Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology

Zooplankton-based adverse outcome pathways: A tool for assessing endocrine disrupting compounds in aquatic environments

Endocrine disrupting compounds (EDCs) pose a significant ecological risk, particularly in aquatic ecosystems. EDCs have become a focal point in ecotoxicology, and their identification and regulation have become a priority. Zooplankton have gained global recognition as bioindicators, benefiting from rigorous standardization and regulatory validation processes. This review aims to provide a comprehensive summary of zooplankton-based adverse outcome pathways (AOPs) with a focus on EDCs as toxicants and the utilisation of freshwater zooplankton as bioindicators in ecotoxicological assessments. This review presents case studies in which zooplankton have been used in the development of AOPs, emphasizing the identification of molecular initiating events (MIEs) and key events (KEs) specific to zooplankton exposed to EDCs. Zooplankton-based AOPs may become an important resource for understanding the intricate processes by which EDCs impair the endocrine system. Furthermore, the data sources, experimental approaches, advantages, and challenges associated with zooplankton-based AOPs are discussed. Zooplankton-based AOPs framework can provide vital tools for consolidating toxicological knowledge into a structured toxicity pathway of EDCs, offering a transformative platform for facilitating enhanced risk assessment and chemical regulation.

The database makes the poison: How the selection of datasets in QSAR models impacts toxicant prediction of higher tier endpoints

As the United States and the European Union continue their steady march towards the acceptance of new approach methodologies (NAMs), we need to ensure that the available tools are fit for purpose. Critics will be well-positioned to caution against NAMs acceptance and adoption if the tools turn out to be inadequate. In this paper, we focus on Quantitative Structure Activity-Relationship (QSAR) models and highlight how the training database affects quality and performance of these models. Our analysis goes to the point of asking, "are the endpoints extracted from the experimental studies in the database trustworthy, or are they false negatives/positives themselves?" We also discuss the impacts of chemistry on QSAR models, including issues with 2-D structure analyses when dealing with isomers, metabolism, and toxicokinetics. We close our analysis with a discussion of challenges associated with translational toxicology, specifically the lack of adverse outcome pathways/adverse outcome pathway networks (AOPs/AOPNs) for many higher tier endpoints. We recognize that it takes a collaborate effort to build better and higher quality QSAR models especially for higher tier toxicological endpoints. Hence, it is critical to bring toxicologists, statisticians, and machine learning specialists together to discuss and solve these challenges to get relevant predictions.

Projection of Interspecific Competition (PIC) Matrices: A Conceptual Framework for Inclusion in Population Risk Assessments

Accounting for intraspecific and interspecific competition when assessing the effects of chemical and nonchemical stressors is an important uncertainty in ecological risk assessments. We developed novel projection of interspecific competition (PIC) matrices that allow for analysis of population dynamics of two or more species exposed to a given stressor(s) that compete for shared resources within a landscape. We demonstrate the application of PIC matrices to investigate the population dynamics of two hypothetical fish species that compete with one another and have differences in net reproductive rate and intrinsic rate of population increase. Population status predictions were made under scenarios that included exposure to a chemical stressor that reduced fecundity for one or both species. The results of our simulations demonstrated that measures obtained from the life table and Leslie matrix of an organism, including net reproductive rate and intrinsic rate of increase, can result in erroneous conclusions of population status and viability in the absence of a consideration of resource limitation and interspecific competition. This modeling approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects due to stressors to possible outcomes within an ecosystem. In addition, PIC matrices could be combined with adverse outcome pathways to allow for ecosystem projection based on taxonomic conservation of molecular targets of chemicals to predict the likelihood of relative cross-species susceptibility. Overall, the present study shows how PIC matrices can integrate effects across the life cycles of multiple species, provide a linkage between endpoints observed in individual and population-level responses, and project outcomes at the community level for multiple generations for multiple species that compete for limited resources. Environ Toxicol Chem 2024;43:1406-1422. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.

Developing an Approach for Integrating Chemical Analysis and Transcriptional Changes to Assess Contaminants in Water, Sediment, and Fish

Pharmaceuticals in aquatic environments pose threats to aquatic organisms because of their continuous release and potential accumulation. Monitoring methods for these contaminants are inadequate, with targeted analyses falling short in assessing water quality's impact on biota. The present study advocates for integrated strategies combining suspect and targeted chemical analyses with molecular biomarker approaches to better understand the risks posed by complex chemical mixtures to nontarget organisms. The research aimed to integrate chemical analysis and transcriptome changes in fathead minnows to prioritize contaminants, assess their effects, and apply this strategy in Wascana Creek, Canada. Analysis revealed higher pharmaceutical concentrations downstream of a wastewater-treatment plant, with clozapine being the most abundant in fathead minnows, showing notable bioavailability from water and sediment sources. Considering the importance of bioaccumulation factor and biota-sediment accumulation factor in risk assessment, these coefficients were calculated based on field data collected during spring, summer, and fall seasons in 2021. Bioaccumulation was classified as very bioaccumulative with values >5000 L kg-1, suggesting the ability of pharmaceuticals to accumulate in aquatic organisms. The study highlighted the intricate relationship between nutrient availability, water quality, and key pathways affected by pharmaceuticals, personal care products, and rubber components. Prioritization of these chemicals was done through suspect analysis, supported by identifying perturbed pathways (specifically signaling and cellular processes) using transcriptomic analysis in exposed fish. This strategy not only aids in environmental risk assessment but also serves as a practical model for other watersheds, streamlining risk-assessment processes to identify environmental hazards and work toward reducing risks from contaminants of emerging concern. Environ Toxicol Chem 2024;00:1-22. © 2024 SETAC.

Single-cell and multi-omics analyses highlight cancer-associated fibroblasts-induced immune evasion and epithelial mesenchymal transition for smoking bladder cancer

Tobacco carcinogens are recognized as critical hazard factors for bladder tumorigenesis, affecting the prognosis of patients through aromatic amines components. However, the specific function of tobacco carcinogens and systematic assessment models in the prognosis of bladder cancer remains poorly elucidated. We retrieved bladder cancer specific tobacco carcinogens-related genes from Comparative Toxicogenomic Database, our Nanjing Bladder Cancer cohort and TCGA database. Gene×Gene interaction method was utilized to establish a prognostic signature. Integrative assessment of immunogenomics, tumor microenvironments and single-cell RNA-sequencing were performed to illustrate the internal relations of key events from different levels. Finally, we comprehensively identified 33 essential tobacco carcinogens-related genes to construct a novel prognostic signature, and found that high-risk patients were characterized by significantly worse overall survival (HR=2.25; Plog-rank < 0.01). Single-cell RNA-sequencing and multi-omics analysis demonstrated that cancer-associated fibroblasts mediated the crosstalk between epithelial-mesenchymal transition progression and immune evasion. Moreover, an adverse outcome pathway framework was established to facilitate our understanding to the tobacco carcinogens-triggered bladder tumorigenesis. Our study systematically provided immune microenvironmental alternations for smoking-induced adverse survival outcomes in bladder cancer. These findings facilitated the integrative multi-omics insights into risk assessment and toxic mechanisms of tobacco carcinogens.

An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity

Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium from five exposome-relevant databases using a data-centric approach, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs). By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.

Beyond Encapsulation: Exploring Macrophage-Fibroblast Cross Talk in Implant-Induced Fibrosis

The foreign body response (FBR) and organ fibrosis are complex biological processes involving the interaction between macrophages and fibroblasts. Understanding the molecular mechanisms underlying macrophage-fibroblast cross talk is crucial for developing strategies to mitigate implant encapsulation, a major cause of implant failure. This article reviews the current knowledge on the role of macrophages and fibroblasts in the FBR and organ fibrosis, highlighting the similarities between these processes. The FBR is characterized by the formation of a fibrotic tissue capsule around the implant, leading to functional impairment. Various factors, including material properties such as surface chemistry, stiffness, and topography, influence the degree of encapsulation. Cross talk between macrophages and fibroblasts plays a critical role in both the FBR and organ fibrosis. However, the precise molecular mechanisms remain poorly understood. Macrophages secrete a wide range of cytokines that modulate fibroblast behavior such as abundant collagen deposition and myofibroblast differentiation. However, the heterogeneity of macrophages and fibroblasts and their dynamic behavior in different tissue environments add complexity to this cross talk. Experimental evidence from in vitro studies demonstrates the impact of material properties on macrophage cytokine secretion and fibroblast physiology. However, the correlation between in vitro response and in vivo encapsulation outcomes is not robust. Adverse outcome pathways (AOPs) offer a potential framework to understand and predict process complexity. AOPs describe causal relationships between measurable events leading to adverse outcomes, providing mechanistic insights for in vitro testing and predictive modeling. However, the development of an AOP for the FBR does require a comprehensive understanding of the molecular initiating events and key event relationships to identify which events are essential. In this article, we describe the current knowledge on macrophage-fibroblast cross talk in the FBR and discuss how targeted research can help build an AOP for implant-related fibrosis.

