04619nas a2201021 4500008004100000022001400041245012900055210006900184260001200253300001300265490000700278520172700285653001502012653001002027653000902037653002202046653003802068653002602106653003402132653001102166653002902177653002202206653003402228653001502262653001102277653001202288653004202300653000902342653001602351653002602367653005002393653001102443653001902454653003602473653002802509653002602537653001002563653002602573653001602599100001902615700001402634700002302648700001502671700002502686700001802711700002202729700002302751700001702774700002402791700002102815700002802836700002002864700002202884700002402906700002202930700001902952700002202971700001502993700002003008700001303028700002203041700002103063700001903084700002203103700002203125700002103147700001403168700001903182700001703201700002003218700002503238700001703263700002003280700002003300700002003320700002003340700002203360700002003382700002303402700002103425700002303446700002103469700001803490700001803508700001603526700001903542856003603561 2019 eng d a1553-740400aAssociations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep.0 aAssociations of variants In the hexokinase 1 and interleukin 18 c2019 04 ae10077390 v153 a
Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.
10aAdolescent10aAdult10aAged10aAged, 80 and over10aCell Adhesion Molecules, Neuronal10aComputational Biology10aExtracellular Matrix Proteins10aFemale10aGene Regulatory Networks10aGenetic Variation10aGenome-Wide Association Study10aHexokinase10aHumans10aHypoxia10aInterleukin-18 Receptor alpha Subunit10aMale10aMiddle Aged10aNerve Tissue Proteins10aNLR Family, Pyrin Domain-Containing 3 Protein10aOxygen10aOxyhemoglobins10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aSerine Endopeptidases10aSleep10aSleep Apnea Syndromes10aYoung Adult1 aCade, Brian, E1 aChen, Han1 aStilp, Adrienne, M1 aLouie, Tin1 aAncoli-Israel, Sonia1 aArens, Raanan1 aBarfield, Richard1 aBelow, Jennifer, E1 aCai, Jianwen1 aConomos, Matthew, P1 aEvans, Daniel, S1 aFrazier-Wood, Alexis, C1 aGharib, Sina, A1 aGleason, Kevin, J1 aGottlieb, Daniel, J1 aHillman, David, R1 aJohnson, Craig1 aLederer, David, J1 aLee, Jiwon1 aLoredo, Jose, S1 aMei, Hao1 aMukherjee, Sutapa1 aPatel, Sanjay, R1 aPost, Wendy, S1 aPurcell, Shaun, M1 aRamos, Alberto, R1 aReid, Kathryn, J1 aRice, Ken1 aShah, Neomi, A1 aSofer, Tamar1 aTaylor, Kent, D1 aThornton, Timothy, A1 aWang, Heming1 aYaffe, Kristine1 aZee, Phyllis, C1 aHanis, Craig, L1 aPalmer, Lyle, J1 aRotter, Jerome, I1 aStone, Katie, L1 aTranah, Gregory, J1 aWilson, James, G1 aSunyaev, Shamil, R1 aLaurie, Cathy, C1 aZhu, Xiaofeng1 aSaxena, Richa1 aLin, Xihong1 aRedline, Susan uhttps://chs-nhlbi.org/node/804406391nas a2201909 4500008004100000022001400041245012500055210006900180260001600249300000900265490000700274520109900281100002101380700001901401700001701420700002301437700002001460700002801480700002201508700001801530700002101548700001901569700001901588700002001607700002201627700001401649700002301663700002301686700002101709700002001730700002301750700002001773700002601793700001801819700002401837700001801861700001701879700001601896700001701912700001501929700001701944700002901961700002001990700002402010700002502034700001402059700002102073700002102094700001702115700002502132700002002157700001402177700002102191700002802212700002502240700001902265700002602284700002102310700001702331700002002348700001802368700001702386700001902403700001902422700002502441700001802466700002402484700002102508700001602529700002402545700001502569700002002584700002402604700002202628700002202650700002002672700002102692700002102713700001802734700002002752700002202772700002102794700001502815700001702830700002002847700002302867700001802890700002002908700002202928700002102950700002102971700001902992700002003011700002003031700002103051700002303072700002003095700002503115700001903140700002103159700002103180700002203201700002503223700001903248700002303267700001603290700002403306700001703330700002403347700002203371700002003393700002803413700002303441700001903464700002603483700002403509700002103533700001703554700002303571700002103594700001803615700001603633700002203649700001903671700001903690700002203709700001903731700002703750700002403777700002603801700001703827700002103844700001503865700002103880700002103901700002203922700002403944700001903968700002103987700002804008700002004036700002604056700001904082700002004101700002004121700001804141700001604159700002504175700002004200700001804220700001704238700002104255700001804276700002404294700002404318700001804342700002404360700002004384700002204404700001904426856003604445 2019 eng d a2041-172300aMulti-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.0 aMultiancestry sleepbySNP interaction analysis in 126926 individu c2019 Nov 12 a51210 v103 aBoth short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
