Causal relationship between particulate matter 2.5 and diabetes: two sample Mendelian randomization.

Area of Science:

• Environmental Health
• Genetics
• Epidemiology

Background:

• Particulate matter (PM$_{2.5}$) is a known environmental risk factor for diabetes.
• Genetic studies investigating the causal link between PM$_{2.5}$ and diabetes are limited.

Purpose of the Study:

• To estimate the causal relationship between PM$_{2.5}$ exposure and diabetes.
• To employ genetic approaches, specifically two-sample Mendelian randomization (TSMR), to assess causality.

Main Methods:

• Utilized genome-wide association studies (GWAS) summary data for PM$_{2.5}$ and diabetes in European ancestry.
• Applied three Mendelian randomization (MR) methods: Inverse Variance Weighted (IVW), Egger, and weighted median.
• Employed MR Mixture to identify and exclude outlier single nucleotide polymorphisms (SNPs).

Main Results:

• The IVW method indicated a causal relationship between PM$_{2.5}$ and diabetes (OR: 1.041, P=0.016).
• MR-Egger regression showed no significant horizontal pleiotropy (P=0.687), supporting the causal inference.
• After outlier exclusion, the causal link remained significant (OR: 1.028, P=0.012) with a robust predictive model (AUC=0.72).

Conclusions:

• A causal relationship exists between PM$_{2.5}$ exposure and diabetes in the European population.
• Mendelian randomization provides strong evidence for PM$_{2.5}$ as a causal risk factor for diabetes.