Are adverse outcome pathways here to stay?

Ascertaining sensitive exposure biomarkers of various metal(loid)s to embryo implantation

Close relationships exist between metal(loid)s exposure and embryo implantation failure (EIF) from animal and epidemiological studies. However, there are still inconsistent results and lacking of sensitive metal(loid) exposure biomarkers associated with EIF risk. We aimed to ascertain sensitive metal(loid) biomarkers to EIF and provide potential biological explanations. Candidate metal(loid) biomarkers were measured in the female hair (FH), female serum (FS), and follicular fluid (FF) with various exposure time periods. An analytical framework was established by integrating epidemiological association results, comprehensive literature searching, and knowledge-based adverse outcome pathway (AOP) networks. The sensitive biomarkers of metal(loid)s along with potential biological pathways to EIF were identified in this framework. Among the concerned 272 candidates, 45 metal(loid)s biomarkers across six time periods and three biomatrix were initially identified by single-metal(loid) analyses. Two biomarkers with counterfactual results according to literature summary results were excluded, and a total of five biomarkers were further determined from 43 remained candidates in mixture models. Finally, four sensitive metal(loid) biomarkers were eventually assessed by overlapping AOP networks information, including Se and Co in FH, and Fe and Zn in FS. AOP networks also identified key GO pathways and proteins involved in regulation of oxygen species biosynthetic, cell proliferation, and inflammatory response. Partial dependence results revealed Fe in FS and Co in FH at their low levels might be potential sensitive exposure levels for EIF. Our study provided a typical framework to screen the crucial metal(loid) biomarkers and ascertain that Se and Co in FH, and Fe and Zn in FS played an important role in embryo implantation.

Putative adverse outcome pathways of the male reproductive toxicity derived from toxicological studies of perfluoroalkyl acids

Adverse outcome pathway (AOP) as a conceptual framework is a powerful tool in the field of toxicology to connect seemingly discrete events at different levels of biological organizations into an organized pathway from molecular interactions to whole organism toxicity. Based on numerous toxicological studies, eight AOPs for reproductive toxicity have been endorsed by the Organization for Economic Co-operation and Development (OECD) Task Force on Hazard Assessment. We have conducted a literature survey on the mechanistic studies on male reproductive toxicity of perfluoroalkyl acids (PFAAs), a class of global environmental contaminants with high persistence, bioaccumulation and toxicity. Using the AOP development strategy, five new AOPs for male reproductive toxicity were proposed here, namely (1) changes in membrane permeability leading to reduced sperm motility, (2) disruption of mitochondrial function leading to sperm apoptosis, (3) decreased gonadotropin-releasing hormone (GnRH) expression in hypothalamus leading to reduced testosterone production in male rats, (4) activation of the p38 signaling pathway leading to disruption of BTB in mice, (5) inhibition of p-FAK-Tyr407 activity leading to the destruction of BTB. The molecular initiating events in the proposed AOPs are different from those in the endorsed AOPs, which are either receptor activation or enzyme inhibition. Although some of the AOPs are still incomplete, they can serve as a building block upon which full AOPs can be developed and applied to not only PFAAs but also other chemical toxicants with male reproductive toxicity.

Genes-to-Pathways Species Conservation Analysis: Enabling the Exploration of Conservation of Biological Pathways and Processes Across Species

The last two decades have witnessed a strong momentum toward integration of cell-based and computational approaches in safety assessments. This is fueling a global regulatory paradigm shift toward reduction and replacement of the use of animals in toxicity tests while promoting the use of new approach methodologies. The understanding of conservation of molecular targets and pathways provides an opportunity to extrapolate effects across species and ultimately to determine the taxonomic applicability domain of assays and biological effects. Despite the wealth of genome-linked data available, there is a compelling need for improved accessibility, while ensuring that it reflects the underpinning biology. We present the novel pipeline Genes-to-Pathways Species Conservation Analysis (G2P-SCAN) to further support understanding on cross-species extrapolation of biological processes. This R package extracts, synthetizes, and structures the data available from different databases, that is, gene orthologs, protein families, entities, and reactions, linked to human genes and respective pathways across six relevant model species. The use of G2P-SCAN enables the overall analysis of orthology and functional families to substantiate the identification of conservation and susceptibility at the pathway level. In the present study we discuss five case studies, demonstrating the validity of the developed pipeline and its potential use as species extrapolation support. We foresee this pipeline will provide valuable biological insights and create space for the use of mechanistically based data to inform potential species susceptibility for research and safety decision purposes. Environ Toxicol Chem 2023;42:1152-1166. © 2023 UNILEVER GLOBAL IP LTD. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Identification of molecular initiating events (MIE) using chemical database analysis and nuclear receptor activity assays for screening potential inhalation toxicants

