The potential of AOP networks for reproductive and developmental toxicity assay development

IL-2-mediated hepatotoxicity: knowledge gap identification based on the irAOP concept

Drug-induced hepatotoxicity constitutes a major reason for non-approval and post-marketing withdrawal of pharmaceuticals. In many cases, preclinical models lack predictive capacity for hepatic damage in humans. A vital concern is the integration of immune system effects in preclinical safety assessment. The immune-related Adverse Outcome Pathway (irAOP) approach, which is applied within the Immune Safety Avatar (imSAVAR) consortium, presents a novel method to understand and predict immune-mediated adverse events elicited by pharmaceuticals and thus targets this issue. It aims to dissect the molecular mechanisms involved and identify key players in drug-induced side effects. As irAOPs are still in their infancy, there is a need for a model irAOP to validate the suitability of this tool. For this purpose, we developed a hepatotoxicity-based model irAOP for recombinant human IL-2 (aldesleukin). Besides producing durable therapeutic responses against renal cell carcinoma and metastatic melanoma, the boosted immune activation upon IL-2 treatment elicits liver damage. The availability of extensive data regarding IL-2 allows both the generation of a comprehensive putative irAOP and to validate the predictability of the irAOP with clinical data. Moreover, IL-2, as one of the first cancer immunotherapeutics on the market, is a blueprint for various biological and novel treatment regimens that are under investigation today. This review provides a guideline for further irAOP-directed research in immune-mediated hepatotoxicity.

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.

Development of an adverse outcome pathway network for nephrotoxicity

Adverse outcome pathways (AOPs) were introduced in modern toxicology to provide evidence-based representations of the events and processes involved in the progression of toxicological effects across varying levels of the biological organisation to better facilitate the safety assessment of chemicals. AOPs offer an opportunity to address knowledge gaps and help to identify novel therapeutic targets. They also aid in the selection and development of existing and new in vitro and in silico test methods for hazard identification and risk assessment of chemical compounds. However, many toxicological processes are too intricate to be captured in a single, linear AOP. As a result, AOP networks have been developed to aid in the comprehension and placement of associated events underlying the emergence of related forms of toxicity-where complex exposure scenarios and interactions may influence the ultimate adverse outcome. This study utilised established criteria to develop an AOP network that connects thirteen individual AOPs associated with nephrotoxicity (as sourced from the AOP-Wiki) to identify several key events (KEs) linked to various adverse outcomes, including kidney failure and chronic kidney disease. Analysis of the modelled AOP network and its topological features determined mitochondrial dysfunction, oxidative stress, and tubular necrosis to be the most connected and central KEs. These KEs can provide a logical foundation for guiding the selection and creation of in vitro assays and in silico tools to substitute for animal-based in vivo experiments in the prediction and assessment of chemical-induced nephrotoxicity in human health.

Deriving aquatic PNECs of endocrine disruption effects for PFOS and PFOA by combining species sensitivity weighted distributions and adverse outcome pathway networks

Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), as emerging endocrine-disrupting chemicals (EDCs), pose adverse effects on aquatic organisms. Conventional ecological risk assessment (ERA) not fully considering the mode of toxicity action of PFOS and PFOA, may result in an underestimation of risks and confuse decision-makers. In the study, we developed species sensitivity weighted distribution (SSWD) models based on adverse outcome pathway (AOP) networks for deriving predicted no-effect concentrations (PNECs). Three kinds of weighting criteria (intraspecies variation, trophic level abundance, and data quality) and weighted log-normal distribution methods were adopted. The developed models considered the inter/intraspecies variation and integrated nontraditional endpoints of endocrine-disrupting effects. The PNECs of endocrine disruption effects were derived as 2.52 μg/L (95% confidence intervals 0.667-9.85 μg/L) for PFOS and 18.7 μg/L (5.40-71.0 μg/L) for PFOA, which were more conservative than those derived from the SSD method and were comparable with the values in the literature based on the chronic toxicity data. For PFOS, the effect of growth and development was the most sensitive; however, for PFOA, the effect of reproduction was the most sensitive in the effects of growth and development, reproduction, biochemistry and genetics, and survival. The endocrine-disrupting effects of PFOS and PFOA are significant and need to be fully recognized in the ERA. This study provided an ERA framework that can improve the ecological relevance and reduce the uncertainty of PNECs of EDCs.

Advancing Computational Toxicology by Interpretable Machine Learning

Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals have a critical impact on human health. Traditional animal models to evaluate chemical toxicity are expensive, time-consuming, and often fail to detect toxicants in humans. Computational toxicology is a promising alternative approach that utilizes machine learning (ML) and deep learning (DL) techniques to predict the toxicity potentials of chemicals. Although the applications of ML- and DL-based computational models in chemical toxicity predictions are attractive, many toxicity models are "black boxes" in nature and difficult to interpret by toxicologists, which hampers the chemical risk assessments using these models. The recent progress of interpretable ML (IML) in the computer science field meets this urgent need to unveil the underlying toxicity mechanisms and elucidate the domain knowledge of toxicity models. In this review, we focused on the applications of IML in computational toxicology, including toxicity feature data, model interpretation methods, use of knowledge base frameworks in IML development, and recent applications. The challenges and future directions of IML modeling in toxicology are also discussed. We hope this review can encourage efforts in developing interpretable models with new IML algorithms that can assist new chemical assessments by illustrating toxicity mechanisms in humans.

Comparison between endocrine activity assessed using ToxCast/Tox21 database and human plasma concentration of sunscreen active ingredients/UV filters

Sunscreen products are composed of ultraviolet (UV) filters and formulated to reduce exposure to sunlight thereby lessening skin damage. Concerns have been raised regarding the toxicity and potential endocrine disrupting (ED) effects of UV filters. The ToxCast/Tox21 program, that is, CompTox, is a high-throughput in vitro screening database of chemicals that identify adverse outcome pathways, key events, and ED potential of chemicals. Using the ToxCast/Tox21 database, octisalate, homosalate, octocrylene, oxybenzone, octinoxate, and avobenzone, 6 commonly used organic UV filters, were found to have been evaluated. These UV filters showed low potency in these bioassays with most activity detected above the range of the cytotoxic burst. The pathways that were most affected were the cell cycle and the nuclear receptor pathways. Most activity was observed in liver and kidney-based bioassays. These organic filters and their metabolites showed relatively weak ED activity when tested in bioassays measuring estrogen receptor (ER), androgen receptor (AR), thyroid receptor, and steroidogenesis activity. Except for oxybenzone, all activity in the endocrine assays occurred at concentrations greater than the cytotoxic burst. Moreover, except for oxybenzone, plasma concentrations (Cmax) measured in humans were at least 100× lower than bioactive (AC50/ACC) concentrations that produced a response in ToxCast/Tox21 assays. These data are consistent with in vivo animal/human studies showing weak or negligible endocrine activity. In sum, when considered as part of a weight-of-evidence assessment and compared with measured plasma concentrations, the results show these organic UV filters have low intrinsic biological activity and risk of toxicity including endocrine disruption in humans.

