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Background: Metabolic syndrome severity, expressed by the continuous metabolic syndrome risk score (MetS score), has been demonstrated to be able to predict future health conditions. However, little is known about the association between MetS score and renal function. Methods: A total of 22,719 participants with normal renal function abstracted from the Kailuan Study were followed from 2006 to 2016. The new onset of chronic kidney disease (CKD) was defined as eGFR <60 ml/min per 1.73 m2 and/or proteinuria >300 mg/dl. Progressive decline in renal function was defined as an annual change rate of eGFR below the 10th percentile of the whole population. Results: In the multivariate‐adjusted model, we found that the risk of progressive decline in renal function increased consistently with the MetS score, with an odds ratio of 1.49 (95% CI, 1.28, 1.73) for those subjects>75th percentile compared with those <25th percentile. Additionally, a high MetS score was found to be associated with an increased risk of CKD, with a hazard ratio of 1.53 (95% CI, 1.33, 1.78) for subjects >75th percentile compared with those <25th percentile. Conclusions: Our findings suggested that the MetS score was associated with an increased risk of a progressive decline in renal function and was also a strong and independent risk factor for the development of CKD. These findings provide evidence of the potential clinical utility of the MetS score for assessing metabolic syndrome severity to detect the risk of decreased renal function and CKD. [ABSTRACT FROM AUTHOR]

Prenatal exposure to thallium is related to adverse birth outcomes. However, little is known about the effects of prenatal exposure to thallium on the mitochondrial DNA copy number (mtDNAcn) in newborns; such knowledge might reveal a potential mechanism linking maternal thallium exposure and adverse birth outcomes. To investigate the trimester-specific associations of maternal thallium exposure with cord blood leukocyte mtDNAcn. A total of 746 pregnant women with trimester-specific urinary samples and cord blood samples were recruited from Wuhan Children Hospital between November 2013 and March 2015 in Wuhan City, China. The concentration of thallium in maternal urine was quantified using inductively coupled plasma mass spectrometry (ICP-MS). Cord blood leukocyte mtDNAcn was measured by real-time quantitative polymerase chain reaction (qPCR). Trimester-specific associations of specific gravity (SG)–adjusted urinary thallium concentrations with mtDNAcn were estimated using a multiple informant model. The geometric mean value of maternal urinary thallium was 0.34 μg/L, 0.36 μg/L, and 0.34 μg/L for the first, second, and third trimesters, respectively. Prenatal exposure to thallium during the first trimester, rather than during the second or the third trimester, was identified as negatively related to mtDNAcn. The multiple informant model showed a 10.4% lower level of mtDNAcn with each doubling increase of thallium levels (95% CI, −16.4%, −3.9%; P = 0.002). The observed associations were stronger among female newborns and among newborns born to older mothers. The present study revealed a significant negative association between maternal thallium exposure during early pregnancy and cord blood leukocyte mtDNAcn in Chinese newborns, pointing to the important role of mitochondria as a target of thallium toxicity in early pregnancy. • The first study to date on the association of prenatal thallium exposure with mitochondrial DNA copy number in China. • The first trimester was the window of susceptibility to thallium exposure. • The inverse associations were more prominent in female newborns and newborns born to older mothers. [ABSTRACT FROM AUTHOR]

• Subchronic arsenic exposure via food changes the gut microbiome. • Feces might be the main excreting pathway for arsenic from food exposure. • The toxicity of arsenic in staples should be comprehensively evaluated. • Gut microbiome interaction might be disturbed by arsenic. • Arsenic exposure would disturb carbohydrates, lipid, and amino acids metabolism of gut bacteria. Arsenic, a global pollutant and a threshold-free primary carcinogen, can accumulate in rice. Previous studies have focused on arsenic poisoning in drinking water and the effects on gut microbes. The research on arseniasis through food, which involves the bio-transformation of arsenic, and the related changes in gut microbiome is insufficient. Mice were exposed from animal feed prepared with four arsenic species (iAsIII, iAsV, MMA, and DMA) at a dose of 30 mg/kg according to the arsenic species proportion in rice for 30 days and 60 days. The levels of total arsenic (tAs) and arsenic species in mice feces and urine samples were determined using ICP-MS and HPLC-ICP-MS, respectively. 16S rRNA and ITS gene sequencing were conducted on microbial DNA extracted from the feces samples. At 30 days and 60 days exposure, the tAs levels excreted from urine were 0.0092 and 0.0093 mg/day, and tAs levels in feces were 0.0441 and 0.0409 mg/day, respectively. We found significant differences in arsenic species distribution in urine and feces (p < 0.05). In urine, the predominant arsenic species were iAsIII (23% and 14%, respectively), DMA (55% and 70%, respectively), and uAs (unknown arsenic, 14% and 10%, respectively). In feces, the proportion of major arsenic species (iAsV, 26% and 21%; iAsIII, 16% and 15%; MMA, 14% and 14%; DMA, 19% and 19%; and uAs, 22% and 29%, respectively) were evenly distributed. Microbiological analysis (MRPP test, α- and β-diversities) showed that diversity of gut bacteria was significantly related to arsenic exposure through food, but diversity of gut fungi is less affected. Manhattan plot and LEfSe analysis showed that arsenic exposure significantly changes microbial taxa, which might be directly associated with arsenic metabolism and diseases mediated by arsenic exposure, such as Deltaproteobacteria , Polynucleobacter , Saccharomyces , Candida , Amanitaceae, and Fusarium. Network analysis was used to identify the changing hub taxa in feces along with arsenic exposure. Function predicting analysis indicated that arsenic exposure might also significantly increase differential metabolic pathways and would disturb carbohydrates, lipid, and amino acids metabolism of gut bacteria. The results demonstrate that subchronic arsenic exposure via food significantly changes the gut microbiome, and the toxicity of arsenic in food, especially in staples, should be comprehensively evaluated in terms of the disturbance of microbiome, and feces might be the main pathway through which arsenic from food exposure is excreted and bio-transformed, providing a new insight into the investigation of bio-detoxification for arseniasis. [ABSTRACT FROM AUTHOR]