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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, Charterhouse Sq, London EC1M 6BQ, England.ORCID iD: 0000-0002-1691-9615
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.ORCID iD: 0000-0001-5894-0351
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.ORCID iD: 0000-0003-2335-8542
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Stanford Univ, Sch Med, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA;Stanford Univ, Stanford Cardiovasc Inst, Stanford, CA 94305 USA;Stanford Univ, Stanford Diabet Res Ctr, Stanford, CA 94305 USA.ORCID iD: 0000-0003-2256-6972
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Number of Authors: 5392022 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 23, article id 268Article in journal (Refereed) Published
Abstract [en]

Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Place, publisher, year, edition, pages
BioMed Central (BMC), 2022. Vol. 23, article id 268
Keywords [en]
Cholesterol, Lipids, Genetics, Genome-wide association study, GWAS
National Category
Medical Genetics and Genomics
Identifiers
URN: urn:nbn:se:uu:diva-498949DOI: 10.1186/s13059-022-02837-1ISI: 000927879600003PubMedID: 36575460OAI: oai:DiVA.org:uu-498949DiVA, id: diva2:1745114
Funder
Wellcome trust, 201543/B/16/ZWellcome trust, 202802/Z/16/ZEU, FP7, Seventh Framework Programme, HEALTH-F2-2013-601456EU, FP7, Seventh Framework Programme, 608765EU, FP7, Seventh Framework Programme, 786833Novo Nordisk, NNF15CC0018486Academy of Finland, 312062
Note

For complete list of authors see http://dx.doi.org/10.1186/s13059-022-02837-1

Available from: 2023-03-22 Created: 2023-03-22 Last updated: 2025-02-10Bibliographically approved

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Gustafsson, StefanLind, LarsIngelsson, Erik

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