Arsenic methylation, GSTO1 polymorphisms, and metabolic syndrome in an arseniasis endemic area of southwestern Taiwan

The association between heavy metal exposure and obesity: A systematic review and meta-analysis

Background

Obesity and metabolic syndrome are global health concerns associated with development of different types of diseases and serious health threats in the long term. Their metabolic imbalance can be attributable to inherited and environmental factors. As a considerable environmental agent, heavy metals exposure can predispose individuals to diseases like obesity. This systematic review and meta-analysis aimed to evaluate the association between heavy metals exposure and the risk of obesity.

Methods

PubMed/MEDLINE, EMBASE and Web of Science were systematically searched until December 17, 2022. Only observational studies that evaluated heavy metals exposure and obesity were included. Studies were excluded if they assessed maternal or prenatal exposure, the mixture of heavy metals and other chemicals, reported the association with overweight or other diseases, and undesirable study designs. The Joanna Briggs Institute checklist was used for quality assessment. The pooled adjusted odds ratio (aOR) and the pooled standardized mean difference (SMD) with their 95% confidence intervals (CIs) were calculated, respectively. The publication bias was evaluated using Egger's and Begg's tests.

Results

Twenty studies (n = 127755), four case-control and sixteen analytical cross-sectional studies, were included. Lead exposure was significantly associated with a lower risk of obesity (aOR: 0.705, 95% CI: 0.498-0.997), while mercury (aOR: 1.458, 95% CI: 1.048-2.031) and barium (aOR: 1.439, 95% CI: 1.142-1.813) exposure increased the risk of obesity. No significant publication bias was found and the studies had a low risk of bias.

Conclusion

Overall, lead exposure reduced obesity risk, while mercury and barium exposure raised it. Further large-scale observational studies are recommended to determine the roles of heavy metals in obesity.Study registration ID: CRD42023394865.

Supplementary information

The online version contains supplementary material available at 10.1007/s40200-023-01307-0.

Arsenic and adipose tissue: an unexplored pathway for toxicity and metabolic dysfunction

Arsenic-contaminated drinking water can induce various disorders by disrupting lipid and glucose metabolism in adipose tissue, leading to insulin resistance. It inhibits adipocyte development and exacerbates insulin resistance, though the precise impact on lipid synthesis and lipolysis remains unclear. This review aims to explore the processes and pathways involved in adipogenesis and lipolysis within adipose tissue concerning arsenic-induced diabetes. Although arsenic exposure is linked to type 2 diabetes, the specific role of adipose tissue in its pathogenesis remains uncertain. The review delves into arsenic's effects on adipose tissue and related signaling pathways, such as SIRT3-FOXO3a, Ras-MAP-AP-1, PI(3)-K-Akt, endoplasmic reticulum stress proteins, CHOP10, and GPCR pathways, emphasizing the role of adipokines. This analysis relies on existing literature, striving to offer a comprehensive understanding of different adipokine categories contributing to arsenic-induced diabetes. The findings reveal that arsenic detrimentally impacts white adipose tissue (WAT) by reducing adipogenesis and promoting lipolysis. Epidemiological studies have hinted at a potential link between arsenic exposure and obesity development, with limited research suggesting a connection to lipodystrophy. Further investigations are needed to elucidate the mechanistic association between arsenic exposure and impaired adipose tissue function, ultimately leading to insulin resistance.

Update of the risk assessment of inorganic arsenic in food

The European Commission asked EFSA to update its 2009 risk assessment on arsenic in food carrying out a hazard assessment of inorganic arsenic (iAs) and using the revised exposure assessment issued by EFSA in 2021. Epidemiological studies show that the chronic intake of iAs via diet and/or drinking water is associated with increased risk of several adverse outcomes including cancers of the skin, bladder and lung. The CONTAM Panel used the benchmark dose lower confidence limit based on a benchmark response (BMR) of 5% (relative increase of the background incidence after adjustment for confounders, BMDL05) of 0.06 μg iAs/kg bw per day obtained from a study on skin cancer as a Reference Point (RP). Inorganic As is a genotoxic carcinogen with additional epigenetic effects and the CONTAM Panel applied a margin of exposure (MOE) approach for the risk characterisation. In adults, the MOEs are low (range between 2 and 0.4 for mean consumers and between 0.9 and 0.2 at the 95th percentile exposure, respectively) and as such raise a health concern despite the uncertainties.

Arsenic induces metabolome remodeling in mature human adipocytes

Human lifetime exposure to arsenic through drinking water, food supply or industrial pollution leads to its accumulation in many organs such as liver, kidneys, lungs or pancreas but also adipose tissue. Recently, population-based studies revealed the association between arsenic exposure and the development of metabolic diseases such as obesity and type 2 diabetes. To shed light on the molecular bases of such association, we determined the concentration that inhibited 17% of cell viability and investigated the effects of arsenic acute exposure on adipose-derived human mesenchymal stem cells differentiated in vitro into mature adipocytes and treated with sodium arsenite (NaAsO2, 10 nM to 10 µM). Untargeted metabolomics and gene expression analyses revealed a strong dose-dependent inhibition of lipogenesis and lipolysis induction, reducing the cellular ability to store lipids. These dysregulations were emphasized by the inhibition of the cellular response to insulin, as shown by the perturbation of several genes and metabolites involved in the mentioned biological pathways. Our study highlighted the activation of an adaptive oxidative stress response with the strong induction of metallothioneins and increased glutathione levels in response to arsenic accumulation that could exacerbate the decreased insulin sensitivity of the adipocytes. Arsenic exposure strongly affected the expression of arsenic transporters, responsible for arsenic influx and efflux, and induced a pro-inflammatory state in adipocytes by enhancing the expression of the inflammatory interleukin 6 (IL6). Collectively, our data showed that an acute exposure to low levels of arsenic concentrations alters key adipocyte functions, highlighting its contribution to the development of insulin resistance and the pathogenesis of metabolic disorders.

Association between arsenic (+3 oxidation state) methyltransferase gene polymorphisms and arsenic methylation capacity in rural residents of northern China: a cross-sectional study

Arsenic is a toxic metal-like element. The toxic reaction of the body to arsenic is related to the ability of arsenic methylation metabolism. As the rate-limiting enzyme of arsenic methylation metabolism, the genetic single nucleotide polymorphisms (SNPs) of arsenic (+ 3 oxidation state) methyltransferase (AS3MT) gene are related to capacity of arsenic methylation. In this paper, we investigated the association of five SNPs (rs7085104, rs3740390, 3740393, rs10748835, and rs1046778) in AS3MT with arsenic methylation metabolizing using the data and samples from a cross-sectional case-control study of arsenic and Type 2 diabetes mellitus conducted in Shanxi, China. A total of 340 individuals were included in the study. Urinary total arsenic (tAs, μg/L) was detected by liquid chromatography-atomic fluorescence spectrometry (LC-AFS). According to "safety guidance value of urinary arsenic for population" as specified in WS/T665-2019 (China), participants were divided into the control group (tAs ≤ 32 μg/L, n = 172) and arsenic-exposed group (tAs > 32 μg/L, n = 168). iAs%, MMA%, and DMA% are as the indicator of arsenic methylation capacity. The genotypes of AS3MT SNPs were examined by Multiple PCR combined sequencing. Linear regression analysis showed that AG + GG genotype in rs7085104 was associated with decreased iAs% and increased DMA%. Moreover, AG + AA genotype in rs10748835 and TC + CC genotype in rs1046778 were associated with decreased iAs% and MMA% and increased DMA%. The interaction between rs7085104 and arsenic is associated with iAs% and DMA%. The interaction of rs3740390 and rs10748835 with arsenic is associated with iAs%. Haplotype CTAC (rs3740393-rs3740390-rs10748835-rs1046778) was associated with lower iAs% and higher DMA%, but this association disappeared after adjusting for age, gender, drink, smoking, BMI and tAs. Haplotype GCAC was associated with decreased MMA%. Our study provides additional support for revealing the factors influencing the metabolic capacity of arsenic methylation and might be helpful to identify the population susceptible to arsenic exposure through individualized screening in the future.

Association between Heavy Metals, Metalloids and Metabolic Syndrome: New Insights and Approaches

Metabolic syndrome (MetS) is an important public health issue that affects millions of people around the world and is growing to pandemic-like proportions. This syndrome is defined by the World Health Organization (WHO) as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Moreover, the etiology of MetS is multifactorial, involving many environmental factors, including toxicant exposures. Several studies have associated MetS with heavy metals exposure, which is the focus of this review. Environmental and/or occupational exposure to heavy metals are a major risk, contributing to the development of chronic diseases. Of particular note, toxic metals such as mercury, lead, and cadmium may contribute to the development of MetS by altering oxidative stress, IL-6 signaling, apoptosis, altered lipoprotein metabolism, fluid shear stress and atherosclerosis, and other mechanisms. In this review, we discuss the known and potential roles of heavy metals in MetS etiology as well as potential targeted pathways that are associated with MetS. Furthermore, we describe how new approaches involving proteomic and transcriptome analysis, as well as bioinformatic tools, may help bring about an understanding of the involvement of heavy metals and metalloids in MetS.

Arsenic in Drinking Water and Diabetes

Arsenic is ubiquitous in soil and water environments and is consistently at the top of the Agency for Toxic Substances Disease Registry (ATSDR) substance priority list. It has been shown to induce toxicity even at low levels of exposure. One of the major routes of exposure to arsenic is through drinking water. This review presents current information related to the distribution of arsenic in the environment, the resultant impacts on human health, especially related to diabetes, which is one of the most prevalent chronic diseases, regulation of arsenic in drinking water, and approaches for treatment of arsenic in drinking water for both public utilities and private wells. Taken together, this information points out the existing challenges to understanding both the complex health impacts of arsenic and to implementing the treatment strategies needed to effectively reduce arsenic exposure at different scales.

