Power Analysis of Exposure Mixture Studies via Monte Carlo Simulations.

Estimating sample size and statistical power is an essential part of a good epidemiological study design. Closed-form formulas exist for simple hypothesis tests but not for advanced statistical methods designed for exposure mixture studies. Estimating power with Monte Carlo simulations is flexible and applicable to these methods. However, it is not straightforward to code a simulation for non-experienced programmers and is often hard for a researcher to manually specify multivariate associations among exposure mixtures to set up a simulation. To simplify this process, we present the R package mpower for power analysis of observational studies of environmental exposure mixtures involving recently-developed mixtures analysis methods. The components within mpower are also versatile enough to accommodate any mixtures methods that will developed in the future. The package allows users to simulate realistic exposure data and mixed-typed covariates based on public data set such as the National Health and Nutrition Examination Survey or other existing data set from prior studies. Users can generate power curves to assess the trade-offs between sample size, effect size, and power of a design. This paper presents tutorials and examples of power analysis using mpower.

Associations of exposure to bisphenol-A or parabens with markers of liver injury/function among US adults in NHANES 2011-2016.

BACKGROUND: Bisphenol-A (BPA) and parabens are common endocrine-disrupting compounds (EDCs) that are used extensively in consumer products worldwide and are widely found in the environment. OBJECTIVE: The purpose of this study was to comprehensively explore the correlations between urinary BPA/parabens levels and liver injury/function markers. METHODS: In this cross-sectional study, we used National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2016. The exposure variables were urinary BPA and four urinary parabens [methylparaben (MPB), ethylparaben (EPB), propylparaben (PPB), and butylparaben (BPB)], while the outcome variables were indicators of liver function/injury [alanine aminotransferase (ALT), aspartate aminotransferase (AST), AST/ ALT, albumin (ALB), total protein (TP), total bilirubin (TBIL), alkaline phosphatase (ALP), and the fibrosis-4 index (FIB-4)]. Multiple linear regression and weighted quantile sum (WQS) regression analyses were applied to explore the relationships between the individual/combined exposure variables and the liver injury/function indicators, respectively. Furthermore, stratified analysis was employed to detect the associations influenced by age and sex. RESULTS: A total of 2,179 adults were eligible for the present analysis. Multivariate linear regression analysis revealed positive associations of EPB with AST, ALT, TP, and FIB-4 scores and negative associations of BPA with TP and ALB. The effects of urinary parabens on adverse outcomes in the liver (AST and ALT) were significant in the female and middle-aged subgroups. In addition, the WQS analysis revealed that the mixture of four compounds was negatively associated with ALB. BPA had the greatest effect on the serum ALB concentration (weight = 0.688). IMPACT: Our present study provided novel evidence of significant associations between BPA or certain parabens and numerous markers of liver injury/function indicators. We found that higher urinary BPA concentrations were associated with worse liver function. Exposure to high EPB/PPB ratios was significantly associated with biomarkers of liver injury.

Gestational exposure to organochlorine compounds and metals and infant birth weight: effect modification by maternal hardships.

