A pragmatic approach for human risk assessment of chemical mixtures

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.

Multiomics reveals new biomarkers and mechanistic insights into the combined toxicity effects of 2,2',4,4',5,5'-hexachlorobiphenyl and atrazine exposures in MCF-7 cells

Humans are constantly exposed to complicated chemical mixtures from the environment and food rather than being exposed to a single pollutant. The underlying mechanisms of the complicated combined toxicity of endocrine disrupting chemicals (EDCs) are still mainly unexplored. In this study, two representative EDCs, 2,2',4,4',5,5'-hexachlorobiphenyl (PCB153) and atrazine (ATZ), were selected to explore their combined effects on MCF-7 cell proliferation at environmental exposure concentrations by an integrated analysis of metabolomics and transcriptomics. The results showed that 1 μM ATZ and PCB153 combined exposure significantly accelerated MCF-7 cell growth by 18.2%. More than 400 metabolites detected by UHPLC-QTOF/MS were used to observe metabolism differences induced by binary mixtures. Metabolomics analysis verified that ATZ and PCB153 exposure alone or in combination could have an additive effect on metabolism and induce significant disruption to glycolysis, purine metabolism and the TCA cycle, which provide energy demand and biosynthetic substrates for cell proliferation. Compared to PCB153 and ATZ exposure alone, a combined effect was observed in purine and pyrimidine metabolic pathways. Hexokinase 3 (HK3) and cytochrome P450 19 subfamily A1 (CYP19A1) were identified as differentially expressed genes based on transcriptomic analysis. By integrating metabolome and transcriptome analysis, the proliferation effects of ATZ and PCB153 were induced at low doses in MCF-7 cells through potential interference with the downstream transcription signaling of CYP19A1. Furthermore, molecular docking indicated that PCB153 and ATZ directly affected CYP19A1. Altogether, the regulation of pivotal metabolites and differentially expressed genes could provide helpful information to reveal the mechanism by which PCB153 and ATZ affect MCF-7 cell proliferation.

Identification of phthalate mixture exposure targets in the human and mouse ovary in vitro

Chemical health risk assessment is based on single chemicals, but humans and wildlife are exposed to extensive mixtures of industrial substances and pharmaceuticals. Such exposures are life-long and correlate with multiple morbidities, including infertility. How combinatorial effects of chemicals should be handled in hazard characterization and risk assessment are open questions. Further, test systems are missing for several relevant health outcomes including reproductive health and fertility in women. Here, our aim was to screen multiple ovarian cell models for phthalate induced effects to identify biomarkers of exposure. We used an epidemiological cohort study to define different phthalate mixtures for in vitro testing. The mixtures were then tested in five cell models representing ovarian granulosa or stromal cells, namely COV434, KGN, primary human granulosa cells, primary mouse granulosa cells, and primary human ovarian stromal cells. Exposures at epidemiologically relevant levels did not markedly elicit cytotoxicity or affect steroidogenesis in short 24-hour exposure. However, significant effects on gene expression were identified by RNA-sequencing. Altogether, the exposures changed the expression of 124 genes on the average (9-479 genes per exposure) in human cell models, without obvious concentration or mixture-dependent effects on gene numbers. The mixtures stimulated distinct changes in different cell models. Despite differences, our analyses suggest commonalities in responses towards phthalates, which forms a starting point for follow-up studies on identification and validation of candidate biomarkers that could be developed to novel assays for regulatory testing or even into clinical tests.

A proteomics dataset capturing myeloid cell responses upon cellular exposure to fungicides, adjuvants and fungicide formulations

Dendritic cells are the sentinels of the immune system, linking the innate and adaptive immune response. Myeloid and dendritic cell models have been successfully used in in vitro approaches to predict adverse outcomes such as skin sensitization. We here exposed a well-characterized human dendritic cell-like cell line to agricultural chemicals, including fungicide formulations, active ingredients, adjuvants and defined mixtures for 24 h to profile induced changes on protein levels. Cell pellets were harvested and prepared for bottom-up label-free analysis with peptide separation on an EASY-nano LC system 1200 coupled online with a QExactive HF-X mass spectrometer with data-dependent acquisition (DDA). The raw data files and processed quantitative data have been deposited to ProteomeXchange with the data identification number PXD034624 and are described here. The data in this article may serve as a resource for researchers interested in e.g. human toxicology, immunology, cell biology and pharmacology.

