01904nas a2200577 4500008004100000022001400041245010300055210006900158260001600227300001400243490000700257100002300264700002400287700001900311700002600330700002200356700002500378700002000403700002000423700002400443700002000467700002200487700002700509700001900536700002400555700002300579700002100602700001800623700002200641700002800663700003000691700002100721700002100742700002400763700002300787700002300810700002100833700002500854700002700879700002100906700002200927700002100949700002100970700002000991700002501011710006501036710008501101710005101186710005301237856003601290 2017 eng d a1546-171800aAnalysis commons, a team approach to discovery in a big-data environment for genetic epidemiology.0 aAnalysis commons a team approach to discovery in a bigdata envir c2017 Oct 27 a1560-15630 v491 aBrody, Jennifer, A1 aMorrison, Alanna, C1 aBis, Joshua, C1 aO'Connell, Jeffrey, R1 aBrown, Michael, R1 aHuffman, Jennifer, E1 aAmes, Darren, C1 aCarroll, Andrew1 aConomos, Matthew, P1 aGabriel, Stacey1 aGibbs, Richard, A1 aGogarten, Stephanie, M1 aGupta, Namrata1 aJaquish, Cashell, E1 aJohnson, Andrew, D1 aLewis, Joshua, P1 aLiu, Xiaoming1 aManning, Alisa, K1 aPapanicolaou, George, J1 aPitsillides, Achilleas, N1 aRice, Kenneth, M1 aSalerno, William1 aSitlani, Colleen, M1 aSmith, Nicholas, L1 aHeckbert, Susan, R1 aLaurie, Cathy, C1 aMitchell, Braxton, D1 aVasan, Ramachandran, S1 aRich, Stephen, S1 aRotter, Jerome, I1 aWilson, James, G1 aBoerwinkle, Eric1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aCohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium1 aTOPMed Hematology and Hemostasis Working Group1 aCHARGE Analysis and Bioinformatics Working Group uhttps://chs-nhlbi.org/node/755306994nas a2202101 4500008004100000022001400041245009900055210006900154260001600223300001000239490000600249520104500255100001901300700001901319700002301338700002201361700001701383700001601400700002801416700002201444700001901466700001801485700002201503700002701525700002201552700002301574700001901597700002001616700001801636700002201654700002301676700002201699700002001721700002801741700002801769700002201797700002001819700002701839700003001866700001901896700001701915700002201932700002201954700001801976700001701994700002102011700002702032700002202059700002302081700002202104700001902126700001702145700001802162700002002180700002202200700002502222700002102247700001802268700002102286700002002307700002302327700002202350700002702372700002102399700002102420700002402441700001902465700002102484700002002505700002102525700001902546700002502565700001902590700002602609700002602635700002102661700001902682700002402701700002002725700002602745700001902771700002102790700002002811700002402831700001702855700001802872700002402890700002102914700002202935700001302957700001202970700001902982700002403001700001803025700002503043700002203068700002003090700002203110700003903132700002103171700001803192700002203210700001903232700001803251700002003269700001703289700001903306700002403325700001703349700002003366700002003386700002003406700002303426700002703449700002203476700002103498700002203519700002303541700002403564700002203588700002103610700002203631700002303653700003203676700002403708700002203732700002003754700002803774700002403802700002003826700002203846700002503868700002203893700002803915700002403943700001803967700002603985700002404011700002304035700001704058700002004075700002304095700001804118700002204136700002304158700001504181700002104196700002004217700002704237700001904264700002004283700001904303700002404322700001504346700002204361700001504383700002804398700002404426700002904450700002004479700002504499700002204524700002204546700001904568700002204587700001704609700002304626700002204649700002604671700002704697700002704724700002304751700002104774700002204795700002004817700001904837856003604856 2017 eng d a2041-172300aGenetic loci associated with heart rate variability and their effects on cardiac disease risk.0 aGenetic loci associated with heart rate variability and their ef c2017 Jun 14 a158050 v83 a
