Literature DB >> 29492998

Adverse outcome pathway networks II: Network analytics.

Daniel L Villeneuve1, Michelle M Angrish2, Marie C Fortin3, Ioanna Katsiadaki4, Marc Leonard5, Luigi Margiotta-Casaluci6, Sharon Munn7, Jason M O'Brien8, Nathan L Pollesch1, L Cody Smith9, Xiaowei Zhang10, Dries Knapen11.   

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.
© 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. © 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.

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

Mesh:

Year:  2018        PMID: 29492998      PMCID: PMC6010347          DOI: 10.1002/etc.4124

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  20 in total

1.  The topological relationship between the large-scale attributes and local interaction patterns of complex networks.

Authors:  A Vázquez; R Dobrin; D Sergi; J-P Eckmann; Z N Oltvai; A-L Barabási
Journal:  Proc Natl Acad Sci U S A       Date:  2004-12-14       Impact factor: 11.205

2.  Betweenness centrality of fractal and nonfractal scale-free model networks and tests on real networks.

Authors:  Maksim Kitsak; Shlomo Havlin; Gerald Paul; Massimo Riccaboni; Fabio Pammolli; H Eugene Stanley
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2007-05-31

Review 3.  Network motifs: theory and experimental approaches.

Authors:  Uri Alon
Journal:  Nat Rev Genet       Date:  2007-06       Impact factor: 53.242

4.  Advancing the adverse outcome pathway framework-An international horizon scanning approach.

Authors:  Carlie A LaLone; Gerald T Ankley; Scott E Belanger; Michelle R Embry; Geoff Hodges; Dries Knapen; Sharon Munn; Edward J Perkins; Murray A Rudd; Daniel L Villeneuve; Maurice Whelan; Catherine Willett; Xiaowei Zhang; Markus Hecker
Journal:  Environ Toxicol Chem       Date:  2017-06       Impact factor: 3.742

Review 5.  Integrated Approaches to Testing and Assessment.

Authors:  Andrew P Worth; Grace Patlewicz
Journal:  Adv Exp Med Biol       Date:  2016       Impact factor: 2.622

6.  Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.

Authors:  Rory B Conolly; Gerald T Ankley; WanYun Cheng; Michael L Mayo; David H Miller; Edward J Perkins; Daniel L Villeneuve; Karen H Watanabe
Journal:  Environ Sci Technol       Date:  2017-04-07       Impact factor: 9.028

Review 7.  [Cellular dysfunction in the pathogenesis of organ failure. New insights from molecular and cell biology].

Authors:  T Koch; R H Funk
Journal:  Anaesthesist       Date:  2001-10       Impact factor: 1.041

Review 8.  Crosstalk in cellular signaling: background noise or the real thing?

Authors:  Grégory Vert; Joanne Chory
Journal:  Dev Cell       Date:  2011-12-13       Impact factor: 12.270

9.  Evolution of bow-tie architectures in biology.

Authors:  Tamar Friedlander; Avraham E Mayo; Tsvi Tlusty; Uri Alon
Journal:  PLoS Comput Biol       Date:  2015-03-23       Impact factor: 4.475

10.  XTalkDB: a database of signaling pathway crosstalk.

Authors:  Sarah A Sam; Joelle Teel; Allison N Tegge; Aditya Bharadwaj; T M Murali
Journal:  Nucleic Acids Res       Date:  2016-11-28       Impact factor: 16.971

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  28 in total

1.  Effect of Thyroperoxidase and Deiodinase Inhibition on Anterior Swim Bladder Inflation in the Zebrafish.

Authors:  Evelyn Stinckens; Lucia Vergauwen; Brett R Blackwell; Gerald T Ankley; Daniel L Villeneuve; Dries Knapen
Journal:  Environ Sci Technol       Date:  2020-04-29       Impact factor: 9.028

2.  An AOP-based alternative testing strategy to predict the impact of thyroid hormone disruption on swim bladder inflation in zebrafish.

Authors:  Evelyn Stinckens; Lucia Vergauwen; Gerald T Ankley; Ronny Blust; Veerle M Darras; Daniel L Villeneuve; Hilda Witters; David C Volz; Dries Knapen
Journal:  Aquat Toxicol       Date:  2018-04-21       Impact factor: 4.964

Review 3.  Progress in data interoperability to support computational toxicology and chemical safety evaluation.

Authors:  Sean Watford; Stephen Edwards; Michelle Angrish; Richard S Judson; Katie Paul Friedman
Journal:  Toxicol Appl Pharmacol       Date:  2019-08-09       Impact factor: 4.219

4.  Linking Mitochondrial Dysfunction to Organismal and Population Health in the Context of Environmental Pollutants: Progress and Considerations for Mitochondrial Adverse Outcome Pathways.

Authors:  David A Dreier; Danielle F Mello; Joel N Meyer; Christopher J Martyniuk
Journal:  Environ Toxicol Chem       Date:  2019-08       Impact factor: 3.742

5.  Toward an AOP Network-Based Tiered Testing Strategy for the Assessment of Thyroid Hormone Disruption.

Authors:  Dries Knapen; Evelyn Stinckens; Jenna E Cavallin; Gerald T Ankley; Henrik Holbech; Daniel L Villeneuve; Lucia Vergauwen
Journal:  Environ Sci Technol       Date:  2020-07-09       Impact factor: 9.028

6.  Semantic characterization of adverse outcome pathways.

Authors:  Rong-Lin Wang
Journal:  Aquat Toxicol       Date:  2020-03-30       Impact factor: 4.964

7.  Adverse outcome pathway networks I: Development and applications.

Authors:  Dries Knapen; Michelle M Angrish; Marie C Fortin; Ioanna Katsiadaki; Marc Leonard; Luigi Margiotta-Casaluci; Sharon Munn; Jason M O'Brien; Nathan Pollesch; L Cody Smith; Xiaowei Zhang; Daniel L Villeneuve
Journal:  Environ Toxicol Chem       Date:  2018-05-07       Impact factor: 3.742

Review 8.  Twenty years of transcriptomics, 17alpha-ethinylestradiol, and fish.

Authors:  Christopher J Martyniuk; April Feswick; Kelly R Munkittrick; David A Dreier; Nancy D Denslow
Journal:  Gen Comp Endocrinol       Date:  2019-11-13       Impact factor: 2.822

9.  Adverse Outcome Pathways as Versatile Tools in Liver Toxicity Testing.

Authors:  Emma Arnesdotter; Eva Gijbels; Bruna Dos Santos Rodrigues; Vânia Vilas-Boas; Mathieu Vinken
Journal:  Methods Mol Biol       Date:  2022

10.  A methodology for developing key events to advance nanomaterial-relevant adverse outcome pathways to inform risk assessment.

Authors:  Sabina Halappanavar; James D Ede; Indrani Mahapatra; Harald F Krug; Eileen D Kuempel; Iseult Lynch; Rob J Vandebriel; Jo Anne Shatkin
Journal:  Nanotoxicology       Date:  2020-12-14       Impact factor: 5.913

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