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

Serum Folate and Vitamin B12 Modify the Associations of N6AMT1 Genetic Variants with Gestational Diabetes Mellitus: A Cross-Sectional Study in Chinese Pregnant Women

Purpose

This study aimed to explore the association between N-6 adenine-specific DNA methyltransferase 1 (N6AMT1) single nucleotide polymorphisms (SNPs) and gestational diabetes mellitus (GDM) and the modification of the relationship by folate and vitamin B12.

Methods

A cross-sectional study involving 1303 pregnant women (262 GDM and 1041 non-GDM) was performed in Tianjin, China. Nine SNPs in N6AMT1 were genotyped, and serum folate, vitamin B12, and homocysteine (Hcy) levels were measured. The logistic regression models determined the odds ratios (ORs) for SNPs in N6AMT1 and the gene-nutrition interactions on GDM.

Results

N6AMT1 rs7282280, rs1048546, and rs1997605 were related to GDM under the dominant model after adjusting for multiple covariates. Individuals carrying the N6AMT1 rs7282280 TC/TT genotypes had a lower risk of developing GDM, regardless of serum folate and vitamin B12 levels. However, rs1048546 TG/GG genotypes were associated with lower GDM risk when serum folate ≥ 6.0 ng/mL. Pregnancies with the risk genotypes in N6AMT1 and higher serum folate or lower vitamin B12 are more prone to GDM. The study also showed a statistically significant additive interaction between N6AMT1 rs1997605 GG genotypes and lower vitamin B12 (RERI: 2.54; 95% CI: 0.17, 4.92).

Conclusion

SNPs in N6AMT1 were found to be associated with GDM, and serum folate and vitamin B12 levels can modify their associations.

Associations of arsenic exposure and arsenic metabolism with the risk of non-alcoholic fatty liver disease

Growing evidences supported that arsenic exposure contributes to non-alcoholic fatty liver disease (NAFLD) risk, but findings were still inconsistent. Additionally, once absorbed, arsenic is methylated into monomethyl and dimethyl arsenicals. However, no studies investigated the association of arsenic metabolism with NAFLD. Our objectives were to evaluate the associations of arsenic exposure and arsenic metabolism with NAFLD prevalence. We conducted a case-control study with 1790 participants derived from Dongfeng-Tongji cohort and measured arsenic species (arsenite, arsenate, monomethylarsonate [MMA], dimethylarsinate [DMA], and arsenobetaine) in urine. Arsenic exposure (∑As) was defined as the sum of inorganic arsenic (iAs), MMA, and DMA. Arsenic metabolism was evaluated as the proportions of inorganic-related species (iAs%, MMA%, and DMA%) and methylation efficiency ratios (primary methylation index [PMI], secondary methylation index [SMI]). NAFLD was diagnosed by liver ultrasound. Logistic regression was used to evaluate the associations. The median of ∑As was 13.24 μg/g creatinine. The ∑As showed positive and nonlinear association with moderate/severe NAFLD (OR: per log-SD = 1.33, 95% CI: [1.03,1.71]; Pfor nonlinearity = 0.021). The iAs% (OR: per SD = 1.16, 95% CI: [1.03,1.30]) and SMI (OR: per log-SD = 1.16, 95% CI: [1.03,1.31]) showed positive while MMA% (OR: per SD = 0.80, 95% CI: [0.70,0.91]) and PMI (OR: per log-SD = 0.86, 95% CI: [0.77,0.96]) showed inverse associations with NAFLD. Moreover, the ORs (95% CI) of NAFLD for each 5% increase in iAs% was 1.36 (1.17,1.58) when MMA% decreased and 1.07 (1.01,1.13) when DMA% decreased; and for each 5% increase in MMA%, it was 0.74 (0.63,0.86) and 0.79 (0.69,0.91) when iAs% and DMA% decreased, respectively. The results suggest that inorganic arsenic exposure is positively associated with NAFLD risk and arsenic methylation efficiency plays a role in the NAFLD. The findings provide clues to explore potential interventions for the prevention of NAFLD. Prospective studies are needed to validate our findings.

Glycemic Changes Related to Arsenic Exposure: An Overview of Animal and Human Studies

BACKGROUND

Arsenic (As) is a risk factor associated with glycemic alterations. However, the mechanisms of action and metabolic aspects associated with changes in glycemic profiles have not yet been completely elucidated. Therefore, in this review, we aimed to investigate the metabolic aspects of As and its mechanism of action associated with glycemic changes.

