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Title: Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
Author: Iborra Egea, Oriol
Gálvez Montón, Carolina
Prat Vidal, Cristina
Roura, Santiago
Soler Botija, Carolina
Revuelta López, Elena
Ferrer Corriu, Gemma
Segú Vergés, Cristina
Mellado Bergillos, Araceli
Gómez Puchades, Pol
Gastelurrutia, Paloma
Bayés Genís, Antoni
Keywords: Infart de miocardi
Aprenentatge automàtic
Myocardial infarction
Machine learning
Issue Date: 23-Nov-2021
Publisher: MDPI AG
Abstract: 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.
Note: Reproducció del document publicat a:
It is part of: Cells, 2021, vol. 10, num. 12
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ISSN: 2073-4409
Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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