In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan

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• dc.contributor.author Jorba Argemí, Guillem
• dc.contributor.author Aguirre Plans, Joaquim, 1993-
• dc.contributor.author Junet, Valentin
• dc.contributor.author Segú-Vergés, Cristina
• dc.contributor.author Ruiz, José Luis
• dc.contributor.author Pujol, Albert
• dc.contributor.author Fernández Fuentes, Narcís
• dc.contributor.author Mas, José Manuel
• dc.contributor.author Oliva Miguel, Baldomero
• dc.date.accessioned 2020-04-22T06:55:14Z
• dc.date.available 2020-04-22T06:55:14Z
• dc.date.issued 2020
• dc.description.abstract Unveiling the mechanism of action of a drug is key to understand the benefits and adverse reactions of a medication in an organism. However, in complex diseases such as heart diseases there is not a unique mechanism of action but a wide range of different responses depending on the patient. Exploring this collection of mechanisms is one of the clues for a future personalized medicine. The Therapeutic Performance Mapping System (TPMS) is a Systems Biology approach that generates multiple models of the mechanism of action of a drug. Each molecular mechanism generated could be associated to particular individuals, here defined as prototype-patients, hence the generation of models using TPMS technology may be used for detecting adverse effects to specific patients. TPMS operates by (1) modelling the responses in humans with an accurate description of a protein network and (2) applying a Multilayer Perceptron-like and sampling strategy to find all plausible solutions. In the present study, TPMS is applied to explore the diversity of mechanisms of action of the drug combination sacubitril/valsartan. We use TPMS to generate a wide range of models explaining the relationship between sacubitril/valsartan and heart failure (the indication), as well as evaluating their association with macular degeneration (a potential adverse effect). Among the models generated, we identify a set of mechanisms of action associated to a better response in terms of heart failure treatment, which could also be associated to macular degeneration development. Finally, a set of 30 potential biomarkers are proposed to identify mechanisms (or prototype-patients) more prone of suffering macular degeneration when presenting good heart failure response. All prototype-patients models generated are completely theoretical and therefore they do not necessarily involve clinical effects in real patients. Data and accession to software are available at http://sbi.upf.edu/data/tpms/.
• dc.description.sponsorship Public funders provided support for authors salaries: JAP, NFF and BO received support from the Spanish Ministry of Economy (MINECO) [BIO2017-85329-R] [RYC-2015-17519]; “Unidad de Excelencia María de Maeztu”, funded by the Spanish Ministry of Economy [ref: MDM-2014-0370]. The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and is supported by grant PT13/0001/0023, of the PE I+D+i 2013-2016, funded by ISCIII and FEDER. GJ has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765912. VJ is part of a project (COSMIC; www.cosmic-h2020.eu) that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765158. Funding for publication is from Agència de Gestió D'ajuts Universitaris i de Recerca Generalitat de Catalunya [2017SGR00519]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
• dc.format.mimetype application/pdf
• dc.identifier.citation Jorba G, Aguirre-Plans J, Junet V, Segú-Vergés C, Ruiz JL, Pujol A, Fernández-Fuentes N, Mas JM, Oliva B. In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan. PLoS One. 2020; 15(2):e0228926. DOI: 10.1371/journal.pone.0228926
• dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0228926
• dc.identifier.issn 1932-6203
• dc.identifier.uri http://hdl.handle.net/10230/44305
• dc.language.iso eng
• dc.publisher Public Library of Science (PLoS)
• dc.relation.ispartof PLoS One. 2020; 15(2):e0228926
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/765912
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BIO2017-85329-R
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/RYC-2015-17519
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/765158
• dc.rights © 2020 Jorba et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Biomarkers
• dc.subject.keyword Heart failure
• dc.subject.keyword Adverse reactions
• dc.subject.keyword Adverse events
• dc.subject.keyword Protein interaction networks
• dc.subject.keyword Fibrinolysis
• dc.subject.keyword Gene ontologies
• dc.subject.keyword Macular degeneration
• dc.title In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion