Interaction Between Physical Activity and Polygenic Score on Type 2 Diabetes Mellitus in Older Black and White Participants From the Health and Retirement Study

This study investigated the association of lifestyle factors and polygenic risk scores (PGS), and their interaction, on type 2 diabetes mellitus (T2D). We examined data from the U.S. Health and Retirement Study, a prospective longitudinal cohort of adults aged 50 years and older, containing nationally representative samples of Black and White Americans with precalculated PGS for T2D (N = 14 001). Predicted prevalence and incidence of T2D were calculated with logistic regression models. We calculated differences in T2D prevalence and incidence by PGS percentiles and for interaction variables using nonparametric bootstrap method. Black participants had approximately twice the prevalence of Whites (26.2% vs 14.2%), with a larger difference between the 90th and 10th PGS percentile from age 50 to 80 years. Significant interaction (p(interaction) = .0096) was detected between PGS and physical activity among Whites. Among Whites in the 90th PGS percentile, T2D prevalence for moderate physical activity was 17.0% (95% CI: 14.8, 19.6), 6.8% lower compared to no/some physical activity (23.8%; 95% CI: 20.4, 27.5). T2D prevalence was similar (similar to 10%) for both groups in the 10th PGS percentile. Incident T2D in Whites followed a similar pattern (p(interaction) = .0325). No significant interactions with PGS were detected among Black participants. Interaction of different genetic risk profiles with lifestyle factors may inform understanding of varying inventions' efficacy for different groups of people, potentially improving clinical and prevention interventions.

Automated summary

This study found a significant interaction between polygenic risk scores (PGS) and physical activity on the prevalence and incidence of type 2 diabetes mellitus (T2D) among White participants, while no similar interactions were detected among Black participants. These findings suggest that the interaction of different genetic risk profiles with lifestyle factors may play a role in interventions' efficacy for different population groups.