An adverse outcome pathway (AOP) framework can facilitate the use of alternative assays in chemical regulations by providing scientific evidence. Previously, an AOP, peroxisome proliferative-activating receptor gamma (PPARγ) antagonism that leads to pulmonary fibrosis, was developed. Based on a literature search, PPARγ inactivation has been proposed as a molecular initiating event (MIE). In addition, a list of candidate chemicals that could be used in the experimental validation was proposed using toxicity database and deep learning models. In this study, the screening of environmental chemicals for MIE was conducted using in silico and in vitro tests to maximize the applicability of this AOP for screening inhalation toxicants. Initially, potential inhalation exposure chemicals that are active in three or more key events were selected, and in silico molecular docking was performed. Among the chemicals with low binding energy to PPARγ, nine chemicals were selected for validation of the AOP using in vitro PPARγ activity assay. As a result, rotenone, triorthocresyl phosphate, and castor oil were proposed as PPARγ antagonists and stressor chemicals of the AOP. Overall, the proposed tiered approach of the database-in silico-in vitro can help identify the regulatory applicability and assist in the development and experimental validation of AOP.

Integrated Genomic and Bioinformatics Approaches to Identify Molecular Links between Endocrine Disruptors and Adverse Outcomes

Exposure to Endocrine Disrupting Chemicals (EDC) has been linked with several adverse outcomes. In this review, we examine EDCs that are pervasive in the environment and are of concern in the context of human, animal, and environmental health. We explore the consequences of EDC exposure on aquatic life, terrestrial animals, and humans. We focus on the exploitation of genomics technologies and in particular whole transcriptome sequencing. Genome-wide analyses using RNAseq provides snap shots of cellular, tissue and whole organism transcriptomes under normal physiological and EDC perturbed conditions. A global view of gene expression provides highly valuable information as it uncovers gene families or more specifically, pathways that are affected by EDC exposures, but also reveals those that are unaffected. Hypotheses about genes with unknown functions can also be formed by comparison of their expression levels with genes of known function. Risk assessment strategies leveraging genomic technologies and the development of toxicology databases are explored. Finally, we review how the Adverse Outcome Pathway (AOP) has exploited this high throughput data to provide a framework for toxicology studies.

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.

Systems analysis of the liver transcriptome in adult male zebrafish exposed to the non-ionic surfactant nonylphenol

Nonylphenol (NP) arises from the environmental degradation of nonylphenol ethoxylates. It is a ubiquitous environmental contaminant and has been detected at levels up to 167 nM in rivers in the United States. NP is an endocrine disruptor (ED) that can act as an agonist for estrogen receptors. The Adverse Outcome Pathway (AOP) framework defines an adverse outcome as the causal result of a series of molecular initiating events (MIEs) and key events (KEs) that lead to altered phenotypes. This study examined the liver transcriptome after a 21 day exposure to NP and 17β-estradiol (E2) by exploiting the zebrafish (Danio rerio) as a systems toxicology model. The goal of this study was to tease out non-estrogenic genomic signatures associated with NP exposure using DNA microarray and RNA sequencing. Our experimental design included E2 as a positive and potent estrogenic control in order to effectively compare and contrast the 2 compounds. This approach allowed us to identify hepatic transcriptomic perturbations that could serve as MIEs for adverse health outcomes in response to NP. Our results revealed that exposure to NP was associated with differential expression (DE) of genes associated with the development of steatosis, disruption of metabolism, altered immune response, and metabolism of reactive oxygen species, further highlighting NP as a chemical of emerging concern (CEC).

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.

