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Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
Published on: January 7, 2014
Exploring the association between air pollution and Parkinson's disease or Alzheimer's disease: a Mendelian
Pingping Ning1,2, Xingzhi Guo1,2,3, Qiumin Qu4
1Department of Geriatric Neurology, Shaanxi Provincial People's Hospital, Xi'an, 710068, People's Republic of China.
Abstract:
The correlation between air pollution and neurodegenerative diseases has garnered growing attention. Although observational studies have indicated a potential link between air pollution and neurodegenerative disease, establishing a causal relationship remains uncertain. To address this gap, we performed a two-sample Mendelian randomization analysis utilizing genetic instruments. This analysis aimed to investigate the causal connections between PM2.5, PM10, NO2, and NOX exposure and the occurrence of Parkinson's disease (PD) and Alzheimer's disease (AD). We implemented a series of filtering steps to identify suitable genetic instruments that demonstrated significant associations (P < 5 × 10-8) with PM2.5, PM10, NO2, and NOX. These instruments were derived from a comprehensive genome-wide association study (GWAS) encompassing up to 456,380 participants in the UK Biobank. To obtain summary statistics for PD (N = 482,730) and AD risk (N = 63,926), we utilized the most recent GWAS datasets available. For our primary analysis, we employed the inverse-variance weighted approach for two-sample MR. A multivariable MR (MVMR) was also performed to verify the impact of air pollution exposure on the risk of PD and AD. To ensure the robustness of our findings, sensitivity analyses and heterogeneity assessments were performed. In two-sample MR, by employing the inverse-variance weighted method, our result suggested that genetically NO2 exposure showed a significant association with an elevated risk of PD (OR = 4.07, 95% CI: 1.13 to 19.62, P = 0.034) and genetically PM10 exposure exhibited a significant association with a heightened risk of AD (OR = 1.93, 95% CI: 1.03-3.59, P = 0.040). Further MVMR analysis demonstrated that the causal effect between NO2 and PD disappeared (OR = 3.489, 95% CI: 0.01 to 2.1e + 03, P = 0.703), and only PM10 was associated with an increased risk of AD (OR = 6.500, 95% CI: 1.10 to 38.51, P = 0.039). Sensitivity analysis showed no detectable heterogeneity and pleiotropy (P > 0.05). Our findings demonstrate that NO2 and PM10 exposure may contribute to a risk of PD and AD, respectively. Future research is necessary to elucidate potential physiopathological mechanisms.
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