RNAi–Based Functional Profiling of Loci from Blood Lipid Genome-Wide Association Studies Identifies Genes with Cholesterol-Regulatory Function

摘要

Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL–receptor levels and/or that overexpression as GFP–tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci. Author Summary Complex traits and diseases are assumed to result from interactions between multiple genes in relevant biological processes. Recent genome-wide association studies have uncovered many novel genomic loci where genes with functional significance are expected. However, functional validation of such genes has thus far remained confined to single gene approaches. Here, we use RNA interference and high-content screening microscopy to profile 133 genes at 56 loci associated with blood lipid traits, cardiovascular disease, and/or myocardial infarction for a function in regulating cellular free cholesterol levels and the efficiency of low-density lipoprotein uptake. Our results suggest that a high number of trait-associated genes have conserved cholesterol-regulatory functions in cells, with several GWAS loci harboring more than one gene of likely functional significance. For a number of genes without previously known lipid-regulatory functions, consequences upon siRNA knockdown positively correlated with cellular levels of LDL receptor, a major determinant of blood LDL levels. Moreover, GFP–tagged fusion proteins of several candidates shifted cellular cholesterol levels to inverse directions than knockdown, and subcellular localization of some candidates was sterol-dependent. Our study generates a valuable resource for prioritization of lipid-trait/CAD/MI-associated genes for future in-depth mechanistic analyses and introduces cell-based RNAi as a scalable and unbiased tool for functional follow-up of GWAS loci.