1 aNoordam, Raymond1 aBos, Maxime, M1 aWang, Heming1 aWinkler, Thomas, W1 aBentley, Amy, R1 aKilpeläinen, Tuomas, O1 ade Vries, Paul, S1 aSung, Yun, Ju1 aSchwander, Karen1 aCade, Brian, E1 aManning, Alisa1 aAschard, Hugues1 aBrown, Michael, R1 aChen, Han1 aFranceschini, Nora1 aMusani, Solomon, K1 aRichard, Melissa1 aVojinovic, Dina1 aAslibekyan, Stella1 aBartz, Traci, M1 aFuentes, Lisa, de Las1 aFeitosa, Mary1 aHorimoto, Andrea, R1 aIlkov, Marjan1 aKho, Minjung1 aKraja, Aldi1 aLi, Changwei1 aLim, Elise1 aLiu, Yongmei1 aMook-Kanamori, Dennis, O1 aRankinen, Tuomo1 aTajuddin, Salman, M1 avan der Spek, Ashley1 aWang, Zhe1 aMarten, Jonathan1 aLaville, Vincent1 aAlver, Maris1 aEvangelou, Evangelos1 aGraff, Maria, E1 aHe, Meian1 aKuhnel, Brigitte1 aLyytikäinen, Leo-Pekka1 aMarques-Vidal, Pedro1 aNolte, Ilja, M1 aPalmer, Nicholette, D1 aRauramaa, Rainer1 aShu, Xiao-Ou1 aSnieder, Harold1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aAdolfo, Correa1 aBallantyne, Christie1 aBielak, Larry1 aBiermasz, Nienke, R1 aBoerwinkle, Eric1 aDimou, Niki1 aEiriksdottir, Gudny1 aGao, Chuan1 aGharib, Sina, A1 aGottlieb, Daniel, J1 aHaba-Rubio, José1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeinzer, Raphael1 aHixson, James, E1 aHomuth, Georg1 aIkram, Arfan, M1 aKomulainen, Pirjo1 aKrieger, Jose, E1 aLee, Jiwon1 aLiu, Jingmin1 aLohman, Kurt, K1 aLuik, Annemarie, I1 aMägi, Reedik1 aMartin, Lisa, W1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aNalls, Mike, A1 aO'Connell, Jeff1 aPeters, Annette1 aPeyser, Patricia1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRensen, Patrick, C N1 aRice, Treva, K1 aRich, Stephen, S1 aRoenneberg, Till1 aRotter, Jerome, I1 aSchreiner, Pamela, J1 aShikany, James1 aSidney, Stephen, S1 aSims, Mario1 aSitlani, Colleen, M1 aSofer, Tamar1 aStrauch, Konstantin1 aSwertz, Morris, A1 aTaylor, Kent, D1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aVölzke, Henry1 aWaldenberger, Melanie1 aWallance, Robert, B1 aDijk, Ko Willems1 aYu, Caizheng1 aZonderman, Alan, B1 aBecker, Diane, M1 aElliott, Paul1 aEsko, Tõnu1 aGieger, Christian1 aGrabe, Hans, J1 aLakka, Timo, A1 aLehtimäki, Terho1 aNorth, Kari, E1 aPenninx, Brenda, W J H1 aVollenweider, Peter1 aWagenknecht, Lynne, E1 aWu, Tangchun1 aXiang, Yong-Bing1 aZheng, Wei1 aArnett, Donna, K1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon1 aKelly, Tanika, N1 aKritchevsky, Stephen, B1 aLoos, Ruth, J F1 aPereira, Alexandre, C1 aProvince, Mike1 aPsaty, Bruce, M1 aRotimi, Charles1 aZhu, Xiaofeng1 aAmin, Najaf1 aCupples, Adrienne, L1 aFornage, Myriam1 aFox, Ervin, F1 aGuo, Xiuqing1 aGauderman, James1 aRice, Kenneth1 aKooperberg, Charles1 aMunroe, Patricia, B1 aLiu, Ching-Ti1 aMorrison, Alanna, C1 aRao, Dabeeru, C1 avan Heemst, Diana1 aRedline, Susan uhttps://chs-nhlbi.org/node/820203253nas a2200637 4500008004100000022001400041245013600055210006900191260001600260300001400276490000800290520140100298100002001699700001901719700001701738700001701755700001501772700001701787700002401804700001601828700001401844700002401858700002101882700001701903700002001920700001701940700002201957700002201979700002202001700002802023700002002051700002002071700001902091700002102110700001802131700002002149700001802169700002302187700002102210700001602231700001702247700002002264700002702284700002002311700002102331700002402352700001702376700002102393700002202414700002102436700001902457700001802476710005402494710003102548856003602579 2019 eng d a1537-660500aSequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level.0 aSequencing Analysis at 8p23 Identifies Multiple Rare Variants in c2019 Nov 07 a1057-10680 v1053 aAverage arterial oxyhemoglobin saturation during sleep (AvSpOS) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23, we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpOS and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9 × 10). A risk score for these variants, built on an independent dataset, explains 0.97% of the AvSpOS variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpOS. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpOS.
1 aLiang, Jingjing1 aCade, Brian, E1 aHe, Karen, Y1 aWang, Heming1 aLee, Jiwon1 aSofer, Tamar1 aWilliams, Stephanie1 aLi, Ruitong1 aChen, Han1 aGottlieb, Daniel, J1 aEvans, Daniel, S1 aGuo, Xiuqing1 aGharib, Sina, A1 aHale, Lauren1 aHillman, David, R1 aLutsey, Pamela, L1 aMukherjee, Sutapa1 aOchs-Balcom, Heather, M1 aPalmer, Lyle, J1 aRhodes, Jessica1 aPurcell, Shaun1 aPatel, Sanjay, R1 aSaxena, Richa1 aStone, Katie, L1 aTang, Weihong1 aTranah, Gregory, J1 aBoerwinkle, Eric1 aLin, Xihong1 aLiu, Yongmei1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aCho, Michael, H1 aManichaikul, Ani1 aSilverman, Edwin, K1 aBarr, Graham1 aRich, Stephen, S1 aRotter, Jerome, I1 aWilson, James, G1 aRedline, Susan1 aZhu, Xiaofeng1 aNHLBI Trans-Omics for Precision Medicine (TOPMed)1 aTOPMed Sleep Working Group uhttps://chs-nhlbi.org/node/819906570nas 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/862103741nas a2200625 4500008004100000022001400041245009700055210006900152260001300221300001200234490000700246520194400253100001402197700001402211700002002225700002402245700002302269700002102292700002302313700001702336700001502353700002102368700002402389700001702413700001602430700002502446700002202471700002202493700001502515700002402530700002002554700002002574700002102594700002502615700002002640700002402660700002302684700002602707700001302733700001402746700002002760700002402780700002402804700001802828700002902846700002502875700002002900700001902920700002002939700002202959700002102981700002403002710005303026856003603079 2020 eng d a2574-830000aRole of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.0 aRole of Rare and LowFrequency Variants in GeneAlcohol Interactio c2020 Aug ae0027720 v133 aBACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.
METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.
RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .
CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.
