Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology

Rory B. Conolly, Gerald T. Ankley, Wanyun Cheng, Michael L. Mayo, David H. Miller, Edward J. Perkins, Daniel L. Villeneuve, Karen Watanabe-Sailor

Research output: Contribution to journalArticle

61 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)4661-4672
Number of pages12
JournalEnvironmental Science and Technology
Volume51
Issue number8
DOIs
StatePublished - Apr 18 2017
Externally publishedYes

ASJC Scopus subject areas

  • Chemistry(all)
  • Environmental Chemistry

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    Conolly, R. B., Ankley, G. T., Cheng, W., Mayo, M. L., Miller, D. H., Perkins, E. J., Villeneuve, D. L., & Watanabe-Sailor, K. (2017). Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology. Environmental Science and Technology, 51(8), 4661-4672. https://doi.org/10.1021/acs.est.6b06230