Expose to volatile organic compounds is associated with increased risk of depression: A cross-sectional study.

With increasing prevalence rate of depression by years, more attention has been paid to the influence of environmental pollutants on depression, but relationship between exposure to volatile organic compounds (VOCs) and depression is rarely studied. Therefore, this cross-sectional study use the National Center for Health Statistics (NHANES) database (2013-2016 years) to explore association between exposure to multiple VOCs and depression in general population. Multiple linear and logistic regression models were used to analyze the association between urinary VOC metabolism (mVOCs) and depression. To further analyze effect of multiple mVOCs mixed exposure, Bayesian kernel machine regression (BKMR) models were performed. A total of 3240 participants and 16 mVOCs were included in the analysis. Results showed that 10 mVOCs exposure were positively correlated with depression by multiple linear and logistic regression models, especially CYMA and MHBMA3, which also showed significant positive association with depression in BKMR model. Mixed exposure of multiple mVOCs was significantly positively correlated with depression. Gender differences were existed in effects of some VOCs concentrations on depression. AAMA, CYMA and MA had significant positive correlations with depression by women, and DHBMA had significant positive correlations with depression by men. Hence, this study showed that exposing to VOCs might have negative impacts on depression, and impact of CYMA and MHBMA3 on depression may be more evident, which provide new ideas for prevention and control of depression. But further research and exploration are needed to clarify the mechanism and influence factors of this relationship, to demonstrate the reliability of these relationship.

Melatonin mitigates manganese-induced neural damage via modulation of gut microbiota-metabolism in mice.

Manganese (Mn), a common environmental and occupational risk factor for Parkinson's disease (PD), can cause central nervous system damage and gastrointestinal dysfunction. The melatonin has been shown to effectively improve neural damage and intestinal microbiota disturbances in animal models. This research investigated the mechanism by which exogenous melatonin prevented Mn-induced neurogenesis impairment and neural damage. Here, we established subchronic Mn-exposed mice model and melatonin supplement tests to evaluate the role of melatonin in alleviating Mn-induced neurogenesis impairment. Mn induced neurogenesis impairment and microglia overactivation, behavioral dysfunction, gut microbiota dysbiosis and serum metabolic disorder in mice. All these events were reversed with the melatonin supplement. The behavioral tests revealed that melatonin group showed approximately 30 % restoration of motor activity. According to quantitative real time polymerase chain reaction (qPCR) results, melatonin group showed remarkable restoration of the expression of dopamine neurons and neurogenesis markers, approximately 46.4 % (TH), 68.4 % (DCX in hippocampus) and 48 % (DCX in striatum), respectively. Interestingly, melatonin increased neurogenesis probably via the gut microbiota and metabolism modulation. The correlation analysis of differentially expressed genes associated with hippocampal neurogenesis indicated that Firmicutes-lipid metabolism might mediate the critical repair role of melatonin in neurogenesis in Mn-exposed mice. In conclusion, exogenous melatonin supplementation can promote neurogenesis, and restore neuron loss and neural function in Mn-exposed mice, and the multi-omics results provide new research ideas for future mechanistic studies.

The association of serum neurofilament light chains with early symptoms related to Parkinson's disease: A cross-sectional study.

Neurofilament light chains (NfL), released with neural axon injury, is considered as a potential biomarker for Parkinson's disease (PD). The relationship between NfL and PD has been studied mainly in diagnosed patients. Few large-scale studies analyze the association between NfL levels and multiple non-motor symptoms linked to early PD in the general population. Therefore, this study aims to determine the association of NfL with early symptoms of PD, and effectively respond to the development of early symptoms of PD. We examined the relationship between serum NfL and early non-motor symptoms of PD (smell dysfunction, sleep problems, cognitive function) and serum Klotho levels in the general population using data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). The relationship between serum NfL and early symptoms of PD in 1125 participants was analyzed by multiple linear regression and logistic regression models. The results showed a significant association between serum NfL and early symptoms of PD. There was a significant positive correlation between NfL and smell dysfunction, short sleep and long sleep. There was a significant negative correlation between NfL and Klotho levels and cognitive function test results. Further, we observed gender and age differences in the association of NfL with early symptoms of PD. Our study demonstrate that elevated serum NfL levels are positively associated with an increased risk of early PD-related symptoms, suggesting that serum NfL can be a promising biomarker for early PD.

Exposure to volatile organic compounds is a risk factor for diabetes: A cross-sectional study.

Currently, more studies showed that environmental chemicals were associated with the development of diabetes. However, the effect of volatile organic compounds (VOCs) on diabetes remained uncertain and needed to be studied. This cross-sectional study examined whether exposure to low levels of VOCs was associated with diabetes, insulin resistance (TyG index) and glucose-related indicators (FPG,HbA1c, insulin) in the general population by using the NHANES dataset (2013-2014 and 2015-2016). We analyzed the association between urinary VOC metabolism (mVOCs) and these indicators in 1409 adults by multiple linear regression models or logistic regression models, further Bayesian kernel machine regression (BKMR) models were performed for mixture exposure analysis. The results showed positive associations between multiple mVOCs and diabetes, TyG index, FPG, HbA1c and insulin, respectively. Among them, HPMMA concentration in urine was significantly positively correlated with diabetes and related indicators (TyG index, FPG and HbA1c), and the concentration of CEMA was significantly positively correlated with insulin. The positive association of mVOCs with diabetes and its related indicators was more significant in the female group and in the 40-59 years group. Thus, our study suggested that exposure to VOCs affected insulin resistance and glucose homeostasis, further affecting diabetes levels, which had important public health implications.