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...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Cells |
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| Online Access: | https://www.mdpi.com/2073-4409/10/12/3268 |
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| 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 Antoni Bayes-Genis |
| author_facet | 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 Antoni Bayes-Genis |
| author_sort | Oriol Iborra-Egea |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T04:26:13Z |
| format | Article |
| id | doaj.art-d53d773785f54a7da75c6b9a1c5e0001 |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-10T04:26:13Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-d53d773785f54a7da75c6b9a1c5e00012023-11-23T07:35:27ZengMDPI AGCells2073-44092021-11-011012326810.3390/cells10123268Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial InfarctionOriol Iborra-Egea0Carolina Gálvez-Montón1Cristina Prat-Vidal2Santiago Roura3Carolina Soler-Botija4Elena Revuelta-López5Gemma Ferrer-Curriu6Cristina Segú-Vergés7Araceli Mellado-Bergillos8Pol Gomez-Puchades9Paloma Gastelurrutia10Antoni Bayes-Genis11ICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainAnaxomics Biotech S.L., Diputació 237 1r 1a, 08007 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainICREC Research Program, Health Sciences Research Institute Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Barcelona, SpainSpecific 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.https://www.mdpi.com/2073-4409/10/12/3268myocardial infarctiondeep learninggene regulationtranscriptomics |
| spellingShingle | 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 Antoni Bayes-Genis Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction Cells myocardial infarction deep learning gene regulation transcriptomics |
| 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 | myocardial infarction deep learning gene regulation transcriptomics |
| url | https://www.mdpi.com/2073-4409/10/12/3268 |
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