Cross-Species Extrapolation of Biological Data to Guide the Environmental Safety Assessment of Pharmaceuticals-The State of the Art and Future Priorities

The extrapolation of biological data across species is a key aspect of biomedical research and drug development. In this context, comparative biology considerations are applied with the goal of understanding human disease and guiding the development of effective and safe medicines. However, the widespread occurrence of pharmaceuticals in the environment and the need to assess the risk posed to wildlife have prompted a renewed interest in the extrapolation of pharmacological and toxicological data across the entire tree of life. To address this challenge, a biological "read-across" approach, based on the use of mammalian data to inform toxicity predictions in wildlife species, has been proposed as an effective way to streamline the environmental safety assessment of pharmaceuticals. Yet, how effective has this approach been, and are we any closer to being able to accurately predict environmental risk based on known human risk? We discuss the main theoretical and experimental advancements achieved in the last 10 years of research in this field. We propose that a better understanding of the functional conservation of drug targets across species and of the quantitative relationship between target modulation and adverse effects should be considered as future research priorities. This pharmacodynamic focus should be complemented with the application of higher-throughput experimental and computational approaches to accelerate the prediction of internal exposure dynamics. The translation of comparative (eco)toxicology research into real-world applications, however, relies on the (limited) availability of experts with the skill set needed to navigate the complexity of the problem; hence, we also call for synergistic multistakeholder efforts to support and strengthen comparative toxicology research and education at a global level. Environ Toxicol Chem 2024;43:513-525. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Quantitative modeling of in vitro data using an adverse outcome pathway for the risk assessment of decreased lung function in humans

In the absence of epidemiological data, there is a need to develop computational models that convert in vitro findings to human disease risk predictions following toxicant exposure. In such efforts, in vitro data can be evaluated in the context of adverse outcome pathways (AOPs) that organize mechanistic knowledge based on empirical evidence into a sequence of molecular-, cellular-, tissue-, and organ-level key events that precede an adverse outcome (AO). Here we combined data from advanced in vitro organotypic airway models exposed to combustible cigarette (CC) smoke or Tobacco Heating System (THS) aerosol with an AOP for increased oxidative stress leads to decreased lung function. The mathematical modeling predicted reduced risk of decreased ciliary beating frequency (CBF) based on oxidative stress measurements and reduced risk of decreased mucociliary clearance (MCC) based on CBF measurements in THS aerosol- compared with CC smoke-exposed cultures. To extend the predictions to the AO of decreased lung function, we leveraged human MCC data from current smokers, nonsmokers, former smokers, and users of heated tobacco products. This approach provided a plausible prediction of diminished reduction in lung function in response to THS use compared with continued smoking. The current approach may also present a basis for an integrated approach to testing and assessment of tobacco products for future regulatory decision-making.

Linking Mechanistic Effects of Pharmaceuticals and Personal Care Products to Ecologically Relevant Outcomes: A Decade of Progress

There are insufficient toxicity data to assess the ecological risks of many pharmaceuticals and personal care products (PPCPs). While data limitations are not uncommon for contaminants of environmental concern, PPCPs are somewhat unique in that an a priori understanding of their biological activities in conjunction with measurements of molecular, biochemical, or histological responses could provide a foundation for understanding mode(s) of action and predicting potential adverse apical effects. Over the past decade significant progress has been made in the development of new approach methodologies (NAMs) to efficiently quantify these types of endpoints using computational models and pathway-based in vitro and in vivo assays. The availability of open-access knowledgebases to curate biological response (including NAM) data and sophisticated bioinformatics tools to help interpret the information also has significantly increased. Finally, advances in the development and implementation of the adverse outcome pathway framework provide the critical conceptual underpinnings needed to translate NAM data into predictions of the ecologically relevant outcomes required by risk assessors and managers. The evolution and convergence of these various data streams, tools, and concepts provides the basis for a fundamental change in how ecological risks of PPCPs can be pragmatically assessed. Environ Toxicol Chem 2024;43:537-548. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Towards Precision Ecotoxicology: Leveraging Evolutionary Conservation of Pharmaceutical and Personal Care Product Targets to Understand Adverse Outcomes Across Species and Life Stages

Translation of environmental science to the practice aims to protect biodiversity and ecosystem services, and our future ability to do so relies on the development of a precision ecotoxicology approach wherein we leverage the genetics and informatics of species to better understand and manage the risks of global pollution. A little over a decade ago, a workshop focusing on the risks of pharmaceuticals and personal care products (PPCPs) in the environment identified a priority research question, "What can be learned about the evolutionary conservation of PPCP targets across species and life stages in the context of potential adverse outcomes and effects?" We review the activities in this area over the past decade, consider prospects of more recent developments, and identify future research needs to develop next-generation approaches for PPCPs and other global chemicals and waste challenges. Environ Toxicol Chem 2024;43:526-536. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Proof of concept for quantitative adverse outcome pathway modeling of chronic toxicity in repeated exposure

Adverse Outcome Pathway (AOP) is a useful tool to glean mode of action (MOE) of a chemical. However, in order to use it for the purpose of risk assessment, an AOP needs to be quantified using in vitro or in vivo data. Majority of quantitative AOPs developed so far, were for single exposure to progressively higher doses. Limited attempts were made to include time in the modeling. Here as a proof-of concept, we developed a hypothetical AOP, and quantified it using a virtual dataset for six repeated exposures using a Bayesian Network Analysis (BN) framework. The virtual data was generated using realistic assumptions. Effects of each exposure were analyzed separately using a static BN model and analyzed in combination using a dynamic BN (DBN) model. Our work shows that the DBN model can be used to calculate the probability of adverse outcome when other upstream KEs were observed earlier. These probabilities can help in identification of early indicators of AO. In addition, we also developed a data driven AOP pruning technique using a lasso-based subset selection, and show that the causal structure of AOP is itself dynamic and changes over time. This proof-of-concept study revealed the possibility for expanding the applicability of the AOP framework to incorporate biological dynamism in toxicity appearance by repeated insults.

Polystyrene micro- and nanoplastics induce gastric toxicity through ROS mediated oxidative stress and P62/Keap1/Nrf2 pathway

Microplastics (MPs) exist widely in the environment and can enter the human body indirectly through the food chain or directly through inhalation or ingestion. The primary organ that MPs contaminated food or water enters the human body through the digestive tract is the stomach. However, at present, the effects of MPs on the stomach and the related mechanism remain unclear. In this study, our results indicated that 50 nm and 250 nm polystyrene MPs (PS-MPs) at environmental related dose significantly decreased stomach organ coefficient, inhibited gastric juice secretion and mucus secretion, disrupted gastric barrier function and suppressed antioxidant ability in mice. In vitro experiments showed that PS-MPs inhibited cell viability, increased ROS generation, and induced apoptosis through mitochondria-dependent pathway. Simultaneously, PS-MPs also decreased mitochondrial membrane potential, ATP level, disrupted mitochondrial kinetic homeostasis, and activated P62 / Nrf2 / Keap1 pathway. Furthermore, blocking ROS (NAC) partially alleviated ROS and apoptosis caused by PS-MPs. Based on above findings, the potential adverse outcome pathway (AOP) of PS-MPs-caused gastric toxicity was proposed which provides a new insight into the risk assessment of MP related gastric damage. Our study unveils the gastric injury induced by PS MPs is dependent on ROS - mediated P62 / Nrf2 / Keap1 signaling pathway, and provides scientific basis for further exploration the mechanism of gastric toxicity of PS MPs.

