The impact of PM 2.5 on lung function and chronic respiratory diseases: insights from genetic evidence.

Background: PM _2.5 has been associated with various adverse health effects, particularly affecting lung function and chronic respiratory diseases. However, the genetic causality relationship between PM _2.5 exposure and lung function as well as chronic respiratory diseases remains poorly understood.
Method: We conducted a two-sample Mendelian randomization analysis to investigate the causal impact of PM _2.5 on lung function and chronic respiratory diseases. Instrumental variables were carefully selected, with significance thresholds (P < 5 × 10 ^- 8 ), and linkage disequilibrium with an r ² value below 0.001. Additionally, SNPs with an F-statistic exceeding 10 were included to mitigate potential bias stemming from weak instrumental variables. The primary analytical approach employed the Inverse Variance Weighted method, supplemented by the Weighted Median, MR-Egger, Simple Model, and Weighted Model. Furthermore, pleiotropy and heterogeneity were evaluated through the MR-Egger intercept test and Cochrane's Q test, with a sensitivity analysis conducted using the leave-one-out method.
Results: Eight SNPs significantly associated with PM _2.5 exposure were identified as Instrumental variables. Mendelian randomization analysis revealed a significant causal association between PM _2.5 exposure and lung function (FEV), with an OR of 0.7284 (95% CI: 0.5799-0.9150). Similarly, PM _2.5 exposure demonstrated a substantial causal effect on asthma, with an OR of 1.5280 (95% CI: 1.0470-2.2299). However, no causal association was observed between PM _2.5 exposure and chronic obstructive pulmonary disease, with an OR of 1.5176 (95% CI: 0.8294-2.7768).
Conclusion: These findings emphasize the necessity for continued research efforts in environmental health to develop effective strategies for the prevention and management of chronic respiratory diseases.
(© 2024. The Author(s) under exclusive licence to International Society of Biometeorology.)