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Karine Audouze – One of the best experts on this subject based on the ideXlab platform.

  • deciphering Adverse Outcome pathway network linked to bisphenol f using text mining and systems toxicology approaches
    Toxicological Sciences, 2020
    Co-Authors: Marylene Rugard, Xavier Coumoul, Jeancharles Carvaillo, Robert Barouki, Karine Audouze

    Abstract:

    Bisphenol F (BPF) is one of several Bisphenol A (BPA) substituents that is increasingly used in manufacturing industry leading to detectable human exposure. Whereas a large number of studies have been devoted to decipher BPA effects, much less is known about its substituents. To support decision making on BPF’s safety, we have developed a new computational approach to rapidly explore the available data on its toxicological effects, combining text mining and integrative systems biology, and aiming at connecting BPF to Adverse Outcome pathways (AOPs). We first extracted from different databases BPF-protein associations that were expanded to protein complexes using protein-protein interaction datasets. Over-representation analysis of the protein complexes allowed to identify the most relevant biological pathways putatively targeted by BPF. Then, automatic screening of scientific abstracts from literature using the text mining tool, AOP-helpFinder, combined with data integration from various sources (AOP-wiki, CompTox, etc.) and manual curation allowed us to link BPF to AOP events. Finally, we combined all the information gathered through those analyses and built a comprehensive complex framework linking BPF to an AOP network including, as Adverse Outcomes, various types of cancers such as breast and thyroid malignancies. These results which integrate different types of data can support regulatory assessment of the BPA substituent, BPF, and trigger new epidemiological and experimental studies.

  • deciphering Adverse Outcome pathway network linked to bisphenol f using text mining and systems toxicology approaches
    Toxicological Sciences, 2020
    Co-Authors: Marylene Rugard, Xavier Coumoul, Jeancharles Carvaillo, Robert Barouki, Karine Audouze

    Abstract:

    : Bisphenol F (BPF) is one of several Bisphenol A (BPA) substituents that is increasingly used in manufacturing industry leading to detectable human exposure. Whereas a large number of studies have been devoted to decipher BPA effects, much less is known about its substituents. In order to support decision making on BPF’s safety, we have developed a new computational approach to rapidly explore the available data on its toxicological effects, combining text mining and integrative systems biology, and aiming at connecting BPF to Adverse Outcome pathways (AOPs). We first extracted from different databases BPF-protein associations that were expanded to protein complexes using protein-protein interaction datasets. Overrepresentation analysis of the protein complexes allowed to identify the most relevant biological pathways putatively targeted by BPF. Then, automatic screening of scientific abstracts from literature using the text mining tool, AOP-helpFinder, combined with data integration from various sources (AOP-wiki, CompTox, etc.) and manual curation allowed us to link BPF to AOP events. Finally, we combined all the information gathered through those analyses and built a comprehensive complex framework linking BPF to an AOP network including, as Adverse Outcomes, various types of cancers such as breast and thyroid malignancies. These results which integrate different types of data can support regulatory assessment of the BPA substituent, BPF and trigger new epidemiological and experimental studies.

  • Linking Bisphenol S to Adverse Outcome Pathways Using a Combined Text Mining and Systems Biology Approach
    Environmental Health Perspectives, 2019
    Co-Authors: Jeancharles Carvaillo, Xavier Coumoul, Robert Barouki, Karine Audouze

    Abstract:

    Background:Available toxicity data can be optimally interpreted if they are integrated using computational approaches such as systems biology modeling. Such approaches are particularly warranted in cases where regulatory decisions have to be made rapidly.Objectives:The study aims at developing and applying a new integrative computational strategy to identify associations between bisphenol S (BPS), a substitute for bisphenol A (BPA), and components of Adverse Outcome pathways (AOPs). Methods: The proposed approach combines a text mining (TM) procedure and integrative systems biology to comprehensively analyze the scientific literature to enrich AOPs related to environmental stressors. First, to identify relevant associations between BPS and different AOP components, a list of abstracts was screened using the developed text-mining tool AOP-helpFinder, which calculates scores based on the graph theory to prioritize the findings. Then, to fill gaps between BPS, biological events, and Adverse Outcomes (AOs), a systems biology approach was used to integrate information from the AOP-Wiki and ToxCast databases, followed by manual curation of the relevant publications. Results: Links between BPS and 48 AOP key events (KEs) were identified and scored via 31 references. The main Outcomes were related to reproductive health, endocrine disruption, impairments of metabolism, and obesity. We then explicitly analyzed co-mention of the terms BPS and obesity by data integration and manual curation of the full text of the publications. Several molecular and cellular pathways were identified, which allowed the proposal of a biological explanation for the association between BPS and obesity. Conclusions: By analyzing dispersed information from the literature and databases, our novel approach can identify links between stressors and AOP KEs. The findings associating BPS and obesity illustrate the use of computational tools in predictive toxicology and highlight the relevance of the approach to decision makers assessing substituents to toxic chemicals. https://doi.org/10.1289/EHP4200

Jeancharles Carvaillo – One of the best experts on this subject based on the ideXlab platform.

