Association between air pollutants and four major mental disorders: Evidence from a Mendelian randomization study

Abstract

Existing epidemiological studies have indicated a correlation between air pollutants and the occurrence of mental disorders. However, it is difficult to estimate the causal relationship between the two because of the limitations of traditional epidemiological research. In our study, we aimed to extensively explore the causal relationship between five types of air pollutants and four types of mental disorders. Based on the IEU OPEN GWAS database, we performed a two-sample MR analysis. The primary analysis method utilized was the inverse variance weighted (IVW) method, supplemented by the MR-Egger method and the weighted median method. Additionally, we conducted sensitivity analyses with the Cochran's Q statistic method, the leave-one-out method, and the MR-Egger intercept. We chose at least 4 GWAS datasets for each of the four psychiatric diseases and conducted a meta-analysis of our results of the MR analysis. The meta-analysis's findings demonstrated a causal link between depression and PM2.5 (OR=1.020, 95 %CI: (1.010,1.030), P=0.001). PM10 and schizophrenia are also causally related (OR=1.136, 95 %CI: (1.034,1.248), P=0.008). Nitrogen oxides and bipolar disorder have a causal relationship (OR=1.002, 95 %CI: (1.000,1.003), P=0.022). Nitrogen oxides and schizophrenia have a high causal association (OR=1.439, 95 %CI: (1.183,1.752), P<0.001). This study observed a causal association between increased concentrations of PM2.5, PM10, and nitrogen oxides and the occurrence of depression, schizophrenia, and bipolar disorder. Our research findings have certain guiding implications for treating and preventing mental disorders. ● This study applied Mendelian randomization and meta-analysis to large GWAS data to investigate the causal link between air pollutants and mental disorders in Europeans. ● By using two-sample MR analysis, the study bypassed traditional research limitations, bolstering causal inference and research credibility. ● The study's causal findings offer scientific support for public health policies to reduce mental illness incidence.

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