Embryonic Exposure to the Benzotriazole Ultraviolet Stabilizer 2-(2H-benzotriazol-2-yl)-4-methylphenol Decreases Fertility of Adult Zebrafish (Danio rerio)

Benzotriazole ultraviolet stabilizers (BUVSs) are emerging contaminants of concern. They are added to a variety of products, including building materials, personal care products, paints, and plastics, to prevent degradation caused by ultraviolet (UV) light. Despite widespread occurrence in aquatic environments, little is known regarding the effects of BUVSs on aquatic organisms. The aim of the present study was to characterize the effects of exposure to 2-(2H-benzotriazol-2-yl)-4-methylphenol (UV-P) on the reproductive success of zebrafish (Danio rerio) following embryonic exposure. Embryos were exposed, by use of microinjection, to UV-P at <1.5 (control), 2.77, and 24.25 ng/g egg, and reared until sexual maturity, when reproductive performance was assessed, following which molecular and biochemical endpoints were analyzed. Exposure to UV-P did not have a significant effect on fecundity. However, there was a significant effect on fertilization success. Using UV-P-exposed males and females, fertility was decreased by 8.75% in the low treatment group and by 15.02% in the high treatment group relative to control. In a reproduction assay with UV-P-exposed males and control females, fertility was decreased by 11.47% in the high treatment group relative to the control. Embryonic exposure to UV-P might have perturbed male sex steroid synthesis as indicated by small changes in blood plasma concentrations of 17β-estradiol and 11-ketotestosterone, and small statistically nonsignificant decreases in mRNA abundances of cyp19a1a, cyp11c1, and hsd17b3. In addition, decreased transcript abundances of genes involved in spermatogenesis, such as nanos2 and dazl, were observed. Decreases in later stages of sperm development were observed, suggesting that embryonic exposure to UV-P impaired spematogenesis, resulting in decreased sperm quantity. The present study is the first to demonstrate latent effects of BUVSs, specifically on fish reproduction. Environ Toxicol Chem 2024;43:385-397. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Construction of an adverse outcome pathway framework based on integrated data to evaluate arsenic-induced non-alcoholic fatty liver disease

Arsenic is a recognized environmental pollutant naturally occurring in aquifers through geological processes. Toxicological studies have revealed that liver is the main target organ harmed by arsenic exposure. However, systematic studies of non-alcoholic fatty liver disease (NAFLD) are not comprehensive, and information regarding threats and risk assessment remains insufficient. This research aimed to examine the association between arsenic exposure and NAFLD and uncover the role of molecular initiating events and key events in disease development using the Adverse Outcome Pathway (AOP). Data from 8,104 adults in the National Health and Nutrition Examination Survey were used to explore the relationship between urinary arsenic and NAFLD. In a logistic regression model, urinary inorganic arsenic levels positively correlated with NAFLD (odds ratio = 1.12, 95 % confidence interval = 1.07-1.16). Subsequently, to gain a deeper understanding of arsenic-induced NAFLD, an AOP framework was constructed, revealing that arsenic exposure led to elevate levels of TNF-α, which regulated the NF-κB pathway and led to hepatic lipid deposition, causing NAFLD. This AOP was assessed as "high" according to the Organization for Economic Co-operation and Development users' handbook, and in vitro and in vivo models validated the AOP framework. In summary, this study highlights the potential mechanisms of arsenic-induced NAFLD. We combined the AOP with classical toxicological approaches with a view of establishing, rapidly and accurately, the lowest level at which environmental arsenic exposure can have adverse effects on the body, thereby contributing to risk assessment strategies for arsenic exposure through iterative and animal modeling at the population level.

Editorial trend: adverse outcome pathway (AOP) and computational strategy - towards new perspectives in ecotoxicology

The adverse outcome pathway (AOP) has been conceptualized in 2010 as an analytical construct to describe a sequential chain of causal links between key events, from a molecular initiating event leading to an adverse outcome (AO), considering several levels of biological organization. An AOP aims to identify and organize available knowledge about toxic effects of chemicals and drugs, either in ecotoxicology or toxicology, and it can be helpful in both basic and applied research and serve as a decision-making tool in support of regulatory risk assessment. The AOP concept has evolved since its introduction, and recent research in toxicology, based on integrative systems biology and artificial intelligence, gave it a new dimension. This innovative in silico strategy can help to decipher mechanisms of action and AOP and offers new perspectives in AOP development. However, to date, this strategy has not yet been applied to ecotoxicology. In this context, the main objective of this short article is to discuss the relevance and feasibility of transferring this strategy to ecotoxicology. One of the challenges to be discussed is the level of organisation that is relevant to address for the AO (population/community). This strategy also offers many advantages that could be fruitful in ecotoxicology and overcome the lack of time, such as the rapid identification of data available at a time t, or the identification of "data gaps". Finally, this article proposes a step forward with suggested priority topics in ecotoxicology that could benefit from this strategy.

Impairment of oocyte maturation as a mechanism of decreased fecundity in Japanese medaka (Oryzias latipes) exposed to the brominated flame retardant, 1,2,5,6-tetrabromocyclooctane (TBCO)

Inhibition of oocyte maturation is an understudied mechanism by which chemical stressors can impair fecundity of female fishes. The primary objective of the present study was to develop an assay to assess oocyte maturation disruption by chemical stressors in Japanese medaka (Oryzias latipes). First, an in vitro assay to assess maturation inducing hormone (MIH)-stimulated oocyte maturation in zebrafish was validated for use with Japanese medaka. Next, using the brominated flame retardant, 1,2,5,6-tetrabromocyclooctane (TBCO), which previously was shown to decrease fecundity of Japanese medaka and inhibit oocyte maturation in zebrafish, effects on oocyte maturation were quantified using in vitro and in vivo exposure. Adaptation of the protocol for in vitro MIH-stimulated maturation of stage IV oocytes from zebrafish was successful in inducing greater than 80% of stage IX oocytes from female Japanese medaka to mature. To assess effects of in vitro exposure, stage IX oocytes were exposed to 0, 2, 20, and 200 μg/L of TBCO, followed by exposure to MIH. The in vitro exposure caused a significant decrease in maturation of oocytes exposed to 20 and 200 μg/L of TBCO. To assess effects of TBCO on fecundity and oocyte maturation following in vivo exposure, sexually mature fish were fed a control, 100 μg/g, or 1000 μg/g concentration of TBCO-spiked fish food for 21 days, where fecundity was measured daily, and following the exposure, stage IX oocytes were excised to assess MIH-stimulated maturation. Fecundity and oocyte maturation were significantly decreased at either concentration of TBCO. Plasma concentrations of 17β-estradiol (E2) and hepatic abundances of transcripts of vitellogenin (vtgI and vtgII) were quantified, but there were no significant differences between treatments. Results suggest that inhibition of oocyte maturation is a mechanism by which TBCO decreases fecundity, and that in vitro assays of oocyte maturation might be predictive of fecundity in this species.

Are New Phthalate Ester Substitutes Safer than Traditional DBP and DiBP? Comparative Endocrine-Disrupting Analyses on Zebrafish Using In Vivo, Transcriptome, and In Silico Approaches

Although previous studies have confirmed the association between phthalate esters (PAEs) exposure and endocrine disorders in humans, few studies to date have systematically assessed the threats of new PAE alternatives to endocrine disruptions. Herein, zebrafish embryos were continuously exposed to two PAEs [di-n-butyl phthalate (DBP) and diisobutyl phthalate (DiBP)], two structurally related alternatives [diiononyl phthalate (DINP) and diisononyl hexahydrophthalate (DINCH)], and two non-PAE substitutes [dipropylene glycol dibenzoate (DGD) and glyceryl triacetate (GTA)], and the endocrine-disrupting effects were investigated during the early stages (8-48 hpf). For five endogenous hormones, including progesterone, testosterone, 17β-estradiol, triiodothyronine (T3), and cortisol, the tested chemicals disturbed the contents of at least one hormone at environmentally relevant concentrations (≤3.9 μM), except DINCH and GTA. Then, the concentration-dependent reduced zebrafish transcriptome analysis was performed. Thyroid hormone (TH)- and androgen/estrogen-regulated adverse outcome pathways (AOPs) were the two types of biological pathways most sensitive to PAE exposure. Notably, six compounds disrupted four TH-mediated AOPs, from the inhibition of deiodinases (molecular initiating event, MIE), a decrease in T3 levels (key event, KE), to mortality (adverse outcome, AO) with the quantitatively linear relationships between MIE-KE (|r| = 0.96, p = 0.002), KE-AO (|r| = 0.88, p = 0.02), and MIE-AO (|r| = 0.89, p = 0.02). Multiple structural analyses showed that benzoic acid is the critical toxicogenic fragment. Our data will facilitate the screening and development of green alternatives.

