Exposures to volatile organic compounds, serum vitamin D, and kidney function: association and interaction assessment in the US adult population

Relation of volatile organic compounds to renal function in American adolescents: three statistical models

This study was conducted to evaluate the relationship between 17 urinary metabolites of volatile organic compounds (mVOCs) in adolescents and renal function parameters (estimated glomerular filtration rate (eGFR), albumin-to-creatinine ratio (ACR), urinary albumin, serum uric acid (SUA), and blood urea nitrogen (BUN)). In adjusted generalised linear models (GLM), mVOCs were positively correlated with eGFR, urinary albumin, and BUN, and mVOCs were negatively correlated with ACR and SUA. Weighted Quartile Sum (WQS) index correlated with eGFR [β(95%CI): 0.040 (0.028, 0.052)], urine albumin [β(95%CI): 0.275 (0.203, 0.622)], SUA [β(95%CI): 0.040 (0.025, 0.055)] and BUN [β(95%CI): 0.102 (0.082, 0.122)]. In Bayesian Kernel Machine Regression (BKMR) model, total compound effect was positively correlated with eGFR, positive associations were observed in high concentration of the mixture with urine albumin and ACR. Findings suggest that single and mixed exposures to mVOCs may affect renal parameters in adolescents.

Association of urinary volatile organic compounds and chronic kidney disease in patients with diabetes: real-world evidence from the NHANES

BACKGROUND

Chronic kidney disease (CKD) is common in patients with diabetes mellitus (DM). Volatile organic compounds (VOCs) are widespread pollutants that may impact DM development.

OBJECTIVE

This study aims to explore the association between urinary VOC metabolites and CKD in patients with DM.

METHODS

Adult National Health and Nutrition Examination Survey (NHANES) 2011 to 2018 participants with DM were included in this study. CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 or urine albumin-to-creatinine ratio (UACR) ≥ 30 mg/g. Multivariable regression models were used to analyze the associations between urinary VOC metabolites and CKD.

RESULTS

A total of 1,295 participants with DM and a mean age of 59 years were included. After adjustment for demographic and clinical characteristics, elevated levels of N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA) (tertile 2: adjusted odds ratio (aOR)  =   1.81, 95% confidence interval (CI): 1.15-2.85, p  =  0.012), N-acetyl-S-(N-methylcarbamoyl)-L-cysteine (AMCC) (tertile 2: aOR   =  1.84, 95% CI: 1.10-3.08, p  =  0.021), DHBMA (tertile 3: aOR  =  1.93, 95% CI: 1.12-3.35, p  =   0.020), and phenylglyoxylic acid (PGA) (tertile 3: aOR   =  1.71, 95% CI: 1.11-2.63, p  =  0.017) were significantly associated with increased likelihood of CKD.

CONCLUSION

Specific urinary VOC metabolite levels are positively associated with an increased risk of CKD in patients with DM. These findings suggest that monitoring urinary VOC metabolites could be important for the prevention and management of CKD in this population. Future longitudinal studies should focus on establishing causality and elucidating the underlying mechanisms of these associations.

Assessing the Co-Exposure Patterns of Volatile Organic Compounds and the Risk of Hyperuricemia: An Analysis of the National Health and Nutrition Examination Survey 2003-2012

BACKGROUND

Co-exposure to multiple volatile organic compounds (VOCs) is common in daily life. However, few studies have evaluated the associations between the patterns of simultaneous exposure to multiple VOCs and the risk of hyperuricemia.

METHODS

This study included 7490 adults from the National Health and Nutrition Examination Survey conducted between 2003 and 2012. The K-means clustering method was applied to cluster eight kinds of VOCs in the blood into various co-exposure patterns, including benzene, bromodichloromethane, chloroform, dibromochloromethane, 1,4-dichlorobenzene, ethylbenzene, methyl tertiary-butyl ether (MTBE), and o-xylene. Binary logistic regression analysis was utilized to assess the association between single VOCs, the co-exposure patterns of multiple VOCs, and the hyperuricemia risk. Restricted cubic spline functions were utilized to investigate the non-linear relationships.