Identification of an adverse outcome pathway (AOP) for chemical-induced craniofacial anomalies using the transgenic zebrafish model

Craniofacial anomalies are one of the most frequent birth defects worldwide and are often caused by genetic and environmental factors such as pharmaceuticals and chemical agents. Although identifying adverse outcome pathways (AOPs) is a central issue for evaluating the teratogenicity, the AOP causing craniofacial anomalies has not been identified. Recently, zebrafish has gained interest as an emerging model for predicting teratogenicity because of high throughput, cost-effectiveness and availability of various tools for examining teratogenic mechanisms. Here, we established zebrafish sox10-EGFP reporter lines to visualize cranial neural crest cells (CNCCs) and have identified the AOPs for craniofacial anomalies. When we exposed the transgenic embryos to teratogens that were reported to cause craniofacial anomalies in mammals, CNCC migration and subsequent morphogenesis of the first pharyngeal arch were impaired at 24 hours post-fertilization. We also found that cell proliferation and apoptosis of the migratory CNCCs were disturbed, which would be key events of the AOP. From these results, we propose that our sox10-EGFP reporter lines serve as a valuable model for detecting craniofacial skeletal abnormalities, from early to late developmental stages. Given that the developmental process of CNCCs around this stage is highly conserved between zebrafish and mammals, our findings can be extrapolated to mammalian craniofacial development and thus help in predicting craniofacial anomalies in human.

Enhancing developmental and reproductive toxicity knowledge: A new AOP stemming from glutathione depletion

Integrated approaches to testing and assessments (IATAs) have been proposed as a method to organise new approach methodologies in order to replace traditional animal testing for chemical safety assessments. To capture the mechanistic aspects of toxicity assessments, IATAs can be framed around the adverse outcome pathway (AOP) concept. To utilise AOPs fully in this context, a sufficient number of pathways need to be present to develop fit for purpose IATAs. In silico approaches can support IATA through the provision of predictive models and also through data integration to derive conclusions using a weight-of-evidence approach. To examine the maturity of a developmental and reproductive toxicity (DART) AOP network derived from the literature, an assessment of its coverage was performed against a novel toxicity dataset. A dataset of diverse compounds, with data from studies performed according to OECD test guidelines TG-421 and TG-422, was curated to test the performance of an in silico model based on the AOP network - allowing for the identification of knowledge gaps within the network. One such gap in the knowledge was filled through the development of an AOP stemming from the molecular initiating event 'glutathione reaction with an electrophile' leading to male fertility toxicity. The creation of the AOP provided the mechanistic rationale for the curation of pre-existing structural alerts to relevant key events. Integrating this new knowledge and associated alerts into the DART AOP network will improve its coverage of DART-relevant chemical space. In addition, broadening the coverage of AOPs for a particular regulatory endpoint may facilitate the development of, and confidence in, robust IATAs.

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.

AOP-helpFinder 2.0: Integration of an event-event searches module

To support the use of alternative methods in regulatory assessment of chemical risks, the concept of adverse outcome pathway (AOP) constitutes an important toxicological tool. AOP represents a structured representation of existing knowledge, linking molecular initiating event (MIE) initiated by a prototypical stressor that leads to a cascade of biological key event (KE) to an adverse outcome (AO). Biological information to develop such AOP is very dispersed in various data sources. To increase the chance of capturing relevant existing data to develop a new AOP, the AOP-helpFinder tool was recently implemented to assist researchers to design new AOP. Here, an updated version of AOP-helpFinder proposes novel functionalities. The main one being the implementation of an automatic screening of the abstracts from the PubMed database to identify and extract event-event associations. In addition, a new scoring system was created to classify the identified co-occurred terms (stressor-event or event-event (which represent key event relationships) to help prioritization and support the weight of evidence approach, allowing a global assessment of the strength and reliability of the AOP. Moreover, to facilitate interpretation of the results, visualization options are also proposed. The AOP-helpFinder source code are fully accessible via GitHub, and searches can be performed via a web interface at http://aop-helpfinder-v2.u-paris-sciences.fr/.

Review of ecologically relevant in vitro bioassays to supplement current in vivo tests for whole effluent toxicity testing - Part 1: Apical endpoints

Whole effluent toxicity (WET) testing is commonly used to ensure that wastewater discharges do not pose an unacceptable risk to receiving environments. Traditional WET testing involves exposing animals to (waste)water samples to assess four major ecologically relevant apical endpoints: mortality, growth, development, and reproduction. Recently, with the widespread implementation of the 3Rs to replace, reduce and refine the use of animals in research and testing, there has been a global shift away from in vivo testing towards in vitro alternatives. However, prior to the inclusion of in vitro bioassays in regulatory frameworks, it is critical to establish their ecological relevance and technical suitability. This is part 1 of a two-part review that aims to identify in vitro bioassays that can be used in WET testing and relate them to ecologically relevant endpoints through toxicity pathways, providing the reader with a high-level overview of current capabilities. Part 1 of this review focuses on four apical endpoints currently included in WET testing: mortality, growth, development, and reproduction. For each endpoint, the link between responses at the molecular or cellular level, that can be measured in vitro, and the adverse outcome at the organism level were established through simplified toxicity pathways. Additionally, literature from 2015 to 2020 on the use of in vitro bioassays for water quality assessments was reviewed to identify a list of suitable bioassays for each endpoint. This review will enable the prioritization of relevant endpoints and bioassays for incorporation into WET testing.

In vitro models of human development and their potential application in developmental toxicity testing

Recent publications describe the development of in vitro models of human development, for which applications in developmental toxicity testing can be envisaged. To date, these regulatory assessments have exclusively been performed in animal studies, the relevance of which to adverse reactions in humans may be questioned. Recently developed cell culture-based models of embryo-fetal development, however, do not yet exhibit sufficient levels of standardisation and reproducibility. Here, the advantages and shortcomings of both in vivo and in vitro developmental toxicity testing are addressed, as well as the possibility of integrated testing strategies as a viable option in the near future.

Adverse outcome pathways (AOPs) for radiation-induced reproductive effects in environmental species: state of science and identification of a consensus AOP network

BACKGROUND

Reproductive effects of ionizing radiation in organisms have been observed under laboratory and field conditions. Such assessments often rely on associations between exposure and effects, and thus lacking a detailed mechanistic understanding of causality between effects occurring at different levels of biological organization. The Adverse Outcome Pathway (AOP), a conceptual knowledge framework to capture, organize, evaluate and visualize the scientific knowledge of relevant toxicological effects, has the potential to evaluate the causal relationships between molecular, cellular, individual, and population effects. This paper presents the first development of a set of consensus AOPs for reproductive effects of ionizing radiation in wildlife. This work was performed by a group of experts formed during a 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. The work presents a series of taxon-specific case studies that were used to identify relevant empirical evidence, identify common AOP components and propose a set of consensus AOPs that could be organized into an AOP network with broader taxonomic applicability.

