A read-across case study on chronic toxicity of branched carboxylic acids (1): Integration of mechanistic evidence from new approach methodologies (NAMs) to explore a common mode of action

Impact of endocrine disruptors on key events of hepatic steatosis in HepG2 cells

Endocrine-disrupting chemicals (EDCs) may contribute to the rising incidence of metabolic dysfunction-associated steatotic liver disease (MASLD). We investigated the potential of 10 environmentally relevant EDCs to affect key events of hepatic steatosis in HepG2 human hepatoblastoma cells. Increased lipid droplet formation, a key marker of steatosis, was induced by PFOA, bisphenol F, DDE, butylparaben, and DEHP, within the non-cytotoxic concentration range of 1 nM-25 μM. Cadmium also induced this effect, but at concentrations impairing cell viability (>1 μM). At non-cytotoxic concentrations, these compounds, along with bisphenol A, dysregulated major genes controlling lipid homeostasis. Cadmium, PFOA, DDE, and DEHP significantly upregulated the DGAT1 gene involved in triglyceride synthesis, while butylparaben increased the expression of the FAT/CD36 gene responsible for fatty acid uptake. Bisphenol A downregulated the CPT1A gene involved in fatty acid oxidation. No significant effects on lipid droplet accumulation or lipid metabolism-related genes were observed for PFOS, bisphenol S, and dibutyl phthalate. Among the tested EDCs, lipid accumulation positively correlated with the expression of SREBF1, DGAT1, and CPT1A. These findings provide additional evidence that EDCs can affect MASLD and highlight the utility of in vitro methods in the screening of EDCs with hazardous steatogenic and metabolism-disrupting properties.

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.

Assessment of pulmonary fibrosis using weighted gene co-expression network analysis

For many industrial chemicals toxicological data is sparse regarding several regulatory endpoints, so there is a high and often unmet demand for NAMs that allow for screening and prioritization of these chemicals. In this proof of concept case study we propose multi-gene biomarkers of compounds' ability to induce lung fibrosis and demonstrate their application in vitro. For deriving these biomarkers we used weighted gene co-expression network analysis to reanalyze a study where the time-dependent pulmonary gene-expression in mice treated with bleomycin had been documented. We identified eight modules of 58 to 273 genes each which were particularly activated during the different phases (inflammatory; acute and late fibrotic) of the developing fibrosis. The modules' relation to lung fibrosis was substantiated by comparison to known markers of lung fibrosis from DisGenet. Finally, we show the modules' application as biomarkers of chemical inducers of lung fibrosis based on an in vitro study of four diketones. Clear differences could be found between the lung fibrosis inducing diketones and other compounds with regard to their tendency to induce dose-dependent increases of module activation as determined using a previously proposed differential activation score and the fraction of differentially expressed genes in the modules. Accordingly, this study highlights the potential use of composite biomarkers mechanistic screening for compound-induced lung fibrosis.

Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study

The evolving landscape of chemical risk assessment is increasingly focused on developing tiered, mechanistically driven approaches that avoid the use of animal experiments. In this context, adverse outcome pathways have gained importance for evaluating various types of chemical-induced toxicity. Using hepatic steatosis as a case study, this review explores the use of diverse computational techniques, such as structure-activity relationship models, quantitative structure-activity relationship models, read-across methods, omics data analysis, and structure-based approaches to fill data gaps within adverse outcome pathway networks. Emphasizing the regulatory acceptance of each technique, we examine how these methodologies can be integrated to provide a comprehensive understanding of chemical toxicity. This review highlights the transformative impact of in silico techniques in toxicology, proposing guidelines for their application in evidence gathering for developing and filling data gaps in adverse outcome pathway networks. These guidelines can be applied to other cases, advancing the field of toxicological risk assessment.

Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure-activity relationship (q-RASAR) with the application of machine learning

This article aims to provide a comprehensive critical, yet readable, review of general interest to the chemistry community on molecular similarity as applied to chemical informatics and predictive modeling with a special focus on read-across (RA) and read-across structure-activity relationships (RASAR). Molecular similarity-based computational tools, such as quantitative structure-activity relationships (QSARs) and RA, are routinely used to fill the data gaps for a wide range of properties including toxicity endpoints for regulatory purposes. This review will explore the background of RA starting from how structural information has been used through to how other similarity contexts such as physicochemical, absorption, distribution, metabolism, and elimination (ADME) properties, and biological aspects are being characterized. More recent developments of RA's integration with QSAR have resulted in the emergence of novel models such as ToxRead, generalized read-across (GenRA), and quantitative RASAR (q-RASAR). Conventional QSAR techniques have been excluded from this review except where necessary for context.