RESULTS

Based on eight VOCs, four characteristic co-exposure patterns were generated. Compared with the low-level exposure group, the levels of volatile organic compound (VOC) co-exposure in cluster 2, characterized by relatively high levels of MTBE and moderate levels of bromodichloromethane, chloroform, and dibromochloromethane, were associated with increased hyperuricemia risk, with an odds ratio of 1.32 (1.02, 1.71). Increasing levels of bromodichloromethane and chloroform were significantly associated with an increased risk of hyperuricemia. A strong J-shaped relationship was found between MTBE and hyperuricemia.

CONCLUSIONS

This study indicated that blood bromodichloromethane and chloroform were positively associated with hyperuricemia risk. Blood MTBE had a J-shaped association with hyperuricemia. In addition, the significant association of the co-exposure patterns of multiple VOCs in the blood with hyperuricemia risk was observed. Changing VOC co-exposure patterns may play a crucial role in the occurrence of hyperuricemia.

Association between volatile organic compounds exposure and periodontitis: A representative cross-sectional study

AIM

Periodontitis is one of the most common oral diseases and a major cause of tooth loss in adults. Environmental pollution is closely associated with the prevalence of periodontitis. However, few studies have focused on the association between volatile organic compounds (VOCs) and periodontitis. This cross-sectional study aims to examine whether exposure to VOCs is associated with periodontitis, based on data from the National Health and Nutrition Examination Survey (NHANES, 2011-2014).

MATERIALS AND METHODS

We analysed data on blood VOC levels, periodontitis and related covariates from 2772 participants of the NHANES. The association between the blood VOCs and periodontitis was analysed using weighted logistic regression analysis, the restricted cubic spline (RCS) model and the weighted quantile sum (WQS) regression model. Interaction tests and mediation analysis were also conducted.

RESULTS

After adjusting for covariates, for each natural constant-fold increase in 1,4-dichlorobenzene, the odds of having periodontitis increased by 16% (odds ratio = 1.16; 95% confidence interval: 1.08-1.24, p < .001). WQS regression model indicated that 1,4-dichlorobenzene contributed the most to the association between VOC co-exposure and periodontitis. Mediation analysis further revealed that total bilirubin levels mediated the association between 1,4-dichlorobenzene and the prevalence of periodontitis, accounting for 4.32%. In addition, the positive association between o-xylene and periodontitis was more pronounced in the <65-year-old group.

CONCLUSIONS

This study has provided relatively little evidence to demonstrate a specific link between VOCs and periodontitis. Nonetheless, exposure to VOCs remains a non-negligible public health concern, and further research is required to investigate the association and potential mechanisms of action between VOCs and periodontitis.

Integrated evaluation of workplace exposures and biomarkers of bladder cancer among textile dyeing workers

BACKGROUND

The textile industry is the second risk factor for bladder cancer, after smoking. Previous studies focused on the impact of exposure to high concentrations of bladder carcinogenic chemicals in the textile dyeing industry on the elevation of bladder cancer biomarkers. This study aimed to evaluate bladder carcinogenic air pollutants in a textile dyeing factory and investigate its role and the role of serum 25-hydroxyvitamin D (25-OH vit. D) on cancer bladder biomarkers in exposed workers.

METHODS

A cross-sectional study was conducted. Particulate and vapor forms of polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) were monitored in the printing, dyeing, and preparing sections of a textile factory. Bladder tumor antigen (BTA), nuclear matrix protein 22 (NMP-22), and 25-OH vit. D were estimated in all the exposed workers (147 exposed workers) and in workers not occupationally exposed to chemicals (130 unexposed workers).

