Abstract
The adverse outcome pathway (AOP) framework is a conceptual construct that mechanistically links molecular initiating events to adverse biological outcomes through a series of causal key events (KEs) that represent the perturbation of the biological system. Quantitative, predictive AOPs are necessary for screening emerging contaminants and potential substitutes to inform their prioritization for testing. In practice, they are not widely used because they can be costly to develop and validate. A modular approach for assembly of quantitative AOPs, based on existing knowledge, would allow for rapid development of biological pathway models to screen contaminants for potential hazards and prioritize them for subsequent testing and modeling. For each pair of KEs, a quantitative KE relationship (KER) can be derived as a response-response function or a conditional probability matrix describing the anticipated change in a KE based on the response of the prior KE. This transfer of response across KERs can be used to assemble a quantitative AOP. Here we demonstrate the use of proposed approach in two cases: inhibition of cytochrome P450 aromatase leading to reduced fecundity in fathead minnows and ionic glutamate receptor mediated excitotoxicity leading to memory impairment in rodents. The model created from these chains have value in characterizing the pathway and the potential or relative level of toxicological effect anticipated. This approach to simplistic, modular AOP models has wide applicability for rapid development of biological pathway models.
Highlights
Adverse outcome pathways, or adverse outcome pathway (AOP), are pragmatic descriptions of a biological pathway leading to an outcome of regulatory concern that have the potential to inform chemical risk management decisions (Ankley and Giesy, 1998; OECD, 2017, 2018; Perkins et al, 2019)
By combining the four qKERs developed for aromatase inhibition as depicted in Figure 5, the level of activation of specific nodes can be tracked for a hypothetical scenario in which a fathead minnow population is exposed to a chemical that reduces aromatase activity by 25%
The outcomes calculated from this simple chain of modular qKERs are similar to the results from the linked systemic models developed by Conolly et al (2017)
Summary
AOPs, are pragmatic descriptions of a biological pathway leading to an outcome of regulatory concern that have the potential to inform chemical risk management decisions (Ankley and Giesy, 1998; OECD, 2017, 2018; Perkins et al, 2019). Given the potentially large number of AOPs needed to describe known toxicological pathways, the limited availability of relevant mechanistic data, and the extensive time required to develop mechanistic AOP models, a complementary approach is needed to utilize existing data to develop easy-to-assemble, modular, quantitative AOPs (qAOPs). Such an approach could be developed from a current understanding of the responses of biological pathways that are perturbed, and relate the level of “activation” quantitatively with the anticipated degree or probability of the adverse outcome. This modular approach, coarser and more uncertain (Fig. 1), would facilitate rapid prototyping and updating of both modules and complete AOP models, making it better-suited for screening and prioritization than the more detailed and resource-intensive
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
