AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development

Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives

Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into ten priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, we showed the utility of the constructed plastic additives-AOP network by identifying highly relevant AOPs associated with benzo[a]pyrene (B[a]P), bisphenol A (BPA), and bis(2-ethylhexyl) phthalate (DEHP) and thereafter, explored the associated toxicity pathways in humans and aquatic species. Overall, the constructed plastic additives-AOP network will assist regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.

Radiation Adverse Outcome pathways (AOPs): examining priority questions from an international horizon-style exercise

PURPOSE

The Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway (AOP) Development Programme is being explored in the radiation field, as an overarching framework to identify and prioritize research needs that best support strengthening of radiation risk assessment and risk management strategies. To advance the use of AOPs, an international horizon-style exercise (HSE) was initiated through the Radiation/Chemical AOP Joint Topical Group (JTG) formed by the OECD Nuclear Energy Agency (NEA) High-Level Group on Low Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The intent of the HSE was to identify key research questions for consideration in AOP development that would help to reduce uncertainties in estimating the health risks following exposures to low dose and low dose-rate ionizing radiation. The HSE was conducted in several phases involving the solicitation of relevant questions, a collaborative review of open-ended candidate questions and an elimination exercise that led to the selection of 25 highest priority questions for the stated purpose. These questions were further ranked by over 100 respondents through an international survey. This final set of questions was judged to provide insights into how the OECD's AOP approach can be put into practice to meet the needs of hazard and risk assessors, regulators, and researchers. This paper examines the 25 priority questions in the context of hazard/risk assessment framework for ionizing radiation.

CONCLUSION

By addressing the 25 priority questions, it is anticipated that constructed AOPs will have a high level of specificity, making them valuable tools for simplifying and prioritizing complex biological processes for use in developing revised radiation hazard and risk assessment strategies.

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.

Comprehensive mapping of the AOP-Wiki database: identifying biological and disease gaps

Introduction: The Adverse Outcome Pathway (AOP) concept facilitates rapid hazard assessment for human health risks. AOPs are constantly evolving, their number is growing, and they are referenced in the AOP-Wiki database, which is supported by the OECD. Here, we present a study that aims at identifying well-defined biological areas, as well as gaps within the AOP-Wiki for future research needs. It does not intend to provide a systematic and comprehensive summary of the available literature on AOPs but summarizes and maps biological knowledge and diseases represented by the already developed AOPs (with OECD endorsed status or under validation). Methods: Knowledge from the AOP-Wiki database were extracted and prepared for analysis using a multi-step procedure. An automatic mapping of the existing information on AOPs (i.e., genes/proteins and diseases) was performed using bioinformatics tools (i.e., overrepresentation analysis using Gene Ontology and DisGeNET), allowing both the classification of AOPs and the development of AOP networks (AOPN). Results: AOPs related to diseases of the genitourinary system, neoplasms and developmental anomalies are the most frequently investigated on the AOP-Wiki. An evaluation of the three priority cases (i.e., immunotoxicity and non-genotoxic carcinogenesis, endocrine and metabolic disruption, and developmental and adult neurotoxicity) of the EU-funded PARC project (Partnership for the Risk Assessment of Chemicals) are presented. These were used to highlight under- and over-represented adverse outcomes and to identify and prioritize gaps for further research. Discussion: These results contribute to a more comprehensive understanding of the adverse effects associated with the molecular events in AOPs, and aid in refining risk assessment for stressors and mitigation strategies. Moreover, the FAIRness (i.e., data which meets principles of findability, accessibility, interoperability, and reusability (FAIR)) of the AOPs appears to be an important consideration for further development.

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

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

The adverse outcome pathway for breast cancer: a knowledge management framework bridging biomedicine and toxicology

Breast cancer is the most common cancer worldwide, with an estimated 2.3 million new cases diagnosed every year. Effective measures for cancer prevention and cancer therapy require a detailed understanding of the individual key disease mechanisms involved and their interactions at the molecular, cellular, tissue, organ, and organism level. In that regard, the rapid progress of biomedical and toxicological research in recent years now allows the pursuit of new approaches based on non-animal methods that provide greater mechanistic insight than traditional animal models and therefore facilitate the development of Adverse Outcome Pathways (AOPs) for human diseases. We performed a systematic review of the current state of published knowledge with regard to breast cancer to identify relevant key mechanisms for inclusion into breast cancer AOPs, i.e. decreased cell stiffness and decreased cell adhesion, and to concurrently map non-animal methods addressing these key events. We conclude that the broader sharing of expertise and methods between biomedical research and toxicology enabled by the AOP knowledge management framework can help to coordinate global research efforts and accelerate the transition to advanced non-animal methods, which, when combined into powerful method batteries, closely mimic human physiology and disease states without the need for animal testing.

