Probabilistic modelling of developmental neurotoxicity based on a simplified adverse outcome pathway network

Recent advances and current challenges of new approach methodologies in developmental and adult neurotoxicity testing

Adult neurotoxicity (ANT) and developmental neurotoxicity (DNT) assessments aim to understand the adverse effects and underlying mechanisms of toxicants on the human nervous system. In recent years, there has been an increasing focus on the so-called new approach methodologies (NAMs). The Organization for Economic Co-operation and Development (OECD), together with European and American regulatory agencies, promote the use of validated alternative test systems, but to date, guidelines for regulatory DNT and ANT assessment rely primarily on classical animal testing. Alternative methods include both non-animal approaches and test systems on non-vertebrates (e.g., nematodes) or non-mammals (e.g., fish). Therefore, this review summarizes the recent advances of NAMs focusing on ANT and DNT and highlights the potential and current critical issues for the full implementation of these methods in the future. The status of the DNT in vitro battery (DNT IVB) is also reviewed as a first step of NAMs for the assessment of neurotoxicity in the regulatory context. Critical issues such as (i) the need for test batteries and method integration (from in silico and in vitro to in vivo alternatives, e.g., zebrafish, C. elegans) requiring interdisciplinarity to manage complexity, (ii) interlaboratory transferability, and (iii) the urgent need for method validation are discussed.

New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project

In the European regulatory context, rodent in vivo studies are the predominant source of neurotoxicity information. Although they form a cornerstone of neurotoxicological assessments, they are costly and the topic of ethical debate. While the public expects chemicals and products to be safe for the developing and mature nervous systems, considerable numbers of chemicals in commerce have not, or only to a limited extent, been assessed for their potential to cause neurotoxicity. As such, there is a societal push toward the replacement of animal models with in vitro or alternative methods. New approach methods (NAMs) can contribute to the regulatory knowledge base, increase chemical safety, and modernize chemical hazard and risk assessment. Provided they reach an acceptable level of regulatory relevance and reliability, NAMs may be considered as replacements for specific in vivo studies. The European Partnership for the Assessment of Risks from Chemicals (PARC) addresses challenges to the development and implementation of NAMs in chemical risk assessment. In collaboration with regulatory agencies, Project 5.2.1e (Neurotoxicity) aims to develop and evaluate NAMs for developmental neurotoxicity (DNT) and adult neurotoxicity (ANT) and to understand the applicability domain of specific NAMs for the detection of endocrine disruption and epigenetic perturbation. To speed up assay time and reduce costs, we identify early indicators of later-onset effects. Ultimately, we will assemble second-generation developmental neurotoxicity and first-generation adult neurotoxicity test batteries, both of which aim to provide regulatory hazard and risk assessors and industry stakeholders with robust, speedy, lower-cost, and informative next-generation hazard and risk assessment tools.

Proof of concept for quantitative adverse outcome pathway modeling of chronic toxicity in repeated exposure

Adverse Outcome Pathway (AOP) is a useful tool to glean mode of action (MOE) of a chemical. However, in order to use it for the purpose of risk assessment, an AOP needs to be quantified using in vitro or in vivo data. Majority of quantitative AOPs developed so far, were for single exposure to progressively higher doses. Limited attempts were made to include time in the modeling. Here as a proof-of concept, we developed a hypothetical AOP, and quantified it using a virtual dataset for six repeated exposures using a Bayesian Network Analysis (BN) framework. The virtual data was generated using realistic assumptions. Effects of each exposure were analyzed separately using a static BN model and analyzed in combination using a dynamic BN (DBN) model. Our work shows that the DBN model can be used to calculate the probability of adverse outcome when other upstream KEs were observed earlier. These probabilities can help in identification of early indicators of AO. In addition, we also developed a data driven AOP pruning technique using a lasso-based subset selection, and show that the causal structure of AOP is itself dynamic and changes over time. This proof-of-concept study revealed the possibility for expanding the applicability of the AOP framework to incorporate biological dynamism in toxicity appearance by repeated insults.

Developmental neurotoxicity (DNT) QSAR combination prediction model establishment and structural characteristics interpretation

With the incidence of neurodevelopmental disorders on the rise, it is imperative to screen and evaluate developmental neurotoxicity (DNT) compounds from a large number of environmental chemicals and understand their mechanisms. In this study, DNT qualitative structure-activity relationship (QSAR) study was carried out for the first time based on DNT data of mammals and structural characterization of DNT compounds was preliminarily illustrated. Five different classification algorithms and two feature selection methods were used to construct prediction models. The best model had good predictive ability on the external test set, but a small application domain (AD). Through combining of three different models, both MCC and AD values were improved. Furthermore, electronical properties, van der Waals volume-related properties and S, Cl or P containing substructure were found to be associated with DNT through modeling descriptors analysis and structure alerts (SAs) identification. This study lays a foundation for further DNT prediction of environmental exposures in human and contributes to the understanding of DNT mechanism.

