Effects Of Chemical Mixtures Research Articles

Joint Toxicity and Interaction of Carbon-Based Nanomaterials with Co-Existing Pollutants in Aquatic Environments: A Review.

This review paper focuses on the joint toxicity and interaction of carbon-based nanomaterials (CNMs) with co-existing pollutants in aquatic environments. It explores the potential harmful effects of chemical mixtures with CNMs on aquatic organisms, emphasizing the importance of scientific modeling to predict mixed toxic effects. The study involved a systematic literature review to gather information on the joint toxicity and interaction between CNMs and various co-contaminants in aquatic settings. A total of 53 publications were chosen and analyzed, categorizing the studies based on the tested CNMs, types of co-contaminants, and the used species. Common test models included fish and microalgae, with zebrafish being the most studied species. The review underscores the necessity of conducting mixture toxicity testing to assess whether the combined effects of CNMs and co-existing pollutants are additive, synergistic, or antagonistic. The development of in silico models based on the solid foundation of research data represents the best opportunity for joint toxicity prediction, eliminating the need for a great quantity of experimental studies.

Neurotoxic mixture effects of chemicals extracted from blood of pregnant women.

Human biomonitoring studies typically capture only a small and unknown fraction of the entire chemical universe. We combined chemical analysis with a high-throughput in vitro assay for neurotoxicity to capture complex mixtures of organic chemicals in blood. Plasma samples of 624 pregnant women from the German LiNA cohort were extracted with a nonselective extraction method for organic chemicals. 294 of >1000 target analytes were detected and quantified. Many of the detected chemicals as well as the whole extracts interfered with neurite development. Experimental testing of simulated complex mixtures of detected chemicals in the neurotoxicity assay confirmed additive mixture effects at concentrations less than individual chemicals' effect thresholds. The use of high-throughput target screening combined with bioassays has the potential to improve human biomonitoring and provide a new approach to including mixture effects in epidemiological studies.

Invited Perspective: Challenges and Opportunities in Evaluating the Effect of Chemical Mixtures on Congenital Chromosomal Abnormalities.

Invited Perspective: Challenges and Opportunities in Evaluating the Effect of Chemical Mixtures on Congenital Chromosomal Abnormalities.

The dark side of beauty: an in-depth analysis of the health hazards and toxicological impact of synthetic cosmetics and personal care products.

Over the past three decades, the popularity of cosmetic and personal care products has skyrocketed, largely driven by social media influence and the propagation of unrealistic beauty standards, especially among younger demographics. These products, promising enhanced appearance and self-esteem, have become integral to contemporary society. However, users of synthetic, chemical-based cosmetics are exposed to significantly higher risks than those opting for natural alternatives. The use of synthetic products has been associated with a variety of chronic diseases, including cancer, respiratory conditions, neurological disorders, and endocrine disruption. This review explores the toxicological impact of beauty and personal care products on human health, highlighting the dangers posed by various chemicals, the rise of natural ingredients, the intricate effects of chemical mixtures, the advent of nanotechnology in cosmetics, and the urgent need for robust regulatory measures to ensure safety. The paper emphasizes the necessity for thorough safety assessments, ethical ingredient sourcing, consumer education, and collaboration between governments, regulatory bodies, manufacturers, and consumers. As we delve into the latest discoveries and emerging trends in beauty product regulation and safety, it is clear that the protection of public health and well-being is a critical concern in this ever-evolving field.

Sex-Specific Associations between Prenatal Exposure to Bisphenols and Phthalates and Infant Epigenetic Age Acceleration.