RESULTS

Aromatic bladder carcinogenic compounds were either in low concentrations or not detected in the air samples of working areas. BTA and NMP-22 of exposed workers were not significantly different from the unexposed. However, 25-OH vit. D was significantly lower in the exposed than unexposed workers. There was a significant inverse correlation between 25-OH vit. D and duration of exposure in exposed workers.

CONCLUSION

The mean levels of PAHs and VOCs were within the safe standard levels in the working areas. The non-significant difference in BTA and NMP-22 between the exposed and unexposed groups suggests the presence of occupational exposures to safe levels of bladder carcinogenic aromatics, while the significantly lower 25-OH vit. D levels among the exposed than the unexposed groups could suggest the potential association of 25-OH vit. D with occupational exposures to low levels of PAHs and VOCs, and this association was found to be inversely correlated with the duration of exposures. Accordingly, more specific predictor tests must be applied for early diagnosis of bladder cancer among the exposed workers.

Sexual dimorphism association of combined exposure to volatile organic compounds (VOC) with kidney damage

BACKGROUND

Epidemiological evidence emphasizes air pollutants' role in chronic kidney disease (CKD). Volatile organic compounds (VOCs) contribute to air pollution, yet research on VOCs and kidney damage, especially gender disparities, is limited.

METHODS

This study analyzed NHANES data to explore associations between urinary VOC metabolite mixtures (VOCMs) and key kidney-related parameters: estimated glomerular filtration rate (eGFR), albumin-to-creatinine ratio (ACR), chronic kidney disease (CKD), and albuminuria. Mediation analyses assessed the potential mediating roles of biological aging (BA) and serum albumin in VOCM mixtures' effects on kidney damage. Sensitivity analyses were also conducted.

RESULTS

The mixture analysis unveiled a noteworthy positive association between VOCM mixtures and the risk of developing CKD, coupled with a significant negative correlation with eGFR within the overall participant cohort. These findings remained consistent when examining the female subgroup. However, among male participants, no significant link emerged between VOCM mixtures and CKD or eGFR. Furthermore, in both the overall and female participant groups, there was an absence of a significant correlation between VOCM mixtures and either ACR or albuminuria. On the other hand, in male participants, while no significant correlation was detected with albuminuria, a significant positive correlation was observed with ACR. Pollutant analysis identified potential links between kidney damage and 1,3-butadiene, toluene, ethylbenzene, styrene, xylene, acrolein, crotonaldehyde and propylene oxide. Mediation analyses suggested that BA might partially mediate the relationship between VOCM mixtures and kidney damage.

CONCLUSION

The current findings highlight the widespread exposure to VOCs among the general U.S. adult population and indicate a potential correlation between exposure to VOC mixtures and compromised renal function parameters, with notable gender disparities. Females appear to exhibit greater sensitivity to impaired renal function resulting from VOCs exposure. Anti-aging treatments may offer some mitigation against kidney damage due to VOCs exposure.

Paper spray mass spectrometry combined with machine learning as a rapid diagnostic for chronic kidney disease

A new analytical method for chronic kidney disease (CKD) detection utilizing paper spray mass spectrometry (PS-MS) combined with machine learning is presented. The analytical protocol is rapid and simple, based on metabolic profile alterations in urine. Anonymized raw urine samples were deposited (10 μL each) onto pointed PS-MS sample strips. Without waiting for the sample to dry, 75 μL of acetonitrile and high voltage were applied to the strips, using high resolution mass spectrometry measurement (15 s per sample) with polarity switching to detect a wide range of metabolites. Random forest machine learning was used to classify the resulting data. The diagnostic performance for the potential diagnosis of CKD was evaluated for accuracy, sensitivity, and specificity, achieving results >96% for the training data and >91% for validation and test data sets. Metabolites selected by the classification model as up- or down-regulated in healthy or CKD samples were tentatively identified and in agreement with previously reported literature. The potential utilization of this approach to discriminate albuminuria categories (normo, micro, and macroalbuminuria) was also demonstrated. This study indicates that PS-MS combined with machine learning has the potential to be used as a rapid and simple diagnostic tool for CKD.

