Abstract
Diabetic cardiomyopathy (DbCM) is one of the most common vascular complications of diabetes, and can cause heart failure and threaten the life of patients. The pathogenesis is complex, and key genes have not fully identified. In this study, bioinformatics analysis was used to predict DbCM-related gene targets. Published datasets from the NCBI Gene Expression Omnibus with accession numbers GSE62203 and GSE197850 were selected for analysis. Differentially expressed genes (DEGs) were identified by the online tool GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID online database. Protein–protein interaction network construction and hub gene identification were performed using STRING and Cytoscape. We used 30 mM and 1 μM hydrocortisone-stimulated AC16 cells as an in vitro model of diabetic cardiomyopathy. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression levels of hub genes. A total of 73 common DEGs were identified in both datasets, including 47 upregulated and 26 downregulated genes. GO and KEGG pathway enrichment analyses revealed that the DEGs were significantly enriched in metabolism, hypoxia response, apoptosis, cell proliferation regulation, and cytoplasmic and HIF signalling pathways. The top 10 hub genes were LDHA, PGK1, SLC2A1, ENO1, PFKFB3, EGLN1, MYC, PDK1, EGLN3 and BNIP3. In our in vitro study, we found that PGK1, SLC2A1, PFKFB3, EGLN1, MYC, EGLN3 and BNIP3 were upregulated, ENO1 was downregulated, and LDHA was unchanged. Except for PGK1 and ENO1, these hub genes have been previously reported to be involved in DbCM. In summary, we identified DEGs and hub genes and first reported PGK1 and ENO1 in DbCM, which may serve as potential candidate genes for DbCM targeted therapy.
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Data Availability
The open-access datasets are available through the following URL: GSE62203 (https://www.ncbi.nlm.nih.gov/gds/?term=GSE62203) and GSE197850. (https://www.ncbi.nlm.nih.gov/gds/?term=GSE197850). All data generated or analyzed during this study are available from the corresponding author on reasonable request.
Abbreviations
- DbCM:
-
Diabetic cardiomyopathy
- DEGs:
-
Differentially expressed genes
- GEO:
-
Gene Expression Omnibus
- GO:
-
Gene Ontology
- hi-PSCs:
-
Human induced pluripotent stem cells
- hiPSCs-CMs:
-
Human induced pluripotent stem cell-derived cardiomyocytes
- KEGG:
-
Kyoto Encyclopedia of Genes and Genomes
- PPI:
-
Protein–protein interaction
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This work was supported by National College Students' Innovative Entrepreneurial Training Plan Program (202210062018), CAMS Innovation Fund for Medical Sciences (CIFMS) (approval No. 2021-I2M-1–073, 2022-I2M-C&T-B-091), Tianjin Natural Science Foundation (approval No. 20JCZDJC00410, TJWJ2022MS001), Sansheng TCP Young Research Funding (approval No. 57) and National Natural Science Foundation of China (approval No. 82170217, 82070192, 81670171).
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Shuo An, Hongchen Bi and Xiaoli Luo wrote the main manuscript text. Caiying Zhu and Min Wang prepared Figs.1-7. All authors read and approved the final manuscript.
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An, S., Bi, H., Luo, X. et al. Identification of key genes of diabetic cardiomyopathy in hiPSCs-CMs based on bioinformatics analysis. Mol Cell Biochem (2024). https://doi.org/10.1007/s11010-023-04915-9
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DOI: https://doi.org/10.1007/s11010-023-04915-9