Association of genetic risk and physical activity with incident type 2 diabetes

Objective

To assess whether daily step counts and genetic risk interact to influence the risk of developing type 2 diabetes.

Research Design and Methods

We analyzed data from 9,501 participants in the All of Us Research Program with both genetic and wearable device–derived physical activity data and without diabetes at baseline. Physical activity was quantified using daily step counts. Genetic risk was assessed using a global polygenic score. Incident type 2 diabetes was identified using electronic health record–linked diagnostic codes. Multivariable Cox proportional hazards models estimated hazard ratios (HRs) for type 2 diabetes across genetic risk and physical activity levels. We tested for additive interaction using the relative excess risk due to interaction (RERI). In secondary analyses we used physical-activity intensity measures using wearable-derived and self-reported intensity levels.

Results

Type 2 diabetes incidence rates ranged from 4.1 per 1,000 person-years (95% CI, 2.5–5.7) in individuals with high physical activity and low genetic risk to 18.4 (95% CI, 15.2–21.6) in those with low physical activity and high genetic risk (HR, 6.2 (95% CI: 3.97, 9.6)). A significant additive interaction was observed (RERI, 0.20; 95% CI, 0.04–0.36; P = .007), with 15% (95% CI, 2–27) of excess risk attributed to the interaction. Similar interaction patterns were found using device-based intensity metrics and self-reported physical activity measures.

Conclusions

These findings provide evidence of additive interactions between genetic risk and physical activity, underscoring the potential value of integrating genomic and device-derived data to identify individuals who would more likely benefit from increasing physical activity.

Article Highlights

Why did we undertake this study?

Despite longstanding interest in gene–environment interactions influencing the development of type 2 diabetes, identifying such interactions in human populations remains challenging, partially due to difficulties in accurately measuring environmental exposures. Step count is an objective, interpretable measure of daily ambulatory physical activity that offers a novel opportunity to evaluate these interactions. To date, no studies have specifically investigated how daily step counts may interact with genetic susceptibility to influence type 2 diabetes risk.

What is the specific question(s) we wanted to answer?

To what extent do genetic risk and physical activity, measured via daily step count, independently and jointly contribute to the risk of developing type 2 diabetes?

What did we find?

We observed a gradient of increasing type 2 diabetes risk associated with high genetic susceptibility and low step count. This gradient deviated from additivity, with the combination of high genetic risk and low physical activity accounting for substantial proportion of excess type 2 diabetes risk. The evidence of additive interactions between genetic risk and physical activity was replicated in an independent cohort using self-reported physical activity data and longer-term follow-up.

What are the implications of our findings?

Our results highlight the joint impact of genetic risk and physical inactivity on type 2 diabetes development. These findings support the integration of genetic and behavioral risk factors in risk stratification and prevention strategies and may inform targeted public health interventions aimed at reducing the global burden of type 2 diabetes.