Associations of arsenic exposure with blood pressure and platelet indices in pregnant women: A cross-sectional study in Wuhan, China

BACKGROUND

Environmental inorganic arsenic (iAs) exposure is potentially related to abnormal blood pressure (BP) changes and abnormal platelet activation. However, limited epidemiological studies have explored the impacts of iAs exposure on platelet change mediated by BP, especially for pregnant women.

OBJECTIVES

Our purpose was to investigate the associations of arsenic exposure with blood pressure and platelet indices among pregnant women.

METHODS

The present study population included 765 pregnant women drawn from a prospective birth cohort study in Wuhan, China, recruited between October 2013 and April 2016. Urine sampled in the second trimester were used to assess arsenic species concentrations. The relative distribution of urinary arsenic species was used to measure human methylation capacity. BP parameters and platelet indices originated from the medical record. We applied multivariable linear regression models to explore the cross-sectional relationships between urinary arsenic metabolites, BP parameters, and platelet indices. We utilized mediation analysis to investigate the impacts of arsenic exposure on platelet indices through BP as mediator variables.

RESULTS

We observed significant positive correlations between iAs and systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP). Pregnant women with higher methylation capacity to metabolize iAs characterized by higher secondary methylation index (SMI) and total methylation index (TMI) had a more significant reduction in SBP, DBP, and MAP. Pregnant women with higher DBP and MAP had higher platelet counts (PLC). A decreased PLC was found in subjects wither higher SMI. Additionally, SMI was negatively linked to PLC mediated through MAP.

CONCLUSIONS

Obtained results suggested that higher methylation capacity to metabolize iAs might contribute to decreased PLC among pregnant women, and MAP might mediate the influence of SMI on PLC.

Arsenic exposure promotes the emergence of cardiovascular diseases

A large number of studies conducted in the past decade 2010-2020 refer to the impact of arsenic (As) exposure on cardiovascular risk factors. The arsenic effect on humans is complex and mainly depends on the varying individual susceptibilities, its numerous toxic expressions and the variation in arsenic metabolism between individuals. In this review we present relevant data from studies which document the association of arsenic exposure with various biomarkers, the effect of several genome polymorphisms on arsenic methylation and the underling molecular mechanisms influencing the cardiovascular pathology. The corresponding results provide strong evidence that high and moderate-high As intake induce oxidative stress, inflammation and vessel endothelial dysfunction that are associated with increased risk for cardiovascular diseases (CVDs) and in particular hypertension, myocardial infarction, carotid intima-media thickness and stroke, ventricular arrhythmias and peripheral arterial disease. In addition, As exposure during pregnancy implies risks for blood pressure abnormalities among infants and increased mortality rates from acute myocardial infarction during early adulthood. Low water As concentrations are associated with increased systolic, diastolic and pulse pressure, coronary heart disease and incident stroke. For very low As concentrations the relevant studies are few. They predict a risk for myocardial infarction, stroke and ischemic stroke and incident CVD, but they are not in agreement regarding the risk magnitude.

Metals and risk of incident metabolic syndrome in a prospective cohort of midlife women in the United States

Exposure to metals may contribute to the development of metabolic syndrome (MetS); however, evidence from midlife women who are at greater risk of cardiometabolic disease is limited. We assessed the associations of 15 urinary metal concentrations with incident MetS in a prospective cohort of midlife women in the United States. The study population included 947 White, Black, Chinese and Japanese women, aged 45-56 years, free of MetS at baseline (1999-2000), who participated in the Study of Women's Health Across the Nation Multi-Pollutant Study. Fifteen metals were detected in almost all participants urine samples using inductively coupled plasma mass spectrometry at the baseline. Incident MetS was identified annually through 2017 as having at least three of the following five components: high blood pressure, impaired fasting glucose, abdominal obesity, high triglycerides, and poor high-density lipoprotein cholesterol. We used the Cox proportional hazards models to investigate the associations between individual metals and MetS incidence. The adjusted hazard ratios (HR) (95% CI) for MetS in associations with each doubling of urinary metal concentration were 1.14 (1.08, 1.23) for arsenic, 1.14 (1.01, 1.29) for cobalt, and 1.20 (1.06, 1.37) for zinc. We further evaluated the associations between metal mixtures and MetS using the elastic net penalized Cox model and summarized the results into the environmental risk score (ERS). Arsenic, barium, cobalt, copper, nickel, antimony, thallium, and zinc had positive weights, and cadmium, cesium, mercury, molybdenum, lead, and tin had negative weights in the construction of the ERS. The adjusted HR of MetS comparing 75th vs. 25th percentiles of the ERS was 1.45 (1.13, 1.87). These findings support the view that arsenic, cobalt, zinc, as well as metal mixtures, might influence the risks of incident MetS in midlife women.

Intrauterine exposure of mice to arsenite induces abnormal and transgenerational glycometabolism

The adverse, transgenerational effects on health caused by environmental pollutants are receiving increasing attention. For humans and mice, inorganic arsenic (iAs), a widespread environmental contaminant, is associated with diabetic phenotypes. However, the transgenerational effects of arsenite-induced changes in glucose metabolism in mice have not been fully investigated. In the present study, F0 pregnant mice were exposed to arsenite via drinking water (0, 0.5, 5, or 50 ppm NaAsO₂) from gestational day 0 (GD0) until parturition. We examined the effects of arsenite exposure on the metabolic phenotypes and the levels of proteins and genes related to glucose metabolism of dams and their offspring (F1∼F4). Arsenite exposure altered the glucose tolerance of offspring. Notably, glucose transporter-2 (GLUT2) and insulin receptor substrate-1 (IRS1), which are related to the maintenance of glucose homeostasis, were also changed. The homeostasis assessment-insulin resistance (HOMA-IR), an indicator of insulin resistance, was higher in the offspring from the F0 female mice exposed to arsenite. Furthermore, imprinted genes, insulin-like growth factor 2 (IGF2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1), related to glycometabolism across multiple generations, were lower in the offspring. In sum, arsenite exposure during pregnancy transgenerationally affects glucose metabolism, which is related to altered levels of IGF2 and KCNQ1.

Is Arsenic Exposure a Risk Factor for Metabolic Syndrome? A Review of the Potential Mechanisms

Exposure to arsenic in drinking water is a worldwide health problem. This pollutant is associated with increased risk of developing chronic diseases, including metabolic diseases. Metabolic syndrome (MS) is a complex pathology that results from the interaction between environmental and genetic factors. This condition increases the risk of developing type 2 diabetes, cardiovascular diseases, and cancer. The MS includes at least three of the following signs, central obesity, impaired fasting glucose, insulin resistance, dyslipidemias, and hypertension. Here, we summarize the existing evidence of the multiple mechanisms triggered by arsenic to developing the cardinal signs of MS, showing that this pollutant could contribute to the multifactorial origin of this pathology.

Associations between rice consumption, arsenic metabolism, and insulin resistance in adults without diabetes

Rice consumption is an important source of arsenic exposure. Little has known about the impact of rice consumption on arsenic metabolism, which is related to insulin resistance. In this study, we examined the associations between rice consumption and arsenic metabolism, and between arsenic metabolism and insulin resistance in non-diabetic U.S adults who participated in the National Health and Nutrition Examination Survey (NHANES) 2003-2016. Rice consumer was defined as ≥0.25 cups of cooked rice/day. HOMA2-IR was calculated using HOMA2 Calculator software based on participant's fasting glucose and insulin values. Urinary arsenic concentrations below limits of detection were imputed first, and then arsenic metabolism (the proportions of inorganic arsenic (iAs), monomethylarsonate (MMA), and dimethylarsinate (DMA) to their sum) were calculated (expressed as iAs%, MMA%, and DMA%). Using the leave-one-out approach, rice consumers compared with non-consumers had a 1.71% (95% CI: 1.12%, 2.29%) higher DMA% and lower MMA% when iAs% fixed; a 1.55% (95% CI: 0.45%, 2.66%) higher DMA% and lower iAs% when MMA% fixed; and a 1.62% (95% CI: 0.95%, 2.28%) higher iAs% and lower MMA% when DMA% fixed, in multivariable adjustment models. With every 10% decrease in MMA%, the geometric mean ratio of HOMA2-IR was 1.06 (95% CI: 1.03,1.08) and 1.05 (95% CI: 1.02, 1.09) when DMA% and iAs% was fixed, respectively; however, the associations were attenuated after adjusting for body mass index. In stratified analysis, we found that lower MMA% was associated with higher HOMA2-IR in participants with obesity: a 10% increase in iAs% with a 10% decrease in MMA% was associated with higher HOMA2-IR with the geometric mean ratio of 1.05 (95% CI: 1.01, 1.09). Our findings suggest that rice consumption may contribute to lower MMA% that was further associated with higher insulin resistance, especially in individuals with obesity. Future prospective studies are needed to confirm our results in different populations.

Relationship between urinary heavy metals with metabolic syndrome and its components in population from Hoveyzeh cohort study: A case-control study in Iran

BACKGROUND

The incidence of Metabolic Syndrome (MetS) has been growing rapidly and is rising to pandemic proportions. Although obesity is a primary risk factor for the enhancement of these conditions, not all obese individuals develop metabolic syndrome, indicating that the risk for developing MetS is impacted by other genetic and/or environmental factors such as heavy metals. Therefore, the present study focused on the association between exposures to heavy metal and MetS.