BACKGROUND: Gestational exposure to toxic environmental chemicals and maternal social hardships are individually associated with impaired fetal growth, but it is unclear whether the effects of environmental chemical exposure on infant birth weight are modified by maternal hardships. METHODS: We used data from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a pan-Canadian cohort of 1982 pregnant females enrolled between 2008 and 2011. We quantified eleven environmental chemical concentrations from two chemical classes - six organochlorine compounds (OCs) and five metals - that were detected in ≥ 70% of blood samples collected during the first trimester. We examined fetal growth using birth weight adjusted for gestational age and assessed nine maternal hardships by questionnaire. Each maternal hardship variable was dichotomized to indicate whether the females experienced the hardship. In our analysis, we used elastic net to select the environmental chemicals, maternal hardships, and 2-way interactions between maternal hardships and environmental chemicals that were most predictive of birth weight. Next, we obtained effect estimates using multiple linear regression, and plotted the relationships by hardship status for visual interpretation. RESULTS: Elastic net selected trans-nonachlor, lead, low educational status, racially minoritized background, and low supplemental folic acid intake. All were inversely associated with birth weight. Elastic net also selected interaction terms. Among those with increasing environmental chemical exposures and reported hardships, we observed stronger negative associations and a few positive associations. For example, every two-fold increase in lead concentrations was more strongly associated with reduced infant birth weight among participants with low educational status (ß = -100 g (g); 95% confidence interval (CI): -215, 16), than those with higher educational status (ß = -34 g; 95% CI: -63, -3). In contrast, every two-fold increase in mercury concentrations was associated with slightly higher birth weight among participants with low educational status (ß = 23 g; 95% CI: -25, 71) compared to those with higher educational status (ß = -9 g; 95% CI: -24, 6). CONCLUSIONS: Our findings suggest that maternal hardships can modify the associations of gestational exposure to some OCs and metals with infant birth weight.

Mapping the influence of hydrocarbons mixture on molecular mechanisms, involved in breast and lung neoplasms: in silico toxicogenomic data-mining.

BACKGROUND: Exposure to chemical mixtures inherent in air pollution, has been shown to be associated with the risk of breast and lung cancers. However, studies on the molecular mechanisms of exposure to a mixture of these pollutants, such as hydrocarbons, in the development of breast and lung cancers are scarce. We utilized in silico toxicogenomic analysis to elucidate the molecular pathways linked to both cancers that are influenced by exposure to a mixture of selected hydrocarbons. The Comparative Toxicogenomics Database and Cytoscape software were used for data mining and visualization. RESULTS: Twenty-five hydrocarbons, common in air pollution with carcinogenicity classification of 1 A/B or 2 (known/presumed or suspected human carcinogen), were divided into three groups: alkanes and alkenes, halogenated hydrocarbons, and polyaromatic hydrocarbons. The in silico data-mining revealed 87 and 44 genes commonly interacted with most of the investigated hydrocarbons are linked to breast and lung cancer, respectively. The dominant interactions among the common genes are co-expression, physical interaction, genetic interaction, co-localization, and interaction in shared protein domains. Among these genes, only 16 are common in the development of both cancers. Benzo(a)pyrene and tetrachlorodibenzodioxin interacted with all 16 genes. The molecular pathways potentially affected by the investigated hydrocarbons include aryl hydrocarbon receptor, chemical carcinogenesis, ferroptosis, fluid shear stress and atherosclerosis, interleukin 17 signaling pathway, lipid and atherosclerosis, NRF2 pathway, and oxidative stress response. CONCLUSIONS: Within the inherent limitations of in silico toxicogenomics tools, we elucidated the molecular pathways associated with breast and lung cancer development potentially affected by hydrocarbons mixture. Our findings indicate adaptive responses to oxidative stress and inflammatory damages are instrumental in the development of both cancers. Additionally, ferroptosis-a non-apoptotic programmed cell death driven by lipid peroxidation and iron homeostasis-was identified as a new player in these responses. Finally, AHR potential involvement in modulating IL-8, a critical gene that mediates breast cancer invasion and metastasis to the lungs, was also highlighted. A deeper understanding of the interplay between genes associated with these pathways, and other survival signaling pathways identified in this study, will provide invaluable knowledge in assessing the risk of inhalation exposure to hydrocarbons mixture. The findings offer insights into future in vivo and in vitro laboratory investigations that focus on inhalation exposure to the hydrocarbons mixture.

An in vitro model system for testing chemical effects on microbiome-immune interactions - examples with BPX and PFAS mixtures.