Systems Analysis of the Liver Transcriptome in Adult Male Zebrafish Exposed to the Plasticizer (2-Ethylhexyl) Phthalate (DEHP)

The organic compound diethylhexyl phthalate (DEHP) represents a high production volume chemical found in cosmetics, personal care products, laundry detergents, and household items. DEHP, along with other phthalates causes endocrine disruption in males. Exposure to endocrine disrupting chemicals has been linked to the development of several adverse health outcomes with apical end points including Non-Alcoholic Fatty Liver Disease (NAFLD). This study examined the adult male zebrafish (Danio rerio) transcriptome after exposure to environmental levels of DEHP and 17α-ethinylestradiol (EE2) using both DNA microarray and RNA-sequencing technologies. Our results show that exposure to DEHP is associated with differentially expressed (DE) transcripts associated with the disruption of metabolic processes in the liver, including perturbation of five biological pathways: ‘FOXA2 and FOXA3 transcription factor networks’, ‘Metabolic pathways’, ‘metabolism of amino acids and derivatives’, ‘metabolism of lipids and lipoproteins’, and ‘fatty acid, triacylglycerol, and ketone body metabolism’. DE transcripts unique to DEHP exposure, not observed with EE2 (i.e. non-estrogenic effects) exhibited a signature related to the regulation of transcription and translation, and ruffle assembly and organization. Collectively our results indicate that exposure to low DEHP levels modulates the expression of liver genes related to fatty acid metabolism and the development of NAFLD.

Linking nanomaterial properties to biological outcomes: analytical chemistry challenges in nanotoxicology for the next decade

This article provides our perspective on the analytical challenges in nanotoxicology as the field is entering its third decade.

Use of adverse outcome pathways in chemical toxicity testing: potential advantages and limitations

Amid revolutionary changes in toxicity assessment brought about by increasing regulation of chemicals, adverse outcome pathways (AOPs) have emerged as a useful framework to assess adverse effect of chemicals using molecular level effect, which aid in setting environmental regulation policies. AOPs are biological maps that describe mechanisms linking molecular initiating event to adverse outcomes (AOs) at an individual level. Each AOP consists of a molecular initiating event, key events, and an AO. AOPs use molecular markers to predict endpoints currently used in risk assessment, promote alternatives to animal model-based test methods, and provide scientific explanations for the effects of chemical exposures. Moreover, AOPs enhance certainty in interpreting existing and new information. The application of AOPs in chemical toxicity testing will help shift the existing paradigm of chemical management based on apical endpoints toward active application of in silico and in vitro data.

Hepatic transcriptomic profiles from barramundi, Lates calcarifer, as a means of assessing organism health and identifying stressors in rivers in northern Queensland

Resource managers need to differentiate between sites with and without contaminants and those where contaminants cause impacts. Potentially, transcriptomes could be used to evaluate sites where contaminant-induced effects may occur, to identify causative stressors of effects and potential adverse outcomes. To test this hypothesis, the hepatic transcriptomes in Barramundi, a perciforme teleost fish, (Lates calcarifer) from two reference sites, two agriculturally impacted sites sampled during the dry season, and an impacted site sampled during the wet season were compared. The hepatic transcriptome was profiled using RNA-Seq. Multivariate analysis showed that transcriptomes were clustered based on site and by inference water quality, but not sampling time. The largest differences in transcriptomic profile were between reference sites and a site sampled during high run-off, showing that impacted sites can be identified via RNA-Seq. Transcripts with altered abundance were linked to xenobiotic metabolism, peroxisome proliferation and stress responses, indicating putative stressors with the potential for adverse outcomes in barramundi.

Practical approaches to adverse outcome pathway development and weight-of-evidence evaluation as illustrated by ecotoxicological case studies

Adverse outcome pathways (AOPs) describe toxicant effects as a sequential chain of causally linked events beginning with a molecular perturbation and culminating in an adverse outcome at an individual or population level. Strategies for developing AOPs are still evolving and depend largely on the intended use or motivation for development and data availability. The present review describes 4 ecotoxicological AOP case studies, developed for different purposes. In each situation, creation of the AOP began in a manner determined by the initial motivation for its creation and expanded either to include additional components of the pathway or to address the domains of applicability in terms of chemical initiators, susceptible species, life stages, and so forth. Some general strategies can be gleaned from these case studies, which a developer may find to be useful for supporting an existing AOP or creating a new one. Several web-based tools that can aid in AOP assembly and evaluation of weight of evidence for scientific robustness of AOP components are highlighted. Environ Toxicol Chem 2017;36:1429-1449. © 2017 SETAC.

