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Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction

Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarctio...

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Autores principales: Iborra-Egea, Oriol, Gálvez-Montón, Carolina, Prat-Vidal, Cristina, Roura, Santiago, Soler-Botija, Carolina, Revuelta-López, Elena, Ferrer-Curriu, Gemma, Segú-Vergés, Cristina, Mellado-Bergillos, Araceli, Gomez-Puchades, Pol, Gastelurrutia, Paloma, Bayes-Genis, Antoni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699769/
https://www.ncbi.nlm.nih.gov/pubmed/34943776
http://dx.doi.org/10.3390/cells10123268
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author Iborra-Egea, Oriol
Gálvez-Montón, Carolina
Prat-Vidal, Cristina
Roura, Santiago
Soler-Botija, Carolina
Revuelta-López, Elena
Ferrer-Curriu, Gemma
Segú-Vergés, Cristina
Mellado-Bergillos, Araceli
Gomez-Puchades, Pol
Gastelurrutia, Paloma
Bayes-Genis, Antoni
author_facet Iborra-Egea, Oriol
Gálvez-Montón, Carolina
Prat-Vidal, Cristina
Roura, Santiago
Soler-Botija, Carolina
Revuelta-López, Elena
Ferrer-Curriu, Gemma
Segú-Vergés, Cristina
Mellado-Bergillos, Araceli
Gomez-Puchades, Pol
Gastelurrutia, Paloma
Bayes-Genis, Antoni
author_sort Iborra-Egea, Oriol
collection PubMed
description Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. We cross-validated the results using available clinical and experimental information. MI progression was accompanied by the regulation of adipogenesis, fatty acid metabolism, and epithelial–mesenchymal transition. The infarct core region was enriched in processes related to muscle contraction and membrane depolarization. Angiogenesis was among the first morphogenic responses detected as being sustained over time, but other processes suggesting post-ischemic recapitulation of embryogenic processes were also observed. Finally, protein-triggering analysis established the key genes mediating each process at each time point, as well as the complete adverse remodeling response. We modeled the behaviors of these genes, generating a description of the integrative mechanism of action for MI progression. This mechanistic analysis overlapped at different time points; the common pathways between the source proteins and cardiac remodeling involved IGF1R, RAF1, KPCA, JUN, and PTN11 as modulators. Thus, our data delineate a structured and comprehensive picture of the molecular remodeling process, identify new potential biomarkers or therapeutic targets, and establish therapeutic windows during disease progression.
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spelling pubmed-86997692021-12-24 Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction Iborra-Egea, Oriol Gálvez-Montón, Carolina Prat-Vidal, Cristina Roura, Santiago Soler-Botija, Carolina Revuelta-López, Elena Ferrer-Curriu, Gemma Segú-Vergés, Cristina Mellado-Bergillos, Araceli Gomez-Puchades, Pol Gastelurrutia, Paloma Bayes-Genis, Antoni Cells Article Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. We cross-validated the results using available clinical and experimental information. MI progression was accompanied by the regulation of adipogenesis, fatty acid metabolism, and epithelial–mesenchymal transition. The infarct core region was enriched in processes related to muscle contraction and membrane depolarization. Angiogenesis was among the first morphogenic responses detected as being sustained over time, but other processes suggesting post-ischemic recapitulation of embryogenic processes were also observed. Finally, protein-triggering analysis established the key genes mediating each process at each time point, as well as the complete adverse remodeling response. We modeled the behaviors of these genes, generating a description of the integrative mechanism of action for MI progression. This mechanistic analysis overlapped at different time points; the common pathways between the source proteins and cardiac remodeling involved IGF1R, RAF1, KPCA, JUN, and PTN11 as modulators. Thus, our data delineate a structured and comprehensive picture of the molecular remodeling process, identify new potential biomarkers or therapeutic targets, and establish therapeutic windows during disease progression. MDPI 2021-11-23 /pmc/articles/PMC8699769/ /pubmed/34943776 http://dx.doi.org/10.3390/cells10123268 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Iborra-Egea, Oriol
Gálvez-Montón, Carolina
Prat-Vidal, Cristina
Roura, Santiago
Soler-Botija, Carolina
Revuelta-López, Elena
Ferrer-Curriu, Gemma
Segú-Vergés, Cristina
Mellado-Bergillos, Araceli
Gomez-Puchades, Pol
Gastelurrutia, Paloma
Bayes-Genis, Antoni
Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
title Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
title_full Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
title_fullStr Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
title_full_unstemmed Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
title_short Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
title_sort deep learning analyses to delineate the molecular remodeling process after myocardial infarction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699769/
https://www.ncbi.nlm.nih.gov/pubmed/34943776
http://dx.doi.org/10.3390/cells10123268
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