Introduction: More than 350,000 chemicals make up the chemical universe that surrounds us every day. The impact of this vast array of compounds on our health is still poorly understood. Manufacturers are required to carry out toxicological studies, for example on the reproductive or nervous systems, before putting a new substance on the market. However, toxicological safety does not exclude effects resulting from chronic exposure to low doses or effects on other potentially affected organ systems. This is the case for the microbiome-immune interaction, which is not yet included in any safety studies. Methods: A high-throughput in vitro model was used to elucidate the potential effects of environmental chemicals and chemical mixtures on microbiome-immune interactions. Therefore, a simplified human intestinal microbiota (SIHUMIx) consisting of eight bacterial species was cultured in vitro in a bioreactor that partially mimics intestinal conditions. The bacteria were continuously exposed to mixtures of representative and widely distributed environmental chemicals, i.e. bisphenols (BPX) and/or per- and polyfluoroalkyl substances (PFAS) at concentrations of 22 µM and 4 µM, respectively. Furthermore, changes in the immunostimulatory potential of exposed microbes were investigated using a co-culture system with human peripheral blood mononuclear cells (PBMCs). Results: The exposure to BPX, PFAS or their mixture did not influence the community structure and the riboflavin production of SIHUMIx in vitro. However, it altered the potential of the consortium to stimulate human immune cells: in particular, activation of CD8+ MAIT cells was affected by the exposure to BPX- and PFAS mixtures-treated bacteria. Discussion: The present study provides a model to investigate how environmental chemicals can indirectly affect immune cells via exposed microbes. It contributes to the much-needed knowledge on the effects of EDCs on an organ system that has been little explored in this context, especially from the perspective of cumulative exposure.

Assessing the impact of imidacloprid, glyphosate, and their mixtures on multiple biomarkers in Corbicula largillierti.

Pesticide mixtures are frequently utilized in agriculture, yet their cumulative effects on aquatic organisms remain poorly understood. Aquatic animals can be effective bioindicators and invasive bivalves, owing to their widespread distribution, provide an opportunity to assess these impacts. Glyphosate and imidacloprid, among the most prevalent pesticides globally, are frequently detected in freshwater systems in South America. This study aims to understand the cumulative effects of pesticide mixtures on aquatic organisms, using invasive Corbicula largillierti clams from a natural stream in northwestern Argentina. We conducted 48-hour exposure experiments using two concentrations of imidacloprid (20 and 200 µg L-1 a.i), two concentrations of glyphosate (0.3 and 3 mg L-1 a.i), and two combinations of these pesticides (both at low and high concentrations, respectively), simulating the direct contamination of both pesticides based on their agronomic recipe and observed values in Argentine aquatic environments. Clam metabolism was assessed through the examination of multiple oxidative stress parameters and measuring oxygen consumption rate as a proxy for standard metabolic rate (SMR). Our findings revealed that imidacloprid has a more pronounced effect compared to glyphosate. Imidacloprid significantly decreased clam SMR and cellular levels of reduced glutathione (GSH). However, when both pesticides were present, also cellular glycogen and thiobarbituric acid-reactive substances (TBARS) were affected. Proteins and glutathione S-Transferase (GST) activity were unaffected by either pesticide or their mixture at the assayed concentrations, highlighting the need to test several stress parameters to detect toxicological impacts. Our results indicated additive effects of imidacloprid and glyphosate across all measured parameters. The combination of multiple physiological and cytological biomarkers in invasive bivalves offers significant potential to enhance biomonitoring sensitivity and obtain insights into the origins and cellular mechanisms of chemical impacts. These studies can improve pollution regulatory policies and pesticide management.

The use of effect biomarkers in chemical mixtures risk assessment - Are they still important?

Human epidemiological studies with biomarkers of effect play an invaluable role in identifying health effects with chemical exposures and in disease prevention. Effect biomarkers that measure genetic damage are potent tools to address the carcinogenic and/or mutagenic potential of chemical exposures, increasing confidence in regulatory risk assessment decision-making processes. The micronucleus (MN) test is recognized as one of the most successful and reliable assays to assess genotoxic events, which are associated with exposures that may cause cancer. To move towards the next generation risk assessment is crucial to establish bridges between standard approaches, new approach methodologies (NAMs) and tools for increase the mechanistically-based biological plausibility in human studies, such as the adverse outcome pathways (AOPs) framework. This paper aims to highlight the still active role of MN as biomarker of effect in the evolution and applicability of new methods and approaches in human risk assessment, with the positive consequence, that the new methods provide a deeper knowledge of the mechanistically-based biology of these endpoints.

Human Biomonitoring of Environmental Chemicals among Elderly in Wuhan, China: Prioritizing Risks Using EPA's ToxCast Database.

In line with the "healthy aging" principle, we aim to assess the exposure map and health risks of environmental chemicals in the elderly. Blood samples from 918 elderly individuals in Wuhan, China, were analyzed using the combined gas/liquid-mass spectrometry technology to detect levels of 118 environmental chemicals. Cluster analysis identified exposure profiles, while risk indexes and bioanalytical equivalence percentages were calculated using EPA's ToxCast database. The detection rates for 87 compounds exceeded 70%. DEHP, DiBP, naphthalene, phenanthrene, DnBP, pyrene, anthracene, permethrin, fluoranthene, and PFOS showed the highest concentrations. Fat-soluble pollutants varied across lifestyles. In cluster 2, which was characterized by higher concentrations of fat-soluble substances, the proportion of smokers or drinkers was higher than that of nonsmokers or nondrinkers. Pesticides emerged as the most active environmental chemicals in peroxisome proliferator-activated receptor gamma antagonist, thyroid hormone receptor (TR) antagonist, TR agonist, and androgen receptor (AR) agonist activity assays. Additionally, PAEs and polycyclic aromatic hydrocarbons played significant roles as active contaminants for the corresponding targets of AR antagonists and estrogen receptor alpha. We proposed a list of priority pollutants linked to endocrine-disrupting toxic effects in the elderly, which may provide the groundwork for further research into environmental etiology.

Association between exposure to chemical mixtures and epigenetic ageing biomarkers: Modifying effects of thyroid hormones and physical activity.

Evidence on the effects of internal chemical mixture exposures on biological age is limited. It also remains unclear whether hormone homeostasis and lifestyle factors can modify such a relationship. Based on the Biomarkers for Air Pollutants Exposure (BAPE) study, which involved healthy older adults aged 60-69 years in China, we found that chemical mixture exposures, including metals, polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFASs), phthalates (PAEs), and organophosphate esters (OPEs), were significantly associated with shortened DNAmTL and accelerated SkinBloodClock, in which PFASs and OPEs in blood were the primary contributors to DNAmTL, while metals and PAEs had relatively higher contributions in urine. Furthermore, lower levels of thyroxin appeared to exacerbate the adverse effects of environmental chemicals on epigenetic ageing but relatively higher levels of physical activity had the beneficial impact. These findings may have important implications for the development of healthy ageing strategy and aged care policy, particularly in light of the global acceleration of population ageing.

A high-throughput analytical method for complex contaminant mixtures in biosolids.

Biosolids are rich in organic matter and other nutrients that contribute to environmental and agricultural sustainability by improving soil textural and biological properties and enhancing plant growth when applied to agricultural crops. Land application of biosolids encourages resource recovery and circumvents drawbacks associated with landfilling or incineration. However, biosolids contain numerous chemicals at trace levels, and quantitative analysis of such mixtures in this complex matrix is crucial for understanding and managing application risks. There are currently few analytical methods available that are capable of extracting and quantifying a large range of the emerging contaminants found in biosolids. In this study, a simplified, rapid, and robust method of analysis was developed and validated for a high-priority organic contaminant mixture of 44 endocrine disrupting compounds known to occur in biosolids. Analytes consisted of chemicals from many classes with a wide range of physiochemical properties (e.g., log Kow values from -1.4 to 8.9). The biosolids extraction and cleanup protocol was validated for 42 of the targeted compounds. The UPLC-MS2 parameters were validated for all 44 organic contaminants targeted for study. From the two batches of biosolids tested using this analytical method, most of the targeted contaminants (86%) were detected with 100% frequency at concentrations ranging from 0.036 to 10,226 µg/kg dw. Performance results highlighted that internal standards alone could not negate biosolids matrix effects; thus, internal standards and the standard addition method were used for residue quantification. This was the first study to detect and quantify 6PPD-q in biosolids, and the first to quantify lidocaine and 11 other chemicals in biosolids using a single analytical method. This method may be expanded for analysis of additional chemicals in biosolids and comparable matrices.

