Urinary concentrations of bisphenol A, parabens and benzophenone-type ultra violet light filters in relation to sperm DNA fragmentation in young men: A chemical mixtures approach

People are daily exposed to multiple endocrine disruptor compounds (EDCs) that may interfere with different molecular and cellular processes, promoting a potential estrogenic, androgenic, or anti-androgenic state. However, most epidemiological studies attempting to establish relationships between EDCs exposure and health effects are still considering individual compounds. A few studies have shown associations between exposure to individual non-persistent EDCs and sperm DNA fragmentation (SDF) in different male populations. Thus, the aim of this study was to investigate associations between combined exposure to non-persistent EDCs and SDF index in young men. A cross-sectional study was conducted with 158 healthy university students from Southeaster Spain. The participants provided spot urine and semen samples on the same day. The concentrations of urinary bisphenol A (BPA), benzophenones [2,4-dihydroxybenzophenone (BP-1); 2,2',4,4'-tetrahydroxybenzophenone (BP-2), 2-hydroxy-4-methoxybenzophenone (BP-3), 2,2'-dihydroxy-4-methoxybenzophenone (BP-8), 4-hydroxybenzophenone (4OHBP)], and parabens (methylparaben, ethylparaben, propylparaben, butylparaben) were measured by dispersive liquid-liquid microextraction and ultrahigh-performance liquid chromatography with tandem mass spectrometry detection. SDF was analysed using a Sperm Chromatin Dispersion test. Statistical analyses were carried out using Bayesian Kernel Machine Regression models to evaluate associations between combined exposure to these compounds and SDF index while adjusting by relevant covariates. The increase in urinary concentration of 4OHBP was found to be the most important contributor to the negative association between urinary EDCs concentrations and SDF index, being of -5.5 % [95 % CI: -10.7, -0.3] for those in percentile 50, and - 5.4 % [95 % CI: -10.8, -0.1] for those in percentile 75. No significant associations were observed between other EDCs and SDF index. Our findings show that urinary 4OHBP levels may be associated with a decrease in the SDF index. Nonetheless, the effects we observed were likely to be small and of uncertain clinical significance. Further research is needed to replicate our findings in other male populations.

Hepatotoxicity assessment investigations on PFASs targeting L-FABP using binding affinity data and machine learning-based QSAR model

Per- and polyfluoroalkyl substances (PFASs) are persistent organic pollutants that have been detected in various environmental media and human serum, but their safety assessment remains challenging. PFASs may accumulate in liver tissues and cause hepatotoxicity by binding to liver fatty acid binding protein (L-FABP). Therefore, evaluating the binding affinity of PFASs to L-FABP is crucial in assessing the potential hepatotoxic effects. In this study, two binding sites of L-FABP were evaluated, results suggested that the outer site possessed high affinity to polyfluoroalkyl sulfates and the inner site preferred perfluoroalkyl sulfonamides, overall, the inner site of L-FABP was more sensitive to PFASs. The binding affinity data of PFASs to L-FABP were used as training set to develop a machine learning model-based quantitative structure-activity relationship (QSAR) for efficient prediction of potentially hazardous PFASs. Further Bayesian Kernel Machine Regression (BKMR) model disclosed flexibility as the determinant molecular property on PFASs-induced hepatotoxicity. It can influence affinity of PFASs to target protein through affecting binding conformations directly (individual effect) as well as integrating with other molecular properties (joint effect). Our present work provided more understanding on hepatotoxicity of PFASs, which could be significative in hepatotoxicity gradation, administration guidance, and safer alternatives development of PFASs.

Sex-specific relationships between prenatal exposure to metal mixtures and birth weight in a Chinese birth cohort

Birth weight is an indicator linking intrauterine environmental exposures to later-life diseases, and intrauterine metal exposure may affect birth weight in a sex-specific manner. We investigated sex-specific associations between prenatal exposure to metal mixtures and birth weight in a Chinese birth cohort. The birth weight of 1296 boys and 1098 girls were recorded, and 10 metals in maternal urine samples collected during pregnancy were measured using inductively coupled plasma mass spectrometry. Bayesian Kernel Machine Regression was used to estimate the association of individual metals or metal mixtures and birth weight for gestational age (BW for GA). The model showed a sex-specific relationship between prenatal exposure to metal mixtures and BW for GA with a significant negative association in girls and a non-significant positive association in boys. Cadmium (Cd) and nickel (Ni) were positively and negatively associated with BW for GA in girls, respectively. Moreover, increasing thallium (Tl) concentration lowered the positive association between Cd and BW for GA and enhanced the negative association between Ni and BW for GA in girls. When exposure to other metals increased, the positive association with Cd diminished, whereas the negative association with Ni or Tl increased. Our findings provide evidence supporting the complex effects of intrauterine exposure to metal mixtures on the birth weight of girls and further highlight the sex heterogeneity in fetal development influenced by intrauterine environmental factors.

