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Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks
To explore potential biomarkers of acute myocardial infarction (AMI) in females by using bioinformatics analysis. In this study, we explored potential biomarkers of AMI in females using bioinformatics analysis. We screened a total of 186 differentially expressed genes from the Gene Expression Omnibu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10145720/ https://www.ncbi.nlm.nih.gov/pubmed/37115066 http://dx.doi.org/10.1097/MD.0000000000033634 |
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author | Jiao, Kun Su, Ping Feng, Yubao Li, Changqing |
author_facet | Jiao, Kun Su, Ping Feng, Yubao Li, Changqing |
author_sort | Jiao, Kun |
collection | PubMed |
description | To explore potential biomarkers of acute myocardial infarction (AMI) in females by using bioinformatics analysis. In this study, we explored potential biomarkers of AMI in females using bioinformatics analysis. We screened a total of 186 differentially expressed genes from the Gene Expression Omnibus. In the study, we found that weighted gene co-expression network analysis explored the co-expression network of genes and identified key modules. Simultaneously, we chose brown modules as key modules related to AMI. In this study, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that genes in the brown module were mainly enriched in “heparin” and ‘complementation and coagulation cascade. Based on the protein-protein interaction network, we identified S100A9, mitogen-activated protein kinase (MAPK) 3, MAPK1, MMP3, interleukin (IL)-17A, and HSP90AB1 as hub gene sets. Whereas, polymerase chain reaction results showed that S100A9, MAPK3, MAPK1, MMP3, IL-17A, and HSP90AB1 were highly expressed compared with the control group. The IL-17 signaling pathway associated with an inflammatory response may be a potential biomarker and target for the treatment of women with myocardial infarction. |
format | Online Article Text |
id | pubmed-10145720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-101457202023-04-29 Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks Jiao, Kun Su, Ping Feng, Yubao Li, Changqing Medicine (Baltimore) 7400 To explore potential biomarkers of acute myocardial infarction (AMI) in females by using bioinformatics analysis. In this study, we explored potential biomarkers of AMI in females using bioinformatics analysis. We screened a total of 186 differentially expressed genes from the Gene Expression Omnibus. In the study, we found that weighted gene co-expression network analysis explored the co-expression network of genes and identified key modules. Simultaneously, we chose brown modules as key modules related to AMI. In this study, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that genes in the brown module were mainly enriched in “heparin” and ‘complementation and coagulation cascade. Based on the protein-protein interaction network, we identified S100A9, mitogen-activated protein kinase (MAPK) 3, MAPK1, MMP3, interleukin (IL)-17A, and HSP90AB1 as hub gene sets. Whereas, polymerase chain reaction results showed that S100A9, MAPK3, MAPK1, MMP3, IL-17A, and HSP90AB1 were highly expressed compared with the control group. The IL-17 signaling pathway associated with an inflammatory response may be a potential biomarker and target for the treatment of women with myocardial infarction. Lippincott Williams & Wilkins 2023-04-25 /pmc/articles/PMC10145720/ /pubmed/37115066 http://dx.doi.org/10.1097/MD.0000000000033634 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | 7400 Jiao, Kun Su, Ping Feng, Yubao Li, Changqing Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
title | Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
title_full | Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
title_fullStr | Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
title_full_unstemmed | Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
title_short | Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
title_sort | bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks |
topic | 7400 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10145720/ https://www.ncbi.nlm.nih.gov/pubmed/37115066 http://dx.doi.org/10.1097/MD.0000000000033634 |
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