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 (-0.741 aNolte, Ilja, M1 aMunoz, Loretto1 aTragante, Vinicius1 aAmare, Azmeraw, T1 aJansen, Rick1 aVaez, Ahmad1 avon der Heyde, Benedikt1 aAvery, Christy, L1 aBis, Joshua, C1 aDierckx, Bram1 avan Dongen, Jenny1 aGogarten, Stephanie, M1 aGoyette, Philippe1 aHernesniemi, Jussi1 aHuikari, Ville1 aHwang, Shih-Jen1 aJaju, Deepali1 aKerr, Kathleen, F1 aKluttig, Alexander1 aKrijthe, Bouwe, P1 aKumar, Jitender1 avan der Laan, Sander, W1 aLyytikäinen, Leo-Pekka1 aMaihofer, Adam, X1 aMinassian, Arpi1 avan der Most, Peter, J1 aMüller-Nurasyid, Martina1 aNivard, Michel1 aSalvi, Erika1 aStewart, James, D1 aThayer, Julian, F1 aVerweij, Niek1 aWong, Andrew1 aZabaneh, Delilah1 aZafarmand, Mohammad, H1 aAbdellaoui, Abdel1 aAlbarwani, Sulayma1 aAlbert, Christine1 aAlonso, Alvaro1 aAshar, Foram1 aAuvinen, Juha1 aAxelsson, Tomas1 aBaker, Dewleen, G1 ade Bakker, Paul, I W1 aBarcella, Matteo1 aBayoumi, Riad1 aBieringa, Rob, J1 aBoomsma, Dorret1 aBoucher, Gabrielle1 aBritton, Annie, R1 aChristophersen, Ingrid1 aDietrich, Andrea1 aEhret, George, B1 aEllinor, Patrick, T1 aEskola, Markku1 aFelix, Janine, F1 aFloras, John, S1 aFranco, Oscar, H1 aFriberg, Peter1 aGademan, Maaike, G J1 aGeyer, Mark, A1 aGiedraitis, Vilmantas1 aHartman, Catharina, A1 aHemerich, Daiane1 aHofman, Albert1 aHottenga, Jouke-Jan1 aHuikuri, Heikki1 aHutri-Kähönen, Nina1 aJouven, Xavier1 aJunttila, Juhani1 aJuonala, Markus1 aKiviniemi, Antti, M1 aKors, Jan, A1 aKumari, Meena1 aKuznetsova, Tatiana1 aLaurie, Cathy, C1 aLefrandt, Joop, D1 aLi, Yong1 aLi, Yun1 aLiao, Duanping1 aLimacher, Marian, C1 aLin, Henry, J1 aLindgren, Cecilia, M1 aLubitz, Steven, A1 aMahajan, Anubha1 aMcKnight, Barbara1 aSchwabedissen, Henriette, Meyer Zu1 aMilaneschi, Yuri1 aMononen, Nina1 aMorris, Andrew, P1 aNalls, Mike, A1 aNavis, Gerjan1 aNeijts, Melanie1 aNikus, Kjell1 aNorth, Kari, E1 aO'Connor, Daniel, T1 aOrmel, Johan1 aPerz, Siegfried1 aPeters, Annette1 aPsaty, Bruce, M1 aRaitakari, Olli, T1 aRisbrough, Victoria, B1 aSinner, Moritz, F1 aSiscovick, David1 aSmit, Johannes, H1 aSmith, Nicholas, L1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aStaessen, Jan, A1 aStein, Phyllis, K1 aStilp, Adrienne, M1 aStolarz-Skrzypek, Katarzyna1 aStrauch, Konstantin1 aSundström, Johan1 aSwenne, Cees, A1 aSyvänen, Ann-Christine1 aTardif, Jean-Claude1 aTaylor, Kent, D1 aTeumer, Alexander1 aThornton, Timothy, A1 aTinker, Lesley, E1 aUitterlinden, André, G1 avan Setten, Jessica1 aVoss, Andreas1 aWaldenberger, Melanie1 aWilhelmsen, Kirk, C1 aWillemsen, Gonneke1 aWong, Quenna1 aZhang, Zhu-Ming1 aZonderman, Alan, B1 aCusi, Daniele1 aEvans, Michele, K1 aGreiser, Halina, K1 aHarst, Pim1 aHassan, Mohammad1 aIngelsson, Erik1 aJarvelin, Marjo-Riitta1 aKääb, Stefan1 aKähönen, Mika1 aKivimaki, Mika1 aKooperberg, Charles1 aKuh, Diana1 aLehtimäki, Terho1 aLind, Lars1 aNievergelt, Caroline, M1 aO'Donnell, Chris, J1 aOldehinkel, Albertine, J1 aPenninx, Brenda1 aReiner, Alexander, P1 aRiese, Harriëtte1 avan Roon, Arie, M1 aRioux, John, D1 aRotter, Jerome, I1 aSofer, Tamar1 aStricker, Bruno, H1 aTiemeier, Henning1 aVrijkotte, Tanja, G M1 aAsselbergs, Folkert, W1 aBrundel, Bianca, J J M1 aHeckbert, Susan, R1 aWhitsel, Eric, A1 aHoed, Marcel, den1 aSnieder, Harold1 aGeus, Eco, J C uhttps://chs-nhlbi.org/node/757904580nas a2200937 4500008004100000022001400041245022100055210006900276260001300345300001200358490000700370520179400377100002102171700002402192700002202216700002202238700002702260700002202287700002002309700002102329700001602350700002102366700001602387700001202403700002102415700001902436700002302455700001902478700002302497700002102520700002402541700002502565700001502590700002102605700002902626700002202655700002302677700002202700700001902722700002002741700001702761700002202778700001202800700002002812700002102832700001802853700002302871700002302894700002902917700001802946700002502964700002102989700001903010700002503029700002403054700001903078700001703097700002303114700002003137700002403157700002203181700002003203700001803223700002003241700002503261700002803286700002403314700002103338700002403359700001903383700002103402700001703423700002903440700002403469700002203493700002703515700002003542700002303562700002103585856003603606 2017 eng d a1468-624400aA genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.0 agenomewide interaction analysis of tricyclictetracyclic antidepr c2017 May a313-3230 v543 aBACKGROUND: Increased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals.
METHODS AND RESULTS: We conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates. Among the populations of European ancestry, two genome-wide significant loci were identified for RR interval: rs6737205 in BRE (β=56.3, pinteraction=3.9e(-9)) and rs9830388 in UBE2E2 (β=25.2, pinteraction=1.7e(-8)). In Hispanic/Latino cohorts, rs2291477 in TGFBR3 significantly modified the association between TCAs and QT intervals (β=9.3, pinteraction=2.55e(-8)). In the meta-analyses of the other ethnicities, these loci either were excluded from the meta-analyses (as part of quality control), or their effects did not reach the level of nominal statistical significance (pinteraction>0.05). No new variants were identified in these ethnicities. No additional loci were identified after inverse-variance-weighted meta-analysis of the three ancestries.
