Dataset Information

Integrated analysis of differentially expressed genes and miRNA expression profiles in dilated cardiomyopathy.

ABSTRACT:

Background

Although dilated cardiomyopathy (DCM) is a prevalent form of cardiomyopathy, the molecular mechanisms underlying its pathogenesis and progression remain poorly understood. It is possible to identify and validate DCM-associated genes, pathways, and miRNAs using bioinformatics analysis coupled with clinical validation methods.

Methods

Our analysis was performed using 3 mRNA datasets and 1 miRNA database. We employed several approaches, including gene ontology (GO) analysis, KEGG pathway enrichment analysis, protein-protein interaction networks analysis, and analysis of hub genes to identify critical genes and pathways linked to DCM. We constructed a regulatory network for DCM that involves interactions between miRNAs and mRNAs. We also validated the differently expressed miRNAs in clinical samples (87 DCM ，83 Normal) using qRT-PCR.The miRNAs' clinical value was evaluated by receiver operating characteristic curves (ROCs).

Results

78 differentially expressed genes (DEGs) and 170 differentially expressed miRNAs (DEMs) were associated with DCM. The top five GO annotations were collagen-containing extracellular matrix, cell substrate adhesion, negative regulation of cell differentiation, and inflammatory response. The most enriched KEGG pathways were the Neurotrophin signaling pathway, Thyroid hormone signaling pathway, Wnt signaling pathway, and Axon guidance. In the PPI network, we identified 10 hub genes, and in the miRNA-mRNA regulatory network, we identified 8 hub genes and 15 miRNAs. In the clinical validation, we found 13 miRNAs with an AUC value greater than 0.9.

Conclusion

Our research offers novel insights into the underlying mechanisms of DCM and has implications for identifying potential targets for diagnosis and treatment of this condition.

SUBMITTER: Chen Y

PROVIDER: S-EPMC10878877 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated analysis of differentially expressed genes and miRNA expression profiles in dilated cardiomyopathy.

Chen Yu Y Cai Wen-Ke WK Yu Jie J Shen Ming M Zhou Jin-Huan JH Yang Sheng-Yu SY Liu Wei W Lu Si S Shi Yan-Kun YK Yang Li-Xia LX

Heliyon 20240212 4

<h4>Background</h4>Although dilated cardiomyopathy (DCM) is a prevalent form of cardiomyopathy, the molecular mechanisms underlying its pathogenesis and progression remain poorly understood. It is possible to identify and validate DCM-associated genes, pathways, and miRNAs using bioinformatics analysis coupled with clinical validation methods.<h4>Methods</h4>Our analysis was performed using 3 mRNA datasets and 1 miRNA database. We employed several approaches, including gene ontology (GO) analysi ...[more]

PMID: 38384527

Similar Datasets

Project description:ObjectiveWound healing is a complex process involving the coordinated interaction of various genes and molecularpathways. The study aimed to uncover novel therapeutic targets, biomarkers and candidate genes for drug developmentto improve successful wound repair interventions.Materials and Methods: This study is a network-meta analysis study. Nine wound healing microarray datasets obtainedfrom the Gene Expression Omnibus (GEO) database were used for this study. Differentially expressed genes (DEGs)were described using the Limma package and shared genes were used as input for weighted gene co-expressionnetwork analysis. The Gene Ontology analysis was performed using the EnrichR web server, and construction of aprotein-protein interaction (PPI) network was achieved by the STRING and Cytoscape.Results: A total of 424 DEGs were determined. A co-expression network was constructed using 7692 shared genesbetween nine data sets, resulting in the identification of seven modules. Among these modules, those with the top 20genes of up and down-regulation were selected. The top down-regulated genes, including TJP1, SEC61A1, PLEK,ATP5B, PDIA6, PIK3R1, SRGN, SDC2, and RBBP7, and the top up-regulated genes including RPS27A, EEF1A1,HNRNPA1, CTNNB1, POLR2A, CFL1, CSNk1E, HSPD1, FN1, and AURKB, which can potentially serve as therapeutictargets were identified. The KEGG pathway analysis found that the majority of the genes are enriched in the "Wntsignaling pathway".Conclusion: In our study of nine wound healing microarray datasets, we identified DEGs and co-expressed modulesusing WGCNA. These genes are involved in important cellular processes such as transcription, translation, and posttranslationalmodifications. We found nine down-regulated genes and ten up-regulated genes, which could serve aspotential therapeutic targets for further experimental validation. Targeting pathways related to protein synthesis and celladhesion and migration may enhance wound healing, but additional experimental validation is needed to confirm theeffectiveness and safety of targeted interventions.

Dataset Information

Integrated analysis of differentially expressed genes and miRNA expression profiles in dilated cardiomyopathy.

Background

Methods

Results

Conclusion

Publications

Integrated analysis of differentially expressed genes and miRNA expression profiles in dilated cardiomyopathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets