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Research ArticleMinireview

Adverse Outcome Pathways—Organizing Toxicological Information to Improve Decision Making

Stephen W. Edwards, Yu-Mei Tan, Daniel L. Villeneuve, M.E. Meek and Charlene A. McQueen
Journal of Pharmacology and Experimental Therapeutics January 2016, 356 (1) 170-181; DOI: https://doi.org/10.1124/jpet.115.228239
Stephen W. Edwards
Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory (S.W.E., C.A.M.), and Human Exposure & Atmospheric Sciences Division, National Exposure Research Laboratory (Y.-M.T.), Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina; Mid-Continent Ecology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Duluth, Minnesota (D.L.V.); and McLaughlin Centre for Risk Science, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada (M.E.M.)
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Yu-Mei Tan
Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory (S.W.E., C.A.M.), and Human Exposure & Atmospheric Sciences Division, National Exposure Research Laboratory (Y.-M.T.), Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina; Mid-Continent Ecology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Duluth, Minnesota (D.L.V.); and McLaughlin Centre for Risk Science, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada (M.E.M.)
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Daniel L. Villeneuve
Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory (S.W.E., C.A.M.), and Human Exposure & Atmospheric Sciences Division, National Exposure Research Laboratory (Y.-M.T.), Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina; Mid-Continent Ecology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Duluth, Minnesota (D.L.V.); and McLaughlin Centre for Risk Science, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada (M.E.M.)
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M.E. Meek
Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory (S.W.E., C.A.M.), and Human Exposure & Atmospheric Sciences Division, National Exposure Research Laboratory (Y.-M.T.), Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina; Mid-Continent Ecology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Duluth, Minnesota (D.L.V.); and McLaughlin Centre for Risk Science, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada (M.E.M.)
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Charlene A. McQueen
Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory (S.W.E., C.A.M.), and Human Exposure & Atmospheric Sciences Division, National Exposure Research Laboratory (Y.-M.T.), Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina; Mid-Continent Ecology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Duluth, Minnesota (D.L.V.); and McLaughlin Centre for Risk Science, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada (M.E.M.)
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    Fig. 1.

    AOP and MOA components. An AOP consists of KEs and KERs at different levels of biologic organization ranging from macromolecular interactions to population responses. The MIE represents the interaction of the chemical with the biologic system. The AO represents overt adversity at either the individual or population level, which in turn represents the endpoints used when determining safe levels of chemicals. KEs at molecular and cellular levels represent toxicity pathways that can potentially be evaluated using high-throughput screens. A MOA can be constructed from the AOP by including chemical-specific information such as ADME and a prediction of the relationship between the chemical concentration at the site of the MIE and the strength of perturbation of the MIE.

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    Fig. 2.

    AOP examples. (A) AOP network containing two AOPs linked to a decrease in signaling through the estrogen receptor. Estrogen receptor antagonists bind directly to the estrogen receptor, resulting in a reduction of estrogen receptor signaling (purple node) as the MIE. The AOP initiated by the inhibition of the aromatase enzyme and reduction of estrogen synthesis includes three additional KEs (green nodes) upstream of the decrease in estrogen receptor signaling. In this case, decreased signaling by estrogen receptors would be secondary to decrease circulating estrogen levels and the MIE would be the inhibition of the aromatase enzyme. (B) AOP example highlighting the capture of several biologic processes within a single KER.

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    Fig. 3.

    Tiered structures for defining AOPs and ADME allow for MOA at varying levels of confidence. The left side shows the phases of AOP development including three expert-derived types of AOPs and one cpAOP type. The left triangle represents the relative number of AOPs expected for any given type based on the time and effort required to reach that phase of development. This type of phased structure allows the acceptable uncertainty based on the intended use of the AOP to determine the effort expended to define and evaluate the AOP. The right side shows a tiered approach to defining the ADME for a chemical, which provides the same benefits as the phased AOP development. The triangle in this case represents the relative number of chemicals for which an ADME prediction at a given tier can be made. The tiered approaches for both chemical-specific ADME and chemical-agnostic AOPs allow for the development of MOAs for a wide array of chemicals with lower confidence. As more confidence is required (represented by the width of the green triangle in the middle), the number of chemical/AO pairs that can be characterized will decrease.

