Polygenic risk and air pollution trends in relation to type 2 diabetes: evidence from the Taiwan Biobank

Both genetic predisposition and air pollution may lead to type 2 diabetes mellitus (T2D). However, the synergistic effects of gene by environment interactions between air pollution exposure and genetic susceptibility to T2D remain underexplored in Asian populations. This study assessed the association between air pollutants, including fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃), and T2D, while considering polygenic risk scores (PRS).

Data were obtained from 104,554 participants in the Taiwan Biobank. Air pollutant concentrations were estimated using satellite-based models, and long-term trends were represented by slopes derived from linear regression models. The PRS for T2D was constructed from East Asian-specific genome-wide association study summary statistics (AGEN consortium) using the clumping and thresholding method. Logistic regression models were applied to examine associations of T2D with air pollution and PRS, expressed as odds ratios (ORs) and 95% confidence intervals (CIs). Additive interaction was evaluated using the relative excess risk due to interaction (RERI), and multiplicative interaction was tested via cross-product terms in logistic models.

Every 1 µg/m³ per year increase in PM_2.5 concentrations was significantly associated with increased T2D risk (OR: 1.036, 95% CI: 1.003-1.071). A positive exposure-response relationship between PRS and T2D was observed, with individuals in the highest PRS quartile showing significantly higher risk (OR: 1.385, 95% CI: 1.279,1.499). The association between PM_2.5 slope and T2D was slightly stronger among those with the highest genetic risk; however, the additive interaction was weak and borderline significant (RERI: 0.144, 95% CI: 0.008-0.319).

Both worsening PM_2.5 exposure and PRS were associated with T2D. The observed PM_2.5 and PRS interaction was weak and should be interpreted cautiously. Our findings highlight the importance of improving air quality and adopting personalized prevention strategies for individuals with high genetic risk.