Proficiency of data interpretation: identification of signaling SNPs/specific loci for coronary artery disease

Abstract Coronary artery disease (CAD) is a complex disorder involving both genetic and non-genetic factors. Genome-wide association studies (GWAS) have identified hundreds of single nucleotides polymorphisms (SNPs) tagging over > 40 CAD risk loci. We hypothesized that some non-coding variants might directly regulate the gene expression rather than tagging a nearby locus. We used RegulomeDB to examine regulatory functions of 58 SNPs identified in two GWAS and those SNPs in linkage disequilibrium (LD) (r2 ≥ 0.80) with the GWAS SNPs. Of the tested 1200 SNPs, 858 returned scores of 1–6 by RegulomeDB. Of these 858 SNPs, 97 were predicted to have regulatory functions with RegulomeDB score of < 3. Notably, only 8 of the 97 predicted regulatory variants were genome-wide significant SNPs (LIPA/rs2246833, RegulomeDB score = 1b; ZC3HC1/rs11556924, CYP17A1-CNNM2-NT5C2/rs12413409, APOE-APOC1/rs2075650 and UBE2Z/rs46522, each with a RegulomeDB score = 1f; ZNF259-APOA5-APOA1/rs964184, SMG6/rs2281727 and COL4A1-COL4A2/rs4773144, each with a RegulomeDB score = 2b). The remainder 89 functional SNPs were in linkage disequilibrium with GWAS SNPs. This study supports the hypothesis that some of the non-coding variants are true signals via regulation of gene expression at transcription level. Our study indicates that RegulomeDB is a useful database to examine the putative functions of large number of genetic variants and it may help to identify a true association among multiple tagged SNPs in a complex disease, such as CAD. Database URLs http://www.regulomedb.org/; https://www.broadinstitute.org/mpg/snap/

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