CONCLUSIONS: Among Europeans, TCA interactions with variants in BRE and UBE2E2 were identified in relation to RR intervals. Among Hispanic/Latinos, variants in TGFBR3 modified the relation between TCAs and QT intervals. Future studies are required to confirm our results.
1 aNoordam, Raymond1 aSitlani, Colleen, M1 aAvery, Christy, L1 aStewart, James, D1 aGogarten, Stephanie, M1 aWiggins, Kerri, L1 aTrompet, Stella1 aWarren, Helen, R1 aSun, Fangui1 aEvans, Daniel, S1 aLi, Xiaohui1 aLi, Jin1 aSmith, Albert, V1 aBis, Joshua, C1 aBrody, Jennifer, A1 aBusch, Evan, L1 aCaulfield, Mark, J1 aChen, Yii-der, I1 aCummings, Steven, R1 aCupples, Adrienne, L1 aDuan, Qing1 aFranco, Oscar, H1 aMéndez-Giráldez, Rául1 aHarris, Tamara, B1 aHeckbert, Susan, R1 avan Heemst, Diana1 aHofman, Albert1 aFloyd, James, S1 aKors, Jan, A1 aLauner, Lenore, J1 aLi, Yun1 aLi-Gao, Ruifang1 aLange, Leslie, A1 aLin, Henry, J1 ade Mutsert, Renée1 aNapier, Melanie, D1 aNewton-Cheh, Christopher1 aPoulter, Neil1 aReiner, Alexander, P1 aRice, Kenneth, M1 aRoach, Jeffrey1 aRodriguez, Carlos, J1 aRosendaal, Frits, R1 aSattar, Naveed1 aSever, Peter1 aSeyerle, Amanda, A1 aSlagboom, Eline1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aStott, David, J1 aStürmer, Til1 aTaylor, Kent, D1 aThornton, Timothy, A1 aUitterlinden, André, G1 aWilhelmsen, Kirk, C1 aWilson, James, G1 aGudnason, Vilmundur1 aJukema, Wouter1 aLaurie, Cathy, C1 aLiu, Yongmei1 aMook-Kanamori, Dennis, O1 aMunroe, Patricia, B1 aRotter, Jerome, I1 aVasan, Ramachandran, S1 aPsaty, Bruce, M1 aStricker, Bruno, H1 aWhitsel, Eric, A uhttps://chs-nhlbi.org/node/735303238nas a2200529 4500008004100000022001400041245012300055210006900178260001600247300000900263490000600272520170300278100002301981700002302004700002002027700002202047700002902069700002402098700002302122700002502145700001202170700002402182700001402206700001502220700001902235700001302254700001702267700002002284700002302304700002202327700001902349700002502368700002002393700002202413700001902435700002102454700002702475700001802502700002302520700002002543700002002563700002202583700002402605700002202629700002102651856003602672 2018 eng d a2045-232200aGenome-wide association study and meta-analysis identify loci associated with ventricular and supraventricular ectopy.0 aGenomewide association study and metaanalysis identify loci asso c2018 Apr 04 a56750 v83 aThe genetic basis of supraventricular and ventricular ectopy (SVE, VE) remains largely uncharacterized, despite established genetic mechanisms of arrhythmogenesis. To identify novel genetic variants associated with SVE/VE in ancestrally diverse human populations, we conducted a genome-wide association study of electrocardiographically identified SVE and VE in five cohorts including approximately 43,000 participants of African, European and Hispanic/Latino ancestry. In thirteen ancestry-stratified subgroups, we tested multivariable-adjusted associations of SVE and VE with single nucleotide polymorphism (SNP) dosage. We combined subgroup-specific association estimates in inverse variance-weighted, fixed-effects and Bayesian meta-analyses. We also combined fixed-effects meta-analytic t-test statistics for SVE and VE in multi-trait SNP association analyses. No loci reached genome-wide significance in trans-ethnic meta-analyses. However, we found genome-wide significant SNPs intronic to an apoptosis-enhancing gene previously associated with QRS interval duration (FAF1; lead SNP rs7545860; effect allele frequency = 0.02; P = 2.0 × 10) in multi-trait analysis among European ancestry participants and near a locus encoding calcium-dependent glycoproteins (DSC3; lead SNP rs8086068; effect allele frequency = 0.17) in meta-analysis of SVE (P = 4.0 × 10) and multi-trait analysis (P = 2.9 × 10) among African ancestry participants. The novel findings suggest several mechanisms by which genetic variation may predispose to ectopy in humans and highlight the potential value of leveraging pleiotropy in future studies of ectopy-related phenotypes.
