Genetic Determinants Of Treatment Benefit Of The Angiotensin-Converting Enzyme-Inhibitor Perindopril In Patients With Stable Coronary Artery Disease

The efficacy of angiotensin-converting enzyme (ACE)-inhibitors in stable coronary artery disease (CAD) may be increased by targeting the therapy to those patients most likely to benefit. However, these patients cannot be identified by clinical characteristics. We developed a genetic profile to predict the treatment benefit of ACE-inhibitors exist and to optimize therapy with ACE-inhibitors.In 8907 stable CAD patients participating in the randomized placebo-controlled EUROPA-trial, we analysed 12 candidate genes within the pharmacodynamic pathway of ACE-inhibitors, using 52 haplotype-tagging-single nucleotide polymorphisms (SNPs). The primary outcome was the reduction in cardiovascular mortality, non-fatal myocardial infarction, and resuscitated cardiac arrest during 4.2 years of follow-up. Multivariate Cox regression was performed with multiple testing corrections using permutation analysis. Three polymorphisms, located in the angiotensin-II type I receptor and bradykinin type I receptor genes, were significantly associated with the treatment benefit of perindopril after multivariate adjustment for confounders and correction for multiple testing. A pharmacogenetic score, combining these three SNPs, demonstrated a stepwise reduction of risk in the placebo group and a stepwise decrease in treatment benefit of perindopril with an increasing scores (interaction P < 0.0001). A pronounced treatment benefit was observed in a subgroup of 73.5% of the patients [hazard ratio (HR) 0.67; 95% confidence interval (CI) 0.56-0.79], whereas no benefit was apparent in the remaining 26.5% (HR 1.26; 95% CI 0.97-1.67) with a trend towards a harmful effect. In 1051 patients with cerebrovascular disease from the PROGRESS-trial, treated with perindopril or placebo, an interaction effect of similar direction and magnitude, although not statistically significant, was observed.The current study is the first to identify genetic determinants of treatment benefit of ACE-inhibitor therapy. We developed a genetic profile which predicts the treatment benefit of ACE-inhibitors and which could be used to optimize therapy.