Adverse Outcome Pathways Mechanistically Describing Hepatotoxicity.

Adverse outcome pathways (AOPs) describe toxicological processes from a dynamic perspective by linking a molecular initiating event to a specific adverse outcome via a series of key events and key event relationships. In the field of computational toxicology, AOPs can potentially facilitate the design and development of in silico prediction models for hazard identification. Various AOPs have been introduced for several types of hepatotoxicity, such as steatosis, cholestasis, fibrosis, and liver cancer. This chapter provides an overview of AOPs on hepatotoxicity, including their development, assessment, and applications in toxicology.

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.

A Quantitative Adverse Outcome Pathway for Embryonic Activation of the Aryl Hydrocarbon Receptor of Fishes by Polycyclic Aromatic Hydrocarbons Leading to Decreased Fecundity at Adulthood.

Quantitative adverse outcome pathways (qAOPs) describe the response-response relationships that link the magnitude and/or duration of chemical interaction with a specific molecular target to the probability and/or severity of the resulting apical-level toxicity of regulatory relevance. The present study developed the first qAOP for latent toxicities showing that early life exposure adversely affects health at adulthood. Specifically, a qAOP for embryonic activation of the aryl hydrocarbon receptor 2 (AHR2) of fishes by polycyclic aromatic hydrocarbons (PAHs) leading to decreased fecundity of females at adulthood was developed by building on existing qAOPs for (1) activation of the AHR leading to early life mortality in birds and fishes, and (2) inhibition of cytochrome P450 aromatase activity leading to decreased fecundity in fishes. Using zebrafish (Danio rerio) as a model species and benzo[a]pyrene as a model PAH, three linked quantitative relationships were developed: (1) plasma estrogen in adult females as a function of embryonic exposure, (2) plasma vitellogenin in adult females as a function of plasma estrogen, and (3) fecundity of adult females as a function of plasma vitellogenin. A fourth quantitative relationship was developed for early life mortality as a function of sensitivity to activation of the AHR2 in a standardized in vitro AHR transactivation assay to integrate toxic equivalence calculations that would allow prediction of effects of exposure to untested PAHs. The accuracy of the predictions from the resulting qAOP were evaluated using experimental data from zebrafish exposed as embryos to another PAH, benzo[k]fluoranthene. The qAOP developed in the present study demonstrates the potential of the AOP framework in enabling consideration of latent toxicities in quantitative ecological risk assessments and regulatory decision-making. Environ Toxicol Chem 2024;43:2145-2156. © 2024 SETAC.

A systematic review and BMD modeling approach to develop an AOP for humidifier disinfectant-induced pulmonary fibrosis and cell death.

Dosimetry modeling and point of departure (POD) estimation using in vitro data are essential for mechanism-based hazard identification and risk assessment. This study aimed to develop a putative adverse outcome pathway (AOP) for humidifier disinfectant (HD) substances used in South Korea through a systematic review and benchmark dose (BMD) modeling. We collected in vitro toxicological studies on HD substances, including polyhexamethylene guanidine hydrochloride (PHMG-HCl), PHMG phosphate (PHMG-p), a mixture of 5-chloro-2-methyl-4-isothiazolin-3-one and 2-methyl-4-isothiazolin-3-one (CMIT/MIT), CMIT, and MIT from scientific databases. A total of 193 sets of dose-response data were extracted from 34 articles reporting in vitro experimental results of HD toxicity. The risk of bias (RoB) in each study was assessed following the office of health assessment and translation (OHAT) guideline. The BMD of each HD substance at different toxicity endpoints was estimated using the US Environmental Protection Agency (EPA) BMD software (BMDS). Interspecies- or interorgan differences or most critical effects in the toxicity of the HD substances were analyzed using a 95% lower confidence limit of the BMD (BMDL). We found a critical molecular event and cells susceptible to each HD substance and constructed an AOP of PHMG-p- or CMIT/MIT-induced damage. Notably, PHMG-p induced ATP depletion at the lowest in vitro concentration, endoplasmic reticulum (ER) stress, epithelial-to-mesenchymal transition (EMT), inflammation, leading to fibrosis. CMIT/MIT enhanced mitochondrial reactive oxygen species (ROS) production, oxidative stress, mitochondrial dysfunction, resulting in cell death. Our approach will increase the current understanding of the effects of HD substances on human health and contribute to evidence-based risk assessment of these compounds.