1 aNapier, Melanie, D1 aFranceschini, Nora1 aGondalia, Rahul1 aStewart, James, D1 aMéndez-Giráldez, Rául1 aSitlani, Colleen, M1 aSeyerle, Amanda, A1 aHighland, Heather, M1 aLi, Yun1 aWilhelmsen, Kirk, C1 aYan, Song1 aDuan, Qing1 aRoach, Jeffrey1 aYao, Jie1 aGuo, Xiuqing1 aTaylor, Kent, D1 aHeckbert, Susan, R1 aRotter, Jerome, I1 aNorth, Kari, E1 aReiner, Alexander, P1 aZhang, Zhu-Ming1 aTinker, Lesley, F1 aLiao, Duanping1 aLaurie, Cathy, C1 aGogarten, Stephanie, M1 aLin, Henry, J1 aBrody, Jennifer, A1 aBartz, Traci, M1 aPsaty, Bruce, M1 aSotoodehnia, Nona1 aSoliman, Elsayed, Z1 aAvery, Christy, L1 aWhitsel, Eric, A uhttps://chs-nhlbi.org/node/766906570nas a2201753 4500008004100000022001400041245007100055210006900126260001200195300001200207490000800219520164100227100002301868700002501891700002601916700002201942700001701964700002401981700002002005700001902025700002602044700001902070700001602089700002002105700002902125700002702154700001602181700002202197700002002219700002002239700002502259700002402284700001902308700002002327700001902347700002002366700002402386700002002410700002602430700002702456700002502483700002402508700001402532700002202546700002302568700002102591700002302612700001902635700002302654700001702677700002302694700001802717700002102735700001902756700002302775700002502798700002202823700002402845700002402869700001902893700002702912700001902939700001702958700002202975700001902997700002103016700001903037700002203056700001903078700001903097700002003116700002203136700002203158700002503180700001903205700002103224700002303245700002103268700002303289700002303312700002203335700001903357700001803376700002203394700002103416700002203437700002103459700002103480700002003501700001903521700002003540700002203560700001803582700002203600700002003622700001703642700001703659700001603676700001503692700002703707700002303734700001703757700002403774700002103798700002003819700002103839700002403860700002503884700002403909700002303933700002503956700002303981700002104004700001904025700002004044700001904064700002804083700001804111700002104129700002104150700002304171700001804194700002004212700002304232700001804255700002404273700002104297700002504318700002104343700001704364700001704381700001804398700002104416700002204437700002104459700001704480700002204497700002004519700002304539700002304562700002504585700002404610700002204634700002304656700002204679700002304701710005604724856003604780 2020 eng d a1476-468700aInherited causes of clonal haematopoiesis in 97,691 whole genomes.0 aInherited causes of clonal haematopoiesis in 97691 whole genomes c2020 10 a763-7680 v5863 aAge is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.
1 aBick, Alexander, G1 aWeinstock, Joshua, S1 aNandakumar, Satish, K1 aFulco, Charles, P1 aBao, Erik, L1 aZekavat, Seyedeh, M1 aSzeto, Mindy, D1 aLiao, Xiaotian1 aLeventhal, Matthew, J1 aNasser, Joseph1 aChang, Kyle1 aLaurie, Cecelia1 aBurugula, Bala, Bharathi1 aGibson, Christopher, J1 aLin, Amy, E1 aTaub, Margaret, A1 aAguet, Francois1 aArdlie, Kristin1 aMitchell, Braxton, D1 aBarnes, Kathleen, C1 aMoscati, Arden1 aFornage, Myriam1 aRedline, Susan1 aPsaty, Bruce, M1 aSilverman, Edwin, K1 aWeiss, Scott, T1 aPalmer, Nicholette, D1 aVasan, Ramachandran, S1 aBurchard, Esteban, G1 aKardia, Sharon, L R1 aHe, Jiang1 aKaplan, Robert, C1 aSmith, Nicholas, L1 aArnett, Donna, K1 aSchwartz, David, A1 aCorrea, Adolfo1 ade Andrade, Mariza1 aGuo, Xiuqing1 aKonkle, Barbara, A1 aCuster, Brian1 aPeralta, Juan, M1 aGui, Hongsheng1 aMeyers, Deborah, A1 aMcGarvey, Stephen, T1 aChen, Ida Yii-Der1 aShoemaker, Benjamin1 aPeyser, Patricia, A1 aBroome, Jai, G1 aGogarten, Stephanie, M1 aWang, Fei, Fei1 aWong, Quenna1 aMontasser, May, E1 aDaya, Michelle1 aKenny, Eimear, E1 aNorth, Kari, E1 aLauner, Lenore, J1 aCade, Brian, E1 aBis, Joshua, C1 aCho, Michael, H1 aLasky-Su, Jessica1 aBowden, Donald, W1 aCupples, Adrienne, L1 aC Y Mak, Angel1 aBecker, Lewis, C1 aSmith, Jennifer, A1 aKelly, Tanika, N1 aAslibekyan, Stella1 aHeckbert, Susan, R1 aTiwari, Hemant, K1 aYang, Ivana, V1 aHeit, John, A1 aLubitz, Steven, A1 aJohnsen, Jill, M1 aCurran, Joanne, E1 aWenzel, Sally, E1 aWeeks, Daniel, E1 aRao, Dabeeru, C1 aDarbar, Dawood1 aMoon, Jee-Young1 aTracy, Russell, P1 aButh, Erin, J1 aRafaels, Nicholas1 aLoos, Ruth, J F1 aDurda, Peter1 aLiu, Yongmei1 aHou, Lifang1 aLee, Jiwon1 aKachroo, Priyadarshini1 aFreedman, Barry, I1 aLevy, Daniel1 aBielak, Lawrence, F1 aHixson, James, E1 aFloyd, James, S1 aWhitsel, Eric, A1 aEllinor, Patrick, T1 aIrvin, Marguerite, R1 aFingerlin, Tasha, E1 aRaffield, Laura, M1 aArmasu, Sebastian, M1 aWheeler, Marsha, M1 