Are We Justified in Modeling Human Exposure to Chlorinated Paraffin Mixtures Using the Average Properties of Congeners and Homologues?

Concern over human exposure to chlorinated paraffin (CP) mixtures keeps increasing. The absence of a comprehensive understanding of how human exposure varies with the physicochemical properties of CP constituents has hindered the ability to determine at what level of aggregation exposure to CPs should be assessed. We answer this question by comparing exposure predicted with either a "complex" method that utilizes isomer-specific properties or "simplified" methods that rely on median properties of congener, homologue, or short-/medium-/long-chain CP groups. Our results demonstrate the wide range of physicochemical properties across CP mixtures and their dependence on molecular structures. Assuming unit emissions in the environment, these variances translate into an extensive disparity in whole-body concentrations predicted for different isomers, spanning ∼11 orders of magnitude. CPs with 13-19 carbons and 6-10 chlorines exhibit the highest human exposure potential, primarily owing to moderate to high hydrophobicity and slow environmental degradation and biotransformation. Far-field exposure is dominant for most CP constituents. Our study underscores that using average properties of congener, homologue, or S/M/LCCP groups yields results that are consistent with those derived from isomer-based modeling, thus offering an efficient and practical framework for future risk assessments and human exposure studies of CPs and other complex chemical mixtures.

Association of exposure to mixture of chemicals during pregnancy with cognitive abilities and fine motor function of children.

Chemical exposures often occur in mixtures and exposures during pregnancy may lead to adverse effects on the fetal brain, potentially reducing lower cognitive abilities and fine motor function of the child. We investigated the association of mothers exposure to a mixture of chemicals during pregnancy (i.e., organochlorine compounds, per- and polyfluoroalkyl substances, phenols, phthalates, organophosphate pesticides) with cognitive abilties and fine motor function in their children. We studied 1097 mother-child pairs from five European cohorts participating in the Human Early Life Exposome study (HELIX). Measurement of 26 biomarkers of exposure to chemicals was performed on urine or blood samples of pregnant women (mean age 31 years). Cognitive abilities and fine motor function were assessed in their children (mean age 8 years) with a battery of computerized tests administered in person (Ravens Coloured Progressive Matrices, Attention Network Test, N-back Test, Trail Making Test, Finger Tapping Test). We estimated the joint effect of prenatal exposure to chemicals on cognitive abilities and fine motor function using the quantile-based g-computation method, adjusting for sociodemographic characteristics. A quartile increase in all the chemicals in the overall mixture was associated with worse fine motor function, specifically lower scores in the Finger Tapping Test [-8.5 points, 95 % confidence interval (CI) -13.6 to -3.4; -14.5 points, 95 % CI -22.4 to -6.6, and -18.0 points, 95 % CI -28.6 to -7.4) for the second, third and fourth quartile of the overal mixture, respectively, when compared to the first quartile]. Organochlorine compounds, phthalates, and per- and polyfluoroalkyl substances contributed most to this association. We did not find a relationship with cognitive abilities. We conclude that exposure to chemical mixtures during pregnancy may influence neurodevelopment, impacting fine motor function of the offspring.

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

Chemical mixture that targets the epidermal growth factor pathway impairs human trophoblast cell functions.