AOP Report: An Upstream Network for Reduced Androgen Signaling Leading to Altered Gene Expression of Androgen Receptor-Responsive Genes in Target Tissues.

Adverse outcome pathways (AOPs) can aid with chemical risk assessment by providing plausible links between chemical activity at the molecular level and effect outcomes in intact organisms. Because AOPs can be used to infer causality between upstream and downstream events in toxicological pathways, the AOP framework can also facilitate increased uptake of alternative methods and new approach methodologies to help inform hazard identification. However, a prevailing challenge is the limited number of fully developed and endorsed AOPs, primarily due to the substantial amount of work required by AOP developers and reviewers. Consequently, a more pragmatic approach to AOP development has been proposed where smaller units of knowledge are developed and reviewed independent of full AOPs. In this context, we have developed an upstream network comprising key events (KEs) and KE relationships related to decreased androgen signaling, converging at a nodal KE that can branch out to numerous adverse outcomes (AOs) relevant to androgen-sensitive toxicological pathways. Androgen signaling represents an extensively studied pathway for endocrine disruption. It is linked to numerous disease outcomes and can be affected by many different endocrine-disrupting chemicals. Still, pathways related to disrupted androgen signaling remain underrepresented in the AOP-wiki, and endorsed AOPs are lacking. Given the pivotal role of androgen signaling in development and function across vertebrate taxa and life stages of both sexes, this upstream AOP network serves as a foundational element for developing numerous AOPs. By connecting the upstream network with various downstream AOs, encompassing different species, it can also facilitate cross-species extrapolations for hazard and risk assessment of chemicals. Environ Toxicol Chem 2024;43:2329-2337. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A transcriptomic biomarker predictive of cell proliferation for use in adverse outcome pathway-informed testing and assessment.

High-throughput transcriptomics (HTTr) is increasingly being used to identify molecular targets of chemicals that can be linked to adverse outcomes. Cell proliferation (CP) is an important key event in chemical carcinogenesis. Here, we describe the construction and characterization of a gene expression biomarker that is predictive of the CP status in human and rodent tissues. The biomarker was constructed from 30 genes known to be increased in expression in prostate cancers relative to surrounding tissues and in cycling human MCF-7 cells after estrogen receptor (ER) agonist exposure. Using a large compendium of gene expression profiles to test utility, the biomarker could identify increases in CP in (i) 308 out of 367 tumor vs. normal surrounding tissue comparisons from 6 human organs, (ii) MCF-7 cells after activation of ER, (iii) after partial hepatectomy in mice and rats, and (iv) the livers of mice and rats after exposure to nongenotoxic hepatocarcinogens. The biomarker identified suppression of CP (i) under conditions of p53 activation by DNA damaging agents in human cells, (ii) in human A549 lung cells exposed to therapeutic anticancer kinase inhibitors (dasatinib, nilotnib), and (iii) in the mouse liver when comparing high levels of CP at birth to the low background levels in the adult. The responses using the biomarker were similar to those observed using conventional markers of CP including PCNA, Ki67, and BrdU labeling. The CP biomarker will be a useful tool for interpretation of HTTr data streams to identify CP status after exposure to chemicals in human cells or in rodent tissues.

Construction of an adverse outcome pathway framework for arsenic-induced lung cancer using a network-based approach.

