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AnnetteGieger, ChristianHattersley, Andrew TPedersen, Nancy LMagnusson, Patrik K EBoomsma, Dorret Ide Geus, Eco J CCupples, L Adriennevan Meurs, Joyce B JIkram, ArfanGhanbari, MohsenGordon-Larsen, PennyHuang, WeiKim, Young JinTabara, YasuharuWareham, Nicholas JLangenberg, ClaudiaZeggini, EleftheriaTuomilehto, JaakkoKuusisto, JohannaLaakso, MarkkuIngelsson, ErikAbecasis, GoncaloChambers, John CKooner, Jaspal Sde Vries, Paul SMorrison, Alanna CHazelhurst, ScottRamsay, MichèleNorth, Kari EDaviglus, MarthaKraft, PeterMartin, Nicholas GWhitfield, John BAbbas, ShahidSaleheen, DanishWalters, Robin GHolmes, Michael VBlack, CorriSmith, Blair HBaras, ArisJustice, Anne EBuring, Julie ERidker, Paul MChasman, Daniel IKooperberg, CharlesTamiya, GenYamamoto, Masayukivan Heel, David ATrembath, Richard CWei, Wei-QiJarvik, Gail PNamjou, BahramHayes, M GeoffreyRitchie, Marylyn DJousilahti, PekkaSalomaa, VeikkoHveem, KristianÅsvold, Bjørn OlavKubo, MichiakiKamatani, YoichiroOkada, YukinoriMurakami, YoshinoriKim, Bong-JoThorsteinsdottir, UnnurStefansson, KariZhang, JifengChen, Y EugeneHo, Yuk-LamLynch, Julie ATsao, Philip SChang, Kyong-MiCho, KellyO'Donnell, Christopher JGaziano, John MWilson, PeterMohlke, Karen LFrayling, Timothy MHirschhorn, Joel NKathiresan, SekarBoehnke, MichaelMillion Veterans ProgramGlobal Lipids Genetics ConsortiumStruan Grant,Natarajan, PradeepSun, Yan VMorris, Andrew PDeloukas, PanosPeloso, GinaAssimes, Themistocles LWiller, Cristen JZhu, XiangBrown, Christopher D2023-05-032023-05-032022/01/23Ramdas S, Judd J, Graham SE, Kanoni S, Wang Y, Surakka I,, et al. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. Am J Hum Genet. 2022 Aug 4;109(8):1366-1387.http://hdl.handle.net/10668/21878A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.encomplex traitsfine-mappingfunctional genomicslipid biologypost-GWASregulatory mechanismvariant prioritizationChromatinGenome-Wide Association StudyGenomicsHumansLipidsPolymorphism, Single Nucleotideresearch article35931049Restricted AccessCromatinaEstudio de asociación del GenomaGenómicaPolimorfismo de nucleótido simpleLípidos10.1016/j.ajhg.2022.06.0121537-6605PMC9388392https://doi.org/10.1016/j.ajhg.2022.06.012https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388392/pdf