METHODS

Urine samples were collected from 150 participants (75 patients with MetS and 75 healthy participants), which were used from Hoveyzeh Cohort center. To make a quantitative comparison between the two groups, Man-Whitney nonparametric test was used. The logistic regression was performed adjusted for age, demographic, lifestyle factor, physical activity, occupational history and urine creatinine.

RESULTS

The results of logistic regression showed that OR and 95 % CI for Cd, Pb, Sr, As and Fe concentration were still significant after adjusting for urine creatinine. Moreover, there was a relationship between Cd and Pb levels and waist circumstance (WC). After adjusting for urine creatinine, age, sex, occupation, smoking status, education and place of residence, only Pb concentration was showed a significant association with systolic blood pressure (SBP). The subjects with high urine level of Cd had the high odds (OR: 6.273; 95 % Cl: 1.783-22.070) of MetS and low high-density lipoprotein (HDL-C). The relationship between As concentration and high fasting blood sugars confirmed the previous evidence suggesting that high As level can cause diabetes.

CONCLUSION

These results indicated that outbreak of MetS and its component are associated with heavy metal concentrations in urine.

Nutrition, one-carbon metabolism and arsenic methylation

Exposure to arsenic (As) is a major public health concern globally. Inorganic As (InAs) undergoes hepatic methylation to form monomethyl (MMAs)- and dimethyl (DMAs)-arsenical species, facilitating urinary As elimination. MMAsIII is considerably more toxic than either InAsIII or DMAsV, and a higher proportion of MMAs in urine has been associated with risk for a wide range of adverse health outcomes. Efficiency of As methylation differs substantially between species, between individuals, and across populations. One-carbon metabolism (OCM) is a biochemical pathway that provides methyl groups for the methylation of As, and is influenced by folate and other micronutrients, such as vitamin B12, choline, betaine and creatine. A growing body of evidence has demonstrated that OCM-related micronutrients play a critical role in As methylation. This review will summarize observational epidemiological studies, interventions, and relevant experimental evidence examining the role that OCM-related micronutrients have on As methylation, toxicity of As, and risk for associated adverse health-related outcomes. There is fairly robust evidence supporting the impact of folate on As methylation, and some evidence from case-control studies indicating that folate nutritional status influences risk for As-induced skin lesions and bladder cancer. However, the potential for folate to be protective for other As-related health outcomes, and the potential beneficial effects of other OCM-related micronutrients on As methylation and risk for health outcomes are less well studied and warrant additional research.

Association between body mass index and arsenic methylation in three studies of Bangladeshi adults and adolescents

BACKGROUND

Water-borne arsenic (As) exposure is a global health problem. Once ingested, inorganic As (iAs) is methylated to mono-methyl (MMA) and dimethyl (DMA) arsenicals via one-carbon metabolism (OCM). People with higher relative percentage of MMA (MMA%) in urine (inefficient As methylation), have been shown to have a higher risk of cardiovascular disease and several cancers but appear to have a lower risk of diabetes and obesity in populations from the US, Mexico, and Taiwan. It is unknown if this opposite pattern with obesity is present in Bangladesh, a country with lower adiposity and higher As exposure in drinking water.

OBJECTIVE

To characterize the association between body mass index (BMI) and As methylation in Bangladeshi adults and adolescents participating in the Folic Acid and Creatine Trial (FACT); Folate and Oxidative Stress (FOX) study; and Metals, Arsenic, and Nutrition in Adolescents Study (MANAS).

METHODS

Arsenic species (iAs, MMA, DMA) were measured in urine and blood. Height and weight were measured to calculate BMI. The associations between concurrent BMI with urine and blood As species were analyzed using linear regression models, adjusting for nutrients involved in OCM such as choline. In FACT, we also evaluated the prospective association between weight change and As species.

RESULTS

Mean BMIs were 19.2/20.4, 19.8/21.0, and 17.7/18.7 kg/m2 in males/females in FACT, FOX, and MANAS, respectively. BMI was associated with As species in female but not in male participants. In females, after adjustment for total urine As, age, and plasma folate, the adjusted mean differences (95% confidence) in urinary MMA% and DMA% for a 5 kg/m2 difference in BMI were -1.21 (-1.96, -0.45) and 2.47 (1.13, 3.81), respectively in FACT, -0.66 (-1.56, 0.25) and 1.43 (-0.23, 3.09) in FOX, and -0.59 (-1.19, 0.02) and 1.58 (-0.15, 3.30) in MANAS. The associations were attenuated after adjustment for choline. Similar associations were observed with blood As species. In FACT, a 1-kg of weight increase over 2 to 10 (mean 5.4) years in males/females was prospectively associated with mean DMA% that was 0.16%/0.19% higher.

DISCUSSION

BMI was negatively associated with MMA% and positively associated with %DMA in females but not males in Bangladesh; associations were attenuated after plasma choline adjustment. These findings may be related to the role of body fat on estrogen levels that can influence one-carbon metabolism, e.g. by increasing choline synthesis. Research is needed to determine whether the associations between BMI and As species are causal and their influence on As-related health outcomes.

Associations between metabolic syndrome and four heavy metals: A systematic review and meta-analysis

Four most concerned heavy metal pollutants, arsenic, cadmium, lead, and mercury may share common mechanisms to induce metabolic syndrome (MetS). However, recent studies exploring the relationships between MetS and metal exposure presented inconsistent findings. We aimed to clarify the relationship between heavy metal exposure biomarkers and MetS using a meta-analysis and systematic review approach. Literature search was conducted in international and the Chinese national databases up to June 2020. Of selected studies, we extracted the relevant data and evaluated the quality of each study's methodology. We then calculated the pooled effect sizes (ESs), standardized mean differences (SMDs), and their 95% confidence intervals (CIs) using a random-effect meta-analysis approach followed by stratification analyses for control of potential confounders. Involving 55,536 participants, the included 22 articles covered 52 observational studies reporting ESs and/or metal concentrations on specific metal and gender. Our results show that participants with MetS had significantly higher levels of heavy metal exposure [pooled ES = 1.16, 95% CI: 1.09, 1.23; n = 42, heterogeneity I2 = 75.6%; and SMD = 0.22, 95% CI: 0.15, 0.29; n = 32, I2 = 94.2%] than those without MetS. Pooled ESs in the subgroups stratified by arsenic, cadmium, lead, and mercury were 1.04 (95% CI: 0.97, 1.10; n = 8, I2 = 61.0%), 1.10 (0.95, 1.27; 11, 45.0%), 1.21 (1.00, 1.48; 12, 82.9%), and 1.26 (1.06, 1.48; 11, 67.7%), respectively. Pooled ESs in the subgroups stratified by blood, urine, and the other specimen were 1.22 (95% CI: 1.08, 1.38; n = 26, I2 = 75.8%), 1.06 (1.00, 1.13; 14, 58.1%), and 2.41 (1.30, 4.43; 2, 0.0%), respectively. In conclusion, heavy metal exposure was positively associated with MetS. Further studies are warranted to examine the effects of individual metals and their interaction on the relationship between MetS and heavy metals.

Interactions of arsenic metabolism with arsenic exposure and individual factors on diabetes occurrence: Baseline findings from Arsenic and Non-Communicable disease cohort (AsNCD) in China

The interaction between arsenic metabolism and potential modifiers on the risk of diabetes is unclear. This research aimed to investigate arsenic metabolism and diabetes prevalence and to identify the interactive effects of arsenic metabolism with some risk factors on diabetes in a Chinese population. A baseline cross-sectional survey was performed in two areas with groundwater arsenic contamination in China. Arsenic levels in water and arsenic metabolites in urine were analyzed. The proportions of each arsenic metabolite (inorganic arsenic [iAs%], monomethylarsonic acid [MMA%], and dimethylarsinic acid [DMA%]) were computed to evaluate arsenic metabolism. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between arsenic and diabetes. Interaction on the additive scale between arsenic methylation index and effect modifier was evaluated by calculating the relative excess risk due to interaction (RERI). Compared with participants in the lower tertile of MMA%, participants in the middle and upper tertiles of MMA% were less prone to diabetes (OR: 0.47 and 0.31, respectively). However, participants in the upper tertiles of urinary DMA% (OR: 3.18) were more likely to have diabetes than those participants in the lower tertiles. The stratified analyses revealed that a one-unit increase in DMA% was associated with higher odds of diabetes in females (OR: 1.06, 95% CI: 1.01, 1.11), older people (OR: 1.05, 95% CI: 1.00, 1.10), and subjects with body mass index (BMI) under 25 kg/m² (OR: 1.07, 95% CI: 1.01, 1.14). The additive interactions between DMA% and female gender (RERI: 0.40, 95% CI: 0.01, 11.88), DMA% and age (RERI: 0.02, 95% CI: 0.01, 8.85), as well as DMA% and BMI (RERI: 0.49, 95% CI: 0.01, 9.62), were statistically significant. In conclusion, efficient arsenic metabolism is associated with higher odds of diabetes. Urinary DMA% and individual factors interact to synergistically influence diabetes occurrence in the Chinese population.

Joint effects of genomic markers and urinary methylation capacity associated with inorganic arsenic metabolism on the occurrence of cancers among residents in arseniasis-endemic areas: A cohort subset with average fifteen-year follow-up

Background

Chronic exposure to inorganic arsenic results in many cancers in susceptible persons. The metabolism of inorganic arsenic and genomic susceptibility are thought to be associated with cancer occurrence.

