Gut microbiota deficiency aggravates arsenic-induced toxicity by affecting bioaccumulation and biotransformation in C57BL/6J mice.

Gut microbiome can influence the arsenic metabolism in mammals. Confusingly, gut microbiome was found to both mitigate and exacerbate arsenic toxicity. In this study, the role of gut microbiota in arsenic bioaccumulation, biotransformation, and organ toxicity in C57BL/6J mice was investigated. Gut microbiota deficiency model was established by antibiotics (Ab) cocktail AVNM. Conventional and gut microbiota deficiency mice were exposed to NaAsO2 for 4 weeks. Comparing with Ab-treated mice, the total arsenic (tAs) in the tissues was significantly reduced in conventional mice, which was opposed to the results of those in feces. Interestingly, dimethyl arsenite (DMA) was the most abundant metabolite in the feces of Ab-treated mice, while arsenic acid (AsV) had the highest proportion in the feces of conventional mice with approximately 16-fold than that in Ab-treated mice, indicating the critical role of gut microbiota in metabolizing arsenious acid (AsIII) to AsV. Additionally, the liver and kidney in Ab-treated mice showed more severe pathological changes and apoptosis. The significant increased level of ionized calcium-binding adapter molecule 1 (IBA-1) was also found in the brains of Ab-treated mice. Our results indicated that gut microbiota protected the host from arsenic-induced toxicity in liver, kidney, and brain by reducing the arsenic accumulation.

Epigenome-wide perspective of cadmium-associated DNA methylation and its mediation role in the associations of cadmium with lipid levels and dyslipidemia risk.

BACKGROUND: Studies demonstrated the associations of cadmium (Cd) with lipid levels and dyslipidemia risk, but the mechanisms involved need further exploration. OBJECTIVES: We aimed to explore the role of DNA methylation (DNAM) in the relationship of Cd with lipid levels and dyslipidemia risk. METHODS: Urinary cadmium levels (UCd) were measured by inductively coupled plasma mass spectrometry, serum high-density lipoprotein (HDL), total cholesterol, triglyceride, and low-density lipoprotein were measured with kits, and DNAM was measured using the Infinium MethylationEPIC BeadChip. Robust linear regressions were conducted for epigenome-wide association study. Multivariate linear and logistic regressions were performed to explore the associations of UCd with lipid levels and dyslipidemia risk, respectively. Mediation analyses were conducted to explore potential mediating role of DNAM in the associations of Cd with lipid levels and dyslipidemia risk. RESULTS: UCd was negatively associated with HDL levels (p = 0.01) and positively associated with dyslipidemia (p < 0.01). There were 92/11 DMPs/DMRs (FDR<0.05) associated with UCd. Cd-associated DNAM and pathways were connected with cardiometabolic diseases and immunity. Cg07829377 (LINC01060) mediated 42.05%/22.88% of the UCd-HDL/UCd-dyslipidemia associations (p = 0.02 and 0.01, respectively). CONCLUSIONS: Cadmium caused site-specific DNAM alterations and the associations of UCd with lipid levels and dyslipidemia risk may be partially mediated by DNAM.

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 of serum phthalates exposure with incident type 2 diabetes risk in Chinese population: A nested case-control study.

Prospective epidemiological evidence was lacking on the association of phthalates (PAEs) exposure with incident type 2 diabetes mellitus (T2DM) risk. In present nested case-control study, we identified 1006 T2DM cases and matched 1006 controls based on Dongfeng-Tongji cohort study, and 6 PAEs were detected in baseline serum. The conditional logistic regression model, Bayesian kernel machine regression (BKMR) model and Quantile-based g-computation were applied to evaluate the associations of determined PAEs, either as individuals or as a mixture, with incident T2DM risk. Subgroup analysis was conducted to identify the potential sensitive population of PAEs effects on T2DM. After multiple adjustment, no statistically significant association was observed between single or mixture of PAEs and incident T2DM risk in the whole population. However, serum levels of Di-n-butyl phthalate (DnBP) [OR= 2.06; 95% CI: (1.11-3.96)], Σdibutyl phthalate (ΣDBP) [OR= 1.96; 95% CI: (1.06-3.76)], and Σlow-molecular- weight phthalate (ΣLMW) [OR= 2.27; 95% CI: (1.17-4.57)] were significantly associated with T2DM in current drinker group. Moreover, significant potential interactions were observed among Di-iso-butyl phthalate (DiBP), DnBP, Butyl-benzyl phthalate (BBP), ΣDBP, and ΣLMW with drinking status on T2DM risk (P for interaction = 0.036, 0.005, 0.049. 0.010, and 0.005). We did not find significant associations between serum PAEs levels and T2DM in the whole population. However, current alcohol drinkers expose to higher levels of DnBP, ΣDBP, and ΣLMW had higher risk of T2DM.