Effects of perchlorate, nitrate, and thiocyanate exposures on serum total testosterone in children and adolescents

Perchlorate, nitrate, and thiocyanate are common thyroid disruptors in daily life and alter testosterone levels in animals. However, little is known about the effects of perchlorate, nitrate, and thiocyanate on serum total testosterone (TT) in the general population. The study was designed to assess the associations between urinary levels of perchlorate, nitrate, and thiocyanate and serum total testosterone (TT) in the general population. The present study utilized data from the 2011-2016 National Health and Nutritional Examination Survey (NHANES). A total of 6201 participants aged 6-79 with information on urinary perchlorate, nitrate, thiocyanate, and serum total testosterone were included. We conducted multiple linear regression models and Bayesian Kernel Machine Regression (BKMR) models to estimate the associations by sex-age groups. Children (ages 6-11) have higher levels of perchlorate and nitrate than the rest. After adjusting for covariates, urinary perchlorate was significantly negatively associated with serum TT in male adolescents (β = -0.1, 95 % confidence interval: -0.2, -0.01) and female children [-0.13, (-0.21, -0.05)]. Urinary nitrate was significantly negatively associated with serum TT in female children, while urinary thiocyanate was significantly positively associated with serum TT in female adults aged 20 to 49 [0.05 (0.02, 0.08)]. BKMR analysis indicated that no other interactions were found between urinary perchlorate, nitrate, and thiocyanate. Our findings suggested that urinary perchlorate, nitrate, and thiocyanate levels may relate to serum total testosterone levels in specific sex-age groups. We identified male adolescents and female children as are most sensitive subgroups where testosterone is susceptible to interference.

Early pregnancy essential and non-essential metal mixtures and gestational glucose concentrations in the 2nd trimester: Results from project viva

Metals are involved in glucose metabolism, and some may alter glycemic regulation. However, joint effects of essential and non-essential metals on glucose concentrations during pregnancy are unclear. This study explored the joint associations of pregnancy exposures to essential (copper, magnesium, manganese, selenium, zinc) and non-essential (arsenic, barium, cadmium, cesium, lead, mercury) metals with gestational glucose concentrations using 1,311 women enrolled 1999-2002 in Project Viva, a Boston, MA-area pregnancy cohort. The study measured erythrocyte metal concentrations from 1st trimester blood samples and used glucose concentrations measured 1 h after non-fasting 50-gram glucose challenge tests (GCT) from clinical gestational diabetes screening at 26-28 weeks gestation. Bayesian Kernel Machine Regression (BKMR) and quantile-based g-computation were applied to model the associations of metal mixtures-including their interactions-with glucose concentrations post-GCT. We tested for reproducibility of BKMR results using generalized additive models. The BKMR model showed an inverse U-shaped association for barium and a linear inverse association for mercury. Specifically, estimated mean glucose concentrations were highest around 75th percentile of barium concentrations [2.1 (95% confidence interval: -0.2, 4.4) mg/dL higher comparing to the 25th percentile], and each interquartile range increase of erythrocyte mercury was associated with 1.9 mg/dL lower mean glucose concentrations (95% credible interval: -4.2, 0.4). Quantile g-computation showed joint associations of all metals, essential-metals, and non-essential metals on gestational glucose concentrations were all null, however, we observed evidences of interaction for barium and lead. Overall, we found early pregnancy barium and mercury erythrocytic concentrations were associated with altered post-load glucose concentrations in later pregnancy, with potential interactions between barium and lead.

Prenatal phthalate, paraben, and phenol exposure and childhood allergic and respiratory outcomes: Evaluating exposure to chemical mixtures

BACKGROUND

Chemicals found in personal care products and plastics have been associated with asthma, allergies, and lung function, but methods to address real life exposure to mixtures of these chemicals have not been applied to these associations.