Genotoxicity assessment: opportunities, challenges and perspectives for quantitative evaluations of dose-response data

Genotoxicity data are mainly interpreted in a qualitative way, which typically results in a binary classification of chemical entities. For more than a decade, there has been a discussion about the need for a paradigm shift in this regard. Here, we review current opportunities, challenges and perspectives for a more quantitative approach to genotoxicity assessment. Currently discussed opportunities mainly include the determination of a reference point (e.g., a benchmark dose) from genetic toxicity dose-response data, followed by calculation of a margin of exposure (MOE) or derivation of a health-based guidance value (HBGV). In addition to new opportunities, major challenges emerge with the quantitative interpretation of genotoxicity data. These are mainly rooted in the limited capability of standard in vivo genotoxicity testing methods to detect different types of genetic damage in multiple target tissues and the unknown quantitative relationships between measurable genotoxic effects and the probability of experiencing an adverse health outcome. In addition, with respect to DNA-reactive mutagens, the question arises whether the widely accepted assumption of a non-threshold dose-response relationship is at all compatible with the derivation of a HBGV. Therefore, at present, any quantitative genotoxicity assessment approach remains to be evaluated case-by-case. The quantitative interpretation of in vivo genotoxicity data for prioritization purposes, e.g., in connection with the MOE approach, could be seen as a promising opportunity for routine application. However, additional research is needed to assess whether it is possible to define a genotoxicity-derived MOE that can be considered indicative of a low level of concern. To further advance quantitative genotoxicity assessment, priority should be given to the development of new experimental methods to provide a deeper mechanistic understanding and a more comprehensive basis for the analysis of dose-response relationships.

Connecting Suborganismal Data to Bioenergetic Processes: Killifish Embryos Exposed to a Dioxin-Like Compound

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population-level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal responses that influence population dynamics. We describe a novel application of dynamic energy budget (DEB) theory in the context of a toxicity framework (adverse outcome pathways [AOPs]) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early-life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP key events to DEB processes through "damage" that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and DEB models to predict sublethal and lethal effects on young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters point to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern. Environ Toxicol Chem 2023;42:2040-2053. © 2023 Oak Ridge National Laboratory and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Putative adverse outcome pathway development based on physiological responses of female fathead minnows to model estrogen versus androgen receptor agonists

Several adverse outcome pathways (AOPs) have linked molecular initiating events like aromatase inhibition, androgen receptor (AR) agonism, and estrogen receptor (ER) antagonism to reproductive impairment in adult fish. Estrogen receptor agonists can also cause adverse reproductive effects, however, the early key events (KEs) in an AOP leading to this are mostly unknown. The primary aim of this study was to develop hypotheses regarding the potential mechanisms through which exposure to ER agonists might lead to reproductive impairment in female fish. Mature fathead minnows were exposed to 1 or 10 ng 17α-ethynylestradiol (EE2)/L or 10 or 100 µg bisphenol A (BPA)/L for 14 d. The response to EE2 and BPA was contrasted with the effects of 500 ng/L of 17β-trenbolone (TRB), an AR agonist, as well as TRB combined with the low and high concentrations of EE2 or BPA tested individually. Exposure to 10 ng EE2/L, 100 µg BPA/L, TRB, or the various mixtures with TRB caused significant decreases in plasma concentrations of 17β-estradiol. Exposure to TRB alone caused a significant reduction in plasma vitellogenin (VTG), but VTG was unaffected or even increased in females exposed to EE2 or BPA alone or, in most cases, in mixtures with TRB. Over the course of the 14-d exposure, the only treatments that clearly did not affect egg production were 1 ng EE2/L and 10 µg BPA/L. Based on these results and knowledge of hypothalamic-pituitary-gonadal axis function, we hypothesize an AOP whereby decreased production of maturation-inducing steroid leading to impaired oocyte maturation and ovulation, possibly due to negative feedback or direct inhibitory effects of membrane ER activation, could be responsible for causing adverse reproductive impacts in female fish exposed to ER agonists.

New Approach Methodologies for the Endocrine Activity Toolbox: Environmental Assessment for Fish and Amphibians

Multiple in vivo test guidelines focusing on the estrogen, androgen, thyroid, and steroidogenesis pathways have been developed and validated for mammals, amphibians, or fish. However, these tests are resource-intensive and often use a large number of laboratory animals. Developing alternatives for in vivo tests is consistent with the replacement, reduction, and refinement principles for animal welfare considerations, which are supported by increasing mandates to move toward an "animal-free" testing paradigm worldwide. New approach methodologies (NAMs) hold great promise to identify molecular, cellular, and tissue changes that can be used to predict effects reliably and more efficiently at the individual level (and potentially on populations) while reducing the number of animals used in (eco)toxicological testing for endocrine disruption. In a collaborative effort, experts from government, academia, and industry met in 2020 to discuss the current challenges of testing for endocrine activity assessment for fish and amphibians. Continuing this cross-sector initiative, our review focuses on the current state of the science regarding the use of NAMs to identify chemical-induced endocrine effects. The present study highlights the challenges of using NAMs for safety assessment and what work is needed to reduce their uncertainties and increase their acceptance in regulatory processes. We have reviewed the current NAMs available for endocrine activity assessment including in silico, in vitro, and eleutheroembryo models. New approach methodologies can be integrated as part of a weight-of-evidence approach for hazard or risk assessment using the adverse outcome pathway framework. The development and utilization of NAMs not only allows for replacement, reduction, and refinement of animal testing but can also provide robust and fit-for-purpose methods to identify chemicals acting via endocrine mechanisms. Environ Toxicol Chem 2023;42:757-777. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Health risk assessment of cadmium exposure by integration of an in silico physiologically based toxicokinetic model and in vitro tests

Cadmium (Cd) is a common environmental pollutant that can damage multiple organs, including the kidney. To prevent renal effects, international authorities have set health-based guidance values of Cd from epidemiological studies. To explore the health risk of Cd exposure and whether human equivalent doses (HEDs) derived from in vitro tests match the current guidance values, we integrated renal tubular epithelial cell-based assays with a physiologically based toxicokinetic model combined with the Monte Carlo method. For females, the HEDs (μg/kg/week) derived from KE2 (DNA damage), KE3 (cell cycle arrest), and KE4 (apoptosis) were 0.20 (2.5th-97.5th percentiles: 0.09-0.48), 0.52 (0.24-1.26), and 2.73 (1.27-6.57), respectively; for males the respective HEDs were 0.23 (0.10-0.49), 0.60 (0.27-1.30), and 3.11 (1.39-6.78). Among them, HED_KE4 (female) was close to the tolerable weekly intake (2.5 μg/kg/week) set by the European Food Safety Authority. The margin of exposure (MOE) derived from HED_KE4 (female) indicated that risks of renal toxicity for populations living in cadmium-contaminated regions should be of concern. This study provided a new approach methodology (NAM) for environmental chemical risk assessment using in silico and in vitro methods.

The brominated flame retardant, 1,2,5,6-tetrabromocyclooctane (TBCO), causes multigenerational effects on reproductive capacity of Japanese medaka (Oryzias latipes)

Exposure of fishes to endocrine disrupting chemicals (EDCs) during early development can induce multigenerational and transgenerational effects on reproduction. Both in vivo and in vitro studies have demonstrated that the brominated flame retardant, 1,2,5,6-tetrabromocyclooctane (TBCO), is an EDC. The present study investigated whether TBCO has mutigenerational and/or transgenerational effects on the reproductive performance of Japanese medaka (Oryzias latipes). Sexually mature fish (F0 generation) were fed either a control diet or a low (40.6 μg/g) or high (1034.4 μg/g) diet containing TBCO, and three generations of embryos were reared to determine reproductive performance using a standard 21-day reproduction assay. Concentrations of TBCO in eggs (F1 generation) from F0 fish given the low and high diets were 711.3 and 2535.5 ng/g wet weight, respectively. Cumulative fecundity of the F1 generation in the low and high treatment were reduced by 33.9% and 33.3%, respectively, compared to the control. In the F2 generation, cumulative fecundity of the low treatment returned to the level of the controls, but the high treatment was decreased by 29.8%. There was no decrease in cumulative fecundity in the F3 generation compared to the controls. Mechanistically, mRNA abundances of cholesterol side chain cleavage enzyme (cyp11a), aromatase (cyp19a), and luteinizing hormone receptor (lhr) were differentially expressed in gonads from F1 females, suggesting that TBCO might cause developmental reprogramming that disrupts steroidogenesis leading to decreased fecundity. However, concentrations of E2 in plasma and mRNA abundance of vitellogenin in liver were not significantly different compared to controls suggesting a mechanism other than disruption of steroidogenesis or vitellogenesis. Mechanistically, no effects were observed in the F2 or F3 generation. Overall, results suggest that TBCO has multigenerational effects on the reproductive performance of Japanese medaka. However, no transgenerational effects were observed as the F3 generation fully recovered. The mechanism by which multigenerational effects were induced is not known.

