| Literature DB >> 29492998 |
Daniel L Villeneuve1, Michelle M Angrish2, Marie C Fortin3, Ioanna Katsiadaki4, Marc Leonard5, Luigi Margiotta-Casaluci6, Sharon Munn7, Jason M O'Brien8, Nathan L Pollesch1, L Cody Smith9, Xiaowei Zhang10, Dries Knapen11.
Abstract
Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734-1748.Keywords: Adverse outcome pathway; Adverse outcome pathway network; Interactions; Mixture toxicology; Network topology; Predictive toxicology; Risk assessment
Mesh:
Year: 2018 PMID: 29492998 PMCID: PMC6010347 DOI: 10.1002/etc.4124
Source DB: PubMed Journal: Environ Toxicol Chem ISSN: 0730-7268 Impact factor: 3.742