Risk Assessment Of Mixtures Research Articles

Machine learning-driven QSAR models for predicting the mixture toxicity of nanoparticles

Research on theoretical prediction methods for the mixture toxicity of engineered nanoparticles (ENPs) faces significant challenges. The application of in silico methods based on machine learning is emerging as an effective strategy to address the toxicity prediction of chemical mixtures. Herein, we combined toxicity data generated in our lab with experimental data reported in the literature to predict the combined toxicity of seven metallic ENPs for Escherichia coli at different mixing ratios (22 binary combinations). We thereafter applied two machine learning (ML) techniques, support vector machine (SVM) and neural network (NN), and compared the differences in the ability to predict the combined toxicity by means of the ML-based methods and two component-based mixture models: independent action and concentration addition. Among 72 developed quantitative structure–activity relationship (QSAR) models by the ML methods, two SVM-QSAR models and two NN-QSAR models showed good performance. Moreover, an NN-based QSAR model combined with two molecular descriptors, namely enthalpy of formation of a gaseous cation and metal oxide standard molar enthalpy of formation, showed the best predictive power for the internal dataset (R2test = 0.911, adjusted R2test = 0.733, RMSEtest = 0.091, and MAEtest = 0.067) and for the combination of internal and external datasets (R2test = 0.908, adjusted R2test = 0.871, RMSEtest = 0.255, and MAEtest = 0.181). In addition, the developed QSAR models performed better than the component-based models. The estimation of the applicability domain of the selected QSAR models showed that all the binary mixtures in training and test sets were in the applicability domain. This study approach could provide a methodological and theoretical basis for the ecological risk assessment of mixtures of ENPs.

A case study of neurodevelopmental risks from combined exposures to lead, methyl-mercury, inorganic arsenic, polychlorinated biphenyls, polybrominated diphenyl ethers and fluoride.

We performed a mixture risk assessment (MRA) case study of dietary exposure to the food contaminants lead, methylmercury, inorganic arsenic (iAs), fluoride, non-dioxin-like polychlorinated biphenyls (NDL-PCBs) and polybrominated diphenyl ethers (PBDEs), all substances associated with declines in cognitive abilities measured as IQ loss. Most of these chemicals are frequently measured in human biomonitoring studies. A component-based, personalised modified reference point index (mRPI) approach, in which we expressed the exposures and potencies of our chosen substances as lead equivalent values, was applied to perform a MRA for dietary exposures. We conducted the assessment for four different age groups (toddlers, children, adolescents, and women aged 18-45 years) in nine European countries. Populations in all countries considered exceeded combined tolerable levels at median exposure levels. NDL-PCBs in fish, other seafood and dairy, lead in grains and fruits, methylmercury in fish and other seafoods, and fluoride in water contributed most to the combined exposure. We identified uncertainties for the likelihood of co-exposure, assessment group membership, endpoint-specific reference values (ESRVs) based on epidemiological (lead, methylmercury, iAs, fluoride and NDL-PCBs) and animal data (PBDE), and exposure data. Those uncertainties lead to a complex pattern of under- and overestimations, which would require probabilistic modelling based on expert knowledge elicitation for integration of the identified uncertainties into an overall uncertainty estimate. In addition, the identified uncertainties could be used to refine future MRA for cognitive decline.

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.

Epidemiology-based wastewater monitoring for ecological risks of anti-tuberculosis drugs mixture effects

