Research overview
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Several recent observational studies have found associations between nitrogen dioxide (NO2) exposure and the risk of Parkinson's disease (PD), but the causal relationship between them remains unclear. Our objective is to employ a 2-sample Mendelian randomization (MR) approach to determine the causal effect of NO2 exposure on the risk of PD. MR analyses were performed using genome-wide association studies (GWAS) data on NO2 exposure (n = 456,380) and PD GWAS data (33,674 cases and 449,056 controls). Inverse variance weighting (IVW) was the primary analytical method used to examine causal effects, coupled with the MR-Egger, weighted median, weighted model and MR pleiotropy residual sum and outlier (MR-PRESSO). The main results of the IVW method (odds ratio: 4.701; 95% CI: 1.127-19.615, P = .034) showed evidence for a causal relationship between NO2 exposure and the risk of PD. Heterogeneity analyses was conducted using the MR-Egger method (Cochran's Q = 1.155; P = .764) and IVW (Cochran's Q = 1.356; P = .852) demonstrated no statistically significant heterogeneity among the selected SNPs. We employed MR-Egger regression (β intercept = -0.026; SE = 0.058; P = .684) and the MR-PRESSO global test (P = .840), which revealed no significant impact of pleiotropy on the results of the MR evaluation. Based on MR analysis, higher levels of NO2 exposure are causally associated with an increased risk of PD. Consequently, mitigating air pollution could be an important strategy for reducing the risk of PD.
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