1 aWang, Zhe1 aChen, Han1 aBartz, Traci, M1 aBielak, Lawrence, F1 aChasman, Daniel, I1 aFeitosa, Mary, F1 aFranceschini, Nora1 aGuo, Xiuqing1 aLim, Elise1 aNoordam, Raymond1 aRichard, Melissa, A1 aWang, Heming1 aCade, Brian1 aCupples, Adrienne, L1 ade Vries, Paul, S1 aGiulanini, Franco1 aLee, Jiwon1 aLemaitre, Rozenn, N1 aMartin, Lisa, W1 aReiner, Alex, P1 aRich, Stephen, S1 aSchreiner, Pamela, J1 aSidney, Stephen1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 avan Dijk, Ko, Willems1 aYao, Jie1 aZhao, Wei1 aFornage, Myriam1 aKardia, Sharon, L R1 aKooperberg, Charles1 aLiu, Ching-Ti1 aMook-Kanamori, Dennis, O1 aProvince, Michael, A1 aPsaty, Bruce, M1 aRedline, Susan1 aRidker, Paul, M1 aRotter, Jerome, I1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aCHARGE Gene-Lifestyle Interactions Working Group uhttps://chs-nhlbi.org/node/840704776nas a2201261 4500008004100000022001400041245010300055210006900158260001500227300000900242490000700251520104900258653001001307653002201317653000901339653002201348653005001370653002901420653002401449653001101473653002201484653001701506653003801523653003401561653001101595653005001606653000901656653000901665653001601674653003601690653004101726653004301767653004001810653004601850653002801896100001701924700001601941700001801957700001801975700001501993700001502008700001702023700001902040700001702059700003002076700002902106700002202135700002302157700001302180700002102193700001902214700001902233700001502252700002002267700001902287700002302306700002002329700002502349700002002374700002002394700002402414700002002438700002702458700002102485700002002506700001702526700001902543700002002562700001702582700001702599700002202616700002302638700002002661700002502681700002802706700002202734700002402756700001702780700002602797700002002823700002302843700003102866700002502897700001902922700002002941700002102961700002402982700001903006700002003025700002103045700002403066700002503090700002403115700002203139700002003161700002103181700002503202700002303227700002603250700002503276700002403301700001703325700002003342700002103362710006503383710003003448856003603478 2020 eng d a2041-172300aWhole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants.0 aWhole genome sequence analysis of pulmonary function and COPD in c2020 10 14 a51820 v113 aChronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.
10aAdult10aAfrican Americans10aAged10aAged, 80 and over10aAlpha-Ketoglutarate-Dependent Dioxygenase FTO10aCalcium-Binding Proteins10aFeasibility Studies10aFemale10aFollow-Up Studies10aGenetic Loci10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aIntracellular Signaling Peptides and Proteins10aLung10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aProtein Inhibitors of Activated STAT10aPulmonary Disease, Chronic Obstructive10aRespiratory Physiological Phenomena10aSmall Ubiquitin-Related Modifier Proteins10aWhole Genome Sequencing1 aZhao, Xutong1 aQiao, Dandi1 aYang, Chaojie1 aKasela, Silva1 aKim, Wonji1 aMa, Yanlin1 aShrine, Nick1 aBatini, Chiara1 aSofer, Tamar1 aTaliun, Sarah, A Gagliano1 aSakornsakolpat, Phuwanat1 aBalte, Pallavi, P1 aProkopenko, Dmitry1 aYu, Bing1 aLange, Leslie, A1 aDupuis, Josée1 aCade, Brian, E1 aLee, Jiwon1 aGharib, Sina, A1 aDaya, Michelle1 aLaurie, Cecelia, A1 aRuczinski, Ingo1 aCupples, Adrienne, L1 aLoehr, Laura, R1 aBartz, Traci, M1 aMorrison, Alanna, C1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aWilson, James, G1 aTaylor, Kent, D1 aDurda, Peter1 aJohnson, Craig1 aCornell, Elaine1 aGuo, Xiuqing1 aLiu, Yongmei1 aTracy, Russell, P1 aArdlie, Kristin, G1 aAguet, Francois1 aVanDenBerg, David, J1 aPapanicolaou, George, J1 aRotter, Jerome, I1 aBarnes, Kathleen, C1 aJain, Deepti1 aNickerson, Deborah, A1 aMuzny, Donna, M1 aMetcalf, Ginger, A1 aDoddapaneni, Harshavardhan1 aDugan-Perez, Shannon1 aGupta, Namrata1 aGabriel, Stacey1 aRich, Stephen, S1 aO'Connor, George, T1 aRedline, Susan1 aReed, Robert, M1 aLaurie, Cathy, C1 aDaviglus, Martha, L1 aPreudhomme, Liana, K1 aBurkart, Kristin, M1 aKaplan, Robert, C1 aWain, Louise, V1 aTobin, Martin, D1 aLondon, Stephanie, J1 aLappalainen, Tuuli1 aOelsner, Elizabeth, C1 aAbecasis, Goncalo, R1 aSilverman, Edwin, K1 aBarr, Graham1 aCho, Michael, H1 aManichaikul, Ani1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Lung Working Group uhttps://chs-nhlbi.org/node/863903306nas a2200565 4500008004100000022001400041245014400055210006900199260001600268490000600284520159100290100001701881700001501898700002501913700001701938700002301955700002701978700002402005700001702029700001202046700002402058700002202082700002702104700002502131700002402156700002002180700002002200700001402220700002602234700001502260700002402275700002002299700002002319700002202339700002002361700002102381700001702402700002102419700002402440700002102464700002302485700002102508700002002529700001902549700002302568700002102591700002702612710006502639856003602704 2021 eng d a2666-247700aBinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.0 aBinomiRare A robust test for association of a rare genetic varia c2021 Jul 080 v23 aWhole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.