First-line anti-tuberculosis (TB) drugs are commonly used to treat TB worldwide, leading to more contaminated wastewater being widely discharged into aquatic environments. However, studies of mixture interactions of anti-TB drugs and their residues in aquatic environments are scarce. This study aimed to determine the toxic interactions of anti-TB drugs—isoniazid (INH), rifampicin (RMP), and ethambutol (EMB)—in binary and ternary mixtures on Daphnia magna and used the epidemiology of TB history to construct epidemiology-based wastewater monitoring for assessing the environmental release of residues and related ecological risks. The acute immobilization of median effect concentrations (EC50) was 25.6 mg L−1 for INH, 80.9 mg L−1 for RMP, and 188.8 mg L−1 for EMB, as toxic units (TUs) for assessing mixture toxicity. The ternary mixture exhibited the lowest TUs at 50 % effects with 1.12, followed by 1.28 for RMP + EMB, 1.54 for INH + RMP, and 1.93 for INH + EMB, indicating antagonistic interactions. Nevertheless, the combination index (CBI) was used to examine the mixture toxicity in response to immobilization, revealing that the ternary mixture of CBI ranged from 1.01 to 1.08, tending to have a nearly additive effect when suffering >50 % effect (at high concentration levels). The forecasted environmentally relevant concentrations of anti-TB drugs have been on downward trends with ng L−1 level from 2020 to 2030 in Kaohsiung, Taiwan. Although ecotoxicological risks from the wastewater treatment plant and receiving water in the field were slightly greater than the prediction from epidemiology-based wastewater monitoring, there were no risk concerns. Here, we achieved the establishment of evidence that anti-TB drug mixtures' interaction and epidemiological-based monitoring support a systematic approach, resolving the absence of the mixture toxicity information for anti-TB mixture risk assessment in aquatic environments.

Time-dependent hormetic effects of polypeptide antibiotics and two antibacterial agents contribute to time-dependent cross-phenomena of their binary mixtures

Polypeptide antibiotics (PPAs), silver nanoparticles (plural) (AgNP) and quorum sensing inhibitors (QSIs) are considered to be the ideal antibiotic substitutes. Due to the great potential for the combined use of these antibacterial agents, it is necessary to evaluate their joint effects. In this study, the joint toxic actions for the binary mixtures of PPA + PPA, PPA + AgNP, and PPA + QSI were judged via the independent action (IA) model based on the individual and combined toxicity of test agents to the bioluminescence of Aliivibrio fischeri during 24 h. It was observed that the single agents (PPAs, AgNP, and QSI) and the binary mixtures (PPA + PPA, PPA + AgNP, and PPA + QSI) all triggered the time-dependent hormetic effects on the bioluminescence, where the maximum stimulatory rate, the median effective concentration, and the occurrence of hormesis varied with the increase of time. While bacitracin triggered the maximum stimulatory rate (266.98 % at 8 h) among the single agents, the mixture of capreomycin sulfate and 2-Pyrrolidinone induced the maximum stimulatory rate (262.21 % at 4 h) among the binary mixtures. The cross-phenomenon that the dose-response curve of mixture crossed the corresponding IA curve was observed in all treatments, which also varied with time, exhibiting that the joint toxic actions and corresponding intensities possessed dose- and time-dependent features. Furthermore, three kinds of binary mixtures resulted in three different variation tendencies for the time-dependent cross-phenomena. Mechanistic speculation indicated that test agents possessed the stimulatory modes of action (MOAs) at low-dose and inhibitory MOAs at high-dose to induce the hormetic effects, and the interplays between these MOAs varied with time to trigger the time-dependent cross-phenomenon. This study provides the reference data for the joint effects of PPAs and typical antibacterial agents, which will benefit the application of hormesis in the exploration of time-dependent cross-phenomenon and promote the future development of environmental risk assessment of pollutant mixtures.

Text Mining-Based Suspect Screening for Aquatic Risk Assessment in the Big Data Era: Event-Driven Taxonomy Links Chemical Exposures and Hazards

To improve the accuracy of mixture risk assessment, researchers are employing suspect analysis with expanded lists of contaminants in addition to conventional target lists. However, there are some inherent challenges for these instrument-based analyses, including subjective selection of suspect contaminants, no information for chemical bioactivity, requirements for costly verification, and limited regional coverage. As a supplementary approach, we propose a data-driven suspect screening and risk assessment method informed by mining big data from high-throughput screening bioassay platforms and the refereed literature. The Pearl River Delta (PRD) with main event drivers of arylhydrocarbon receptor (AhR) and oxidative stress (ARE) response was examined. Bioactivity concentrations were collected from the CompTox Chemicals Dashboard, which contained more than 900 000 substances. In addition, exposure metadata from 24 986 literature entries for the environmental occurrence and distribution of contaminants in the PRD over the past three decades were mined. Collectively, a regional distribution map of aquatic hazards induced by AhR- and ARE-active compounds was generated, indicating gradients of low to moderate risks. This study specifically reports a novel big data approach for addressing the increasingly common challenge of objectively selecting analytes during suspect screening, which was recently identified as an urgent research question to advance more sustainable environmental quality.