Integrating -omics approaches into population-based studies of endocrine disrupting chemicals: A scoping review

Health effects of endocrine disrupting chemicals (EDCs) are challenging to detect in the general population. Omics technologies become increasingly common to identify early biological changes before the apparition of clinical symptoms, to explore toxic mechanisms and to increase biological plausibility of epidemiological associations. This scoping review systematically summarises the application of omics in epidemiological studies assessing EDCs-associated biological effects to identify potential gaps and priorities for future research. Ninety-eight human studies (2004-2021) were identified through database searches (PubMed, Scopus) and citation chaining and focused on phthalates (34 studies), phenols (19) and PFASs (17), while PAHs (12) and recently-used pesticides (3) were less studied. The sample sizes ranged from 10 to 12,476 (median = 159), involving non-pregnant adults (38), pregnant women (11), children/adolescents (15) or both latter populations studied together (23). Several studies included occupational workers (10) and/or highly exposed groups (11) focusing on PAHs, PFASs and pesticides, while studies on phenols and phthalates were performed in the general population only. Analysed omics layers included metabolic profiles (30, including 14 targeted analyses), miRNA (13), gene expression (11), DNA methylation (8), microbiome (5) and proteins (3). Twenty-one studies implemented targeted multi-assays focusing on clinical routine blood lipid traits, oxidative stress or hormones. Overall, DNA methylation and gene expression associations with EDCs did not overlap across studies, while some EDC-associated metabolite groups, such as carnitines, nucleotides and amino acids in untargeted metabolomic studies, and oxidative stress markers in targeted studies, were consistent across studies. Studies had common limitations such as small sample sizes, cross-sectional designs and single sampling for exposure biomonitoring. In conclusion, there is a growing body of evidence evaluating the early biological responses to exposure to EDCs. This review points to a need for larger longitudinal studies, wider coverage of exposures and biomarkers, replication studies and standardisation of research methods and reporting.

An integrative systems biology strategy to support the development of adverse outcome pathways (AOPs): a case study on radiation-induced microcephaly

Adverse Outcome Pathways (AOPs) are useful tools for assessing the potential risks associated with exposure to various stressors, including chemicals and environmental contaminants. They provide a framework for understanding the causal relationships between different biological events that can lead to adverse outcomes (AO). However, developing an AOP is a challenging task, particularly in identifying the molecular initiating events (MIEs) and key events (KEs) that constitute it. Here, we propose a systems biology strategy that can assist in the development of AOPs by screening publicly available databases, literature with the text mining tool AOP-helpFinder, and pathway/network analyses. This approach is straightforward to use, requiring only the name of the stressor and adverse outcome to be studied. From this, it quickly identifies potential KEs and literature providing mechanistic information on the links between the KEs. The proposed approach was applied to the recently developed AOP 441 on radiation-induced microcephaly, resulting in the confirmation of the KEs that were already present and identification of new relevant KEs, thereby validating the strategy. In conclusion, our systems biology approach represents a valuable tool to simplify the development and enrichment of Adverse Outcome Pathways (AOPs), thus supporting alternative methods in toxicology.

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/.

Investigating fatty liver disease-associated adverse outcome pathways of perfluorooctane sulfonate using a systems toxicology approach