METHODS

We searched the PubMed (MEDLINE) and Google Scholar databases for relevant articles published in English. A combination of free text and medical subject heading keywords and search terms was used to construct search equations. The search yielded 466 articles; however, only 50 were included in the review.

RESULTS

We observed that the relationship between As exposure and glycemic alterations in humans may be associated with sex, smoking status, body mass index, age, occupation, and genetic factors. The main mechanisms of action associated with changes induced by exposure to As in the glycemic profile identified in animals are increased oxidative stress, reduced expression of glucose transporter type 4, induction of inflammatory factor expression and dysfunction of pancreatic β cells.

CONCLUSIONS

Therefore, As exposure may be associated with glycemic alterations according to inter-individual differences.

Mediating Role of Liver Dysfunction in the Association between Arsenic Exposure and Diabetes in Chinese Adults: A Nationwide Cross-Sectional Study of China National Human Biomonitoring (CNHBM) 2017-2018

Inconsistent results have been reported regarding the association between low-to-moderate arsenic (As) exposure and diabetes. The effect of liver dysfunction on As-induced diabetes remains unclear. The cross-sectional study included 10,574 adults from 2017-2018 China National Human Biomonitoring. Urinary total As (TAs) levels were analyzed as markers of As exposure. Generalized linear mixed models and restricted cubic splines models were used to examine the relationships among TAs levels, serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) concentrations, and diabetes prevalence. Mediating analysis was performed to assess whether liver dysfunction mediated the association between TAs and diabetes. Overall, the OR (95% CI) of diabetes in participants in the second, third, and fourth quartiles of TAs were 1.08 (0.88, 1.33), 1.17 (0.94, 1.45), and 1.52 (1.22, 1.90), respectively, in the fully adjusted models compared with those in the lowest quartile. Serum ALT was positively associated with TAs and diabetes. Additionally, mediation analyses showed that ALT mediated 4.32% of the association between TAs and diabetes in the overall population and 8.86% in the population without alcohol consumption in the past year. This study suggested that alleviating the hepatotoxicity of As could have implications for both diabetes and liver disease.

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.

Urinary arsenic metabolism, genetic susceptibility, and their interaction on type 2 diabetes

Growing studies investigated the association of arsenic metabolism with type 2 diabetes (T2D), however, the epidemiological evidence is inconsistent. In addition, the interaction of arsenic metabolism-related genetic risk score (GRS)-arsenic on T2D risk was unclear. The present study aimed to evaluate the association of arsenic metabolism efficiency [inorganic arsenic (iAs)%, monomethylarsonic acid (MMA)%, and dimethylarsinic acid (DMA%)] with T2D risk. Moreover, the relationship of GRS and arsenic metabolism efficiency and the interaction of GRS-arsenic on T2D were investigated. Age- and sex-matched new-onset diabetes case-control study derived from the Dongfeng-Tongji cohort was conducted and 996 pairs participants were included in this study. The leave-one-out approach was used to evaluate the association of arsenic metabolism efficiency with T2D risk. The GRS and weight GRS (wGRS) were calculated based on 79 candidate SNPs. We estimated the relationship of GRS with arsenic metabolism efficiency by linear regression model. The interaction of GRS-arsenic on T2D was assessed by adding a multiplicative interaction term (GRS × arsenic) in the logistic regression models. Urinary iAs% was positively associated with T2D risk, and the OR (95% CI) was 1.06 (1.01, 1.12). MMA% and PMI were negatively associated with T2D risk, and the ORs (95% CI) were 0.87 (0.78, 0.97) and 0.64 (0.47, 0.86), respectively. Urinary DMA, As3+, and As5+ were positively associated with T2D risk. Similar relationships were found between arsenic metabolites and levels of FPG and HbA1c. Moreover, arsenic metabolism-related GRS/wGRS was positively associated with MMA% but negatively associated with DMA%. Genetic predisposition to arsenic metabolism modified the association of inorganic arsenic with T2D risk (Pinteraction = 0.033). Taken together, lower arsenic primary metabolism efficiency (higher iAs% and lower MMA%) may increase T2D risk. Genetic predisposition to arsenic metabolism was associated with arsenic metabolism efficiency, and might modify the association of inorganic arsenic with T2D risk.