CONCLUSION

Expert consultation led to the identification of key biological events and description of causal linkages between ionizing radiation, reproductive impairment and reduction in population fitness. The study characterized the knowledge domain of taxon-specific AOPs, identified knowledge gaps pertinent to reproductive-relevant AOP development and reflected on how AOPs could assist applications in radiation (radioecological) research, environmental health assessment, and radiological protection. Future advancement and consolidation of the AOPs is planned to include structured weight of evidence considerations, formalized review and critical assessment of the empirical evidence prior to formal submission and review by the OECD sponsored AOP development program.

Mapping DEHP to the adverse outcome pathway network for human female reproductive toxicity

Adverse outcome pathways (AOPs) and AOP networks are tools for mechanistic presentation of toxicological effects across different levels of biological organization. These tools are used to better understand how chemicals impact human health. In this study, a four-step workflow was used to derive the AOP network of human female reproductive toxicity (HFRT-AOP) from five AOPs available in the AOP-Wiki and ten AOPs obtained from the literature. Standard network analysis identified key events (KEs) that are point of convergence and divergence, upstream and downstream KEs, and bottlenecks across the network. To map di-(2-ethylhexyl) phthalate (DEHP) to the HFRT-AOP network, we extracted DEHP target genes and proteins from the Comparative Toxicogenomic and the CompTox Chemicals Dashboard databases. Enriched GO terms analysis was used to identify relevant biological processes in the ovary that are DEHP targets, whereas screening of scientific literature was performed manually and automatically using AOP-helpFinder. We combined this information to map DEHP to HFRT-AOP network to provide insight on the KEs and system-level perturbations caused by this endocrine disruptor and the emergent paths. This approach can enable better understanding of the toxic mechanism of DEHP-induced human female reproductive toxicity and reveal potential novel DEHP female reproductive targets for experimental studies.

Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations

An adverse outcome pathway (AOP) is a compact representation of the available mechanistic information on observed adverse effects upon environmental exposure. Sharing of events across individual AOPs has led to the emergence of AOP networks. Since AOP networks are expected to be functional units of toxicity prediction, there is current interest in their development tailored to specific research question or regulatory problem. To this end, we have developed a detailed workflow to construct an endocrine-relevant AOP (ED-AOP) network based on the existing information available in AOP-Wiki. We propose a cumulative weight of evidence (WoE) score for each ED-AOP based on the WoE scores assigned to key event relationships (KERs) by AOP-Wiki, revealing gaps in AOP development. Connectivity analysis of the ED-AOP network comprising 48 AOPs reveals 7 connected components and 12 isolated AOPs. Subsequently, we apply standard network measures to perform an in-depth analysis of the two largest connected components of the ED-AOP network. Notably, the graph-theoretic analyses led to the identification of important events including points of convergence or divergence in the ED-AOP network. These findings can suggest potential adverse outcomes and facilitate the development of new endpoints or assays for chemical risk assessment. Detailed analysis of the largest component in the ED-AOP network gives insights on the systems-level perturbations caused by endocrine disruption, emergent paths, and stressor-event associations. In sum, the derived ED-AOP network can provide a broader view of the biological events disrupted by endocrine disruption, as well as facilitate better risk assessment of environmental chemicals.

Predicting Prenatal Developmental Toxicity Based On the Combination of Chemical Structures and Biological Data

For hazard identification, classification, and labeling purposes, animal testing guidelines are required by law to evaluate the developmental toxicity potential of new and existing chemical products. However, guideline developmental toxicity studies are costly, time-consuming, and require many laboratory animals. Computational modeling has emerged as a promising, animal-sparing, and cost-effective method for evaluating the developmental toxicity potential of chemicals, such as endocrine disruptors, without the use of animals. We aimed to develop a predictive and explainable computational model for developmental toxicants. To this end, a comprehensive dataset of 1244 chemicals with developmental toxicity classifications was curated from public repositories and literature sources. Data from 2140 toxicological high-throughput screening assays were extracted from PubChem and the ToxCast program for this dataset and combined with information about 834 chemical fragments to group assays based on their chemical-mechanistic relationships. This effort revealed two assay clusters containing 83 and 76 assays, respectively, with high positive predictive rates for developmental toxicants identified with animal testing guidelines (PPV = 72.4 and 77.3% during cross-validation). These two assay clusters can be used as developmental toxicity models and were applied to predict new chemicals for external validation. This study provides a new strategy for constructing alternative chemical developmental toxicity evaluations that can be replicated for other toxicity modeling studies.

Towards regulation of Endocrine Disrupting chemicals (EDCs) in water resources using bioassays - A guide to developing a testing strategy

Endocrine disrupting chemicals (EDCs) are found in every environmental medium and are chemically diverse. Their presence in water resources can negatively impact the health of both human and wildlife. Currently, there are no mandatory screening mandates or regulations for EDC levels in complex water samples globally. Bioassays, which allow quantifying in vivo or in vitro biological effects of chemicals are used commonly to assess acute toxicity in water. The existing OECD framework to identify single-compound EDCs offers a set of bioassays that are validated for the Estrogen-, Androgen-, and Thyroid hormones, and for Steroidogenesis pathways (EATS). In this review, we discussed bioassays that could be potentially used to screen EDCs in water resources, including in vivo and in vitro bioassays using invertebrates, fish, amphibians, and/or mammalians species. Strengths and weaknesses of samples preparation for complex water samples are discussed. We also review how to calculate the Effect-Based Trigger values, which could serve as thresholds to determine if a given water sample poses a risk based on existing quality standards. This work aims to assist governments and regulatory agencies in developing a testing strategy towards regulation of EDCs in water resources worldwide. The main recommendations include 1) opting for internationally validated cell reporter in vitro bioassays to reduce animal use & cost; 2) testing for cell viability (a critical parameter) when using in vitro bioassays; and 3) evaluating the recovery of the water sample preparation method selected. This review also highlights future research avenues for the EDC screening revolution (e.g., 3D tissue culture, transgenic animals, OMICs, and Adverse Outcome Pathways (AOPs)).

An exposomic framework to uncover environmental drivers of aging

The exposome, the environmental complement of the genome, is an omics level characterization of an individual’s exposures. There is growing interest in uncovering the role of the environment in human health using an exposomic framework that provides a systematic and unbiased analysis of the non-genetic drivers of health and disease. Many environmental toxicants are associated with molecular hallmarks of aging. An exposomic framework has potential to advance understanding of these associations and how modifications to the environment can promote healthy aging in the population. However, few studies have used this framework to study biological aging. We provide an overview of approaches and challenges in using an exposomic framework to investigate environmental drivers of aging. While capturing exposures over a life course is a daunting and expensive task, the use of historical data can be a practical way to approach this research.

Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing

New Approach Methodologies (NAMs) promise to offer a unique opportunity to enable human-relevant safety decisions to be made without the need for animal testing in the context of exposure-driven Next Generation Risk Assessment (NGRA). Protecting human health against the potential effects a chemical may have on embryo-foetal development and/or aspects of reproductive biology using NGRA is particularly challenging. These are not single endpoint or health effects and risk assessments have traditionally relied on data from Developmental and Reproductive Toxicity (DART) tests in animals. There are numerous Adverse Outcome Pathways (AOPs) that can lead to DART, which means defining and developing strict testing strategies for every AOP, to predict apical outcomes, is neither a tenable goal nor a necessity to ensure NAM-based safety assessments are fit-for-purpose. Instead, a pragmatic approach is needed that uses the available knowledge and data to ensure NAM-based exposure-led safety assessments are sufficiently protective. To this end, the mechanistic and biological coverage of existing NAMs for DART were assessed and gaps to be addressed were identified, allowing the development of an approach that relies on generating data relevant to the overall mechanisms involved in human reproduction and embryo-foetal development. Using the knowledge of cellular processes and signalling pathways underlying the key stages in reproduction and development, we have developed a broad outline of endpoints informative of DART. When the existing NAMs were compared against this outline to determine whether they provide comprehensive coverage when integrated in a framework, we found them to generally cover the reproductive and developmental processes underlying the traditionally evaluated apical endpoint studies. The application of this safety assessment framework is illustrated using an exposure-led case study.

From Causal Networks to Adverse Outcome Pathways: A Developmental Neurotoxicity Case Study

The last decade has seen the adverse outcome pathways (AOP) framework become one of the most powerful tools in chemical risk assessment, but the development of new AOPs remains a slow and manually intensive process. Here, we present a faster approach for AOP generation, based on manually curated causal toxicological networks. As a case study, we took a recently published zebrafish developmental neurotoxicity network, which contains causally connected molecular events leading to neuropathologies, and developed two new adverse outcome pathways: Inhibition of Fyna (Src family tyrosine kinase A) leading to increased mortality via decreased eye size (AOP 399 on AOP-Wiki) and GSK3beta (Glycogen synthase kinase 3 beta) inactivation leading to increased mortality via defects in developing inner ear (AOP 410). The approach consists of an automatic separation of the toxicological network into candidate AOPs, filtering the AOPs according to available evidence and length as well as manual development of new AOPs and weight-of-evidence evaluation. The semiautomatic approach described here provides a new opportunity for fast and straightforward AOP development based on large network resources.

A Putative Adverse Outcome Pathway Network for Disrupted Female Pubertal Onset to Improve Testing and Regulation of Endocrine Disrupting Chemicals

The average age for pubertal onset in girls has declined over recent decades. Epidemiological studies in humans and experimental studies in animals suggest a causal role for endocrine disrupting chemicals (EDCs) that are present in our environment. Of concern, current testing and screening regimens are inadequate in identifying EDCs that may affect pubertal maturation, not least because they do not consider early-life exposure. Also, the causal relationship between EDC exposure and pubertal timing is still a matter of debate. To address this issue, we have used current knowledge to elaborate a network of putative adverse outcome pathways (pAOPs) to identify how chemicals can affect pubertal onset. By using the AOP framework, we highlight current gaps in mechanistic understanding that need to be addressed and simultaneously point towards events causative of pubertal disturbance that could be exploited for alternative test methods. We propose 6 pAOPs that could explain the disruption of pubertal timing by interfering with the central hypothalamic trigger of puberty, GnRH neurons, and by so doing highlight specific modes of action that could be targeted for alternative test method development.

(Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future

Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects of chemicals on aquatic species and ecosystems. This is primarily because of the increasing number of (unknown) chemical stressors and mixture effects present in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal, population, or community level. We performed a literature search to obtain a state-of-the-art overview of ecotoxicological tests available for assessing impacts of chemicals to aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level, and 78 tests at the population- community- and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests at the community- and ecosystem-level were almost missing for organisms other than microorganisms and algae. In addition, we provide an overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemical stressors to aquatic ecosystems.

Development of a putative adverse outcome pathway network for male rat reproductive tract abnormalities with specific considerations for the androgen sensitive window of development

Structured approaches like the adverse outcome pathway (AOP) framework offer great potential for depicting complex toxicological processes in a manner that can facilitate informed integration of mechanistic information in regulatory decisions. While this concept provides a structure for organizing evidence and facilitates consistency in evidence integration; the process, inputs, and manner in which AOPs and AOP networks are developed is still evolving. Following the OECD guiding principles of AOP development, we propose three AOPs for male reproductive tract abnormalities and derive a putative AOP network. The AOPs were developed using a fundamental understanding of the developmental biology of the organs of interest, paying close attention to the gestational timing of key events (KEs) to very specifically inform the domain of life stage applicability for the key event relationships (KERs). Chemical stressor data primarily from studies on low molecular weight phthalates (LMWPs) served to 'bound' the pathways of focus in this dynamic period of development and were integrated with the developmental biology data through an iterative process to define KEs and conclude on the extent of evidence in support of the KERs. The AOPs developed describe the linkage between 1) a decrease in Insl3 gene expression and cryptorchidism, 2) the sustained expression of Coup-tfII and hypospadias and 3) the sustained expression of Coup-tfII and altered Wolffian duct development/ epididymal agenesis. A putative AOP network linking AOP2 and AOP3 through decreased steroidogenic biosynthetic protein expression and converging of all AOPS at the population level impaired fertility adverse outcome is proposed. The network depiction specifies and displays the KEs aligned with their occurrence in gestational time. The pathways and network described herein are intended to catalyze collaborative initiatives for expansion into a larger network to enable effective data collection and inform alternative approaches for identifying stressors impacting this sensitive period of male reproductive tract development.

Cadmium Exposure and Testis Susceptibility: a Systematic Review in Murine Models

It is known that cadmium induces damage to the testis. However, the significant cadmium impact on the testicular architecture and the mechanisms involved in this process are not clear. Besides, the relationship between dose, route, and time of exposure and injuries remains poorly understood. Thus, we aimed to assess whether cadmium exposure in any dose, route, and time of exposure causes significant alteration in the testicular tissue of murine models, as well as the main mechanisms involved. We performed a structured search on the Medline/PubMed and Scopus databases to retrieve studies published until September 2018. The results were organized into an Adverse Outcome Pathway (AOP) framework. Also, a bias analysis of included studies was performed. We included 37 studies, and most of them identified significant histopathologies in both tubule and intertubule regarding routes, in a dose- and time-dependent manner. The damages were observed after the first hours of exposure, mainly vascular damages suggesting that vasculature failure is the primary mechanism. The AOP showed that potential molecular initiating events may mimic and interfere with essential elements disrupting proteins (structural and antioxidants), change in the oxidative phosphorylation enzyme activities, and gene expression alteration, which lead to reproductive failure (adverse outcome). Analysis of methodological quality showed that the current evidence is at high risk of bias. Despite the high risk of bias, cadmium triggers significant lesions in the testis of murine models, regarding routes, in a dose- and time-dependent manner, mainly due to vascular changes. Therefore, cadmium is a risk factor for male reproductive health.

