Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis
Background. Acute myocardial infarction (AMI) is a common disease with high morbidity and mortality around the world. The aim of this research was to determine the differentially expressed genes (DEGs), which may serve as potential therapeutic targets or new biomarkers in AMI. Methods. From the Gene...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Cardiovascular Therapeutics |
| Online Access: | http://dx.doi.org/10.1155/2019/8490707 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832563360429768704 |
|---|---|
| author | Da-Qiu Chen Xiang-Sheng Kong Xue-Bin Shen Mao-Zhi Huang Jian-Ping Zheng Jing Sun Shang-Hua Xu |
| author_facet | Da-Qiu Chen Xiang-Sheng Kong Xue-Bin Shen Mao-Zhi Huang Jian-Ping Zheng Jing Sun Shang-Hua Xu |
| author_sort | Da-Qiu Chen |
| collection | DOAJ |
| description | Background. Acute myocardial infarction (AMI) is a common disease with high morbidity and mortality around the world. The aim of this research was to determine the differentially expressed genes (DEGs), which may serve as potential therapeutic targets or new biomarkers in AMI. Methods. From the Gene Expression Omnibus (GEO) database, three gene expression profiles (GSE775, GSE19322, and GSE97494) were downloaded. To identify the DEGs, integrated bioinformatics analysis and robust rank aggregation (RRA) method were applied. These DEGs were performed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses by using Clusterprofiler package. In order to explore the correlation between these DEGs, the interaction network of protein-protein internet (PPI) was constructed using the STRING database. Utilizing the MCODE plug-in of Cytoscape, the module analysis was performed. Utilizing the cytoHubba plug-in, the hub genes were screened out. Results. 57 DEGs in total were identified, including 2 down- and 55 upregulated genes. These DEGs were mainly enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and so on. The module analysis filtered out 18 key genes, including Cxcl5, Arg1, Cxcl1, Spp1, Selp, Ptx3, Tnfaip6, Mmp8, Serpine1, Ptgs2, Il6, Il1r2, Il1b, Ccl3, Ccr1, Hmox1, Cxcl2, and Ccl2. Ccr1 was the most fundamental gene in PPI network. 4 hub genes in total were identified, including Cxcl1, Cxcl2, Cxcl5, and Mmp8. Conclusion. This study may provide credible molecular biomarkers in terms of screening, diagnosis, and prognosis for AMI. Meanwhile, it also serves as a basis for exploring new therapeutic target for AMI. |
| format | Article |
| id | doaj-art-61c94edeb1704d3e9760058361cd4a22 |
| institution | Kabale University |
| issn | 1755-5914 1755-5922 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Cardiovascular Therapeutics |
| spelling | doaj-art-61c94edeb1704d3e9760058361cd4a222025-02-03T01:20:18ZengWileyCardiovascular Therapeutics1755-59141755-59222019-01-01201910.1155/2019/84907078490707Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics AnalysisDa-Qiu Chen0Xiang-Sheng Kong1Xue-Bin Shen2Mao-Zhi Huang3Jian-Ping Zheng4Jing Sun5Shang-Hua Xu6Department of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaDepartment of Medical Laboratory Medicine, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaDepartment of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaDepartment of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaDepartment of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaDepartment of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaDepartment of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping 353000, Fujian Province, ChinaBackground. Acute myocardial infarction (AMI) is a common disease with high morbidity and mortality around the world. The aim of this research was to determine the differentially expressed genes (DEGs), which may serve as potential therapeutic targets or new biomarkers in AMI. Methods. From the Gene Expression Omnibus (GEO) database, three gene expression profiles (GSE775, GSE19322, and GSE97494) were downloaded. To identify the DEGs, integrated bioinformatics analysis and robust rank aggregation (RRA) method were applied. These DEGs were performed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses by using Clusterprofiler package. In order to explore the correlation between these DEGs, the interaction network of protein-protein internet (PPI) was constructed using the STRING database. Utilizing the MCODE plug-in of Cytoscape, the module analysis was performed. Utilizing the cytoHubba plug-in, the hub genes were screened out. Results. 57 DEGs in total were identified, including 2 down- and 55 upregulated genes. These DEGs were mainly enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and so on. The module analysis filtered out 18 key genes, including Cxcl5, Arg1, Cxcl1, Spp1, Selp, Ptx3, Tnfaip6, Mmp8, Serpine1, Ptgs2, Il6, Il1r2, Il1b, Ccl3, Ccr1, Hmox1, Cxcl2, and Ccl2. Ccr1 was the most fundamental gene in PPI network. 4 hub genes in total were identified, including Cxcl1, Cxcl2, Cxcl5, and Mmp8. Conclusion. This study may provide credible molecular biomarkers in terms of screening, diagnosis, and prognosis for AMI. Meanwhile, it also serves as a basis for exploring new therapeutic target for AMI.http://dx.doi.org/10.1155/2019/8490707 |
| spellingShingle | Da-Qiu Chen Xiang-Sheng Kong Xue-Bin Shen Mao-Zhi Huang Jian-Ping Zheng Jing Sun Shang-Hua Xu Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis Cardiovascular Therapeutics |
| title | Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis |
| title_full | Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis |
| title_fullStr | Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis |
| title_full_unstemmed | Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis |
| title_short | Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis |
| title_sort | identification of differentially expressed genes and signaling pathways in acute myocardial infarction based on integrated bioinformatics analysis |
| url | http://dx.doi.org/10.1155/2019/8490707 |
| work_keys_str_mv | AT daqiuchen identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis AT xiangshengkong identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis AT xuebinshen identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis AT maozhihuang identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis AT jianpingzheng identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis AT jingsun identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis AT shanghuaxu identificationofdifferentiallyexpressedgenesandsignalingpathwaysinacutemyocardialinfarctionbasedonintegratedbioinformaticsanalysis |