Will Genetic Data Significantly Change Cardiovascular Risk Prediction in Daily Practice?

Abstract

Precision medicine has been heralded as an opportunity to improve risk prediction, driven significantly by an increasing availability of genetic data. Genetic testing for rare mutations linked with Mendelian monogenic syndromes is available in specialised clinics. For complex diseases however, aggregation of common and low frequency variants into a “polygenic risk score” (PRS) is necessary due to their small individual effect sizes. PRSs for coronary artery disease (CAD), hypertension and atrial fibrillation have shown some modest success at a population level. However, scepticism remains whether the genetic effects in CV disease are sufficient to have meaningful clinical impact. This review explores recent efforts to utilise genomic data for risk prediction using CAD as an example.