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.
Highlights
Genome-wide association studies (GWAS) have been very successful in identifying genes or loci that are associated with complex diseases or quantitative traits
We identified 102 genes in the sterol transport and metabolism pathways that collectively associate with high-density lipoprotein cholesterol (HDL-C) levels, and replicated these association signals in an independent GWAS
Our current study focused on a quantitative trait, plasma levels of high-density lipoprotein cholesterol (HDL-C), to examine whether pathway-based approaches can be effective in enriching a group of truly associated genes
Summary
Genome-wide association studies (GWAS) have been very successful in identifying genes or loci that are associated with complex diseases or quantitative traits. An alternative approach to detect trait-associated loci in GWAS, which can provide complementary information to single-marker analysis, is a pathway-based approach, which examines whether test statistics for related genes in the same pathway are consistently associated with a disease trait under study (Wang et al, 2010). There have been a few published examples demonstrating the power and effectiveness of pathway-wide association approaches for several diseases. We have previously developed a pathway association approach (Wang et al, 2007), by adopting the Gene Set Enrichment Analysis (Subramanian et al, 2005) strategies, but with appropriate modifications to account for the linkage disequilibrium between SNP markers, the different sizes of genes and www.frontiersin.org
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