Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi‑ancestry meta‑analysis
Metadatos
Mostrar el registro completo del ítemEditorial
BMC
Materia
Cholesterol Lipids Genetics Genome-wide association study GWAS
Fecha
2022-12-27Referencia bibliográfica
Kanoni, S... [et al.]. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis. Genome Biol 23, 268 (2022). [https://doi.org/10.1186/s13059-022-02837-1]
Patrocinador
United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Heart Lung & Blood Institute (NHLBI) R01HL127564 R01HL142711; Wellcome Trust 201543/B/16/Z 202802/Z/16/Z; European Commission HEALTH-F2-2013-601456 608765 786833; TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation NNF15CC0018486; American Diabetes Association 1-19-ICTS-068; Academy of Finland 312062 Finnish Foundation for Cardiovascular Research; Sigrid Juselius Foundation; Finnish innovation fund Sitra (EW) Finska Lakaresallskapet; American Heart Association 15POST24470131 17POST33650016; University of Bristol NIHR Biomedical Research Centre BRC-1215-2001; MRC & WT 217065/Z/19/Z; UK Research & Innovation (UKRI); Medical Research Council UK (MRC) MC_UU_00011; CRUK Integrative Cancer Epidemiology Programme C18281/A19169; UK Research & Innovation (UKRI); Medical Research Council UK (MRC) MC_UU_00011/1; UK National Institute for Health Research Academic Clinical Fellowship; American Heart Association 18CDA34110116; Miguel Servet contract from the ISCIII Spanish Health Institute CP17/00142; European Social Fund (ESF); Westlake Education Foundation; British Heart Foundation FS/14/66/3129 Z01HG200362 R01HL142302 R01HL105756Resumen
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 metaanalysis
(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.