Multi-region assessment of chemical mixture exposures and predicted cumulative effects in USA wadeable urban/agriculture-gradient streams

Chemical-contaminant mixtures are widely reported in large stream reaches in urban/agriculture-developed watersheds, but mixture compositions and aggregate biological effects are less well understood in corresponding smaller headwaters, which comprise most of stream length, riparian connectivity, and spatial biodiversity. During 2014-2017, the U.S. Geological Survey (USGS) measured 389 unique organic analytes (pharmaceutical, pesticide, organic wastewater indicators) in 305 headwater streams within four contiguous United States (US) regions. Potential aquatic biological effects were evaluated for estimated maximum and median exposure conditions using multiple lines of evidence, including occurrence/concentrations of designed-bioactive pesticides and pharmaceuticals and cumulative risk screening based on vertebrate-centric ToxCast™ exposure-response data and on invertebrate and nonvascular plant aquatic life benchmarks. Mixed-contaminant exposures were ubiquitous and varied, with 78% (304) of analytes detected at least once and cumulative maximum concentrations up to more than 156,000 ng/L. Designed bioactives represented 83% of detected analytes. Contaminant summary metrics correlated strong-positive (rho (ρ): 0.569-0.719) to multiple watershed-development metrics, only weak-positive to point-source discharges (ρ: 0.225-353), and moderate- to strong-negative with multiple instream invertebrate metrics (ρ: -0.373 to -0.652). Risk screening indicated common exposures with high probability of vertebrate-centric molecular effects and of acute toxicity to invertebrates, respectively. The results confirm exposures to broad and diverse contaminant mixtures and provide convincing multiple lines of evidence that chemical contaminants contribute substantially to adverse multi-stressor effects in headwater-stream communities.

Novel QSAR Models for Molecular Initiating Event Modeling in Two Intersecting Adverse Outcome Pathways Based Pulmonary Fibrosis Prediction for Biocidal Mixtures

The adverse outcome pathway (AOP) was introduced as an alternative method to avoid unnecessary animal tests. Under the AOP framework, an in silico methods, molecular initiating event (MIE) modeling is used based on the ligand-receptor interaction. Recently, the intersecting AOPs (AOP 347), including two MIEs, namely peroxisome proliferator-activated receptor-gamma (PPAR-γ) and toll-like receptor 4 (TLR4), associated with pulmonary fibrosis was proposed. Based on the AOP 347, this study developed two novel quantitative structure-activity relationship (QSAR) models for the two MIEs. The prediction performances of different MIE modeling methods (e.g., molecular dynamics, pharmacophore model, and QSAR) were compared and validated with in vitro test data. Results showed that the QSAR method had high accuracy compared with other modeling methods, and the QSAR method is suitable for the MIE modeling in the AOP 347. Therefore, the two QSAR models based on the AOP 347 can be powerful models to screen biocidal mixture related to pulmonary fibrosis.

Simultaneous determination of a suite of endogenous steroids by LC-APPI-MS: Application to the identification of endocrine disruptors in aquatic toxicology

Exposure to endocrine-disrupting compounds (EDCs) can alter steroid hormone production in vertebrates, sometimes leading to adverse reproductive or developmental effects. Liquid chromatography mass spectrometry methods are the gold standard for analyte confirmation and quantification in biological matrices, but radioimmunoassays (RIAs) are most commonly used for measurement of select steroid hormones in aquatic toxicology studies. Existing methods for steroid quantification often employ derivatization, limiting the range of steroids that can be simultaneously measured in a single process. In the current study, a method for the simultaneous measurement of thirteen endogenous steroids in small sample volumes without derivatization using liquid chromatography atmospheric pressure photoionization tandem mass spectrometry (LC-APPI-MS/MS) was developed. Several physiologically important steroids, including 11-deoxycortisol, 11-ketotestosterone, 17α- and 17β-estradiol, 17α-hydroxyprogesterone, 17,20β-dihydroxyprogesterone, 17,20β,21-trihydroxyprogesterone, androstenedione, cortisol, estriol, estrone, progesterone, and testosterone, were selected for the analysis. The method was validated for application to small volumes of fish plasma and fish holding water. Method detection limits using only 10 µL of plasma ranged from 0.05 to 1.0 ng/mL. As a potential surrogate for plasma steroid measurements, fish holding water was analyzed to measure excreted steroids. Lower limits of quantification when using 0.25 L of water ranged from 0.05 to 1.0 ng/L. The validated method was applied to two different experiments with small fish species exposed to an EDC known to affect steroid synthesis, fadrozole. Concentrations of the 13 steroids were measured in plasma or holding water from the studies. This work demonstrates the potential application of the developed method to measure endogenous steroids for identification of EDCs in aquatic toxicology studies.

Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models

In recent times, machine learning has become increasingly prominent in predictive toxicology as it has shifted from in vivo studies toward in silico studies. Currently, in vitro methods together with other computational methods such as quantitative structure-activity relationship modeling and absorption, distribution, metabolism, and excretion calculations are being used. An overview of machine learning and its applications in predictive toxicology is presented here, including support vector machines (SVMs), random forest (RF) and decision trees (DTs), neural networks, regression models, naïve Bayes, k-nearest neighbors, and ensemble learning. The recent successes of these machine learning methods in predictive toxicology are summarized, and a comparison of some models used in predictive toxicology is presented. In predictive toxicology, SVMs, RF, and DTs are the dominant machine learning methods due to the characteristics of the data available. Lastly, this review describes the current challenges facing the use of machine learning in predictive toxicology and offers insights into the possible areas of improvement in the field.

Generating adverse outcome pathway (AOP) of inorganic arsenic-induced adult male reproductive impairment via integration of phenotypic analysis in comparative toxicogenomics database (CTD) and AOP wiki

BACKGROUND

Inorganic arsenic (iAs) is a worldwide environmental pollutant which exerts complicated and various toxic effects in organisms. Increasingly epidemic studies have revealed the association between iAs exposure and adult male reproductive impairment. Consistent with the proposal for toxicity testing in the 21st century (TT21C), the adverse outcome pathway (AOP) framework may help unravel the iAs-caused molecular and functional changes leading to male reproductive impairment.