We examined whether prenatal exposure to two classes of endocrine-disrupting chemicals (EDCs) was associated with infant epigenetic age acceleration (EAA), a DNA methylation biomarker of aging. Participants included 224 maternal-infant pairs from a Canadian pregnancy cohort study. Two bisphenols and 12 phthalate metabolites were measured in maternal second trimester urines. Buccal epithelial cell cheek swabs were collected from 3 month old infants and DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The Pediatric-Buccal-Epigenetic tool was used to estimate EAA. Sex-stratified robust regressions examined individual chemical associations with EAA, and Bayesian kernel machine regression (BKMR) examined chemical mixture effects. Adjusted robust models showed that in female infants, prenatal exposure to total bisphenol A (BPA) was positively associated with EAA (B = 0.72, 95% CI: 0.21, 1.24), and multiple phthalate metabolites were inversely associated with EAA (Bs from -0.36 to -0.66, 95% CIs from -1.28 to -0.02). BKMR showed that prenatal BPA was the most important chemical in the mixture and was positively associated with EAA in both sexes. No overall chemical mixture effects or male-specific associations were noted. These findings indicate that prenatal EDC exposures are associated with sex-specific deviations in biological aging, which may have lasting implications for child health and development.

Towards unbiased interpretations of interactive effects in ecotoxicological studies

Ecotoxicological research has increasingly focused on the interactive effects of chemical mixtures on biological models, emphasising additive, synergistic, or antagonistic interactions. However, these combination studies often test chemicals at unique concentrations (e.g. x:y), limiting our understanding of the effects across the full spectrum of possible combinations. Evidence from human toxicology suggests that interactive effects among chemicals can vary significantly with total concentration (e.g. x:y vs. 2x:2y), their ratio (e.g. x:2y vs. 2x:y), and the magnitude of the tested effect (e.g. LC10vs. LC50). Our non-exhaustive review of studies on binary mixtures in bee ecotoxicology reveals that such parameters are frequently neglected. Of the 60 studies we examined, only two utilised multiple total concentrations and ratios, thus exploring a broad range of possible combinations. In contrast, 26 studies tested only a single concentration of each chemical, resulting in incomplete interpretations of the potential interactive effects. Other studies utilised various concentrations and/or ratios but failed to capture a broad spectrum of possible combinations. We also discuss potential discrepancies in interactive effects based on different metrics and exposure designs. We advocate for future ecotoxicological studies to investigate a wider spectrum of chemical combinations, including various concentrations and ratios, and to address different levels of effects.

Maternal pre-pregnancy BMI influences the associations between bisphenol and phthalate exposures and maternal weight changes and fat accumulation

BackgroundBisphenols and phthalates are two classes of endocrine-disrupting chemicals (EDCs) thought to influence weight and adiposity. Limited research has investigated their influence on maternal weight changes, and no prior work has examined maternal fat mass. We examined the associations between exposure to these chemicals during pregnancy and multiple maternal weight and fat mass outcomes. MethodsThis study included a sample of 318 women enrolled in a Canadian prospective pregnancy cohort. Second trimester urinary concentrations of 2 bisphenols and 12 phthalate metabolites were quantified. Self-reported and measured maternal weights and measured skinfold thicknesses were used to calculate gestational weight gain, 3-months and 3- to 5-years postpartum weight retention, late pregnancy fat mass gain, total postpartum fat mass loss, and late postpartum fat mass retention. Adjusted robust regressions examined associations between chemicals and outcomes in the entire study population and sub-groups stratified by pre-pregnancy body mass index (BMI). Bayesian kernel machine regression examined chemical mixture effects. ResultsAmong women with underweight or normal pre-pregnancy BMIs, MBzP was negatively associated with weight retention at 3- to 5-years postpartum (B = −0.04, 95%CI: −0.07, −0.01). Among women with overweight or obese pre-pregnancy BMIs, MEHP and MMP were positively associated with weight retention at 3-months and 3- to 5-years postpartum, respectively (B's = 0.12 to 0.63, 95%CIs: 0.02, 1.07). DEHP metabolites and MCNP were positively associated with late pregnancy fat mass gain and late postpartum fat mass retention (B's = 0.04 to 0.18, 95%CIs: 0.001, 0.32). Further, the mixture of EDCs was positively associated with late pregnancy fat mass gain. ConclusionIn this cohort, pre-pregnancy BMI was a key determinant of the associations between second trimester exposure to bisphenols and phthalates and maternal weight changes and fat accumulation. Investigations of underlying physiological mechanisms, windows of susceptibility, and impacts on maternal and infant health are needed.