Causal inference in cumulative risk assessment: The roles of directed acyclic graphs

Cumulative risk assessments (CRAs) address exposures to multiple chemical and nonchemical stressors and often focus on characterization of health risks in vulnerable populations. Evaluating complex exposure-response relationships in CRAs requires the use of formal and rigorous methods for causal inference. Directed acyclic graphs (DAGs) are graphical causal models used to organize and communicate knowledge about the underlying causal structure that generates observable data. Using existing graphical theories for causal inference with DAGs, risk analysts can identify confounders and effect measure modifiers to determine if the available data are both internally valid to obtain unbiased risk estimates and are generalizable to populations of interest. Conditional independencies implied by the structure of a DAG can be used to test assumptions used in a CRA against empirical data in a selected study and can contribute to the evidence evaluations related to specific causal pathways. This can facilitate quantitative use of these data, as well as help identify key research gaps, prioritize data collection activities, and evaluate risk management alternatives. DAGs also enable risk analysts to be explicit about sources of uncertainty and to determine whether a causal effect can be estimated from available data. Using a conceptual model and DAG for a hypothetical community located near a concentrated animal feeding operation (CAFO), we illustrate the advantages of using DAGs for evaluating causality in CRAs. DAGs also can be used in conjunction with weight of evidence (WOE) methodology to improve causal analysis for CRA, which could lead to more effective interventions to reduce population health risks.

A Semi-automated Approach to Create Purposeful Mechanistic Datasets from Heterogeneous Data: Data Mining Towards the in silico Predictions for Oestrogen Receptor Modulation and Teratogenicity

The need to find an alternative to costly animal studies for developmental and reproductive toxicity testing has shifted the focus considerably to the assessment of in vitro developmental toxicology models and the exploitation of pharmacological data for relevant molecular initiating events. We hereby demonstrate how automation can be applied successfully to handle heterogeneous oestrogen receptor data from ChEMBL. Applying expert-derived thresholds to specific bioactivities allowed an activity call to be attributed to each data entry. Human intervention further improved this mechanistic dataset which was mined to develop structure-activity relationship alerts and an expert model covering 45 chemical classes for the prediction of oestrogen receptor modulation. The evaluation of the model using FDA EDKB and Tox21 data was quite encouraging. This model can also provide a teratogenicity prediction along with the additional information it provides relevant to the query compound, all of which will require careful assessment of potential risk by experts.

Novel adverse outcome pathways revealed by chemical genetics in a developing marine fish

Crude oil spills are a worldwide ocean conservation threat. Fish are particularly vulnerable to the oiling of spawning habitats, and crude oil causes severe abnormalities in embryos and larvae. However, the underlying mechanisms for these developmental defects are not well understood. Here, we explore the transcriptional basis for four discrete crude oil injury phenotypes in the early life stages of the commercially important Atlantic haddock (Melanogrammus aeglefinus). These include defects in (1) cardiac form and function, (2) craniofacial development, (3) ionoregulation and fluid balance, and (4) cholesterol synthesis and homeostasis. Our findings suggest a key role for intracellular calcium cycling and excitation-transcription coupling in the dysregulation of heart and jaw morphogenesis. Moreover, the disruption of ionoregulatory pathways sheds new light on buoyancy control in marine fish embryos. Overall, our chemical-genetic approach identifies initiating events for distinct adverse outcome pathways and novel roles for individual genes in fundamental developmental processes.

Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources

The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of HTT testing, thereby reducing the use of animals in toxicity testing and greatly increasing the number of chemicals that can be tested.

