A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
Author | Ramdas, Shweta |
Author | Judd, Jonathan |
Author | Graham, Sarah E. |
Author | Kanoni, Stavroula |
Author | Wang, Yuxuan |
Author | Surakka, Ida |
Author | Wenz, Brandon |
Author | Clarke, Shoa L. |
Author | Chesi, Alessandra |
Author | Wells, Andrew |
Author | Bhatti, Konain Fatima |
Author | Vedantam, Sailaja |
Author | Winkler, Thomas W. |
Author | Locke, Adam E. |
Author | Marouli, Eirini |
Author | Zajac, Greg J.M. |
Author | Wu, Kuan Han H. |
Author | Ntalla, Ioanna |
Author | Hui, Qin |
Author | Klarin, Derek |
Author | Hilliard, Austin T. |
Author | Wang, Zeyuan |
Author | Xue, Chao |
Author | Thorleifsson, Gudmar |
Author | Helgadottir, Anna |
Author | Gudbjartsson, Daniel F. |
Author | Holm, Hilma |
Author | Olafsson, Isleifur |
Author | Hwang, Mi Yeong |
Author | Han, Sohee |
Author | Akiyama, Masato |
Author | Sakaue, Saori |
Author | Terao, Chikashi |
Author | Kanai, Masahiro |
Author | Zhou, Wei |
Author | Brumpton, Ben M. |
Author | Rasheed, Humaira |
Author | Havulinna, Aki S. |
Author | Veturi, Yogasudha |
Author | Pacheco, Jennifer Allen |
Author | Rosenthal, Elisabeth A. |
Author | Lingren, Todd |
Author | Feng, Qi Ping |
Author | Kullo, Iftikhar J. |
Author | Narita, Akira |
Author | Takayama, Jun |
Author | Martin, Hilary C. |
Author | Hunt, Karen A. |
Author | Trivedi, Bhavi |
Author | Haessler, Jeffrey |
Author | Giulianini, Franco |
Author | Bradford, Yuki |
Author | Miller, Jason E. |
Author | Campbell, Archie |
Author | Lin, Kuang |
Author | Millwood, Iona Y. |
Author | Rasheed, Asif |
Author | Hindy, George |
Author | Faul, Jessica D. |
Author | Zhao, Wei |
Author | Weir, David R. |
Author | Turman, Constance |
Author | Huang, Hongyan |
Author | Graff, Mariaelisa |
Author | Choudhury, Ananyo |
Author | Sengupta, Dhriti |
Author | Mahajan, Anubha |
Author | Brown, Michael R. |
Author | Zhang, Weihua |
Author | Yu, Ketian |
Author | Schmidt, Ellen M. |
Author | Pandit, Anita |
Author | Gustafsson, Stefan |
Author | Yin, Xianyong |
Author | Luan, Jian'an |
Author | Zhao, Jing Hua |
Author | Matsuda, Fumihiko |
Author | Jang, Hye Mi |
Author | Yoon, Kyungheon |
Author | Medina-Gomez, Carolina |
Author | Pitsillides, Achilleas |
Author | Hottenga, Jouke Jan |
Author | Wood, Andrew R. |
Author | Ji, Yingji |
Author | Gao, Zishan |
Author | Haworth, Simon |
Author | Mitchell, Ruth E. |
Author | Chai, Jin Fang |
Author | Aadahl, Mette |
Author | Bjerregaard, Anne A. |
Author | Yao, Jie |
Author | Manichaikul, Ani |
Author | Lee, Wen Jane |
Author | Hsiung, Chao Agnes |
Author | Warren, Helen R. |
Author | Ramirez, Julia |
Author | Bork-Jensen, Jette |
Author | Kårhus, Line L. |
Author | Goel, Anuj |
Author | Sabater-Lleal, Maria |
Available date | 2023-05-09T10:54:18Z |
Publication Date | 2022-08-04 |
Publication Name | American Journal of Human Genetics |
Identifier | http://dx.doi.org/10.1016/j.ajhg.2022.06.012 |
ISSN | 00029297 |
Abstract | A 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. |
Sponsor | Xiang 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. |
Language | en |
Publisher | Elsevier |
Subject | complex traits fine-mapping functional genomics lipid biology post-GWAS regulatory mechanism variant prioritization |
Type | Article |
Pagination | 1366-1387 |
Issue Number | 8 |
Volume Number | 109 |
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