Cyanotoxin cylindrospermopsin disrupts lipid homeostasis and metabolism in a 3D in vitro model of the human liver

Cylindrospermopsin, a potent hepatotoxin produced by harmful cyanobacterial blooms, poses environmental and human health concerns. We used a 3D human liver in vitro model based on spheroids of HepG2 cells, in combination with molecular and biochemical assays, automated imaging, targeted LC-MS-based proteomics, and lipidomics, to explore cylindrospermopsin effects on lipid metabolism and the processes implicated in hepatic steatosis. Cylindrospermopsin (1 μM, 48 h) did not significantly affect cell viability but partially reduced albumin secretion. However, it increased neutral lipid accumulation in HepG2 spheroids while decreasing phospholipid levels. Simultaneously, cylindrospermopsin upregulated genes for lipogenesis regulation (SREBF1) and triacylglycerol synthesis (DGAT1/2) and downregulated genes for fatty acid synthesis (ACLY, ACCA, FASN, SCD1). Fatty acid uptake, oxidation, and lipid efflux genes were not significantly affected. Targeted proteomics revealed increased levels of perilipin 2 (adipophilin), a major hepatocyte lipid droplet-associated protein. Lipid profiling quantified 246 lipid species in the spheroids, with 28 significantly enriched and 15 downregulated by cylindrospermopsin. Upregulated species included neutral lipids, sphingolipids (e.g., ceramides and dihexosylceramides), and some glycerophospholipids (phosphatidylethanolamines, phosphatidylserines), while phosphatidylcholines and phosphatidylinositols were mostly reduced. It suggests that cylindrospermopsin exposures might contribute to developing and progressing towards hepatic steatosis or metabolic dysfunction-associated steatotic liver disease (MASLD).

Uncovering the toxicity mechanisms of a series of carboxylic acids in liver cells through computational and experimental approaches

Hepatotoxicity poses a significant concern in drug design due to the potential liver damage that can be caused by new drugs. Among common manifestations of hepatotoxic damage is lipid accumulation in hepatic tissue, resulting in liver steatosis or phospholipidosis. Carboxylic derivatives are prone to interfere with fatty acid metabolism and cause lipid accumulation in hepatocytes. This study investigates the toxic behaviour of 24 structurally related carboxylic acids in hepatocytes, specifically their ability to cause accumulation of fatty acids and phospholipids. Using high-content screening (HCS) assays, we identified two distinct lipid accumulation patterns. Subsequently, we developed structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) models to determine relevant molecular substructures and descriptors contributing to these adverse effects. Additionally, we calculated physicochemical properties associated with lipid accumulation in hepatocytes and examined their correlation with our chemical structure characteristics. To assess the applicability of our findings to a wide range of chemical compounds, we employed two external datasets to evaluate the distribution of our QSAR descriptors. Our study highlights the significance of subtle molecular structural variations in triggering hepatotoxicity, such as the presence of nitrogen or the specific arrangement of substitutions within the carbon chain. By employing our comprehensive approach, we pinpointed specific molecules and elucidated their mechanisms of toxicity, thus offering valuable insights to guide future toxicology investigations.

Is read-across for chemicals comparable to medical device equivalence and where to use it for conformity assessment?

Novel medical devices must conform to medical device regulation (MDR) for European market entry. Likewise, chemicals must comply with the Registration, Evaluation, Authorization and Restriction of Chemicals (REACh) regulation. Both pose regulatory challenges for manufacturers, but concordantly provide an approach for transferring data from an already registered device or compound to the one undergoing accreditation. This is called equivalence for medical devices and read-across for chemicals. Although read-across is not explicitly prohibited in the process of medical device accreditation, it is usually not performed due to a lack of guidance and acceptance criteria from the authorities. Nonetheless, a scientifically justified read-across of material-based endpoints, as well as toxicological assessment of chemical aspects, such as extractables and leachables, can prevent failure of MDR device equivalence if data is lacking. Further, read-across, if applied correctly can facilitate the standard MDR conformity assessment. The need for read-across within medical device registration should let authorities to reconsider device accreditation and the formulation of respective guidance documents. Acceptance criteria like in the European Chemicals Agency (ECHA) read-across assessment framework (RAAF) are needed. This can reduce the impact of the MDR and help with keeping high European innovation device rate, beneficial for medical device patients.

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.

The sensitivity of the zebrafish embryo coiling assay for the detection of neurotoxicity by compounds with diverse modes of action

In the aim to determine neurotoxicity, new methods are being validated, including tests and test batteries comprising in vitro and in vivo approaches. Alternative test models such as the zebrafish (Danio rerio) embryo have received increasing attention, with minor modifications of the fish embryo toxicity test (FET; OECD TG 236) as a tool to assess behavioral endpoints related to neurotoxicity during early developmental stages. The spontaneous tail movement assay, also known as coiling assay, assesses the development of random movement into complex behavioral patterns and has proven sensitive to acetylcholine esterase inhibitors at sublethal concentrations. The present study explored the sensitivity of the assay to neurotoxicants with other modes of action (MoAs). Here, five compounds with diverse MoAs were tested at sublethal concentrations: acrylamide, carbaryl, hexachlorophene, ibuprofen, and rotenone. While carbaryl, hexachlorophene, and rotenone consistently induced severe behavioral alterations by ~ 30 h post fertilization (hpf), acrylamide and ibuprofen expressed time- and/or concentration-dependent effects. At 37-38 hpf, additional observations revealed behavioral changes during dark phases with a strict concentration-dependency. The study documented the applicability of the coiling assay to MoA-dependent behavioral alterations at sublethal concentrations, underlining its potential as a component of a neurotoxicity test battery.