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    TABLE 1

    Glossary of terms

    TermDefinition
    AOP“An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event (e.g., a molecular interaction between a xeno-biotic and a specific biomolecule) and an adverse outcome at a biological level of organization relevant to risk assessment.”a
    MOAA “biologically plausible series of key events leading to” an adverse effect.b
    A “sequence of Key Events and processes, starting with interaction of an agent with a cell, proceeding through operational and anatomical changes, and resulting in” an adverse effect. “Mode of action is contrasted with ‘mechanism of action,’ which implies a more detailed understanding and description of events.”c
    KE“A key event is an empirically observable step or its marker, which is a necessary element of the mode of action critical to the outcome (i.e., necessary, but not necessarily sufficient in its own right); key events are measurable and reproducible.”b
    Measureable/observable biologic changes that are essential to the progression from the molecular interaction of a xenobiotic with the biologic system to an AO considered relevant to regulatory decision making. “KEs are, in essence, measurements of biological state or change in state with regard to a control or reference. Because KEs are measurements or observations of state, the confidence one has in a KE is dictated by the accuracy and precision with which that biological state can be measured.”d
    KERThe predictive and/or causal linkages between a pair of KEs. “KERs, in contrast, are a unit of inference or extrapolation. They are defined by the biological plausibility and evidence that provide a scientifically credible basis for inferring or predicting the state of a downstream KE based on the known state of an upstream KE and the confidence in that inference or prediction is defined by the weight of supporting evidence.”d
    MIEThe first KE within an AOP representing the biologic perturbation resulting from a molecular interaction between a xenobiotic and a specific biomolecule.
    AOLate stage KE in an AOP representing a biologic perturbation that would be considered adverse in a regulatory context. These typically occur at either the individual (e.g., cancer) or population (e.g., lack of reproductive carrying capacity) levels of organization.
    • ↵a Ankley et al. (2010).

    • ↵b Meek et al. (2014a).

    • ↵c EPA (2005).

    • ↵d Villeneuve et al. (2014a).

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    TABLE 2

    Five principles of AOP developmenta

    Principle NumberPrinciple
    1AOPs are not chemical specific.
    2AOPs are modular (consisting of KEs and KERs).
    3An individual AOP is a pragmatic unit of development and evaluation.
    4For most real-world applications, AOP networks are the functional unit of prediction.
    5AOPs are living documents.
    • ↵a Villeneuve et al. (2014a).

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Journal of Pharmacology and Experimental Therapeutics: 356 (1)
Journal of Pharmacology and Experimental Therapeutics
Vol. 356, Issue 1
1 Jan 2016
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Research ArticleMinireview

Adverse Outcome Pathways

Stephen W. Edwards, Yu-Mei Tan, Daniel L. Villeneuve, M.E. Meek and Charlene A. McQueen
Journal of Pharmacology and Experimental Therapeutics January 1, 2016, 356 (1) 170-181; DOI: https://doi.org/10.1124/jpet.115.228239

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Research ArticleMinireview

Adverse Outcome Pathways

Stephen W. Edwards, Yu-Mei Tan, Daniel L. Villeneuve, M.E. Meek and Charlene A. McQueen
Journal of Pharmacology and Experimental Therapeutics January 1, 2016, 356 (1) 170-181; DOI: https://doi.org/10.1124/jpet.115.228239
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    • Abstract
    • Introduction
    • Adverse Outcome Pathways—Evolution of the Concept
    • Adverse Outcome Pathways—Where Are We Now?
    • Developing a MOA from an AOP and Absorption, Distribution, Metabolism, and Excretion (ADME) Information
    • Applications for the AOP/MOA Framework
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