Polygenetic regression model of renin-angiotensin system genes and the risk of coronary artery disease in a large angiographic population

Background: Polygenetic effect has rarely been addressed in the genetic studies of coronary artery disease (CAD). We used the largest and ethnically homogeneous angiographic cohort to analyze multilocus data in renin-angiotensin system genes, and provide an explicit demonstration of gene-gene interactions. Methods: A total of 1254 consecutive patients who underwent cardiac catheterization (735 with coronary artery disease and 519 without) were recruited. Angiotensin converting enzyme(ACE) gene I/D polymorphism; T174M, M235T, G-6A, A-20C, G-152A, and G-217A polymorphisms of the angiotensinogen (AGT) gene; and A1166C polymorphism of the angiotensin II type I receptor (AT1R) gene were genotyped. We used a regression approach based on a generalized linear model to evaluate haplotype effects, adjust non-genetic confounding effects and detect gene-gene interaction between ACE and AT1R genes. Results: We found significant differences in global AGT gene haplotype profile and individual haplotypes between cases and controls. Significant two-way and three-way gene-gene interactions between ACE I/D, AT1R A1166C polymorphisms and AGT gene haplotypes were detected. However, subjects carrying both D allele and GGCATC haplotype had an increased risk of CAD (odds ratio = 1.63 [1.16-2.29]; P= 0.004). We also used haplotype counting to directly estimate the odds ratio of each specific AGT gene haplotype, and found that the effects of haplotypes were markedly different in subgroups with different ACE or AT1R gene genotype. Conclusions: The regression-based haplotype analyses permits simultaneous dectection of multi-locus and multi-gene effects in determining the risk of CAD. We provide the paradigm for genetic studies of complex-trait diseases using candidate genes based on biological pathways.