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Adverse outcome pathway networks II: Network analytics.

Daniel L Villeneuve1, Michelle M Angrish2, Marie C Fortin3

  • 1US Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, Minnesota, USA.

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|March 2, 2018
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Summary
This summary is machine-generated.

This study introduces methods for analyzing adverse outcome pathway (AOP) networks, moving beyond single pathways to understand complex toxicological interactions. These network analysis tools aid in predicting environmental stressor effects for better risk assessment.

Keywords:
Adverse outcome pathwayAdverse outcome pathway networkInteractionsMixture toxicologyNetwork topologyPredictive toxicologyRisk assessment

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Area of Science:

  • Environmental Toxicology
  • Computational Toxicology
  • Risk Assessment

Background:

  • Toxicological responses to environmental stressors are complex, involving multiple biological perturbations and adverse outcomes.
  • The adverse outcome pathway (AOP) framework facilitates the development of AOP networks to understand pleiotropic and interactive effects.
  • Existing AOP descriptions need advanced analytical methods for network analysis in complex exposure scenarios.

Purpose of the Study:

  • To introduce qualitative analysis concepts for adverse outcome pathway (AOP) networks.
  • To explore graph theory for identifying key topological features within AOP networks.
  • To describe methods for identifying significant pathways and interactions (additive, synergistic, antagonistic) within AOP networks.

Main Methods:

  • Application of graph theory to analyze topological features of two example AOP networks.
  • Development of criteria for identifying the most significant paths from biological and risk assessment perspectives.
  • Introduction of approaches to characterize interactions among AOPs, including emergent response patterns.

Main Results:

  • Demonstrated graph theory-based approaches for identifying important structural features in AOP networks.
  • Presented considerations for determining critical pathways through AOP networks relevant to toxicology and risk assessment.
  • Introduced novel concepts for analyzing interactions and emergent effects within AOP networks.

Conclusions:

  • The developed concepts provide a foundation for rigorous analysis of AOP networks.
  • These analytical tools and approaches will enhance the utility of AOP network-based predictions for research and regulatory decision-making.
  • This work addresses a key need identified by the Society of Environmental Toxicology and Chemistry for advancing the AOP framework.