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

Roles of serum uric acid on the association between arsenic exposure and incident metabolic syndrome in an older Chinese population

Growing evidences showed that heavy metals exposure may be associated with metabolic diseases. Nevertheless, the mechanism underlying arsenic (As) exposure and metabolic syndrome (MetS) risk has not been fully elucidated. So we aimed to prospectively investigate the role of serum uric acid (SUA) on the association between blood As exposure and incident MetS. A sample of 1045 older participants in a community in China was analyzed. We determined As at baseline and SUA concentration at follow-up in the Yiwu Elderly Cohort. MetS events were defined according to the criteria of the International Diabetes Federation (IDF). Generalized linear model with log-binominal regression model was applied to estimate the association of As with incident MetS. To investigate the role of SUA in the association between As and MetS, a mediation analysis was conducted. In the fully adjusted log-binominal model, per interquartile range increment of As, the risk of MetS increased 1.25-fold. Compared with the lowest quartile of As, the adjusted relative risk (RR) of MetS in the highest quartile was 1.42 (95% confidence interval, CI: 1.03, 2.00). Additionally, blood As was positively associated with SUA, while SUA had significant association with MetS risk. Further mediation analysis demonstrated that the association of As and MetS risk was mediated by SUA, with the proportion of 15.7%. Our study found higher As was remarkably associated with the elevated risk of MetS in the Chinese older adults population. Mediation analysis indicated that SUA might be a mediator in the association between As exposure and MetS.

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.

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.

Additive interaction of urinary total arsenic concentrations with being overweight/obesity on the risk of insulin resistance: NHANES 2007-2016

Arsenic exposure has been associated with the risk of diabetes or insulin resistance (IR), which are also related with overweight/obesity. This study aimed to explore the interaction between arsenic exposure and being overweight/obesity on diabetes or IR risk. Data from the National Health and Nutrition Examination Survey (NHANES) in cycles 2007-2016 were used to assess the interaction between arsenic exposure and being overweight/obesity on IR or diabetes risk among adults. Urinary total arsenic concentrations (UTAs) were used as a biomarker for arsenic exposure. The homeostasis model of insulin resistance (HOMA-IR) was calculated to index IR. Survey-weighted logistic regression and restricted cubic spline (RCS) analyses were performed to determine the association and dose-response relationship between UTAs and IR or diabetes risk. Additive interaction was evaluated by relative excess risk due to interaction (RERI), attributable proportion of interaction (AP), and synergy index (S). A total of 3,133 participants were included. The median (interquartile range) UTAs were 6.61 (3.83, 13.95) μg/L. The adjusted OR of IR was 1.40 (95% CI: 0.99-1.97) for UTAs, comparing the highest with the lowest quartile. And significant additive interaction was observed between high UTAs and being overweight/obesity on IR risk (RERI = 2.47, 95% CI: 0.30-4.63; AP = 0.29, 95% CI: 0.07-0.50; S = 1.48, 95% CI: 1.03-2.13). Our results suggested that there might be a potential additive interaction between high UTAs with being overweight/obesity on diabetes risk (AP = 0.27, 95%CI: 0.04-0.51). Our results indicated an additive interaction between arsenic exposure and being overweight/obesity on IR risk.

Heavy Metal and Rice in Gluten-Free Diets: Are They a Risk?

A gluten-free diet (GFD) is the treatment of choice for gluten-related disorders. It has been associated with macro- and micronutrient deficiencies. Recently, consumption of arsenic-contaminated rice has raised concern because of the potential greater risk that it may represent for people on GFDs, whose rice consumption is high, since it is a fundamental cereal in GFDs. We reviewed the data published over the last 20 years in Medline and Scielo, in English, French and Spanish, on four metals (As, Hg, Cd, and Pb), to assess whether the evidence suggests that celiac disease or consumption of a GFD is associated with increased levels of blood/urinary metal concentrations. The review revealed a few articles that were directly related to the four metals and their relationships with a GFD. The evidence supports that rice-based products are a relevant source of As and other metals. Clinical studies and evaluations based on NHANES have indicated that persons on GFDs have higher As and Hg blood/urinary levels, suggesting that the diet and not the disease is responsible for it. The levels described are statistically significant compared to those of persons on complete diets, but far from toxic levels. The question of whether higher exposure to heavy metals associated with a GFD is biologically relevant remains unanswered and deserves study.

