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Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology
Citation:
Conolly, R., G. Ankley, W. Cheng, M. Mayo, D. Miller, E. Perkins, Dan Villeneuve, AND K. Watanabe. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 51(8):4661-4672, (2017).
Impact/Purpose:
This manuscript describes a fully quantitative version of an adverse outcome pathway (AOP). The AOP links inhibition of the enzyme CYP19A (aromatase) in the ovary of the fathead minnow (FHM) with reproductive failure and population decline. Aromatase converts testosterone into estradiol (E2). Egg production in the FHM is E2-dependent, hence the reproductive failure. The significance of having a quantitative AOP (qAOP) is that it provides a capability to describe (1) how the FHM attempts to maintain homeostasis by compensating for the aromatase inhibition and (2) the dose-response and time course of reproductive failure and population decline when compensation fails. These quantitative, predictive capabilities that are functions of the degree and duration of inhibition of aromatase distinguish the qAOP from the AOP on which it is based.
Description:
A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose–response, and time-course predictions that can support regulatory decision-making. Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications. The qAOP used as an illustrative example for these points describes the linkage between inhibition of cytochrome P450 19A aromatase (the MIE) and population-level decreases in the fathead minnow (FHM; Pimephales promelas). The qAOP consists of three linked computational models for the following: (a) the hypothalamic-pitutitary-gonadal axis in female FHMs, where aromatase inhibition decreases the conversion of testosterone to 17β-estradiol (E2), thereby reducing E2-dependent vitellogenin (VTG; egg yolk protein precursor) synthesis, (b) VTG-dependent egg development and spawning (fecundity), and (c) fecundity-dependent population trajectory. While development of the example qAOP was based on experiments with FHMs exposed to the aromatase inhibitor fadrozole, we also show how a toxic equivalence (TEQ) calculation allows use of the qAOP to predict effects of another, untested aromatase inhibitor, iprodione. While qAOP development can be resource-intensive, the quantitative predictions obtained, and TEQ-based application to multiple chemicals, may be sufficient to justify the cost for some applications in regulatory decision-making.
