99b04072783c37bcb9b1a978a881029c pmc_34943776.pdf 29bd14182ffc1793c3f4198921220711460386c4 pmc_34943776.pdf 6ec6c1514623003c0c490165752270337b78e6d31204e823fe131350c0bed706 pmc_34943776.pdf Title: Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction Subject: 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. Keywords: myocardial infarction; deep learning; gene regulation; transcriptomics Author: Oriol Iborra-Egea, Carolina Gálvez-Montón, Cristina Prat-Vidal, Santiago Roura, Carolina Soler-Botija, Elena Revuelta-López, Gemma Ferrer-Curriu, Cristina Segú-Vergés, Araceli Mellado-Bergillos, Pol Gomez-Puchades, Paloma Gastelurrutia and Antoni Bayes-Genis Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Mon Dec 6 11:41:33 2021 CET ModDate: Mon Dec 6 11:47:41 2021 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 19 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 6068719 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- AWWFCC+VnURWPalladioL Type 1 Custom yes yes no 10 0 DWIUZN+URWPalladioL-Ital Type 1 Custom yes yes no 15 0 IIHQHH+URWPalladioL-Bold Type 1 Custom yes yes no 20 0 BFRTZN+URWPalladioL-Roma 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FOCCHM+PalatinoLinotype-Roman TrueType WinAnsi yes yes no 411 0 CKBPVA+EURM10 Type 1 Builtin yes yes no 427 0 Jhove (Rel. 1.22.1, 2019-04-17) Date: 2022-03-22 02:27:33 CET RepresentationInformation: pmc_34943776.pdf ReportingModule: PDF-hul, Rel. 1.12.1 (2019-04-17) LastModified: 2022-01-11 05:04:22 CET Size: 6068719 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 564 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7b69c6ba Item: Title: Materials and Methods Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Children: Item: Title: Myocardial Infarction Model Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Item: Title: Tissue Collection and RNA Extraction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Item: Title: Microarray Gene Expression Analysis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Compilation of Transcriptomic Data Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Item: Title: Molecular Characterization of Pathology Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Item: Title: Therapeutic Performance Mapping System (TPMS) Generation of Mathematical Models Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@50d0686 Item: Title: Analyzing and Solving the Mathematical Models Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7a3d45bd Item: Title: Biomarker Identification Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1e7c7811 Item: Title: Generating A Molecular Model of Cardiac Remodeling Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@77ec78b9 Item: Title: Data Integration Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1a3869f4 Item: Title: Results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@a38d7a3 Children: Item: Title: High-Dimensional Data Integration of Microarray Gene Expression during 6 Weeks of MI Progression Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@77f99a05 Item: Title: Time-Dependent Identification of MI-Derived Biomarkers Strongly Related to Cardiac Remodeling Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@63440df3 Item: Title: Description of the Molecular Mechanistic Relationships Defining MI Evolution Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@3aeaafa6 Item: Title: Identification of Key Proteins Driving Post-MI Alterations Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@76a3e297 Item: Title: Unraveling the Molecular Mechanism of Action Relating the Source Proteins to Cardiac Remodeling Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4d3167f4 Item: Title: Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@ed9d034 Item: Title: Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@6121c9d6 Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@87f383f Info: Title: Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction Author: Oriol Iborra-Egea, Carolina Gálvez-Montón, Cristina Prat-Vidal, Santiago Roura, Carolina Soler-Botija, Elena Revuelta-López, Gemma Ferrer-Curriu, Cristina Segú-Vergés, Araceli Mellado-Bergillos, Pol Gomez-Puchades, Paloma Gastelurrutia and Antoni Bayes-Genis Subject: 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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