An introduction to polygenic scores - methodological basics and recent advances

Polygenic scores (PGS) allow the estimation of genetic predisposition to complex diseases and traits. Based on results from genome-wide association studies (GWAS) and data from large deeply phenotyped population biobanks, numerous PGS have been developed in recent years. These scores summarize the combined effects of many genetic variants and can support risk stratification for multifactorial diseases based on an individual's genetic susceptibility. In this review, we introduce the basic principles and methods of PGS and explain how they are generated and applied. We outline their potential translational role, particularly in the context of precision medicine and personalized risk stratification for preventive measures, in combination with established clinical risk factors. At the same time, we discuss important limitations, including limited generalizability across populations and the issue of missing heritability. Finally, we highlight current methodological developments and future perspectives for the integration of PGS into clinical practice.