Micronutrients and heavy metals in rice farms: the case of Ahvaz and Bawie Counties, Khuzestan Province, Iran

This study addressed micronutrients (Fe, Zn, Cu, Mn, Co) and heavy metals (As, Pb) in the soil and rice crop in Khuzestan Province, Iran. Twenty-eight composite soil and grain samples from the intended rice farms were garnered during harvest time. Concentrations of the elements in the samples and in the grains were, respectively, determined by inductively coupled plasma optical emission spectrometry and inductively coupled plasma mass spectrometry device. The average concentration of As, Fe, Co, Cu, Mn, Pb, and Zn in soil of crop were 2.71, 20,065.8, 10.43, 22.28, 422.28, 5.85, and 47.07 mg/kg, respectively. The physicochemical properties of soil, bioconcentration factor, daily intakes, and health risk assessment of the elements were calculated. The results revealed that the area covered by alkaline saline soils is poor in micronutrients. Bioconcentration factor values of all elements were less than 1. Low levels of bioconcentration factor may be for low levels of nutrients in the soil and physicochemical conditions of the soil. Furthermore, the daily intake of Co (adults' group) and Fe and Zn (children group) was very low. Health risk assessment showed only adults are threatened by non-cancerous diseases due to excessive value of all the elements (HI = 2.53) and cancerous diseases caused by excessive As and Pb (2.86E-04 and 2.01E-05, respectively). Considering that Khuzestan Province is the fourth largest producer of rice in Iran, the lack of micronutrients and the presence of heavy metals in rice produced in the study area can adversely affect consumers. Further investigation is therefore a must in the region.

Annexin A1 inhibition facilitates NLRP3 inflammasome activation in arsenic-induced insulin resistance in rat liver

Hepatic insulin resistance (IR) is the primary pathology of type 2 diabetes (T2D). The role of the NOD-like receptor protein 3 (NLRP3) inflammasome in arsenic-induced hepatic IR has been previously demonstrated. However, the mechanism of the arsenic-induced activation of the NLRP3 inflammasome is still unclear. Here, we demonstrate that NaAsO₂ downregulated the mRNA and protein level of Annexin A1 (AnxA1), an anti-inflammatory factor, in rat livers and L-02 cells. Moreover, AnxA1 overexpression significantly alleviated arsenic-induced NLRP3 inflammasome activation and IR in L-02 cells. Importantly, Co-immunoprecipitation (Co-IP) results showed that AnxA1 1-190 peptide could bind to the domain encompassing amino acids 1-210 and 211-550 of NLRP3. In conclusion, our experiments demonstrated that arsenic exposure could activate the NLRP3 inflammasome and IR by inhibiting the AnxA1 activity. These findings suggest that AnxA1 may be a promising therapeutic target of arsenicosis.

Concentrations of blood and urinary arsenic species and their characteristics in general Korean population

Arsenic (As) exposure has been extensively studied by investigating As species (e.g., inorganic arsenic (iAs), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA)) in urine, yet recent research suggests that blood could be a possible biomarker of As exposure. These investigations, however, were conducted on iAs-contaminated areas, and evidence on populations exposed to low levels of iAs is limited. This study aimed to describe the levels and distributions of As species in urine and blood, as well as to estimate methylation efficiency and related factors in the Korean population. Biological samples were obtained by the Korean Ministry of Food and Drug Safety. A total of 2025 urine samples and 598 blood samples were utilized in this study. Six As species were measured using ultra-high-performance liquid chromatography with inductively coupled plasma mass spectrometry (UPLC-ICP-MS): As(V), As(III), MMA, DMA, arsenobetaine (AsB), and arsenocholine (AsC). Multiple linear regression models were used to examine the relationship between As species (concentrations and proportions) and covariates. AsB was the most prevalent species in urine and blood. The relative composition of iAs, MMA, DMA, and AsC in urine and blood differed significantly. Consumption of blue-backed fish was linked to higher levels of AsB in urine and blood. Type of drinking water and multigrain rice consumption were associated with increased iAs concentration in urine. Except for iAs, every species had correlations in urine and blood in both univariate and multivariate analyses. Adolescents and smokers presented a lower methylation efficiency (higher %MMA and lower %DMA in urine) and females presented a higher methylation efficiency (lower %iAs, %MMA, and higher %DMA in urine). In conclusion, blood iAs concentration cannot represent urinary iAs; nonetheless, different compositions of urine and blood might reflect distinct information about iAs exposure. Further investigations on exposure factors and health are needed using low-exposure groups.

Association of urinary arsenic with insulin resistance: Cross-sectional analysis of the National Health and Nutrition Examination Survey, 2015-2016

BACKGROUND

Long-term arsenic exposure is associated with diabetes in adults, the mechanism of which involves insulin resistance. The relationship between arsenic and insulin resistance in adults is unclear. We analyzed the relationship between urinary arsenic and insulin resistance in US adults.

RESULTS

We identified 815 adults aged 20-79 years who participated in the 2015-2016 National Health and Nutrition Examination Survey (NHANES). Urinary arsenic, fasting glucose, serum insulin, and other key covariates were obtained from the NHANES data. The association between urinary arsenic and insulin resistance was evaluated by analyzing the urinary arsenic level and homeostasis model assessment-insulin resistance. The median total urinary arsenic level was 6.82 µg/L. After adjusting for possible confounding factors (gender, age, and body mass index), the 80th and 20th percentile odds ratio (OR) was 1.41 (95% confidence interval [CI] 1.07, 1.87); the OR of the 70th and 30th percentiles was 1.41 (95% CI 1.08, 1.84).

CONCLUSIONS

In most subgroups, after similar adjustment, the relationship between urine total arsenic and insulin resistance remained. Total arsenic exposure in urine may be associated with insulin resistance. Evidence from larger and more adequately powered cohort studies is needed to confirm our results.