Polygenic risk scores: how much do they add?

Purpose of review Current methods to assess genetic risk of familial hypercholesterolemia and coronary artery disease (CAD) focus on testing monogenic mutations in well known genes. Here we review recent developments in polygenic risk scores (PRSs) for LDL cholesterol and for CAD, and how they may add to current risk prediction algorithms. Recent findings PRSs can identify 10-20 times as many individuals at high polygenic risk compared with monogenic mutations, and PRSs can modulate the effect of a monogenic variant on risk. Current risk factor prediction tools for prevention of CAD incompletely capture polygenic susceptibility, and PRSs may identify subgroups of patients who are likely to benefit more from lipid-lowering therapy. Finally, PRSs can be quantified already at birth, long before other risk factors used to predict CAD, and before clinical manifestations of disease. PRSs for CAD may soon be incorporated into clinical practice. Therefore, there is an urgent need to establish both analytical and clinical reporting standards for PRSs, and for validating scores in different ethnicities. Thresholds for intervention need to be established for PRSs and integrated into established risk scores. Training programs are needed for clinical staff to learn to communicate polygenic risk in a comprehensive way to the patient.