Adverse outcome pathway (AOP) frameworks help elucidate toxic mechanisms and support chemical regulation. AOPs link a molecular initiating event (MIE), key events (KEs), and an adverse outcome by key event relationships (KERs), which assess the biological plausibility, essentiality, and empirical evidence involved. Perfluorooctane sulfonate (PFOS), a hazardous poly-fluoroalkyl substance, demonstrates hepatotoxicity in rodents. PFOS may induce fatty liver disease (FLD) in humans; however, the underlying mechanism remains unclear. In this study, we evaluated the toxic mechanisms of PFOS-associated FLD by developing an AOP using publicly available data. We identified MIE and KEs by performing GO enrichment analysis on PFOS- and FLD-associated target genes collected from public databases. The MIEs and KEs were then prioritized by PFOS-gene-phenotype-FLD networks, AOP-helpFinder, and KEGG pathway analyses. Following a comprehensive literature review, an AOP was then developed. Finally, six KEs for the AOP of FLD were identified. This AOP indicated that toxicological processes initiated by SIRT1 inhibition led to SREBP-1c activation, de novo fatty acid synthesis, and fatty acid and triglyceride accumulation, culminating in liver steatosis. Our study provides insights into the toxic mechanism of PFOS-induced FLD and suggests approaches to assessing the risk of toxic chemicals.

Development of a data-driven approach to Adverse Outcome Pathway network generation: a case study on the EATS-modalities

Adverse Outcome Pathways (AOPs) summarize mechanistic understanding of toxicological effects and have, for example, been highlighted as a promising tool to integrate data from novel in vitro and in silico methods into chemical risk assessments. Networks based on AOPs are considered the functional implementation of AOPs, as they are more representative of complex biology. At the same time, there are currently no harmonized approaches to generate AOP networks (AOPNs). Systematic strategies to identify relevant AOPs, and methods to extract and visualize data from the AOP-Wiki, are needed. The aim of this work was to develop a structured search strategy to identify relevant AOPs in the AOP-Wiki, and an automated data-driven workflow to generate AOPNs. The approach was applied on a case study to generate an AOPN focused on the Estrogen, Androgen, Thyroid, and Steroidogenesis (EATS) modalities. A search strategy was developed a priori with search terms based on effect parameters in the ECHA/EFSA Guidance Document on Identification of Endocrine Disruptors. Furthermore, manual curation of the data was performed by screening the contents of each pathway in the AOP-Wiki, excluding irrelevant AOPs. Data were downloaded from the Wiki, and a computational workflow was utilized to automatically process, filter, and format the data for visualization. This study presents an approach to structured searches of AOPs in the AOP-Wiki coupled to an automated data-driven workflow for generating AOPNs. In addition, the case study presented here provides a map of the contents of the AOP-Wiki related to the EATS-modalities, and a basis for further research, for example, on integrating mechanistic data from novel methods and exploring mechanism-based approaches to identify endocrine disruptors (EDs). The computational approach is freely available as an R-script, and currently allows for the (re)-generation and filtering of new AOP networks based on data from the AOP-Wiki and a list of relevant AOPs used for filtering.

Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells

Sulforaphane (SFN) is a naturally occurring molecule present in plants from Brassica family. It becomes bioactive after hydrolytic reaction mediated by myrosinase or human gastrointestinal microbiota. Sulforaphane gained scientific popularity due to its antioxidant and anti-cancer properties. However, its toxicity profile and potential to cause adverse effects remain largely unidentified. Thus, this study aimed to generate SFN-triggered adverse outcome pathway (AOP) by looking at the relationship between SFN-chemical structure and its toxicity, as well as SFN-gene interactions. Quantitative structure-activity relationship (QSAR) analysis identified 2 toxophores (Derek Nexus software) that have the potential to cause chromosomal damage and skin sensitization in mammals or mutagenicity in bacteria. Data extracted from Comparative Toxicogenomics Database (CTD) linked SFN with previously proposed outcomes via gene interactions. The total of 11 and 146 genes connected SFN with chromosomal damage and skin diseases, respectively. However, network analysis (NetworkAnalyst tool) revealed that these genes function in wider networks containing 490 and 1986 nodes, respectively. The over-representation analysis (ExpressAnalyst tool) pointed out crucial biological pathways regulated by SFN-interfering genes. These pathways are uploaded to AOP-helpFinder tool which found the 2321 connections between 19 enriched pathways and SFN which were further considered as key events. Two major, interconnected AOPs were generated: first starting from disruption of biological pathways involved in cell cycle and cell proliferation leading to increased apoptosis, and the second one connecting activated immune system signaling pathways to inflammation and apoptosis. In both cases, chromosomal damage and/or skin diseases such as dermatitis or psoriasis appear as adverse outcomes.