Association between Arsenic Methylation in Early Pregnancy and Gestational Diabetes Mellitus: A Prospective Cohort Study

The metabolism of arsenic (As) plays a crucial role in its health effects. However, the impact of arsenic methylation during early pregnancy on gestational diabetes mellitus (GDM) remains unclear. This study aimed to investigate the associations between As methylation in the first and second trimesters and the incidence of GDM by conducting a prospective cohort study in Chongqing, China. Urine samples from first (n = 131) and second (n = 53) trimester pregnant women were analyzed for arsenite (AsIII), arsenate (AsV), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) concentrations. Logistic regressions assessed associations between the concentrations of As species, methylation indices, and GDM risk. As species concentrations showed no significant differences between GDM and non-GDM groups. Higher MMA% (OR = 1.11; 95% CI = 1.02, 1.22) and lower secondary methylation index (SMI) (OR = 0.81; 95% CI = 0.71, 0.93) correlated with GDM risk, primarily in the first trimester. MMA% decreased and DMA% and SMI increased from the first to the second trimester. Results of stratified analyses revealed these associations in women under 28 or with normal BMIs (18-24 kg/m2). The study underscores inefficient arsenic methylation as a GDM risk, modified by age and BMI, with the first trimester as a critical period.

AS3MT facilitates NLRP3 inflammasome activation by m6A modification during arsenic-induced hepatic insulin resistance

N6-methyladenosine (m6A) messenger RNA methylation is the most widespread gene regulatory mechanism affecting liver functions and disorders. However, the relationship between m6A methylation and arsenic-induced hepatic insulin resistance (IR), which is a critical initiating event in arsenic-induced metabolic syndromes such as type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD), remains unclear. Here, we showed that arsenic treatment facilitated methyltransferase-like 14 (METTL14)-mediated m6A methylation, and that METTL14 interference reversed arsenic-impaired hepatic insulin sensitivity. We previously showed that arsenic-induced NOD-like receptor protein 3 (NLRP3) inflammasome activation contributed to hepatic IR. However, the regulatory mechanisms underlying the role of arsenic toward the post-transcriptional modification of NLRP3 remain unclear. Here, we showed that NLRP3 mRNA stability was enhanced by METTL14-mediated m6A methylation during arsenic-induced hepatic IR. Furthermore, we demonstrated that arsenite methyltransferase (AS3MT), an essential enzyme in arsenic metabolic processes, interacted with NLRP3 to activate the inflammasome, thereby contributing to arsenic-induced hepatic IR. Also, AS3MT strengthened the m6A methylase association with NLRP3 to stabilize m6A-modified NLRP3. In summary, we showed that AS3MT-induced m6A modification critically regulated NLRP3 inflammasome activation during arsenic-induced hepatic IR, and we identified a novel post-transcriptional function of AS3MT in promoting arsenicosis.

An updated systematic review and dose-response meta-analysis on the relation between exposure to arsenic and risk of type 2 diabetes

Arsenic is among the most critical environmental toxicants associated with many human disorders. However, its effect on type 2 diabetes mellitus (T2DM) is contradictory. This systematic review and dose-response meta-analysis aim to update information on the association between arsenic exposure and the risk of T2DM. The sample type (drinking water, urine, blood, and nails) conducted the subgroup analysis. Evaluation of the high vs. low arsenic concentrations showed a significant association between drinking water arsenic (OR: 1.58, 95% CI: 1.20-2.08) and urinary arsenic (OR: 1.37, 95% CI: 1.24-1.51) with the risk of T2DM. The linear dose-response meta-analysis showed that each 1 μg/L increase in levels of drinking water arsenic (OR: 1.01, 95% CI: 1.00-1.01) and urinary arsenic (OR: 1.01, 95% CI: 1.00-1.02) was associated with a 1% increased risk of T2DM. The non-linear dose-response analysis indicated that arsenic in urine was associated with the risk of T2DM (Pnon-linearity<0.001). However, this effect was not statistically significant for arsenic in drinking water (Pnon-linearity=0.941). Our findings suggest that blood arsenic was not significantly linked to the increased risk of T2DM in high vs. low (OR: 1.21, 95% CI: 0.85-1.71), linear (OR: 1.04, 95% CI: 0.99-1.09), and non-linear (Pnon-linearity=0.365) analysis. Also, nail arsenic was not associated with the risk of T2DM in this meta-analysis (OR: 1.33, 95% CI: 0.69-2.59). This updated dose-response meta-analysis indicated that arsenic exposure was significantly correlated with the risk of T2DM.