aSabino, Ester, C1 aBlangero, John1 aWilliams, Keoki1 aLevy, Bruce, D1 aSheu, Wayne, Huey-Herng1 aRoden, Dan, M1 aBoerwinkle, Eric1 aManson, JoAnn, E1 aMathias, Rasika, A1 aDesai, Pinkal1 aTaylor, Kent, D1 aJohnson, Andrew, D1 aAuer, Paul, L1 aKooperberg, Charles1 aLaurie, Cathy, C1 aBlackwell, Thomas, W1 aSmith, Albert, V1 aZhao, Hongyu1 aLange, Ethan1 aLange, Leslie1 aRich, Stephen, S1 aRotter, Jerome, I1 aWilson, James, G1 aScheet, Paul1 aKitzman, Jacob, O1 aLander, Eric, S1 aEngreitz, Jesse, M1 aEbert, Benjamin, L1 aReiner, Alexander, P1 aJaiswal, Siddhartha1 aAbecasis, Goncalo1 aSankaran, Vijay, G1 aKathiresan, Sekar1 aNatarajan, Pradeep1 aNHLBI Trans-Omics for Precision Medicine Consortium uhttps://chs-nhlbi.org/node/862107958nas a2202377 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2020 eng d a2041-172300aMulti-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.0 aMultiancestry GWAS of the electrocardiographic PR interval ident c2020 May 21 a25420 v113 aThe electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
1 aNtalla, Ioanna1 aWeng, Lu-Chen1 aCartwright, James, H1 aHall, Amelia, Weber1 aSveinbjornsson, Gardar1 aTucker, Nathan, R1 aChoi, Seung, Hoan1 aChaffin, Mark, D1 aRoselli, Carolina1 aBarnes, Michael, R1 aMifsud, Borbala1 aWarren, Helen, R1 aHayward, Caroline1 aMarten, Jonathan1 aCranley, James, J1 aConcas, Maria, Pina1 aGasparini, Paolo1 aBoutin, Thibaud1 aKolcic, Ivana1 aPolasek, Ozren1 aRudan, Igor1 aAraujo, Nathalia, M1 aLima-Costa, Maria, Fernanda1 aRibeiro, Antonio, Luiz P1 aSouza, Renan, P1 aTarazona-Santos, Eduardo1 aGiedraitis, Vilmantas1 aIngelsson, Erik1 aMahajan, Anubha1 aMorris, Andrew, P1 aM, Fabiola, del Greco1 aFoco, Luisa1 aGögele, Martin1 aHicks, Andrew, A1 aCook, James, P1 aLind, Lars1 aLindgren, Cecilia, M1 aSundström, Johan1 aNelson, Christopher, P1 aRiaz, Muhammad, B1 aSamani, Nilesh, J1 aSinagra, Gianfranco1 aUlivi, Sheila1 aKähönen, Mika1 aMishra, Pashupati, P1 aMononen, Nina1 aNikus, Kjell1 aCaulfield, Mark, J1 aDominiczak, Anna1 aPadmanabhan, Sandosh1 aMontasser, May, E1 aO'Connell, Jeff, R1 aRyan, Kathleen1 aShuldiner, Alan, R1 aAeschbacher, Stefanie1 aConen, David1 aRisch, Lorenz1 aThériault, Sébastien1 aHutri-Kähönen, Nina1 aLehtimäki, Terho1 aLyytikäinen, Leo-Pekka1 aRaitakari, Olli, T1 aBarnes, Catriona, L K1 aCampbell, Harry1 aJoshi, Peter, K1 aWilson, James, F1 aIsaacs, Aaron1 aKors, Jan, A1 aDuijn, Cornelia, M1 aHuang, Paul, L1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aLauner, Lenore, J1 aSmith, Albert, V1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aNadkarni, Girish, N1 aPreuss, Michael, H1 aCorrea, Adolfo1 aMei, Hao1 aWilson, James1 aMeitinger, Thomas1 aMüller-Nurasyid, Martina1 aPeters, Annette1 aWaldenberger, Melanie1 aMangino, Massimo1 aSpector, Timothy, D1 aRienstra, Michiel1 avan de Vegte, Yordi, J1 aHarst, Pim1 aVerweij, Niek1 aKääb, Stefan1 aSchramm, Katharina1 aSinner, Moritz, F1 aStrauch, Konstantin1 aCutler, Michael, J1 aFatkin, Diane1 aLondon, Barry1 aOlesen, Morten1 aRoden, Dan, M1 aShoemaker, Benjamin1 aSmith, Gustav1 aBiggs, Mary, L1 aBis, Joshua, C1 aBrody, Jennifer, A1 aPsaty, Bruce, M1 aRice, Kenneth1 aSotoodehnia, Nona1 aDe Grandi, Alessandro1 aFuchsberger, Christian1 aPattaro, Cristian1 aPramstaller, Peter, P1 aFord, Ian1 aJukema, Wouter1 aMacfarlane, Peter, W1 aTrompet, Stella1 aDörr, Marcus1 aFelix, Stephan, B1 aVölker, Uwe1 aWeiss, Stefan1 aHavulinna, Aki, S1 aJula, Antti1 aSääksjärvi, Katri1 aSalomaa, Veikko1 aGuo, Xiuqing1 aHeckbert, Susan, R1 aLin, Henry, J1 aRotter, Jerome, I1 aTaylor, Kent, D1 aYao, Jie1 ade Mutsert, Renée1 aMaan, Arie, C1 aMook-Kanamori, Dennis, O1 aNoordam, Raymond1 aCucca, Francesco1 aDing, Jun1 aLakatta, Edward, G1 aQian, Yong1 aTarasov, Kirill, V1 aLevy, Daniel1 aLin, Honghuang1 aNewton-Cheh, Christopher, H1 aLunetta, Kathryn, L1 aMurray, Alison, D1 aPorteous, David, J1 aSmith, Blair, H1 aStricker, Bruno, H1 aUitterlinden, Andre1 avan den Berg, Marten, E1 aHaessler, Jeffrey1 aJackson, Rebecca, D1 aKooperberg, Charles1 aPeters, Ulrike1 aReiner, Alexander, P1 aWhitsel, Eric, A1 aAlonso, Alvaro1 aArking, Dan, E1 aBoerwinkle, Eric1 aEhret, Georg, B1 aSoliman, Elsayed, Z1 aAvery, Christy, L1 aGogarten, Stephanie, M1 aKerr, Kathleen, F1 aLaurie, Cathy, C1 aSeyerle, Amanda, A1 aStilp, Adrienne1 aAssa, Solmaz1 aSaid, Abdullah1 avan der Ende, Yldau1 aLambiase, Pier, D1 aOrini, Michele1 aRamirez, Julia1 aVan Duijvenboden, Stefan1 aArnar, David, O1 aGudbjartsson, Daniel, F1 aHolm, Hilma1 aSulem, Patrick1 aThorleifsson, Gudmar1 aThorolfsdottir, Rosa, B1 aThorsteinsdottir, Unnur1 