METHOD

Combining CTD's phenotype-disease inference data, iAs-phenotypes were anchored to five male reproductive diseases induced by iAs, and local network topological algorithm was applied in prioritizing their interference significance. Through integrating analysis in AOP Wiki knowledge base, filtered phenotypes were linked to key events consisting of AOPs and assembled together based on evidentially upstream and downstream relationships.

RESULTS

A subset of 655 phenotypes were filtered from CTD as potential key events and showed a significant coherence in five reproductive diseases wherein 39 significant phenotypes showed a good clustering features involving cell cycle, ROS and mitochondria function. Two AOP subnetworks were enriched in AOP Wiki where testosterone reduction and apoptosis of sperm served as focus events respectively. Besides, a candidates list of molecular initialing events was provided of which glucocorticoid receptor activation was overall assessed as an example.

CONCLUSION

This study applied computational and bioinformatics methods in generating AOPs for arsenic reproductive toxicity, which identified the imperative roles of testosterone reduction, response to ROS, spermatogenesis and provided a global view about their internal association. Furthermore, this study helped address the existing knowledge gaps for future experimental verification.

Toward an AOP Network-Based Tiered Testing Strategy for the Assessment of Thyroid Hormone Disruption

A growing number of environmental pollutants are known to adversely affect the thyroid hormone system, and major gaps have been identified in the tools available for the identification, and the hazard and risk assessment of these thyroid hormone disrupting chemicals. We provide an example of how the adverse outcome pathway (AOP) framework and associated data generation can address current testing challenges in the context of fish early life stage tests, and fish tests in general. We demonstrate how a suite of assays covering biological processes involved in the underlying toxicological pathways can be implemented in a tiered screening and testing approach for thyroid hormone disruption, using the levels of assessment of the OECD's Conceptual Framework for the Testing and Assessment of Endocrine Disrupting Chemicals as a guide.

Organizing mechanism-related information on chemical interactions using a framework based on the aggregate exposure and adverse outcome pathways

This paper presents a framework for organizing and accessing mechanistic data on chemical interactions. The framework is designed to support the assessment of risks from combined chemical exposures. The framework covers interactions between chemicals that occur over the entire source-to-outcome continuum including interactions that are studied in the fields of chemical transport, environmental fate, exposure assessment, dosimetry, and individual and population-based adverse outcomes. The framework proposes to organize data using a semantic triple of a chemical (subject), has impact (predicate), and a causal event on the source-to-outcome continuum of a second chemical (object). The location of the causal event on the source-to-outcome continuum and the nature of the impact are used as the basis for a taxonomy of interactions. The approach also builds on concepts from the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP). The framework proposes the linking of AEPs of multiple chemicals and the AOP networks relevant to those chemicals to form AEP-AOP networks that describe chemical interactions that cannot be characterized using AOP networks alone. Such AEP-AOP networks will aid the construction of workflows for both experimental design and the systematic review or evaluation performed in risk assessments. Finally, the framework is used to link the constructs of existing component-based approaches for mixture toxicology to specific categories in the interaction taxonomy.

Critical Review of Read-Across Potential in Testing for Endocrine-Related Effects in Vertebrate Ecological Receptors

Recent regulatory testing programs have been designed to evaluate whether a chemical has the potential to interact with the endocrine system and could cause adverse effects. Some endocrine pathways are highly conserved among vertebrates, providing a potential to extrapolate data generated for one vertebrate taxonomic group to others (i.e., biological read-across). To assess the potential for biological read-across, we reviewed tools and approaches that support species extrapolation for fish, amphibians, birds, and reptiles. For each of the estrogen, androgen, thyroid, and steroidogenesis (EATS) pathways, we considered the pathway conservation across species and the responses of endocrine-sensitive endpoints. The available data show a high degree of confidence in the conservation of the hypothalamus-pituitary-gonadal axis between fish and mammals and the hypothalamus-pituitary-thyroid axis between amphibians and mammals. Comparatively, there is less empirical evidence for the conservation of other EATS pathways between other taxonomic groups, but this may be due to limited data. Although more information on sensitive pathways and endpoints would be useful, current developments in the use of molecular target sequencing similarity tools and thoughtful application of the adverse outcome pathway concept show promise for further advancement of read-across approaches for testing EATS pathways in vertebrate ecological receptors. Environ Toxicol Chem 2020;39:739-753. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity

High-throughput and computational tools provide a new opportunity to calculate combined bioactivity of exposure to diverse chemicals acting through a common mechanism. We used high throughput in vitro bioactivity data and exposure predictions from the U.S. EPA's Toxicity and Exposure Forecaster (ToxCast and ExpoCast) to estimate combined estrogen receptor (ER) agonist activity of non-pharmaceutical chemical exposures for the general U.S. population. High-throughput toxicokinetic (HTTK) data provide conversion factors that relate bioactive concentrations measured in vitro (µM), to predicted population geometric mean exposure rates (mg/kg/day). These data were available for 22 chemicals with ER agonist activity and were estimated for other ER bioactive chemicals based on the geometric mean of HTTK values across chemicals. For each chemical, ER bioactivity across ToxCast assays was compared to predicted population geometric mean exposure at different levels of in vitro potency and model certainty. Dose additivity was assumed in calculating a Combined Exposure-Bioactivity Index (CEBI), the sum of exposure/bioactivity ratios. Combined estrogen bioactivity was also calculated in terms of the percent maximum bioactivity of chemical mixtures in human plasma using a concentration-addition model. Estimated CEBIs vary greatly depending on assumptions used for exposure and bioactivity. In general, CEBI values were <1 when using median of the estimated general population chemical intake rates, while CEBI were ≥1 when using the upper 95th confidence bound for those same intake rates for all chemicals. Concentration-addition model predictions of mixture bioactivity yield comparable results. Based on current in vitro bioactivity data, HTTK methods, and exposure models, combined exposure scenarios sufficient to influence estrogen bioactivity in the general population cannot be ruled out. Future improvements in screening methods and computational models could reduce uncertainty and better inform the potential combined effects of estrogenic chemicals.