Methods

This study aims to examine the interaction of genomic susceptibility markers and urinary methylation capacity indicators involved in inorganic arsenic metabolism with all-cancer occurrence. This study conducted a follow-up on 96 residents to determine their urinary inorganic arsenic metabolites and genomic assay from an arseniasis area. Among them, 24 cancer developed. Multivariable Cox proportional hazards model was used to determine and estimate the candidate independent variables for cancer development.

Results

The residents with high inorganic arsenic exposure, high primary methylation index (PMI; MMA/InAs) (but lower secondary methylation index (SMI)), and non-heterogeneity type of genomic markers, including GSTO1, AS3MT, and MPO, tend to develop cancers. Subjects with higher PMI are at higher risk of developing cancers (HR = 1.66; 95% CI = 1.30–2.12). Cancer occurrence was greater among the CC type of GSTO1 (HR = 3.33; 95% CI = 1.11–10.00), CC type of AS3MT (HR = 19.21; 95% CI = 1.16–318.80), and AA type of MPO (HR = 13.40; 95% CI = 1.26–142.40). After adjusting confounders, a mutually moderating effect was revealed between genomic markers and methylation capacity on cancer occurrence.

Conclusions

This study found the hypermethylation responses to inorganic arsenic exposure and an array of genomic markers may increase the susceptibility of a wide range of organ cancers. The findings indicated a high-risk arsenic-exposed population to develop cancers. The phenotype of arsenic metabolism and genomic polymorphism suggested a potential preventive strategy for arsenic carcinogenesis.

Association between urinary metals levels and metabolic phenotypes in overweight and obese individuals

Epidemiologic studies suggest that circulating metals from the natural environment are linked with cardiometabolic health. However, few studies examined the relationship between multiple metals exposure and metabolic phenotypes, especially in obese individuals. We conducted a cross-sectional study to explore the association between 23 urinary metals and metabolic phenotypes in 1392 overweight and obese individuals (592 males, 800 females, mean age 43.1 ± 9.8 years). Participants were classified as metabolically unhealthy if they had ≥2 of the following metabolic abnormalities: elevated blood pressure, elevated fasting blood glucose, elevated triglycerides, and reduced high-density lipoprotein cholesterol. Odds ratios (ORs) of unhealthy metabolic phenotypes for metal levels categorized into tertiles were assessed using logistic regression models. Five metals (barium, copper, iron, uranium, and zinc) were associated with unhealthy metabolic phenotypes in single-metal models, while in the multiple-metal model, only zinc and zinc-copper ratio remained significant. The ORs (95% CIs) comparing extreme tertiles were 2.57 (1.69, 3.89) for zinc and 1.68 (1.24, 2.27) for zinc-copper ratio after adjustment for confounders (both p-trends were <0.001). The numbers of metabolic abnormalities significantly increased with the levels of zinc and the zinc-copper ratio increased. Similar associations were observed with metabolic syndrome risk. High levels of urinary zinc were positively associated with elevated fasting blood glucose (p-trend < 0.001) and elevated triglycerides (p-trend = 0.003). The results suggest that urinary zinc and zinc-copper ratio are positively associated with increased risk of unhealthy metabolic phenotype. Further prospective studies with a larger sample size are required to verify these findings.

Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices

Previous studies have revealed associations between heavy metals and extensive health problems. However, the association between heavy metals and metabolic problems remains poorly defined. This study aims to investigate relationships between heavy metals and metabolic syndrome (MetS), lipid accumulation product (LAP), visceral adiposity index (VAI), and anthropometric indices, including body roundness index (BRI), conicity index (CI), body adiposity index (BAI), and abdominal volume index (AVI). We conducted a health survey of people living in southern Taiwan. Six heavy metals were measured: lead (Pb) in blood and nickel (Ni), chromium (Cr), manganese (Mn), arsenic (As), and copper (Cu) in urine. A total of 2444 participants (976 men and 1468 women) were enrolled. MetS was defined according to the Adult Treatment Panel III for Asians. Multivariable analysis showed that participants with high urine Ni (log per 1 μg/L; odds ratio (OR): 1.193; 95% confidence interval (CI): 1.019 to 1.397; p = 0.028) and high urine Cu (log per 1 μg/dL; OR: 3.317; 95% CI: 2.254 to 4.883; p < 0.001) concentrations were significantly associated with MetS. There was a significant trend of a stepwise increase in blood Pb and urine Ni, As, and Cu according to the number of MetS components (from 0 to 5, a linear p ≤ 0.002 for trend). For the determinants of indices, urine Cu was positively correlated with LAP, BRI, CI, and VAI; blood Pb was positively correlated with BRI, BAI, and AVI; urine Ni was positively correlated with LAP. High urine Cu and urine Ni levels were significantly associated with MetS, and there was a significant trend for stepwise increases in blood Pb and urine Ni, As, and Cu, accompanied by an increasing number of MetS components. Furthermore, several indices were positively correlated with urine Cu, urine Ni, and blood Pb.

Factors Affecting Arsenic Methylation in Contaminated Italian Areas

Chronic arsenic (As) exposure is a critical public health issue. The As metabolism can be influenced by many factors. The objective of this study is to verify if these factors influence As metabolism in four Italian areas affected by As pollution. Descriptive analyses were conducted on 271 subjects aged 20-49 in order to assess the effect of each factor considered on As methylation. Percentages of metabolites of As in urine, primary and secondary methylation indexes were calculated as indicators for metabolic capacity. The results indicate that women have a better methylation capacity (MC) than men, and drinking As-contaminated water from public aqueducts is associated with poorer MC, especially in areas with natural As pollution. In areas with anthropogenic As pollution occupational exposure is associated with a higher MC while smoking with a poorer MC. Dietary habits and genetic characteristics are probably implicated in As metabolism. BMI, alcohol consumption and polymorphism of the AS3MT gene seem not to influence As MC. Arsenic metabolism may be affected by various factors and in order to achieve a comprehensive risk assessment of As-associated disease, it is crucial to understand how these factors contribute to differences in As metabolism.

Evaluation of different types of arsenic methylation and its relationship with metabolic syndrome in an area chronically exposed to arsenic

Evidence suggests that the relationship between arsenic metabolism and diseases, including metabolic syndrome, is complex. The aim of this study was to evaluate the different types of arsenic methylation and its association with metabolic syndrome in an arsenic endemic area. A cross-sectional study was conducted on 132 subjects from Shahid-Abad Village, Qazvin province, Iran (arsenic endemic area). Demographic characteristics, metabolic syndrome, and urinary arsenic species, including iAs (inorganic arsenic), MMA (monomethylarsonic acid), and DMA (dimethylarsinic acid) were measured for all patients and their relationship was analyzed by appropriate statistical methods. In this study, 34.5% of the participants had metabolic syndrome. The decrease in %MMA, increase in %DMA and increase in secondary methylation index (DMA/MMA) were associated with increased risk of metabolic syndrome (p<0.05). We did not find any association between the incidence of metabolic syndrome with primary methylation index (MMA/iAs) and %iAs (p>0.05). This study showed that the prevalence of metabolic syndrome was significantly higher in people with metabolic syndrome than in the general population. A closer examination revealed that the secondary methylation index is related to the metabolic syndrome and its components. Given the higher prevalence of cardiovascular disease and diabetes in patients with metabolic syndrome, it is necessary to change the pathogenesis of the disease using comprehensive management methods for decreasing patient complications.

The relationship between PNP, GSTO-1, AS3MT and ADRB3 gene polymorphisms and urinary arsenic concentration among copper smelter and refinery employers

INTRODUCTION

The aim of this study was to assess the relationship between polymorphisms of genes encoding enzymes involved in arsenic metabolism and urinary arsenic concentration in people occupationally exposed to arsenic.

MATERIALS AND METHODS

The data from 113 employers directly exposed to lead, cadmium, and arsenic in copper smelter in Legnica and Glogow were collected. Urinary arsenic concentration was measured. In addition, blood level of cadmium, lead, and zinc protoporphyrins was assayed. Genetic analyses included polymorphism of PNP (rs 1130650), GSTO-1 (rs 4925), AS3MT (rs 11191439), and ADRB3 (rs4994) genes.

RESULTS

Individuals occupationally exposed to arsenic compounds, who have allele T in homozygous constellation in locus rs 1130650 of PNP gene, are predisposed to lower urinary arsenic concentration, while AA homozygosity in locus rs 4925 of GSTO-1 gene may result in statistically significant higher urinary arsenic concentration. Polymorphisms of AS3MT and ADRB3 genes showed no statistically significant correlation with urinary arsenic, however, there was a tendency to higher arsenic concentration in allele A carriers in locus rs4994 of ADRB3 gene and in allele T carriers in rs 11191439 of AS3MT gene.

CONCLUSION

This study indicates that arsenic absorption and metabolism depend on polymorphisms of genes encoding PNP and GSTO-1. Individuals with disadvantageous constellation of polymorphisms are more susceptible to harmful effects of arsenic exposure.

