Development and analysis of an adverse outcome pathway network for human neurotoxicity

Nicoleta Spinu,Andrew P Worth,Judith C Madden,Anna Bal-Price,Mark T D Cronin,Steven J Enoch

doi:10.1007/s00204-019-02551-1

Nicoleta Spinu, Andrew P Worth + Show 4 more

Open Access

https://doi.org/10.1007/s00204-019-02551-1

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Abstract

An adverse outcome pathway (AOP) network is an attempt to represent the complexity of systems toxicology. This study illustrates how an AOP network can be derived and analysed in terms of its topological features to guide research and support chemical risk assessment. A four-step workflow describing general design principles and applied design principles was established and implemented. An AOP network linking nine linear AOPs was mapped and made available in AOPXplorer. The resultant AOP network was modelled and analysed in terms of its topological features, including level of degree, eccentricity and betweenness centrality. Several well-connected KEs were identified, and cell injury/death was established as the most hyperlinked KE across the network. The derived network expands the utility of linear AOPs to better understand signalling pathways involved in developmental and adult/ageing neurotoxicity. The results provide a solid basis to guide the development of in vitro test method batteries, as well as further quantitative modelling of key events (KEs) and key event relationships (KERs) in the AOP network, with an eventual aim to support hazard characterisation and chemical risk assessment.

Highlights

The science of networks is defined as the collection, management, analysis, interpretation and presentation of relational data (Brandes et al 2013)
12 linear adverse outcome pathway (AOP) relevant to human neurotoxicity were identified in accordance with the methodology (Fig. 1) outlined in “Materials and methods”
An AOP network for human neurotoxicity was developed using the principles of the derived AOP network

Summary

Introduction

The science of networks is defined as the collection, management, analysis, interpretation and presentation of relational data (Brandes et al 2013). The investigation of networks is spread widely throughout all branches of biology and chemistry, from neurobiology (Bassett and Sporns 2017) to genomics (Li et al 2017). In biology, the application of networks has made advances towards uncovering the organising principles of various complex systems, e.g. protein-protein interactions, metabolomics, signalling and transcription-regulatory networks Systems toxicology, considered as an application of systems biology, aims to describe the perturbation by toxicants and the resilience of the essential defence and adaptive mechanisms across multiple levels of biological organisations (Hartung et al 2017; Sturla et al 2014). Systems biology captures interactions between biological entities, while systems toxicology focuses on the temporal/spatial relationships between processes/ events, triggered by an exposure to stressor(s), chemicals

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