Application of bioassays and physicochemical analysis for assessing groundwater quality of selected tube wells in a CKDu impacted area

Groundwater from tube and dug wells are primarily used for drinking purposes by rural communities inhabiting Chronic Kidney Disease of unknown aetiology (CKDu) impacted areas in Sri Lanka. Groundwater safety assessment using targeted physicochemical analysis alone is not adequate to capture interactive effects of chemical mixtures in the groundwater. This study explored for the first time combined use of physicochemical analysis and bioassays with root meristems of Allium cepa and erythrocytes of Cyprinus carpio to assess groundwater quality of selected tube wells in Medawachchiya (a CKDu impacted area), Sri Lanka covering pre-monsoon, monsoon and postmonsoon seasons. The pH, turbidity, arsenic, cadmium, lead, mercury, fluoride, chloride, nitrate and nitrite levels in the groundwater complied with Sri Lanka standards for potable drinking water in all seasons. Yet, alkalinity and total hardness levels in the groundwater exceeded national drinking water standards (nearly up to two folds) mostly in the monsoon season. Bioassays revealed genotoxic effects of the groundwater of some tube wells in pre-monsoon and monsoon seasons. Observed genotoxicity may be associated with synergistic effects of contaminants including undetected and unknown chemicals in the groundwater depending on the season. The results support the use of bioassays as complementary tools for evaluating groundwater quality of CKDu hotspots considering consumer safety.

Co-exposure to deltamethrin and cyazofamid: variations in enzyme activity and gene transcription in the earthworm (Eisenia fetida).

Pesticide formulations are typically applied as mixtures, and their synergistic effects can increase toxicity to the organisms in the environment. Despite pesticide mixtures being the leading cause of pesticide exposure incidents, little attention has been given to assessing their combined toxicity and interactions. This survey purposed to reveal the cumulative toxic effects of deltamethrin (DEL) and cyazofamid (CYA) on earthworms (Eisenia fetida) by examining multiple endpoints. Our findings revealed that the LC50 values of DEL for E. fetida, following 7- and 14-day exposures, ranged from 887.7 (728-1095) to 1552 (1226-2298) mg kg-1, while those of CYA ranged from 316.8 (246.2-489.4) to 483.2 (326.1-1202) mg kg-1. The combinations of DEL and CYA induced synergistic influences on the organisms. The contents of Cu/Zn-SOD and CarE showed significant variations when exposed to DEL, CYA, and their combinations compared to the untreated group. Furthermore, the mixture administration resulted in more pronounced alterations in the expression of five genes (hsp70, tctp, gst, mt, and crt) associated with cellular stress, carcinogenesis, detoxification, and endoplasmic reticulum compared to single exposures. In conclusion, our comprehensive findings provided detailed insights into the cumulative toxic effects of chemical mixtures across miscellaneous endpoints and concentration ranges. These results underscored the importance of considering mixture administration during ecological risk evaluations of chemicals.

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.

A brief review on the assessment of potential joint effects of complex mixtures of contaminants in the environment

Many contaminants can have long-term effects on organisms when they are exposed to low concentrations for extended periods. This review presents new methods for identifying the effects of chemical mixtures.

Chemical risks in drinking water of inhabitants in the basin of the Tonle Sap Great Lake.

The present study aimed to assess chemical risks in the drinking water of inhabitants in the basin of the Tonle Sap Great Lake. Water samples from tube wells (n = 52), dug wells (n = 13), stored rain water (n = 39), ponds/lakes (n = 19), canals/rivers (n = 24), and household pipe water (n = 45) were collected and analyzed for physicochemical properties, as well as microbial and chemical qualities using standard methods. Analytical results revealed that 42.1% of tube wells had As > 10 μg L-1 while 8.3% had Cr > 0.05 mg L-1. Concurrently, 55.2 and 11.8% of tube wells had Cd > 3.00 μg L-1 and Pb > 10 μg L-1, respectively. Moreover, 35.0% of pipe water had Fe > 0.3 mg L-1, whereas 85.7% of tube wells and 69.2% of dug wells had Mn > 0.1 mg L-1. All water sources including pipe water could pose risks of non-carcinogenic effects of chemical mixtures to all exposure groups through their drinking water pathway. Children were at a higher risk of chemical mixtures in their drinking water than adults. This study suggests that advanced treatment technologies should be applied to the current water treatment plants to provide inhabitants with safe drinking water.