aBenjamin, Emelia, J1 aTinker, Andrew1 aStefansson, Kari1 aEllinor, Patrick, T1 aJamshidi, Yalda1 aLubitz, Steven, A1 aMunroe, Patricia, B uhttps://chs-nhlbi.org/node/836803306nas a2200565 4500008004100000022001400041245014400055210006900199260001600268490000600284520159100290100001701881700001501898700002501913700001701938700002301955700002701978700002402005700001702029700001202046700002402058700002202082700002702104700002502131700002402156700002002180700002002200700001402220700002602234700001502260700002402275700002002299700002002319700002202339700002002361700002102381700001702402700002102419700002402440700002102464700002302485700002102508700002002529700001902549700002302568700002102591700002702612710006502639856003602704 2021 eng d a2666-247700aBinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.0 aBinomiRare A robust test for association of a rare genetic varia c2021 Jul 080 v23 aWhole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.
1 aSofer, Tamar1 aLee, Jiwon1 aKurniansyah, Nuzulul1 aJain, Deepti1 aLaurie, Cecelia, A1 aGogarten, Stephanie, M1 aConomos, Matthew, P1 aHeavner, Ben1 aHu, Yao1 aKooperberg, Charles1 aHaessler, Jeffrey1 aVasan, Ramachandran, S1 aCupples, Adrienne, L1 aCoombes, Brandon, J1 aSeyerle, Amanda1 aGharib, Sina, A1 aChen, Han1 aO'Connell, Jeffrey, R1 aZhang, Man1 aGottlieb, Daniel, J1 aPsaty, Bruce, M1 aLongstreth, W T1 aRotter, Jerome, I1 aTaylor, Kent, D1 aRich, Stephen, S1 aGuo, Xiuqing1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aPankow, James, S1 aJohnson, Andrew, D1 aPankratz, Nathan1 aReiner, Alex, P1 aRedline, Susan1 aSmith, Nicholas, L1 aRice, Kenneth, M1 aSchifano, Elizabeth, D1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883803417nas a2200493 4500008004100000022001400041245018000055210006900235260000900304300001300313490000700326520180900333100002102142700001402163700001902177700003202196700001802228700002502246700002202271700001902293700002102312700002502333700002002358700002702378700002502405700001702430700002002447700002402467700002102491700002502512700002402537700002602561700002002587700001802607700002102625700002702646700001802673700002102691700002402712700002402736710005302760710007402813856003602887 2021 eng d a1932-620300aIdentification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program.0 aIdentification of novel and rare variants associated with handgr c2021 ae02536110 v163 aHandgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.
1 aSarnowski, Chloe1 aChen, Han1 aBiggs, Mary, L1 aWassertheil-Smoller, Sylvia1 aBressler, Jan1 aIrvin, Marguerite, R1 aRyan, Kathleen, A1 aKarasik, David1 aArnett, Donna, K1 aCupples, Adrienne, L1 aFardo, David, W1 aGogarten, Stephanie, M1 aHeavner, Benjamin, D1 aJain, Deepti1 aKang, Hyun, Min1 aKooperberg, Charles1 aMainous, Arch, G1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aO'Connell, Jeffrey, R1 aPsaty, Bruce, M1 aRice, Kenneth1 aSmith, Albert, V1 aVasan, Ramachandran, S1 aWindham, Gwen1 aKiel, Douglas, P1 aMurabito, Joanne, M1 aLunetta, Kathryn, L1 aTOPMed Longevity and Healthy Aging Working Group1 afrom the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883608483nas a2202413 4500008004100000022001400041245007200055210006900127260001200196300001200208490000800220520169100228100001901919700002201938700002401960700002201984700002402006700001702030700003002047700002002077700002702097700002002124700003002144700002202174700002002196700001802216700002302234700001802257700002202275700002102297700002302318700002002341700002502361700002102386700001702407700001802424700002402442700001802466700002002484700002202504700001902526700002302545700001902568700002302587700001802610700001802628700001702646700001902663700002102682700002102703700002402724700002402748700001902772700002102791700002202812700002302834700002502857700001902882700002202901700002202923700002302945700002202968700002002990700002203010700001903032700002003051700001903071700002203090700001803112700001903130700001903149700002303168700001903191700002203210700002403232700002103256700001703277700001803294700002103312700001703333700002003350700002303370700002703393700002803420700001803448700002103466700002403487700001703511700002103528700001403549700002603563700002303589700002503612700002103637700002303658700001903681700002403700700001803724700001903742700002103761700002103782700002003803700002303823700002403846700001903870700002103889700002203910700001703932700001603949700001803965700001603983700002003999700001704019700002104036700002204057700002404079700001904103700002104122700002204143700002304165700002204188700002504210700002004235700002