Development of a reference and proficiency chemical list for human steatosis endpoints in vitro

The most prevalent liver disease in humans is non-alcoholic fatty liver disease, characterised by excessive hepatic fat accumulation, or steatosis. The western diet and a sedentary lifestyle are considered to be major influences, but chemical exposure may also play a role. Suspected environmental chemicals of concern include pesticides, plasticizers, metals, and perfluorinated compounds. Here we present a detailed literature analysis of chemicals that may (or may not) be implicated in lipid accumulation in the liver, to provide a basis for developing and optimizing human steatosis-relevant in vitro test methods. Independently collated and reviewed reference and proficiency chemicals are needed to assist in the test method development where an assay is intended to ultimately be taken forward for OECD Test Guideline development purposes. The selection criteria and considerations required for acceptance of proficiency chemical selection for OECD Test Guideline development. (i.e., structural diversity, range of activity including negatives, relevant chemical sectors, global restrictions, etc.) is described herein. Of 160 chemicals initially screened for inclusion, 36 were prioritized for detailed review. Based on the selection criteria and a weight-of-evidence basis, 18 chemicals (9 steatosis inducers, 9 negatives), including some environmental chemicals of concern, were ranked as high priority chemicals to assist in vitro human steatosis test method optimisation and proficiency testing, and inform potential subsequent test method (pre-)validation.

Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

Article title: Transcriptional profiling efficacy to define biological activity similarity for cosmetic ingredients' safety assessment based on next-generation read-across

The objective of this work was to use transcriptional profiling to assess the biological activity of structurally related chemicals to define their biological similarity and with that, substantiate the validity of a read-across approach usable in risk assessment. Two case studies are presented, one with 4 short alkyl chain parabens: methyl (MP), ethyl (EP), butyl (BP), and propylparaben (PP), as well as their main metabolite, p-hydroxybenzoic acid (pHBA) with the assumption that propylparaben was the target chemical; and a second one with caffeine and its main metabolites theophylline, theobromine and paraxanthine where CA was the target chemical. The comprehensive transcriptional response of MCF7, HepG2, A549 and ICell cardiomyocytes was evaluated (TempO-Seq) after exposure to vehicle-control, each paraben or pHBA, CA or its metabolites, at 3 non-cytotoxic concentrations, for 6 h. Differentially expressed genes (FDR ≥0.05, and fold change ±1.2≥) were identified for each chemical, at each concentration, and used to determine similarities. Each of the chemicals is able to elicit changes in the expression of a number of genes, as compared to controls. Importantly, the transcriptional profile elicited by each of the parabens shares a high degree of similarity across the group. The highest number of genes commonly affected was between butylparaben and PP. The transcriptional profile of the parabens is similar to the one elicited by estrogen receptor agonists, with BP being the closest structural and biological analogue for PP. In the CA case, the transcriptional profile elicited of all four methylxanthines had a high degree of similarity across the cell types, with CA and theophylline being the most active. The most robust response was obtained in the cardiomyocytes with the highest transcriptional profile similarity between CA and TP. The transcriptional profile of the methylxanthines is similar to the one elicited by inhibitors of phosphatidylinositol 3-kinase as well as other kinase inhibitors. Overall, our results support the approach of incorporating transcriptional profiling in well-designed in vitro tests as one robust stream of data to support biological similarity driven read-across procedures and strengthening the traditional structure-based approaches useful in risk assessment.

SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp® simulator

SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara’s Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.

Are Non-animal Systemic Safety Assessments Protective? A Toolbox and Workflow

An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.

Potential of the zebrafish (Danio rerio) embryo test to discriminate between chemicals of similar molecular structure-a study with valproic acid and 14 of its analogues

Valproic acid is a frequently used antiepileptic drug and known pediatric hepatotoxic agent. In search of pharmaceuticals with increased effectiveness and reduced toxicity, analogue chemicals came into focus. So far, toxicity and teratogenicity data of drugs and metabolites have usually been collected from mammalian model systems such as mice and rats. However, in an attempt to reduce mammalian testing while maintaining the reliability of toxicity testing of new industrial chemicals and drugs, alternative test methods are being developed. To this end, the potential of the zebrafish (Danio rerio) embryo to discriminate between valproic acid and 14 analogues was investigated by exposing zebrafish embryos for 120 h post fertilization in the extended version of the fish embryo acute toxicity test (FET; OECD TG 236), and analyzing liver histology to evaluate the correlation of liver effects and the molecular structure of each compound. Although histological evaluation of zebrafish liver did not identify steatosis as the prominent adverse effect typical in human and mice, the structure–activity relationship (SAR) derived was comparable not only to human HepG2 cells, but also to available in vivo mouse and rat data. Thus, there is evidence that zebrafish embryos might serve as a tool to bridge the gap between subcellular, cell-based systems and vertebrate models.