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Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism.
- Source :
-
Cell metabolism [Cell Metab] 2020 Apr 07; Vol. 31 (4), pp. 741-754.e5. Date of Electronic Publication: 2020 Mar 19. - Publication Year :
- 2020
-
Abstract
- Identifying the causal gene(s) that connects genetic variation to a phenotype is a challenging problem in genome-wide association studies (GWASs). Here, we develop a systematic approach that integrates mouse liver co-expression networks with human lipid GWAS data to identify regulators of cholesterol and lipid metabolism. Through our approach, we identified 48 genes showing replication in mice and associated with plasma lipid traits in humans and six genes on the X chromosome. Among these 54 genes, 25 have no previously identified role in lipid metabolism. Based on functional studies and integration with additional human lipid GWAS datasets, we pinpoint Sestrin1 as a causal gene associated with plasma cholesterol levels in humans. Our validation studies demonstrate that Sestrin1 influences plasma cholesterol in multiple mouse models and regulates cholesterol biosynthesis. Our results highlight the power of combining mouse and human datasets for prioritization of human lipid GWAS loci and discovery of lipid genes.<br />Competing Interests: Declaration of Interests D.W.L. has received funding from, and is a scientific advisory board member of, Aeonian Pharmaceuticals, which seeks to develop novel, selective mTOR inhibitors for the treatment of various diseases.<br /> (Copyright © 2020 Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1932-7420
- Volume :
- 31
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Cell metabolism
- Publication Type :
- Academic Journal
- Accession number :
- 32197071
- Full Text :
- https://doi.org/10.1016/j.cmet.2020.02.015