The advantages of prescribing angiotensin-converting enzyme (ACE) inhibitors for stable coronary artery disease (CAD) may be increased by targeting the therapy to the patients most likely to benefit. Clinical characteristics alone do not allow a reliable identification of these patients, so a research programme was carried out at Erasmus University Medical Centre in Rotterdam to develop a genetic profiling model that predicts the treatment benefits of ACE inhibitors and optimises the recommended therapy.
Research lead, Doctor Jasper Brugts, explained the methodology used, "Around 9,000 stable CAD patients were selected to take part in a randomised, placebo-controlled trial known as EUROPA. We analysed 12 candidate genes that were determined as being within the pharmacodynamic pathway of ACE-inhibitors, using 52 haplotype-tagging single nucleotide polymorphisms (SNPs). The primary outcome was a reduction in cardiovascular mortality, non-fatal myocardial infarction and resuscitated cardiac arrest over a four-year follow-up period."
Three SNPs, located in the angiotensin-II type I receptor genes 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 score.
A pronounced treatment benefit was observed in a subgroup of 73.5 percent of the patients, while no benefit was apparent in the remaining 26.5 percent. An interaction effect of similar direction and magnitude, although not statistically significant, was observed in a preliminary confirmatory analysis of over 1,000 patients with cerebrovascular disease, who were treated with perindopril or placebo from the PROGRESS-trial.
This research study is the first to identify genetic determinants of the treatment benefit of ACE-inhibitor therapy. A group of responders (73.5 percent) and non-responders (26.5 percent) to treatment was identified by genetic markers. If confirmed in subsequent studies, our findings open the route to individualise therapy by pharmacogenetic profiling. Such individualised therapy could revolutionise medical drug therapy by prescribing drugs only to those patients most likely to benefit from the therapy. This would not only increase efficacy, but also decrease unnecessary treatment of patients and avoid unwanted side-effects, thereby decreasing the overall costs.
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