Environmental pollutants are considered as a cause of tumorigenesis, but approaches to assess their risk of causing tumors remain insufficient. As an alternative approach, the adverse outcome pathway (AOP) framework is used to assess the risk of tumors caused by environmental pollutants. Arsenic is a pollutant associated with lung cancer, but early assessment of lung cancer risk is lacking. Therefore, we applied the AOP framework to arsenic-induced lung cancer. A systematic review revealed increased risks of lung cancer following exposure to a range of arsenic concentrations in drinking water (OR = 1.83, 95 % CI = 1.46-2.30). We obtained, from public databases, genes related to risk of arsenic-induced lung cancer. Then, Cox and LASSO regressions were used to screen target genes from the risk genes. Subsequently, target genes, phenotypes, and pathways were used to construct the computational AOP network, which was determined by Cytoscape to have 156 edges and 45 nodes. Further, target genes, phenotypes, and pathways were used as molecular initiating events and key events to construct the AOP framework depending on upstream and downstream relationships. In the AOP framework, by Weight of Evidence, arsenic exposure increased levels of EGFR, activated the PI3K/AKT pathway, regulated cell proliferation by promoting the G1/S phase transition, and caused generation of lung cancers. External validation was achieved through arsenite-induced, malignant transformed human bronchial epithelial (HBE) cells. Overall, these results, by integration into existing data to construct an AOP framework, provide insights into the assessment of lung cancer risk for arsenic exposure. Special attention needs to be focused on populations with low-dose arsenic exposure.

Methodology for developing data-rich Key Event Relationships for Adverse Outcome Pathways exemplified by linking decreased androgen receptor activity with decreased anogenital distance.

The Adverse Outcome Pathway (AOP) framework has gained widespread acceptance in toxicological disciplines as a tool for aiding chemical hazard assessment. Despite increased activity in AOP development, progress towards a high volume of fully endorsed AOPs has been slow, partly due to the challenging task of constructing complete AOPs according to the AOP Developer's Handbook. To facilitate greater uptake of new knowledge units onto the open-source AOP-wiki platform, a pragmatic approach was recently proposed. This approach involves considering Key Event Relationships (KERs) for individual development through systematic approaches, as they represent essential units of knowledge from which causality can be inferred; from low complexity test data to adverse outcomes in intact organisms. However, more broadly adopted harmonized methodologies for KER development would be desirable. Using the AOP Developer's Handbook as a guide, a KER linking 'decreased androgen receptor (AR) activity' with 'reduced anogenital distance (AGD)' was developed to demonstrate a methodology applicable for future developments of KERs requiring systematic literature retrieval approaches.

Combination of toxicological and epidemiological approaches for estimating the health impact of atmospheric pollutants. A proof of concept for NO2.

BACKGROUND: Regular monitoring of the air pollutant nitrogen dioxide (NO2), an indicator for traffic-related emissions, is a priority in urban environments. The health impacts associated with NO2 exposure are the result of a combination of factors, including concentration, duration of exposure, and interactions with other pollutants. WHO has established air quality guidelines based on epidemiological studies. OBJECTIVE: This study develops a new concept "Health Impact Pathways (HIPs)" using adversity as a probabilistic indicator of health effects. For this purpose, it integrates available toxicological and epidemiological information, using Adverse Outcome Pathways (AOPs), in order to understand chemical-biological interactions and their consequences on health. METHODS: Literature review and meta-analysis of toxicological data supported by expert judgment were performed to establish: a) adversity pathways, b) quantitative criteria for scoring the observed toxicological effects (adversity indicators), c) NO2 exposure - adversity relationship for both long-term (1-36 months) and shortterm (1-7 days). The NO2 daily concentrations from January 2001 to December 2022, were obtained from Madrid city Air Quality network monitoring database. Adversity levels were compared with relative risk levels for all-cause and respiratory mortality estimated using linear equations from WHO 2021 guidelines. RESULTS: Non-linear relations were obtained for all long- and short-term NO2 related adversity indicators; for long-term effects, the best fitting was obtained with a modified Haber's law model with an exponential coefficient for the exposure time of 0.25. Estimations are presented for a set of case studies for Madrid city, covering temporal and spatial variability. A clear improvement trend along the two decades was observed, as well as high inter- and intra-station variability; the adversity indicators provided integrated information on the temporal and spatial evolution of population level risk. DISCUSSION: The proposed HIP conceptual approach offers promising advances for integrating experimental and epidemiological data. The next step is linking the concentration-adversity relationship with population health impacts through probability estimations, the preliminary estimations confirm the need for assessing independently different population groups.