304255700002204278700002204300700002504322700002504347700002204372700002504394700002404419700002404443700001904467700002304486700002104509700001904530700002604549700002604575700002104601700002004622700002404642700002004666700001904686700002004705700001404725700001904739700002504758700001504783700002204798700002004820700002104840700002604861700002304887700001904910700002004929700002304949700001904972700002404991700002305015700002305038700002205061700002305083700001805106700002005124700001905144700002505163700002205188700002705210700002705237700003005264700001805294700002105312700001905333700002005352700001805372700002305390700001805413700001705431700002105448700002805469700002405497700002105521700002005542700001905562700002105581700002105602700002405623700001805647700001605665700002805681700002605709700002405735700002105759700002405780700002105804700002505825700002105850700002405871700002305895700002505918700002505943710006505968856003606033 2021 eng d a1476-468700aSequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.0 aSequencing of 53831 diverse genomes from the NHLBI TOPMed Progra c2021 02 a290-2990 v5903 aThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
1 aTaliun, Daniel1 aHarris, Daniel, N1 aKessler, Michael, D1 aCarlson, Jedidiah1 aSzpiech, Zachary, A1 aTorres, Raul1 aTaliun, Sarah, A Gagliano1 aCorvelo, André1 aGogarten, Stephanie, M1 aKang, Hyun, Min1 aPitsillides, Achilleas, N1 aLeFaive, Jonathon1 aLee, Seung-Been1 aTian, Xiaowen1 aBrowning, Brian, L1 aDas, Sayantan1 aEmde, Anne-Katrin1 aClarke, Wayne, E1 aLoesch, Douglas, P1 aShetty, Amol, C1 aBlackwell, Thomas, W1 aSmith, Albert, V1 aWong, Quenna1 aLiu, Xiaoming1 aConomos, Matthew, P1 aBobo, Dean, M1 aAguet, Francois1 aAlbert, Christine1 aAlonso, Alvaro1 aArdlie, Kristin, G1 aArking, Dan, E1 aAslibekyan, Stella1 aAuer, Paul, L1 aBarnard, John1 aBarr, Graham1 aBarwick, Lucas1 aBecker, Lewis, C1 aBeer, Rebecca, L1 aBenjamin, Emelia, J1 aBielak, Lawrence, F1 aBlangero, John1 aBoehnke, Michael1 aBowden, Donald, W1 aBrody, Jennifer, A1 aBurchard, Esteban, G1 aCade, Brian, E1 aCasella, James, F1 aChalazan, Brandon1 aChasman, Daniel, I1 aChen, Yii-Der Ida1 aCho, Michael, H1 aChoi, Seung, Hoan1 aChung, Mina, K1 aClish, Clary, B1 aCorrea, Adolfo1 aCurran, Joanne, E1 aCuster, Brian1 aDarbar, Dawood1 aDaya, Michelle1 ade Andrade, Mariza1 aDeMeo, Dawn, L1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aEng, Celeste1 aFatkin, Diane1 aFingerlin, Tasha1 aForer, Lukas1 aFornage, Myriam1 aFranceschini, Nora1 aFuchsberger, Christian1 aFullerton, Stephanie, M1 aGermer, Soren1 aGladwin, Mark, T1 aGottlieb, Daniel, J1 aGuo, Xiuqing1 aHall, Michael, E1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHeckbert, Susan, R1 aIrvin, Marguerite, R1 aJohnsen, Jill, M1 aJohnson, Andrew, D1 aKaplan, Robert1 aKardia, Sharon, L R1 aKelly, Tanika1 aKelly, Shannon1 aKenny, Eimear, E1 aKiel, Douglas, P1 aKlemmer, Robert1 aKonkle, Barbara, A1 aKooperberg, Charles1 aKöttgen, Anna1 aLange, Leslie, A1 aLasky-Su, Jessica1 aLevy, Daniel1 aLin, Xihong1 aLin, Keng-Han1 aLiu, Chunyu1 aLoos, Ruth, J F1 aGarman, Lori1 aGerszten, Robert1 aLubitz, Steven, A1 aLunetta, Kathryn, L1 aC Y Mak, Angel1 aManichaikul, Ani1 aManning, Alisa, K1 aMathias, Rasika, A1 aMcManus, David, D1 aMcGarvey, Stephen, T1 aMeigs, James, B1 aMeyers, Deborah, A1 aMikulla, Julie, L1 aMinear, Mollie, A1 aMitchell, Braxton, D1 aMohanty, Sanghamitra1 aMontasser, May, E1 aMontgomery, Courtney1 aMorrison, Alanna, C1 aMurabito, Joanne, M1 aNatale, Andrea1 aNatarajan, Pradeep1 aNelson, Sarah, C1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPankratz, Nathan1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aPleiness, Jacob1 aPost, Wendy, S1 aPsaty, Bruce, M1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRoden, Dan1 aRotter, Jerome, I1 aRuczinski, Ingo1 aSarnowski, Chloe1 aSchoenherr, Sebastian1 aSchwartz, David, A1 aSeo, Jeong-Sun1 aSeshadri, Sudha1 aSheehan, Vivien, A1 aSheu, Wayne, H1 aShoemaker, Benjamin1 aSmith, Nicholas, L1 aSmith, Jennifer, A1 aSotoodehnia, Nona1 aStilp, Adrienne, M1 aTang, Weihong1 aTaylor, Kent, D1 aTelen, Marilyn1 aThornton, Timothy, A1 aTracy, Russell, P1 aVan Den Berg, David, J1 aVasan, Ramachandran, S1 aViaud-Martinez, Karine, A1 aVrieze, Scott1 aWeeks, Daniel, E1 aWeir, Bruce, S1 aWeiss, Scott, T1 aWeng, Lu-Chen1 aWiller, Cristen, J1 aZhang, Yingze1 aZhao, Xutong1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBoerwinkle, Eric1 aGabriel, Stacey1 aGibbs, Richard1 aRice, Kenneth, M1 aRich, Stephen, S1 aSilverman, Edwin, K1 aQasba, Pankaj1 aGan, Weiniu1 