Polymorphisms in arsenic (+ 3 oxidation state) methyltransferase (AS3MT) predict the occurrence of hyperleukocytosis and arsenic metabolism in APL patients treated with As2O3

Polymorphisms in arsenic (+ 3 oxidation state) methyltransferase (AS3MT) have been shown to be related to interindividual variations in arsenic metabolism and to influence adverse health effects in acute promyelocytic leukemia (APL) patients treated with arsenic trioxide (As₂O₃). The occurrence of hyperleukocytosis with As₂O₃ treatment seriously affects the early survival rate of APL patients, but no definite explanation for such a complication has been clearly established. To clarify the causes of this situation, AS3MT polymorphisms 14215 (rs3740390), 14458 (rs11191439), 27215 (rs11191446), and 35991 (rs10748835) and profiles of plasma arsenic metabolites were evaluated in a group of 54 newly diagnosed APL patients treated with single-agent As₂O₃. High-performance liquid chromatography-hydride generation-atomic fluorescence spectrometry (HPLC-HG-AFS) was used to determine the concentrations of plasma arsenic metabolites. Plasma arsenic methylation metabolism capacity was evaluated by the percentage of inorganic arsenic (iAs), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), primary methylation index (PMI, MMA/iAs), and secondary methylation index (SMI, DMA/MMA). The results showed that APL patients who developed hyperleukocytosis had a higher plasma iAs%, but a lower MMA% and PMI than those who did not develop hyperleukocytosis during As₂O₃ treatment. In addition, patients with the AS3MT 14215 (rs3740390) CC genotype had significantly higher plasma iAs% and incidence of hyperleukocytosis, but lower PMI than patients with the CT + TT genotype. Conversely, we did not observe statistically significant associations between the occurrence of hyperleukocytosis and AS3MT 14458 (rs11191439), 27215 (rs11191446), and 35991 (rs10748835) polymorphisms in our study subjects. These results indicated that AS3MT 14215 (rs3740390) might be used as an indicator for predicting the occurrence of hyperleukocytosis in APL patients treated with As₂O₃.

The association of tryptophan and phenylalanine are associated with arsenic-induced skin lesions in a Chinese population chronically exposed to arsenic via drinking water: a case-control study

OBJECTIVES

We investigated the association of specific serum amino acids (AAs) with the odds of arsenic-induced skin lesions (AISL) and their ability to distinguish patients with AISL from people chronically exposed to arsenic.

DESIGN

Case-control study.

SETTING

Three arsenic-exposed villages in Wuyuan County, Hetao Plain, Inner Mongolia, China were evaluated.

PARTICIPANTS

Among the 450 residents aged 18-79 years, who were chronically exposed to arsenic via drinking water, 56 were diagnosed as having AISL (defined as cases). Another 56 participants without AISL, matched by gender and age (±1 year) from the same population, were examined as controls.

MAIN OUTCOME MEASURES AND METHODS

AA levels were determined by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabolomics analysis. Potential confounding variables were identified via a standardised questionnaire and clinical examination. Multivariable conditional logistic regression model and receiver operating characteristic curve analyses were performed to investigate the relationship between specific AAs and AISL.

RESULTS

Tryptophan and phenylalanine levels were negatively associated with AISL (p<0.05). Compared with that in the first quartile, the adjusted OR of AISL in the second, third and fourth quartiles were decreased by 44%, 88% and 79% for tryptophan and 30%, 80% and 80% for phenylalanine, respectively. The combination of these two higher-level AAs showed the lowest OR for AISL (OR=0.08; 95% CI 0.02 to 0.25; p<0.001). Furthermore, both AAs showed a moderate ability to distinguish patients with AISL from the control, with the area under the curve (AUC; 95% CI) as 0.67 (0.57 to 0.77) for tryptophan and 0.70 (0.60 to 0.80) for phenylalanine (p<0.05). The combined pattern with AUC (95% CI) was 0.72 (0.62 to 0.81), showing a sensitivity of 76.79% and specificity of 58.93% (p<0.001).

CONCLUSIONS

Specific AAs may be linked to AISL and play important roles in early AISL identification.

TRIAL REGISTRATION NUMBER

NCT02235948.

Differential metabolism of inorganic arsenic in mice from genetically diverse Collaborative Cross strains

Mice have been frequently used to study the adverse effects of inorganic arsenic (iAs) exposure in laboratory settings. Like humans, mice metabolize iAs to monomethyl-As (MAs) and dimethyl-As (DMAs) metabolites. However, mice metabolize iAs more efficiently than humans, which may explain why some of the effects of iAs reported in humans have been difficult to reproduce in mice. In the present study, we searched for mouse strains in which iAs metabolism resembles that in humans. We examined iAs metabolism in male mice from 12 genetically diverse Collaborative Cross (CC) strains that were exposed to arsenite in drinking water (0.1 or 50 ppm) for 2 weeks. Concentrations of iAs and its metabolites were measured in urine and livers. Significant differences in total As concentration and in proportions of total As represented by iAs, MAs, and DMAs were observed between the strains. These differences were more pronounced in livers, particularly in mice exposed to 50 ppm iAs. In livers, large variations among the strains were found in percentage of iAs (15-48%), MAs (11-29%), and DMAs (29-66%). In contrast, DMAs represented 96-99% of total As in urine in all strains regardless of exposure. Notably, the percentages of As species in urine did not correlate with total As concentration in liver, suggesting that the urinary profiles were not representative of the internal exposure. In livers of mice exposed to 50 ppm, but not to 0.1 ppm iAs, As3mt expression correlated with percent of iAs and DMAs. No correlations were found between As3mt expression and the proportions of As species in urine regardless of exposure level. Although we did not find yet a CC strain in which proportions of As species in urine would match those reported in humans (typically 10-30% iAs, 10-20% MAs, 60-70% DMAs), CC strains characterized by low %DMAs in livers after exposure to 50 ppm iAs (suggesting inefficient iAs methylation) could be better models for studies aiming to reproduce effects of iAs described in humans.

Targeted metabolomics to understand the association between arsenic metabolism and diabetes-related outcomes: Preliminary evidence from the Strong Heart Family Study

BACKGROUND

Inorganic arsenic exposure is ubiquitous and both exposure and inter-individual differences in its metabolism have been associated with cardiometabolic risk. A more efficient arsenic metabolism profile (lower MMA%, higher DMA%) has been associated with reduced risk for arsenic-related health outcomes. This profile, however, has also been associated with increased risk for diabetes-related outcomes.

OBJECTIVES

The mechanism behind these conflicting associations is unclear; we hypothesized the one-carbon metabolism (OCM) pathway may play a role.

METHODS

We evaluated the influence of OCM on the relationship between arsenic metabolism and diabetes-related outcomes (HOMA2-IR, waist circumference, fasting plasma glucose) using metabolomic data from an OCM-specific and P180 metabolite panel measured in plasma, arsenic metabolism measured in urine, and HOMA2-IR and FPG measured in fasting plasma. Samples were drawn from baseline visits (2001-2003) in 59 participants from the Strong Heart Family Study, a family-based cohort study of American Indians aged ≥14 years from Arizona, Oklahoma, and North/South Dakota.

RESULTS

In unadjusted analyses, a 5% increase in DMA% was associated with higher HOMA2-IR (geometric mean ratio (GMR)= 1.13 (95% CI: 1.03, 1.25)) and waist circumference (mean difference=3.66 (0.95, 6.38). MMA% was significantly associated with lower HOMA2-IR and waist circumference. After adjustment for OCM-related metabolites (SAM, SAH, cysteine, glutamate, lysophosphatidylcholine 18.2, and three phosphatidlycholines), associations were attenuated and no longer significant.

CONCLUSIONS

These preliminary results indicate that the association of lower MMA% and higher DMA% with diabetes-related outcomes may be influenced by OCM status, either through confounding, reverse causality, or mediation.

Arsenic, one carbon metabolism and diabetes-related outcomes in the Strong Heart Family Study

BACKGROUND

Inorganic arsenic exposure and inter-individual differences in its metabolism have been associated with cardiometabolic risk. A more efficient arsenic metabolism profile (lower MMA%, higher DMA%) has been associated with reduced risk for arsenic-related health outcomes; however, this profile has also been associated with increased risk for diabetes-related outcomes. The mechanism behind these contrasting associations is equivocal; we hypothesized one carbon metabolism (OCM) may play a role.

METHODS

We evaluated the association between OCM-related variables (nutrient intake and genetic variants) and both arsenic metabolism biomarkers (iAs%, MMA% and DMA%) and diabetes-related outcomes (metabolic syndrome, diabetes, HOMA2-IR and waist circumference) in 935 participants free of prevalent diabetes and metabolic syndrome from the Strong Heart Family Study, a family-based prospective cohort comprised of American Indian tribal members aged 14+ years.

RESULTS

Of the 935 participants free of both diabetes and metabolic syndrome at baseline, 279 (29.8%) developed metabolic syndrome over a median of 5.3 years of follow-up and of the 1458 participants free of diabetes at baseline, 167 (11.3%) developed diabetes over follow-up. OCM nutrients were not associated with arsenic metabolism, however, higher vitamin B₆ was associated with diabetes-related outcomes (higher HOMA2-IR and increased risk for diabetes and metabolic syndrome). A polymorphism in an OCM-related gene, methionine synthase (MTR), was associated with both higher MMA% (β = 2.57, 95% CI: 0.22, 4.92) and lower HOMA2-IR (GMR = 0.79, 95% CI = 0.66, 0.93 per 5 years of follow-up). Adjustment for OCM variables did not affect previously reported associations between arsenic metabolism and diabetes-related outcomes; however, the association between the MTR variant and diabetes-related outcomes were attenuated after adjustment for arsenic metabolism.

CONCLUSIONS

Our findings suggest MMA% may be a partial mediator in the association between OCM and diabetes-related outcomes. Additional mediation analyses with longer follow-up period are needed to confirm this finding. Further research is needed to determine whether excess B vitamin intake is associated with increased risk for diabetes-related outcomes.