PFASs: What can we learn from the European Human Biomonitoring Initiative HBM4EU.

Per- and polyfluoroalkyl substances (PFASs) were one of the priority substance groups selected which have been investigated under the ambitious European Joint programme HBM4EU (2017-2022). In order to answer policy relevant questions concerning exposure and health effects of PFASs in Europe several activities were developed under HBM4EU namely i) synthesis of HBM data generated in Europe prior to HBM4EU by developing new platforms, ii) development of a Quality Assurance/Quality Control Program covering 12 biomarkers of PFASs, iii) aligned and harmonized human biomonitoring studies of PFASs. In addition, some cohort studies (on mother-child exposure, occupational exposure to hexavalent chromium) were initiated, and literature researches on risk assessment of mixtures of PFAS, health effects and effect biomarkers were performed. The HBM4EU Aligned Studies have generated internal exposure reference levels for 12 PFASs in 1957 European teenagers aged 12-18 years. The results showed that serum levels of 14.3% of the teenagers exceeded 6.9μg/L PFASs, which corresponds to the EFSA guideline value for a tolerable weekly intake (TWI) of 4.4ng/kg for some of the investigated PFASs (PFOA, PFOS, PFNA and PFHxS). In Northern and Western Europe, 24% of teenagers exceeded this level. The most relevant sources of exposure identified were drinking water and some foods (fish, eggs, offal and locally produced foods). HBM4EU occupational studies also revealed very high levels of PFASs exposure in workers (P95: 192μg/L in chrome plating facilities), highlighting the importance of monitoring PFASs exposure in specific workplaces. In addition, environmental contaminated hotspots causing high exposure to the population were identified. In conclusion, the frequent and high PFASs exposure evidenced by HBM4EU strongly suggests the need to take all possible measures to prevent further contamination of the European population, in addition to adopting remediation measures in hotspot areas, to protect human health and the environment. HBM4EU findings also support the restriction of the whole group of PFASs. Further, research and definition for additional toxicological dose-effect relationship values for more PFASs compounds is needed.

Toxicity Weighting for Human Biomonitoring Mixture Risk Assessment: A Proof of Concept.

Chemical mixture risk assessment has, in the past, primarily focused on exposures quantified in the external environment. Assessing health risks using human biomonitoring (HBM) data provides information on the internal concentration, from which a dose can be derived, of chemicals to which human populations are exposed. This study describes a proof of concept for conducting mixture risk assessment with HBM data, using the population-representative German Environmental Survey (GerES) V as a case study. We first attempted to identify groups of correlated biomarkers (also known as 'communities', reflecting co-occurrence patterns of chemicals) using a network analysis approach (n = 515 individuals) on 51 chemical substances in urine. The underlying question is whether the combined body burden of multiple chemicals is of potential health concern. If so, subsequent questions are which chemicals and which co-occurrence patterns are driving the potential health risks. To address this, a biomonitoring hazard index was developed by summing over hazard quotients, where each biomarker concentration was weighted (divided) by the associated HBM health-based guidance value (HBM-HBGV, HBM value or equivalent). Altogether, for 17 out of the 51 substances, health-based guidance values were available. If the hazard index was higher than 1, then the community was considered of potential health concern and should be evaluated further. Overall, seven communities were identified in the GerES V data. Of the five mixture communities where a hazard index was calculated, the highest hazard community contained N-Acetyl-S-(2-carbamoyl-ethyl)cysteine (AAMA), but this was the only biomarker for which a guidance value was available. Of the other four communities, one included the phthalate metabolites mono-isobutyl phthalate (MiBP) and mono-n-butyl phthalate (MnBP) with high hazard quotients, which led to hazard indices that exceed the value of one in 5.8% of the participants included in the GerES V study. This biological index method can put forward communities of co-occurrence patterns of chemicals on a population level that need further assessment in toxicology or health effects studies. Future mixture risk assessment using HBM data will benefit from additional HBM health-based guidance values based on population studies. Additionally, accounting for different biomonitoring matrices would provide a wider range of exposures. Future hazard index analyses could also take a common mode of action approach, rather than the more agnostic and non-specific approach we have taken in this proof of concept.

