RESUMO
Coronary artery disease (CAD) remains the leading cause of death worldwide. The role of hypertension, cholesterol, diabetes mellitus, and smoking in driving disease has been well recognized at a population level and has been the target of primary prevention strategies for over 50 years with substantial impact. However, in many cases, these factors alone do not provide enough precision at the individual level to allow physicians and patients to take appropriate preventive measures and many patients continue to suffer acute coronary syndromes in the absence of these risk factors. Recent advances in user-friendly chip designs, high speed throughput, and economic efficiency of genome-wide association studies complemented by advances in statistical analytical approaches have facilitated the rapid development of polygenic risk scores (PRSs). The latest PRSs combine data regarding hundreds of thousands of single-nucleotide polymorphisms to predict chronic diseases including CAD. Novel CAD PRSs are strong predictors of risk and may have application, in a complementary manner with existing risk prediction algorithms. However, there remain substantial controversies, and ultimately, we need to move forward from observational studies to prospectively and rigorously assess the potential impact if widespread implementation is to be aspired to. Consideration needs to be made of ethnicity, sex, as well as age, and risk estimate based on existing non-genomic algorithms. We provide an overview and commentary on the important advances in deriving and validating PRSs, as well as pragmatic considerations that will be required for implementation of the new knowledge into clinical practice.