This study identifies trans eQTLs (expression quantitative trait loci) as potential drivers of known disease associations. Researchers conducted a meta-analysis of expression quantitative trait loci (eQTLs) in peripheral blood samples from 5,311 individuals, with replication in 2,775 individuals. They identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease. For example, rs4917014, previously associated with systemic lupus erythematosus (SLE), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3' UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants. Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits and diseases. However, because most variants are noncoding, it is difficult to identify causal genes. Several eQTL-mapping studies have shown that disease-predisposing variants often affect the gene expression levels of nearby genes (cis eQTLs). A few recent studies have also identified trans eQTLs, showing the downstream consequences of some variants. However, the total number of reported trans eQTLs is low, mainly owing to the multiple-testing burden. To improve statistical power, the researchers performed an eQTL meta-analysis in 5,311 peripheral blood samples from 7 studies and replication analysis in another 2,775 samples. They aimed to ascertain to what extent SNPs affect genes in cis and in trans and to determine whether eQTL mapping in peripheral blood could identify downstream pathways that might be drivers of disease processes. The study found that trans eQTLs showed similar effect sizes across the various cohorts. The researchers identified cis eQTLs for 44% of all tested genes and trans-eQTLs for 1,513 significant trans eQTLs. They used stringent procedures for trans-eQTL detection and various benchmarks to ensure reliability. The study also found that some trans eQTLs could be detected in three cell type-specific data sets. The results suggest that trans-eQTL effects are tissue specific, a notion supported by the inability to replicate a trans eQTL previously identified in adipose tissue for SNP rs4731702, associated with bothThis study identifies trans eQTLs (expression quantitative trait loci) as potential drivers of known disease associations. Researchers conducted a meta-analysis of expression quantitative trait loci (eQTLs) in peripheral blood samples from 5,311 individuals, with replication in 2,775 individuals. They identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease. For example, rs4917014, previously associated with systemic lupus erythematosus (SLE), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3' UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants. Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits and diseases. However, because most variants are noncoding, it is difficult to identify causal genes. Several eQTL-mapping studies have shown that disease-predisposing variants often affect the gene expression levels of nearby genes (cis eQTLs). A few recent studies have also identified trans eQTLs, showing the downstream consequences of some variants. However, the total number of reported trans eQTLs is low, mainly owing to the multiple-testing burden. To improve statistical power, the researchers performed an eQTL meta-analysis in 5,311 peripheral blood samples from 7 studies and replication analysis in another 2,775 samples. They aimed to ascertain to what extent SNPs affect genes in cis and in trans and to determine whether eQTL mapping in peripheral blood could identify downstream pathways that might be drivers of disease processes. The study found that trans eQTLs showed similar effect sizes across the various cohorts. The researchers identified cis eQTLs for 44% of all tested genes and trans-eQTLs for 1,513 significant trans eQTLs. They used stringent procedures for trans-eQTL detection and various benchmarks to ensure reliability. The study also found that some trans eQTLs could be detected in three cell type-specific data sets. The results suggest that trans-eQTL effects are tissue specific, a notion supported by the inability to replicate a trans eQTL previously identified in adipose tissue for SNP rs4731702, associated with both