Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI
Chan Li,1 Zhaoya Liu2 1Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Geriatrics, Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of ChinaCorrespondence: Zhaoya LiuThi...
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doaj-18fef39c21284d8f8f0b75958ffc6cb82021-08-10T20:07:10ZengDove Medical PressInternational Journal of General Medicine1178-70742021-08-01Volume 144337434767687Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MILi CLiu ZChan Li,1 Zhaoya Liu2 1Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Geriatrics, Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of ChinaCorrespondence: Zhaoya LiuThird Xiangya Hospital, Central South University, No. 138 Tongzipuo Road, Changsha, Hunan, 410013, People’s Republic of ChinaEmail liuzhaoya@csu.edu.cnBackground: Type 2 diabetes mellitus (T2DM), a major risk factor of coronary heart disease, is associated with an approximately twofold increase in the risk of myocardial infarction (MI). We studied co-expressed genes to demonstrate relationships between DM and MI and revealed the potential biomarkers and therapeutic targets of T2DM-related MI.Methods: DM and MI-related differentially expressed genes (DEGs) were identified by bioinformatic analysis, Gene Expression Omnibus (GEO) datasets GSE42148 and GSE61144 of MI patients, and the normal control and GSE26168 and GSE15932 of DM patients and normal controls, respectively. Further target prediction and network analysis method were used to detect protein-protein interaction (PPI) networks, gene ontology (GO) terms, and pathway enrichment of DEGs. Co-expressed DEGs of T2DM-related MI were analyzed as well.Results: We identified 210 upregulated and 127 downregulated DEGs in T2DM, as well as 264 upregulated and 242 downregulated DEGs in MI. Eighteen upregulated and four downregulated DEGs were identified as co-DEGs of T2DM and MI. Functional analysis revealed that T2DM-related DEGs were mostly enriched in the viral process and ubiquitin-mediated proteolysis, while MI-related DEGs were mostly enriched in protein phosphorylation and TNF signaling pathway. MPO, MMP9, CAMP, LTF, AZU1, DEFA4, STAT3, and PECAM1 were recognized as the hub genes of the co-DEGs with acceptable diagnostic values in T2DM and MI datasets. Adenosine receptor agonist IB-MECA was predicted to be a potential drug for T2DM-related MI with the highest CMap connectivity score.Conclusion: Our study identified that the co-DEGs of MPO, MMP9, CAMP, LTF, AZU1, DEFA4, STAT3, and PECAM1 are significantly associated with novel biomarkers involved in T2DM-related MI. However, more experimental research and clinical trials are demanded to verify our results.Keywords: myocardial infarction, diabetes mellitus, Gene Expression Omnibus, differentially expressed genes, protein-protein interactionhttps://www.dovepress.com/bioinformatic-analysis-for-potential-biomarkers-and-therapeutic-target-peer-reviewed-fulltext-article-IJGMmyocardial infarctiondiabetes mellitusgene expressed omnibusdifferentially expressed genesprotein-protein interaction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Li C Liu Z |
spellingShingle |
Li C Liu Z Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI International Journal of General Medicine myocardial infarction diabetes mellitus gene expressed omnibus differentially expressed genes protein-protein interaction |
author_facet |
Li C Liu Z |
author_sort |
Li C |
title |
Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI |
title_short |
Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI |
title_full |
Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI |
title_fullStr |
Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI |
title_full_unstemmed |
Bioinformatic Analysis for Potential Biomarkers and Therapeutic Targets of T2DM-related MI |
title_sort |
bioinformatic analysis for potential biomarkers and therapeutic targets of t2dm-related mi |
publisher |
Dove Medical Press |
series |
International Journal of General Medicine |
issn |
1178-7074 |
publishDate |
2021-08-01 |
description |
Chan Li,1 Zhaoya Liu2 1Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Geriatrics, Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of ChinaCorrespondence: Zhaoya LiuThird Xiangya Hospital, Central South University, No. 138 Tongzipuo Road, Changsha, Hunan, 410013, People’s Republic of ChinaEmail liuzhaoya@csu.edu.cnBackground: Type 2 diabetes mellitus (T2DM), a major risk factor of coronary heart disease, is associated with an approximately twofold increase in the risk of myocardial infarction (MI). We studied co-expressed genes to demonstrate relationships between DM and MI and revealed the potential biomarkers and therapeutic targets of T2DM-related MI.Methods: DM and MI-related differentially expressed genes (DEGs) were identified by bioinformatic analysis, Gene Expression Omnibus (GEO) datasets GSE42148 and GSE61144 of MI patients, and the normal control and GSE26168 and GSE15932 of DM patients and normal controls, respectively. Further target prediction and network analysis method were used to detect protein-protein interaction (PPI) networks, gene ontology (GO) terms, and pathway enrichment of DEGs. Co-expressed DEGs of T2DM-related MI were analyzed as well.Results: We identified 210 upregulated and 127 downregulated DEGs in T2DM, as well as 264 upregulated and 242 downregulated DEGs in MI. Eighteen upregulated and four downregulated DEGs were identified as co-DEGs of T2DM and MI. Functional analysis revealed that T2DM-related DEGs were mostly enriched in the viral process and ubiquitin-mediated proteolysis, while MI-related DEGs were mostly enriched in protein phosphorylation and TNF signaling pathway. MPO, MMP9, CAMP, LTF, AZU1, DEFA4, STAT3, and PECAM1 were recognized as the hub genes of the co-DEGs with acceptable diagnostic values in T2DM and MI datasets. Adenosine receptor agonist IB-MECA was predicted to be a potential drug for T2DM-related MI with the highest CMap connectivity score.Conclusion: Our study identified that the co-DEGs of MPO, MMP9, CAMP, LTF, AZU1, DEFA4, STAT3, and PECAM1 are significantly associated with novel biomarkers involved in T2DM-related MI. However, more experimental research and clinical trials are demanded to verify our results.Keywords: myocardial infarction, diabetes mellitus, Gene Expression Omnibus, differentially expressed genes, protein-protein interaction |
topic |
myocardial infarction diabetes mellitus gene expressed omnibus differentially expressed genes protein-protein interaction |
url |
https://www.dovepress.com/bioinformatic-analysis-for-potential-biomarkers-and-therapeutic-target-peer-reviewed-fulltext-article-IJGM |
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