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.

Recent Trends in Multiclass Analysis of Emerging Endocrine Disrupting Contaminants (EDCs) in Drinking Water

Ingestion of water is a major route of human exposure to environmental contaminants. There have been numerous studies exploring the different compounds present in drinking water, with recent attention drawn to a new class of emerging contaminants: endocrine-disrupting compounds (EDCs). EDCs encompass a broad range of physio-chemically diverse compounds; from naturally occurring to manmade. Environmentally, EDCs are found as mixtures containing multiple classes at trace amounts. Human exposure to EDCs, even at low concentrations, is known to lead to adverse health effects. Therefore, the ability to evaluate EDC contamination with a high degree of sensitivity and accuracy is of the utmost importance. This review includes (i) discussion on the perceived and actual risks associated with EDC exposure (ii) regulatory actions that look to limit EDC contamination (iii) analytical methods, including sample preparation, instrumentation and bioassays that have been advanced and employed for multiclass EDC identification and quantitation.

Combined Exposure to Multiple Mycotoxins: An Example of Using a Tiered Approach in a Mixture Risk Assessment

Humans are exposed to mycotoxins on a regular basis. Exposure to a mixture of mycotoxins may, therefore, result in a combination of adverse effects, or trigger the same effects. This should be accounted for when assessing the combined risk of multiple mycotoxins. Here, we show the outcome of using different approaches in assessing the risks related to the combined exposure to mycotoxins. We performed a tiered approach using assessment groups with a common target organ (kidney, liver and haematologic system), or a common adverse effect (phenomenon) (reduced white blood cell count), to combine the exposure to mycotoxins. The combined exposure was calculated for the individuals in this assessment, using the Monte Carlo Risk Assessment (MCRA) tool. The risk related to this combined exposure was assessed using toxicological reference values, e.g., health based guidance values. We show that estimating the combined risk by adding the single compounds’ risk distributions slightly overestimates the combined risk in the 95th percentile, as compared to combining the exposures at an individual level. We also show that relative potency factors can be used to refine the mixture risk assessment, as compared to ratios of toxicological reference values with different effect sizes and assessment factors.

Risk assessment of chemical mixtures by benchmark dose-principle component analysis approach in occupational exposure

Mixtures of organic solvents are widely used in industrial processes. Risk assessment for chemical co-exposure has always been a challenge in past years. The present study aims to employ principle component analysis (PCA) to produce an entry for benchmark dose approximation in shoemakers based on the color vision effect. A total of 134 subjects consisting of 67 shoemakers and 67 staff workers were employed for Benchmark Dose (BMD) evaluation. Occupational exposure to benzene, toluene, xylene, and n-hexane was evaluated using NIOSH 1501 and OSHA ID-07 methods. The color vision effect was quantified using Lanthony D-15 desaturated test (D-15d). PCA was run for cumulative exposure dose (CED) of the solvents by MATLAB 2018. Finally, the lowest 95% confidence limit of the benchmark dose (BMDL) was determined using US EPA benchmark dose software (BMDS) version 3.2.1. The color confusion index (CCI) level in shoemakers increased from 1 to 1.15 by a median of 1.07. There was a significant difference in the CCI level (p value<0.0001) between exposed and control subjects. The first score of PCA was used as intake dose level (IDL) in solvents co-exposure. Using BMD analysis, the log-logistics model was fitted with a p-value> 0.1 and the lowest BMDL level. BMDL level was evaluated at 1.63, 10.25, 2.21, and 3.35 ppm for benzene, toluene, xylene, and n-hexane, respectively. The results showed a risk of color vision effect with co-exposure to solvents at different levels in the occupational exposure standards. In conclusion BMDL-PCA approach has been suggested for the risk assessment of chemical co-exposure.

