Background: Genomic variants identified by genome-wide association studies (GWAS) explain <20% of heritability of coronary artery disease (CAD), thus many risk variants remain missing for CAD. Identification of new variants may unravel new biological pathways and genetic mechanisms for CAD. To identify new variants associated with CAD, we developed a candidate pathway-based GWAS by integrating expression quantitative loci analysis and mining of GWAS data with variants in a candidate pathway.
Methods and results: Mining of GWAS data was performed to analyze variants in 32 complement system genes for positive association with CAD. Functional variants in genes showing positive association were then identified by searching existing expression quantitative loci databases and validated by real-time reverse transcription polymerase chain reaction. A follow-up case-control design was then used to determine whether the functional variants are associated with CAD in 2 independent GeneID Chinese populations. Candidate pathway-based GWAS identified positive association between variants in C3AR1 and C6 and CAD. Two functional variants, rs7842 in C3AR1 and rs4400166 in C6, were found to be associated with expression levels of C3AR1 and C6, respectively. Significant association was identified between rs7842 and CAD (P=3.99×10(-6); odds ratio, 1.47) and between rs4400166 and CAD (P=9.30×10(-3); odds ratio, 1.24) in the validation cohort. The significant findings were confirmed in the replication cohort (P=1.53×10(-5); odds ratio, 1.37 for rs7842; P=8.41×10(-3); odds ratio, 1.21 for rs4400166).
Conclusions: Integration of GWAS with biological pathways and expression quantitative loci is effective in identifying new risk variants for CAD. Functional variants increasing C3AR1 and C6 expression were shown to confer significant risk of CAD for the first time.
Keywords: complement system; coronary artery disease; genome-wide association study; single nucleotide polymorphisms; variants.
© 2014 American Heart Association, Inc.