Pathway-Wide Association Study Implicates Multiple Sterol Transport and Metabolism Genes in HDL Cholesterol Regulation.

Details

Serval ID
serval:BIB_168169954F39
Type
Article: article from journal or magazin.
Collection
Publications
Title
Pathway-Wide Association Study Implicates Multiple Sterol Transport and Metabolism Genes in HDL Cholesterol Regulation.
Journal
Frontiers in Genetics
Author(s)
Wang K., Edmondson A.C., Li M., Gao F., Qasim A.N., Devaney J.M., Burnett M.S., Waterworth D.M., Mooser V., Grant S.F., Epstein S.E., Reilly M.P., Hakonarson H., Rader D.J.
ISSN
1664-8021 (Electronic)
ISSN-L
1664-8021
Publication state
Published
Issued date
2011
Volume
2
Pages
41
Language
english
Notes
Publication types: Journal ArticlePublication Status: ppublish
Abstract
Pathway-based association methods have been proposed to be an effective approach in identifying disease genes, when single-marker association tests do not have sufficient power. The analysis of quantitative traits may be benefited from these approaches, by sampling from two extreme tails of the distribution. Here we tested a pathway association approach on a small genome-wide association study (GWAS) on 653 subjects with extremely high high-density lipoprotein cholesterol (HDL-C) levels and 784 subjects with low HDL-C levels. We identified 102 genes in the sterol transport and metabolism pathways that collectively associate with HDL-C levels, and replicated these association signals in an independent GWAS. Interestingly, the pathways include 18 genes implicated in previous GWAS on lipid traits, suggesting that genuine HDL-C genes are highly enriched in these pathways. Additionally, multiple biologically relevant loci in the pathways were not detected by previous GWAS, including genes implicated in previous candidate gene association studies (such as LEPR, APOA2, HDLBP, SOAT2), genes that cause Mendelian forms of lipid disorders (such as DHCR24), and genes expressing dyslipidemia phenotypes in knockout mice (such as SOAT1, PON1). Our study suggests that sampling from two extreme tails of a quantitative trait and examining genetic pathways may yield biological insights from smaller samples than are generally required using single-marker analysis in large-scale GWAS. Our results also implicate that functionally related genes work together to regulate complex quantitative traits, and that future large-scale studies may benefit from pathway-association approaches to identify novel pathways regulating HDL-C levels.
Keywords
analysis , Genes , Genome-Wide Association Study , metabolism , Mice , Phenotype
Pubmed
Open Access
Yes
Create date
22/03/2012 9:44
Last modification date
20/08/2019 12:46
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