Assessing the effects of single and binary exposures of copper and lead on Mytilus galloprovincialis: Physiological and genotoxic approaches

It is becoming increasingly recognised that contaminants are not isolated in their threats to the aquatic environment, with recent shifts towards studying the effects of chemical mixtures. In this study, adult marine mussels (Mytilus galloprovincialis) were exposed to two aqueous concentrations of the essential trace metal, Cu (5 and 32 μg L−1), and the non-essential metal, Pb (5 and 25 μg L−1), both individually and in binary mixtures. After a 14-day exposure, metal accumulation was determined in the digestive gland, gill and mantle tissues by inductively coupled plasma-mass spectrometry following acid digestion, and a number of biochemical, neurotoxic and physiological markers were assessed. These included measurements of DNA damage using comet assay, total glutathione concentration, acetylcholinesterase (AChE) activity and clearance rate. Metal accumulation was greater in the digestive gland and gill than in the mantle, and based on computed free ion concentrations, was greater for Pb than for Cu. Copper exhibited an inhibitory effect on Pb accumulation but Pb did not appear to affect Cu accumulation. Comet assay results revealed DNA damage (i.e., genotoxic effects) in all treatments but differences between the exposures were not significant (p > 0.05), and there were no significant differences in AChE activities between treatments. The most distinctive impacts were a reduction in clearance rate resulting from the higher concentration of Cu, with and without Pb, and an increase in glutathione in the gill resulting from the higher concentration of Cu without Pb. Multivariate analysis facilitated the development of a conceptual model based on the current findings and previously published data on the toxicity and intracellular behaviour of Cu and Pb that will assist in the advancement of regulations and guidelines regarding multiple metal contaminants in the environment.

A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome.

Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.

A weighted quantile sum regression with penalized weights and two indices.

New statistical methodologies were developed in the last decade to face the challenges of estimating the effects of exposure to multiple chemicals. Weighted Quantile Sum (WQS) regression is a recent statistical method that allows estimating a mixture effect associated with a specific health effect and identifying the components that characterize the mixture effect. In this study, we propose an extension of WQS regression that estimates two mixture effects of chemicals on a health outcome in the same model through the inclusion of two indices, one in the positive direction and one in the negative direction, with the introduction of a penalization term. To evaluate the performance of this new model we performed both a simulation study and a real case study where we assessed the effects of nutrients on obesity among adults using the National Health and Nutrition Examination Survey (NHANES) data. The method showed good performance in estimating both the regression parameter and the weights associated with the single elements when the penalized term was set equal to the magnitude of the Akaike information criterion of the unpenalized WQS regression. The two indices further helped to give a better estimate of the parameters [Positive direction Median Error (PME): 0.022; Negative direction Median Error (NME): -0.044] compared to the standard WQS without the penalization term (PME: -0.227; NME: 0.215). In the case study, WQS with two indices was able to find a significant effect of nutrients on obesity in both directions identifying sodium and magnesium as the main actors in the positive and negative association, respectively. Through this work, we introduced an extension of WQS regression that improved the accuracy of the parameter estimates when considering a mixture of elements that can have both a protective and a harmful effect on the outcome; and the advantage of adding a penalization term when estimating the weights.

Association of a mixture of phthalates and phenols with frailty among middle-aged and older adults: A population-based cross-sectional study

