摘要：Background Arsenic (As) occurs as monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) in humans, and the methylation pattern demonstrates large interindividual differences. The fraction of urinary MMA is a marker for susceptibility to As-related diseases. Objectives We evaluated the impact of polymorphisms in five methyltransferase genes on As metabolism in two populations, one in South America and one in Southeast Asia. The methyltransferase genes were arsenic(+III oxidation state) methyltransferase ( AS3MT ), DNA-methyltransferase 1a and 3b ( DNMT1a and DNMT3b , respectively), phosphatidylethanolamine N-methyltransferase ( PEMT ), and betaine-homocysteine methyltransferase ( BHMT ). AS3MT expression was analyzed in peripheral blood. Methods Subjects were women exposed to As in drinking water in the Argentinean Andes [ n = 172; median total urinary As (U-As), 200 μg/L] and in rural Bangladesh ( n = 361; U-As, 100 μg/L; all in early pregnancy). Urinary As metabolites were measured by high-pressure liquid chromatography/inductively coupled plasma mass spectrometry. Polymorphisms ( n = 22) were genotyped with Sequenom, and AS3MT expression was measured by quantitative real-time polymerase chain reaction using TaqMan expression assays. Results Six AS3MT polymorphisms were significantly associated with As metabolite patterns in both populations ( p ≤ 0.01). The most frequent AS3MT haplotype in Bangladesh was associated with a higher percentage of MMA (%MMA), and the most frequent haplotype in Argentina was associated with a lower %MMA and a higher percentage of DMA. Four polymorphisms in the DNMT genes were associated with metabolite patterns in Bangladesh. Noncoding AS3MT polymorphisms affected gene expression of AS3MT in peripheral blood, demonstrating that one functional impact of AS3MT polymorphisms may be altered levels of gene expression. Conclusions Polymorphisms in AS3MT significantly predicted As metabolism across these two very different populations, suggesting that AS3MT may have an impact on As metabolite patterns in populations worldwide.
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