AOP-based framework for predicting the joint action mode of di-(2-ethylhexyl) phthalate and bisphenol A co-exposure on autism spectrum disorder.

Autism spectrum disorder (ASD), also known as autism, is a common, highly hereditary and heterogeneous neurodevelopmental disorder. The global prevalence of ASD among children continues to rise significantly, which is partially attributed to environmental pollution. It has been reported that pre- or post-natal exposure to di-(2-ethylhexyl) phthalate (DEHP) or bisphenol A (BPA), two prevalent environmental endocrine disruptors, increases the risk of ASD in offspring. Yet, the joint action mode linking DEHP and BPA with ASD is incompletely understood. This study aims to unravel the joint action mode of DEHP and BPA co-exposure on the development of ASD. An adverse outcome pathway (AOP) framework was employed to integrate data from multiple public database and construct chemical-gene-phenotype-disease networks (CGPDN) for DEHP- and BPA-related ASD. Topological analysis and comprehensive literature exploration of the CGPDN were performed to build the AOP. By analysis of shared key events (KEs) or phenotypes within the AOP or the CGPDN, we uncovered two AOPs, decreased N-methyl-D-aspartate receptor (NMDAR) and estrogen antagonism that were likely linked to ASD, both with moderate confidence. Our analysis further predicted that the joint action mode of DEHP and BPA related ASD was possibly an additive or synergistic action. Thus, we propose that the co-exposure to BPA and DEHP perhaps additively or synergistically increases the risk of ASD.

Neurotoxicity of fine and ultrafine particulate matter: A comprehensive review using a toxicity pathway-oriented adverse outcome pathway framework.

Fine particulate matter (PM2.5) can cause brain damage and diseases. Of note, ultrafine particles (UFPs) with an aerodynamic diameter less than or equal to 100 nm are a growing concern. Evidence has suggested toxic effects of PM2.5 and UFPs on the brain and links to neurological diseases. However, the underlying mechanism has not yet been fully illustrated due to the variety of the study models, different endpoints, etc. The adverse outcome pathway (AOP) framework is a pathway-based approach that could systematize mechanistic knowledge to assist health risk assessment of pollutants. Here, we constructed AOPs by collecting molecular mechanisms in PM-induced neurotoxicity assessments. We chose particulate matter (PM) as a stressor in the Comparative Toxicogenomics Database (CTD) and identified the critical toxicity pathways based on Ingenuity Pathway Analysis (IPA). We found 65 studies investigating the potential mechanisms linking PM2.5 and UFPs to neurotoxicity, which contained 2, 675 genes in all. IPA analysis showed that neuroinflammation signaling and glucocorticoid receptor signaling were the common toxicity pathways. The upstream regulator analysis (URA) of PM2.5 and UFPs demonstrated that the neuroinflammation signaling was the most initially triggered upstream event. Therefore, neuroinflammation was recognized as the MIE. Strikingly, there is a clear sequence of activation of downstream signaling pathways with UFPs, but not with PM2.5. Moreover, we found that inflammation response and homeostasis imbalance were key cellular events in PM2.5 and emphasized lipid metabolism and mitochondrial dysfunction, and blood-brain barrier (BBB) impairment in UFPs. Previous AOPs, which only focused on phenotypic changes in neurotoxicity upon PM exposure, we for the first time propose AOP framework in which PM2.5 and UFPs may activate pathway cascade reactions, resulting in adverse outcomes associated with neurotoxicity. Our toxicity pathway-based approach not only advances risk assessment for PM-induced neurotoxicity but shines a spotlight on constructing AOP frameworks for new chemicals.

Adverse outcome pathway-based approach to reveal the mechanisms of skin sensitization and long-term aging effects of chlorothalonil.