Probabilistic ecotoxicological risk assessment of heavy metal and rare earth element mixtures in aquatic biota using the DGT technique in coastal sediments

Heavy metals (HMs) are routine contaminants due to their extensive use worldwide. Rare earth elements (REEs) are emerging contaminants because of their global exploitation for use in the high-tech sector. Diffusive gradients in thin films (DGT) are an effective method for measuring the bioavailable component of pollutants. This study represents the first assessment of the mixture toxicity of HMs and REEs in aquatic biota using the DGT technique in sediments. Xincun Lagoon was chosen as the case study site because it has been contaminated by pollutants. Nonmetric multidimensional scaling (NMS) analysis reveals that a wide variety of pollutants (Cd, Pb, Ni, Cu, InHg, Co, Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Ho, Er, Tm, and Yb) are primarily impacted by sediment characteristics. Appraisal of single HM-REE toxicity reveals that the risk quotient (RQ) values for Y, Yb and Ce notably exceeded 1, demonstrating that the adverse effects of these single HMs and REEs should not be ignored. The combined toxicity of HM-REE mixtures in terms of probabilistic ecological risk assessment shows that the Xincun surface sediments had a medium probability (31.29%) of toxic effects on aquatic biota.

Mixture risk assessment and human biomonitoring: Lessons learnt from HBM4EU.

Unintentional chemical mixtures that are present in the environment are of societal concern as the (environmental) chemicals contained therein, either singly or in combination, may possess properties that are hazardous (toxic) for human health. The current regulatory practice, however, is still largely based on evaluating single chemical substances one-by-one. Over the years various research efforts have delivered tools and approaches for risk assessment of chemical mixtures, but many of these were not considered sufficiently mature for regulatory implementation. This is (partly) due to mixture risk assessment (MRA) being very complex because of the large number of chemicals present in the environment. A key element in risk assessment is information on actual exposures in the population of interest. To date, information on actual personal (internal) mixture exposures is largely absent, severely limiting MRA. The use of human biomonitoring data may improve this situation. Therefore, we investigated within the European Human Biomonitoring Initiative (HBM4EU) various approaches to assess combined exposures and MRA. Based on the insights and lessons learnt in the context of the HBM4EU project, conclusions as well as recommendations for policy development regarding chemical mixtures and for further research were drafted. These conclusions and recommendations relate to both exposure and adverse health effects in humans. The recommendations were discussed with stakeholders in a workshop held in October 2021. There was considerable support and agreement with the spirit, scope and intention of the draft recommendations. Here we describe the lessons learnt on mixture risk assessment through the HBM4EU project and present the final recommendations. Overall, HBM4EU results demonstrated the potential of human biomonitoring as an instrument to obtain insight into the real-life mixtures the human population is exposed to. Also, HBM4EU results demonstrated that chemical mixtures are of public health concern. In the majority of the cases, it was possible to identify risk drivers, i.e. chemicals that contribute more strongly than others to the health risk. The novel approaches to identify co-occurrence patterns demonstrated clusters of co-occurring chemicals; chemicals in these mixture clusters are regulated independently under different legislative frameworks. Moreover, HBM4EU data and expertise can support a science-based derivation of a Mixture Assessment Factor and gauge potential impacts on the population's exposure to chemicals. While further expansion is needed on various aspects of the mixture activities carried out in the context of HBM4EU, application of available methodologies for mixture risk assessment should already be implemented to the degree possible.

Identification of Real-Life Mixtures Using Human Biomonitoring Data: A Proof of Concept Study.

Human health risk assessment of chemical mixtures is complex due to the almost infinite number of possible combinations of chemicals to which people are exposed to on a daily basis. Human biomonitoring (HBM) approaches can provide inter alia information on the chemicals that are in our body at one point in time. Network analysis applied to such data may provide insight into real-life mixtures by visualizing chemical exposure patterns. The identification of groups of more densely correlated biomarkers, so-called "communities", within these networks highlights which combination of substances should be considered in terms of real-life mixtures to which a population is exposed. We applied network analyses to HBM datasets from Belgium, Czech Republic, Germany, and Spain, with the aim to explore its added value for exposure and risk assessment. The datasets varied in study population, study design, and chemicals analysed. Sensitivity analysis was performed to address the influence of different approaches to standardise for creatinine content of urine. Our approach demonstrates that network analysis applied to HBM data of highly varying origin provides useful information with regards to the existence of groups of biomarkers that are densely correlated. This information is relevant for regulatory risk assessment, as well as for the design of relevant mixture exposure experiments.

