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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
- Source :
- American Journal of Human Genetics, 109(8), 1366-1387. CELL PRESS, Million Veterans Program, Ramdas, S, Judd, J, Graham, S E, Kanoni, S, Wang, Y, Surakka, I, Wenz, B, Clarke, S L, Chesi, A, Wells, A, Bhatti, K F, Vedantam, S, Winkler, T W, Locke, A E, Marouli, E, Zajac, G J M, Wu, K-H H, Ntalla, I, Hui, Q, Klarin, D, Hilliard, A T, Wang, Z, Xue, C, Thorleifsson, G, Helgadottir, A, Gudbjartsson, D F, Holm, H, Olafsson, I, Hwang, M Y, Han, S, Akiyama, M, Sakaue, S, Terao, C, Kanai, M, Zhou, W, Brumpton, B M, Rasheed, H, Havulinna, A S, Veturi, Y, Pacheco, J A, Weir, D R, Brown, M R, Smyth, L J, Cañadas-Garre, M, Li, X, Nelson, C P, McKnight, A J, Kee, F, Wilson, P & Brown, C D 2022, ' A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids ', The American Journal of Human Genetics, vol. 109, no. 8, pp. 1366-1387 . https://doi.org/10.1016/j.ajhg.2022.06.012, Ramdas, S, Judd, J, Graham, S E, Hottenga, J J, Penninx, B, Boomsma, D I, de Geus, E J C, Million Veterans Program & Global Lipids Genetics Consortium 2022, ' A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids ', American Journal of Human Genetics, vol. 109, no. 8, pp. 1366-1387 . https://doi.org/10.1016/j.ajhg.2022.06.012, Million Veterans Program & Global Lipids Genetics Consortium 2022, ' A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids ', American journal of human genetics, vol. 109, no. 8, pp. 1366-1387 . https://doi.org/10.1016/j.ajhg.2022.06.012, Am J Hum Genet, American journal of human genetics, vol 109, iss 8, AMERICAN JOURNAL OF HUMAN GENETICS, r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau, instname, American Journal of Human Genetics, American journal of human genetics, 109(8), 1366-1387. Cell Press, American journal of human genetics, vol. 109, no. 8, pp. 1366-1387, Ramdas, S, Judd, J, Graham, S E, Kanoni, S, Wang, Y, Surakka, I, Wenz, B, Clarke, S L, Brumpton, B M, Rasheed, H, Haworth, S J, Mitchell, R E, Zhu, X & Brown, C D & et, A 2022, ' A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids ', American Journal of Human Genetics, vol. 109, no. 8, pp. 1366-1387 . https://doi.org/10.1016/j.ajhg.2022.06.012, 2022, ' A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids ', American Journal of Human Genetics, vol. 109, no. 8, pp. 1366-1387 . https://doi.org/10.1016/j.ajhg.2022.06.012, American Journal of Human Genetics, 109, 8, pp. 1366-1387, American Journal of Human Genetics, 109, 1366-1387, American Journal of Human Genetics, 109(8), 1366-1387. Cell Press
- Publication Year :
- 2022
-
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. 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.
- Subjects :
- regulatory mechanism
Vascular damage Radboud Institute for Health Sciences [Radboudumc 16]
post-GWAS
Medizin
complex traits
fine-mapping
functional genomics
lipid biology
variant prioritization
Medical and Health Sciences
Polymorphism, Single Nucleotide
Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12]
Article
INTEGRATIVE ANALYSIS
WIDE ASSOCIATION
3D GENOME
VARIANTS
CHOLESTEROL
ANNOTATION
OBESITY
COMMON
LOCI
EXPRESSION
functional genomic
Genetics
2.1 Biological and endogenous factors
Humans
Genetics(clinical)
Polymorphism
Aetiology
Genetics (clinical)
Genetics & Heredity
Chromatin/genetics
Genome-Wide Association Study
Genomics
Lipids/genetics
Polymorphism, Single Nucleotide/genetics
Human Genome
Million Veterans Program
Global Lipids Genetics Consortium
Single Nucleotide
Biological Sciences
Lipids
Chromatin
complex trait
Urological cancers Radboud Institute for Health Sciences [Radboudumc 15]
3111 Biomedicine
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 00029297
- Volume :
- 109
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- American Journal of Human Genetics
- Accession number :
- edsair.doi.dedup.....ce85872de65cda3bd9b22e7d06fabeed