Effects of particulate matter exposure on the risk of type 2 diabetes: a Mendelian randomization study.

Objective: The impact of particulate matter (PM) on the risk of type 2 diabetes (T2D) remains inconclusive. The purpose of this study was to assess the causal relationship between PM and T2D using Mendelian randomization (MR) analysis.

Materials and methods: Single nucleotide polymorphisms (SNPs) for PM2.5, PM10, and T2D were obtained from the UK Biobank and FinnGen datasets. Inverse variance weighted, MR-Egger, and weighted median were utilized to examine the causal relationship between exposure and outcome. MR-Egger intercept analysis, Cochran's Q test, and leave-one-out sensitivity analysis were used to assess horizontal pleiotropy, heterogeneity, and robustness of the results, respectively.

Results: The MR analysis revealed a significant association between PM2.5 and increased risk of T2D (OR: 1.159, 95% CI: 1.003 to 1.339, p = 0.045), while no significant association was found between PM10 and T2D risk (OR: 1.031, 95% CI: 0.788 to 1.350, p = 0.822). MR-Egger intercept analysis and Cochran's Q test indicated no evidence of horizontal pleiotropy or heterogeneity in these results. Sensitivity analysis demonstrated the robustness of the results.

Conclusions: This MR analysis suggests that PM2.5, rather than PM10, is associated with an increased risk of T2D. The use of air purifiers and anti-smog masks may potentially help reduce the risk of T2D. Further research is needed to elucidate the specific effects and underlying mechanisms of PM2.5 and PM10 on T2D.