aPapanicolaou, George, J1 aNickerson, Deborah, A1 aBrowning, Sharon, R1 aZody, Michael, C1 aZöllner, Sebastian1 aWilson, James, G1 aCupples, Adrienne, L1 aLaurie, Cathy, C1 aJaquish, Cashell, E1 aHernandez, Ryan, D1 aO'Connor, Timothy, D1 aAbecasis, Goncalo, R1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/866603549nas a2200541 4500008004100000022001400041245010100055210006900156260001600225300001200241520193400253100002302187700002302210700002402233700001702257700002402274700002002298700002002318700002702338700002402365700001902389700002302408700002402431700002302455700001402478700002102492700002202513700002302535700002402558700002502582700001702607700001802624700002202642700002102664700002302685700002302708700002202731700002102753700002002774700002702794700001402821700002402835700002102859700002302880700002102903710004702924856003602971 2023 eng d a2574-830000aWhole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program.0 aWhole Genome Analysis of Venous Thromboembolism the TransOmics f c2023 Mar 24 ae0035323 aBackground Risk for venous thromboembolism has a strong genetic component. Whole genome sequencingfrom the Trans-Omics for Precision Medicine program allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods The 3793 cases and 7834 controls (11.6% of cases were Black, Hispanic/Latino, or Asian American) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only (odds ratio, 6.2 for carriers of rare variants; =7.4×10) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at (odds ratio, 3.8; =1.6×10), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: became significant (minimum =1.8×10 with the secondary filter), while did not (minimum =4.4×10 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, , became significant (=4.4×10 using all missense variants with minor allele frequency <0.0005). Conclusions Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel locus and to identify additional rare variation associated with venous thromboembolism.
1 aSeyerle, Amanda, A1 aLaurie, Cecelia, A1 aCoombes, Brandon, J1 aJain, Deepti1 aConomos, Matthew, P1 aBrody, Jennifer1 aChen, Ming-Huei1 aGogarten, Stephanie, M1 aBeutel, Kathleen, M1 aGupta, Namrata1 aHeckbert, Susan, R1 aJackson, Rebecca, D1 aJohnson, Andrew, D1 aKo, Darae1 aManson, JoAnn, E1 aMcKnight, Barbara1 aMetcalf, Ginger, A1 aMorrison, Alanna, C1 aReiner, Alexander, P1 aSofer, Tamar1 aTang, Weihong1 aWiggins, Kerri, L1 aBoerwinkle, Eric1 ade Andrade, Mariza1 aGabriel, Stacey, B1 aGibbs, Richard, A1 aLaurie, Cathy, C1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aRice, Ken1 aKooperberg, Charles1 aPankow, James, S1 aSmith, Nicholas, L1 aPankratz, Nathan1 aTrans-Omics for Precision Medicine Program uhttps://chs-nhlbi.org/node/932103779nas a2200673 4500008004100000245013300041210006900174260001600243520177100259100001902030700002202049700001402071700002002085700002002105700001502125700001902140700002202159700002702181700001402208700002102222700002002243700001902263700002102282700001902303700001702322700002202339700002102361700002202382700002502404700002102429700002002450700002502470700002402495700002202519700001902541700001602560700002302576700002002599700001902619700001502638700002102653700002302674700002202697700002402719700002002743700001902763700001902782700001602801700002002817700002402837700002502861700002302886700001602909700001802925700002302943710006502966710003803031856003603069 2023 eng d00aWhole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.0 aWhole Genome Sequencing Based Analysis of Inflammation Biomarker c2023 Sep 123 aInflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
1 aJiang, Min-Zhi1 aGaynor, Sheila, M1 aLi, Xihao1 aVan Buren, Eric1 aStilp, Adrienne1 aButh, Erin1 aWang, Fei, Fei1 aManansala, Regina1 aGogarten, Stephanie, M1 aLi, Zilin1 aPolfus, Linda, M1 aSalimi, Shabnam1 aBis, Joshua, C1 aPankratz, Nathan1 aYanek, Lisa, R1 aDurda, Peter1 aTracy, Russell, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aMitchell, Braxton, D1 aLewis, Joshua, P1 aPsaty, Bruce, M1 aPratte, Katherine, A1 aSilverman, Edwin, K1 aKaplan, Robert, C1 aAvery, Christy1 aNorth, Kari1 aMathias, Rasika, A1 aFaraday, Nauder1 aLin, Honghuang1 aWang, Biqi1 aCarson, April, P1 aNorwood, Arnita, F1 aGibbs, Richard, A1 aKooperberg, Charles1 aLundin, Jessica1 aPeters, Ulrike1 aDupuis, Josée1 aHou, Lifang1 aFornage, Myriam1 aBenjamin, Emelia, J1 aReiner, Alexander, P1 aBowler, Russell, P1 aLin, Xihong1 aAuer, Paul, L1 aRaffield, Laura, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Inflammation Working Group uhttps://chs-nhlbi.org/node/9500