Pregnant women are exposed to complex chemical mixtures, many of which reach the placenta. Some of these chemicals interfere with epidermal growth factor receptor (EGFR) activation, a receptor tyrosine kinase that modulates several placenta cell functions. We hypothesized that a mixture of chemicals (Chem-Mix) known to reduce EGFR activation (polychlorinated biphenyl (PCB)-126, PCB-153, atrazine, trans-nonachlor, niclosamide, and bisphenol S) would interfere with EGFR-mediated trophoblast cell functions. To test this, we determined the chemicals' EGFR binding ability, EGFR and downstream effectors activation, and trophoblast functions (proliferation, invasion, and endovascular differentiation) known to be regulated by EGFR in extravillous trophoblasts (EVTs). The Chem-Mix competed with EGF for EGFR binding, however only PCB-153, niclosamide, trans-nonachlor, and BPS competed for binding as single chemicals. The effects of the Chem-Mix on EGFR phosphorylation were tested by exposing the placental EVT cell line, HTR-8/SVneo to control (0.1% DMSO), Chem-Mix (1, 10, or 100 ng/ml), EGF (30 ng/ml), or Chem-Mix + EGF. The Chem-Mix - but not the individual chemicals - reduced EGF-mediated EGFR phosphorylation in a dose dependent manner, while no effect was observed in its downstream effectors (AKT and STAT3). None of the individual chemicals affected EVT cell invasion, but the Chem-Mix reduced EVT cell invasion independent of EGF. In support of previous studies that have explored chemicals targeting a specific pathway (estrogen/androgen receptor), current findings indicate that exposure to a chemical mixture that targets the EGFR pathway can result in a greater impact compared to individual chemicals in the context of placental cell functions.

Predictive value of the ToxCast/Tox21 high throughput toxicity screening data for approximating in vivo ecotoxicity endpoints and ecotoxicological risk in eco- surveillance applications.

Ecotoxicology has long relied on assessing the hazard potential of chemicals through traditional in vivo testing methods to understand the possible risk exposure could pose to ecological taxa. In the past decade, the development of non-animal new approach methods (NAMs) for assessing chemical hazard and risk has quickly grown. These methods are often cheaper and faster than traditional toxicity testing, and thus are amenable to high-throughput toxicity testing (HTT), resulting in large datasets. The ToxCast/Tox21 HTT programs have produced in vitro data for thousands of chemicals covering a large space of biological activity. The relevance of these data to in vivo mammalian toxicity has been much explored. Interest has also grown in using these data to evaluate the risk of environmental exposures to taxa of ecological importance such as fish, aquatic invertebrates, etc.; particularly for the purpose of estimating the risk of exposure from real-world complex mixtures. Understanding the relationship and relative sensitivity of NAMs versus standardized ecotoxicological whole organism models is a key component of performing reliable read-across from mammalian in vitro data to ecotoxicological in vivo data. In this work, we explore the relationship between in vivo ecotoxicity data from several publicly available databases and the ToxCast/Tox21 data. We also performed several case studies in which we compare how using different ecotoxicity datasets, whether traditional or ToxCast-based, affects risk conclusions based on exposure to complex mixtures derived from existing large-scale chemical monitoring data. Generally, predictive value of ToxCast data for traditional in vivo endpoints (EPs) was poor (r ≤ 0.3). Risk conclusions, including identification of different chemical risk drivers and prioritized monitoring sites, were different when using HTT data vs. traditional in vivo data.

Enhancing knowledge of chemical exposures and fate in honey bee hives: Insights from colony structure and interactions.

Honey bees are unintentionally exposed to a wide range of chemicals through various routes in their natural environment, yet research on the cumulative effects of multi-chemical and sublethal exposures on important caste members, including the queen bee and brood, is still in its infancy. The hive's social structure and food-sharing (trophallaxis) practices are important aspects to consider when identifying primary and secondary exposure pathways for residential hive members and possible chemical reservoirs within the colony. Secondary exposures may also occur through chemical transfer (maternal offloading) to the brood and by contact through possible chemical diffusion from wax cells to all hive members. The lack of research on peer-to-peer exposures to contaminants and their metabolites may be in part due to the limitations in sensitive analytical techniques for monitoring chemical fate and dispersion. Combined application of automated honey bee monitoring and modern chemical trace analysis techniques could offer rapid progress in quantifying chemical transfer and accumulation within the hive environment and developing effective mitigation strategies for toxic chemical co-exposures. To enhance the understanding of chemical fate and toxicity within the entire colony, it is crucial to consider both the intricate interactions among hive members and the potential synergistic effects arising from combinations of chemical and their metabolites.

