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Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification
BACKGROUND: Acute myocardial infarction (AMI) is one of the leading causes of death worldwide. The etiology of AMI is complex and has not been fully defined. In recent years, the role of immune response in the development, progression and prognosis of AMI has received increasing attention. The aim o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198157/ https://www.ncbi.nlm.nih.gov/pubmed/37214088 http://dx.doi.org/10.7717/peerj.15058 |
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author | Liu, Jian Chen, Lu Zheng, Xiang Guo, Caixia |
author_facet | Liu, Jian Chen, Lu Zheng, Xiang Guo, Caixia |
author_sort | Liu, Jian |
collection | PubMed |
description | BACKGROUND: Acute myocardial infarction (AMI) is one of the leading causes of death worldwide. The etiology of AMI is complex and has not been fully defined. In recent years, the role of immune response in the development, progression and prognosis of AMI has received increasing attention. The aim of this study was to identify key genes associated with the immune response in AMI and to analyze their immune infiltration. METHODS: The study included a total of two GEO databases, containing 83 patients with AMI and 54 healthy individuals. We used the linear model of microarray data (limma) package to find the differentially expressed genes associated with AMI, performing weighted gene co-expression analysis (WGCNA) to further identify the genes associated with inflammatory response to AMI. We found the final hub genes through the protein-protein interaction (PPI) network and least absolute shrinkage and selection operator (LASSO) regression model. To verify the above conclusions, we constructed mice AMI model, extracting myocardial tissue to perform qRT-PCR. Furthermore, the CIBERSORT tool for immune cells infiltration analysis was also carried out. RESULTS: A total of 5,425 significant up-regulated and 2,126 down-regulated genes were found in GSE66360 and GSE24519. A total of 116 immune-related genes in close association with AMI were screened by WGCNA analysis. These genes were mostly clustered in the immune response on the basis of GO and KEGG enrichment. With construction of PPI network and LASSO regression analysis, this research found three hub genes (SOCS2, FFAR2, MYO10) among these differentially expressed genes. The immune cell infiltration results revealed that significant differences could be found on T cells CD4 memory activated, Tregs (regulatory T cells), macrophages M2, neutrophils, T cells CD8, T cells CD4 naive, eosinophils between controls and AMI patients. |
format | Online Article Text |
id | pubmed-10198157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101981572023-05-20 Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification Liu, Jian Chen, Lu Zheng, Xiang Guo, Caixia PeerJ Bioinformatics BACKGROUND: Acute myocardial infarction (AMI) is one of the leading causes of death worldwide. The etiology of AMI is complex and has not been fully defined. In recent years, the role of immune response in the development, progression and prognosis of AMI has received increasing attention. The aim of this study was to identify key genes associated with the immune response in AMI and to analyze their immune infiltration. METHODS: The study included a total of two GEO databases, containing 83 patients with AMI and 54 healthy individuals. We used the linear model of microarray data (limma) package to find the differentially expressed genes associated with AMI, performing weighted gene co-expression analysis (WGCNA) to further identify the genes associated with inflammatory response to AMI. We found the final hub genes through the protein-protein interaction (PPI) network and least absolute shrinkage and selection operator (LASSO) regression model. To verify the above conclusions, we constructed mice AMI model, extracting myocardial tissue to perform qRT-PCR. Furthermore, the CIBERSORT tool for immune cells infiltration analysis was also carried out. RESULTS: A total of 5,425 significant up-regulated and 2,126 down-regulated genes were found in GSE66360 and GSE24519. A total of 116 immune-related genes in close association with AMI were screened by WGCNA analysis. These genes were mostly clustered in the immune response on the basis of GO and KEGG enrichment. With construction of PPI network and LASSO regression analysis, this research found three hub genes (SOCS2, FFAR2, MYO10) among these differentially expressed genes. The immune cell infiltration results revealed that significant differences could be found on T cells CD4 memory activated, Tregs (regulatory T cells), macrophages M2, neutrophils, T cells CD8, T cells CD4 naive, eosinophils between controls and AMI patients. PeerJ Inc. 2023-05-16 /pmc/articles/PMC10198157/ /pubmed/37214088 http://dx.doi.org/10.7717/peerj.15058 Text en ©2023 Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Liu, Jian Chen, Lu Zheng, Xiang Guo, Caixia Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
title | Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
title_full | Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
title_fullStr | Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
title_full_unstemmed | Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
title_short | Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
title_sort | identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198157/ https://www.ncbi.nlm.nih.gov/pubmed/37214088 http://dx.doi.org/10.7717/peerj.15058 |
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