Arsenic metabolism, N6AMT1 and AS3MT single nucleotide polymorphisms, and their interaction on gestational diabetes mellitus in Chinese pregnant women

BACKGROUND

Single nucleotide polymorphisms (SNPs) in N6AMT1 and AS3MT are associated with arsenic (As) metabolism, and efficient As methylation capacity has been associated with diabetes. However, little is known about the gene-As interaction on gestational diabetes mellitus (GDM).

OBJECTIVE

This study aimed to explore the individual and combined effects of N6AMT1 and AS3MT SNPs with As metabolism on GDM.

METHODS

A cross-sectional study was performed among 385 Chinese pregnant women (86 GDM and 299 Non-GDM). Four SNPs in N6AMT1 (rs1997605 and rs1003671) and AS3MT (rs1046778 and rs11191453) were genotyped. Urinary inorganic arsenic (iAs), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) were determined, and the percentages of As species (iAs%, MMA%, and DMA%) were calculated to assess the efficiency of As metabolism.

RESULTS

Pregnant women with N6AMT1 rs1997605 AA genotype had lower iAs% (B: 2.11; 95% CI: 4.08, -0.13) and MMA% (B: 0.21; 95% CI: 0.39, -0.04) than pregnant women with GG genotype. The AS3MT rs1046778 and rs11191453 C alleles were negatively associated with iAs% and MMA% but positively associated with DMA%. Higher urinary MMA% was significantly associated with a lower risk of GDM (OR: 0.54; 95% CI: 0.30, 0.97). The A allele in N6AMT1 rs1997605 (OR: 0.46; 95% CI: 0.26, 0.79) was associated with a decreased risk of GDM. The additive interactions between N6AMT1 rs1997605 GG genotypes and lower iAs% (AP: 0.50; 95% CI: 0.01, 0.99) or higher DMA% (AP: 0.52; 95% CI: 0.04, 0.99) were statistically significant. Similar additive interactions were also found between N6AMT1 rs1003671 GG genotypes and lower iAs% or higher DMA%.

CONCLUSIONS

Genetic variants in N6AMT1 and efficient As metabolism (indicated by lower iAs% and higher DMA%) can interact to influence GDM occurrence synergistically in Chinese pregnant women.

Critical Overview on Endocrine Disruptors in Diabetes Mellitus

Diabetes mellitus is a major public health problem in all countries due to its high human and economic burden. Major metabolic alterations are associated with the chronic hyperglycemia that characterizes diabetes and causes devastating complications, including retinopathy, kidney failure, coronary disease and increased cardiovascular mortality. The most common form is type 2 diabetes (T2D) accounting for 90 to 95% of the cases. These chronic metabolic disorders are heterogeneous to which genetic factors contribute, but so do prenatal and postnatal life environmental factors including a sedentary lifestyle, overweight, and obesity. However, these classical risk factors alone cannot explain the rapid evolution of the prevalence of T2D and the high prevalence of type 1 diabetes in particular areas. Among environmental factors, we are in fact exposed to a growing amount of chemical molecules produced by our industries or by our way of life. In this narrative review, we aim to give a critical overview of the role of these pollutants that can interfere with our endocrine system, the so-called endocrine-disrupting chemicals (EDCs), in the pathophysiology of diabetes and metabolic disorders.

Inorganic arsenic induces MDM2, p53, and their phosphorylation and affects the MDM2/p53 complex in vitro

Arsenic, as a human carcinogen, has posed a certain threat to environmental health globally. However, the underlying mechanism of the arsenic carcinogenic effect remains largely undetermined. The up-regulation of MDM2 seems to play a crucial part in tumors in especial carcinomas of the diffuse type. The interaction of MDM2 and p53 is closely relevant to the pathogenesis of tumors. In this study, we aimed to investigate the effect on MDM2, p53, and their phosphorylation after As(III). In the epidemiological study, we investigated that MDM2 expression was up-regulation and was positively linked to methylated metabolites (monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA)) after As(III)-exposure. In vitro studies employing A549 and 16HBE cells confirmed the epidemiological data. Studies on MDM2 phosphorylation sites consisting of Ser166, Ser260, and Ser394 in response to arsenic exposure, which have not been studied presently, indicated that As(III) could induce the expression of MDM2 phosphorylation. Moreover, we studied the alterations of p53 and its N-terminus phosphorylation sites of Ser9, Ser15, and Ser33, which demonstrated that p53 and its phosphorylation were highly expressed after As(III) exposure. Subsequently, Co-immunoprecipitation assays validated our hypothesis that the bonding of MDM2 and p53 was altered by arsenic exposure. What's more, outcomes coming from different cell types of A549, 16HBE, and 60 T-16HBE revealed that MDM2 and its phosphorylation expression existed a significant difference. The study provides evidence that As(III) and its methylated metabolites modulate the expression of MDM2, p53, and their phosphorylation and then affect the interaction between MDM2 and p53.