Human risk associated with exposure to mixtures of antiandrogenic chemicals evaluated using in vitro hazard and human biomonitoring data

BackgroundScientific evidence for underestimated toxicity from unintentional exposure to chemical mixtures is mounting. Yet, harmonized approaches on how to assess the actual risk of mixtures is lacking. As part of the European Joint programme ‘Human Biomonitoring for Europe’ we explored a novel methodology for mixture risk assessment of chemicals affecting male reproductive function. MethodologyWe explored a methodology for chemical mixture risk assessment based on human in vitro data combined with human exposure data, thereby circumventing the drawbacks of using hazard data from rodents and estimated exposure intake levels. Human androgen receptor (hAR) antagonism was selected as the most important molecular initiating event linked to adverse outcomes on male reproductive health. ResultsOur work identified 231 chemicals able to interfere with hAR activity. Among these were 61 finally identified as having both reliable hAR antagonist and human biomonitoring data. Calculation of risk quotients indicated that PCBs (118, 138, 157), phthalates (BBP, DBP, DIBP), benzophenone-3, PFOS, methylparaben, triclosan, some pesticides (i.e cypermethrin, β-endosulfan, methylparathion, p,p-DDE), and a PAH metabolite (1-hydroxypyrene) contributed to the mixture effect. The major chemical mixture drivers were PCB 118, BBP, PFOS, DBP, and the UV filter benzophenone-3, together contributing with 75% of the total mixture effect that was primarily driven by high exposure values. ConclusionsThis viable way forward for mixture risk assessment of chemicals has the advantages of (1) being a more comprehensive mixture risk assessment also covering data-poor chemicals, and (2) including human data only. However, the approach is subjected to uncertainties in terms of in vitro to in vivo extrapolation, it is not ready for decision making, and needs further development. Still, the results indicate a concern for adverse effects on reproductive function in highly exposed boys, especially when considering additional exposure to data-poor chemicals and chemicals acting by other mechanisms of action.

Approaches to mixture risk assessment of PFASs in the European population based on human hazard and biomonitoring data.

Per- and polyfluoroalkyl substances (PFASs) are a highly persistent, mobile, and bioaccumulative class of chemicals, of which emissions into the environment result in long-lasting contamination with high probability for causing adverse effects to human health and the environment. Within the European Biomonitoring Initiative HBM4EU, samples and data were collected in a harmonized way from human biomonitoring (HBM) studies in Europe to derive current exposure data across a geographic spread. We performed mixture risk assessments based on recent internal exposure data of PFASs in European teenagers generated in the HBM4EU Aligned Studies (dataset with N=1957, sampling years 2014-2021). Mixture risk assessments were performed based on three hazard-based approaches: the Hazard Index (HI) approach, the sum value approach as used by the European Food Safety Authority (EFSA) and the Relative Potency Factor (RPF) approach. The HI approach resulted in the highest risk estimates, followed by the RPF approach and the sum value approach. The assessments indicate that PFAS exposure may result in a health risk in a considerable fraction of individuals in the HBM4EU teenager study sample, thereby confirming the conclusion drawn in the recent EFSA scientific opinion. This study underlines that HBM data are of added value in assessing the health risks of aggregate and cumulative exposure to PFASs, as such data are able to reflect exposure from different sources and via different routes.

Internal relative potency factors based on immunotoxicity for the risk assessment of mixtures of per- and polyfluoroalkyl substances (PFAS) in human biomonitoring

