Polygenic Risk Scores and Lifestyle in Japanese Type 2 Diabetes Risk

Key Takeaways

• Higher polygenic risk scores were associated with increased risk of incident type 2 diabetes in Japanese cohorts, with consistent findings across study populations.
• Favorable lifestyle factors—including regular exercise and absence of hypertension or dyslipidemia—were associated with lower diabetes risk, particularly among those at high genetic risk.
• The authors reported that adding polygenic risk scores to conventional models improved diabetes risk prediction, supporting a potential role in personalized risk assessment.

The study is presented in terms of genetic susceptibility estimates, lifestyle-related factors, and type 2 diabetes risk, with explicit methodological detail. Participants were categorized into low, intermediate, and high genetic risk groups using PRS derived from genome-wide association study data in East Asian populations.

Authors frame these elements as complementary contributors to diabetes risk. Incident type 2 diabetes served as the outcome in the longitudinal cohort, with associations assessed using multivariate logistic regression and Cox proportional hazards models. Diabetes was defined by hemoglobin A1c, fasting glucose, self-reported diagnosis, or medication use.

The analysis included two cohorts: a cross-sectional Shika resident cohort (n = 895) and a longitudinal Toshiba worker cohort (n = 7,019). Higher PRS were associated with increased diabetes risk in both cohorts, including an odds ratio of 4.51 (95% CI 2.53–8.04) in the resident cohort and a hazard ratio of 1.82 (95% CI 1.48–2.24) in the worker cohort for high versus low genetic risk.

Lifestyle factors were evaluated alongside genetic risk. Regular exercise and absence of hypertension or dyslipidemia were associated with lower diabetes risk, with effects particularly noted among participants with higher PRS. These findings were presented as part of a combined genetic and lifestyle risk framework.

The authors also reported that adding PRS to conventional risk models improved discrimination of diabetes risk. The interpretation emphasizes the potential for integrating genetic and lifestyle information in risk stratification.