biostudies-literatureSelvaraj MSNHLBI TOPMed fellowshipNational Institutes of Health (NIH)273https://www.ebi.ac.uk/biostudies/studies/S-EPMC12418676biostudies-literatureUnknown26(1)<h4>Background</h4>Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.<h4>Results</h4>Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) pGenome biologyWhole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.PMC12418676R01HL14271175N92021F00229Ekunwe LBowden DWLaurie CManning AGlahn DBoueiz AESalzberg SSylvia JSandow KNekhai SGraham Barr RTsai MYWalker TXu HChaffin MRussell PGass MChung RHLevy DFarek JHwu CMPreuss MTishkoff SCarrier JChuang LMReed RZiv EAvramopoulos DCornell EYarden RSotoodehnia NYu KMay SMathai Sde Las Fuentes LPapanicolaou GStorm GHeard-Costa Nde Andrade MSmith AVBroome JTaylor KDWong QHong EAlmasy LChung MRoden DRunnels AManson JRegan ESnyder MZhu XNessner CMcFarland SNadkarni GPostupaka DCurran JEDavis CCarlson JCBroeckel UFranceschini NGu CCAbe NSalvi SClish CTracy RLunetta KVrieze SKral BGGladwin MPeralta JMDevine SRajendran MConomos MPhillips LSLiu SWeir BLiu YMeigs JJohnson APollin TRuczinski IDavid SJohnson CArnett DKPerez MBlue NErzurum SWeinstock JStilp AMHernandez RHou LFlickinger MGuan YChoi SHWinterkorn LHuston HHarris DAnderson PMontasser MEBeitelshees AGelb BMagalang UMathias RGuo XSzpiro ANelson SCJohnsen JTong CDamrauer SMReupena M'SMychaleckyj JCArdlie KAlonso ASung YJZoellner SLevine DLeBoff MMcGarvey SHerrington DHixson JKimoff JFrazar CRyan KKramer HJohnston RKalyani RRYanek LRVandeHaar PBlangero JGraff MHan YWalts AViali SMomin ZMarton MSeidman CSabino ECChang CCasella JGeiger HReiner APSelvaraj MSSeidman SMontgomery CKenny ECurtis JThrelkeld MHobbs BCuster BKooperberg CCastaldi PCarson APFu Mde Vries PSGrine DSilverman EKonkle BMinear MMin NWatson KHaessler JRafaels NDeBaun MGabriel SLubitz SCarey VCasaburi RComhair SFreedman BIKonigsberg IRSeries FTinker LFingerlin TGao YManichaikul AWLange LAAslibekyan SDuggirala RKraus WEBurchard EGao SHeavner BZekavat SMBecker LMignot EKhan ZCasas Romero JPTiwari HSchwartz DCho MWang FFDeka RMcHugh CPerry JGraw SRao DCKhan ALeFaive JSmith JMahaney MGross CSmith NCade BEBenos TSmith TMei HDeMeo DAyas NBecker DGan WRobillard RNorth KECupples LAPsaty BMKardia SLRMetcalf GDarbar DWilliams KBezerra MLin XTaylor STaylor MSnively BPack AGeraci MSheehan VHall MKang HMPost WHe JGignoux CJain DFulton LMuzny DWilliams LKChavan SShoemaker MBHu JLin HShah SHHersh CSalimi SWilliams SKelly SZhao WNaseri TRuuska SLoos RJFRamachandran VSMestroni LRasmussen-Torvik LTirschwell DMinster RLAguet FMake BGhosh AHokanson JLange ELange CReeves CHoth KMartin LWMeyers DABis JCAssimes TAuer PHidalgo BABarnard JMitchell BDRotter JICrandall CCardwell JGerszten RRich SSO'Connor TMcNeil BNickerson DVaidya DPeters UWatt JGupta NAbecasis GLewis JRobine NLi CBarnes KKwee LCGoring HParker CFarber CBecker JPLi XLi YLi ZJones KKelly TNOkwuonu GFornage MKaplan RCNeltner BViaud-Martinez KAChen BJSherman SLWessel JRoselli CArking DDaya MHaidermota SWallace RAshley-Koch ABielak LMenon VBeer RNatarajan PWiller COchs-Balcom HJackson RLee WJChasman DChang YCThornton TAHanly PLuo JZhang YNHLBI Trans-Omics for Precision Medicine (TOPMed) ConsortiumSaleheen DZhao SXVan Buren EMcArdle PAlbert CEmery LRice KWilson JMorrison ACSheu WHPleiness JBalasubramanian AHawley NLTelen MJaquish CRaffield LO'Connell JRBlackwell TSankaran VGQiao DSmit RAJEllinor PTTaliun DRedline SBeck GChen WMSciurba FDutcher SKShetty ABustamante CSchwander KIrvin RIrvin MRLee SKessler MRatan ALee JCorrea ASantibanez JVan Den Berg DCrapo JDugan-Perez STang HEaton CBarron-Casella EQin ZHsiung CACarty CSmith JAHornsby WSkomro RTaub MSilver BSu JLPalmer NDHung YJFullerton SMKim RWilson CKim WGibbs RWu JNkechinyere ODinh HNaik RZody MBoerwinkle EWu BWang HBrown DWang JMikulla JQasba PJudy RBeaty TPeloso GMBarwick LWang YWang ZYang IApplebaum-Bowden DAment SPaik DTAnugu PMcGoldrick DWeeks DEBrody JADamcott CDurda JPO'Connell JPeyser PAGogarten SKinney GRader DJSmoller SWeng LCPankow JButh EHeckbert SGong DWBoorgula MPSofer TWeiss STGermer SMoll MBunting KMcDonald MLDoddapaneni HDuan QBenjamin EStreeten EGray KJChen YIfalseWhole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.<h4>Background</h4>Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.<h4>Results</h4>Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) p2025-01-01T00:00:00Z2025 Sep2026-06-02T17:44:18.162Z2026-05-27T03:07:30.82ZS-EPMC124186764092620910.1186/s13059-025-03698-0