Partitioning of Persistent Organic Pollutants between Adipose Tissue and Serum in Human Studies

Blood is the most widely used matrix for biomonitoring of persistent organic pollutants (POPs). It is assumed that POPs are homogenously distributed within body lipids at steady state; however, the variability underlying the partitioning of POPs between fat compartments is poorly understood. Hence, the objective of this study was to review the state of the science about the relationships of POPs between adipose tissue and serum in humans. We conducted a narrative literature review of human observational studies reporting concentrations of POPs in paired samples of adipose tissue with other lipid-based compartments (e.g., serum lipids). The searches were conducted in SCOPUS and PUBMED. A meta-regression was performed to identify factors responsible for variability. All included studies reported high variability in the partition coefficients of POPs, mainly between adipose tissue and serum. The number of halogen atoms was the physicochemical variable most strongly and positively associated with the partition ratios, whereas body mass index was the main biological factor positively and significantly associated. To conclude, although this study provides a better understanding of partitioning of POPs to refine physiologically based pharmacokinetic and epidemiological models, further research is still needed to determine other key factors involved in the partitioning of POPs.

Reduced Birth Weight and Exposure to Per- and Polyfluoroalkyl Substances: A Review of Possible Underlying Mechanisms Using the AOP-HelpFinder

Prenatal exposure to per- and polyfluorinated substances (PFAS) may impair fetal growth. Our knowledge of the underlying mechanisms is incomplete. We used the Adverse Outcome Pathway (AOP)-helpFinder tool to search PubMed for studies published until March 2021 that examined PFAS exposure in relation to birth weight, oxidative stress, hormones/hormone receptors, or growth signaling pathways. Of these 1880 articles, 106 experimental studies remained after abstract screening. One clear finding is that PFAS are associated with oxidative stress in in vivo animal studies and in vitro studies. It appears that PFAS-induced reactive-oxygen species (ROS) generation triggers increased peroxisome proliferator-activated receptor (PPAR)γ expression and activation of growth signaling pathways, leading to hyperdifferentiation of pre-adipocytes. Fewer proliferating pre-adipocytes result in lower adipose tissue weight and in this way may reduce birth weight. PFAS may also impair fetal growth through endocrine effects. Estrogenic effects have been noted in in vivo and in vitro studies. Overall, data suggest thyroid-damaging effects of PFAS affecting thyroid hormones, thyroid hormone gene expression, and histology that are associated in animal studies with decreased body and organ weight. The effects of PFAS on the complex relationships between oxidative stress, endocrine system function, adipogenesis, and fetal growth should be further explored.

Identifying the landscape of developmental toxicity new approach methodologies

BACKGROUND

The dynamics and complexities of in utero fetal development create significant challenges in transitioning from lab animal-centric developmental toxicity testing methods to assessment strategies based on new approach methodologies (NAMs). Nevertheless, considerable progress is being made, stimulated by increased research investments and scientific advances, such as induced pluripotent stem cell-derived models. To help identify developmental toxicity NAMs for toxicity screening and potential funding through the American Chemistry Council's Long-Range Research Initiative, a systematic literature review was conducted to better understand the current landscape of developmental toxicity NAMs.

METHODS

Scoping review tools were used to systematically survey the literature (2010-2021; ~18,000 references identified), results and metadata were then extracted, and a user-friendly interactive dashboard was created.

RESULTS

The data visualization dashboard, developed using Tableau® software, is provided as a free, open-access web tool. This dashboard enables straightforward interactive queries and visualizations to identify trends and to distinguish and understand areas or NAMs where research has been most, or least focused.

CONCLUSIONS

Herein, we describe the approach and methods used, summarize the benefits and challenges of applying the systematic-review techniques, and highlight the types of questions and answers for which the dashboard can be used to explore the many different facets of developmental toxicity NAMs.