Combined exposure to multiple metals on cardiovascular disease in NHANES under five statistical models

BACKGROUND

It is well-documented that heavy metals are associated with cardiovascular disease (CVD). However, there is few studies exploring effect of metal mixture on CVD. Therefore, the primary objective of present study was to investigate the joint effect of heavy metals on CVD and to identify the most influential metals in the mixture.

METHODS

Original data for study subjects were obtained from the National Health and Nutrition Examination Survey. In this study, adults with complete data on 12 kinds of urinary metals (antimony, arsenic, barium, cadmium, cobalt, cesium, molybdenum, mercury, lead, thallium, tungsten, and uranium), cardiovascular disease, and core covariates were enrolled. We applied five different statistical strategies to examine the CVD risk with metal exposure, including multivariate logistic regression, adaptive elastic net combined with Environmental Risk Score, Quantile g-computation, Weighted Quantile Sum regression, and Bayesian kernel machine regression.

RESULTS

Higher levels of cadmium, tungsten, cobalt, and antimony were significantly associated with Increased risk of CVD when covariates were adjusted for multivariate logistic regression. The results from multi-pollutant strategies all indicated that metal mixture was positively associated with the risk of CVD. Based on the results of multiple statistical strategies, it was determined that cadmium, tungsten, cobalt, and antimony exhibited the strongest positive correlations, whereas barium, lead, molybdenum, and thallium were most associated with negative correlations.

CONCLUSION

Overall, our study demonstrates that exposure to heavy metal mixture is linked to a higher risk of CVD. Meanwhile, this association may be driven primarily by cadmium, tungsten, cobalt, and antimony. Further prospective studies are warranted to validate or refute our primary findings as well as to identify other important heavy metals linked with CVD.

Research for type 2 diabetes mellitus in endemic arsenism areas in central China: role of low level of arsenic exposure and KEAP1 rs11545829 polymorphism

Type 2 diabetes mellitus (T2DM) is one of the major public health problems worldwide; both genetic and environmental factors are its risk factors. Arsenic, an environmental pollutant, might be a risk factor for T2DM, but the association of low-to-moderate level arsenic exposure with the risk of T2DM is still inconsistent. Single nucleotide polymorphisms (SNPs) can affect the development of T2DM, but the study on KEAP1 rs11545829 (G>A) SNP is few. In this paper, we explored the effect of KEAP1 rs11545829 (G>A) SNP and low-to-moderate level arsenic exposure on risk of T2DM in a cross-sectional case-control study conducted in Shanxi, China. Total of 938 participants, including 318 T2DM cases and 618 controls, were enrolled. Blood glycosylated haemoglobin (HbA1c) was detected by Automatic Biochemical Analyzer, and participants with HbA1c≧6.5% were diagnosed as T2DM. Urinary total arsenic (tAs, mg/L), as the indicator of arsenic exposure, was detected by liquid chromatography-atomic fluorescence spectrometry (LC-AFS). Genomic DNA was extracted and the genotypes of KEAP1 rs11545829 SNP were examined by multiplex polymerase chain reaction (PCR). The urinary tAs concentration in recruited participants was 0.075 (0.03-0.15) mg/L, and was associated with an increased risk of T2DM (OR = 8.45, 95% CI 2.63-27.17); rs11545829 mutation homozygote AA genotype had a protective effect on risk of T2DM (OR = 0.42, 95 % CI 0.25-0.73). Although this protective effect of AA genotype was found in participants with higher urinary tAs level (>0.032 mg/L) (OR = 0.48, 95% CI 0.26-0.86), there was no interaction effect for arsenic exposure and rs11545829 SNP on risk of T2DM. In addition, BMI modified the association between rs11545829 SNP and the risk of T2DM (RERI = -1.11, 95% CI -2.18-0.04). The present study suggest that low-to-moderate level arsenic exposure may be a risk factor, while KEAP1 rs11545829 SNP mutation homozygote AA genotype may be a protective factor for risk of T2DM, especially for T2DM patients with urinary tAs level>0.032 mg/L.

