Abhiram S Rao1, Joshua W Knowles2. 1. Department of Bioengineering. 2. Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA.
Abstract
PURPOSE OF REVIEW: Large genome-wide association studies (GWAS) have identified variants accounting for a substantial portion of the heritable risk for coronary artery disease (CAD). These studies have catalyzed drug discovery and generated the possibility of improved risk prediction and stratification. Here, we review the current state-of-the art in polygenic risk scores (PRSs) and look to the future, as these scores move towards clinical application. RECENT FINDINGS: Over the last decade, multilocus PRSs for CAD have expanded to include millions of variants and demonstrated strong association with CAD outcomes, even when adjusted for traditional risk factors. Recently, PRSs have shown better prediction of CAD outcomes than any single traditional risk factor alone. Advances in statistical methods used to generate PRSs have improved their predictive ability and transferability between populations with varied ancestries. Initial clinical studies have also demonstrated the potential of genetic information to impact shared decision-making between patients and providers, leading to improved outcomes. SUMMARY: PRSs can improve risk stratification for CAD especially in white/European populations and have the potential to alter routine clinical care. However, unlocking this potential will require additional research in PRSs in nonwhite populations and substantial investment in clinical implementation studies.
PURPOSE OF REVIEW: Large genome-wide association studies (GWAS) have identified variants accounting for a substantial portion of the heritable risk for coronary artery disease (CAD). These studies have catalyzed drug discovery and generated the possibility of improved risk prediction and stratification. Here, we review the current state-of-the art in polygenic risk scores (PRSs) and look to the future, as these scores move towards clinical application. RECENT FINDINGS: Over the last decade, multilocus PRSs for CAD have expanded to include millions of variants and demonstrated strong association with CAD outcomes, even when adjusted for traditional risk factors. Recently, PRSs have shown better prediction of CAD outcomes than any single traditional risk factor alone. Advances in statistical methods used to generate PRSs have improved their predictive ability and transferability between populations with varied ancestries. Initial clinical studies have also demonstrated the potential of genetic information to impact shared decision-making between patients and providers, leading to improved outcomes. SUMMARY: PRSs can improve risk stratification for CAD especially in white/European populations and have the potential to alter routine clinical care. However, unlocking this potential will require additional research in PRSs in nonwhite populations and substantial investment in clinical implementation studies.