826700002602847700002502873700002002898700001702918700002002935700002502955700002602980700002203006700001903028700001903047700001803066700002003084700001703104700002103121700002103142700001703163700002003180700002303200700002003223700003603243700002003279700002203299700002603321700002103347700002203368700002403390700001903414700002203433700003003455700001903485700002303504700002103527700001903548700001903567700002003586700002003606700002503626700003103651700002103682700002203703700002103725700002303746700001703769700001603786700002103802700001803823700002403841700002403865700001803889700001903907700002203926700001903948700002003967700002103987700002204008700002204030700002304052700002404075700002004099700002704119700002104146700002104167700001904188700001904207700001804226700002204244700002104266700002004287700002004307700002304327700002604350700002104376700002004397700002504417700002104442710002804463856003604491 2021 eng d a2041-172300aDeterminants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.0 aDeterminants of penetrance and variable expressivity in monogeni c2021 06 09 a35050 v123 aHundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
10aAdult10aBiological Variation, Population10aBiomarkers10aDiabetes Mellitus, Type 210aDyslipidemias10aExome10aGenetic Predisposition to Disease10aGenotype10aHumans10aMultifactorial Inheritance10aPenetrance10aRisk Assessment1 aGoodrich, Julia, K1 aSinger-Berk, Moriel1 aSon, Rachel1 aSveden, Abigail1 aWood, Jordan1 aEngland, Eleina1 aCole, Joanne, B1 aWeisburd, Ben1 aWatts, Nick1 aCaulkins, Lizz1 aDornbos, Peter1 aKoesterer, Ryan1 aZappala, Zachary1 aZhang, Haichen1 aMaloney, Kristin, A1 aDahl, Andy1 aAguilar-Salinas, Carlos, A1 aAtzmon, Gil1 aBarajas-Olmos, Francisco1 aBarzilai, Nir1 aBlangero, John1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBottinger, Erwin1 aBowden, Donald, W1 aCenteno-Cruz, Federico1 aChambers, John, C1 aChami, Nathalie1 aChan, Edmund1 aChan, Juliana1 aCheng, Ching-Yu1 aCho, Yoon Shin1 aContreras-Cubas, Cecilia1 aCórdova, Emilio1 aCorrea, Adolfo1 aDeFronzo, Ralph, A1 aDuggirala, Ravindranath1 aDupuis, Josée1 aGaray-Sevilla, Ma, Eugenia1 aGarcía-Ortiz, Humberto1 aGieger, Christian1 aGlaser, Benjamin1 aGonzález-Villalpando, Clicerio1 aGonzalez, Ma, Elena1 aGrarup, Niels1 aGroop, Leif1 aGross, Myron1 aHaiman, Christopher1 aHan, Sohee1 aHanis, Craig, L1 aHansen, Torben1 aHeard-Costa, Nancy, L1 aHenderson, Brian, E1 aHernandez, Juan, Manuel Mal1 aHwang, Mi, Yeong1 aIslas-Andrade, Sergio1 aJørgensen, Marit, E1 aKang, Hyun, Min1 aKim, Bong-Jo1 aKim, Young, Jin1 aKoistinen, Heikki, A1 aKooner, Jaspal, Singh1 aKuusisto, Johanna1 aKwak, Soo-Heon1 aLaakso, Markku1 aLange, Leslie1 aLee, Jong-Young1 aLee, Juyoung1 aLehman, Donna, M1 aLinneberg, Allan1 aLiu, Jianjun1 aLoos, Ruth, J F1 aLyssenko, Valeriya1 aMa, Ronald, C W1 aMartínez-Hernández, Angélica1 aMeigs, James, B1 aMeitinger, Thomas1 aMendoza-Caamal, Elvia1 aMohlke, Karen, L1 aMorris, Andrew, D1 aMorrison, Alanna, C1 aC Y Ng, Maggie1 aNilsson, Peter, M1 aO'Donnell, Christopher, J1 aOrozco, Lorena1 aPalmer, Colin, N A1 aPark, Kyong, Soo1 aPost, Wendy, S1 aPedersen, Oluf1 aPreuss, Michael1 aPsaty, Bruce, M1 aReiner, Alexander, P1 aRevilla-Monsalve, Cristina1 aRich, Stephen, S1 aRotter, Jerome, I1 aSaleheen, Danish1 