Influence of combined exposure levels of total arsenic and inorganic arsenic on arsenic methylation capacity among university students: findings from Bayesian kernel machine regression analysis

The arsenic (As) methylation capacity is an important determinant of susceptibility to As-related diseases. Total As (TAs) or inorganic As (iAs) was reported to associated with As methylation capacity. We measured urinary concentrations of iAs, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) by using HPLC-HG-AFS and calculated the primary methylation capacity index (PMI) and secondary methylation capacity index (SMI) in 209 university students in Hefei, China, a non-As endemic area. Volunteers were given a standardized questionnaire asking about their sociodemographic characteristics. Bayesian kernel machine regression (BKMR) analysis was used to estimate the association of lnTAs and lniAs levels with methylation indices (ln%MMA, ln%DMA, lnPMI, lnSMI). The median concentrations of iAs, MMA, and DMA were 1.22, 0.92, and 12.17 μg/L, respectively; the proportions of iAs, MMA, and DMA were 8.76%, 6.13%, and 84.84%, respectively. Females had higher %DMA and lower %MMA than males. The combined levels of lnTAs and lniAs showed a decrease in the changes in ln%DMA and lnSMI. With regard to the single exposure level, the lnTAs showed positive correlations with ln%DMA, lnPMI, and lnSMI when lniAs was set at a specific level, while lniAs showed negative correlations with ln%DMA, lnPMI, and lnSMI when lnTAs was set at a specific level; all the dose-response relationships were nonlinear. Our results suggested that combined levels of TAs and iAs play an important role in reducing As methylation capacity, especially iAs, and the reduction only occurs when TAs and iAs are present up to a certain combined level.

Associations of Maternal rs1801131 Genotype in MTHFR and Serum Folate and Vitamin B12 with Gestational Diabetes Mellitus in Chinese Pregnant Women

Circumstantial evidence links one-carbon metabolism (OCM) related nutrients, such as folate and vitamin B₁₂, with gestational diabetes mellitus (GDM). However, few studies have evaluated the combined effects of these nutrients with OCM related gene polymorphisms on GDM. This study investigated whether OCM related genetic variants modified the associations of folate and B₁₂ with GDM. Logistic regression was used to estimate odds ratios (ORs) for OCM related nutrients and single nucleotide polymorphisms (SNPs) in genes encoding main OCM related enzymes (MTHFR, MTR, and MTRR) on GDM. Higher folate concentrations were associated with increased GDM risk (OR: 1.59; 95% CI: 1.22, 2.13). However, higher B₁₂ concentrations were associated with reduced GDM risk (OR: 0.76; 95% CI: 0.65, 0.92). Pregnancies with MTHFR rs1801131 G alleles had a significantly lower risk of GDM than pregnancies with T alleles (OR: 0.65; 95% CI: 0.47, 0.91) under the dominant model. The genotype-stratified analysis revealed the association between folate and GDM (OR: 1.66, 95% CI: 1.20, 2.30) or B₁₂ and GDM (OR: 0.80, 95% CI: 0.65, 0.98) was more evident in pregnancies with TT genotype. Higher folate and lower B₁₂ are associated with GDM. Pregnancies with MTHFR rs1801131 TT genotype are more susceptible to OCM nutrient-related GDM.

A review of environmental metabolism disrupting chemicals and effect biomarkers associating disease risks: Where exposomics meets metabolomics

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been elucidated to be important risk factors for metabolic diseases, such as diabetes and obesity. These metabolism-sensitive diseases typically occur when key metabolic and signaling pathways were disrupted, which can be influenced by the exposure to contaminants such as endocrine disrupting chemicals (EDCs), along with genetic and lifestyle factors. This promotes the concept and research on environmental metabolism disrupting chemicals (MDCs). In addition, identifying endogenous biochemical markers of effect linked to disease states is becoming an important tool to screen the biological targets following environmental contaminant exposure, as well as to provide an overview of toxicity risk assessment. As such, the current review aims to contribute to the further understanding of exposome and human health and disease by characterizing environmental exposure and effect metabolic biomarkers. We summarized MDC-associated metabolic biomarkers in laboratory animal and human cohort studies using high throughput targeted and nontargeted metabolomics techniques. Contaminants including heavy metals and organohalogen compounds, especially EDCs, have been repetitively associated with metabolic disorders, whereas emerging contaminants such as perfluoroalkyl substances and microplastics have also been found to disrupt metabolism. In addition, we found major limitations in the effective identification of metabolic biomarkers especially in human studies, toxicological research on the mixed effect of environmental exposure has also been insufficient compared to the research on single chemicals. Thus, it is timely to call for research efforts dedicated to the study of combined effect and metabolic alterations for the better assessment of exposomic toxicology and health risks. Moreover, advanced computational and prediction tools, further validation of metabolic biomarkers, as well as systematic and integrative investigations are also needed in order to reliably identify novel biomarkers and elucidate toxicity mechanisms, and to further utilize exposome and metabolome profiling in public health and safety management.

