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Jing Cao,1,* Zhaoya Liu,2,* Jie Liu,3 Chan Li,3 Guogang Zhang,1 Ruizheng Shi3 1Department of Cardiovascular Medicine, Third 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 China; 3Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ruizheng ShiDepartment of Cardiovascular Medicine, Xiangya Hospital, Central South University, Xiangya Road, Changsha, 410008, Hunan, People’s Republic of ChinaEmail xyshiruizheng@csu.edu.cnPurpose: Ischemic cardiomyopathy (ICM) is considered to be the most common cause of heart failure, with high prevalence and mortality. This study aimed to investigate the different expressed genes (DEGs) and pathways in the pathogenesis of ICM using bioinformatics analysis.Methods: The control and ICM datasets GSE116250, GSE46224 and GSE5406 were collected from the gene expression omnibus (GEO) database. DEGs were identified using limma package of R software, and co-expressed genes were identified using Venn diagrams. Then, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore the biological functions and signaling pathways. Protein–protein interaction (PPI) networks were assembled with Cytoscape software to identify hub genes related to the pathogenesis of ICM. RT-PCR of Heart tissues (n=2 for non-failing controls and n=4 for ischemic cardiomyopathy patients) was used to validate the bioinformatic results.Results: A total of 844 DEGs were screened from GSE116250, of which 447 were up-regulated genes and 397 were down-regulated genes, respectively. A total of 99 DEGs were singled out from GSE46224, of which 58 were up-regulated genes and 41 were down-regulate

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