Polygenic Risk Score and Precision Medicine in Diabetes

Abstract

Precision medicine involves tailoring medical treatment to the individual characteristics, needs, and preferences of each patient. In the realm of diabetes, genetic, environmental, and lifestyle factors must all be considered when developing personalized management strategies. Polygenic risk refers to the cumulative risk of developing a disease based on the presence of multiple genetic variants across the genome. Understanding the polygenic nature of diabetes assists in identifying various genetic factors that contribute to its onset, progression, and the development of complications. Recent studies indicate that polygenic risk scores are instrumental in distinguishing between type 1 diabetes, monogenic diabetes, and type 2 diabetes. Moreover, these scores can predict incident type 2 diabetes in women with a history of gestational diabetes and can be used to forecast diabetic complications. When polygenic risk scores are combined with other risk factors such as age, body mass index, and family history, risk stratification is enhanced, pinpointing individuals who may benefit most from early intervention strategies. Challenges related to practical use of polygenic scores include ethnicity specificity, data privacy, and generating evidence in the clinical setting. We aim to explore opportunities as well as challenges related to utilizing polygenic risk in precision medicine.