METHODS

We quantified urinary concentrations of eleven phthalate metabolites, four parabens, and five other phenols in mothers twice during pregnancy and assessed probable asthma, aeroallergies, and lung function in their age seven children. We implemented Bayesian Profile Regression (BPR) to cluster women by their exposures to these chemicals and tested the clusters for differences in outcome measurements. We used Bayesian Kernel Machine Regression (BKMR) to fit biomarkers into one model as joint independent variables.

RESULTS

BPR clustered women into seven groups characterized by patterns of personal care product and plastic use, though there were no significant differences in outcomes across clusters. BKMR showed that monocarboxyisooctyl phthalate and 2,4-dichlorophenol were associated with probable asthma (predicted probability of probable asthma per IQR of biomarker z-score (standard deviation) = 0.08 (0.09) and 0.11 (0.12), respectively) and poorer lung function (predicted probability per IQR = -0.07 (0.05) and -0.07 (0.06), respectively), and that mono(3-carboxypropyl) phthalate and bisphenol A were associated with aeroallergies (predicted probability per IQR = 0.13 (0.09) and 0.11 (0.08), respectively). Several biomarkers demonstrated positive additive effects on other associations.

CONCLUSIONS

BPR and BKMR are useful tools to evaluate associations of biomarker concentrations within a mixture of exposure and should supplement single-chemical regression models when data allow.

Levels of polycyclic aromatic hydrocarbons in umbilical cord and risk of orofacial clefts

Polycyclic aromatic hydrocarbons (PAHs), which are ubiquitous in the environment, have been found to cause orofacial clefts (OFCs) in mouse model. However, evidence from the human study with markers of intrauterine exposure is absent. We explored the associations between the levels of sixteen PAHs in umbilical cord tissue and risk for OFCs using multivariable logistic models and Bayesian Kernel Machine Regression (BKMR). This case-control study included 89 OFC cases and 129 controls without congenital malformations. Concentrations of PAHs in umbilical cord tissue were detected using gas chromatography coupled to triple quadrupole tandem mass spectrometry. The median levels of ΣPAHs, Σlow molecular weight polycyclic aromatic hydrocarbons, and Σhigh molecular weight polycyclic aromatic hydrocarbons were all higher in cases of total OFCs and its subtypes than in controls, although the differences were not statistically significant. No statistical associations between levels of PAHs in umbilical cord tissue and risk for OFCs were observed in either multivariable logistic models or BKMR models. Maternal using a stove for heating and lower frequency of ventilation in the bedroom/living room, and consumptions of fresh green vegetables were positively correlated with levels of PAHs in umbilical cord. In conclusion, our results did not suggest that in utero exposure to PAHs were associated with the risk for OFCs, in estimating whether single effect of PAHs or joint effects of multiple PAHs.

Evaluating effects of prenatal exposure to phthalate mixtures on birth weight: A comparison of three statistical approaches

OBJECTIVES

We applied three statistical approaches for evaluating associations between prenatal urinary concentrations of a mixture of phthalate metabolites and birth weight.

METHODS

We included 300 women who provided 732 urine samples during pregnancy and delivered a singleton infant. We measured urinary concentrations of metabolites of di(2-ethylhexyl)-phthalate, di-isobutyl-, di-n-butyl-, butylbenzyl-, and diethyl phthalates. We applied 1) linear regressions; 2) classification methods [principal component analysis (PCA) and structural equation models (SEM)]; and 3) Bayesian kernel machine regression (BKMR), to evaluate associations between phthalate metabolite mixtures and birth weight adjusting for potential confounders. Data were presented as mean differences (95% CI) in birth weight (grams) as each phthalate increased from the 10th to the 90th percentile.

RESULTS

When analyzing individual phthalate metabolites using linear regressions, each metabolite demonstrated a modest inverse association with birth weight [from -93 (-206, 21) to -49 (-164, 65)]. When simultaneously including all metabolites in a multivariable model, inflation of the estimates and standard errors were noted. PCA identified two principal components, both inversely associated with birth weight [-23 (-68, 22), -27 (-71, 17), respectively]. These inverse associations were confirmed when applying SEM. BKMR further identified that monoethyl and mono(2-ethylhexyl) phthalate and phthalate concentrations were linearly related to lower birth weight [-51(-164, 63) and -122 (-311, 67), respectively], and suggested no evidence of interaction between metabolites.

CONCLUSIONS

While none of the methods produced significant results, we demonstrated the potential issues arising using linear regression models in the context of correlated exposures. Among the other selected approaches, classification techniques identified common sources of exposures with implications for interventions, while BKMR further identified specific contributions of individual metabolites.