Relative potency factors (RPFs) for per- and polyfluoroalkyl substances (PFAS) have previously been derived based on liver effects in rodents for the purpose of performing mixture risk assessment with primary input from biomonitoring studies. However, in 2020, EFSA established a tolerable weekly intake for four PFAS assuming equal toxic potency for immune suppressive effects in humans. In this study we explored the possibility of deriving RPFs for immune suppressive effects using available data in rodents and humans. Lymphoid organ weights, differential blood cell counts, and clinical chemistry from 28-day studies in male rats from the National Toxicology Program (NTP) were combined with modeled serum PFAS concentrations to derive internal RPFs by applying dose–response modelling. Identified functional studies used diverse protocols and were not suitable for derivation of RPFs but were used to support immunotoxicity of PFAS in a qualitative manner. Furthermore, a novel approach was used to estimate internal RPFs based on epidemiological data by dose–response curve fitting optimization, looking at serum antibody concentrations and key cell populations from the National Health and Nutrition Examination Survey (NHANES). Internal RPFs were successfully derived for PFAS based on rat thymus weight, spleen weight, and globulin concentration. The available dose–response information for blood cell counts did not show a significant trend. Immunotoxic potency in serum was determined in the order PFDA > PFNA > PFHxA > PFOS > PFBS > PFOA > PFHxS. The epidemiological data showed inverse associations for the sum of PFOA, PFNA, PFHxS, and PFOS with serum antibody concentrations to mumps and rubella, but the data did not allow for deduction of reliable internal RPF estimates. The internal RPFs for PFAS based on decreased rat lymphoid organ weights are similar to those previously established for increased rat liver weight, strengthening the confidence in the overall applicability of these RPFs.

Adverse Outcome Pathway 'Footprinting': A Novel Approach to the Integration of 21st Century Toxicology Information into Chemical Mixtures Risk Assessment.

For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose-response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP 'footprinting' proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the 'footprint' for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment.

Antibiotic Toxicity Isolated and as Binary Mixture to Freshwater Algae Raphidocelis subcapitata: Growth Inhibition, Prediction Model, and Environmental Risk Assessment.

Antibiotics in aqueous environments can have extremely adverse effects on non-targeted organisms. However, many research projects have only focused on the toxicological evaluation of individual antibiotics in various environments. In the present work, individual and binary mixture toxicity experiments have been conducted with the model organism Raphidocelis subcapitata (R. subcapitata), and a mixture concentration-response curve was established and contrasted with the estimated effects on the basis of both the concentration addition (CA) and the independent action (IA) models. In addition, different risk assessment methods were used and compared to evaluate the environmental risk of binary mixtures. The toxic ranking of the selected antibiotics to R. subcapitata was erythromycin (ERY) > sulfamethoxazole (SMX) > sulfamethazine (SMZ). In general, the conclusion of this study is that the adverse effects of binary mixtures are higher than the individual antibiotics. The CA model and RQSTU are more suitable for toxicity prediction and risk assessment of binary mixtures. This study reveals the potential ecological risks that antibiotics and their mixtures may pose to water ecosystems, thus providing scientific information for environmental quality regulation.

Mixtures of environmental pharmaceuticals in marine organisms: Mechanistic evidence of carbamazepine and valsartan effects on Mytilus galloprovincialis

Unravelling the adverse outcomes of pharmaceuticals mixture represents a research priority to characterize the risk for marine ecosystems. The present study investigated, for the first time, the interactions between two of the most largely detected pharmaceuticals in marine species: carbamazepine (CBZ) and valsartan (VAL), elucidating mechanisms that can modulate bioaccumulation, excretion and the onset of toxicity. Mytilus galloprovincialis were exposed to environmental levels of CBZ and VAL dosed alone or in combination: measurement of drug bioaccumulation was integrated with changes in the whole transcriptome and responsiveness of various biochemical and cellular biomarkers. Interactive and competing mechanisms between tested drugs were revealed by the much higher CBZ accumulation in mussels exposed to this compound alone, while an opposite trend was observed for VAL. A complex network of responses was observed as variations of gene expression, functional effects on neurotransmission, cell cycle, immune responses and redox homeostasis. The elaboration of results through a quantitative Weight of Evidence model summarized a greater biological reactivity of CBZ compared to VAL and antagonistic interactions between these compounds, resulting in a reduced effect of the antiepileptic when combined with valsartan. Overall, new perspectives are highlighted for a more comprehensive risk assessment of environmental mixtures of pharmaceuticals.