Environmental arsenic exposure and its contribution to human diseases, toxicity mechanism and management

Arsenic is a well-recognized environmental contaminant that occurs naturally through geogenic processes in the aquifer. More than 200 million people around the world are potentially exposed to the elevated level of arsenic mostly from Asia and Latin America. Many adverse health effects including skin diseases (i.e., arsenicosis, hyperkeratosis, pigmentation changes), carcinogenesis, and neurological diseases have been reported due to arsenic exposure. In addition, arsenic has recently been shown to contribute to the onset of non-communicable diseases, such as diabetes mellitus and cardiovascular diseases. The mechanisms involved in arsenic-induced diabetes are pancreatic β-cell dysfunction and death, impaired insulin secretion, insulin resistance and reduced cellular glucose transport. Whereas, the most proposed mechanisms of arsenic-induced hypertension are oxidative stress, disruption of nitric oxide signaling, altered vascular response to neurotransmitters and impaired vascular muscle calcium (Ca²⁺) signaling, damage of renal, and interference with the renin-angiotensin system (RAS). However, the contributions of arsenic exposure to non-communicable diseases are complex and multifaceted, and little information is available about the molecular mechanisms involved in arsenic-induced non-communicable diseases and also no suitable therapeutic target identified yet. Therefore, in the future, more basic research is necessary to identify the appropriate therapeutic target for the treatment and management of arsenic-induced non-communicable diseases. Several reports demonstrated that a daily balanced diet with proper nutrient supplements (vitamins, micronutrients, natural antioxidants) has shown effective to reduce the damages caused by arsenic exposure. Arsenic detoxication through natural compounds or nutraceuticals is considered a cost-effective treatment/management and researchers should focus on these alternative options. This review paper explores the scenarios of arsenic contamination in groundwater with an emphasis on public health concerns. It also demonstrated arsenic sources, biogeochemistry, toxicity mechanisms with therapeutic targets, arsenic exposure-related human diseases, and onsets of cardiovascular diseases as well as feasible management options for arsenic toxicity.

Joint effect of urinary arsenic species and serum one-carbon metabolism nutrients on gestational diabetes mellitus: A cross-sectional study of Chinese pregnant women

BACKGROUND

Growing evidence indicates that arsenic (As) exposure can increase the risk of gestational diabetes mellitus (GDM). However, little is known about As species and GDM and the combined effect of As and one-carbon metabolism (OCM) on GDM.

OBJECTIVES

We aimed to examine the associations between As species and GDM and evaluate the potential interactions of folate, vitamin B₁₂, and homocysteine (Hcy) with As species on GDM prevalence.

METHOD

We measured levels of arsenite (As³⁺), arsenate (As⁵⁺), dimethylarsinic acid (DMA), and arsenobetaine (AsB) species in urine and folate, vitamin B₁₂, and Hcy in serum from 396 pregnant women in Tianjin, China. The diagnosis of GDM was based on an oral glucose tolerance test. Associations of As species in urine with GDM were evaluated using generalized linear models (GLMs) and Bayesian kernel machine regression (BKMR). Additive interactions of As and OCM with GDM were estimated by determining the relative excess risk due to interaction (RERI).

RESULTS

Of the 396 pregnant women, 89 were diagnosed with GDM. Continuous increases in urinary inorganic As were associated with GDM in the GLMs, with adjusted odds ratios of 2.12 (95% CI: 0.96, 4.71) for As³⁺, and 0.27 (95% CI: 0.07, 0.98) for As⁵⁺. The BKMR in estimating the exposure-response functions showed that As³⁺ and AsB were positively associated with GDM. However, As⁵⁺ showed a negative relationship with GDM. Although the additive interactions between As exposure and OCM indicators were not significant, we found that pregnant women with higher urinary As³⁺ and total As accompanied by lower serum vitamin B₁₂ were more likely to have higher odds of GDM (3.12, 95% CI: 1.32, 7.38 and 3.10, 95% CI: 1.30, 7.38, respectively).