A review on in silico prediction of the environmental risks posed by pharmaceutical emerging contaminants

Computer-aided (in silico) prediction has shown good potential to support the environmental risk assessment (ERA) of pharmaceutical emerging contaminants (PECs), allowing low-cost, animal-free, high-throughput screening of multiple potential risks posed by a wide variety of pharmaceuticals in the environment based on insufficient toxicity data. This review provided recent insights regarding the application of in silico approaches in prediction for environmental risks of PECs. Based on the review of 20 included articles from 8 countries published since 2018, we found that the researchers' interest and concern in this research topic were sharply aroused since 2021. Recently, in silico approaches have been widely used for the prediction of bioaccumulation and biodegradability, lethal endpoints, developmental toxicity, mutagenicity, other eco-toxicological effects such as ototoxicity and hematological toxicity, and human health hazards of exposure to PECs. Particular attention has been given to the simultaneous discernment of multiple environmental risks and health effects of PECs based on mechanistic data of pharmaceuticals using advanced bioinformatic methods such as transcriptomic analysis and network pharmacology prediction. In silico software platforms and databases used in the included studies were diversified, and there is currently no standardized and accepted in silico model for ERA of PECs. Date suggested that in silico prediction of the environmental risks posed by PECs is still in its infancy. Considerable critical challenges need to be addressed, including consideration of environmental exposure concentration for PECs, interactions among mixtures of PECs and other contaminants coexisting in environments, and development of in silico models specific to ERA of PECs.

Structural Insights into Neonicotinoids and N-Unsubstituted Metabolites on Human nAChRs by Molecular Docking, Dynamics Simulations, and Calcium Imaging

Neonicotinoid pesticides were initially designed in order to achieve species selectivity on insect nicotinic acetylcholine receptors (nAChRs). However, concerns arose when agonistic effects were also detected in human cells expressing nAChRs. In the context of next-generation risk assessments (NGRAs), new approach methods (NAMs) should replace animal testing where appropriate. Herein, we present a combination of in silico and in vitro methodologies that are used to investigate the potentially toxic effects of neonicotinoids and nicotinoid metabolites on human neurons. First, an ensemble docking study was conducted on the nAChR isoforms α7 and α3β4 to assess potential crucial molecular initiating event (MIE) interactions. Representative docking poses were further refined using molecular dynamics (MD) simulations and binding energy calculations using implicit solvent models. Finally, calcium imaging on LUHMES neurons confirmed a key event (KE) downstream of the MIE. This method was also used to confirm the predicted agonistic effect of the metabolite descyano-thiacloprid (DCNT).

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).

Evaluation of mRNA markers in differentiating human SH-SY5Y cells for estimation of developmental neurotoxicity

Current guidelines for developmental neurotoxicity (DNT) evaluation are based on animal models. These have limitations so more relevant, efficient and robust approaches for DNT assessment are needed. We have used the human SH-SY5Y neuroblastoma cell model to evaluate a panel of 93 mRNA markers that are frequent in Neuronal diseases and functional annotations and also differentially expressed during retinoic acid-induced differentiation in the cell model. Rotenone, valproic acid (VPA), acrylamide (ACR) and methylmercury chloride (MeHg) were used as DNT positive compounds. Tolbutamide, D-mannitol and clofibrate were used as DNT negative compounds. To determine concentrations for exposure for gene expression analysis, we developed a pipeline for neurite outgrowth assessment by live-cell imaging. In addition, cell viability was measured by the resazurin assay. Gene expression was analyzed by RT-qPCR after 6 days of exposure during differentiation to concentrations of the DNT positive compounds that affected neurite outgrowth, but with no or minimal effect on cell viability. Methylmercury affected cell viability at lower concentrations than neurite outgrowth, hence the cells were exposed with the highest non-cytotoxic concentration. Rotenone (7.3nM) induced 32 differentially expressed genes (DEGs), ACR (70µM) 8 DEGs, and VPA (75µM) 16 DEGs. No individual genes were significantly dysregulated by all 3 DNT positive compounds (p<0.05), but 9 genes were differentially expressed by 2 of them. Methylmercury (0.8nM) was used to validate the 9 DEGs. The expression of SEMA5A (encoding semaphorin 5A) and CHRNA7 (encoding nicotinic acetylcholine receptor subunit α7) was downregulated by all 4 DNT positive compounds. None of the DNT negative compounds dysregulated any of the 9 DEGs in common for the DNT positive compounds. We suggest that SEMA5A or CHRNA7 should be further evaluated as biomarkers for DNT studies in vitro since they also are involved in neurodevelopmental adverse outcomes in humans.