  • deciphering Adverse Outcome pathway network linked to bisphenol f using text mining and systems toxicology approaches
    Toxicological Sciences, 2020
    Co-Authors: Marylene Rugard, Xavier Coumoul, Jeancharles Carvaillo, Robert Barouki, Karine Audouze

    Abstract:

    Bisphenol F (BPF) is one of several Bisphenol A (BPA) substituents that is increasingly used in manufacturing industry leading to detectable human exposure. Whereas a large number of studies have been devoted to decipher BPA effects, much less is known about its substituents. To support decision making on BPF’s safety, we have developed a new computational approach to rapidly explore the available data on its toxicological effects, combining text mining and integrative systems biology, and aiming at connecting BPF to Adverse Outcome pathways (AOPs). We first extracted from different databases BPF-protein associations that were expanded to protein complexes using protein-protein interaction datasets. Over-representation analysis of the protein complexes allowed to identify the most relevant biological pathways putatively targeted by BPF. Then, automatic screening of scientific abstracts from literature using the text mining tool, AOP-helpFinder, combined with data integration from various sources (AOP-wiki, CompTox, etc.) and manual curation allowed us to link BPF to AOP events. Finally, we combined all the information gathered through those analyses and built a comprehensive complex framework linking BPF to an AOP network including, as Adverse Outcomes, various types of cancers such as breast and thyroid malignancies. These results which integrate different types of data can support regulatory assessment of the BPA substituent, BPF, and trigger new epidemiological and experimental studies.

  • deciphering Adverse Outcome pathway network linked to bisphenol f using text mining and systems toxicology approaches
    Toxicological Sciences, 2020
    Co-Authors: Marylene Rugard, Xavier Coumoul, Jeancharles Carvaillo, Robert Barouki, Karine Audouze

    Abstract:

    : Bisphenol F (BPF) is one of several Bisphenol A (BPA) substituents that is increasingly used in manufacturing industry leading to detectable human exposure. Whereas a large number of studies have been devoted to decipher BPA effects, much less is known about its substituents. In order to support decision making on BPF’s safety, we have developed a new computational approach to rapidly explore the available data on its toxicological effects, combining text mining and integrative systems biology, and aiming at connecting BPF to Adverse Outcome pathways (AOPs). We first extracted from different databases BPF-protein associations that were expanded to protein complexes using protein-protein interaction datasets. Overrepresentation analysis of the protein complexes allowed to identify the most relevant biological pathways putatively targeted by BPF. Then, automatic screening of scientific abstracts from literature using the text mining tool, AOP-helpFinder, combined with data integration from various sources (AOP-wiki, CompTox, etc.) and manual curation allowed us to link BPF to AOP events. Finally, we combined all the information gathered through those analyses and built a comprehensive complex framework linking BPF to an AOP network including, as Adverse Outcomes, various types of cancers such as breast and thyroid malignancies. These results which integrate different types of data can support regulatory assessment of the BPA substituent, BPF and trigger new epidemiological and experimental studies.

  • Linking Bisphenol S to Adverse Outcome Pathways Using a Combined Text Mining and Systems Biology Approach
    Environmental Health Perspectives, 2019
    Co-Authors: Jeancharles Carvaillo, Xavier Coumoul, Robert Barouki, Karine Audouze

    Abstract:

    Background:Available toxicity data can be optimally interpreted if they are integrated using computational approaches such as systems biology modeling. Such approaches are particularly warranted in cases where regulatory decisions have to be made rapidly.Objectives:The study aims at developing and applying a new integrative computational strategy to identify associations between bisphenol S (BPS), a substitute for bisphenol A (BPA), and components of Adverse Outcome pathways (AOPs). Methods: The proposed approach combines a text mining (TM) procedure and integrative systems biology to comprehensively analyze the scientific literature to enrich AOPs related to environmental stressors. First, to identify relevant associations between BPS and different AOP components, a list of abstracts was screened using the developed text-mining tool AOP-helpFinder, which calculates scores based on the graph theory to prioritize the findings. Then, to fill gaps between BPS, biological events, and Adverse Outcomes (AOs), a systems biology approach was used to integrate information from the AOP-Wiki and ToxCast databases, followed by manual curation of the relevant publications. Results: Links between BPS and 48 AOP key events (KEs) were identified and scored via 31 references. The main Outcomes were related to reproductive health, endocrine disruption, impairments of metabolism, and obesity. We then explicitly analyzed co-mention of the terms BPS and obesity by data integration and manual curation of the full text of the publications. Several molecular and cellular pathways were identified, which allowed the proposal of a biological explanation for the association between BPS and obesity. Conclusions: By analyzing dispersed information from the literature and databases, our novel approach can identify links between stressors and AOP KEs. The findings associating BPS and obesity illustrate the use of computational tools in predictive toxicology and highlight the relevance of the approach to decision makers assessing substituents to toxic chemicals. https://doi.org/10.1289/EHP4200

Daniel L Villeneuve – One of the best experts on this subject based on the ideXlab platform.