Clinical Efficacy and Mechanism of Vitamin D2 in Treating Hashimoto's Thyroiditis

Objective

Hashimoto's thyroiditis (HT) is one of the most common autoimmune diseases, with the highest incidence rate among autoimmune thyroid disorders. Vitamin D2 may have therapeutic effects on HT. This study aimed to elucidate the molecular mechanisms underlying vitamin D2 therapy for HT.

Methods

Differentially expressed genes (DEGs) associated with vitamin D2-treated HT were identified, and the DEG-associated gene enrichment pathway was explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The correlation between the hub genes and infiltrating immune cells was investigated, and the interactions among the hub genes and target drug and competing endogenous RNA (ceRNA; long non-coding RNA [lncRNA]-microRNA [miRNA]-messenger RNA [mRNA]) regulatory networks were determined.

Results

GO and KEGG enrichment analyses identified a total of 102 DEGs (6 upregulated and 96 downregulated) in the vitamin D2-treated group samples. The area under the curve values of the identified 10 hub genes was as follows: CCR1(0.920), CXCL1 (0.960), CXCL8 (0.960), EGR1 (0.960), FCGR3B (0.920), FOS (1.000), FPR1 (0.840), MMP9 (0.720), PTGS2 (0.960), and TREM1 (1.000). The immune enrichment scores of the mast cell (P = 0.008), neutrophil (P = 0.016), and plasmacytoid dendritic cell (P = 0.016) were significantly decreased in the vitamin D2-treated group (P < 0.05). The hub gene/drug regulatory network included 8 hub genes, 108 molecular drugs, and 114 interaction relationship pairs. The ceRNA regulatory network included 129 lncRNAs, 145 miRNAs, mRNAs (hub genes), and 324 interaction relationship pairs.

Conclusion

Vitamin D2 may play an immunomodulatory role by regulating the aforementioned immune-related molecules and immune cells, thereby improving its therapeutic effects on HT.

Volatile organic compounds exposure associated with depression among U.S. adults: Results from NHANES 2011-2020

Volatile organic compounds (VOCs) are important contributors to air pollution. VOCs exposure was associated with various human diseases. Depression is one of the most prevalent mental disorders and poses a serious mental health burden. Although VOCs are neurotoxic and can damage the central nervous system, the association between VOCs exposure and depression remains obscure. Based on data from the National Health and Nutrition Examination Survey, we included 5676 adult individuals and 15 major components of urinary volatile organic compound metabolites (mVOCs). We comprehensively evaluated the potential association between each single urinary mVOC exposure and depressive symptoms using binary logistic and restricted cubic spline regression, whereas the weighted quantile sum regression and least absolute shrinkage and selection operator regression model were used to explore the mixture co-exposure association. The results indicated significantly higher mean concentrations of the 11 urinary mVOC components in the depression group than that in the non-depression group. And 12 mVOC components had a significantly positive association with depression. The overall effect of all 15 mVOCs components was also significantly positive. The corresponding odds ratio was 1.56 (95%CI: 1.2-2.03) in the categorical variable model and the regression coefficient was 0.36 (95%CI: 0.12-0.6) in the numerical variable model. Five urinary mVOCs (URXCYM, URXPHG, URX34 M, URXMB3, and URXAMC) were identified as the most relevant components associated with depression, with 89.06% total weights in the categorical variable model and 89.39% in the numerical variable model. The mVOCs were the biomarkers of VOCs, their concentrations in urine could specifically represent the contents of their metabolic parents in the human body. Considering that the metabolic parents of the above five mVOCs were predominantly acrylonitrile, toluene, styrene, acrylamide, 1,3-Butadiene, and xylenes, our results further indicated that exposure to these VOCs was closely related to depression, and more attention should be paid to the mental health risks of VOCs exposure.