Chemical Mixture Calculator - A novel tool for mixture risk assessment

Humans are continuously exposed to complex chemical mixtures from foods and the environment. Experimental models in vivo and in vitro have increased our knowledge on how we can predict mixture effects. To accommodate a need for tools for efficient mixture risk assessment across different chemical classes and exposure sources, we have developed fit-for-purpose criteria for grouping of chemicals and a web-based tool for mixture risk assessment. The Chemical Mixture Calculator (available at www.chemicalmixturecalculator.dk) can be used for mixture risk assessment or identification of main drivers of risk. The underlying database includes hazard and exposure estimates for more than 200 chemicals in foods and environment. We present a range of cumulative assessment groups for effects on haematological system, kidney, liver, nervous system, developmental and reproductive system, and thyroid. These cumulative assessment groups are useful for grouping of chemicals at several levels of refinement depending on the question addressed. We present a mixture risk assessment case for phthalates, evaluated with and without contributions from other chemicals with similar effects. This case study shows the usefulness of the tool as a starting point for mixture risk assessment by the risk assessor, and emphasizes that solid scientific insight regarding underlying assumptions and uncertainties is crucial for result interpretation.

Network Analysis to Identify Communities Among Multiple Exposure Biomarkers Measured at Birth in Three Flemish General Population Samples

Introduction: Humans are exposed to multiple environmental chemicals via different sources resulting in complex real-life exposure patterns. Insight into these patterns is important for applications such as linkage to health effects and (mixture) risk assessment. By providing internal exposure levels of (metabolites of) chemicals, biomonitoring studies can provide snapshots of exposure patterns and factors that drive them. Presentation of biomonitoring data in networks facilitates the detection of such exposure patterns and allows for the systematic comparison of observed exposure patterns between datasets and strata within datasets. Methods: We demonstrate the use of network techniques in human biomonitoring data from cord blood samples collected in three campaigns of the Flemish Environment and Health Studies (FLEHS) (sampling years resp. 2002-2004, 2008-2009, and 2013-2014). Measured biomarkers were multiple organochlorine compounds, PFAS and metals. Comparative network analysis (CNA) was conducted to systematically compare networks between sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Results: Network techniques offered an intuitive approach to visualize complex correlation structures within human biomonitoring data. The identification of groups of highly connected biomarkers, "communities," within these networks highlighted which biomarkers should be considered collectively in the analysis and interpretation of epidemiological studies or in the design of toxicological mixture studies. Network analyses demonstrated in our example to which extent biomarker networks and its communities changed across the sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Conclusion: Network analysis is a data-driven and intuitive screening method when dealing with multiple exposure biomarkers, which can easily be upscaled to high dimensional HBM datasets, and can inform mixture risk assessment approaches.

Receptor-based in vitro activities to assess human exposure to chemical mixtures and related health impacts

Humans are exposed to a large number of chemicals from sources such as the environment, food, and consumer products. There is growing concern that human exposure to chemical mixtures, especially during critical periods of development, increases the risk of adverse health effects in newborns or later in life. Historically, the one-chemical-at-a-time approach has been applied both for exposure assessment and hazard characterisation, leading to insufficient knowledge about human health effects caused by exposure to mixtures of chemicals that have the same target. To circumvent this challenge researchers can apply in vitro assays to analyse both exposure to and human health effects of chemical mixtures in biological samples. The advantages of using in vitro assays are: (i) that an integrated effect is measured, taking combined mixture effects into account and (ii) that in vitro assays can reduce complexity in identification of Chemicals of Emerging Concern (CECs) in human tissues. We have reviewed the state-of-the-art on the use of receptor-based in vitro assays to assess human exposure to chemical mixtures and related health impacts. A total of 43 studies were identified, in which endpoints for the arylhydrocarbon receptor (AhR), the estrogen receptor (ER), and the androgen receptor (AR) were used. The majority of studies reported biological activities that could be associated with breast cancer incidence, male reproductive health effects, developmental toxicities, human demographic characteristics or lifestyle factors such as dietary patterns. A few studies used the bioactivities to check the coverage of the chemical analyses of the human samples, whereas in vitro assays have so far not regularly been used for identifying CECs in human samples, but rather in environmental matrices or food packaging materials. A huge field of novel applications using receptor-based in vitro assays for mixture toxicity assessment on human samples and effect-directed analysis (EDA) using high resolution mass spectrometry (HRMS) for identification of toxic compounds waits for exploration. In the future this could lead to a paradigm shift in the way we unravel adverse human health effects caused by chemical mixtures.

