The genetic architecture of arsenic metabolism efficiency: A SNP-based heritability study of bangladeshi adults

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Abstract

© 2015, Public Health Services, US Dept of Health and Human Services. All rights reserved. Background: Consumption of arsenic-contaminated drinking water adversely affects health. There is interindividual variation in arsenic metabolism efficiency, partially due to genetic variation in the arsenic methyltransferase (AS3MT) gene region. Objectives: The goal of this study was to assess the overall contribution of genetic factors to variation in arsenic metabolism efficiency, as measured by the relative concentration of dimethylarsinic acid (DMA%) in urine. Methods: Using data on genome-wide single nucleotide polymorphisms (SNPs) and urinary DMA% for 2,053 arsenic-exposed Bangladeshi individuals, we employed various SNP-based approaches for heritability estimation and polygenic modeling. Results: Using data on all participants, the percent variance explained (PVE) for DMA% by all measured and imputed SNPs was 16% (p = 0.08), which was reduced to 5% (p = 0.34) after adjusting for AS3MT SNPs. Using information on close relatives only, the PVE was 63% (p = 0.0002), but decreased to 41% (p = 0.01) after adjusting for AS3MT SNPs. Regional heritability analysis confirmed 10q24.32 (AS3MT) as a major arsenic metabolism locus (PVE = 7%, p = 4.4 × 10 –10 ), but revealed no additional regions. We observed a moderate association between a polygenic score reflecting elevated DMA% (composed of thousands of non-AS3MT SNPs) and reduced skin lesion risk in an independent sample (p < 0.05). We observed no associations for SNPs reported in prior candidate gene studies of arsenic metabolism. Conclusions: Our results suggest that there are common variants outside of the AS3MT region that influence arsenic metabolism in Bangladeshi individuals, but the effects of these variants are very weak compared with variants near AS3MT. The high heritability estimates observed using family-based heritability approaches suggest substantial effects for rare variants and/or unmeasured environmental factors.

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Gao, J., Tong, L., Argos, M., Bryan, M. S., Ahmed, A., Rakibuz-Zaman, M., … Pierce, B. L. (2015). The genetic architecture of arsenic metabolism efficiency: A SNP-based heritability study of bangladeshi adults. Environmental Health Perspectives, 123(10), 985–992. https://doi.org/10.1289/ehp.1408909

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