  • Representing the Process of Inflammation as Key Events in Adverse Outcome Pathways
    TOXICOLOGICAL SCIENCES, 2018
    Co-Authors: Daniel L Villeneuve, Anna Bal-price, Brigitte Landesmann, Paola Allavena, Noah Ashley, Emanuela Corsini, Sabina Halappanavar, Tracy Hussell, Debra Laskin, Toby Lawrence

    Abstract:

    Inflammation is an important biological process involved in many target organ toxicities. However, there has been little consensus on how to represent inflammatory processes using the Adverse Outcome pathway (AOP) framework. In particular, there were concerns that inflammation was not being represented in a way that it would be recognized as a highly connected, central node within the global AOP network. The consideration of salient features common to the inflammatory process across tissues was used as a basis to propose 3 hub key events (KEs) for use in AOP network development. Each event, “tissue resident cell activation”, “increased pro-inflammatory mediators”, and “leukocyte recruitment/activation,” is viewed as a hallmark of inflammation, independent of tissue, and can be independently measured. Using these proposed hub KEs, it was possible to link together a series of AOPs that previously had no shared KEs. Significant challenges remain with regard to accurate prediction of inflammation-related toxicological Outcomes even if a broader and more connected network of inflammation-centered AOPs is developed. Nonetheless, the current proposal addresses one of the major hurdles associated with representation of inflammation in AOPs and may aid fit-for-purpose evaluations of other AOPs operating in a network context.

  • increasing scientific confidence in Adverse Outcome pathways application of tailored bradford hill considerations for evaluating weight of evidence
    Regulatory Toxicology and Pharmacology, 2015
    Co-Authors: Richard A Becker, Magdalini Sachana, Stephen W. Edwards, Gerald T Ankley, Sean W Kennedy, Igor Linkov, Bette Meek, Helmut Segner, Bart Van Der Burg, Daniel L Villeneuve

    Abstract:

    Systematic consideration of scientific support is a critical element in developing and, ultimately, using Adverse Outcome pathways (AOPs) for various regulatory applications. Though weight of evidence (WoE) analysis has been proposed as a basis for assessment of the maturity and level of confidence in an AOP, methodologies and tools are still being formalized. The Organization for Economic Co-operation and Development (OECD) Users’ Handbook Supplement to the Guidance Document for Developing and Assessing AOPs (OECD 2014a; hereafter referred to as the OECD AOP Handbook) provides tailored Bradford-Hill (BH) considerations for systematic assessment of confidence in a given AOP. These considerations include (1) biological plausibility and (2) empirical support (dose-response, temporality, and incidence) for Key Event Relationships (KERs), and (3) essentiality of key events (KEs). Here, we test the application of these tailored BH considerations and the guidance outlined in the OECD AOP Handbook using a number of case examples to increase experience in more transparently documenting rationales for assigned levels of confidence to KEs and KERs, and to promote consistency in evaluation within and across AOPs. The major lessons learned from experience are documented, and taken together with the case examples, should contribute to better common understanding of the nature and form of documentation required to increase confidence in the application of AOPs for specific uses. Based on the tailored BH considerations and defining questions, a prototype quantitative model for assessing the WoE of an AOP using tools of multi-criteria decision analysis (MCDA) is described. The applicability of the approach is also demonstrated using the case example aromatase inhibition leading to reproductive dysfunction in fish. Following the acquisition of additional experience in the development and assessment of AOPs, further refinement of parameterization of the model through expert elicitation is recommended. Overall, the application of quantitative WoE approaches hold promise to enhance the rigor, transparency and reproducibility for AOP WoE determinations and may play an important role in delineating areas where research would have the greatest impact on improving the overall confidence in the AOP.

  • Adverse Outcome pathways organizing toxicological information to improve decision making
    Journal of Pharmacology and Experimental Therapeutics, 2015
    Co-Authors: Stephen W. Edwards, M.e. Meek, Daniel L Villeneuve, Yumei Tan, Charlene A Mcqueen

    Abstract:

    The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High-throughput screening commonly used for drug discovery has the potential to increase this capacity. The Adverse Outcome pathway (AOP) concept has emerged as a framework for connecting high-throughput toxicity testing (HTT) and other results to potential impacts on human and wildlife populations. As a result of international efforts, the AOP development process is now well-defined and efforts are underway to broaden the participation through outreach and training. One key principle is that AOPs represent the chemical-agnostic portions of pathways to increase the generalizability of their application from early key events to overt toxicity. The closely related mode of action framework extends the AOP as needed when evaluating the potential risk of a specific chemical. This in turn enables integrated approaches to testing and assessment (IATA), which incorporate results of assays at various levels of biologic organization such as in silico; HTT; chemical-specific aspects including absorption, distribution, metabolism, and excretion (ADME); and an AOP describing the biologic basis of toxicity. Thus, it is envisaged that provision of limited information regarding both the AOP for critical effects and the ADME for any chemical associated with any Adverse Outcome would allow for the development of IATA and permit more detailed AOP and ADME research, where higher precision is needed based on the decision context.