The Association of Arsenic Exposure and Arsenic Metabolism With the Metabolic Syndrome and Its Individual Components: Prospective Evidence From the Strong Heart Family Study

Inorganic arsenic exposure is ubiquitous, and both exposure and interindividual differences in its metabolism have been associated with cardiometabolic risk. However, the associations of arsenic exposure and arsenic metabolism with the metabolic syndrome (MetS) and its individual components are relatively unknown. We used Poisson regression with robust variance to evaluate the associations of baseline arsenic exposure (urinary arsenic levels) and metabolism (relative percentage of arsenic species over their sum) with incident MetS and its individual components (elevated waist circumference, elevated triglycerides, reduced high-density lipoprotein cholesterol, hypertension, and elevated fasting plasma glucose) in 1,047 participants from the Strong Heart Family Study, a prospective family-based cohort study in American Indian communities (baseline visits were held in 1998-1999 and 2001-2003, follow-up visits in 2001-2003 and 2006-2009). Over the course of follow-up, 32% of participants developed MetS. An interquartile-range increase in arsenic exposure was associated with a 1.19-fold (95% confidence interval: 1.01, 1.41) greater risk of elevated fasting plasma glucose concentration but not with other individual components of the MetS or MetS overall. Arsenic metabolism, specifically lower percentage of monomethylarsonic acid and higher percentage of dimethylarsinic acid, was associated with higher risk of overall MetS and elevated waist circumference but not with any other MetS component. These findings support the hypothesis that there are contrasting and independent associations of arsenic exposure and arsenic metabolism with metabolic outcomes which may contribute to overall diabetes risk.

Comparison of arsenic methylation capacity and polymorphisms of arsenic methylation genes between bladder cancer and upper tract urothelial carcinoma

Arsenic exposure is an environmental risk factor for urothelial carcinoma (UC). The natural history of upper tract urothelial carcinoma (UTUC) differs from that of bladder cancer (BC). However, the risk factors of BC and UTUC are not exactly the same and should be discussed separately. The aims of this study were to evaluate 1) the association between arsenic methylation capacity and UTUC and/or BC, separately, and 2) the association between polymorphisms of the arsenic metabolism-related genes AS3MT, GSTOs, and PNP against BC and/or UTUC, separately. We conducted a hospital-based study and collected 216 BC and 212 UTUC cases, and 813 healthy controls, from September 2007 to October 2011. Urinary arsenic profiles were measured using high-performance liquid chromatography-hydride generator-atomic absorption spectrometry. The polymorphisms of AS3MT, GSTO, and PNP were identified using the Sequenom MassARRAY platform with iPLEX Gold chemistry. We found that inefficient arsenic methylation capacity was associated with BC in a significant dose-response relationship, but only found that high urinary total arsenic concentration was related to the risk of UTUC, also in a significant dose-response manner. Those with a total urinary arsenic level of > 30.28 μg/L compared to ≤ 9.78 μg/L, had a odds ratio (OR), and 95% confidence interval (CI) of UTUC, of 4.80 (2.22-10.39). The polymorphisms of AS3MT rs11191438, AS3MT rs10748835, and AS3MT rs1046778 were related to the risk of BC and UTUC, while the polymorphisms of AS3MT rs3740393, AS3MT rs11191453, and AS3MT rs11191454 were associated with arsenic methylation capacity. The AS3MT gene polymorphisms and arsenic methylation capacity appear to independently affect the risk of BC and UTUC.

Nutritional Influences on One-Carbon Metabolism: Effects on Arsenic Methylation and Toxicity

Exposure to inorganic arsenic (InAs) via drinking water and/or food is a considerable worldwide problem. Methylation of InAs generates monomethyl (MMAs^III+V)- and dimethyl (DMAs^III+V)-arsenical species in a process that facilitates urinary As elimination; however, MMAs is considerably more toxic than either InAs or DMAs. Emerging evidence suggests that incomplete methylation of As to DMAs, resulting in increased MMAs, is associated with increased risk for a host of As-related health outcomes. The biochemical pathway that provides methyl groups for As methylation, one-carbon metabolism (OCM), is influenced by folate and other micronutrients, including choline and betaine. Individuals and species differ widely in their ability to methylate As. A growing body of research, including cell-culture, animal-model, and epidemiological studies, has demonstrated the role of OCM-related micronutrients in As methylation. This review examines the evidence that nutritional status and nutritional interventions can influence the metabolism and toxicity of As, with a primary focus on folate.

Shielding effect of anethole against arsenic induced genotoxicity in cultured human peripheral blood lymphocytes and effect of GSTO1 polymorphism

Chronic exposure of inorganic arsenic compounds is responsible for the manifestation of various tumours as well as other diseases. The principal mechanism behind arsenic toxicity is the induction of a strong oxidative stress with production of free radicals in cells. The present study was aimed to explore the shielding effect of anethole against oxidative damage induced by arsenic in cultured human peripheral blood lymphocytes and the effect of GSTO1 polymorphism. Sister chromatid exchange (SCE) frequency, comet tail moment and lipid peroxidation levels were used as biomarkers to assess the oxidative damage. Heparinised venous blood was collected from healthy individuals and treated with sodium arsenite (50 µM) in the presence of anethole (25 and 50 µM) for the analysis of shielding effect of anethole. For the genotyping of GSTO1, PCR RFLP method was adopted. A significant dose-dependent increase in the frequency of SCEs, tail moment and lipid peroxidation levels, was observed when lymphocytes were treated with sodium arsenite. Anethole in combination with sodium arsenite has shown a dose-dependent significant decrease in the frequency of SCEs, tail moment and lipid peroxidation levels. Genetic polymorphism of GSTO1 was found to effect individual susceptibility towards arsenic-mediated genotoxicity and was found insignificant when antigenotoxic effect of anethole was considered. GSTO1 mutant genotypes were found to have significant higher genotoxicity of sodium arsenite as compared to wild-type genotype. The results of the present study suggest ameliorative effects of anethole against arsenic-mediated genotoxic damage in cultured human peripheral blood lymphocytes. A significant effect of GSTO1 polymorphism was observed on genotoxicity of sodium arsenite.

Individual susceptibility to arsenic-induced diseases: the role of host genetics, nutritional status, and the gut microbiome

Arsenic (As) contamination in water or food is a global issue affecting hundreds of millions of people. Although As is classified as a group 1 carcinogen and is associated with multiple diseases, the individual susceptibility to As-related diseases is highly variable, such that a proportion of people exposed to As have higher risks of developing related disorders. Many factors have been found to be associated with As susceptibility. One of the main sources of the variability found in As susceptibility is the variation in the host genome, namely, polymorphisms of many genes involved in As transportation, biotransformation, oxidative stress response, and DNA repair affect the susceptibility of an individual to As toxicity and then influence the disease outcomes. In addition, lifestyles and many nutritional factors, such as folate, vitamin C, and fruit, have been found to be associated with individual susceptibility to As-related diseases. Recently, the interactions between As exposure and the gut microbiome have been of particular concern. As exposure has been shown to perturb gut microbiome composition, and the gut microbiota has been shown to also influence As metabolism, which raises the question of whether the highly diverse gut microbiota contributes to As susceptibility. Here, we review the literature and summarize the factors, such as host genetics and nutritional status, that influence As susceptibility, and we also present potential mechanisms of how the gut microbiome may influence As metabolism and its toxic effects on the host to induce variations in As susceptibility. Challenges and future directions are also discussed to emphasize the importance of characterizing the specific role of these factors in interindividual susceptibility to As-related diseases.

Arsenic Methylation Capacity and Metabolic Syndrome in the 2013-2014 U.S. National Health and Nutrition Examination Survey (NHANES)

Arsenic methylation capacity is associated with metabolic syndrome and its components among highly exposed populations. However, this association has not been investigated in low to moderately exposed populations. Therefore, we investigated arsenic methylation capacity in relation to the clinical diagnosis of metabolic syndrome in a low arsenic exposure population. Additionally, we compared arsenic methylation patterns present in our sample to those of more highly exposed populations. Using logistic regression models adjusted for relevant biological and lifestyle covariates, we report no association between increased arsenic methylation and metabolic syndrome in a population in which arsenic is regulated at 10 ppb in drinking water. However, we cannot rule out the possibility of a positive association between arsenic methylation and metabolic syndrome in a subsample of women with normal body mass index (BMI). To our knowledge this is the first investigation of arsenic methylation capacity with respect to metabolic syndrome in a low exposure population. We also report that methylation patterns in our sample are similar to those found in highly exposed populations. Additionally, we report that gender and BMI significantly modify the effect of arsenic methylation on metabolic syndrome. Future studies should evaluate the effectiveness of arsenic policy enforcement on subclinical biomarkers of cardiovascular disease.

