Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
Détails
Télécharger: s13059-022-02837-1.pdf (2183.57 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
Etat: Public
Version: Final published version
Licence: CC BY 4.0
Document(s) secondaire(s)
Télécharger: Tables S1-S22.pdf (17776.14 [Ko])
Etat: Public
Version: Supplementary document
Licence: Non spécifiée
Etat: Public
Version: Supplementary document
Licence: Non spécifiée
Télécharger: Figures 1-10.pdf (2945.51 [Ko])
Etat: Public
Version: Supplementary document
Licence: CC BY 4.0
Etat: Public
Version: Supplementary document
Licence: CC BY 4.0
ID Serval
serval:BIB_3CFF377B1981
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
Périodique
Genome biology
ISSN
1474-760X (Electronic)
ISSN-L
1474-7596
Statut éditorial
Publié
Date de publication
27/12/2022
Peer-reviewed
Oui
Volume
23
Numéro
1
Pages
268
Langue
anglais
Notes
Publication types: Meta-Analysis ; Journal Article ; Research Support, N.I.H., Intramural ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
Publication Status: epublish
Publication Status: epublish
Résumé
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.
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.
Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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.
Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
Mots-clé
Humans, Genome-Wide Association Study, Genetic Predisposition to Disease, Sex Characteristics, Phenotype, Lipids/genetics, Polymorphism, Single Nucleotide, Genetic Pleiotropy, Cholesterol, GWAS, Genetics, Genome-wide association study, Lipids
Pubmed
Web of science
Open Access
Oui
Création de la notice
10/01/2023 15:40
Dernière modification de la notice
08/08/2024 6:26