Adverse outcome pathway networks II: Network analytics

Daniel L. Villeneuve; Michelle M. Angrish; Marie C. Fortin; Ioanna Katsiadaki; Marc Leonard; Luigi Margiotta-Casaluci; Sharon Munn; Jason M. O'Brien; Nathan L. Pollesch; L. Cody Smith; Xiaowei Zhang; Dries Knapen

doi:10.1002/etc.4124

Adverse outcome pathway networks II: Network analytics

Daniel L. Villeneuve^*, Michelle M. Angrish, Marie C. Fortin, Ioanna Katsiadaki, Marc Leonard, Luigi Margiotta-Casaluci, Sharon Munn, Jason M. O'Brien, Nathan L. Pollesch, L. Cody Smith, Xiaowei Zhang, Dries Knapen

^*Corresponding author for this work

Analytical, Environmental & Forensic Sciences

Research output: Contribution to journal › Article › peer-review

122 Citations (Scopus)

Abstract

Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory–based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734–1748.

Original language	English
Pages (from-to)	1734-1748
Number of pages	15
Journal	ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
Volume	37
Issue number	6
DOIs	https://doi.org/10.1002/etc.4124
Publication status	Published - Jun 2018

Keywords

Adverse outcome pathway
Adverse outcome pathway network
Interactions
Mixture toxicology
Network topology
Predictive toxicology
Risk assessment

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10.1002/etc.4124

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@article{bb8c088186674673b435f4910720d4ba,

title = "Adverse outcome pathway networks II: Network analytics",

abstract = "Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory–based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734–1748.",

keywords = "Adverse outcome pathway, Adverse outcome pathway network, Interactions, Mixture toxicology, Network topology, Predictive toxicology, Risk assessment",

author = "Villeneuve, {Daniel L.} and Angrish, {Michelle M.} and Fortin, {Marie C.} and Ioanna Katsiadaki and Marc Leonard and Luigi Margiotta-Casaluci and Sharon Munn and O'Brien, {Jason M.} and Pollesch, {Nathan L.} and Smith, {L. Cody} and Xiaowei Zhang and Dries Knapen",

note = "Funding Information: aUS Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, Minnesota, USA bUS Environmental Protection Agency, National Center for Environmental Assessment, Research Triangle Park, North Carolina, USA cDepartment of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, USA dCentre for Environment, Fisheries and Aquaculture Science, Weymouth, United Kingdom eL{\textquoteright}Or{\'e}al Advanced Research, Aulnay-sous-Bois, France fInstitute of Environment, Health and Societies, Brunel University London, London, United Kingdom gJoint Research Centre, European Commission, Ispra, Italy hEnvironment and Climate Change Canada, National Wildlife Research Centre, Ottawa, Ontario, Canada iCenter for Environmental and Human Toxicology, University of Florida, Gainesville, Florida, USA jState Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, People{\textquoteright}s Republic of China kZebrafishlab, Veterinary Physiology and Biochemistry, University of Antwerp, Wilrijk, Belgium Funding Information: Acknowledgment—The authors thank the Society of Environmental Toxicology and Chemistry (SETAC) Pellston Workshop co-chairs, C. LaLone and M. Hecker, for their coordination, organization, and guidance of the workshop. We acknowledge the other workshop participants (see LaLone and Hecker 2017) for their stimulating discussions and feedback and the respondents to the Horizon Scanning efforts for the charge questions and themes that informed our discussion. We gratefully acknowledge the SETAC North America staff, in particular G. Schiefer, N. Mayo, and T. Schlekat, who provided support to the workshop co-chairs, steering committee, and workshop participants before, during, and after the Pellston Workshop. Funding for the workshop was provided by SETAC, the US Environmental Protection Agency, the American Cleaning Institute, the European Chemical Industry Council Long-Range Research Initiative, Chevron Environmental Management, the European Center for Ecotoxicology and Toxicology of Chemicals, the European Commission Joint Research Centre, the European Crop Protection Association, ExxonMobil, Humane Society International, The Humane Society of the United States, the Human Toxicology Project Consortium, Syngenta, and Unilever. In addition, we thank the groups from academia, industry, and government who supported the participants{\textquoteright} travel. Finally, we thank S. Edwards for review and input on the draft manuscript. Publisher Copyright: {\textcopyright} 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.",

year = "2018",

month = jun,

doi = "10.1002/etc.4124",

language = "English",

volume = "37",

pages = "1734--1748",

journal = "ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY",

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T1 - Adverse outcome pathway networks II

T2 - Network analytics

AU - Villeneuve, Daniel L.

AU - Angrish, Michelle M.

AU - Fortin, Marie C.

AU - Katsiadaki, Ioanna

AU - Leonard, Marc

AU - Margiotta-Casaluci, Luigi

AU - Munn, Sharon

AU - O'Brien, Jason M.

AU - Pollesch, Nathan L.

AU - Smith, L. Cody

AU - Zhang, Xiaowei

AU - Knapen, Dries

N1 - Funding Information: aUS Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, Minnesota, USA bUS Environmental Protection Agency, National Center for Environmental Assessment, Research Triangle Park, North Carolina, USA cDepartment of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, USA dCentre for Environment, Fisheries and Aquaculture Science, Weymouth, United Kingdom eL’Oréal Advanced Research, Aulnay-sous-Bois, France fInstitute of Environment, Health and Societies, Brunel University London, London, United Kingdom gJoint Research Centre, European Commission, Ispra, Italy hEnvironment and Climate Change Canada, National Wildlife Research Centre, Ottawa, Ontario, Canada iCenter for Environmental and Human Toxicology, University of Florida, Gainesville, Florida, USA jState Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, People’s Republic of China kZebrafishlab, Veterinary Physiology and Biochemistry, University of Antwerp, Wilrijk, Belgium Funding Information: Acknowledgment—The authors thank the Society of Environmental Toxicology and Chemistry (SETAC) Pellston Workshop co-chairs, C. LaLone and M. Hecker, for their coordination, organization, and guidance of the workshop. We acknowledge the other workshop participants (see LaLone and Hecker 2017) for their stimulating discussions and feedback and the respondents to the Horizon Scanning efforts for the charge questions and themes that informed our discussion. We gratefully acknowledge the SETAC North America staff, in particular G. Schiefer, N. Mayo, and T. Schlekat, who provided support to the workshop co-chairs, steering committee, and workshop participants before, during, and after the Pellston Workshop. Funding for the workshop was provided by SETAC, the US Environmental Protection Agency, the American Cleaning Institute, the European Chemical Industry Council Long-Range Research Initiative, Chevron Environmental Management, the European Center for Ecotoxicology and Toxicology of Chemicals, the European Commission Joint Research Centre, the European Crop Protection Association, ExxonMobil, Humane Society International, The Humane Society of the United States, the Human Toxicology Project Consortium, Syngenta, and Unilever. In addition, we thank the groups from academia, industry, and government who supported the participants’ travel. Finally, we thank S. Edwards for review and input on the draft manuscript. Publisher Copyright: © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

PY - 2018/6

Y1 - 2018/6

N2 - Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory–based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734–1748.

AB - Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory–based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734–1748.

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KW - Adverse outcome pathway network

KW - Interactions

KW - Mixture toxicology

KW - Network topology

KW - Predictive toxicology

KW - Risk assessment

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JO - ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY

JF - ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY

IS - 6

ER -

Adverse outcome pathway networks II: Network analytics

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Keywords

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Adverse outcome pathway networks I: Development and applications

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