Chlorothalonil (CHT) is a widely used antifungal agent and is reported to be a sensitizer that can cause allergic contact dermatitis (ACD). ACD initiation is associated with various innate immune cell contributions and is usually accompanied by persistent inflammation, which is a potential contributing factor to skin damage. However, detailed information on the mechanisms by which CHT induces skin sensitization and damage is still insufficient. This study focused on investigating the possible sensitization process and mechanism of CHT and the adverse effects of repeated CHT exposure. CHT activates dendritic cells and promotes the proliferation of lymph cells in the skin sensitization phase, causing severe inflammation. Keratinocytes activate the NLRP3 inflammasome pathway to cause inflammation during CHT treatment, and macrophages also secrete inflammatory cytokines. In addition, CHT-induced inflammation triggered skin wrinkles, decreased epidermal thickness and decreased collagen. Cell experiments also showed that repeated exposure to CHT led to cell proliferation inhibition and senescence, and CHT-induced autophagy dysfunction was not only the reason for inflammation but also for senescence. This study defined the possible process through which CHT is involved in the skin sensitization phase and elucidated the mechanism of CHT-induced inflammation in innate immune responses. We also determined that repeated CHT exposure caused persistent inflammation, ultimately leading to skin aging.

Transcriptome-centric approach to the derivation of adverse outcome pathway networks of vascular dysfunction after long-term low-level exposure of human endothelial cells to dibutyl phthalate.

Dibutyl phthalate (DBP) is an endocrine disruptor that adversely affects reproduction; however, evidence suggests it can also impact other systems, including vascular function. The mechanisms underlying DBP-induced vascular dysfunction, particularly after long-term low-level exposure of endothelial cells to this phthalate, remain largely unknown. To address this gap, we used experimentally derived data on differentially expressed genes (DEGs) obtained after 12 weeks of exposure of human vascular endothelial cells EA.hy926 to the concentrations of DBP to which humans are routinely exposed (10-9 M, 10-8 M, and 10-7 M) and various computational tools and manual data curation to build the first adverse outcome pathway (AOP) network relevant to DBP-induced vascular toxicity. DEGs were used to infer transcription factors (molecular initiating events) and molecular functions and biological processes (key events, KEs) using the Enrichr database. The AOP-helpFinder 2.0, an artificial intelligence-based web tool, was used to link genes and KEs and assign confidence scores to co-occurred terms. We constructed the AOP networks using Cytoscape and then manually arranged KEs to depict the flow of mechanistic information across different levels of network organization. An AOP network was created for each DBP concentration, revealing several distinct high-confidence subnetworks that could be involved in DBP-induced vascular toxicity: the insulin-like growth factor subnetwork for 10-7 M DBP, the CXCL8-dependent chemokine subnetwork for 10-8 M DBP, and the fatty acid subnetwork for 10-9 M DBP. We also developed an AOP network providing a mechanistic insight into the dose-dependent effects of DBP in endothelial cells leading to vascular dysfunction. In summary, we present novel putative AOP networks describing the mechanistic flow of information involved in DBP-induced vascular dysfunction in a long-term low-level exposure scenario.

Determination of OTNE-induced thyroid effects within an adverse outcome pathway (AOP) network.

Octahydro-tetramethyl-naphthalenyl-ethanone (OTNE) is a synthetic fragrance ingredient. OTNE was evaluated in repeated-dose toxicological studies. Target organs via oral and dermal routes were the liver and skin/liver, respectively. Effects were observed on the thyroid and thyroid hormones, suggesting hypothalamic-pituitary-thyroid axis perturbation. We investigated the molecular initiating event(s) (MIEs), key events (KEs), and adverse outcomes of OTNE-induced thyroid perturbation within an adverse outcome pathway (AOP). Data were generated using new approach methodologies (NAMs) on human, mouse, and/or rat receptors exploring MIEs using in vitro receptor ligand-binding assays for androstane receptor variant 3 (CAR), farnesoid X receptor (FXR), liver X receptor alpha (LXRα), peroxisome proliferator-activated receptors alpha, delta, and gamma (PPARα, δ, and γ), pregnane X receptor (PXR), and aryl hydrocarbon receptor (AhR). These data inform an AOP network where CAR, FXR, and PXR activation serve as MIEs with thyroid perturbation occurring as secondary effects. These data represent a robust evaluation using NAMs for mapping OTNE-induced thyroid effects and identifying activation of receptor-ligand binding as MIEs in lieu of additional in vivo experimentation. These data indicate the observed thyroid effects are secondary to liver effects and the thyroid effects, therefore, should not be the basis for assessing potential OTNE-induced human health hazards.

