Abstract
BackgroundIdentification of single nucleotide polymorphisms (SNPs) associated with gene expression levels, known as expression quantitative trait loci (eQTLs), may improve understanding of the functional role of phenotype-associated SNPs in genome-wide association studies (GWAS). The small sample sizes of some previous eQTL studies have limited their statistical power. We conducted an eQTL investigation of microarray-based gene and exon expression levels in whole blood in a cohort of 5257 individuals, exceeding the single cohort size of previous studies by more than a factor of 2.ResultsWe detected over 19,000 independent lead cis-eQTLs and over 6000 independent lead trans-eQTLs, targeting over 10,000 gene targets (eGenes), with a false discovery rate (FDR) < 5%. Of previously published significant GWAS SNPs, 48% are identified to be significant eQTLs in our study. Some trans-eQTLs point toward novel mechanistic explanations for the association of the SNP with the GWAS-related phenotype. We also identify 59 distinct blocks or clusters of trans-eQTLs, each targeting the expression of sets of six to 229 distinct trans-eGenes. Ten of these sets of target genes are significantly enriched for microRNA targets (FDR < 5%). Many of these clusters are associated in GWAS with multiple phenotypes.ConclusionsThese findings provide insights into the molecular regulatory patterns involved in human physiology and pathophysiology. We illustrate the value of our eQTL database in the context of a recent GWAS meta-analysis of coronary artery disease and provide a list of targeted eGenes for 21 of 58 GWAS loci.
Highlights
Identification of single nucleotide polymorphisms (SNPs) associated with gene expression levels, known as expression quantitative trait loci, may improve understanding of the functional role of phenotype-associated SNPs in genome-wide association studies (GWAS)
Out of 39 million imputed SNPs, we found 8.5 million with a minor allele frequency (MAF) ≥ 0.01 and imputation quality R2 ≥ 0.3 (See “Methods” for further details)
We identified 2.2 million cis-eQTLs and 160 thousand trans-eQTLs at a nominal false discovery rate (FDR) < 0.05 (Table 2)
Summary
Identification of single nucleotide polymorphisms (SNPs) associated with gene expression levels, known as expression quantitative trait loci (eQTLs), may improve understanding of the functional role of phenotype-associated SNPs in genome-wide association studies (GWAS). We conducted an eQTL investigation of microarray-based gene and exon expression levels in whole blood in a cohort of 5257 individuals, exceeding the single cohort size of previous studies by more than a factor of 2. We report results of a microarray-based genome-wide eQTL study, considering both cis and trans elements, in whole blood samples from over 5000 participants in the Framingham Heart Study (FHS) [10, 11], a multi-generational community-based prospective study. Our study utilizes the largest, single-site study to date, and reports both gene-level and exon-level cis-eQTLs and trans-eQTLs genome wide
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