Impact of endocrine disruptors from mother's diet on immuno-hormonal orchestration of brain development and introduction of the virtual human twin tool

Diet has long been known to modify physiology during development and adulthood. However, due to a growing number of manufactured contaminants and additives over the last few decades, diet has increasingly become a source of exposure to chemicals that has been associated with adverse health risks. Sources of food contaminants include the environment, crops treated with agrochemicals, inappropriate storage (e.g., mycotoxins) and migration of xenobiotics from food packaging and food production equipment. Hence, consumers are exposed to a mixture of xenobiotics, some of which are endocrine disruptors (EDs). The complex interactions between immune function and brain development and their orchestration by steroid hormones are insufficiently understood in human populations, and little is known about the impact on immune-brain interactions by transplacental fetal exposure to EDs via maternal diet. To help to identify the key data gaps, this paper aims to present (a) how transplacental EDs modify immune system and brain development, and (b) how these mechanisms may correlate with diseases such as autism and disturbances of lateral brain development. Attention is given to disturbances of the subplate, a transient structure of crucial significance in brain development. Additionally, we describe cutting edge approaches to investigate the developmental neurotoxicity of EDs, such as the application of artificial intelligence and comprehensive modelling. In the future, highly complex investigations will be performed using virtual brain models constructed using sophisticated multi-physics/multi-scale modelling strategies based on patient and synthetic data, which will enable a greater understanding of healthy or disturbed brain development.

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.

Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach

Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals and the development of safe-by-design compounds. Although toxicogenomics supports mechanistic evaluation of chemical exposures, its implementation into the regulatory framework is hindered by uncertainties in the analysis and interpretation of such data. The use of mechanistic evidence through the adverse outcome pathway (AOP) concept is promoted for the development of new approach methodologies (NAMs) that can reduce animal experimentation. However, to unleash the full potential of AOPs and build confidence into toxicogenomics, robust associations between AOPs and patterns of molecular alteration need to be established. Systematic curation of molecular events to AOPs will create the much-needed link between toxicogenomics and systemic mechanisms depicted by the AOPs. This, in turn, will introduce novel ways of benefitting from the AOPs, including predictive models and targeted assays, while also reducing the need for multiple testing strategies. Hence, a multi-step strategy to annotate AOPs is developed, and the resulting associations are applied to successfully highlight relevant adverse outcomes for chemical exposures with strong in vitro and in vivo convergence, supporting chemical grouping and other data-driven approaches. Finally, a panel of AOP-derived in vitro biomarkers for pulmonary fibrosis (PF) is identified and experimentally validated.

Neuronal differentiation pathways and compound-induced developmental neurotoxicity in the human neural progenitor cell test (hNPT) revealed by RNA-seq

There is an increased awareness that the use of animals for compound-induced developmental neurotoxicity (DNT) testing has limitations. Animal-free innovations, especially the ones based on human stem cell-based models are pivotal in studying DNT since they can mimic processes relevant to human brain development. Here we present the human neural progenitor test (hNPT), a 10-day protocol in which neural progenitor cells differentiate into a neuron-astrocyte co-culture. The study aimed to characterise differentiation over time and to find neurodevelopmental processes sensitive to compound exposure using transcriptomics. 3992 genes regulated in unexposed control cultures (p ≤ 0.001, log2FC ≥ 1) showed Gene Ontology (GO-) term enrichment for neuronal and glial differentiation, neurite extension, synaptogenesis, and synaptic transmission. Exposure to known or suspected DNT compounds (acrylamide, chlorpyrifos, fluoxetine, methyl mercury, or valproic acid) at concentrations resulting in 95% cell viability each regulated unique combinations of GO-terms relating to neural progenitor proliferation, neuronal and glial differentiation, axon development, synaptogenesis, synaptic transmission, and apoptosis. Investigation of the GO-terms 'neuron apoptotic process' and 'axon development' revealed common genes that were responsive across compounds, and might be used as biomarkers for DNT. The GO-term 'synaptic signalling', on the contrary, whilst also responsive to all compounds tested, showed little overlap in gene expression regulation patterns between the conditions. This GO-term may articulate compound-specific effects that may be relevant for revealing differences in mechanism of toxicity. Given its focus on neural progenitor cell to mature multilineage neuronal cell maturation and its detailed molecular readout based on gene expression analysis, hNPT might have added value as a tool for neurodevelopmental toxicity testing in vitro. Further assessment of DNT-specific biomarkers that represent these processes needs further studies.