Current testing programs for pesticides adequately capture endocrine activity and adversity for protection of vertebrate wildlife

The toxicity and ecotoxicity of pesticide active ingredients are evaluated by a number of standardized test methods using vertebrate animals. These standard test methods are required under various regulatory programs for the registration of pesticides. Over the past two decades, additional test methods have been developed with endpoints that are responsive to endocrine activity and subsequent adverse effects. This article examines the available test methods and their endpoints that are relevant to an assessment of endocrine-disrupting properties of pesticides. Furthermore, the article highlights how weight-of-evidence approaches should be applied to determine whether an adverse response in (eco)toxicity tests is caused by an endocrine mechanism of action. The large number of endpoints in the current testing paradigms for pesticides make it unlikely that endocrine activity and adversity is being overlooked. Integr Environ Assess Manag 2023;00:1-21. © 2023 Bayer CropScience and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Case Study in 21st-Century Ecotoxicology: Using In Vitro Aromatase Inhibition Data to Predict Reproductive Outcomes in Fish In Vivo

To reduce the use of intact animals for chemical safety testing, while ensuring protection of ecosystems and human health, there is a demand for new approach methodologies (NAMs) that provide relevant scientific information at a quality equivalent to or better than traditional approaches. The present case study examined whether bioactivity and associated potency measured in an in vitro screening assay for aromatase inhibition could be used together with an adverse outcome pathway (AOP) and mechanistically based computational models to predict previously uncharacterized in vivo effects. Model simulations were used to inform designs of 60-h and 10-21-day in vivo exposures of adult fathead minnows (Pimephales promelas) to three or four test concentrations of the in vitro aromatase inhibitor imazalil ranging from 0.12 to 260 µg/L water. Consistent with an AOP linking aromatase inhibition to reproductive impairment in fish, exposure to the fungicide resulted in significant reductions in ex vivo production of 17β-estradiol (E2) by ovary tissue (≥165 µg imazalil/L), plasma E2 concentrations (≥74 µg imazalil/L), vitellogenin (Vtg) messenger RNA expression (≥165 µg imazalil/L), Vtg plasma concentrations (≥74 µg imazalil/L), uptake of Vtg into oocytes (≥260 µg imazalil/L), and overall reproductive output in terms of cumulative fecundity, number of spawning events, and eggs per spawning event (≥24 µg imazalil/L). Despite many potential sources of uncertainty in potency and efficacy estimates based on model simulations, observed magnitudes of apical effects were quite consistent with model predictions, and in vivo potency was within an order of magnitude of that predicted based on in vitro relative potency. Overall, our study suggests that NAMs and AOP-based approaches can support meaningful reduction and refinement of animal testing. Environ Toxicol Chem 2023;42:100-116. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

The path via pathway-based approaches towards safety assessment: A concise review

For decades, chemical safety assessment has been proposed to shift from animal testing to in vitro testing systems in response to the call for the 3R. In Europe, the answer was to combine various information sources in integrated testing strategies (ITS); In the US, it was in 2007 when the landmark report by the National Research Council put forward a vision of in vitro toxicity testing paradigm. Since then, efforts to develop pathway-based assessment framework have been on the track. In 2010, systems biology brought out a conceptual framework called adverse outcome pathway (AOP), which took one step further from toxicity pathway to regulatory toxicology. Computational modeling, high-throughput screening, high-content omics have all been approached to facilitate this progress. This paper briefly reviewed the achievement of pathway-based chemical assessment since 2007, discussed potential pitfalls and challenges that mechanism-driven chemical assessment may undergo, and presented future perspectives of safety assessment that is to be based on computational system biology.

Development of an Adverse Outcome Pathway for radiation-induced microcephaly via expert consultation and machine learning

BACKGROUND

Brain development during embryogenesis and in early postnatal life is particularly complex and involves the interplay of many cellular processes and molecular mechanisms, making it extremely vulnerable to exogenous insults, including ionizing radiation (IR). Microcephaly is one of the most frequent neurodevelopmental abnormalities that is characterized by small brain size, and is often associated with intellectual deficiency. Decades of research span from epidemiological data on in utero exposure of the A-bomb survivors, to studies on animal and cellular models that allowed deciphering the most prominent molecular mechanisms leading to microcephaly. The Adverse Outcome Pathway (AOP) framework is used to organize, evaluate and portray the scientific knowledge of toxicological effects spanning different biological levels of organizations, from the initial interaction with molecular targets to the occurrence of a disease or adversity. In the present study, the framework was used in an attempt to organize the current scientific knowledge on microcephaly progression in the context of ionizing radiation (IR) exposure. This work was performed by a group of experts formed during a recent workshop organized jointly by the Multidisciplinary European Low Dose Initiative (MELODI) and the European Radioecology Alliance (ALLIANCE) associations to present the AOP approach and tools. Here we report on the development of a putative AOP for congenital microcephaly resulting from IR exposure based on discussions of the working group and we emphasize the use of a novel machine-learning approach to assist in the screening of the available literature to develop AOPs.

CONCLUSION

The expert consultation led to the identification of crucial biological events for the progression of microcephaly upon exposure to IR, and highlighted current knowledge gaps. The machine learning approach was successfully used to screen the existing knowledge and helped to rapidly screen the body of evidence and in particular the epidemiological data. This systematic review approach also ensured that the analysis was sufficiently comprehensive to identify the most relevant data and facilitate rapid and consistent AOP development. We anticipate that as machine learning approaches become more user-friendly through easy-to-use web interface, this would allow AOP development to become more efficient and less time consuming.

A high-level overview of the Organisation for Economic Co-operation and Development Adverse Outcome Pathway Programme

Background The Organisation for Economic Co-operation and Development (OECD), through its Chemical Safety Programme, is delegated to ensure the safety of humans and wildlife from harmful toxicants. To support these needs, initiatives to increase the efficiency of hazard identification and risk management are under way. Amongst these, the adverse outcome pathway (AOP) approach integrates information on biological knowledge and test methodologies (both established and new) to support regulatory decision making. AOPs collate biological knowledge from different sources, assess lines of evidence through considerations of causality and undergo rigorous peer-review before being subsequently endorsed by the OECD. It is envisioned that the OECD AOP Development Programme will transform the toxicity testing paradigm by leveraging the strengths of mechanistic and modelling based approaches and enhance the utility of high throughput screening assays. Since its launch, in 2012, the AOP Development Programme has matured with a greater number of AOPs endorsed since inception, and the attraction of new scientific disciplines (e.g. the radiation field). Recently, a Radiation and Chemical (Rad/Chem) AOP Joint Topical Group has been formed by the OECD Nuclear Energy Agency High-Level Group on Low-Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The topical group will work to evolve the development and use of the AOP framework in radiation research and regulation. As part of these efforts, the group will bring awareness and understanding on the programme, as it has matured from the chemical perspective. In this context, this paper provides the radiation community with a high-level overview of the OECD AOP Development Programme, including examples of application using knowledge gleaned from the field of chemical toxicology, and their work towards regulatory implementation. Conclusion: Although the drivers for developing AOPs in chemical sector differ from that of the radiation field, the principles and transparency of the approach can benefit both scientific disciplines. By providing perspectives and an understanding of the evolution of the OECD AOP Development Programme including case examples and work towards quantitative AOP development, it may motivate the expansion and implementation of AOPs in the radiation field.

Signal amplification in the KEAP1-NRF2-ARE antioxidant response pathway

The KEAP1-NRF2-ARE signaling pathway plays a central role in mediating the adaptive cellular stress response to oxidative and electrophilic chemicals. This canonical pathway has been extensively studied and reviewed in the past two decades, but rarely was it looked at from a quantitative signaling perspective. Signal amplification, i.e., ultrasensitivity, is crucially important for robust induction of antioxidant genes to appropriate levels that can adequately counteract the stresses. In this review article, we examined a number of well-known molecular events in the KEAP1-NRF2-ARE pathway from a quantitative perspective with a focus on how signal amplification can be achieved. We illustrated, by using a series of mathematical models, that redox-regulated protein sequestration, stabilization, translation, nuclear trafficking, DNA promoter binding, and transcriptional induction - which are embedded in the molecular network comprising KEAP1, NRF2, sMaf, p62, and BACH1 - may generate highly ultrasensitive NRF2 activation and antioxidant gene induction. The emergence and degree of ultrasensitivity depend on the strengths of protein-protein and protein-DNA interaction and protein abundances. A unique, quantitative understanding of signal amplification in the KEAP1-NRF2-ARE pathway will help to identify sensitive targets for the prevention and therapeutics of oxidative stress-related diseases and develop quantitative adverse outcome pathway models to facilitate the health risk assessment of oxidative chemicals.

