AS3MT, GSTO, and PNP polymorphisms: Impact on arsenic methylation and implications for disease susceptibility

Antonelli, Ray; Shao, Kan; Thomas, David J.; Sams, Reeder; Cowden, John

doi:10.1016/j.envres.2014.03.012

Cited by 108 publications

(72 citation statements)

References 83 publications

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“…Polymorphisms of glutathione S-transferase omega 1 (GSTO1) and omega 2 (GSTO2) have also been posited as potential modifiers of iAs methylation capacity, at least in areas with moderate to high exposures (Hsieh et al, 2011). However, these polymorphisms have not shown consistent associations with increased risk of adverse health outcomes (Antonelli et al, 2014). Some polymorphisms are associated with increases and other with decreases in the percentage of MMA; for example, Engstrom et al (2011) reported that the most frequent As3MT haplotype in Argentina lowered the proportion of MMA and increased the proportion of DMA in urine, while in Bangladesh, the most frequent As3MT haplotype increased the percent of MMA.…”

Section: Difference In Susceptibility Across Humansmentioning

confidence: 98%

“…Genetic polymorphisms in the As3MT gene can affect the ratio between various methylated species excreted in the urine. Other methyl-transferases including N-6 adenine-specific DNA methyl-transferase 1 (N6AMT) and purine nucleoside phosphorylase (PNP) may also affect methylation of iAs (Cohen et al, 2013;Antonelli et al, 2014). Antonelli et al (2014) performed a comprehensive review of the human literature and found that three specific polymorphisms in As3MT (rs3740390, rs11191439, and rs111914rsrs1139, and rs111914rs1139, and rs11191453) were associated with significant changes in the percent of MMA in the urine.…”

Section: Difference In Susceptibility Across Humansmentioning

confidence: 99%

“…Other methyl-transferases including N-6 adenine-specific DNA methyl-transferase 1 (N6AMT) and purine nucleoside phosphorylase (PNP) may also affect methylation of iAs (Cohen et al, 2013;Antonelli et al, 2014). Antonelli et al (2014) performed a comprehensive review of the human literature and found that three specific polymorphisms in As3MT (rs3740390, rs11191439, and rs111914rsrs1139, and rs111914rs1139, and rs11191453) were associated with significant changes in the percent of MMA in the urine. Polymorphisms of glutathione S-transferase omega 1 (GSTO1) and omega 2 (GSTO2) have also been posited as potential modifiers of iAs methylation capacity, at least in areas with moderate to high exposures (Hsieh et al, 2011).…”

Section: Difference In Susceptibility Across Humansmentioning

confidence: 99%

See 2 more Smart Citations

Mechanisms of action for arsenic in cardiovascular toxicity and implications for risk assessment

et al. 2015

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Section: Difference In Susceptibility Across Humansmentioning

confidence: 98%

Section: Difference In Susceptibility Across Humansmentioning

confidence: 99%

Section: Difference In Susceptibility Across Humansmentioning

confidence: 99%

See 1 more Smart Citation

Mechanisms of action for arsenic in cardiovascular toxicity and implications for risk assessment

et al. 2015

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“…The trivalent metabolites (particularly MMA III) are most commonly associated with adverse health outcomes and the distribution of urinary As metabolites is determined to a greater extend by genetic variations and is illustrated by the aggregation of methylation patterns within families [120, 121]. Mn secretion in the bile may vary according to individuals’ genotypic status.…”

Section: Biomarkers For Lead (Pb) Arsenic (As) and Manganese (Mn)mentioning

confidence: 99%

Lead, Arsenic, and Manganese Metal Mixture Exposures: Focus on Biomarkers of Effect

Andrade

Mateus

Batoréu

et al. 2015

Biol Trace Elem Res

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Summary The increasing exposure of human populations to excessive levels of metals continues to represent a matter of public health concern. Several biomarkers have been studied and proposed for the detection of adverse health effects induced by lead (Pb), arsenic (As) and manganese (Mn); however, these studies have relied on exposures to each single metal, which fails to replicate real-life exposure scenarios. These 3 metals are commonly detected in different environmental, occupational and food contexts and they share common neurotoxic effects, which are progressive and once clinically apparent may be irreversible. Thus, chronic exposure to low levels of a mixture of these metals represents an additive risk of toxicity. Building upon their shared mechanisms of toxicity, such as oxidative stress, interference with neurotransmitters and effects on hematopoietic system, we address putative biomarkers, which may be assist in assessing onset of neurological diseases associated with exposure to this metal mixture.

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“…Typical urine metabolite percentages in humans are 10-30% for iAs, 10-20% for MMA, and 60-80% for DMA (15–21). Both pentavalent and trivalent forms of these arsenic species can be present in urine (20,22–25). The trivalent forms of iAs, MMA, and DMA are likely to be the more toxic forms (20,26–29) with MMA III having the highest toxicity followed by iAs III (30,31).…”

Section: Introductionmentioning

confidence: 99%

Determinants and Consequences of Arsenic Metabolism Efficiency among 4,794 Individuals: Demographics, Lifestyle, Genetics, and Toxicity

Jansen

Argos

Lin

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Exposure to inorganic arsenic (iAs), class I carcinogen, affects several hundred-million people worldwide. Once absorbed, iAs is converted to monomethylated (MMA) and then dimethylated forms (DMA), with methylation facilitating urinary excretion. The abundance of each species in urine relative to their sum (iAs%, MMA%, and DMA%), varies across individuals, reflecting differences in arsenic metabolism capacity. Methods The association of arsenic metabolism phenotypes with participant characteristics and arsenical skin lesions was characterized among 4,794 participants in the Health Effects of Arsenic Longitudinal Study (Araihazar, Bangladesh). Metabolism phenotypes include those obtained from principal components (PC) analysis of arsenic species. Results Two independent PCs were identified: PC1 appears to represent capacity to produce DMA (2nd methylation step), and PC2 appears to represent capacity to convert iAs to MMA (1st methylation step). PC 1 was positively associated (p <0.05) with age, female sex, and BMI, while negatively associated with smoking, arsenic exposure, education, and land ownership. PC2 was positively associated with age and education but negative associated with female sex and BMI. PC2 was positively associated with skin lesion status, while PC1 was not. 10q24.32/AS3MT region polymorphisms were strongly associated with PC1, but not PC2. Patterns of association for most variables were similar for PC1 and DMA%, and for PC2 and MMA% with the exception of arsenic exposure and SNP associations. Conclusions Two distinct arsenic metabolism phenotypes show unique associations with age, sex, BMI, 10q24.32 polymorphisms, and skin lesions. Impact: This work enhances our understanding of arsenic metabolism kinetics and toxicity risk profiles.

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AS3MT, GSTO, and PNP polymorphisms: Impact on arsenic methylation and implications for disease susceptibility

Cited by 108 publications

References 83 publications

Mechanisms of action for arsenic in cardiovascular toxicity and implications for risk assessment

Mechanisms of action for arsenic in cardiovascular toxicity and implications for risk assessment

Lead, Arsenic, and Manganese Metal Mixture Exposures: Focus on Biomarkers of Effect

Determinants and Consequences of Arsenic Metabolism Efficiency among 4,794 Individuals: Demographics, Lifestyle, Genetics, and Toxicity

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