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.