Selvaraj, Margaret SunithaMargaret SunithaSelvarajLi, XihaoXihaoLiLi, ZilinZilinLiVan Buren, EricEricVan BurenHaidermota, SaraSaraHaidermotaPostupaka, DarinaDarinaPostupakaHornsby, WhitneyWhitneyHornsbyBis, Joshua CJoshua CBisBrody, Jennifer AJennifer ABrodyCade, Brian EBrian ECadeChung, Ren-HuaRen-HuaChungCurran, Joanne EJoanne ECurranDamrauer, Scott MScott MDamrauerde Las Fuentes, LisaLisade Las Fuentesde Vries, Paul SPaul Sde VriesDuggirala, RavindranathRavindranathDuggiralaFreedman, Barry IBarry IFreedmanGraff, MariaElisaMariaElisaGraffGuo, XiuqingXiuqingGuoHidalgo, Bertha ABertha AHidalgoHou, LifangLifangHouIrvin, RyanRyanIrvinJudy, RenaeRenaeJudyKalyani, Rita RRita RKalyaniKelly, Tanika NTanika NKellyKonigsberg, Iain RIain RKonigsbergKral, Brian GBrian GKralKwee, Lydia CoulterLydia CoulterKweeLevy, DanielDanielLevyLi, ChangweiChangweiLiManichaikul, Ani WAni WManichaikulMartin, Lisa WarsingerLisa WarsingerMartinMontasser, May EMay EMontasserMorrison, Alanna CAlanna CMorrisonNaseri, TakeTakeNaseriNorth, Kari EKari ENorthO'Connell, Jeffrey RJeffrey RO'ConnellPalmer, Nicholette DNicholette DPalmerPeyser, Patricia APatricia APeyserReiner, Alex PAlex PReinerShah, Svati HSvati HShahSmit, Roelof A JRoelof A JSmitSmith, Jennifer AJennifer ASmithTaylor, Kent DKent DTaylorTiwari, HemantHemantTiwariTsai, Michael YMichael YTsaiViali, Satupa'iteaSatupa'iteaVialiWang, ZheZheWangWang, YuxuanYuxuanWangZhao, WeiWeiZhaoArnett, Donna KDonna KArnettBlangero, JohnJohnBlangeroBoerwinkle, EricEricBoerwinkleBowden, Donald WDonald WBowdenCarlson, Jenna CJenna CCarlsonChen, Yii-Der IdaYii-Der IdaChenEllinor, Patrick TPatrick TEllinorFornage, MyriamMyriamFornageHe, JiangJiangHeHeard-Costa, NancyNancyHeard-CostaKaplan, Robert CRobert CKaplanKardia, Sharon L RSharon L RKardiaKooperberg, CharlesCharlesKooperbergKraus, William EWilliam EKrausLange, Leslie ALeslie ALangeLoos, Ruth J FRuth J FLoosMitchell, Braxton DBraxton DMitchellPsaty, Bruce MBruce MPsatyRader, Daniel JDaniel JRaderRedline, SusanSusanRedlineRich, Stephen SStephen SRichYanek, Lisa RLisa RYanekGibbs, RichardRichardGibbsGabriel, StaceyStaceyGabrielViaud-Martinez, Karine AKarine AViaud-MartinezDutcher, Susan KSusan KDutcherGermer, SorenSorenGermerKim, RyanRyanKimRotter, Jerome IJerome IRotterLin, XihongXihongLinPeloso, Gina MGina MPelosoNatarajan, PradeepPradeepNatarajanLEE-MING CHUANGYI-CHENG CHANGet al.2025-12-122025-12-122025-09-09https://scholars.lib.ntu.edu.tw/handle/123456789/734535Background: 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. Results: 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) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate. Conclusions: This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.enjournal article10.1186/s13059-025-03698-0409262092-s2.0-105015796289