Polygenic Risk Scores: Towards Clinical Application

Common diseases are largely caused by the combined contributions of genetic and environmental risk factors. On the genetic side, numerous variants contribute to disease susceptibility, resulting in a substantial polygenic component of disease risk. Many such variants have already been identified. Polygenic risk scores (PRS), which aggregate the effects of these variants, enable more precise estimation of an individual's disease risk. We review the current state of bench-to-bedside translation of PRS.

This review is based on publications retrieved by a selective PubMed literature search using predefined search terms relevant to PRS.

Studies across a range of diseases have shown that PRS can markedly influence the assessment of disease risk, enabling the identification of individuals at high risk. The predictive value of PRS can be improved by integrating them into established clinical risk models; this is the area of application in which the implementation of PRS in clinical practice is currently most advanced. For example, studies on coronary heart disease (CHD) and on breast and pancreatic cancer have shown that integrating PRS into clinical risk models changes personalized recommendations for primary and secondary prevention. Depending on the study, this affects 24% (CHD) to 25% (breast cancer) of individuals in the respective clinical risk groups. A major limitation is that most PRS are based on data from European populations, and their predictive value may be lower in individuals of other ancestral backgrounds. Moreover, quality standards must be established to ensure that the potential of PRS can be effectively translated into routine clinical practice.

As genetic data continue to grow, the predictive value of PRS is expected to increase further. PRS are therefore likely to become an integral component of risk prediction in preventive and precision medicine.