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Background and Aims: The risk of adverse health conditions varied according to the number of metabolic syndrome components. We aimed to evaluate the risk of mortality and incident cardiovascular events according to the number of components with high variability.Methods and Results: A total of 43,737 Kailuan Study participants with ≥3 examinations of waist circumference, fasting blood glucose, systolic blood pressure, triglyceride, and high-density lipoprotein during 2006-2013 were included in the present study. Visit-to-visit variability in each parameter was defined by the intraindividual standard deviation across visits. High variability was defined as the highest quartile of variability. Participants were classified numerically according to the number of high-variability components (e.g., a score of 0 indicated no high-variability component). There were 1551 deaths during a median follow-up of 5.9 years, and 950 incident cardiovascular disease (CVD) cases during a median follow-up of 4.9 years. In the multivariable adjusted model, compared with participants with low variability for all components, participants with ≥3 high-variability components had significantly higher risks for all-cause mortality (hazards ratio [HR], 1.61; 95 % confidence interval [CI], 1.35-1.91) and incident CVD event (HR, 1.45; 95 % CI, 1.16-1.82). Additionally, participants with ≥3 high-variability components had increased odds of arterial stiffness, as measured by brachia-ankle pulse wave velocity (odds ratio [OR], 1.39; 95 % CI, 1.19-1.63).Conclusions: Our findings suggest that participants with at least three metabolic parameters with high variability experienced increased risk of CVD and all-cause mortality. [ABSTRACT FROM AUTHOR]

Growing evidence suggested that lifestyle factors including dietary habits may influence the telomere length which is a reliable marker of biological aging and predictor for chronic diseases. However, the role of dietary selenium intake in telomere length maintenance is rarely examined. We aimed to test the relationship between dietary selenium intake and telomere length among middle-aged and older adults in America. A total of 3194 United States adults older than 45 years old were extracted from the National Health and Nutrition Examination Survey (NHANES) in 1999–2000 and 2001–2002. Leukocyte telomere length was measured using the quantitative real-time polymerase chain reaction (qPCR). Dietary selenium intake was assessed by a trained interviewer using 24-h dietary recall method. Generalized linear models were performed to evaluate the association of dietary selenium intake with telomere length. The restricted cubic spline analysis was used to further explore the nonlinear dose–response relationship between dietary selenium intake and telomere length. After adjusting potential confounders, every 20 μg increase in dietary selenium intake was associated with 0.42% (95% CI: 0.02%, 0.82%) longer telomere length in all participants. In the subgroup analyses, dietary selenium intake was related to longer telomere length in females (Percentage change: 0.87%; 95% CI: 0.26%, 1.49%) and non-obese participants (Percentage change: 0.53%; 95% CI: 0.04%, 1.02%), but not in males (Percentage change: 0.04%; 95% CI: −0.49%, 0.57%) and obese participants (Percentage change: 0.21%; 95% CI: −0.47%, 0.91%). The restricted cubic spline analysis showed a linear association between dietary selenium intake and telomere length. This study indicated that the increased dietary selenium intake was associated with longer telomere length among middle-aged and older adults in America. These findings require further corroboration from future prospective studies. • The first study to date on the relationship between dietary selenium intake and leukocyte telomere length in American. • This study indicated that the increased dietary selenium intake was associated with longer telomere length. • The association of dietary selenium intake with telomere length was more prominent among females and non-obese participants. [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]