Mining the effect of the neonicotinoids imidacloprid and clothianidin on the chemical homeostasis and energy equilibrium of primary mouse neural stem/progenitor cells using metabolomics

The projection of plant protection products' (PPPs) toxicity to non-target organisms at early stages of their development is challenging and demanding. Recent developments in bioanalytics, however, have facilitated the study of fluctuations in the metabolism of biological systems in response to treatments with bioactives and the discovery of corresponding toxicity biomarkers. Neonicotinoids are improved insecticides that target nicotinic acetylocholine receptors (nAChR) in insects which are similar to mammals. Nonetheless, they have sparked controversy due to effects on non-target organisms. Within this context, mammalian cell cultures represent ideal systems for the development of robust models for the dissection of PPPs' toxicity. Thus, we have investigated the toxicity of imidacloprid, clothianidin, and their mixture on primary mouse (Mus musculus) neural stem/progenitor (NSPCs) and mouse neuroblastoma-derived Neuro-2a (N2a) cells, and the undergoing metabolic changes applying metabolomics. Results revealed that NSPCs, which in vitro resemble those that reside in the postnatal and adult central nervous system, are five to seven-fold more sensitive than N2a to the applied insecticides. The energy equilibrium of NSPCs was substantially altered, as it is indicated by fluctuations of metabolites involved in energy production (e.g. glucose, lactate), Krebs cycle intermediates, and fatty acids, which are important components of cell membranes. Such evidence plausibly suggests a switch of cells' energy-producing mechanism to the direct metabolism of glucose to lactate in response to insecticides. The developed pipeline could be further exploited in the discovery of unintended effects of PPPs at early steps of development and for regulatory purposes.

Grouping of endocrine disrupting chemicals for mixture risk assessment - Evidence from a rat study

Exposure to mixtures of endocrine disrupting chemicals may contribute to the rising incidence of hormone-related diseases in humans. Real-life mixtures are complex, comprised of chemicals with mixed modes of action, and essential knowledge is often lacking on how to group such chemicals into cumulative assessment groups, which is an essential prerequisite to conduct a chemical mixture risk assessment. We investigated if mixtures of chemicals with diverse endocrine modes of action can cause mixture effects on hormone sensitive endpoints in developing and adult rat offspring after perinatal exposure. Wistar rats were exposed during pregnancy and lactation simultaneously to either bisphenol A and butylparaben (Emix), diethylhexyl phthalate and procymidone (Amix), or a mixture of all four substances (Totalmix). In male offspring, the anogenital distance was significantly reduced and nipple retention increased in animals exposed to Amix and Totalmix, and the mixture effects were well approximated by the dose addition model. The combination of Amix and Emix responded with more marked changes on these and other endocrine-sensitive endpoints than each binary mixture on its own. Sperm counts were reduced by all exposures. These experimental outcomes suggest that the grouping of chemicals for mixture risk assessment should be based on common health outcomes rather than only similar modes or mechanisms of action. Mechanistic-based approaches such as the concept of Adverse Outcome Pathway (AOP) can provide important guidance if both the information on shared target tissues and the information on shared mode/mechanism of action are taken into account.

Public data sources to support systems toxicology applications

Public databases provide a wealth of freely available information about chemicals, genes, proteins, biological networks, phenotypes, diseases, and exposure science that can be integrated to construct pathways for systems toxicology applications. Relating this disparate information from public repositories, however, can be challenging since databases use a variety of ways to represent, describe, and make available their content. The use of standard vocabularies to annotate key data concepts, however, allows the information to be more easily exchanged and combined for discovery of new findings. We explore some of the many public data sources currently available to support systems toxicology, and demonstrate the value of standardizing data to help construct chemical-induced outcome pathways.