Causal relationship between particulate matter 2.5 and hypothyroidism: A two-sample Mendelian randomization study

Abstract

Background: Epidemiological surveys have found that particulate matter 2.5 (PM_2.5) plays an important role in hypothyroidism. However, due to the methodological limitations of traditional observational studies, it is difficult to make causal inferences. In the present study, we assessed the causal association between PM_2.5 concentrations and risk of hypothyroidism using two-sample Mendelian randomization (TSMR).

Methods: We performed TSMR by using aggregated data from genome-wide association studies (GWAS) on the IEU Open GWAS database. We identified seven single nucleotide polymorphisms (SNPs) associated with PM_2.5 concentrations as instrumental variables (IVs). We used inverse-variance weighting (IVW) as the main analytical method, and we selected MR-Egger, weighted median, simple model, and weighted model methods for quality control.

Results: MR analysis showed that PM_2.5 has a positive effect on the risk of hypothyroidism: An increase of 1 standard deviation (SD) in PM_2.5 concentrations increases the risk of hypothyroidism by ~10.0% (odds ratio 1.10, 95% confidence interval 1.06-1.13, P = 2.93E-08, by IVW analysis); there was no heterogeneity or pleiotropy in the results.

Conclusion: In conclusion, increased PM_2.5 concentrations are associated with an increased risk of hypothyroidism. This study provides evidence of a causal relationship between PM_2.5 and the risk of hypothyroidism, so air pollution control may have important implications for the prevention of hypothyroidism.

Keywords: GWAS; Mendelian randomization; PM2.5; air pollution; hypothyroidism.