Dietary B Vitamin Intake Is Associated with Lower Urinary Monomethyl Arsenic and Oxidative Stress Marker 15-F2t-Isoprostane among New Hampshire Adults

Background: Arsenic exposure has been associated with an increased risk of cardiovascular disease (CVD). Growing evidence suggests that B vitamins facilitate arsenic metabolism and may protect against arsenic toxicity. However, to our knowledge, few studies have evaluated this in US populations.Objective: Our objective was to examine whether higher B vitamin intake is associated with enhanced arsenic metabolism and lower concentrations of preclinical markers of CVD among New Hampshire adults.Methods: We used weighted quantile sum (WQS) regression to evaluate the collective impact of 6 dietary B vitamins (thiamin, riboflavin, folate, niacin, and vitamins B-6 and B-12) on 1) the proportion of arsenic metabolites in urine and 2) 6 CVD-related markers [including urinary 15-F_2t-isoprostane (15-F_2t-IsoP)] among 418 participants (26-75 y of age) from the New Hampshire Health Study. Contributions of arsenic metabolites to B vitamin-CVD marker associations were also explored in structural equation models.Results: In WQS models, the weighted sum of B vitamin intakes from food sources was inversely associated with the proportion of monomethyl arsenic species in urine (uMMA) (β: -1.03; 95% CI: -1.91, -0.15; P = 0.02). Thiamin and vitamins B-6 and B-12 contributed the most to this association, whereas riboflavin had a negligible effect. Higher overall B vitamin intake was also inversely associated with 15-F_2t-IsoP (β: -0.21; 95% CI: -0.32, -0.11; P < 0.01), with equal contributions from the 6 B vitamins, which was partially explained by differences in the proportion of uMMA (indirect effect β: -0.01; 95% CI: -0.04, -0.00).Conclusions: Among New Hampshire adults, higher intakes of certain B vitamins (particularly thiamin and vitamins B-6 and B-12 from food sources) may reduce the proportion of uMMA, an intermediate of arsenic metabolism that has been associated with an increased risk of CVD. Higher overall B vitamin intake may also reduce urinary 15-F_2t-IsoP, a marker of oxidative stress and potential risk factor for CVD, in part by reducing the proportion of uMMA.

The role of cadmium in obesity and diabetes

Multiple studies have shown an association between environmental exposure to hazardous chemicals including toxic metals and obesity, diabetes, and metabolic syndrome. At the same time, the existing data on the impact of cadmium exposure on obesity and diabetes are contradictory. Therefore, the aim of the present work was to review the impact of cadmium exposure and status on the risk and potential etiologic mechanisms of obesity and diabetes. In addition, since an effect of cadmium exposure on incidence of diabetes mellitus and insulin resistance was suggested by several epidemiologic studies, we carried out a meta-analysis of all studies assessing risk of prevalence and incidence of diabetes. By comparing the highest versus the lowest cadmium exposure category, we found a high risk of diabetes incidence (odds ratio=1.38, 95% confidence interval 1.12-1.71), which was higher for studies using urine as exposure assessment. On the converse, results of epidemiologic studies linking cadmium exposure and overweight or obesity are far less consistent and even conflicting, also depending on differences in exposure levels and the specific marker of exposure (blood, urine, hair, nails). In turn, laboratory studies demonstrated that cadmium adversely affects adipose tissue physiopathology through several mechanisms, thus contributing to increased insulin resistance and enhancing diabetes. However, intimate biological mechanisms linking Cd exposure with obesity and diabetes are still to be adequately investigated.

The Association of Arsenic Metabolism with Cancer, Cardiovascular Disease, and Diabetes: A Systematic Review of the Epidemiological Evidence

BACKGROUND

The available evidence on the role of arsenic metabolism in individual susceptibility to the development of cancer, cardiovascular disease, and diabetes has not been formally and comprehensively reviewed.

OBJECTIVES

Our goal was to systematically investigate the association of arsenic metabolism with cancer, cardiovascular disease, and diabetes-related outcomes in epidemiologic studies. As a secondary objective, we characterized the variation of arsenic metabolism in different populations worldwide.

METHODS

We searched Medline/PubMed and EMBASE from inception to January 2016 and applied predetermined exclusion criteria. Compositional data analysis was used to describe the distribution of arsenic metabolism biomarkers and evaluate the association between arsenic exposure and metabolism.

RESULTS

Twenty-eight studies met the inclusion criteria, 12 on cancer, nine on cardiovascular disease, and seven on diabetes-related outcomes. The median (interquartile range) for mean iAs%, MMA%, and DMA% was 11.2 (7.8-14.9)%, 13.0 (10.4-13.6)%, and 74.9 (69.8-80.0)%, respectively. Findings across studies suggested that higher arsenic exposure levels were associated with higher iAs% and lower DMA% and not associated with MMA%. For cancer, most studies found a pattern of higher MMA% and lower DMA% associated with higher risk of all-site, urothelial, lung, and skin cancers. For cardiovascular disease, higher MMA% was generally associated with higher risk of carotid atherosclerosis and clinical cardiovascular disease but not with hypertension. For diabetes-related outcomes, the pattern of lower MMA% and higher DMA% was associated with higher risk of metabolic syndrome and diabetes.

CONCLUSIONS

Population level of iAs% and DMA%, but not MMA%, were associated with arsenic exposure levels. Overall, study findings suggest that higher MMA% was associated with an increased risk of cancer and cardiovascular disease, while lower MMA% was associated with an increased risk of diabetes and metabolic syndrome. Additional population-based studies and experimental studies are needed to further evaluate and understand the role of arsenic exposure in arsenic metabolism and the role of arsenic metabolism in disease development. https://doi.org/10.1289/EHP577.

Knockout of arsenic (+3 oxidation state) methyltransferase is associated with adverse metabolic phenotype in mice: the role of sex and arsenic exposure

Susceptibility to toxic effects of inorganic arsenic (iAs) depends, in part, on efficiency of iAs methylation by arsenic (+3 oxidation state) methyltransferase (AS3MT). As3mt-knockout (KO) mice that cannot efficiently methylate iAs represent an ideal model to study the association between iAs metabolism and adverse effects of iAs exposure, including effects on metabolic phenotype. The present study compared measures of glucose metabolism, insulin resistance and obesity in male and female wild-type (WT) and As3mt-KO mice during a 24-week exposure to iAs in drinking water (0.1 or 1 mg As/L) and in control WT and As3mt-KO mice drinking deionized water. Results show that effects of iAs exposure on fasting blood glucose (FBG) and glucose tolerance in either WT or KO mice were relatively minor and varied during the exposure. The major effects were associated with As3mt KO. Both male and female control KO mice had higher body mass with higher percentage of fat than their respective WT controls. However, only male KO mice were insulin resistant as indicated by high FBG, and high plasma insulin at fasting state and 15 min after glucose challenge. Exposure to iAs increased fat mass and insulin resistance in both male and female KO mice, but had no significant effects on body composition or insulin resistance in WT mice. These data suggest that As3mt KO is associated with an adverse metabolic phenotype that is characterized by obesity and insulin resistance, and that the extent of the impairment depends on sex and exposure to iAs, including exposure to iAs from mouse diet.

Arsenic metabolism and one-carbon metabolism at low-moderate arsenic exposure: Evidence from the Strong Heart Study

B-vitamins involved in one-carbon metabolism (OCM) can affect arsenic metabolism efficiency in highly arsenic exposed, undernourished populations. We evaluated whether dietary intake of OCM nutrients (including vitamins B2, B6, folate (B9), and B12) was associated with arsenic metabolism in a more nourished population exposed to lower arsenic than previously studied. Dietary intake of OCM nutrients and urine arsenic was evaluated in 405 participants from the Strong Heart Study. Arsenic exposure was measured as the sum of iAs, monomethylarsonate (MMA) and dimethylarsenate (DMA) in urine. Arsenic metabolism was measured as the individual percentages of each metabolite over their sum (iAs%, MMA%, DMA%). In adjusted models, increasing intake of vitamins B2 and B6 was associated with modest but significant decreases in iAs% and MMA% and increases in DMA%. A significant interaction was found between high folate and B6 with enhanced arsenic metabolism efficiency. Our findings suggest OCM nutrients may influence arsenic metabolism in populations with moderate arsenic exposure. Stronger and independent associations were observed with B2 and B6, vitamins previously understudied in relation to arsenic. Research is needed to evaluate whether targeting B-vitamin intake can serve as a strategy for the prevention of arsenic-related health effects at low-moderate arsenic exposure.

Genetic and epigenetic mechanisms underlying arsenic-associated diabetes mellitus: a perspective of the current evidence

Chronic exposure to arsenic has been associated with the development of diabetes mellitus (DM), a disease characterized by hyperglycemia resulting from dysregulation of glucose homeostasis. This review summarizes four major mechanisms by which arsenic induces diabetes, namely inhibition of insulin-dependent glucose uptake, pancreatic β-cell damage, pancreatic β-cell dysfunction and stimulation of liver gluconeogenesis that are supported by both in vivo and in vitro studies. Additionally, the role of polymorphic variants associated with arsenic toxicity and disease susceptibility, as well as epigenetic modifications associated with arsenic exposure, are considered in the context of arsenic-associated DM. Taken together, in vitro, in vivo and human genetic/epigenetic studies support that arsenic has the potential to induce DM phenotypes and impair key pathways involved in the regulation of glucose homeostasis.

