Risk prediction models, including a combination of clinical, biochemistry, lifestyle, and historical risk factors, are currently used to predict 10-year risk of cardiovascular disease and diabetes [36–39]. These models combining risk factors achieve a good prediction (AUCs of 80–85%) and are included in clinical guidelines for prevention and public health [40]. Polygenic risk scores have much lower AUCs, as expected from a single risk factor, and should not be considered as an alternative to these clinical risk models but as a possible addition. With the established polygenic architecture of complex disorders, the improvement of genetic and statistical methodology, and the increase of global genotyped samples, it is reasonable to anticipate that genetic prediction will improve. In the meantime, it may be timely to consider the use of PRS in specific cohorts where there is a higher prior probability of disease.
