Clinical applications of polygenic risk score for coronary artery disease through the life course

Abstract

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, highlighting the limitations of current primary and secondary prevention frameworks. In this review, we detail how the polygenic risk score for CAD can improve our current preventive and treatment frameworks across three clinical applications that span the life course: (i) identification and treatment of people at increased risk early in the life course prior to the onset of clinical risk factors, (ii) improving the precision around risk estimation in middle age, and (ii) guiding treatment decisions and enabling more efficient clinical trials even after the onset of CAD. We end by summarizing the efforts needed as we head towards more widespread use of polygenic risk score for CAD in clinical practice.

Keywords: Cardiovascular prevention; Coronary artery disease; Genetics; Genomic medicine; Genomic risk prediction; Polygenic score.

Figure 1:

Simplified framework of how a polygenic risk score is developed and reported In a simplified three-step framework of how polygenic risk score (PRS) for CAD is developed, first risk-increasing (red) and risk-decreasing (green) variants are compared in people with and without CAD to estimate effect size. This is known as a genome-wide association study (GWAS). Second, in any individual the summed effect of all risk-increasing and risk-decreasing variants is computed. At a population level, this results in a single number that quantifies risk and is normally distributed in the population. Third, the number is expressed as a percentile, with higher percentiles associating with a relative risk increase compared to the population average. This illustration was adopted from www.polygenicscores.org which includes a more detailed explanation.

Fig. 2:

Clinical application of polygenic risk score for CAD through the life course Polygenic risk score (PRS) for CAD could identify people at high risk in young age such as those in the 18 to 40 years group prior to onset of clinical risk factors and serve as the single risk factor to decide on initiation of targeted interventions including LDL cholesterol lowering. In early middle age (40-55 years) after the onset of clinical risk factors such as diabetes, hypercholesterolemia and hypertension, CAD PRS has been shown to improve precision in risk estimation when added to clinical risk calculators. Finally, even after the onset of CAD such as in people older than 55 years, CAD PRS predicts recurrent events and could be used to personalize treatment strategies and enrich clinical trials.