Assessing the impact of arsenic metabolism efficiency on DNA methylation using Mendelian randomization

Environ Epidemiol. 2020 Apr 9;4(2):e083. doi: 10.1097/EE9.0000000000000083. eCollection 2020 Apr.


Background: Arsenic exposure affects >100 million people globally and increases risk for chronic diseases. One possible toxicity mechanism is epigenetic modification. Previous epigenome-wide association studies (EWAS) have identified associations between arsenic exposure and CpG-specific DNA methylation. To provide additional evidence that observed associations represent causal relationships, we examine the association between genetic determinants of arsenic metabolism efficiency (percent dimethylarsinic acid, DMA%, in urine) and DNA methylation among individuals from the Health Effects of Arsenic Longitudinal Study (n = 379) and Bangladesh Vitamin E and Selenium Trial (n = 393).

Methods: We used multivariate linear models to assess the association of methylation at 221 arsenic-associated CpGs with DMA% and measures of genetically predicted DMA% derived from three SNPs (rs9527, rs11191527, and rs61735836). We also conducted two-sample Mendelian randomization analyses to estimate the association between arsenic metabolism efficiency and CpG methylation.

Results: Among the associations between DMA% and methylation at each of 221 CpGs, 64% were directionally consistent with associations observed between arsenic exposure and the 221 CpGs from a prior EWAS. Similarly, among the associations between genetically predicted DMA% and each CpG, 62% were directionally consistent with the prior EWAS results. Two-sample Mendelian randomization analyses produced similar conclusions.

Conclusion: Our findings support the hypothesis that arsenic exposure effects DNA methylation at specific CpGs in whole blood. Our novel approach for assessing the impact of arsenic exposure on DNA methylation requires larger samples in order to draw more robust conclusions for specific CpG sites.

Keywords: Arsenic; Bangladesh; DNA methylation; Epigenomics; Mendelian randomization.