Evaluation of the scientific underpinnings for identifying estrogenic chemicals in nonmammalian taxa using mammalian test systems

The US Environmental Protection Agency has responsibility for assessing endocrine activity of more than 10 000 chemicals, a task that cannot reasonably be achieved solely through use of available mammalian and nonmammalian in vivo screening assays. Hence, it has been proposed that chemicals be prioritized for in vivo testing using data from in vitro high-throughput assays for specific endocrine system targets. Recent efforts focused on potential estrogenic chemicals-specifically those that activate estrogen receptor-alpha (ERα)-have broadly demonstrated feasibility of the approach. However, a major uncertainty is whether prioritization based on mammalian (primarily human) high-throughput assays accurately reflects potential chemical-ERα interactions in nonmammalian species. The authors conducted a comprehensive analysis of cross-species comparability of chemical-ERα interactions based on information concerning structural attributes of estrogen receptors, in vitro binding and transactivation data for ERα, and the effects of a range of chemicals on estrogen-signaling pathways in vivo. Overall, this integrated analysis suggests that chemicals with moderate to high estrogenic potency in mammalian systems also should be priority chemicals in nonmammalian vertebrates. However, the degree to which the prioritization approach might be applicable to invertebrates is uncertain because of a lack of knowledge of the biological role(s) of possible ERα orthologs found in phyla such as annelids. Further, comparative analysis of in vitro data for fish and reptiles suggests that mammalian-based assays may not effectively capture ERα interactions for low-affinity chemicals in all vertebrate classes. Environ Toxicol Chem 2016;35:2806-2816. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US Government work and, as such, is in the public domain in the United States of America.

The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions

BACKGROUND

The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions.

OBJECTIVE

Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures.

METHODS

New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling.

DISCUSSION

NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams.

CONCLUSIONS

While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

Adverse Outcome Pathways for Regulatory Applications: Examination of Four Case Studies With Different Degrees of Completeness and Scientific Confidence

Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a specific purpose in a regulatory application: (i) Membrane disruption (Narcosis) leading to respiratory failure (low confidence), (ii) Hepatocellular proliferation leading to cancer (partial pathway, moderate confidence), (iii) Covalent binding to proteins leading to skin sensitization (high confidence), and (iv) Aromatase inhibition leading to reproductive dysfunction in fish (high confidence). Partially complete AOPs with unknown molecular initiating events, such as 'Hepatocellular proliferation leading to cancer', were found to be valuable. We demonstrate that scientific confidence in these pathways can be increased though the use of unconventional information (eg, computational identification of potential initiators). AOPs at all levels of confidence can contribute to specific uses. A significant statistical or quantitative relationship between events and/or the adverse outcome relationships is a common characteristic of AOPs, both incomplete and complete, that have specific regulatory uses. For AOPs to be useful in a regulatory context they must be at least as useful as the tools that regulators currently possess, or the techniques currently employed by regulators.

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the "systems approaches" used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.

Adverse outcome pathways: From research to regulation scientific workshop report

An adverse outcome pathway (AOP) helps to organize existing knowledge on chemical mode of action, starting with a molecular initiating event such as receptor binding, continuing through key events, and ending with an adverse outcome such as reproductive impairment. AOPs can help identify knowledge gaps where more research is needed to understand the underlying mechanisms, aid in chemical hazard characterization, and guide the development of new testing approaches that use fewer or no animals. A September 2014 workshop in Bethesda, Maryland considered how the AOP concept could improve regulatory assessments of chemical toxicity. Scientists from 21 countries, representing industry, academia, regulatory agencies, and special interest groups, attended the workshop, titled Adverse Outcome Pathways: From Research to Regulation. Workshop plenary presentations were followed by breakout sessions that considered regulatory acceptance of AOPs and AOP-based tools, criteria for building confidence in an AOP for regulatory use, and requirements to build quantitative AOPs and AOP networks. Discussions during the closing session emphasized a need to increase transparent and inclusive collaboration, especially with disciplines outside of toxicology. Additionally, to increase impact, working groups should be established to systematically prioritize and develop AOPs. Multiple collaborative projects and follow-up activities resulted from the workshop.

