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Use of the adverse outcome pathway framework to represent cross-species consequences of specific pathway perturbations
Citation:
Villeneuve, Dan, C. LaLone, M. Hornung, A. Schroeder, G. Ankley, H. Mortenson, S. Edwards, D. Knapen, AND M. Hecker. Use of the adverse outcome pathway framework to represent cross-species consequences of specific pathway perturbations. SETAC, North America, Salt Lake City, UT, November 01 - 05, 2015.
Impact/Purpose:
not applicable
Description:
The adverse outcome pathway (AOP) framework has been developed as a means for assembling scientifically defensible descriptions of how particular molecular perturbations, termed molecular initiating events (MIEs), can evoke a set of predictable responses at different levels of biological organisation (key events, KEs) culminating in an adverse outcome (AO) of regulatory significance. It is however recognized that the consequences of chemical-induced pathway perturbations can vary significantly among species. Therefore, for the framework to be useful in an ecological risk assessment context, it is important that both cross-species similarities and differences can be represented. Recent case studies with thyroperoxidase and deiodinase inhibition leading to adverse developmental outcomes in fish, frogs, and mammals, and aryl hydrocarbon receptor activation leading to adverse effects in fish, birds, and mammals, provide examples of how the AOP framework, and AOP networks, can be applied to capture knowledge concerning the range of AOs that may manifest across species. The examples provide insight into how the AOP framework can serve as a foundation and justification for using high throughput toxicology data from a limited range of model species to predict apical outcomes in a broader range of taxa. Additionally, they demonstrate how a systematic evaluation framework can be applied to consider the relevant taxonomic applicability domain of any given AOP. Overall, the case studies demonstrate how the AOP framework can be effectively applied to support and inform cross-species extrapolation as part of a pathway-based to risk-based ecological decision-making.