1 aSofer, Tamar1 aLee, Jiwon1 aKurniansyah, Nuzulul1 aJain, Deepti1 aLaurie, Cecelia, A1 aGogarten, Stephanie, M1 aConomos, Matthew, P1 aHeavner, Ben1 aHu, Yao1 aKooperberg, Charles1 aHaessler, Jeffrey1 aVasan, Ramachandran, S1 aCupples, Adrienne, L1 aCoombes, Brandon, J1 aSeyerle, Amanda1 aGharib, Sina, A1 aChen, Han1 aO'Connell, Jeffrey, R1 aZhang, Man1 aGottlieb, Daniel, J1 aPsaty, Bruce, M1 aLongstreth, W T1 aRotter, Jerome, I1 aTaylor, Kent, D1 aRich, Stephen, S1 aGuo, Xiuqing1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aPankow, James, S1 aJohnson, Andrew, D1 aPankratz, Nathan1 aReiner, Alex, P1 aRedline, Susan1 aSmith, Nicholas, L1 aRice, Kenneth, M1 aSchifano, Elizabeth, D1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883805153nas a2201369 4500008004100000022001400041245011700055210006900172260001500241300000900256490000700265520124400272100002301516700001901539700002101558700002701579700002001606700002201626700001901648700002601667700002601693700002001719700002001739700002301759700003001782700001901812700002301831700002901854700002801883700002401911700001901935700001901954700001201973700002401985700002102009700001702030700002502047700001902072700001802091700001502109700002402124700002002148700002002168700002202188700002002210700001702230700002602247700002602273700002102299700002402320700002302344700001802367700001902385700002102404700001902425700002102444700002202465700002102487700002102508700001902529700002102548700002202569700002002591700002102611700002002632700001902652700002202671700001802693700002202711700002402733700002002757700002302777700002002800700001802820700002202838700001402860700002002874700002002894700002202914700002402936700001802960700001702978700002402995700002103019700001803040700002403058700002003082700002203102700002303124700003003147700002503177700002503202700002603227700001903253700001903272700002103291700002003312700001403332700001903346700002503365700001703390700001903407700002103426700002203447700002703469700002203496700002503518700002203543700002403565700002103589700002003610700002003630700002003650710006503670710001203735856003603747 2021 eng d a2041-172300aChromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.0 aChromosome Xq23 is associated with lower atherogenic lipid conce c2021 04 12 a21820 v123 aAutosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
1 aNatarajan, Pradeep1 aPampana, Akhil1 aGraham, Sarah, E1 aRuotsalainen, Sanni, E1 aPerry, James, A1 ade Vries, Paul, S1 aBroome, Jai, G1 aPirruccello, James, P1 aHonigberg, Michael, C1 aAragam, Krishna1 aWolford, Brooke1 aBrody, Jennifer, A1 aAntonacci-Fulton, Lucinda1 aArden, Moscati1 aAslibekyan, Stella1 aAssimes, Themistocles, L1 aBallantyne, Christie, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aDo, Ron1 aDoddapaneni, Harsha1 aEmery, Leslie, S1 aHung, Yi-Jen1 aIrvin, Marguerite, R1 aKhan, Alyna, T1 aLange, Leslie1 aLee, Jiwon1 aLemaitre, Rozenn, N1 aMartin, Lisa, W1 aMetcalf, Ginger1 aMontasser, May, E1 aMoon, Jee-Young1 aMuzny, Donna1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aStilp, Adrienne, M1 aTsai, Michael1 aWang, Fei, Fei1 aWeeks, Daniel, E1 aYanek, Lisa, R1 aWilson, James, G1 aAbecasis, Goncalo1 aArnett, Donna, K1 aBecker, Lewis, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aChoi, Won, Jung1 aCorrea, Adolfo1 aCurran, Joanne, E1 aDaly, Mark, J1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aFornage, Myriam1 aFreedman, Barry, I1 aGabriel, Stacey1 aGermer, Soren1 aGibbs, Richard, A1 aHe, Jiang1 aHveem, Kristian1 aJarvik, Gail, P1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKenny, Eimear1 aKim, Ryan, W1 aKooperberg, Charles1 aLaurie, Cathy, C1 aLee, Seonwook1 aLloyd-Jones, Don, M1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aMathias, Rasika, A1 aMartinez, Karine, A Viaud1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aNickerson, Deborah, A1 aNorth, Kari, E1 aPalotie, Aarno1 aPark, Cheol, Joo1 aPsaty, Bruce, M1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSmith, Albert, V1 aTracy, Russell, P1 aVasan, Ramachandran, S1 aKathiresan, Sekar1 aCupples, Adrienne, L1 aRotter, Jerome, I1 aMorrison, Alanna, C1 aRich, Stephen, S1 aRipatti, Samuli1 aWiller, Cristen1 aPeloso, Gina, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aFinnGen uhttps://chs-nhlbi.org/node/871106233nas a2201609 4500008004100000022001400041245009500055210006900150260001600219520178500235100001702020700002102037700001902058700002102077700002302098700001502121700001802136700002002154700002202174700002002196700002802216700001802244700002202262700002402284700002102308700002002329700002002349700001502369700002502384700001702409700003102426700002002457700002302477700002302500700002102523700001702544700002002561700002102581700002702602700001902629700002402648700002602672700002102698700001802719700001702737700001902754700002802773700002002801700002402821700002202845700002202867700001902889700001402908700002102922700002102943700002502964700002002989700002203009700001803031700002203049700002003071700001903091700002303110700002003133700002803153700001603181700001503197700001703212700001403229700002003243700002303263700001903286700001603305700002003321700001703341700002103358700001903379700001303398700001703411700002203428700002403450700002903474700002003503700001503523700002303538700002403561700002203585700002003607700001803627700001703645700002103662700001903683700002103702700001603723700001503739700002603754700002003780700002403800700002203824700002103846700001703867700001803884700001703902700002203919700002203941700002003963700002603983700002204009700001904031700001504050700002004065700002204085700002404107700002404131700002604155700002004181700002004201700002304221700001804244700002104262700002204283700002104305700001804326700002404344700001804368700001904386700001604405700001904421700001804440700002004458700002704478700002104505700002004526700001904546700002204565856003604587 2021 eng d a1476-557800aMulti-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.0 aMultiancestry genomewide genesleep interactions identify novel l c2021 Apr 153 aLong and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