Impact of hemoglobin adducts of ethylene oxide on the prevalence and prognosis of chronic kidney disease in US adults: an analysis from NHANES 2013-2016

Animal experiments have shown that high exposure to ethylene oxide (EO) can cause multiple system damages including the renal system. Recent studies have reported associations between exposure to EO and cancer, dyslipidemia, diabetes, and cardiovascular disease. However, the impact of exposure to EO on the prevalence and prognosis of chronic kidney disease (CKD) in humans is scarcely investigated. The study was designed to investigate the associations between EO exposure and incidence and prognosis of CKD among 2900 US adults. Exposure to EO was measured by detecting the levels of hemoglobin adducts of EO (HbEO). The diagnosis of CKD was made according to an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 and/or a urinary albumin-to-creatinine ratio (UACR) > 30 mg/g. Prognosis of CKD was assessed based on the evaluation system initiated by KDIGO that consists of eGFR and UACR. Survey-weighted generalized linear models and proportional odds models were constructed to assess the associations between HbEO and prevalence and prognosis of CKD, with odds ratios (ORs) and proportional odds ratios (PORs) and their 95% confidence intervals (CIs) reported, respectively. Restricted cubic spline (RCS) function was performed to depict the correlation between HbEO and CKD. The weighted median (interquartile range) of HbEO was 31.3 (23.1-60.3) pmol/g Hb. A total of 491 participants (16.9%) were diagnosed with CKD, and 153 participants (5.31%) were identified to be at high or very high risk. Referred to the first tertile of HbEO, the adjusted ORs (95% CIs) for CKD in the second and third tertile were 1.46 (0.85, 2.50) and 1.69 (1.00, 2.85), and the adjusted PORs (95% CIs) for prognosis of CKD in the second and third tertile were 1.37 (0.94, 1.99) and 1.58 (1.10, 2.26). When HbEO was analyzed as a continuous variable, the adjusted OR (95% CI) for CKD and POR (95% CI for prognosis of CKD were 1.24 (0.97, 1.58) and 1.22 (1.01, 1.47), respectively. RCS analysis revealed a non-linear positive correlation between HbEO and prevalence of CKD (P for nonlinearity < 0.05). Subgroup analysis indicated smoking status had a significant impact on this association, which remained significant among never smokers but lost significance among smokers. Among US adults, increased EO exposure was independently related to increased CKD prevalence and poor CKD outcomes, which was established in never smokers but not among ever smokers.

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.

Association between multiple metal(loid)s exposure and renal function: a cross-sectional study from southeastern China

In the real world, humans are exposed to multiple metal(loid)s (designated hereafter metals) that contain essential metals as well as toxic metals. Exposure to the metal mixture was assumed to be associated with renal function impairment; however, there is no consensus on available studies. Therefore, we here explored the association between multiple metals exposure and indicators of renal function in the general population from southeastern China. A total of 11 metals with 6 human essential metals and 5 toxic metals were determined in the selected 720 subjects. In addition, serum uric acid (SUA), serum creatinine (SCR), and the estimated glomerular filtration rate (eGFR) were measured or calculated as indicators of renal function. Using multiple flexible statistical models of generalized linear model, elastic net regression, and Bayesian kernel machine regression, the joint as well as the individual effect of metals within the mixture, and the interactions between metals were explored. When exposed to the metal mixture, the statistically non-significantly increased SUA, the significantly increased SCR, and the significantly declined eGFR were observed. In addition, the declined renal function may be primarily attributed to lead (Pb), arsenic (As), and nickel (Ni) exposure. Finally, interactions, such as the synergistic effect between Pb and Mo on SUA, whereas the antagonistic effect between Ni and Cd on SCR and eGFR were identified. Our finding suggests that combined exposure to multiple metals would impair renal function. Therefore, reducing exposure to toxic heavy metals of Pb, As, and Cd and limiting exposure to the human essential metal of Ni would protect renal function.