Establishing a Communication and Engagement Strategy to Facilitate the Adoption of the Adverse Outcome Pathways in Radiation Research and Regulation

BACKGROUND

Studies on human health and ecological effects of ionizing radiation are rapidly evolving as innovative technologies arise and the body of scientific knowledge grows. Structuring this information could effectively support the development of decision making tools and health risk models to complement current system of radiation protection. To this end, the adverse outcome pathway (AOP) approach is being explored as a means to consolidate the most relevant research to identify causation between exposure to a chemical or non-chemical stressor and disease or adverse effect progression. This tool is particularly important for low dose and low dose rate radiation exposures because of the latency and uncertainties in the biological responses at these exposure levels. To progress this aspect, it is essential to build a community of developers, facilitators, risk assessors (in the private sector and in government), policy-makers, and regulators who understand the strengths and weaknesses of, and how to appropriately utilize AOPs for consolidating our knowledge on the impact of low dose ionizing radiation. Through co-ordination with the Organisation of Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) High-Level Group on Low-Dose Research (HLG-LDR) and OECD's AOP Programme, initiatives are under way to demonstrate this approach in radiation research and regulation. Among these, a robust communications strategy and stakeholder engagement will be essential. It will help establish best practices for AOPs in institutional project development and aid in dissemination for more efficient and timely uptake and use of AOPs. In this regard, on June 1, 2021, the Radiation and Chemical (Rad/Chem) AOP Joint Topical Group was formed as part of the initiative from the NEA's HLG-LDR. The topical group will work to develop a communication and engagement strategy to define the target audiences, establish the clear messages and identify the delivery and engagement platforms.

CONCLUSION

The incorporation of the best science and better decision-making should motive the radiation protection community to develop, refine and use AOPs, recognizing that their incorporation into radiation health risk assessments is critical for public health and environmental protection in the 21st century.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

Moving beyond Risk Quotients: Advancing Ecological Risk Assessment to Reflect Better, More Robust and Relevant Methods

Under standard guidance for conducting Ecological Risk Assessments (ERAs), the risks of chemical exposure to diverse organisms are most often based on deterministic point estimates evaluated against safety-factor-based levels of concern (LOCs). While the science and guidance for mechanistic effect models (e.g., demographic, population, and agent-based) have long been demonstrated to provide more ecologically relevant effect endpoints upon which risk can be evaluated, their application in ERAs has been limited, particularly in the US. This special issue highlights the state of the science in effect modeling for ERAs through demonstrated application of the recently published Population modeling Guidance, Use, Interpretation, and Development for ERA (Pop-GUIDE). We introduce this issue with a perspective on why it is critical to move past the current application of deterministic endpoints and LOCs. We demonstrate how the current, widely used approaches contain extensive uncertainty that could be reduced considerably by applying models that account for species life histories and other important endogenous and exogenous factors critical to species sustainability. We emphasize that it is long past time to incorporate better, more robust, and ecologically relevant effect models into ERAs, particularly for chronic risk determination. The papers in this special issue demonstrate how mechanistic models that follow Pop-GUIDE better inform ERAs compared to the current standard practice.

Application of the Adverse Outcome Pathway Concept to In Vitro Nephrotoxicity Assessment: Kidney Injury due to Receptor-Mediated Endocytosis and Lysosomal Overload as a Case Study

Application of adverse outcome pathways (AOP) and integration of quantitative in vitro to in vivo extrapolation (QIVIVE) may support the paradigm shift in toxicity testing to move from apical endpoints in test animals to more mechanism-based in vitro assays. Here, we developed an AOP of proximal tubule injury linking a molecular initiating event (MIE) to a cascade of key events (KEs) leading to lysosomal overload and ultimately to cell death. This AOP was used as a case study to adopt the AOP concept for systemic toxicity testing and risk assessment based on in vitro data. In this AOP, nephrotoxicity is thought to result from receptor-mediated endocytosis (MIE) of the chemical stressor, disturbance of lysosomal function (KE1), and lysosomal disruption (KE2) associated with release of reactive oxygen species and cytotoxic lysosomal enzymes that induce cell death (KE3). Based on this mechanistic framework, in vitro readouts reflecting each KE were identified. Utilizing polymyxin antibiotics as chemical stressors for this AOP, the dose-response for each in vitro endpoint was recorded in proximal tubule cells from rat (NRK-52E) and human (RPTEC/TERT1) in order to (1) experimentally support the sequence of key events (KEs), to (2) establish quantitative relationships between KEs as a basis for prediction of downstream KEs based on in vitro data reflecting early KEs and to (3) derive suitable in vitro points of departure for human risk assessment. Time-resolved analysis was used to support the temporal sequence of events within this AOP. Quantitative response-response relationships between KEs established from in vitro data on polymyxin B were successfully used to predict in vitro toxicity of other polymyxin derivatives. Finally, a physiologically based kinetic (PBK) model was utilized to transform in vitro effect concentrations to a human equivalent dose for polymyxin B. The predicted in vivo effective doses were in the range of therapeutic doses known to be associated with a risk for nephrotoxicity. Taken together, these data provide proof-of-concept for the feasibility of in vitro based risk assessment through integration of mechanistic endpoints and reverse toxicokinetic modelling.

A Collaborative Initiative to Establish Genomic Biomarkers for Assessing Tumorigenic Potential to Reduce Reliance on Conventional Rodent Carcinogenicity Studies

There is growing recognition across broad sectors of the scientific community that use of genomic biomarkers has the potential to reduce the need for conventional rodent carcinogenicity studies of industrial chemicals, agrochemicals, and pharmaceuticals through a weight-of-evidence approach. These biomarkers fall into 2 major categories: (1) sets of gene transcripts that can identify distinct tumorigenic mechanisms of action; and (2) cancer driver gene mutations indicative of rapidly expanding growth-advantaged clonal cell populations. This call-to-action article describes a collaborative approach launched to develop and qualify biomarker gene expression panels that measure widely accepted molecular pathways linked to tumorigenesis and their activation levels to predict tumorigenic doses of chemicals from short-term exposures. Growing evidence suggests that application of such biomarker panels in short-term exposure rodent studies can identify both tumorigenic hazard and tumorigenic activation levels for chemical-induced carcinogenicity. In the future, this approach will be expanded to include methodologies examining mutations in key cancer driver gene mutation hotspots as biomarkers of both genotoxic and nongenotoxic chemical tumor risk. Analytical, technical, and biological validation studies of these complementary genomic tools are being undertaken by multisector and multidisciplinary collaborative teams within the Health and Environmental Sciences Institute. Success from these efforts will facilitate the transition from current heavy reliance on conventional 2-year rodent carcinogenicity studies to more rapid animal- and resource-sparing approaches for mechanism-based carcinogenicity evaluation supporting internal and regulatory decision-making.

A Multidimensional Matrix Model for Predicting the Effects of Male-Biased Sex Ratios on Fish Populations

Laboratory experiments have established that exposure to certain endocrine-active substances prior to and/or during the period of sexual differentiation can lead to skewed sex ratios in fish. However, the potential long-term population impact of biased sex ratio depends on multiple factors including the life history of the species and whether the ratio is male or female-biased. In the present study, we describe a novel multidimensional, density-dependent matrix model that analyzes age class-structure of both males and females over time, allowing for the quantitative evaluation of the effects of biased sex ratio on population status. This approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects on sex ratio due to chemical and/or nonchemical stressors to adverse outcomes in whole organisms and populations. For demonstration purposes, we applied the model to evaluate population trajectories for fathead minnow (Pimephales promelas) exposed to prochloraz, an aromatase inhibitor, during sexual differentiation. The model also was used to explore the population impact in a more realistic exposure scenario in which both adult and early life stages of fish are exposed concurrently to prochloraz, which, in addition to altering sex ratio during development, can decrease vitellogenin and egg production in adult females. For each exposure scenario, the model was used to analyze total population size, numbers of females and of males, and sex specific recruitment of the F1 generation. The present study illustrates the utility of multidimensional matrix population models for ecological risk assessment in terms of integrating effects across a population of an organism even when chemical effects on individuals are manifested via different pathways depending on life stage. Environ Toxicol Chem 2022;41:1066-1077. Published 2022. This article is a U.S. Government work and is in the public domain in the USA.

