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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids


Ramdas, S and Judd, J and Graham, SE and Kanoni, S and Wang, Y and Surakka, I and Wenz, B and Clarke, SL and Chesi, A and Wells, A and Bhatti, KF and Vedantam, S and Winkler, TW and Locke, AE and Marouli, E and Zajac, GJM and Wu, KHH and Ntalla, I and Hui, I and Klarin, D and Hilliard, AT and Wang, Z and Xue, C and Thorleifsson, G and Helgadottir, A and Gudbjartsson, DF and Holm, H and Olafsson, I and Hwang, MY and Han, S and Akiyama, M and Sakaue, S and Terao, C and Kanai, M and Zhou, W and Brumpton, BM and Rasheed, H and Havulinna, AS and Veturi, Y and Pacheco, JA and Rosenthal, EA and Lingren, T and Feng, QP and Kullo, IJ and Narita, A and Takayama, J and Martin, HC and Hunt, KA and Trivedi, B and Haessler, J and Giulianini, F and Bradford, Y and Miller, JE and Campbell, A and Lin, K and Millwood, IY and Rasheed, A and Hindy, G and Faul, JD and Zhao, W and Weir, DR and Turman, C and Huang, H and Graff, M and Choudhury, A and Sengupta, D and Mahajan, A and Brown, MR and Zhang, W and Yu, K and Schmidt, EM and Pandit, A and Gustafsson, S and Yin, X and Luan, J and Zhao, JH and Matsuda, F and Yoon, K and Medina-Gomez, C and Pitsillides, A and Hottenga, JJ and Wood, AR and Ji, Y and Gao, Z and Haworth, S and Mitchell, RE and Chai, JF and Aadahl, M and Bjerregaard, AA and Yao, J and Manichaikul, A and Lee, WJ and Hsiung, CA and Warren, HR and Ramirez, J and Bork-Jensen, J and Karrhus, LL and Goel, A and Hewitt, AW, A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids, American Journal of Human Genetics, 109, (8) pp. 1366-1387. ISSN 1537-6605 (2022) [Refereed Article]

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DOI: doi:10.1016/j.ajhg.2022.06.012


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.

Item Details

Item Type:Refereed Article
Keywords:complex traits; fine-mapping; functional genomics; lipid biology; post-GWAS; regulatory mechanism; variant prioritization.
Research Division:Biological Sciences
Research Group:Genetics
Research Field:Gene mapping
Objective Division:Health
Objective Group:Clinical health
Objective Field:Treatment of human diseases and conditions
UTAS Author:Hewitt, AW (Professor Alex Hewitt)
ID Code:155592
Year Published:2022
Web of Science® Times Cited:1
Deposited By:Menzies Institute for Medical Research
Deposited On:2023-03-01
Last Modified:2023-03-01

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