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

Joyce Mary Kim, Eunji Kim, Do Kyeong Song, Yi Jun Kim, Ji Hyen Lee, Eunhee Ha

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3 Scopus citations


Backgrounds: Many studies have shown particulate matter has emerged as one of the major environmental risk factors for diabetes; however, studies on the causal relationship between particulate matter 2.5 (PM2.5) and diabetes based on genetic approaches are scarce. The study estimated the causal relationship between diabetes and PM2.5 using two sample mendelian randomization (TSMR). Methods: We collected genetic data from European ancestry publicly available genome wide association studies (GWAS) summary data through the MR-BASE repository. The IEU GWAS information output PM2.5 from the Single nucleotide polymorphisms (SNPs) GWAS pipeline using pheasant-derived variables (Consortium = MRC-IEU, sample size: 423,796). The annual relationship of PM2.5 (2010) were modeled for each address using a Land Use Regression model developed as part of the European Study of Cohorts for Air Pollution Effects. Diabetes GWAS information (Consortium = MRC-IEU, sample size: 461,578) were used, and the genetic variants were used as the instrumental variables (IVs). We performed three representative Mendelian Randomization (MR) methods: Inverse Variance Weighted regression (IVW), Egger, and weighted median for causal relationship using genetic variants. Furthermore, we used a novel method called MR Mixture to identify outlier SNPs. Results: From the IVW method, we revealed the causal relationship between PM2.5 and diabetes (Odds ratio [OR]: 1.041, 95% CI: 1.008–1.076, P = 0.016), and the finding was substantiated by the absence of any directional horizontal pleiotropy through MR-Egger regression (β = 0.016, P = 0.687). From the IVW fixed-effect method (i.e., one of the MR machine learning mixture methods), we excluded outlier SNP (rs1537371) and showed the best predictive model (AUC = 0.72) with a causal relationship between PM2.5 and diabetes (OR: 1.028, 95% CI: 1.006–1.049, P = 0.012). Conclusion: We identified the hypothesis that there is a causal relationship between PM2.5 and diabetes in the European population, using MR methods.

Original languageEnglish
Article number1164647
JournalFrontiers in Public Health
StatePublished - 2023

Bibliographical note

Publisher Copyright:
Copyright © 2023 Kim, Kim, Song, Kim, Lee and Ha.


  • GWAS
  • diabetes
  • environmental epidemiology
  • genetics epidemiology
  • particulate matter 2.5
  • two sample Mendelian randomization


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