EDC mixtures during pregnancy and body fat at 7 years of age in a Swedish cohort, the SELMA study.

BACKGROUND: Some endocrine disrupting chemicals (EDC), are "obesogens" and have been associated with overweight and obesity in children. Daily exposure to different classes of EDCs demands for research with mixtures approach. OBJECTIVES: This study evaluates the association, considering sex-specific effects, between prenatal exposure to EDC mixture and children's body fat at seven years of age. METHODS: A total of 26 EDCs were assessed in prenatal urine and serum samples from first trimester in pregnancy from 737 mother-child pairs participating in the Swedish Environmental Longitudinal, Mother and child, Asthma and allergy (SELMA) study. An indicator for children's "overall body fat" was calculated, using principal component analysis (PCA), based on BMI, percent body fat, waist, and skinfolds measured at seven years of age. Weighted quantile sum (WQS) regression was used to assess associations between EDC mixture and children's body fat. RESULTS: Principal component (PC1) represented 83.6 % of the variance, suitable as indicator for children's "overall body fat", with positive loadings of 0.40-0.42 for each body fat measure. A significant interaction term, WQS*sex, confirmed associations in the opposite direction for boys and girls. Higher prenatal exposure to EDC mixture was borderline significant with more "overall body fat" for boys (Mean ß = 0.20; 95 % CI: -0.13, 0.53) and less for girls (Mean ß = -0.23; 95 % CI: -0.58, 0.13). Also, higher prenatal exposure to EDC mixture was borderline significant with more percent body fat (standardized score) for boys (Mean ß = 0.09; 95 % CI: -0.04, 0.21) and less for girls (Mean ß = -0.10 (-0.26, 0.05). The chemicals of concern included bisphenols, phthalates, PFAS, PAH, and pesticides with different patterns for boys and girls. DISCUSSION: Borderline significant associations were found between prenatal exposure to a mixture of EDCs and children's body fat. The associations in opposite directions suggests that prenatal exposure to EDCs may present sex-specific effects on children's body fat.

The U.S. PFAS exposure burden calculator for 2017-2018: Application to the HOME Study, with comparison of epidemiological findings from NHANES.

BACKGROUND: The 2017-2018 U.S. PFAS exposure burden calculator was designed to provide a summary exposure score for per- and polyfluoroalkyl substances (PFAS) mixtures using targeted PFAS analyte data. Its aim was to place PFAS burden score estimates onto a common scale based on nationally representative U.S. reference ranges from 2017 to 2018, enabling comparisons of overall PFAS burden scores across studies even if they did not measure the same set of PFAS analytes. OBJECTIVE: To use the U.S. PFAS exposure burden calculator for comparing the same mixture of PFAS compounds in similarly aged adolescents and their associations with cardiometabolic outcomes in the HOME Study and NHANES between 2015 and 2018. METHODS: We applied the PFAS burden calculator to 8 PFAS analytes measured in the serum of adolescents from the HOME Study (Cincinnati, Ohio; age range 11-14 years; years: 2016-2019; n = 207) and NHANES (US; age range 12-14 years; years 2015-2018; n = 245). We used the non-parametric Mann-Whitney U test and chi-squared test to compare the two study samples. In both studies, we examined associations of PFAS burden scores with the same cardiometabolic outcomes, adjusted for the same core set of covariates using regression analyses. We conducted sensitivity analyses to verify robustness of exposure-outcome associations, by accounting for measurement error of PFAS burden scores. RESULTS: PFAS burden scores were significantly different (p = 0.004) between the HOME Study (median: 0.00, interquartile range - 0.37, 0.34) and the NHANES samples (median: 0.04, IQR -0.11, 0.54), while no significant difference was found for PFAS summed concentrations (p = 0.661). In the HOME Study, an interquartile (IQR) increase in PFAS burden score was associated with higher total cholesterol [7.0 mg/dL, 95% CI: 0.6, 13.4]; HDL [2.8 mg/dL, 95% CI: 0.4, 5.2]; LDL [5.9 mg/dL, 95% CI: 0.5, 11.3], insulin [0.1 log(mIU/L), 95% CI: 0.01, 0.2], and HOMA-IR [0.1, 95% CI: 0.01, 0.2]. In NHANES, an IQR increase in PFAS burden score was associated with higher diastolic blood pressure [2.4 mmHg, 95% CI: 0.4, 4.4] but not with other outcomes. Sensitivity analyses in the HOME Study and NHANES were consistent with the main findings. CONCLUSIONS: Performance of the U.S. PFAS exposure burden calculator was similar in a local versus national sample of adolescents, and may be a useful tool for the assessment of PFAS mixtures across studies.

