Are human exposure assessment the same for non-persistent organic chemicals? -from the lens of urinary variability and predictability

Variability of urinary metal in short-, mid-, long-term periods and its optimal sampling strategy: A novel epidemiological insight to exposure classification

The health effects of metals are well-documented, but relying on single urine samples may inadequately reflect short-, mid-, or long-term exposure, leading to potential misclassification. Variability in urinary metal concentrations and its implications for exposure assessment across different timeframes and epidemiological study designs remain underexplored. Identifying optimal sampling strategies and minimum sample sizes is crucial for exposure assessment of enhancing environmental health research. In a two-year repeated-measures study of healthy adults across 4 visits (2019-2021), first morning void (FMV) urine samples were collected to measure 22 metals. Variance apportionments and intraclass correlation coefficients (ICCs) evaluated metal reproducibility over short-, mid-, and long-term intervals. Surrogate category analyses were conducted to determine the minimum sample size needed for accurate exposure classification. For the long-term variability, four epidemiological scenarios were considered and compared to assess their ability in improving exposure classification. In total, 3,541 FMV samples were collected from 60 participants during all visits. We observed daily variations in metal levels at both the group and individual levels, with fluctuations ranging from several-fold to several tens of times. Co and Zn showed the highest reproducibility, requiring only 2-3 samples to accurately classify exposure across short-, mid-, and long-term periods. Other metals, such as As, Cu, Rb, Sr, Cs, and V, demonstrated good predictive ability, requiring approximately 5 and 10 samples to characterize exposure levels over one month and two years. Conversely, Al, Cr, Sb, and Se consistently failed to meet specificity thresholds of 0.7. Study designs that account for "visits apart" and involve subjects sampling on the same day performed better in exposure classification. Future studies examining the health effects of urinary metals with high temporal variability should carefully consider sampling dates, intervals, and sample size when designing their study to ensure accurate exposure classification across the population.

Perinatal Bisphenol Exposure and Small-for-Gestational-Age Neonates: The Evolving Effect of Replacements Then and Now

Bisphenol analogues have been shown to have similar estrogenic activity to that of BPA and may affect fetal development. However, no human studies have examined the effects of perinatal exposure to emerging bisphenol alternatives [bisphenol G, bisphenol M, and bisphenol BP (BPBP)] on small for gestational age (SGA) and how placental function may mediate the relationship. Here, 13 urinary bisphenol analogues were detected in 1054 contemporary pregnant women, and BPA was still the most dominant congener. Logistic regressions identified BPA and its traditional alternatives [bisphenol B (BPB), bisphenol E (BPE), bisphenol Z, and bisphenol AP (BPAP)] as being associated with an elevated risk of SGA (all ORs > 1.80, P < 0.05). In contrast, the emerging substitutes, despite high occurrences, all showed much attenuated risk. Mixture effect models Bayesian kernel machine regression and quantile-based g-computation demonstrated that coexposure to bisphenols was strongly correlated with SGA risk (OR = 2.70, P < 0.001), with BPA and the conventional substitutes (BPB, BPE, and BPAP) as primary effect drivers, outweighing the effect from emerging substitutes. Finally, mediation analysis revealed that the placental function index estriol mediated the relationship between exposure and SGA, dominated by BPBP (25.4%). Our findings provide new epidemiological evidence that early BPA alternatives may pose a higher risk for offspring development than those emerging alternatives, potentially via mediation by compromised placental function. Future toxicity assessments and validation studies in other settings on these emerging bisphenols are needed.

Role of urinary trace elements in diabetic kidney disease: a cross-sectional analysis

INTRODUCTION

The balance of trace elements plays an important role in diabetic kidney disease (DKD) patients. However, studies on the differences in urinary trace elements across different DKD stages are scarce. This study aimed to explore the associations between nine essential trace elements and DKD.

RESEARCH DESIGN AND METHODS

This cross-sectional analysis included 830 diabetic patients. Participants were classified into non-DKD (NDKD) and DKD, the latter was further grouped into mid and end DKD based on estimated glomerular filtration rate (eGFR), and the case and control were matched based on age and sex. The concentration of urinary trace elements was measured with inductively coupled plasma mass spectrometry.

RESULTS

Urinary concentrations of copper (Cu) and manganese (Mn) in DKD patients were significantly higher than that of NDKD patients, whereas that of iron (Fe), cobalt, selenium, and nickel (Ni) of DKD were lower. Positive correlations between urinary Mn/Cu and the risk of mid-stage and end-stage DKD were revealed by conditional logistic regression, while Fe and Ni were negatively associated with the risk of DKD. In mixed effect analyses, no significant trend was found for joint trace element exposure and risk of mid DKD, while negative associations between combined effects of trace elements and the risk of end DKD were observed.

CONCLUSIONS

This study revealed different associations between trace elements and the risk of mid and end DKD using both single and mixture effect modeling. The results suggested that the urinary trace element profile might be associated with the progression of DKD, which provides important insights for understanding the pathogenesis of DKD and developing individualized nutritive management strategies.