From Qualitative to Quantitative AOP: A Case Study of Neurodegeneration

Adverse outcome pathways (AOPs) include a sequence of events that connect a molecular-level initiating event with an adverse outcome at the cellular level for human health endpoints, or at the population level for ecological endpoints. When there is enough quantitative understanding of the relationships between key events in an AOP, a mathematical model may be developed to connect key events in a quantitative AOP (qAOP). Ideally, a qAOP will reduce the time and resources spent for chemical toxicity testing and risk assessment and enable the extrapolation of data collected at the molecular-level by in vitro assays, for example, to predict whether an adverse outcome may occur. Here, we review AOPs in the AOPWiki, an AOP repository, to determine best practices that would facilitate conversion from AOP to qAOP. Then, focusing on a particular case study, acetylcholinesterase inhibition leading to neurodegeneration, we describe specific methods and challenges. Examples of challenges include the availability and collection of quantitative data amenable to model development, the lack of studies that measure multiple key events, and model accessibility or transferability across platforms. We conclude with recommendations for improving key event and key event relationship descriptions in the AOPWiki that facilitate the transition of qualitative AOPs to qAOPs.

A quantitative AOP of mitochondrial toxicity based on data from three cell lines

Adverse Outcome Pathways (AOPs) are increasingly used to support the integration of in vitro data in hazard assessment for chemicals. Quantitative AOPs (qAOPs) use mathematical models to describe the relationship between key events (KEs). In this paper, data obtained in three cell lines, LHUMES, HepG2 and RPTEC/TERT1, using similar experimental protocols, was used to calibrate a qAOP of mitochondrial toxicity for two chemicals, rotenone and deguelin. The objectives were to determine whether the same qAOP could be used for the three cell types, and to test chemical-independence by cross-validation with a dataset obtained on eight other chemicals in LHUMES cells. Repeating the calibration approach for both chemicals in three cell lines highlighted various practical difficulties. Even when the same readouts of KEs are measured, the mathematical functions used to describe the key event relationships may not be the same. Cross-validation in LHUMES cells was attempted by estimating chemical-specific potency at the molecular initiating events and using the rest of the calibrated qAOP to predict downstream KEs: toxicity of azoxystrobin, carboxine, mepronil and thifluzamide was underestimated. Selection of most relevant readouts and accurate characterization of the molecular initiating event for cross-validation are critical when designing in vitro experiments targeted at calibrating qAOPs.

High throughput data-based, toxicity pathway-oriented development of a quantitative adverse outcome pathway network linking AHR activation to lung damages

The quantitative adverse outcome pathway (qAOP) is proposed to inform dose-responses at multiple biological levels for the purpose of toxicity prediction. So far, qAOP models concerning human health are scarce. Previously, we proposed 5 key molecular pathways that led aryl hydrogen receptor (AHR) activation to lung damages. The present study assembled an AOP network based on the gene expression signatures of these toxicity pathways, and validated the network using publicly available high throughput data combined with machine learning models. In addition, the AOP network was quantitatively evaluated with omics approaches and bioassays, using 16HBE-CYP1A1 cells exposed to benzo(a)pyrene (BaP), a prototypical AHR activator. Benchmark dose (BMD) analysis of transcriptomics revealed that AHR gene held the lowest BMD value, whereas AHR pathway held the lowest point of departure (PoD) compared to the other 4 pathways. Targeted bioassays were further performed to quantitatively understand the cellular responses, including ROS generation, DNA damage, interleukin-6 production, and extracellular matrix increase marked by collagen expression. Eventually, response-response relationships were plotted using nonlinear model fitting. The present study developed a highly reliable AOP model concerning human health, and validated as well as quantitatively evaluated it, and such a method is likely to be adoptable for risk assessment.

Emerging concepts and opportunities for endocrine disruptor screening of the non-EATS modalities

Endocrine disrupting chemicals (EDCs) are ubiquitous in the environment and involve diverse chemical-receptor interactions that can perturb hormone signaling. The Organization for Economic Co-operation and Development has validated several EDC-receptor bioassays to detect endocrine active chemicals and has established guidelines for regulatory testing of EDCs. Focus on testing over the past decade has been initially directed to EATS modalities (estrogen, androgen, thyroid, and steroidogenesis) and validated tests for chemicals that exert effects through non-EATS modalities are less established. Due to recognition that EDCs are vast in their mechanisms of action, novel bioassays are needed to capture the full scope of activity. Here, we highlight the need for validated assays that detect non-EATS modalities and discuss major international efforts underway to develop such tools for regulatory purposes, focusing on non-EATS modalities of high concern (i.e., retinoic acid, aryl hydrocarbon receptor, peroxisome proliferator-activated receptor, and glucocorticoid signaling). Two case studies are presented with strong evidence amongst animals and human studies for non-EATS disruption and associations with wildlife and human disease. This includes metabolic syndrome and insulin signaling (case study 1) and chemicals that impact the cardiovascular system (case study 2). This is relevant as obesity and cardiovascular disease represent two of the most significant health-related crises of our time. Lastly, emerging topics related to EDCs are discussed, including recognition of crosstalk between the EATS and non-EATS axis, complex mixtures containing a variety of EDCs, adverse outcome pathways for chemicals acting through non-EATS mechanisms, and novel models for testing chemicals. Recommendations and considerations for evaluating non-EATS modalities are proposed. Moving forward, improved understanding of the non-EATS modalities will lead to integrated testing strategies that can be used in regulatory bodies to protect environmental, animal, and human health from harmful environmental chemicals.

Towards a qAOP framework for predictive toxicology - Linking data to decisions

•

Chemical toxicity assessment depends on the quantification of kinetics and dynamics.

•

Quantitative AOPs (qAOPs) are toxicodynamic models based on Adverse Outcome Pathways.

•

Existing e-resources could form the basis of an e-infrastructure for qAOP modelling.

•

Best practices for qAOP development, assessment and application are needed.

•

Three qAOP case studies are presented to illustrate a modelling workflow.

The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.

Machine learning-based biomarkers identification from toxicogenomics - Bridging to regulatory relevant phenotypic endpoints

One of the major challenges in realization and implementations of the Tox21 vision is the urgent need to establish quantitative link between in-vitro assay molecular endpoint and in-vivo regulatory-relevant phenotypic toxicity endpoint. Current toxicomics approach still mostly rely on large number of redundant markers without pre-selection or ranking, therefore, selection of relevant biomarkers with minimal redundancy would reduce the number of markers to be monitored and reduce the cost, time, and complexity of the toxicity screening and risk monitoring. Here, we demonstrated that, using time series toxicomics in-vitro assay along with machine learning-based feature selection (maximum relevance and minimum redundancy (MRMR)) and classification method (support vector machine (SVM)), an "optimal" number of biomarkers with minimum redundancy can be identified for prediction of phenotypic toxicity endpoints with good accuracy. We included two case studies for in-vivo carcinogenicity and Ames genotoxicity prediction, using 20 selected chemicals including model genotoxic chemicals and negative controls, respectively. The results suggested that, employing the adverse outcome pathway (AOP) concept, molecular endpoints based on a relatively small number of properly selected biomarker-ensemble involved in the conserved DNA-damage and repair pathways among eukaryotes, were able to predict both Ames genotoxicity endpoints and in-vivo carcinogenicity in rats. A prediction accuracy of 76% with AUC = 0.81 was achieved while predicting in-vivo carcinogenicity with the top-ranked five biomarkers. For Ames genotoxicity prediction, the top-ranked five biomarkers were able to achieve prediction accuracy of 70% with AUC = 0.75. However, the specific biomarkers identified as the top-ranked five biomarkers are different for the two different phenotypic genotoxicity assays. The top-ranked biomarkers for the in-vivo carcinogenicity prediction mainly focused on double strand break repair and DNA recombination, whereas the selected top-ranked biomarkers for Ames genotoxicity prediction are associated with base- and nucleotide-excision repair The method developed in this study will help to fill in the knowledge gap in phenotypic anchoring and predictive toxicology, and contribute to the progress in the implementation of tox 21 vision for environmental and health applications.