Integrating Publicly Available Data to Generate Computationally Predicted Adverse Outcome Pathways for Fatty Liver

Newin vitrotesting strategies make it possible to design testing batteries for large numbers of environmental chemicals. Full utilization of the results requires knowledge of the underlying biological networks and the adverse outcome pathways (AOPs) that describe the route from early molecular perturbations to an adverse outcome. Curation of a formal AOP is a time-intensive process and a rate-limiting step to designing these test batteries. Here, we describe a method for integrating publicly available data in order to generate computationally predicted AOP (cpAOP) scaffolds, which can be leveraged by domain experts to shorten the time for formal AOP development. A network-based workflow was used to facilitate the integration of multiple data types to generate cpAOPs. Edges between graph entities were identified through direct experimental or literature information, or computationally inferred using frequent itemset mining. Data from the TG-GATEs and ToxCast programs were used to channel large-scale toxicogenomics information into a cpAOP network (cpAOPnet) of over 20 000 relationships describing connections between chemical treatments, phenotypes, and perturbed pathways as measured by differential gene expression and high-throughput screening targets. The resulting fatty liver cpAOPnet is available as a resource to the community. Subnetworks of cpAOPs for a reference chemical (carbon tetrachloride, CCl4) and outcome (fatty liver) were compared with published mechanistic descriptions. In both cases, the computational approaches approximated the manually curated AOPs. The cpAOPnet can be used for accelerating expert-curated AOP development and to identify pathway targets that lack genomic markers or high-throughput screening tests. It can also facilitate identification of key events for designing test batteries and for classification and grouping of chemicals for follow up testing.

Adverse Outcome Pathways-Organizing Toxicological Information to Improve Decision Making

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High-throughput screening commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a framework for connecting high-throughput toxicity testing (HTT) and other results to potential impacts on human and wildlife populations. As a result of international efforts, the AOP development process is now well-defined and efforts are underway to broaden the participation through outreach and training. One key principle is that AOPs represent the chemical-agnostic portions of pathways to increase the generalizability of their application from early key events to overt toxicity. The closely related mode of action framework extends the AOP as needed when evaluating the potential risk of a specific chemical. This in turn enables integrated approaches to testing and assessment (IATA), which incorporate results of assays at various levels of biologic organization such as in silico; HTT; chemical-specific aspects including absorption, distribution, metabolism, and excretion (ADME); and an AOP describing the biologic basis of toxicity. Thus, it is envisaged that provision of limited information regarding both the AOP for critical effects and the ADME for any chemical associated with any adverse outcome would allow for the development of IATA and permit more detailed AOP and ADME research, where higher precision is needed based on the decision context.

Environmentally Relevant Concentrations of the Flame Retardant Tris(1,3-dichloro-2-propyl) Phosphate Inhibit Growth of Female Zebrafish and Decrease Fecundity

Bioconcentrations of tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) in brain, gonad, and liver as well as effects on fecundity and development of zebrafish (Danio rerio) were determined. Zebrafish (1-month old) were exposed to environmentally relevant concentrations of 29 ± 2.1, 600 ± 21, or 6300 ± 130 ng TDCIPP/L. After 120 days of exposure, TDCIPP accumulated in the brain, gonad, and liver with bioconcentration factors of 460, 38, and 87 in females and 26, 55, and 110 in males, respectively. TDCIPP accumulated to a greater extent in brains of females than those of males. Exposure to 6300 ± 130 ng TDCIPP/L resulted in significantly (P < 0.05) fewer eggs being produced, but the histology of the gonad, plasma concentrations of estradiol and 11-ketotestosterone, and expression of genes involved in hypothalamic-pituitary-gonadal-liver axis were not significantly (P > 0.05) different between individuals exposed to TDCIPP and the unexposed control fish. Exposure to TDCIPP resulted in shorter body length, lighter body mass, and lower gonadal-somatic index in females. These effects were possibly due to down-regulation of expression of genes along the growth hormone/insulin-like growth factor (GH/IGF) axis. Correlations between the production of eggs and developmental parameters or expression of genes along the GH/IGF axis further suggested that environmentally relevant concentrations of TDCIPP could have adverse effects on reproduction, possibly due to the inhibition of the growth of females.

