Similar Datasets
Project description:Diabetic cardiomyopathy (DCM), a common complication of diabetes, is defined as ventricular dysfunction in the absence of underlying heart disease. Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), play a crucial role in the development of DCM. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key modules in DCM-related pathways. DCM-related miRNA-mRNA network and DCM-related ceRNA network were constructed by miRNA-seq to identify hub genes in these modules. We identified five hub genes that are associated with the onset of DCM, including Troponin C1 (Tnnc1), Phospholamban (Pln), Fatty acid binding proteins 3 (Fabp3), Popeye domain containing 2 (Popdc2), and Tripartite Motif-containing Protein 63 (Trim63). miRNAs that target the hub genes were mainly involved in TGF-β and Wnt signaling pathways. GO BP enrichment analysis found these miRNAs were involved in the signaling of TGF-β and glucose homeostasis. Q-PCR results found the gene expressions of Pln, Fabp3, Trim63, Tnnc1, and Popdc2 were significantly increased in DCM. Our study identified five hub genes (Tnnc1, Pln, Fabp3, Popdc2, Trim63) whose associated ceRNA networks are responsible for the onset of DCM.
| S-EPMC10290640 | biostudies-literature
Project description:To explore the unique pathogenesis of DCM and analyzed the differences in gene expression, associated pathways and immune cell infiltration among different organs that are targeted by high glucose by bioinformatics-based strategy. In order to find the specific factors that trigger DCM, we contrasted the gene profile of DCM to that of other diabetic diseases including diabetic peripheral neuropathy (DPN) and nephropathy (DN). we performed RNA-seq and miRNA sequencing on heart tissue from db/db mice to explore the transcriptome alterations in DCM pathogenesis including lncRNA, miRNA and mRNA.
2023-05-10 | GSE211106 | GEO
Project description:To explore the unique pathogenesis of DCM and analyzed the differences in gene expression, associated pathways and immune cell infiltration among different organs that are targeted by high glucose by bioinformatics-based strategy. In order to find the specific factors that trigger DCM, we contrasted the gene profile of DCM to that of other diabetic diseases including diabetic peripheral neuropathy (DPN) and nephropathy (DN). we performed RNA-seq and miRNA sequencing on heart tissue from db/db mice to explore the transcriptome alterations in DCM pathogenesis including lncRNA, miRNA and mRNA.
2023-05-10 | GSE211107 | GEO
Project description:Identification of Hub Genes and Potential ceRNA Networks of Diabetic Cardiomyopathy
| PRJNA868932 | ENA
Project description:Identification of Hub Genes and Potential ceRNA Networks of Diabetic Cardiomyopathy [RNA-seq]
| PRJNA868933 | ENA
Project description:Identification of Hub Genes and Potential ceRNA Networks of Diabetic Cardiomyopathy [miRNA-seq]
| PRJNA868934 | ENA
Project description:Diabetic nephropathy (DN) is one of the most common microvascular complications in diabetic patients, and is the main cause of end-stage renal disease. The exact molecular mechanism of DN is not fully understood. The aim of this study was to identify novel biomarkers and mechanisms for DN disease progression by weighted gene co-expression network analysis (WGCNA). From the GSE142153 dataset based on the peripheral blood monouclear cells (PBMC) of DN, we identified 234 genes through WGCNA and differential expression analysis. Gene Ontology (GO) annotations mainly included inflammatory response, leukocyte cell-cell adhesion, and positive regulation of proteolysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways mostly included IL-17 signaling pathway, MAPK signaling pathway, and PPAR signaling pathway in DN. A total of four hub genes (IL6, CXCL8, MMP9 and ATF3) were identified by cytoscape, and the relative expression levels of hub genes were also confirmed by RT-qPCR. ROC curve analysis determined that the expression of the four genes could distinguish DN from controls (the area under the curve is all greater than 0.8), and Pearson correlation coefficient analysis suggested that the expression of the four genes was related to estimated glomerular filtration rate (eGFR) of DN. Finally, through database prediction and literature screening, we constructed lncRNA-miRNA-mRNA network. We propose that NEAT1/XIST/KCNQ1T1-let-7b-5p-IL6, NEAT1/XIST-miR-93-5p-CXCL8 and NEAT1/XIST/KCNQ1T1-miR-27a-3p/miR-16-5p-ATF3 might be potential RNA regulatory pathways to regulate the disease progression of early DN. In conclusion, we identified four hub genes, namely, IL6, CXCL8, MMP9, and ATF3, as markers for early diagnosis of DN, and provided insight into the mechanisms of disease development in DN at the transcriptome level.
| S-EPMC8591079 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-10-23 | GSE89066 | GEO
Project description:BackgroundDiabetic retinopathy (DR) is characterized by a gradually progressive alteration in the retinal microvasculature that leads to middle-aged adult acquired persistent blindness. Limited research has been conducted on DR pathogenesis at the gene level. Thus, we aimed to reveal novel key genes that might be associated with DR formation via a bioinformatics analysis.MethodsThe GSE53257 dataset from the Gene Expression Omnibus was downloaded for gene co-expression analysis. We identified significant gene modules via the Weighted Gene Co-expression Network Analysis, which was conducted by the Protein-Protein Interaction (PPI) Network via Cytoscape and from this we screened for key genes and gene sets for particular functional and pathway-specific enrichments. The hub gene expression was verified by real-time PCR in DR rats modeling and an external database.ResultsTwo significant gene modules were identified. Significant key genes were predominantly associated with mitochondrial function, fatty acid oxidation and oxidative stress. Among all key genes analyzed, six up-regulated genes (i.e., SLC25A33, NDUFS1, MRPS23, CYB5R1, MECR, and MRPL15) were highly and significantly relevant in the context of DR formation. The PCR results showed that SLC25A33 and NDUFS1 expression were increased in DR rats modeling group.ConclusionGene co-expression network analysis highlights the importance of mitochondria and oxidative stress in the pathophysiology of DR. DR co-expressing gene module was constructed and key genes were identified, and both SLC25A33 and NDUFS1 may serve as potential biomarker and therapeutic target for DR.
| S-EPMC8445088 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is a malignant tumor originated from gastric mucosa epithelium. It is the third leading cause of cancer mortality in China. The early symptoms are not obvious. When it is discovered, it has developed to the advanced stage, and the prognosis is poor. In order to screen for potential genes for GC development, this study obtained GSE118916 and GSE109476 from the gene expression omnibus (GEO) database for bioinformatics analysis.MethodsFirst, GEO2R was used to identify differentially expressed genes (DEG) and the functional annotation of DEGs was performed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The Search Tool for the Retrieval of Interacting Genes (STRING) tool was used to construct protein-protein interaction (PPI) network and the most important modules and hub genes were mined. Real time quantitative polymerase chain reaction assay was performed to verify the expression level of hub genes.ResultsA total of 139 DEGs were identified. The functional changes of DEGs are mainly concentrated in the cytoskeleton, extracellular matrix and collagen synthesis. Eleven genes were identified as core genes. Bioinformatics analysis shows that the core genes are mainly enriched in many processes related to cell adhesion and collagen.ConclusionIn summary, the DEGs and hub genes found in this study may be potential diagnostic and therapeutic targets.
| S-EPMC9575828 | biostudies-literature