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Background— Despite recent discoveries of new genetic risk factors, the majority of risk for coronary artery disease (CAD) remains elusive. As the most proximal sensor of DNA variation, RNA abundance can help identify subpopulations of genetic variants active in and across tissues mediating CAD risk through gene expression. Methods and Results— By generating new genomic data on DNA and RNA samples from the Stockholm Atherosclerosis Gene Expression (STAGE) study, 8156 cis -acting expression quantitative trait loci (eQTLs) for 6450 genes across 7 CAD-relevant tissues were detected. The inherited risk enrichments of tissue-defined sets of these eQTLs were assessed using 2 independent genome-wide association data sets. eQTLs acting across increasing numbers of tissues were found increasingly enriched for CAD risk and resided at regulatory hot spots. The risk enrichment of 42 eQTLs acting across 5 to 6 tissues was particularly high (≤7.3-fold) and confirmed in the combined genome-wide association data from Coronary Artery Disease Genome Wide Replication And Meta-Analysis Consortium. Sixteen of the 42 eQTLs associated with 19 master regulatory genes and 29 downstream gene sets (n>30) were further risk enriched comparable to that of the 153 genome-wide association risk single-nucleotide polymorphisms established for CAD (8.4-fold versus 10-fold). Three gene sets, governed by the master regulators FLYWCH1 , PSORSIC3 , and G3BP1 , segregated the STAGE patients according to extent of CAD, and small interfering RNA targeting of these master regulators affected cholesterol-ester accumulation in foam cells of the THP1 monocytic cell line. Conclusions— eQTLs acting across multiple tissues are significant carriers of inherited risk for CAD. FLYWCH1 , PSORSIC3 , and G3BP1 are novel master regulatory genes in CAD that may be suitable targets.

Background— As genome-wide association efforts, such as CARDIoGRAM and METASTROKE, are ongoing to reveal susceptibility loci for their underlying disease—atherosclerotic disease—identification of candidate genes explaining the associations of these loci has proven the main challenge. Many disease susceptibility loci colocalize with DNA regulatory elements, which influence gene expression through chromatin interactions. Therefore, the target genes of these regulatory elements can be considered candidate genes. Applying these biological principles, we used an alternative approach to annotate susceptibility loci and identify candidate genes for human atherosclerotic disease based on circular chromosome conformation capture followed by sequencing. Methods and Results— In human monocytes and coronary endothelial cells, we generated 63 chromatin interaction data sets for 37 active DNA regulatory elements that colocalize with known susceptibility loci for coronary artery disease (CARDIoGRAMplusC4D) and large artery stroke (METASTROKE). By circular chromosome conformation capture followed by sequencing, we identified a physical 3-dimensional interaction with 326 candidate genes expressed in at least 1 of these cell types, of which 294 have not been reported before. We highlight 16 genes based on expression quantitative trait loci. Conclusions— Our findings provide additional candidate-gene annotation for 37 disease susceptibility loci for human atherosclerotic disease that are of potential interest to better understand the complex pathophysiology of cardiovascular diseases.

BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. METHODS: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. RESULTS: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10(-4) with a range of other diseases/traits. CONCLUSIONS: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Background Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. Objectives This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. Methods In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. Results We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p< 1× 10−4 with a range of other diseases/traits. Conclusions We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CADrisk.