A shift in paradigm towards human biology-based systems for cholestatic-liver diseases

Cholestatic-liver diseases (CLDs) arise from diverse causes ranging from genetic factors to drug-induced cholestasis. The so-called diseases of civilization (obesity, diabetes, metabolic disorders, non-alcoholic liver disease, cardiovascular diseases, etc.) are intricately implicated in liver and gall bladder diseases. Although CLDs have been extensively studied, there seem to be important gaps in the understanding of human disease. Despite the fact that many animal models exist and substantial clinical data are available, translation of this knowledge towards therapy has been disappointingly limited. Recent advances in liver cell culture such as in vivo-like 3D cultivation of human primary hepatic cells, human induced pluripotent stem cell-derived hepatocytes; and cutting-edge analytical techniques such as 'omics' technologies and high-content screenings could play a decisive role in deeper mechanistic understanding of CLDs. This Topical Review proposes a roadmap to human biology-based research using omics technologies providing quantitative information on mechanisms in an adverse outcome/disease pathway framework. With modern sensitive tools, a shift in paradigm in human disease research seems timely and even inevitable to overcome species barriers in translation.

Linking mechanistic toxicology to population models in forecasting recovery from chemical stress: A case study from Jackfish Bay, Ontario, Canada

Recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating remediation success. Unfortunately, effectively monitoring population status on a routine basis can be difficult and costly. In the present study, the authors describe a framework that can be applied in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) to link chemically induced alterations in molecular and biochemical endpoints to adverse outcomes in whole organisms and populations. The approach employs a simple density-dependent logistic matrix model linked to adverse outcome pathways (AOPs) for reproductive effects in fish. Application of this framework requires a life table for the organism of interest, a measure of carrying capacity for the population of interest, and estimation of the effect of stressors on vital rates of organisms within the study population. The authors demonstrate the framework using linked AOPs and population models parameterized with long-term monitoring data for white sucker (Catostomus commersoni) collected from a study site at Jackfish Bay, Lake Superior, Canada. Individual responses of fish exposed to pulp mill effluent were used to demonstrate the framework's capability to project alterations in population status, both in terms of ongoing impact and subsequent recovery after stressor mitigation associated with process changes at the mill. The general approach demonstrated at the Jackfish Bay site can be applied to characterize population statuses of other species at a variety of impacted sites and can account for effects of multiple stressors (both chemical and nonchemical) and dynamics within complex landscapes (i.e., meta-populations including emigration and immigration processes).

Increasing Scientific Confidence in Adverse Outcome Pathways: Application of Tailored Bradford-Hill Considerations for Evaluating Weight of Evidence

Systematic consideration of scientific support is a critical element in developing and, ultimately, using adverse outcome pathways (AOPs) for various regulatory applications. Though weight of evidence (WoE) analysis has been proposed as a basis for assessment of the maturity and level of confidence in an AOP, methodologies and tools are still being formalized. The Organization for Economic Co-operation and Development (OECD) Users' Handbook Supplement to the Guidance Document for Developing and Assessing AOPs (OECD 2014a; hereafter referred to as the OECD AOP Handbook) provides tailored Bradford-Hill (BH) considerations for systematic assessment of confidence in a given AOP. These considerations include (1) biological plausibility and (2) empirical support (dose-response, temporality, and incidence) for Key Event Relationships (KERs), and (3) essentiality of key events (KEs). Here, we test the application of these tailored BH considerations and the guidance outlined in the OECD AOP Handbook using a number of case examples to increase experience in more transparently documenting rationales for assigned levels of confidence to KEs and KERs, and to promote consistency in evaluation within and across AOPs. The major lessons learned from experience are documented, and taken together with the case examples, should contribute to better common understanding of the nature and form of documentation required to increase confidence in the application of AOPs for specific uses. Based on the tailored BH considerations and defining questions, a prototype quantitative model for assessing the WoE of an AOP using tools of multi-criteria decision analysis (MCDA) is described. The applicability of the approach is also demonstrated using the case example aromatase inhibition leading to reproductive dysfunction in fish. Following the acquisition of additional experience in the development and assessment of AOPs, further refinement of parameterization of the model through expert elicitation is recommended. Overall, the application of quantitative WoE approaches hold promise to enhance the rigor, transparency and reproducibility for AOP WoE determinations and may play an important role in delineating areas where research would have the greatest impact on improving the overall confidence in the AOP.