aSchurmann, Claudia1 aSim, Xueling1 aSladek, Rob1 aSmall, Kerrin, S1 aSo, Wing, Yee1 aSpector, Timothy, D1 aStrauch, Konstantin1 aStrom, Tim, M1 aTai, Shyong, E1 aTam, Claudia, H T1 aTeo, Yik, Ying1 aThameem, Farook1 aTomlinson, Brian1 aTracy, Russell, P1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 avan Dam, Rob, M1 aVasan, Ramachandran, S1 aWilson, James, G1 aWitte, Daniel, R1 aWong, Tien-Yin1 aBurtt, Noel, P1 aZaitlen, Noah1 aMcCarthy, Mark, I1 aBoehnke, Michael1 aPollin, Toni, I1 aFlannick, Jason1 aMercader, Josep, M1 aO'Donnell-Luria, Anne1 aBaxter, Samantha1 aFlorez, Jose, C1 aMacArthur, Daniel, G1 aUdler, Miriam, S1 aAMP-T2D-GENES Consortia uhttps://chs-nhlbi.org/node/877408881nas a2202605 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2022 eng d a1537-660500aRare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.0 aRare coding variants in 35 genes associate with circulating lipi c2022 01 06 a81-960 v1093 aLarge-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
10aAlleles10aBlood Glucose10aCase-Control Studies10aComputational Biology10aDatabases, Genetic10aDiabetes Mellitus, Type 210aExome10aGenetic Predisposition to Disease10aGenetic Variation10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLipid Metabolism10aLipids10aLiver10aMolecular Sequence Annotation10aMultifactorial Inheritance10aOpen Reading Frames10aPhenotype10aPolymorphism, Single Nucleotide1 aHindy, George1 aDornbos, Peter1 aChaffin, Mark, D1 aLiu, Dajiang, J1 aWang, Minxian1 aSelvaraj, Margaret, Sunitha1 aZhang, David1 aPark, Joseph1 aAguilar-Salinas, Carlos, A1 aAntonacci-Fulton, Lucinda1 aArdissino, Diego1 aArnett, Donna, K1 aAslibekyan, Stella1 aAtzmon, Gil1 aBallantyne, Christie, M1 aBarajas-Olmos, Francisco1 aBarzilai, Nir1 aBecker, Lewis, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBottinger, Erwin1 aBowden, Donald, W1 aBown, Matthew, J1 aBrody, Jennifer, A1 aBroome, Jai, G1 aBurtt, Noel, P1 aCade, Brian, E1 aCenteno-Cruz, Federico1 aChan, Edmund1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aCheng, Ching-Yu1 aChoi, Won, Jung1 aChowdhury, Raj1 aContreras-Cubas, Cecilia1 aCórdova, Emilio, J1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDanesh, John1 ade Vries, Paul, S1 aDeFronzo, Ralph, A1 aDoddapaneni, Harsha1 aDuggirala, Ravindranath1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aFlorez, Jose, C1 aFornage, Myriam1 aFreedman, Barry, I1 aFuster, Valentin1 aGaray-Sevilla, Ma, Eugenia1 aGarcía-Ortiz, Humberto1 aGermer, Soren1 aGibbs, Richard, A1 aGieger, Christian1 aGlaser, Benjamin1 aGonzalez, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGraff, Mariaelisa1 aGraham, Sarah, E1 aGrarup, Niels1 aGroop, Leif, C1 aGuo, Xiuqing1 aGupta, Namrata1 aHan, Sohee1 aHanis, Craig, L1 aHansen, Torben1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aIrvin, Marguerite, R1 aIslas-Andrade, Sergio1 aJarvik, Gail, P1 aKang, Hyun, Min1 aKardia, Sharon, L R1 aKelly, Tanika1 aKenny, Eimear, E1 aKhan, Alyna, T1 aKim, Bong-Jo1 aKim, Ryan, W1 aKim, Young, Jin1 aKoistinen, Heikki, A1 aKooperberg, Charles1 aKuusisto, Johanna1 aKwak, Soo, Heon1 aLaakso, Markku1 aLange, Leslie, A1 aLee, Jiwon1 aLee, Juyoung1 aLee, Seonwook1 aLehman, Donna, M1 aLemaitre, Rozenn, N1 aLinneberg, Allan1 aLiu, Jianjun1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aLyssenko, Valeriya1 