Quantitative identification of the co-exposure effects of e-waste pollutants on human oxidative stress by explainable machine learning

Global electronic waste (e-waste) generation continues to grow. The various pollutants released during precarious e-waste disposal activities can contribute to human oxidative stress. This study encompassed 129 individuals residing near e-waste dismantling sites in China, with elevated urinary concentrations of e-waste-related pollutants including heavy metals, polycyclic aromatic hydrocarbons (PAHs), organophosphorus flame retardants (OPFRs), bisphenols (BPs), and phthalate esters (PAEs). Utilizing an explainable machine learning framework, the study quantified the co-exposure effects of these pollutants, finding that approximately 23% and 18% of the variance in oxidative DNA damage and lipid peroxidation, respectively, was attributable to these substances. Heavy metals emerged as the most critical factor in inducing oxidative stress, followed by PAHs and PAEs for oxidative DNA damage, and BPs, OPFRs, and PAEs for lipid peroxidation. The interactions between different pollutant classes were found to be weak, attributable to their disparate biological pathways. In contrast, the interactions among congeneric pollutants were strong, stemming from their shared pathways and resultant synergistic or additive effects on oxidative stress. An intelligent analysis system for e-waste pollutants was also developed, which enables more efficient processing of large-scale and dynamic datasets in evolving environments. This study offered an enticing peek into the intricacies of co-exposure effect of e-waste pollutants.

Developmental toxicity of perfluorohexane sulfonate at human relevant dose during pregnancy via disruption in placental lipid homeostasis

Perfluorohexyl sulfonate (PFHxS) is the third most abundant per- and polyfluoroalkyl substances and its developmental toxicity remains very poorly understood. Here, pregnant mice exposed to PFHxS at human relevant dose showed increased fetal death incidence in the high-dose PFHxS-H group (P < 0.01). Body distribution analyses suggested that PFHxS crossed the placental barrier reaching the fetus in a dose-dependent manner. Histopathological data demonstrated impairment in the placenta with reduced blood sinus volume, placental labyrinth area as well as thickness of labyrinthine layer. Further lipidomic and transcriptomic data together showed that PFHxS exposure caused significant disruption in placental lipid homeostasis, including total lipid accumulation in the placenta, and dysregulation in phospholipid and glycerol lipid metabolism. Gene expression analyses uncovered elevation in key placental fatty acid transporters including fabp2, whereas protein expression showed transporter specific disruptions following exposure. Together, gestational exposure to human relevant level of PFHxS may increase the incidence of fetal deaths and caused placental dysplasia via disruption in lipid metabolism homeostasis. These findings raise the concern regarding the highly prevalent and persistent chemical towards early sensitive developing stages and provide basis for further understanding of its effects on lipid metabolism and underlying mechanisms.

Cell cycle, apoptosis, cell differentiation, and lipid metabolism gene expression in endometriotic tissue and exposure to parabens and benzophenones

AIM

To describe the expression profile in endometriotic tissue of genes involved in four signaling pathways related to the development and progression of endometriosis (cell cycle, apoptosis, cell differentiation and lipid metabolism) and to explore its relationship with the women exposure to chemicals with hormonal activity released from cosmetics and personal care products (PCPs).

METHODS

This cross-sectional study, encompassed within the EndEA study, comprised a subsample of 33 women with endometriosis. Expression levels of 13 genes (BMI1, CCNB1, CDK1, BAX, BCL2L1, FOXO3, SPP1, HOXA10, PDGFRA, SOX2, APOE, PLCG1 and PLCG2) in endometriotic tissue and urinary concentrations of 4 paraben (PB) and 3 benzophenone (BP) congeners were quantified. Bivariate linear and logistic regression analyses were performed to explore the associations between exposure and gene expression levels.

RESULTS

A total of 8 out 13 genes (61.5 %) were expressed in >75 % of the samples. Exposure to congeners of PBs and/or BPs was associated with the overexpression of CDK1 gene (whose protein drives cells through G2 phase and mitosis), HOXA10 and PDGFRA genes (whose proteins favor pluripotent cell differentiation to endometrial cells), and APOE (whose protein regulates the transport and metabolism of cholesterol, triglycerides and phospholipids in multiple tissues) and PLCG2 genes (whose protein creates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol, two important second messengers).

CONCLUSIONS

Our findings suggest that women exposure to cosmetic and PCP-released chemicals might be associated with the promotion of cell cycle and cell differentiation as well as with lipid metabolism disruption in endometriotic tissue, three crucial signaling pathways in the development and progression of endometriosis. However, further studies should be accomplished to confirm these preliminary data.

Human nails as a valuable noninvasive alternative for estimating exposure to parabens

Exposure of human to parabens (commonly used preservatives) is inevitable due to their extensively applied in numerous consumer products. Thus, a reliable noninvasive matrix reflecting long-term exposure to parabens is essential for human biomonitoring study. Human nails are potentially a valuable alternative for measuring intergrated exposure to parabens. In this work, we collected 100 paired nail and urine samples from university students in Nanjing, China, and measured simultaneously for six parent parabens and four metabolites. Methylparaben (MeP), ethylparaben (EtP), and propylparaben (PrP) were three predominant paraben analogue in both matrices, with the median concentrations being 12.9, 0.753, and 3.42 ng/mL in urine, and 1540, 154, and 961 ng/g in nail, respectively, while 4-hydroxybenzoic acid (4-HB) and 3,4-dihydroxybenzoic acid (3,4-DHB) were the most abundant metabolites (median values of 143 and 35.9 ng/mL, respectively) in urine. Gender-related analysis suggested that females exposed to more higher parabens than males. Significantly positive correlations were found between levels of MeP, PrP, EtP, and OH-MeP (r = 0.54-0.62, p < 0.01) in paired urine and nail samples. Our result here suggests that human nails, as an emerging biospecimen, are a potentially valuable biological matrix to evaluate human long-term exposure to parabens.