Identification of key genes of diabetic cardiomyopathy in hiPSCs-CMs based on bioinformatics analysis

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 repor...
Source: Molecular and Cellular Biochemistry - Category: Biochemistry Authors: Source Type: research