Using adverse outcome pathways to contextualise (Q)SAR predictions for reproductive toxicity – A case study with aromatase inhibition

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.

Building an adverse outcome pathway network for estrogen-, androgen- and steroidogenesis-mediated reproductive toxicity

Introduction: Adverse Outcome Pathways (AOPs) can support both testing and assessment of endocrine disruptors (EDs). There is, however, a need for further development of the AOP framework to improve its applicability in a regulatory context. Here we have inventoried the AOP-wiki to identify all existing AOPs related to mammalian reproductive toxicity arising from disruption to the estrogen, androgen, and steroidogenesis modalities. Core key events (KEs) shared between relevant AOPs were also identified to aid in further AOP network (AOPN) development. Methods: A systematic approach using two different methods was applied to screen and search the entire AOP-wiki library. An AOPN was visualized using Cytoscape. Manual refinement was performed to remove AOPS devoid of any KEs and/or KERs. Results: Fifty-eight AOPs relevant for mammalian reproductive toxicity were originally identified, with 42 AOPs included in the final AOPN. Several of the KEs and KE relationships (KERs) described similar events and were thus merged to optimize AOPN construction. Sixteen sub-networks related to effects on hormone levels or hormone activity, cancer outcomes, male and female reproductive systems, and overall effects on fertility and reproduction were identified within the AOPN. Twenty-six KEs and 11 KERs were identified as core blocks of knowledge in the AOPN, of which 19 core KEs are already included as parameters in current OECD and US EPA test guidelines. Discussion: The AOPN highlights knowledge gaps that can be targeted for further development of a more complete AOPN that can support the identification and assessment of EDs.

Spatially Resolved Co-Imaging of Polyhalogenated Xenobiotics and Endogenous Metabolites Reveals Xenobiotic-Induced Metabolic Alterations

A large group of polyhalogenated compounds has been added to the list of persistent organic pollutants in a global convention endorsed by over 100 nations. Once entering the biotas, these pollutants are transported to focal sites of toxicological action and affected endogenous metabolites, which exhibited distinct tissue or organ distribution patterns. However, no study is available to achieve simultaneous mapping of the spatial distributions of xenobiotics and endogenous metabolites for clarifying the molecular mechanism of toxicities. Herein, we present a sensitive mass spectrometry imaging method─tetraphenyl phosphonium chloride-enhanced ionization coupled with air flow-assisted ionization-Orbitrap mass spectrometry─which simultaneously determined the spatial distributions of polyhalogenated xenobiotics and endogenous metabolites. The spatially resolved toxicokinetics and toxicodynamics of typical polyhalogenated compounds (chlorinated paraffins (CPs) and hexabromocyclododecane (HBCD)) were assessed in zebrafish. Co-imaging of polyhalogenated compounds and metabolites visualized the major accumulation organs and maternal transfer of HBCD and CPs, and it clarified the reproductive toxicity of HBCD. CPs were accumulated in the liver, heart, and brain and decreased the concentrations of polyamine/inosine-related metabolites and lipid molecules in these organs. HBCD accumulated in the ovary and was effectively transferred to eggs, and it also disrupted normal follicular development and impaired the production of mature eggs from the ovary by inhibiting expressions of the luteinizing hormone/choriogonadotropin receptor gene. The toxic effects of metabolic disruptions were validated by organ-specific histopathological examinations. These results highlight the necessity to assess the distributions and bioeffects of pollutants in a spatial perspective.

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

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

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.

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

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

Risk assessment in the 21st century: where are we heading?

Reliance on animal tests for chemical safety assessment is increasingly being challenged, not only because of ethical reasons, but also because they procrastinate regulatory decisions and because of concerns over the transferability of results to humans. New approach methodologies (NAMs) need to be fit for purpose and new thinking is required to reconsider chemical legislation, validation of NAMs and opportunities to move away from animal tests. This article summarizes the presentations from a symposium at the 2022 Annual Congress of the British Toxicology Society on the topic of the future of chemical risk assessment in the 21st century. The symposium included three case-studies where NAMs have been used in safety assessments. The first case illustrated how read-across augmented with some in vitro tests could be used reliably to perform the risk assessment of analogues lacking data. The second case showed how specific bioactivity assays could identify an NAM point of departure (PoD) and how this could be translated through physiologically based kinetic modelling in an in vivo PoD for the risk assessment. The third case showed how adverse-outcome pathway (AOP) information, including molecular-initiating event and key events with their underlying data, established for certain chemicals could be used to produce an in silico model that is able to associate chemical features of an unstudied substance with specific AOPs or AOP networks. The manuscript presents the discussions that took place regarding the limitations and benefits of these new approaches, and what are the barriers and the opportunities for their increased use in regulatory decision making.

Representing and describing nanomaterials in predictive nanoinformatics

Engineered nanomaterials (ENMs) enable new and enhanced products and devices in which matter can be controlled at a near-atomic scale (in the range of 1 to 100 nm). However, the unique nanoscale properties that make ENMs attractive may result in as yet poorly known risks to human health and the environment. Thus, new ENMs should be designed in line with the idea of safe-and-sustainable-by-design (SSbD). The biological activity of ENMs is closely related to their physicochemical characteristics, changes in these characteristics may therefore cause changes in the ENMs activity. In this sense, a set of physicochemical characteristics (for example, chemical composition, crystal structure, size, shape, surface structure) creates a unique 'representation' of a given ENM. The usability of these characteristics or nanomaterial descriptors (nanodescriptors) in nanoinformatics methods such as quantitative structure-activity/property relationship (QSAR/QSPR) models, provides exciting opportunities to optimize ENMs at the design stage by improving their functionality and minimizing unforeseen health/environmental hazards. A computational screening of possible versions of novel ENMs would return optimal nanostructures and manage ('design out') hazardous features at the earliest possible manufacturing step. Safe adoption of ENMs on a vast scale will depend on the successful integration of the entire bulk of nanodescriptors extracted experimentally with data from theoretical and computational models. This Review discusses directions for developing appropriate nanomaterial representations and related nanodescriptors to enhance the reliability of computational modelling utilized in designing safer and more sustainable ENMs.