ArticleAmerican journal of translational research2023
Investigating possible dilated cardiomyopathy targets via bioinformatic analysis.
Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- An integrated cell atlas of 2.4 million cardiac cells across 209 individuals in health and disease.Nature cardiovascular research · 2026Article
- A new KLF13 loss-of-function mutation responsible for sporadic dilated cardiomyopathy.Molecular biology reports · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dilated cardiomyopathy (DCM) is the most common cardiomyopathy associated with heart failure; however, the underlying mechanism remains unclear. Initially, gene expression data of patients with DCM from the GSE4172 and GSE21610 datasets were obtained from the Gene Expression Omnibus website. Differentially expressed genes (DEGs) were analyzed with a false discovery rate < 0.05 and log2 fold change > 1.2. Furthermore, both the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA) were used to investigate the functional annotations. STRING and Cytoscape tools were used to form the protein-protein interaction (PPI) network and authenticate hub genes. Thereafter, the signature of immune-related genes (IRGs) was selected from the DEGs and data via the IMMPORT website. Hub genes were selected from the differentially expressed IRGs that formed the PPI network. Finally, the receiver-operating characteristic curves of the key genes were measured as biomarkers of DCM. A total of 173 independent DEGs (103 upregulated and 70 downregulated genes) were found in the microarray datasets GSE4172 and GSE21610. KEGG analysis and GSEA indicated that the BMP signaling pathway and apoptosis-related signals have a key effect on DCM development. The 10 hub genes also indicated the key effect of the BMP signaling pathway on DCM. A total of 224 differentially expressed IRGs and 20 featured IRGs were identified. Finally,
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Registered trials
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