Influence of genetic polymorphisms on arsenic methylation efficiency during pregnancy: Evidence from a Spanish birth cohort.

ABSTRACT

BACKGROUND: Inorganic arsenic (iAs) is a widespread toxic metalloid. It is well-known that iAs metabolism and its toxicity are mediated by polymorphisms in AS3MT and other genes. However, studies during pregnancy are scarce. We aimed to examine the role of genetic polymorphisms in AS3MT, GSTO2, N6AMT1, MTHFR, MTR, FTCD, CBS, and FOLH1 in iAs methylation efficiency during pregnancy. METHODS: The study included 541 pregnant participants from the INMA (Environment and Childhood) Spanish cohort. Using high-performance liquid chromatography coupled to inductively coupled plasma-tandem mass, we measured arsenic (iAs and the metabolites monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA)) in urine samples collected during the first trimester. iAs methylation efficiency was determined based on relative concentrations of the As metabolites in urine (%MMA, %DMA, and %iAs). Thirty-two single nucleotide polymorphisms (SNPs) in nine genes were determined in maternal DNA; AS3MT haplotypes were inferred. We assessed the association between genotypes/haplotypes and maternal As methylation efficiency using multivariate linear regression models. RESULTS: The median %MMA and %DMA were 5.3 %, and 89 %, respectively. Ancestral alleles of AS3MT SNPs (rs3740393, rs3740390, rs11191453, and rs11191454) were significantly associated with higher %MMA, %iAs, and lower %DMA. Pregnant participants with zero copies of the GGCTTCAC AS3MT haplotype presented a higher %MMA. Statistically significant associations were also found for the FOLH1 SNP rs202676 (ß 0.89 95%CI 0.24, 1.55 for carriers of the G allele vs. the A allele). CONCLUSIONS: Our study shows that ancestral alleles in AS3MT polymorphisms were associated with lower As methylation efficiency in early pregnancy and suggests that FOLH1 also plays a role in As methylation efficiency. These results support the hypothesis that As metabolism is multigenic, being a key element for identifying susceptible populations.