aMa, Ronald, C W1 aMartin, Lisa, Warsinger1 aMartínez-Hernández, Angélica1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMcPherson, Ruth1 aMeigs, James, B1 aMeitinger, Thomas1 aMelander, Olle1 aMendoza-Caamal, Elvia1 aMetcalf, Ginger, A1 aMi, Xuenan1 aMohlke, Karen, L1 aMontasser, May, E1 aMoon, Jee-Young1 aMoreno-Macias, Hortensia1 aMorrison, Alanna, C1 aMuzny, Donna, M1 aNelson, Sarah, C1 aNilsson, Peter, M1 aO'Connell, Jeffrey, R1 aOrho-Melander, Marju1 aOrozco, Lorena1 aPalmer, Colin, N A1 aPalmer, Nicholette, D1 aPark, Cheol, Joo1 aPark, Kyong, Soo1 aPedersen, Oluf1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aPost, Wendy, S1 aPreuss, Michael1 aPsaty, Bruce, M1 aQi, Qibin1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRevilla-Monsalve, Cristina1 aRich, Stephen, S1 aSamani, Nilesh1 aSchunkert, Heribert1 aSchurmann, Claudia1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSim, Xueling1 aSladek, Rob1 aSmall, Kerrin, S1 aSo, Wing, Yee1 aStilp, Adrienne, M1 aTai, Shyong, E1 aTam, Claudia, H T1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aThameem, Farook1 aTomlinson, Brian1 aTsai, Michael, Y1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 avan Dam, Rob, M1 aVasan, Ramachandran, S1 aMartinez, Karine, A Viaud1 aWang, Fei, Fei1 aWang, Xuzhi1 aWatkins, Hugh1 aWeeks, Daniel, E1 aWilson, James, G1 aWitte, Daniel, R1 aWong, Tien-Yin1 aYanek, Lisa, R1 aKathiresan, Sekar1 aRader, Daniel, J1 aRotter, Jerome, I1 aBoehnke, Michael1 aMcCarthy, Mark, I1 aWiller, Cristen, J1 aNatarajan, Pradeep1 aFlannick, Jason, A1 aKhera, Amit, V1 aPeloso, Gina, M1 aAMP-T2D-GENES, Myocardial Infarction Genetics Consortium1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aNHLBI TOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/897502608nas a2200541 4500008004100000022001400041245006100055210005800116260001600174300000800190490000700198520111600205653002201321653002601343653001801369653001001387653001301397653001101410100002001421700001701441700001701458700002101475700002101496700002601517700002201543700001901565700002901584700001501613700001801628700002101646700001801667700002001685700002301705700002101728700002001749700002001769700001901789700002101808700002801829700002301857700002101880700002101901700001701922700002801939700001801967710004501985856003602030 2024 eng d a2041-172300aHuman whole-exome genotype data for Alzheimer's disease.0 aHuman wholeexome genotype data for Alzheimers disease c2024 Jan 23 a6840 v153 aThe heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer's Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.
10aAlzheimer Disease10aComputational Biology10aData Accuracy10aExome10aGenotype10aHumans1 aLeung, Yuk, Yee1 aNaj, Adam, C1 aChou, Yi-Fan1 aValladares, Otto1 aSchmidt, Michael1 aHamilton-Nelson, Kara1 aWheeler, Nicholas1 aLin, Honghuang1 aGangadharan, Prabhakaran1 aQu, Liming1 aClark, Kaylyn1 aKuzma, Amanda, B1 aLee, Wan-Ping1 aCantwell, Laura1 aNicaretta, Heather1 aHaines, Jonathan1 aFarrer, Lindsay1 aSeshadri, Sudha1 aBrkanac, Zoran1 aCruchaga, Carlos1 aPericak-Vance, Margaret1 aMayeux, Richard, P1 aBush, William, S1 aDeStefano, Anita1 aMartin, Eden1 aSchellenberg, Gerard, D1 aSan Wang, Li-1 aAlzheimer’s Disease Sequencing Project uhttps://chs-nhlbi.org/node/9577