BackgroundFrailty is a complex geriatric syndrome caused by degenerative changes in the body or various chronic diseases. The use of personal care and consumer products is associated with a wide range of health outcomes, but its relationship with frailty remains unknown. Therefore, our primary aim was to explore the potential links between exposure to phenols and phthalates, either separately or in combination, and frailty. MethodsThe exposure levels of phthalates and phenols were evaluated through the measurement of metabolites in urine samples. Frailty state was assessed by a 36-item frailty index with values ≥ 0.25 indicating frailty. Weighted logistic regression was used to explore the relationship between individual chemical exposure and frailty. In addition, multi-pollutant strategies (WQS, Qgcomp, BKMR) were used to examine the joint effect of chemical mixture on frailty. A series of subgroup analyses and sensitivity analyses were conducted as well. ResultsIn the multivariate logistic regression model, each unit increase in natural log-transformed BPA (OR: 1.21; 95%CI: 1.04, 1.40), MBP (OR: 1.25; 95%CI: 1.07, 1.46), MBzP (OR: 1.18; 95%CI: 1.03, 1.36), and MiBP (OR: 1.19; 95%CI: 1.03, 1.37) were significantly associated with higher odds of frailty. The results of the WQS and Qgcomp indicated that increasing quartiles of chemical mixture was associated with odds of frailty with ORs of 1.29 (95%CI: 1.01, 1.66) and 1.37 (95%CI: 1.06, 1.76). The weight of MBzP is dominant in both the WQS index and the positive weight of Qgcomp. In the BKMR model, the cumulative effect of chemical mixture was positively correlated with the prevalence of frailty. ConclusionsIn summary, higher levels of BPA, MBP, MBzP, and MiBP are significantly associated with higher odds of frailty. Our study provides preliminary evidence that phenol and phthalate biomarker mixture is positively associated with frailty, with MBzP contributing most to the positive association.

Complex chemical mixtures: Approaches for assessing adverse human health effects

In this opinion, we provide a brief overview of three main approaches for assessing effects of chemical mixtures on human health, such as experimental or theoretical component-based or whole mixture studies. We compare the purposes, pros, and cons of the approaches and highlight the recent advances within the field that focus on “real-life” exposures for risk-assessing chemical mixtures. Whole mixture studies combined with effect-directed analysis have been used mostly within ecotoxicology and less so within human toxicology, opening the potential for the determination of mixture drivers in human tissues. Concerning the implementation of mixture risk assessment in legislation, we discuss whether a data-driven factor, for example, a mixture driver factor for each chemical or chemical class could be useful when deriving the toxicologically acceptable limit.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Invited Perspective: Challenges in Evaluating the Effect of Per- and Polyfluoroalkyl Substance Mixtures on Polycystic Ovarian Syndrome

Invited Perspective: Challenges in Evaluating the Effect of Per- and Polyfluoroalkyl Substance Mixtures on Polycystic Ovarian Syndrome

Evaluation of Complex Mixture Toxicity in the Milwaukee Estuary (WI, USA) Using Whole-Mixture and Component-Based Evaluation Methods.

Anthropogenic activities introduce complex mixtures into aquatic environments, necessitating mixture toxicity evaluation during risk assessment. There are many alternative approaches that can be used to complement traditional techniques for mixture assessment. Our study aimed to demonstrate how these approaches could be employed for mixture evaluation in a target watershed. Evaluations were carried out over 2 years (2017-2018) across 8-11 study sites in the Milwaukee Estuary (WI, USA). Whole mixtures were evaluated on a site-specific basis by deploying caged fathead minnows (Pimephales promelas) alongside composite samplers for 96 h and characterizing chemical composition, in vitro bioactivity of collected water samples, and in vivo effects in whole organisms. Chemicals were grouped based on structure/mode of action, bioactivity, and pharmacological activity. Priority chemicals and mixtures were identified based on their relative contributions to estimated mixture pressure (based on cumulative toxic units) and via predictive assessments (random forest regression). Whole mixture assessments identified target sites for further evaluation including two sites targeted for industrial/urban chemical mixture effects assessment; three target sites for pharmaceutical mixture effects assessment; three target sites for further mixture characterization; and three low-priority sites. Analyses identified 14 mixtures and 16 chemicals that significantly contributed to cumulative effects, representing high or medium priority targets for further ecotoxicological evaluation, monitoring, or regulatory assessment. Overall, our study represents an important complement to single-chemical prioritizations, providing a comprehensive evaluation of the cumulative effects of mixtures detected in a target watershed. Furthermore, it demonstrates how different tools and techniques can be used to identify diverse facets of mixture risk and highlights strategies that can be considered in future complex mixture assessments. Environ Toxicol Chem 2023;42:1229-1256. © 2023 SETAC.