1 aWang, Heming1 aNoordam, Raymond1 aCade, Brian, E1 aSchwander, Karen1 aWinkler, Thomas, W1 aLee, Jiwon1 aSung, Yun, Ju1 aBentley, Amy, R1 aManning, Alisa, K1 aAschard, Hugues1 aKilpeläinen, Tuomas, O1 aIlkov, Marjan1 aBrown, Michael, R1 aHorimoto, Andrea, R1 aRichard, Melissa1 aBartz, Traci, M1 aVojinovic, Dina1 aLim, Elise1 aNierenberg, Jovia, L1 aLiu, Yongmei1 aChitrala, Kumaraswamynaidu1 aRankinen, Tuomo1 aMusani, Solomon, K1 aFranceschini, Nora1 aRauramaa, Rainer1 aAlver, Maris1 aZee, Phyllis, C1 aHarris, Sarah, E1 avan der Most, Peter, J1 aNolte, Ilja, M1 aMunroe, Patricia, B1 aPalmer, Nicholette, D1 aKuhnel, Brigitte1 aWeiss, Stefan1 aWen, Wanqing1 aHall, Kelly, A1 aLyytikäinen, Leo-Pekka1 aO'Connell, Jeff1 aEiriksdottir, Gudny1 aLauner, Lenore, J1 ade Vries, Paul, S1 aArking, Dan, E1 aChen, Han1 aBoerwinkle, Eric1 aKrieger, Jose, E1 aSchreiner, Pamela, J1 aSidney, Stephen1 aShikany, James, M1 aRice, Kenneth1 aChen, Yii-Der Ida1 aGharib, Sina, A1 aBis, Joshua, C1 aLuik, Annemarie, I1 aIkram, Arfan, M1 aUitterlinden, André, G1 aAmin, Najaf1 aXu, Hanfei1 aLevy, Daniel1 aHe, Jiang1 aLohman, Kurt, K1 aZonderman, Alan, B1 aRice, Treva, K1 aSims, Mario1 aWilson, Gregory1 aSofer, Tamar1 aRich, Stephen, S1 aPalmas, Walter1 aYao, Jie1 aGuo, Xiuqing1 aRotter, Jerome, I1 aBiermasz, Nienke, R1 aMook-Kanamori, Dennis, O1 aMartin, Lisa, W1 aBarac, Ana1 aWallace, Robert, B1 aGottlieb, Daniel, J1 aKomulainen, Pirjo1 aHeikkinen, Sami1 aMägi, Reedik1 aMilani, Lili1 aMetspalu, Andres1 aStarr, John, M1 aMilaneschi, Yuri1 aWaken, R, J1 aGao, Chuan1 aWaldenberger, Melanie1 aPeters, Annette1 aStrauch, Konstantin1 aMeitinger, Thomas1 aRoenneberg, Till1 aVölker, Uwe1 aDörr, Marcus1 aShu, Xiao-Ou1 aMukherjee, Sutapa1 aHillman, David, R1 aKähönen, Mika1 aWagenknecht, Lynne, E1 aGieger, Christian1 aGrabe, Hans, J1 aZheng, Wei1 aPalmer, Lyle, J1 aLehtimäki, Terho1 aGudnason, Vilmundur1 aMorrison, Alanna, C1 aPereira, Alexandre, C1 aFornage, Myriam1 aPsaty, Bruce, M1 aDuijn, Cornelia, M1 aLiu, Ching-Ti1 aKelly, Tanika, N1 aEvans, Michele, K1 aBouchard, Claude1 aFox, Ervin, R1 aKooperberg, Charles1 aZhu, Xiaofeng1 aLakka, Timo, A1 aEsko, Tõnu1 aNorth, Kari, E1 aDeary, Ian, J1 aSnieder, Harold1 aPenninx, Brenda, W J H1 aGauderman, James1 aRao, Dabeeru, C1 aRedline, Susan1 avan Heemst, Diana uhttps://chs-nhlbi.org/node/871404296nas a2200973 4500008004100000022001400041245010700055210006900162260001600231520147300247100002301720700002101743700001901764700001801783700001901801700002301820700001901843700001701862700001901879700003001898700002601928700002801954700002801982700002102010700001702031700002202048700002302070700002202093700002202115700002102137700002402158700002302182700002002205700002402225700002002249700002102269700002302290700002402313700002402337700001902361700001902380700002002399700001902419700002502438700002302463700002402486700002002510700002302530700001602553700002202569700002002591700002002611700001702631700002202648700001802670700002402688700002402712700002302736700002402759700001902783700001502802700002302817700002502840700002502865700002202890700002402912700001902936700002602955700002602981700002103007700002103028700002203049700002303071700002003094700002703114700002103141700002003162700002103182700001903203700002003222700002303242700002103265856003603286 2021 eng d a1476-625600aA System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.0 aSystem for Phenotype Harmonization in the NHLBI TransOmics for P c2021 Apr 163 aGenotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.
1 aStilp, Adrienne, M1 aEmery, Leslie, S1 aBroome, Jai, G1 aButh, Erin, J1 aKhan, Alyna, T1 aLaurie, Cecelia, A1 aWang, Fei, Fei1 aWong, Quenna1 aChen, Dongquan1 aD'Augustine, Catherine, M1 aHeard-Costa, Nancy, L1 aHohensee, Chancellor, R1 aJohnson, William, Craig1 aJuarez, Lucia, D1 aLiu, Jingmin1 aMutalik, Karen, M1 aRaffield, Laura, M1 aWiggins, Kerri, L1 ade Vries, Paul, S1 aKelly, Tanika, N1 aKooperberg, Charles1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aReiner, Alex, P1 aArnett, Donna, K1 aAslibekyan, Stella1 aBarnes, Kathleen, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aChen, Ming-Huei1 aCorrea, Adolfo1 aCupples, Adrienne, L1 ade Andrade, Mariza1 aEllinor, Patrick, T1 aFornage, Myriam1 aFranceschini, Nora1 aGan, Weiniu1 aGanesh, Santhi, K1 aGraffelman, Jan1 aGrove, Megan, L1 aGuo, Xiuqing1 aHawley, Nicola, L1 aHsu, Wan-Ling1 aJackson, Rebecca, D1 aJaquish, Cashell, E1 aJohnson, Andrew, D1 aKardia, Sharon, L R1 aKelly, Shannon1 aLee, Jiwon1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNorth, Kari, E1 aNouraie, Seyed, Mehdi1 aOelsner, Elizabeth, C1 aPankratz, Nathan1 aRich, Stephen, S1 aRotter, Jerome, I1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aWeeks, Daniel, E1 aWeiss, Scott, T1 aWilson, Carla, G1 aYanek, Lisa, R1 aPsaty, Bruce, M1 aHeckbert, Susan, R1 aLaurie, Cathy, C uhttps://chs-nhlbi.org/node/871303828nas a2200625 4500008004100000022001400041245010800055210006900163260001500232300000800247490000700255520201900262100001902281700001502300700001702315700001702332700001502349700001402364700002002378700002402398700001702422700002402439700002002463700001602483700001302499700002102512700002202533700001802555700001902573700002102592700002002613700002202633700002202655700002002677700002002697700002302717700002502740700002402765700001902789700002502808700002202833700002602855700001902881700002002900700002202920700002102942700002202963700002702985700002103012700001803033700001903051710006503070710003103135856003603166 2021 eng d a1756-994X00aWhole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program.0 aWholegenome association analyses of sleepdisordered breathing ph c2021 08 26 a1360 v133 aBACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.
METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.
RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.
CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.
1 aCade, Brian, E1 aLee, Jiwon1 aSofer, Tamar1 aWang, Heming1 aZhang, Man1 aChen, Han1 aGharib, Sina, A1 aGottlieb, Daniel, J1 aGuo, Xiuqing1 aLane, Jacqueline, M1 aLiang, Jingjing1 aLin, Xihong1 aMei, Hao1 aPatel, Sanjay, R1 aPurcell, Shaun, M1 aSaxena, Richa1 aShah, Neomi, A1 aEvans, Daniel, S1 aHanis, Craig, L1 aHillman, David, R1 aMukherjee, Sutapa1 aPalmer, Lyle, J1 aStone, Katie, L1 aTranah, Gregory, J1 aAbecasis, Goncalo, R1 aBoerwinkle, Eric, A1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aKaplan, Robert, C1 aNickerson, Deborah, A1 aNorth, Kari, E1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aRich, Stephen, S1 aTracy, Russell, P1 aVasan, Ramachandran, S1 aWilson, James, G1 aZhu, Xiaofeng1 aRedline, Susan1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Sleep Working Group uhttps://chs-nhlbi.org/node/892008881nas a2202605 4500008004100000022001400041245012200055210006900177260001500246300001000261490000800271520141300279653001201692653001801704653002501722653002601747653002301773653003001796653001001826653003801836653002201874653002501896653003401921653001101955653002101966653001101987653001001998653003402008653003102042653002402073653001402097653003602111100001802147700001902165700002102184700002002205700001802225700003202243700001702275700001702292700003102309700003002340700002102370700002102391700002302412700001602435700002802451700002902479700001802508700002102526700002402547700001902571700001902590700002102609700002502630700002102655700002202676700002102698700002302719700001902742700001902761700001902780700002702799700001702826700002002843700002102863700002002884700002002904700001902924700002902943700002402972700001902996700002503015700002203040700001703062700002203079700002303101700002403124700002803148700002203176700002403198700002103222700002003243700002003263700002303283700002103306700003103327700002803358700001803386700002203404700002203426700002103448700002303469700003903492700002203531700002103553700001803574700001903592700001703611700001903628700001503647700002003662700001903682700001403701700002603715700001703741700002103758700002503779700002603804700002003830700002003850700002403870700001803894700002103912700001903933700001703952700001703969700002003986700002504006700002404031700002204055700002004077700001904097700002104116700001504137700001704152700001804169700002104187700002404208700002104232700001704253700002004270700002204290700002304312700002004335700002804355700003604383700002304419700002504442700002004467700002004487700002204507700001904529700002604548700002304574700001504597700002104612700002204633700002004655700002904675700002404704700002004728700002104748700002204769700002604791700002504817700001904842700002304861700002604884700002104910700002104931700001904952700002104971700002404992700001905016700002005035700002005055700001405075700001405089700001905103700002505122700003105147700002105178700001905199700002405218700002305242700001705265700001905282700001705301700001605318700002105334700001805355700002305373700001905396700002205415700002005437700001905457700002005476700002105496700002105517700002205538700002305560700002405583700002105607700002005628700002705648700003005675700001905705700001605724700001805740700002105758700002105779700002105800700001905821700001905840700002205859700002105881700002205902700002105924700002205945700002305967700002305990700002306013700001906036700002006055710006106075710006506136710003806201856003606239 2022 eng d a1537-660500aRare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.0 aRare coding variants in 35 genes associate with circulating lipi c2022 01 06 a81-960 v1093 aLarge-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
10aAlleles10aBlood Glucose10aCase-Control Studies10aComputational Biology10aDatabases, Genetic10aDiabetes Mellitus, Type 210aExome10aGenetic Predisposition to Disease10aGenetic Variation10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLipid Metabolism10aLipids10aLiver10aMolecular Sequence Annotation10aMultifactorial Inheritance10aOpen Reading Frames10aPhenotype10aPolymorphism, Single Nucleotide1 aHindy, George1 aDornbos, Peter1 aChaffin, Mark, D1 aLiu, Dajiang, J1 aWang, Minxian1 aSelvaraj, Margaret, Sunitha1 aZhang, David1 aPark, Joseph1 aAguilar-Salinas, Carlos, A1 aAntonacci-Fulton, Lucinda1 aArdissino, Diego1 aArnett, Donna, K1 aAslibekyan, Stella1 aAtzmon, Gil1 aBallantyne, Christie, M1 aBarajas-Olmos, Francisco1 aBarzilai, Nir1 aBecker, Lewis, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBottinger, Erwin1 aBowden, Donald, W1 aBown, Matthew, J1 aBrody, Jennifer, A1 aBroome, Jai, G1 aBurtt, Noel, P1 aCade, Brian, E1 aCenteno-Cruz, Federico1 aChan, Edmund1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aCheng, Ching-Yu1 