Metabolomics revealed disruptions in amino acid and antioxidant biochemistry in Daphnia magna exposed to industrial effluents associated with plastic and polymer production.

Industrial wastewater effluents are a major source of chemicals in aquatic environments, and many of these chemicals may negatively impact aquatic life. In this study, the crustacean Daphnia magna, a common model organism in ecotoxicity studies, was exposed for 48 h to nine different industrial effluent samples from manufacturing facilities associated with the production of plastics, polymers, and coating products at a range of dilutions: 10, 25, 50, 100% (undiluted). A targeted metabolomic-based approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify polar metabolites from individual daphnids that survived the 48 h exposure. Multivariate analyses and metabolite changes revealed metabolic perturbations across all effluent samples studied, with non-monotonic responses and both up and downregulation relative to the unexposed control. Pathway analyses indicated the disruption of similar and distinct pathways, mostly connected to protein synthesis, amino acid metabolism, and antioxidant processes. Overall, we observed disruptions in Daphnia biochemistry that were similar across the effluent samples, but with unique features for each effluent sample. Additionally, non-monotonic heightened responses suggested additive and/or synergistic interactions between the chemicals within the industrial effluents. These findings demonstrate that targeted metabolomic approaches are a powerful tool for the biomonitoring of aquatic ecosystems in the context of complex mixtures, such as industrial wastewater effluents.

Allelopathic effects of Eucalyptus extract and wood vinegar on germination and sprouting of rapeseed (Brassica rapa L.).

Eucalyptus plantations are usually characterized by low biodiversity due to allelopathy effects. Wood vinegar is considered a complex growth regulator that can promote plant growth at low concentrations. However, there is information scarcity about the co-application of eucalypt leaf water extract and wood vinegar on plants. This study aimed at clarifying whether wood vinegar can protect seed germination against suppression by eucalypt-induced allelopathy. We examined germination behavior and seedling elongation characteristics in rapeseed (Brassica rapa L.) treated with different solutions of wood vinegar and eucalypt leaf water extract. The results showed that eucalypt leaf water extracts, wood vinegar solutions, and their mixture allelopathically suppressed seed germination rate. After rapeseed sprouting, eucalypt leaf water extracts promoted root elongation, stem elongation, and fresh weight elongation. Malondialdehyde content was also lower under the influence of eucalypt leaf water extract. Mixture of high concentration of eucalypt leaf water extract and lower concentration of wood vinegar significantly promoted root elongation. Therefore, both eucalypt leaf water extract and wood vinegar are complex plant growth regulators, which can be used to inhibit or stimulate plants at different ontogenic stages. During the seed germination period, both eucalypt leaf extracts and wood vinegar could be used as weed inhibitors. Conversely, during the period of sprouting (seedling establishment), low concentrations of eucalypt leaf extracts and wood vinegar can promote growth.