Abstract
Arsenic contamination of drinking water is a major public health issue in many countries, increasing risk for a wide array of diseases, including cancer. There is inter-individual variation in arsenic metabolism efficiency and susceptibility to arsenic toxicity; however, the basis of this variation is not well understood. Here, we have performed the first genome-wide association study (GWAS) of arsenic-related metabolism and toxicity phenotypes to improve our understanding of the mechanisms by which arsenic affects health. Using data on urinary arsenic metabolite concentrations and approximately 300,000 genome-wide single nucleotide polymorphisms (SNPs) for 1,313 arsenic-exposed Bangladeshi individuals, we identified genome-wide significant association signals (P<5×10
−8
) for percentages of both monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) near the AS3MT gene (arsenite methyltransferase; 10q24.32), with five genetic variants showing independent associations. In a follow-up analysis of 1,085 individuals with arsenic-induced premalignant skin lesions (the classical sign of arsenic toxicity) and 1,794 controls, we show that one of these five variants (rs9527) is also associated with skin lesion risk (P = 0.0005). Using a subset of individuals with prospectively measured arsenic (n = 769), we show that rs9527 interacts with arsenic to influence incident skin lesion risk (P = 0.01). Expression quantitative trait locus (eQTL) analyses of genome-wide expression data from 950 individual's lymphocyte RNA suggest that several of our lead SNPs represent cis-eQTLs for AS3MT (P = 10
−12
) and neighboring gene C10orf32 (P = 10
−44
), which are involved in C10orf32-AS3MT read-through transcription. This is the largest and most comprehensive genomic investigation of arsenic metabolism and toxicity to date, the only GWAS of any arsenic-related trait, and the first study to implicate 10q24.32 variants in both arsenic metabolism and arsenical skin lesion risk. The observed patterns of associations suggest that MMA% and DMA% have distinct genetic determinants and support the hypothesis that DMA is the less toxic of these two methylated arsenic species. These results have potential translational implications for the prevention and treatment of arsenic-associated toxicities worldwide.
Exposure to arsenic through drinking water is a serious public health issue in many countries, including Bangladesh and the United States. Although there is substantial inter-individual variation in arsenic metabolism and toxicity, the biological basis of this variation is not well understood. Here, we have conducted the first genome-wide association study of arsenic-related traits within a unique population cohort of arsenic-exposed Bangladeshi individuals. Using data on 1,313 well-characterized individuals, we identify multiple association signals for urinary arsenic metabolite concentrations in the 10q24.32 regions, near the AS3MT (arsenite methyltransferase) gene. In a subsequent analysis of >2,000 individuals, we show for the first time that variants that influence arsenic metabolism can also influence risk for arsenical skin lesions (the classical sign of arsenic toxicity) through interaction with arsenic exposure. Using array-based genome-wide gene expression data, we show that several of our lead genetic variants are associated with expression of AS3MT and neighboring gene C10orf32, providing a potential mechanism by which 10q24.32 variants influence arsenic metabolism and toxicity. Knowledge of variation in this region and associated biological processes could be used to develop intervention and pharmacological strategies aimed at preventing large numbers of arsenic-related deaths in arsenic-exposed populations.