aChoi, Won, Jung1 aChowdhury, Raj1 aContreras-Cubas, Cecilia1 aCórdova, Emilio, J1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDanesh, John1 ade Vries, Paul, S1 aDeFronzo, Ralph, A1 aDoddapaneni, Harsha1 aDuggirala, Ravindranath1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aFlorez, Jose, C1 aFornage, Myriam1 aFreedman, Barry, I1 aFuster, Valentin1 aGaray-Sevilla, Ma, Eugenia1 aGarcía-Ortiz, Humberto1 aGermer, Soren1 aGibbs, Richard, A1 aGieger, Christian1 aGlaser, Benjamin1 aGonzalez, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGraff, Mariaelisa1 aGraham, Sarah, E1 aGrarup, Niels1 aGroop, Leif, C1 aGuo, Xiuqing1 aGupta, Namrata1 aHan, Sohee1 aHanis, Craig, L1 aHansen, Torben1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aIrvin, Marguerite, R1 aIslas-Andrade, Sergio1 aJarvik, Gail, P1 aKang, Hyun, Min1 aKardia, Sharon, L R1 aKelly, Tanika1 aKenny, Eimear, E1 aKhan, Alyna, T1 aKim, Bong-Jo1 aKim, Ryan, W1 aKim, Young, Jin1 aKoistinen, Heikki, A1 aKooperberg, Charles1 aKuusisto, Johanna1 aKwak, Soo, Heon1 aLaakso, Markku1 aLange, Leslie, A1 aLee, Jiwon1 aLee, Juyoung1 aLee, Seonwook1 aLehman, Donna, M1 aLemaitre, Rozenn, N1 aLinneberg, Allan1 aLiu, Jianjun1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aLyssenko, Valeriya1 aMa, Ronald, C W1 aMartin, Lisa, Warsinger1 aMartínez-Hernández, Angélica1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMcPherson, Ruth1 aMeigs, James, B1 aMeitinger, Thomas1 aMelander, Olle1 aMendoza-Caamal, Elvia1 aMetcalf, Ginger, A1 aMi, Xuenan1 aMohlke, Karen, L1 aMontasser, May, E1 aMoon, Jee-Young1 aMoreno-Macias, Hortensia1 aMorrison, Alanna, C1 aMuzny, Donna, M1 aNelson, Sarah, C1 aNilsson, Peter, M1 aO'Connell, Jeffrey, R1 aOrho-Melander, Marju1 aOrozco, Lorena1 aPalmer, Colin, N A1 aPalmer, Nicholette, D1 aPark, Cheol, Joo1 aPark, Kyong, Soo1 aPedersen, Oluf1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aPost, Wendy, S1 aPreuss, Michael1 aPsaty, Bruce, M1 aQi, Qibin1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRevilla-Monsalve, Cristina1 aRich, Stephen, S1 aSamani, Nilesh1 aSchunkert, Heribert1 aSchurmann, Claudia1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSim, Xueling1 aSladek, Rob1 aSmall, Kerrin, S1 aSo, Wing, Yee1 aStilp, Adrienne, M1 aTai, Shyong, E1 aTam, Claudia, H T1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aThameem, Farook1 aTomlinson, Brian1 aTsai, Michael, Y1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 avan Dam, Rob, M1 aVasan, Ramachandran, S1 aMartinez, Karine, A Viaud1 aWang, Fei, Fei1 aWang, Xuzhi1 aWatkins, Hugh1 aWeeks, Daniel, E1 aWilson, James, G1 aWitte, Daniel, R1 aWong, Tien-Yin1 aYanek, Lisa, R1 aKathiresan, Sekar1 aRader, Daniel, J1 aRotter, Jerome, I1 aBoehnke, Michael1 aMcCarthy, Mark, I1 aWiller, Cristen, J1 aNatarajan, Pradeep1 aFlannick, Jason, A1 aKhera, Amit, V1 aPeloso, Gina, M1 aAMP-T2D-GENES, Myocardial Infarction Genetics Consortium1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aNHLBI TOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/897503348nas a2200541 4500008004100000022001400041245012000055210006900175260001600244520177900260100002002039700001702059700001902076700002502095700001702120700001502137700002002152700002002172700001402192700002402206700002102230700001702251700002002268700001702288700002202305700002202327700002202349700002802371700002002399700001902419700001802438700002102456700002002477700002302497700002102520700001602541700001702557700002002574700002702594700002102621700002102642700002202663700001702685700001902702700001802721710003102739856003602770 2022 eng d a1535-497000aTargeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea.0 aTargeted Genome Sequencing Identifies Multiple Rare Variants in c2022 Jul 133 aINTRODUCTION: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epi-demiologic evidence supporting the importance of genetic factors influencing OSA, but limited data implicating specific genes.
METHODS: Leveraging high depth genomic sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the Cleve-land Family Study (CFS) followed by multi-stage gene-based association analyses in independent cohorts to search for rare variants contributing to OSA severity as assessed by the apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry.
RESULTS: Linkage analysis in CFS identified a suggestive linkage peak on chromosome 7q31 (LOD=2.31). Gene-based analysis identified 21 non-coding rare variants in Caveolin-1 (CAV1) associated with lower AHI after accounting for multiple comparisons (p=7.4×10-8). These non-coding variants together significantly contributed to the linkage evidence (p<10-3). Follow-up anal-ysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (p=0.024) and higher minimum overnight oxygen saturation (p=0.007).
CONCLUSION: Rare variants in CAV1, a membrane scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.