Mitigating dietary arsenic exposure: Current status in the United States and recommendations for an improved path forward

Inorganic arsenic (iAs) is a well-characterized carcinogen, and recent epidemiologic studies have linked chronic exposures to non-cancer health outcomes, including cardiovascular disease, diabetes, skin lesions and respiratory disorders. Greater vulnerability has been demonstrated with early life exposure for health effects including lung and bladder cancer, immunotoxicity and neurodevelopment. Despite its well-known toxicity, there are important gaps in the regulatory oversight of iAs in food and in risk communication. This paper focuses on the US regulatory framework in relation to iAs in food and beverages. The state of existing regulatory agency toxicological assessments, monitoring efforts, standard setting, intervention policies and risk communication are explored. Regarding the approach for standard setting, risk-based evaluations of iAs in particular foods can be informative but are insufficient to create a numeric criterion, given current uncertainties in iAs toxicology and the degree to which traditional risk targets can be exceeded by dietary exposures. We describe a process for prioritizing dietary exposures for different lifestages and recommend a relative source contribution-based approach to setting criteria for arsenic in prioritized foods. Intervention strategies begin with an appropriately set criterion and a monitoring program that documents the degree to which this target is met for a particular food. This approach will promote improvements in food production to lower iAs contamination for those foods which initially do not meet the criterion. Risk communication improvements are recommended to ensure that the public has reliable information regarding sources and alternative dietary choices. A key recommendation is the consideration of meal frequency advice similar to what is currently done for contaminants in fish. Recent action level determinations by FDA for apple juice and infant rice cereal are evaluated and used as illustrations of how our recommended approach can further the goal of exposure mitigation from key sources of dietary iAs in the US.

Dose-Response Relationship between Inorganic Arsenic Exposure and Lung Cancer among Arseniasis Residents with Low Methylation Capacity

Background: Exposure to inorganic arsenic (InAs) has been documented as a risk factor for lung cancer. This study examined the association between InAs exposure, its metabolism, and lung cancer occurrence.Methods: We followed 1,300 residents from an arseniasis area in Taiwan, determined urinary InAs metabolites, and identified 39 lung cancer cases. Cox proportional hazards model was performed.Results: The results demonstrated that participants with either the primary methylation index [monomethylarsonic acid (MMA)/InAs] or the secondary methylation index [dimethylarsenic acid (DMA)/MMA] lower than their respective median values were at a higher risk of lung cancer (HRs from 3.41 to 4.66) than those with high methylation capacity. The incidence density of lung cancer increased from 79.9/100,000 (year^-1) to 467.4/100,000 (year^-1) for residents with low methylation capacity and from 0 to 158.5/100,000 (year^-1) for residents with high methylation capacity when the arsenic exposure dose increased from 2 to 10 ppb to ≥200 ppb, respectively. The analyses revealed a dose-response relationship between lung cancer occurrence and increasing arsenic concentrations in drinking water as well as cumulative arsenic exposure (monotonic trend test; P < 0.05 and P < 0.05, respectively) among the residents with low methylation capacity. The relationship between arsenic exposure and lung cancer among high methylators was not statistically significant.Conclusions: Hypomethylation responses to InAs exposure may dose dependently increase lung cancer occurrence.Impact: The high-risk characteristics observed among those exposed should be considered in future preventive medicine and research on arsenic carcinogenesis. Cancer Epidemiol Biomarkers Prev; 26(5); 756-61. ©2016 AACR.

Factors Affecting Arsenic Methylation in Arsenic-Exposed Humans: A Systematic Review and Meta-Analysis

Chronic arsenic exposure is a critical public health issue in many countries. The metabolism of arsenic in vivo is complicated because it can be influenced by many factors. In the present meta-analysis, two researchers independently searched electronic databases, including the Cochrane Library, PubMed, Springer, Embase, and China National Knowledge Infrastructure, to analyze factors influencing arsenic methylation. The concentrations of the following arsenic metabolites increase (p< 0.000001) following arsenic exposure: inorganic arsenic (iAs), monomethyl arsenic (MMA), dimethyl arsenic (DMA), and total arsenic. Additionally, the percentages of iAs (standard mean difference (SMD): 1.00; 95% confidence interval (CI): 0.60–1.40; p< 0.00001) and MMA (SMD: 0.49; 95% CI: 0.21–0.77; p = 0.0006) also increase, while the percentage of DMA (SMD: −0.57; 95% CI: −0.80–−0.31; p< 0.0001), primary methylation index (SMD: −0.57; 95% CI: −0.94–−0.20; p = 0.002), and secondary methylation index (SMD: −0.27; 95% CI: −0.46–−0.90; p = 0.004) decrease. Smoking, drinking, and older age can reduce arsenic methylation, and arsenic methylation is more efficient in women than in men. The results of this analysis may provide information regarding the role of arsenic oxidative methylation in the arsenic poisoning process.

Chronic Exposure to Arsenic and Markers of Cardiometabolic Risk: A Cross-Sectional Study in Chihuahua, Mexico

BACKGROUND

Exposure to arsenic (As) concentrations in drinking water > 150 μg/L has been associated with risk of diabetes and cardiovascular disease, but little is known about the effects of lower exposures.

OBJECTIVE

This study aimed to examine whether moderate As exposure, or indicators of individual As metabolism at these levels of exposure, are associated with cardiometabolic risk.

METHODS

We analyzed cross-sectional associations between arsenic exposure and multiple markers of cardiometabolic risk using drinking-water As measurements and urinary As species data obtained from 1,160 adults in Chihuahua, Mexico, who were recruited in 2008-2013. Fasting blood glucose and lipid levels, the results of an oral glucose tolerance test, and blood pressure were used to characterize cardiometabolic risk. Multivariable logistic, multinomial, and linear regression were used to assess associations between cardiometabolic outcomes and water As or the sum of inorganic and methylated As species in urine.

RESULTS

After multivariable adjustment, concentrations in the second quartile of water As (25.5 to < 47.9 μg/L) and concentrations of total speciated urinary As (< 55.8 μg/L) below the median were significantly associated with elevated triglycerides, high total cholesterol, and diabetes. However, moderate water and urinary As levels were also positively associated with HDL cholesterol. Associations between arsenic exposure and both dysglycemia and triglyceridemia were higher among individuals with higher proportions of dimethylarsenic in urine.

CONCLUSIONS

Moderate exposure to As may increase cardiometabolic risk, particularly in individuals with high proportions of urinary dimethylarsenic. In this cohort, As exposure was associated with several markers of increased cardiometabolic risk (diabetes, triglyceridemia, and cholesterolemia), but exposure was also associated with higher rather than lower HDL cholesterol.

CITATION

Mendez MA, González-Horta C, Sánchez-Ramírez B, Ballinas-Casarrubias L, Hernández Cerón R, Viniegra Morales D, Baeza Terrazas FA, Ishida MC, Gutiérrez-Torres DS, Saunders RJ, Drobná Z, Fry RC, Buse JB, Loomis D, García-Vargas GG, Del Razo LM, Stýblo M. 2016. Chronic exposure to arsenic and markers of cardiometabolic risk: a cross-sectional study in Chihuahua, Mexico. Environ Health Perspect 124:104-111; http://dx.doi.org/10.1289/ehp.1408742.

Serum metabolomics reveals that arsenic exposure disrupted lipid and amino acid metabolism in rats: a step forward in understanding chronic arsenic toxicity

Chronic arsenic exposure through drinking water threatens public health worldwide. Although its multiorgan toxicity has been reported, the impact of chronic arsenic exposure on the metabolic network remains obscure. In this study, male Sprague Dawley rats were exposed to 0.5, 2 or 10 ppm sodium arsenite for three months. An ultra-high performance liquid chromatography/mass spectrometry based metabolomics approach was utilized to unveil the global metabolic response to chronic arsenic exposure in rats. Distinct serum metabolome profiles were found to be associated with the doses. Eighteen differential metabolites were identified, and most of them showed dose-dependent responses to arsenic exposure. Metabolic abnormalities mainly involved lipid metabolism and amino acid metabolism. The metabolic alterations were further confirmed by hepatic gene expression. Expressions of cpt2, lcat, cact, crot and mtr were significantly elevated in high dose groups. This study provides novel evidence to support the association between arsenic exposure and metabolic disruption, and it contributes to understanding the mechanism of chronic arsenic toxicity.

The Genetic Architecture of Arsenic Metabolism Efficiency:A SNP-Based Heritability Study of Bangladeshi Adults

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.

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

BACKGROUND

Oral exposure to inorganic arsenic (iAs) is associated with adverse health effects. Epidemiological studies suggest differences in susceptibility to these health effects, possibly due to genotypic variation. Genetic polymorphisms in iAs metabolism could lead to increased susceptibility by altering urinary iAs metabolite concentrations.

OBJECTIVE

To examine the impact of genotypic polymorphisms on iAs metabolism.

METHODS

We screened 360 publications from PubMed and Web of Science for data on urinary mono- and dimethylated arsenic (MMA and DMA) percentages and polymorphic genes encoding proteins that are hypothesized to play roles in arsenic metabolism. The genes we examined were arsenic (+3) methyltransferase (AS3MT), glutathione-s-transferase omega (GSTO), and purine nucleoside phosphorylase (PNP). Relevant data were pooled to determine which polymorphisms are associated across studies with changes in urinary metabolite concentration.

RESULTS

In our review, AS3MT polymorphisms rs3740390, rs11191439, and rs11191453 were associated with statistically significant changes in percent urinary MMA. Studies of GSTO polymorphisms did not indicate statistically significant associations with methylation, and there are insufficient data on PNP polymorphisms to evaluate their impact on metabolism.

DISCUSSION

Collectively, these data support the hypothesis that AS3MT polymorphisms alter in vivo metabolite concentrations. Preliminary evidence suggests that AS3MT genetic polymorphisms may impact disease susceptibility. GSTO polymorphisms were not associated with iAs-associated health outcomes. Additional data are needed to evaluate the association between PNP polymorphisms and iAs-associated health outcomes. Delineation of these relationships may inform iAs mode(s) of action and the approach for evaluating low-dose health effects for iAs.

CONCLUSIONS

Genotype impacts urinary iAs metabolite concentrations and may be a potential mechanism for iAs-related disease susceptibility.