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Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction
Oriol Iborra-Egea1, Carolina Gálvez-Montón1,2, Cristina Prat-Vidal1,2
1ICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, Spain.
Cells
|December 24, 2021
Summary
This study maps the molecular changes after myocardial infarction (MI) using machine learning. It identifies key genes and pathways involved in heart remodeling, offering potential therapeutic targets and windows for intervention.
Area of Science:
- Cardiovascular Biology
- Molecular Medicine
- Systems Biology
Background:
- Pathological remodeling after myocardial infarction (MI) involves complex molecular changes.
- A comprehensive understanding of the entire molecular evolution post-MI is currently lacking.
Purpose of the Study:
- To comprehensively map the molecular evolution during post-myocardial infarction (MI) pathological remodeling.
- To identify key genes, pathways, and therapeutic targets involved in adverse cardiac remodeling.
- To establish potential therapeutic windows during MI progression.
Main Methods:
- Generated microarray data from swine heart biopsies at multiple time points post-MI (baseline, 6, 30, 45 days).
- Utilized machine-learning algorithms to analyze transcriptomic data.
- Cross-validated findings with existing clinical and experimental data.
- Performed protein-triggering analysis to identify key mediating genes.
Main Results:
- MI progression involved regulation of adipogenesis, fatty acid metabolism, and epithelial-mesenchymal transition.
- Infarct core regions showed enrichment in muscle contraction and membrane depolarization processes.
- Angiogenesis was an early and sustained response, alongside recapitulation of embryogenic processes.
- Identified common pathways and modulators (IGF1R, RAF1, KPCA, JUN, PTN11) across different time points.
Conclusions:
- Delineated a structured and comprehensive molecular picture of cardiac remodeling post-MI.
- Identified novel potential biomarkers and therapeutic targets for MI.
- Established potential therapeutic windows during the progression of adverse remodeling.