1 aLiang, Jingjing1 aWang, Heming1 aCade, Brian, E1 aKurniansyah, Nuzulul1 aHe, Karen, Y1 aLee, Jiwon1 aSands, Scott, A1 aBrody, Jennifer1 aChen, Han1 aGottlieb, Daniel, J1 aEvans, Daniel, S1 aGuo, Xiuqing1 aGharib, Sina, A1 aHale, Lauren1 aHillman, David, R1 aLutsey, Pamela, L1 aMukherjee, Sutapa1 aOchs-Balcom, Heather, M1 aPalmer, Lyle, J1 aPurcell, Shaun1 aSaxena, Richa1 aPatel, Sanjay, R1 aStone, Katie, L1 aTranah, Gregory, J1 aBoerwinkle, Eric1 aLin, Xihong1 aLiu, Yongmei1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aManichaikul, Ani1 aRich, Stephen, S1 aRotter, Jerome, I1 aSofer, Tamar1 aRedline, Susan1 aZhu, Xiaofeng1 aTOPMed Sleep Working Group uhttps://chs-nhlbi.org/node/910107212nas a2201753 4500008004100000245012700041210006900168260001600237520220800253100002502461700001902486700001602505700001902521700002302540700001902563700002302582700002102605700001802626700002002644700002402664700002302688700002902711700002302740700002002763700002102783700002102804700002102825700002402846700002202870700001902892700001502911700002102926700002002947700001802967700001902985700002103004700002503025700002603050700002103076700001903097700001903116700002803135700002203163700002203185700001903207700002003226700001803246700001703264700001503281700002003296700002803316700001703344700001703361700002703378700002503405700002003430700002003450700002003470700002403490700001203514700001603526700002003542700002803562700001603590700002103606700001903627700002103646700002703667700002103694700002403715700001603739700002203755700002403777700002503801700001703826700001403843700002103857700002003878700002203898700001903920700002003939700001503959700002003974700002203994700002404016700002004040700001804060700002004078700002704098700001804125700001704143700002104160700001604181700001804197700002404215700002004239700002004259700002604279700001904305700002004324700002304344700002304367700002504390700002004415700003004435700001804465700002304483700001804506700002104524700001904545700002004564700001804584700001904602700002304621700002204644700002004666700001904686700002204705700002004727700001904747700002304766700002104789700002004810700002304830700002504853700002904878700002904907700001904936700002604955700001904981700002205000700002005022700002405042700002005066700001705086700001805103700002105121700001305142700003205155700002305187700002205210700002205232700002505254700002405279700002305303710003105326710006505357856003605422 2023 eng d00aWhole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.0 aWhole genome analysis of plasma fibrinogen reveals populationdif c2023 Jun 123 aUNLABELLED: Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( , and signals contain predicted deleterious missense variants. Two loci, and , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.
KEY POINTS: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.
1 aHuffman, Jennifer, E1 aNicolas, Jayna1 aHahn, Julie1 aHeath, Adam, S1 aRaffield, Laura, M1 aYanek, Lisa, R1 aBrody, Jennifer, A1 aThibord, Florian1 aAlmasy, Laura1 aBartz, Traci, M1 aBielak, Lawrence, F1 aBowler, Russell, P1 aCarrasquilla, Germán, D1 aChasman, Daniel, I1 aChen, Ming-Huei1 aEmmert, David, B1 aGhanbari, Mohsen1 aHaessle, Jeffery1 aHottenga, Jouke-Jan1 aKleber, Marcus, E1 aLe, Ngoc-Quynh1 aLee, Jiwon1 aLewis, Joshua, P1 aLi-Gao, Ruifang1 aLuan, Jian'an1 aMalmberg, Anni1 aMangino, Massimo1 aMarioni, Riccardo, E1 aMartinez-Perez, Angel1 aPankratz, Nathan1 aPolasek, Ozren1 aRichmond, Anne1 aRodriguez, Benjamin, At1 aRotter, Jerome, I1 aSteri, Maristella1 aSuchon, Pierre1 aTrompet, Stella1 aWeiss, Stefan1 aZare, Marjan1 aAuer, Paul1 aCho, Michael, H1 aChristofidou, Paraskevi1 aDavies, Gail1 ade Geus, Eco1 aDeleuze, Jean-Francois1 aDelgado, Graciela, E1 aEkunwe, Lynette1 aFaraday, Nauder1 aGögele, Martin1 aGreinacher, Andreas1 aHe, Gao1 aHoward, Tom1 aJoshi, Peter, K1 aKilpeläinen, Tuomas, O1 aLahti, Jari1 aLinneberg, Allan1 aNaitza, Silvia1 aNoordam, Raymond1 aPaüls-Vergés, Ferran1 aRich, Stephen, S1 aRosendaal, Frits, R1 aRudan, Igor1 aRyan, Kathleen, A1 aSouto, Juan, Carlos1 avan Rooij, Frank, Ja1 aWang, Heming1 aZhao, Wei1 aBecker, Lewis, C1 aBeswick, Andrew1 aBrown, Michael, R1 aCade, Brian, E1 aCampbell, Harry1 aCho, Kelly1 aCrapo, James, D1 aCurran, Joanne, E1 ade Maat, Moniek, Pm1 aDoyle, Margaret1 aElliott, Paul1 aFloyd, James, S1 aFuchsberger, Christian1 aGrarup, Niels1 aGuo, Xiuqing1 aHarris, Sarah, E1 aHou, Lifang1 aKolcic, Ivana1 aKooperberg, Charles1 aMenni, Cristina1 aNauck, Matthias1 aO'Connell, Jeffrey, R1 aOrrù, Valeria1 aPsaty, Bruce, M1 aRäikkönen, Katri1 aSmith, Jennifer, A1 aSoria, José, Manuel1 aStott, David, J1 aVlieg, Astrid, van Hylcka1 aWatkins, Hugh1 aWillemsen, Gonneke1 aWilson, Peter1 aBen-Shlomo, Yoav1 aBlangero, John1 aBoomsma, Dorret1 aCox, Simon, R1 aDehghan, Abbas1 aEriksson, Johan, G1 aFiorillo, Edoardo1 aFornage, Myriam1 aHansen, Torben1 aHayward, Caroline1 aIkram, Arfan, M1 aJukema, Wouter1 aKardia, Sharon, Lr1 aLange, Leslie, A1 aMärz, Winfried1 aMathias, Rasika, A1 aMitchell, Braxton, D1 aMook-Kanamori, Dennis, O1 aMorange, Pierre-Emmanuel1 aPedersen, Oluf1 aPramstaller, Peter, P1 aRedline, Susan1 aReiner, Alexander1 aRidker, Paul, M1 aSilverman, Edwin, K1 aSpector, Tim, D1 aVölker, Uwe1 aWareham, Nick1 aWilson, James, F1 aYao, Jie1 aTrégouët, David-Alexandre1 aJohnson, Andrew, D1 aWolberg, Alisa, S1 ade Vries, Paul, S1 aSabater-Lleal, Maria1 aMorrison, Alanna, C1 aSmith, Nicholas, L1 aVA Million Veteran Program1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/9449