ArticleAnnals of translational medicine2022
Integrative bioinformatics analysis of potential therapeutic targets and immune infiltration characteristics in dilated cardiomyopathy.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
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- PHLDA1 is a shared diagnostic and key mediator of inflammatory fibrosis in heart and kidney.Frontiers in immunology · 2026Article
- Prostate cancer and metabolic syndrome: exploring shared signature genes through integrative analysis of bioinformatics and clinical data.Discover oncology · 2025Article
- Combining Bulk and Single Cell RNA-Sequencing Data to Identify Hub Genes of Fibroblasts in Dilated Cardiomyopathy.Journal of inflammation research · 2024Article
- Integration of machine learning to identify diagnostic genes in leukocytes for acute myocardial infarction patients.Journal of translational medicine · 2023Article
- Selection of key genes for dilated cardiomyopathy based on machine learning algorithms and assessment of diagnostic accuracy.Journal of thoracic disease · 2023Article
- Analysis of the role of glucose metabolism-related genes in dilated cardiomyopathy based on bioinformatics.Journal of thoracic disease · 2023Article
- Article
- Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis.Scientific reports · 2023Article
- Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Dilated cardiomyopathy (DCM) is currently the major cause of systolic heart failure. This study explored potential therapeutic targets and investigated the role of immune cell infiltration in DCM. Methods: Three DCM datasets (GSE3585, GSE9800, and GSE84796) from the Gene Expression Omnibus (GEO) database were merged into an integrated dataset, and batch effects were removed. Differentially expressed genes (DEGs) were screened and the associations between gene co-expression modules and clinical traits were assessed by weighted gene co-expression network analysis (WGCNA) in R software. Any DEGs from the integrated dataset overlapped with the significant module genes were defined as common genes (CGs). Enrichment analysis of the CGs was performed. The protein-protein interaction (PPI) network of the CGs was visualized and the hub gene was identified by using Cytoscape 3.8.2 software. The miRNA-transcription factor-mRNA (miRNA-TF-mRNA) network was constructed using Cytoscape to unveil the regulatory relationships in DCM. Finally, the CIBERSORT method (https://cibersort.stanford.edu/) was used to investigate immune cell infiltration in DCM. Results: A total of 53 DEGs were identified, and 5 gene co-expression modules were detected by WGCNA of the DCM and control group samples of cardiac tissue. Genes such as FRZB, ASPN, and PHLDA1 were significantly upregulated, whereas IDH2 and ENDOG were significantly downregulated. Functional enrichment analysis showed that CGs were mainly enriched in the extracellular matrix (ECM) signaling pathway. ASPN was the hub gene in the PPI network. The miRNA-TF-mRNA network revealed that FRZB and ASPN were targeted by paired related homeobox 2 (Prrx2). We also found that miR-129-5p could regulate ASPN, PHLDA1, and IDH2 simultaneously. The immune infiltration analysis revealed higher levels of M1 macrophages in DCM samples than in the control samples. Conclusions: In conclusion, we speculate that miR-129-5p might target ASPN in regulating DCM via the ECM signaling pathway. Macrophage infiltration may be involved in ECM remodeling and eventually lead to DCM.
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