From Causal Networks to Adverse Outcome Pathways: A Developmental Neurotoxicity Case Study.

Roman A. Li,Vid Modic,Colette vom Berg,Anze Zupanic,Živa Ramšak

doi:10.3389/ftox.2022.815754

Abstract

The last decade has seen the adverse outcome pathways (AOP) framework become one of the most powerful tools in chemical risk assessment, but the development of new AOPs remains a slow and manually intensive process. Here, we present a faster approach for AOP generation, based on manually curated causal toxicological networks. As a case study, we took a recently published zebrafish developmental neurotoxicity network, which contains causally connected molecular events leading to neuropathologies, and developed two new adverse outcome pathways: Inhibition of Fyna (Src family tyrosine kinase A) leading to increased mortality via decreased eye size (AOP 399 on AOP-Wiki) and GSK3beta (Glycogen synthase kinase 3 beta) inactivation leading to increased mortality via defects in developing inner ear (AOP 410). The approach consists of an automatic separation of the toxicological network into candidate AOPs, filtering the AOPs according to available evidence and length as well as manual development of new AOPs and weight-of-evidence evaluation. The semiautomatic approach described here provides a new opportunity for fast and straightforward AOP development based on large network resources.

Highlights

A decade ago, adverse outcome pathways (AOPs) (Ankley et al, 2010) have been put forward as a tool for organizing toxicological knowledge across different levels of biological organization, from the initial interaction of chemicals with the biological system (MIE = molecular initiating event) (Allen et al, 2014) to the individual and population level effects relevant for environmental risk assessment (AO = adverse outcome)
In this study we evaluated the suitability of causal toxicological networks (CTNs) for AOP development
We have developed a semi-automatic pipeline and scripts that take a CTN in Biological Expression Language (BEL) format, remove unneeded node and connection annotations and add new functional ones, reduce the network to a size similar to an AOP network (Pollesch et al, 2019)

Summary

Introduction

Through identification of knowledge gaps, AOPs inform future research and the development of novel biological assays that allow more specific in vitro chemical testing and reduction of animal testing (Groh et al, 2015). The AOPs in the AOP-wiki have been useful resources for quite diverse toxicological studies, e.g., to find chemicals likely to activate the AOPs (Jeong et al, 2019), to evaluate the hazard associated with specific chemicals and chemical groups (Carvaillo et al, 2019; Negi et al, 2021), to develop assays for in vitro assessment of mixture toxicity (Pistollato et al, 2020), to develop a new tiered testing approach for thyroid hormone disruptors (Knapen et al, 2020), to find the mechanisms of nanomaterial toxicity (Murugadoss et al, 2021) and to develop quantitative AOPs, mathematical models that can be used directly in chemical risk assessment (Margiotta-Casaluci et al, 2016; Doering et al, 2018; Perkins et al, 2019; Burgoon et al, 2020; Lillicrap et al, 2020)

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Results

Conclusion