Adverse Outcome Pathways Associated with the Ingestion of Titanium Dioxide Nanoparticles-A Systematic Review

Titanium dioxide nanoparticles (TiO₂-NPs) are widely used, and humans are exposed through food (E171), cosmetics (e.g., toothpaste), and pharmaceuticals. The oral and gastrointestinal (GIT) tract are the first contact sites, but it may be systemically distributed. However, a robust adverse outcome pathway (AOP) has not been developed upon GIT exposure to TiO₂-NPs. The aim of this review was to provide an integrative analysis of the published data on cellular and molecular mechanisms triggered after the ingestion of TiO₂-NPs, proposing plausible AOPs that may drive policy decisions. A systematic review according to Prisma Methodology was performed in three databases of peer-reviewed literature: Pubmed, Scopus, and Web of Science. A total of 787 records were identified, screened in title/abstract, being 185 used for data extraction. The main endpoints identified were oxidative stress, cytotoxicity/apoptosis/cell death, inflammation, cellular and systemic uptake, genotoxicity, and carcinogenicity. From the results, AOPs were proposed where colorectal cancer, liver injury, reproductive toxicity, cardiac and kidney damage, as well as hematological effects stand out as possible adverse outcomes. The recent transgenerational studies also point to concerns with regard to population effects. Overall, the findings further support a limitation of the use of TiO₂-NPs in food, announced by the European Food Safety Authority (EFSA).

Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers

Monitoring drug safety is a central concern throughout the drug life cycle. Information about toxicity and adverse events is generated at every stage of this life cycle, and stakeholders have a strong interest in applying text mining and artificial intelligence (AI) methods to manage the ever-increasing volume of this information. Recognizing the importance of these applications and the role of challenge evaluations to drive progress in text mining, the organizers of BioCreative VII (Critical Assessment of Information Extraction in Biology) convened a panel of experts to explore ‘Challenges in Mining Drug Adverse Reactions’. This article is an outgrowth of the panel; each panelist has highlighted specific text mining application(s), based on their research and their experiences in organizing text mining challenge evaluations. While these highlighted applications only sample the complexity of this problem space, they reveal both opportunities and challenges for text mining to aid in the complex process of drug discovery, testing, marketing and post-market surveillance. Stakeholders are eager to embrace natural language processing and AI tools to help in this process, provided that these tools can be demonstrated to add value to stakeholder workflows. This creates an opportunity for the BioCreative community to work in partnership with regulatory agencies, pharma and the text mining community to identify next steps for future challenge evaluations.

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.

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

BACKGROUND

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

CONCLUSION

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

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

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

Characterization of Potential Adverse Outcome Pathways Related to Metabolic Outcomes and Exposure to Per- and Polyfluoroalkyl Substances Using Artificial Intelligence

Human exposure to per- and polyfluoroalkyl substances (PFAS) has been associated with numerous adverse health effects, depending on various factors such as the conditions of exposure (dose/concentration, duration, route of exposure, etc.) and characteristics associated with the exposed target (e.g., age, sex, ethnicity, health status, and genetic predisposition). The biological mechanisms by which PFAS might affect systems are largely unknown. To support the risk assessment process, AOP-helpFinder, a new artificial intelligence tool, was used to rapidly and systematically explore all available published information in the PubMed database. The aim was to identify existing associations between PFAS and metabolic health outcomes that may be relevant to support building adverse outcome pathways (AOPs). The collected information was manually organized to investigate linkages between PFAS exposures and metabolic health outcomes, including dyslipidemia, hypertension, insulin resistance, and obesity. Links between PFAS exposure and events from the existing metabolic-related AOPs were also retrieved. In conclusion, by analyzing dispersed information from the literature, we could identify some associations between PFAS exposure and components of existing AOPs. Additionally, we identified some linkages between PFAS exposure and metabolic outcomes for which only sparse information is available or which are not yet present in the AOP-wiki database that could be addressed in future research.

Natural language processing in toxicology: Delineating adverse outcome pathways and guiding the application of new approach methodologies

Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiating event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and information, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advancement of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.

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.

Adverse outcome pathway from activation of the AhR to breast cancer-related death