CONCLUSIONS

Our data suggest a positive relation between As³⁺ and GDM but a negative relation between As⁵⁺ and GDM. Potential additive interaction of As and OCM with GDM requires further investigation.

Arsenic Secondary Methylation Capacity Is Inversely Associated with Arsenic Exposure-Related Muscle Mass Reduction

Skeletal muscle mass reduction has been implicated in insulin resistance (IR) that promotes cardiometabolic diseases. We have previously reported that arsenic exposure increases IR concomitantly with the reduction of skeletal muscle mass among individuals exposed to arsenic. The arsenic methylation capacity is linked to the susceptibility to some arsenic exposure-related diseases. However, it remains unknown whether the arsenic methylation capacity affects the arsenic-induced reduction of muscle mass and elevation of IR. Therefore, this study examined the associations between the arsenic methylation status and skeletal muscle mass measures with regard to IR by recruiting 437 participants from low- and high-arsenic exposure areas in Bangladesh. The subjects' skeletal muscle mass was estimated by their lean body mass (LBM) and serum creatinine levels. Subjects' drinking water arsenic concentrations were positively associated with total urinary arsenic concentrations and the percentages of MMA, as well as inversely associated with the percentages of DMA and the secondary methylation index (SMI). Subjects' LBM and serum creatinine levels were positively associated with the percentage of DMA and SMI, as well as inversely associated with the percentage of MMA. HOMA-IR showed an inverse association with SMI, with a confounding effect of sex. Our results suggest that reduced secondary methylation capacity is involved in the arsenic-induced skeletal muscle loss that may be implicated in arsenic-induced IR and cardiometabolic diseases.

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.

Inappropriately sweet: Environmental endocrine-disrupting chemicals and the diabetes pandemic

Afflicting hundreds of millions of individuals globally, diabetes mellitus is a chronic disorder of energy metabolism characterized by hyperglycemia and other metabolic derangements that result in significant individual morbidity and mortality as well as substantial healthcare costs. Importantly, the impact of diabetes in the United States is not uniform across the population; rather, communities of color and those with low income are disproportionately affected. While excessive caloric intake, physical inactivity, and genetic susceptibility are undoubted contributors to diabetes risk, these factors alone fail to fully explain the rapid global rise in diabetes rates. Recently, environmental contaminants acting as endocrine-disrupting chemicals (EDCs) have been implicated in the pathogenesis of diabetes. Indeed, burgeoning data from cell-based, animal, population, and even clinical studies now indicate that a variety of structurally distinct EDCs of both natural and synthetic origin have the capacity to alter insulin secretion and action as well as global glucose homeostasis. This chapter reviews the evidence linking EDCs to diabetes risk across this spectrum of evidence. It is hoped that improving our understanding of the environmental drivers of diabetes development will illuminate novel individual-level and policy interventions to mitigate the impact of this devastating condition on vulnerable communities and the population at large.

Comparative removal of As(V) and Sb(V) from aqueous solution by sulfide-modified α-FeOOH

Efficient elimination of As(V) and Sb(V) from wastewater streams has long been a major challenge. Herein, sulfide-modified α-FeOOH adsorbent was fabricated via a simple sulfidation reaction for removing As(V) and Sb(V) from aqueous media. Compared with the pristine α-FeOOH, sulfide-modified α-FeOOH increased the adsorption of As(V) from 153.8 to 384.6 mg/g, and Sb(V) adsorption from 277.8 to 1111.1 mg/g. The enhanced adsorption of both As(V) and Sb(V) was maintained at the pH range from 2 to 11, and was not interfered by various coexisting anions such as Cl^-, SO₄^2-, NO₃^-, SiO₃^2- and PO₄^3-. The adsorption affinity increased from 0.0047 to 0.0915 and 0.0053 to 0.4091 for As(V) and Sb(V), respectively. X-ray photoelectron spectroscopic investigation demonstrated a reductive conversion of As(V) to As(III) during the adsorption process with sulfide-modified α-FeOOH, but with no obvious variation of Sb(V) speciation. While the removal mechanism for As(V) was reduction followed by adsorption via hydroxyl groups, mainly surface complexation was involved in the removal of Sb(V). This study presented a simple strategy to enhance the adsorption capacity and adsorption affinity of α-FeOOH toward As(V)/Sb(V) via sulfide-modification.