Adverse Outcome Pathway Network-Based Assessment of the Interactive Effects of an Androgen Receptor Agonist and an Aromatase Inhibitor on Fish Endocrine Function

Predictive approaches to assessing the toxicity of contaminant mixtures have been largely limited to chemicals that exert effects through the same biological molecular initiating event. However, by understanding specific pathways through which chemicals exert effects, it may be possible to identify shared "downstream" nodes as the basis for forecasting interactive effects of chemicals with different molecular initiating events. Adverse outcome pathway (AOP) networks conceptually support this type of analysis. We assessed the utility of a simple AOP network for predicting the effects of mixtures of an aromatase inhibitor (fadrozole) and an androgen receptor agonist (17β-trenbolone) on aspects of reproductive endocrine function in female fathead minnows. The fish were exposed to multiple concentrations of fadrozole and 17β-trenbolone individually or in combination for 48 or 96 h. Effects on 2 shared nodes in the AOP network, plasma 17β-estradiol (E2) concentration and vitellogenin (VTG) production (measured as hepatic vtg transcripts) responded as anticipated to fadrozole alone but were minimally impacted by 17β-trenbolone alone. Overall, there were indications that 17β-trenbolone enhanced decreases in E2 and vtg in fadrozole-exposed fish, as anticipated, but the results often were not statistically significant. Failure to consistently observe hypothesized interactions between fadrozole and 17β-trenbolone could be due to several factors, including lack of impact of 17β-trenbolone, inherent biological variability in the endpoints assessed, and/or an incomplete understanding of interactions (including feedback) between different pathways within the hypothalamic-pituitary-gonadal axis. Environ Toxicol Chem 2020;39:913-922. © 2020 SETAC.

Deciphering Adverse Outcome Pathway Network Linked to Bisphenol F Using Text Mining and Systems Toxicology Approaches

Bisphenol F (BPF) is one of several Bisphenol A (BPA) substituents that is increasingly used in manufacturing industry leading to detectable human exposure. Whereas a large number of studies have been devoted to decipher BPA effects, much less is known about its substituents. To support decision making on BPF's safety, we have developed a new computational approach to rapidly explore the available data on its toxicological effects, combining text mining and integrative systems biology, and aiming at connecting BPF to adverse outcome pathways (AOPs). We first extracted from different databases BPF-protein associations that were expanded to protein complexes using protein-protein interaction datasets. Over-representation analysis of the protein complexes allowed to identify the most relevant biological pathways putatively targeted by BPF. Then, automatic screening of scientific abstracts from literature using the text mining tool, AOP-helpFinder, combined with data integration from various sources (AOP-wiki, CompTox, etc.) and manual curation allowed us to link BPF to AOP events. Finally, we combined all the information gathered through those analyses and built a comprehensive complex framework linking BPF to an AOP network including, as adverse outcomes, various types of cancers such as breast and thyroid malignancies. These results which integrate different types of data can support regulatory assessment of the BPA substituent, BPF, and trigger new epidemiological and experimental studies.

Progress in data interoperability to support computational toxicology and chemical safety evaluation

New approach methodologies (NAMs) in chemical safety evaluation are being explored to address the current public health implications of human environmental exposures to chemicals with limited or no data for assessment. For over a decade since a push toward "Toxicity Testing in the 21st Century," the field has focused on massive data generation efforts to inform computational approaches for preliminary hazard identification, adverse outcome pathways that link molecular initiating events and key events to apical outcomes, and high-throughput approaches to risk-based ratios of bioactivity and exposure to inform relative priority and safety assessment. Projects like the interagency Tox21 program and the US EPA ToxCast program have generated dose-response information on thousands of chemicals, identified and aggregated information from legacy systems, and created tools for access and analysis. The resulting information has been used to develop computational models as viable options for regulatory applications. This progress has introduced challenges in data management that are new, but not unique, to toxicology. Some of the key questions require critical thinking and solutions to promote semantic interoperability, including: (1) identification of bioactivity information from NAMs that might be related to a biological process; (2) identification of legacy hazard information that might be related to a key event or apical outcomes of interest; and, (3) integration of these NAM and traditional data for computational modeling and prediction of complex apical outcomes such as carcinogenesis. This work reviews a number of toxicology-related efforts specifically related to bioactivity and toxicological data interoperability based on the goals established by Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles. These efforts are essential to enable better integration of NAM and traditional toxicology information to support data-driven toxicology applications.

Arctic marine fish 'biotransformation toxicity' model for ecological risk assessment

Oil and gas exploration and marine transport in the Arctic region have put the focus on the ecological risk of the possibly exposed organisms. In the present study, the impacts of sea ice, extreme light regime, various polar region-specific physiological characteristics in polar cod (Boreogadus saida) and their effects on xenobiotic distribution and metabolism are studied. A Bayesian belief network is used to model individual fish toxicity. The enzyme activity in the fish liver and other pertinent organs is used as a proxy for cellular damage and repair and is subsequently linked to toxicity in polar cod. Seasonal baseline variation in enzyme production is also taken into consideration. The model estimates the probability of exposure concentration to cause cytotoxicity and circumvents the need to use the traditionally obtained No Observed Effect Concentration (NOEC). Instead, it uses biotransformation enzyme activity as a basis to estimate the probability of individual cell damages.

Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development

The U.S. Environmental Protection Agency's ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential apical effects relevant to risk assessors. Thus, efforts are underway to develop AOPs relevant to pathway-specific perturbations detected in ToxCast assays. Previous work identified a "cytotoxic burst" (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared with the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). The prioritization approaches did not appear to be influenced by inter-assay differences in chemical bioavailability. Furthermore, the outcomes were robust based on a variety of different parameters used to define the CTB.

Mixed-chemical exposure and predicted effects potential in wadeable southeastern USA streams

Complex chemical mixtures have been widely reported in larger streams but relatively little work has been done to characterize them and assess their potential effects in headwater streams. In 2014, the United States Geological Survey (USGS) sampled 54 Piedmont streams over ten weeks and measured 475 unique organic compounds using five analytical methods. Maximum and median exposure conditions were evaluated in relation to watershed characteristics and for potential biological effects using multiple lines of evidence. Results demonstrate that mixed-contaminant exposures are ubiquitous and varied in sampled headwater streams. Approximately 56% (264) of the 475 compounds were detected at least once across all sites. Cumulative maximum concentrations ranged 1,922-162,346ngL^-1 per site. Chemical occurrence significantly correlated to urban land use but was not related to presence/absence of wastewater treatment facility discharges. Designed bioactive chemicals represent about 2/3rd of chemicals detected, notably pharmaceuticals and pesticides, qualitative evidence for possible adverse biological effects. Comparative Toxicogenomics Database chemical-gene associations applied to maximum exposure conditions indicate >12,000 and 2,900 potential gene targets were predicted at least once across all sites for fish and invertebrates, respectively. Analysis of cumulative exposure-activity ratios provided additional evidence that, at a minimum, transient exposures with high probability of molecular effects to vertebrates were common. Finally, cumulative detections and concentrations correlated inversely with invertebrate metrics from in-stream surveys. The results demonstrate widespread instream exposure to extensive contaminant mixtures and compelling multiple lines of evidence for adverse effects on aquatic communities.