Adverse outcome pathways (AOPs) are formalized and structured linear concepts that connect one molecular initiating event (MIE) to an adverse outcome (AO) via different key events (KE) through key event relationships (KER). They are mainly used in eco-toxicology toxicology, and regulatory health issues. AOPs must respond to specific guidelines from the Organization for Economic Co-operation and Development (OECD) to weight the evidence between each KE. Breast cancer is the deadliest cancer in women with a poor prognosis in case of metastatic breast cancer. The role of the environments in the formation of metastasis has been suggested. We hypothesized that activation of the AhR (MIE), a xenobiotic receptor, could lead to breast cancer related death (AO), through different KEs, constituting a new AOP. An artificial intelligence tool (AOP-helpfinder), which screens the available literature, was used to collect all existing scientific abstracts to build a novel AOP, using a list of key words. Four hundred and seven abstracts were found containing at least a word from our MIE list and either one word from our AO or KE list. A manual curation retained 113 pertinent articles, which were also screened using PubTator. From these analyses, an AOP was created linking the activation of the AhR to breast cancer related death through decreased apoptosis, inflammation, endothelial cell migration, angiogenesis, and invasion. These KEs promote an increased tumor growth, angiogenesis and migration which leads to breast cancer metastasis and breast cancer related death. The evidence of the proposed AOP was weighted using the tailored Bradford Hill criteria and the OECD guidelines. The confidence in our AOP was considered strong. An in vitro validation must be carried out, but our review proposes a strong relationship between AhR activation and breast cancer-related death with an innovative use of an artificial intelligence literature search.

A Case Study on Integrating a New Key Event Into an Existing Adverse Outcome Pathway on Oxidative DNA Damage: Challenges and Approaches in a Data-Rich Area

Adverse outcome pathways (AOPs) synthesize toxicological information to convey and weigh evidence in an accessible format. AOPs are constructed in modules that include key events (KEs) and key event relationships (KERs). This modular structure facilitates AOP expansion and network development. AOP development requires finding relevant information to evaluate the weight of evidence supporting each KER. To do this, the use of transparent/reproducible search methods, such as systematic review (SR), have been proposed. Applying SR to AOP development in a data-rich area is difficult as SR requires screening each article returned from a search. Here we describe a case study to integrate a single new KE into an existing AOP. We explored the use of SR concepts and software to conduct a transparent and documented literature search to identify empirical data supporting the incorporation of a new KE, increase in cellular reactive oxygen species (ROS), upstream of an existing AOP: “Oxidative DNA Damage Leading to Chromosomal Aberrations and Mutations”. Connecting this KE to the AOP is supported by the development of five new KERs, the most important being the first adjacent KER (increase in ROS leading to oxidative DNA damage). We initially searched for evidence of all five KERs and screened 100 papers to develop a preliminary evidence map. After removing papers not containing relevant data based on our Population, Exposure, Comparator and Outcome statement, 39 articles supported one or more KERs; these primarily addressed temporal or dose concordance of the non-adjacent KERs with limited evidence supporting the first adjacent KER. We thus conducted a second focused set of searches using search terms for specific methodologies to measure these first two KEs. After screening, 12 articles were identified that contained quantitative evidence supporting the first adjacent KER. Given that integrating a new KE into an existing AOP requires the development of multiple KERs, this approach of building a preliminary evidence map, focusing evidence gathering on the first adjacent KER, and applying reproducible search strategies using specific methodologies for the first adjacent KER, enabled us to prioritize studies to support expansion of this data-rich AOP.

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.

The Exposome and Toxicology: A Win-Win Collaboration

The development of the exposome concept has been one of the hallmarks of environmental and health research for the last decade. The exposome encompasses the life course environmental exposures including lifestyle factors from the prenatal period onwards. It has inspired many research programs and is expected to influence environmental and health research, practices, and policies. Yet, the links bridging toxicology and the exposome concept have not been well developed. In this review, we describe how the exposome framework can interface with and influence the field of toxicology, as well as how the field of toxicology can help advance the exposome field by providing the needed mechanistic understanding of the exposome impacts on health. Indeed, exposome-informed toxicology is expected to emphasize several orientations including (1) developing approaches integrating multiple stressors, in particular chemical mixtures, as well as the interaction of chemicals with other stressors, (2) using mechanistic frameworks such as the adverse outcome pathways to link the different stressors with toxicity outcomes, (3) characterizing the mechanistic basis of long-term effects by distinguishing different patterns of exposures and further exploring the environment-DNA interface through genetic and epigenetic studies, and (4) improving the links between environmental and human health, in particular through a stronger connection between alterations in our ecosystems and human toxicology. The exposome concept provides the linkage between the complex environment and contemporary mechanistic toxicology. What toxicology can bring to exposome characterization is a needed framework for mechanistic understanding and regulatory outcomes in risk assessment.