Ecological risk assessment of organochlorine pesticide mixture in South China Sea and East China Sea under the effects of seasonal changes and phase-partitioning

Organochlorine pesticides (OCPs), chlorinated hydrocarbon derivatives extensively used in agriculture and chemical industry, have been banned for several decades in most developed countries. However, OCPs act as persistent organic pollutants due to their semi-volatility nature, high ability for wide range transportation and faster bioaccumulation, and thus it has remained as a topical global concern. This study focuses on OCP distributions, sources and associated ecological risks in the globally important OCP source-sink regions of South China Sea (SCS) and East China Sea (ECS). Given the co-exposure of multiple OCPs that undermine the classical risk assessment of single OCP species, a two-tier mixture risk assessment approach has been employed with explicit consideration of seasonal changes and phase-partitioning effects. The results indicate existence of multiple sources varied across the seasons and between the dissolved and particulate phases. Potential sources include the current-use of lindane or historical use of technical HCH, input of technical DDTs, long-range atmospheric transport, and deposition of HCB from land surfaces. There are no wide high-risk zones. Dissolved HCB and DDTs have posed low-to-medium levels of risks broadly distributed across the seasons. Relatively greater risks are observed in summer in the both dissolved and particulate phases. The study has shown the importance of considering mixture risk assessments with the effects of phase-partitioning and seasonal changes for efficient oceanic risk management.

Systematic review of associations of polychlorinated biphenyl (PCB) exposure with declining semen quality in support of the derivation of reference doses for mixture risk assessments

BackgroundMixture risk assessments require reference doses for common health endpoints of all the chemicals to be considered together. In support of a mixture risk assessment for male reproductive health, we conducted a systematic review of the literature on associations between exposures to Polychlorinated Biphenyls (PCBs) and declines in semen quality. PCBs can act as Aryl-hydrocarbon Receptor (AhR)-agonists and Androgen Receptor (AR)-antagonists, both mechanisms which can affect sperm parameters. PCBs and other AR-antagonists can produce additive combination effects. Based on these observations our objective was to systematically gather data from animal and human studies to derive a reference dose for declines in semen quality for individual PCB.MethodsWe systematically reviewed and evaluated the evidence in human epidemiological and experimental animal studies on associations between PCBs and deteriorations in semen quality. Human data and findings from animal studies with PCB mixtures were considered as supporting evidence. Information for individual congeners from animal studies was required for inclusion in mixture risk assessment. Using a robust confidence rating approach, we identified suitable studies to derive reference doses for individual PCB congeners.ResultsEvaluation of human epidemiological studies revealed several reports of adverse effects on sperm parameters linked to PCB exposures, although some studies reported improved semen quality. Our review of experimental animal studies found that treatments with PCBs affected semen quality, in most cases adversely. We found robust evidence that PCB-118 and -169 were linked to declines in semen quality. Evidence for adverse effects of PCB-126, -132, -149, and -153 was moderate, whereas for PCB-77 it was slight and for PCB-180 indeterminate. Using widely accepted risk assessment procedures, we estimated reference dose values of 0.0029 µg/kg/day for PCB-118 and 0.00533 µg/kg/day for PCB-169. In addition, we derived values for PCB-126: 0.000073 µg/kg/day, PCB-132: 0.0228 µg/kg/day, PCB-149: 0.656 µg/kg/day, and PCB-153: 0.0058 µg/kg/day.ConclusionsWe found robust evidence for links between PCB exposure and deteriorations in semen quality, and derived reference doses for a set of congeners. We intend to use these values in combination with congener-specific exposure data in a mixture risk assessment for declines in semen quality, involving several other antiandrogenic chemicals.

Mixture Risk Assessment of Complex Real-Life Mixtures-The PANORAMIX Project.

Humans are involuntarily exposed to hundreds of chemicals that either contaminate our environment and food or are added intentionally to our daily products. These complex mixtures of chemicals may pose a risk to human health. One of the goals of the European Union’s Green Deal and zero-pollution ambition for a toxic-free environment is to tackle the existent gaps in chemical mixture risk assessment by providing scientific grounds that support the implementation of adequate regulatory measures within the EU. We suggest dealing with this challenge by: (1) characterising ‘real-life’ chemical mixtures and determining to what extent they are transferred from the environment to humans via food and water, and from the mother to the foetus; (2) establishing a high-throughput whole-mixture-based in vitro strategy for screening of real-life complex mixtures of organic chemicals extracted from humans using integrated chemical profiling (suspect screening) together with effect-directed analysis; (3) evaluating which human blood levels of chemical mixtures might be of concern for children’s development; and (4) developing a web-based, ready-to-use interface that integrates hazard and exposure data to enable component-based mixture risk estimation. These concepts form the basis of the Green Deal project PANORAMIX, whose ultimate goal is to progress mixture risk assessment of chemicals.