Carcinogenic Risk of 2,6-Di-tert-Butylphenol and Its Quinone Metabolite 2,6-DTBQ Through Their Interruption of RARβ: In Vivo, In Vitro, and In Silico Investigations

Thousands of contaminants are used worldwide and eventually released into the environment, presenting a challenge of health risk assessment. The identification of key toxic pathways and characterization of interactions with target biomacromolecules are essential for health risk assessments. The adverse outcome pathway (AOP) incorporates toxic mechanisms into health risk assessment by emphasizing the relationship among molecular initiating events (MIEs), key events (KEs), and adverse outcome (AO). Herein, we attempted the use of AOP to decipher the toxic effects of 2,6-di-tert-butylphenol (2,6-DTBP) and its para-quinone metabolite 2,6-di-tert-butyl-1,4-benzoquinone (2,6-DTBQ) based on integrated transcriptomics, molecular modeling, and cell-based assays. Through transcriptomics and quantitative real-time PCR validation, we identified retinoic acid receptor β (RARβ) as the key target biomacromolecule. The epigenetic analysis and molecular modeling revealed RARβ interference as one MIE, including DNA methylation and conformational changes. In vitro assays extended subsequent KEs, including altered protein expression of p-Erk1/2 and COX-2, and promoted cancer cell H4IIE proliferation and metastasis. These toxic effects altogether led to carcinogenic risk as the AO of 2,6-DTBP and 2,6-DTBQ, in line with chemical carcinogenesis identified from transcriptome profiling. Overall, our simplified AOP network of 2,6-DTBP and 2,6-DTBQ facilitates relevant health risk assessment.

Intrathyroidal feedforward and feedback network regulating thyroid hormone synthesis and secretion

Thyroid hormones (THs), including T4 and T3, are produced and released by the thyroid gland under the stimulation of thyroid-stimulating hormone (TSH). The homeostasis of THs is regulated via the coordination of the hypothalamic-pituitary-thyroid axis, plasma binding proteins, and local metabolism in tissues. TH synthesis and secretion in the thyrocytes-containing thyroid follicles are exquisitely regulated by an elaborate molecular network comprising enzymes, transporters, signal transduction machineries, and transcription factors. In this article, we synthesized the relevant literature, organized and dissected the complex intrathyroidal regulatory network into structures amenable to functional interpretation and systems-level modeling. Multiple intertwined feedforward and feedback motifs were identified and described, centering around the transcriptional and posttranslational regulations involved in TH synthesis and secretion, including those underpinning the Wolff-Chaikoff and Plummer effects and thyroglobulin-mediated feedback regulation. A more thorough characterization of the intrathyroidal network from a systems biology perspective, including its topology, constituent network motifs, and nonlinear quantitative properties, can help us to better understand and predict the thyroidal dynamics in response to physiological signals, therapeutic interventions, and environmental disruptions.

The Eco-Exposome Concept: Supporting an Integrated Assessment of Mixtures of Environmental Chemicals

Organisms are exposed to ever-changing complex mixtures of chemicals over the course of their lifetime. The need to more comprehensively describe this exposure and relate it to adverse health effects has led to formulation of the exposome concept in human toxicology. Whether this concept has utility in the context of environmental hazard and risk assessment has not been discussed in detail. In this Critical Perspective, we propose-by analogy to the human exposome-to define the eco-exposome as the totality of the internal exposure (anthropogenic and natural chemicals, their biotransformation products or adducts, and endogenous signaling molecules that may be sensitive to an anthropogenic chemical exposure) over the lifetime of an ecologically relevant organism. We describe how targeted and nontargeted chemical analyses and bioassays can be employed to characterize this exposure and discuss how the adverse outcome pathway concept could be used to link this exposure to adverse effects. Available methods, their limitations, and/or requirement for improvements for practical application of the eco-exposome concept are discussed. Even though analysis of the eco-exposome can be resource-intensive and challenging, new approaches and technologies make this assessment increasingly feasible. Furthermore, an improved understanding of mechanistic relationships between external chemical exposure(s), internal chemical exposure(s), and biological effects could result in the development of proxies, that is, relatively simple chemical and biological measurements that could be used to complement internal exposure assessment or infer the internal exposure when it is difficult to measure. Environ Toxicol Chem 2022;41:30-45. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Adverse Outcome Pathway: A Path towards better Data Consolidation and Global Co-ordination of Radiation Research

Background The purpose of toxicology is to protect human health and the environment. To support this, the Organisation for Economic Co-operation and Development (OECD), operating via its Extended Advisory Group for Molecular Screening and Toxicogenomics (EAGMST), has been developing the Adverse Outcome Pathway (AOP) approach to consolidate evidence for chemical toxicity spanning multiple levels of biological organization. The knowledge transcribed into AOPs provides a structured framework to transparently organize data, examine the weight of evidence of the AOP, and identify causal relationships between exposure to stressors and adverse effects of regulatory perspective. The AOP framework has undergone substantial maturation in the field of hazard characterization of chemicals over the last decade, and has also recently gained attention from the radiation community as a means to advance the mechanistic understanding of human and ecological health effects from exposure to ionizing radiation at low dose and low dose-rates. To fully exploit the value of such approaches for facilitating risk assessment and management in the field of radiation protection, solicitation of experiences and active cooperation between chemical and radiation communities are needed. As a result, the Radiation and Chemical (Rad/Chem) AOP joint topical group was formed on June 1, 2021 as part of the initiative from the High Level Group on Low Dose Research (HLG-LDR). HLG-LDR is overseen by the OECD Nuclear Energy Agency (NEA) Committee on Radiation Protection and Public Health (CRPPH). The main aims of the joint AOP topical group are to advance the use of AOPs in radiation research and foster broader implementation of AOPs into hazard and risk assessment. With global representation, it serves as a forum to discuss, identify and develop joint initiatives that support research and take on regulatory challenges. Conclusion: The Rad/Chem AOP joint topical group will specifically engage, promote, and implement the use of the AOP framework to: a) organize and evaluate mechanistic knowledge relevant to the protection of human and ecosystem health from radiation; b) identify data gaps and research needs pertinent to expanding knowledge of low dose and low dose-rate radiation effects; and c) demonstrate utility to support risk assessment by developing radiation-relevant case studies. It is envisioned that the Rad/Chem AOP joint topical group will actively liaise with the OECD EAGMST AOP developmental program to collectively advance areas of common interest and, specifically, provide recommendations for harmonization of the AOP framework to accommodate non-chemical stressors, such as radiation.

Retinaldehyde Dehydrogenase Inhibition-Related Adverse Outcome Pathway: Potential Risk of Retinoic Acid Synthesis Inhibition during Embryogenesis

Retinoic acid (RA) is one of the factors crucial for cell growth, differentiation, and embryogenesis; it interacts with the retinoic acid receptor and retinoic acid X receptor to eventually regulate target gene expression in chordates. RA is transformed from retinaldehyde via oxidization by retinaldehyde dehydrogenase (RALDH), which belongs to the family of oxidoreductases. Several chemicals, including disulphiram, diethylaminobenzaldehyde, and SB-210661, can effectively inhibit RALDH activity, potentially causing reproductive and developmental toxicity. The modes of action can be sequentially explained based on the molecular initiating event toward key events, and finally the adverse outcomes. Adverse outcome pathway (AOP) is a conceptual and theoretical framework that describes the sequential chain of casually liked events at different biological levels from molecular events to adverse effects. In the present review, we discussed a recently registered AOP (AOP₂₉₇; inhibition of retinaldehyde dehydrogenase leads to population decline) to explain and support the weight of evidence for RALDH inhibition-related developmental toxicity using the existing knowledge.

Deciphering Differential Life Stage Radioinduced Reproductive Decline in Caenorhabditis elegans through Lipid Analysis

Wildlife is chronically exposed to various sources of ionizing radiations, both environmental or anthropic, due to nuclear energy use, which can induce several defects in organisms. In invertebrates, reproduction, which directly impacts population dynamics, has been found to be the most radiosensitive endpoint. Understanding the underlying molecular pathways inducing this reproduction decrease can help in predicting the effects at larger scales (i.e., population). In this study, we used a life stage dependent approach in order to better understand the molecular determinants of reproduction decrease in the roundworm C. elegans. Worms were chronically exposed to 50 mGy·h⁻¹ external gamma ionizing radiations throughout different developmental periods (namely embryogenesis, gametogenesis, and full development). Then, in addition to reproduction parameters, we performed a wide analysis of lipids (different class and fatty acid via FAMES), which are both important signaling molecules for reproduction and molecular targets of oxidative stress. Our results showed that reproductive defects are life stage dependent, that lipids are differently misregulated according to the considered exposure (e.g., upon embryogenesis and full development) and do not fully explain radiation induced reproductive defects. Finally, our results enable us to propose a conceptual model of lipid signaling after radiation stress in which both the soma and the germline participate.