Bioenergetics-adverse outcome pathway: Linking organismal and suborganismal energetic endpoints to adverse outcomes

Adverse outcome pathways (AOPs) link toxicity across levels of biological organization, and thereby facilitate the development of suborganismal responses predictive of whole-organism toxicity and provide the mechanistic information necessary for science-based extrapolation to population-level effects. Thus far AOPs have characterized various acute and chronic toxicity pathways; however, the potential for AOPs to explicitly characterize indirect, energy-mediated effects from toxicants has yet to be fully explored. Indeed, although exposure to contaminants can alter an organism's energy budget, energetic endpoints are rarely incorporated into ecological risk assessment because there is not an integrative framework for linking energetic effects to organismal endpoints relevant to risk assessment (e.g., survival, reproduction, growth). In the present analysis, we developed a generalized bioenergetics-AOP in an effort to make better use of energetic endpoints in risk assessment, specifically exposure scenarios that generate an energetic burden to organisms. To evaluate empirical support for a bioenergetics-AOP, we analyzed published data for links between energetic endpoints across levels of biological organization. We found correlations between 1) cellular energy allocation and whole-animal growth, and 2) metabolic rate and scope for growth. Moreover, we reviewed literature linking energy availability to nontraditional toxicological endpoints (e.g., locomotor performance), and found evidence that toxicants impair aerobic performance and activity. We conclude by highlighting current knowledge gaps that should be addressed to develop specific bioenergetics-AOPs. Environ Toxicol Chem 2019;38:27-45. © 2018 SETAC.

Infer the in vivo point of departure with ToxCast in vitro assay data using a robust learning approach

The development and application of high throughput in vitro assays is an important development for risk assessment in the twenty-first century. However, there are still significant challenges to incorporate in vitro assays into routine toxicity testing practices. In this paper, a robust learning approach was developed to infer the in vivo point of departure (POD) with in vitro assay data from ToxCast and Tox21 projects. Assay data from ToxCast and Tox21 projects were utilized to derive the in vitro PODs for several hundred chemicals. These were combined with in vivo PODs from ToxRefDB regarding the rat and mouse liver to build a high-dimensional robust regression model. This approach separates the chemicals into a majority, well-predicted set; and a minority, outlier set. Salient relationships can then be learned from the data. For both mouse and rat liver PODs, over 93% of chemicals have inferred values from in vitro PODs that are within ± 1 of the in vivo PODs on the log₁₀ scale (the target learning region, or TLR) and R² of 0.80 (rats) and 0.78 (mice) for these chemicals. This is comparable with extrapolation between related species (mouse and rat), which has 93% chemicals within the TLR and the R² being 0.78. Chemicals in the outlier set tend to also have more biologically variable characteristics. With the continued accumulation of high throughput data for a wide range of chemicals, predictive modeling can provide a valuable complement for adverse outcome pathway based approach in risk assessment.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

The Adverse Outcome Pathway: A Multifaceted Framework Supporting 21st Century Toxicology

The adverse outcome pathway (AOP) framework serves as a knowledge assembly, interpretation, and communication tool designed to support the translation of pathway-specific mechanistic data into responses relevant to assessing and managing risks of chemicals to human health and the environment. As such, AOPs facilitate the use of data streams often not employed by risk assessors, including information from in silico models, in vitro assays and short-term in vivo tests with molecular/biochemical endpoints. This translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures. Our mini-review describes the conceptual basis of the AOP framework and aspects of its current status relative to use by toxicologists and risk assessors, including four illustrative applications of the framework to diverse assessment scenarios.

Adverse outcome pathway networks I: Development and applications

Based on the results of a Horizon Scanning exercise sponsored by the Society of Environmental Toxicology and Chemistry that focused on advancing the adverse outcome pathway (AOP) framework, the development of guidance related to AOP network development was identified as a critical need. This not only included questions focusing directly on AOP networks, but also on related topics such as mixture toxicity assessment and the implementation of feedback loops within the AOP framework. A set of two articles has been developed to begin exploring these concepts. In the present article (part I), we consider the derivation of AOP networks in the context of how it differs from the development of individual AOPs. We then propose the use of filters and layers to tailor AOP networks to suit the needs of a given research question or application. We briefly introduce a number of analytical approaches that may be used to characterize the structure of AOP networks. These analytical concepts are further described in a dedicated, complementary article (part II). Finally, we present a number of case studies that illustrate concepts underlying the development, analysis, and application of AOP networks. The concepts described in the present article and in its companion article (which focuses on AOP network analytics) are intended to serve as a starting point for further development of the AOP network concept, and also to catalyze AOP network development and application by the different stakeholder communities. Environ Toxicol Chem 2018;37:1723-1733. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

AOP-DB: A database resource for the exploration of Adverse Outcome Pathways through integrated association networks

The Adverse Outcome Pathway (AOP) framework describes the progression of a toxicity pathway from molecular perturbation to population-level outcome in a series of measurable, mechanistic responses. The controlled, computer-readable vocabulary that defines an AOP has the ability to, automatically and on a large scale, integrate AOP knowledge with publically available sources of biological high-throughput data and its derived associations. To support the discovery and development of putative (existing) and potential AOPs, we introduce the AOP-DB, an exploratory database resource that aggregates association relationships between genes and their related chemicals, diseases, pathways, species orthology information, ontologies, and gene interactions. These associations are mined from publically available annotation databases and are integrated with the AOP information centralized in the AOP-Wiki, allowing for the automatic characterization of both putative and potential AOPs in the context of multiple areas of biological information, referred to here as "biological entities". The AOP-DB acts as a hypothesis-generation tool for the expansion of putative AOPs, as well as the characterization of potential AOPs, through the creation of association networks across these biological entities. Finally, the AOP-DB provides a useful interface between the AOP framework and existing chemical screening and prioritization efforts by the US Environmental Protection Agency.

A Case Study Application of the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) Frameworks to Facilitate the Integration of Human Health and Ecological End Points for Cumulative Risk Assessment (CRA)

Cumulative risk assessment (CRA) methods promote the use of a conceptual site model (CSM) to apportion exposures and integrate risk from multiple stressors. While CSMs may encompass multiple species, evaluating end points across taxa can be challenging due to data availability and physiological differences among organisms. Adverse outcome pathways (AOPs) describe biological mechanisms leading to adverse outcomes (AOs) by assembling causal pathways with measurable intermediate steps termed key events (KEs), thereby providing a framework for integrating data across species. In this work, we used a case study focused on the perchlorate anion (ClO4-) to highlight the value of the AOP framework for cross-species data integration. Computational models and dose-response data were used to evaluate the effects of ClO4- in 12 species and revealed a dose-response concordance across KEs and taxa. The aggregate exposure pathway (AEP) tracks stressors from sources to the exposures and serves as a complement to the AOP. We discuss how the combined AEP-AOP construct helps to maximize the use of existing data and advances CRA by (1) organizing toxicity and exposure data, (2) providing a mechanistic framework of KEs for integrating data across human health and ecological end points, (3) facilitating cross-species dose-response evaluation, and (4) highlighting data gaps and technical limitations.