Significance: Despite significant progress in secondary prevention following myocardial infarction, coronary artery disease (CAD) remains the leading cause of death worldwide. While optimizing traditional risk factors is critical, as much as 30-60% of the variation in risk may be explained by genetics. A growing number of single-nucleotide polymorphisms (SNPs) are associated with increased risk of CAD and provide an opportunity to improve individual risk stratification and personalize therapy. The degree to which these SNPs may identify risk after acute coronary syndrome and predict benefit or side-effects of ezetimibe therapy is not clear. Objective: To assess whether a series of genetic risk scores using established, relevant variants can predict the response to ezetimibe in terms of LDL-C lowering, CV risk reduction, and risk of diabetes. Approach: This study will analyze the genetic data of 6,455 patients from IMPROVE-IT, a multicenter trial of patients with acute coronary syndrome who were randomized to either simvastatin or simvastatin plus ezetimibe. Patients were followed for a median of 6 years for LDL-C levels, the incidence of cardiovascular outcomes, and the incidence of adverse events including diabetes. Genetic risk scores will be constructed based on variants that have an established association with the phenotypes in question. Each individual subject will receive a score for each phenotype equal to the sum of the number of risk alleles for each SNP, weighted by the effect sizes for the phenotype. The genetic scores will then be assessed on how well they predict response to ezetimibe, secondary events, and development of diabetes. Implications: If a genetic risk score can better define a patient?s risk of recurrent events or predict their response to specific therapies, we can personalize our approach to cardiovascular management.
Coronary artery disease is one of the leading causes of death in the United States and strategies to identify high risk patients earlier in their disease course may lead to better management. Advances in genomic technology have allowed for more affordable large- scale genotyping which has identified an increasing number of genetic variants that are associated with coronary artery disease. We intend to analyze genetic data from a large clinical trial population with recent acute coronary syndrome to identify variants that are associated with risk of recurrent events, response to ezetimibe therapy, and development of diabetes.