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

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

Analysis of key circRNA events in the AOP framework of TCS acting on zebrafish based on the data-driven.

Triclosan (TCS) is a broad-spectrum antibiotic widely used in various personal care products. Research has found that exposure to TCS can cause toxic effects on organisms including neurotoxicity, cardiotoxicity, disorders of lipid metabolism, and abnormal vascular development, and the corresponding toxic mechanisms are gradually delving into the level of abnormal expression of miRNA regulating gene expression. Although the downstream mechanism of TCS targeting miRNA abnormal expression to induce toxicity is gradually improving, its upstream mechanism is still in a fog. Starting from the abnormal expression data of circRNA in zebrafish larvae induced by TCS, this study conducted a hierarchical analysis of the expression levels of all circRNAs, differential circRNAs, and trend circRNAs, and identified 29 key circRNA events regulating miRNA abnormal expression. In combination with GO and KEGG, the effects of TCS exposure were analyzed from the function and signaling pathway of the corresponding circRNA host gene. Furthermore, based on existing literature evidence about the biological toxicity induced by TCS targeting miRNA as data support, a competing endogenous RNAs (ceRNA) network characterizing the regulatory relationship between circRNA and miRNA was constructed and optimized. Finally, a comprehensive Adverse Outcome Pathway (AOP) framework of multiple levels of events including circRNA, miRNA, mRNA, pathway, and toxicity endpoints was established to systematically elucidate the toxic mechanism of TCS. Moreover, the rationality of the AOP framework was verified from the expression level of miRNA and adverse outcomes such as neurotoxicity, cardiotoxicity, oxidative stress, and inflammatory response by knockdown of circRNA48. This paper not only provides the key circRNA events for exploring the upstream mechanism of miRNA regulating gene expression but also provides an AOP framework for comprehensively demonstrating the toxicity mechanism of TCS on zebrafish, which is a theoretical basis for subsequent hazard assessment and prevention and control of TCS.

Data derived extrapolation factors (DDEFs) for rat to human interspecies extrapolation for the HPPD inhibitor mesotrione.

In the risk assessment of agrochemicals, there has been a historical paucity of using data to refine the default adjustment factors, even though large datasets are available to support this. The current state of the science for addressing uncertainty regarding animal to human extrapolation (AFA) is to develop a "data-derived" adjustment factor (DDEF) to quantify such differences, if data are available. Toxicokinetic (TK) and toxicodynamic (TD) differences between species can be utilized for the DDEF, with human datasets being ideal yet rare. We identified a case for a currently registered herbicide, mesotrione, in which human TK and TD are available. This case study outlines an approach for the development of DDEFs using comparative human and animal data and based on an adverse outcome pathway (AOP) for inhibition of 4-hydroxyphenol pyruvate dioxygenase (HHPD). The calculated DDEF for rat to human extrapolation (AFA) for kinetics (AFAK = 2.5) was multiplied by the AFA for dynamics (AFAD = 0.3) resulting in a composite DDEF of ∼1 (AFA = 0.75). This reflects the AOP and available scientific evidence that humans are less sensitive than rats to the effects of HPPD inhibitors. Further analyses were conducted utilizing in vitro datasets from hepatocytes and liver cytosols and extrapolated to whole animal using in vitro to in vivo extrapolation (IVIVE) to support toxicodynamic extrapolation. The in vitro datasets resulted in the same AFAD as derived for in vivo data (AFAD = 0.3). These analyses demonstrate that a majority of the species differences are related to toxicodynamics. Future work with additional in vitro/in vivo datasets for other HPPD inhibitors and cell types will further support this result. This work demonstrates utilization of all available toxicokinetic and toxicodynamic data to replace default uncertainty factors for agrochemical human health risk assessment.

A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes.

Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network-based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network-based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data-driven approaches for the hazard assessment of nanomaterials and other advanced materials.

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

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