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AuthorRamdas, Shweta
AuthorJudd, Jonathan
AuthorGraham, Sarah E.
AuthorKanoni, Stavroula
AuthorWang, Yuxuan
AuthorSurakka, Ida
AuthorWenz, Brandon
AuthorClarke, Shoa L.
AuthorChesi, Alessandra
AuthorWells, Andrew
AuthorBhatti, Konain Fatima
AuthorVedantam, Sailaja
AuthorWinkler, Thomas W.
AuthorLocke, Adam E.
AuthorMarouli, Eirini
AuthorZajac, Greg J.M.
AuthorWu, Kuan Han H.
AuthorNtalla, Ioanna
AuthorHui, Qin
AuthorKlarin, Derek
AuthorHilliard, Austin T.
AuthorWang, Zeyuan
AuthorXue, Chao
AuthorThorleifsson, Gudmar
AuthorHelgadottir, Anna
AuthorGudbjartsson, Daniel F.
AuthorHolm, Hilma
AuthorOlafsson, Isleifur
AuthorHwang, Mi Yeong
AuthorHan, Sohee
AuthorAkiyama, Masato
AuthorSakaue, Saori
AuthorTerao, Chikashi
AuthorKanai, Masahiro
AuthorZhou, Wei
AuthorBrumpton, Ben M.
AuthorRasheed, Humaira
AuthorHavulinna, Aki S.
AuthorVeturi, Yogasudha
AuthorPacheco, Jennifer Allen
AuthorRosenthal, Elisabeth A.
AuthorLingren, Todd
AuthorFeng, Qi Ping
AuthorKullo, Iftikhar J.
AuthorNarita, Akira
AuthorTakayama, Jun
AuthorMartin, Hilary C.
AuthorHunt, Karen A.
AuthorTrivedi, Bhavi
AuthorHaessler, Jeffrey
AuthorGiulianini, Franco
AuthorBradford, Yuki
AuthorMiller, Jason E.
AuthorCampbell, Archie
AuthorLin, Kuang
AuthorMillwood, Iona Y.
AuthorRasheed, Asif
AuthorHindy, George
AuthorFaul, Jessica D.
AuthorZhao, Wei
AuthorWeir, David R.
AuthorTurman, Constance
AuthorHuang, Hongyan
AuthorGraff, Mariaelisa
AuthorChoudhury, Ananyo
AuthorSengupta, Dhriti
AuthorMahajan, Anubha
AuthorBrown, Michael R.
AuthorZhang, Weihua
AuthorYu, Ketian
AuthorSchmidt, Ellen M.
AuthorPandit, Anita
AuthorGustafsson, Stefan
AuthorYin, Xianyong
AuthorLuan, Jian'an
AuthorZhao, Jing Hua
AuthorMatsuda, Fumihiko
AuthorJang, Hye Mi
AuthorYoon, Kyungheon
AuthorMedina-Gomez, Carolina
AuthorPitsillides, Achilleas
AuthorHottenga, Jouke Jan
AuthorWood, Andrew R.
AuthorJi, Yingji
AuthorGao, Zishan
AuthorHaworth, Simon
AuthorMitchell, Ruth E.
AuthorChai, Jin Fang
AuthorAadahl, Mette
AuthorBjerregaard, Anne A.
AuthorYao, Jie
AuthorManichaikul, Ani
AuthorLee, Wen Jane
AuthorHsiung, Chao Agnes
AuthorWarren, Helen R.
AuthorRamirez, Julia
AuthorBork-Jensen, Jette
AuthorKårhus, Line L.
AuthorGoel, Anuj
AuthorSabater-Lleal, Maria
Available date2023-05-09T10:54:18Z
Publication Date2022-08-04
Publication NameAmerican Journal of Human Genetics
Identifierhttp://dx.doi.org/10.1016/j.ajhg.2022.06.012
ISSN00029297
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85135598739&origin=inward
URIhttp://hdl.handle.net/10576/42514
AbstractA 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.
SponsorXiang Zhu is supported by the Stein Fellowship from Stanford University and Institute for Computational and Data Sciences Seed Grant from The Pennsylvania State University. C.D.B. is supported by the NIH (R01-HL133218). Funding for the Global Lipids Genetics Consortium was provided by the NIH (R01-HL127564). This research was conducted using the UK Biobank Resource under application number 24460. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by awards 2I01BX003362-03A1 and 1I01BX004821-01A1. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. We thank Bethany Klunder for administrative support. Study-specific acknowledgments are provided in the supplemental information.
Languageen
PublisherElsevier
Subjectcomplex traits
fine-mapping
functional genomics
lipid biology
post-GWAS
regulatory mechanism
variant prioritization
TitleA multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
TypeArticle
Pagination1366-1387
Issue Number8
Volume Number109
dc.accessType Open Access


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