ArticleJournal of thoracic disease2023
Analysis of the role of glucose metabolism-related genes in dilated cardiomyopathy based on bioinformatics.
Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases.International journal of molecular sciences · 2024Pooled it
- BPGM shapes NFAT5-driven cellular responses.Cellular and molecular life sciences : CMLS · 2026Article
- Methylation-centric epigenetic regulation in dilated cardiomyopathy: mechanisms, metabolic interplay, and translational potential.Frontiers in cardiovascular medicine · 2026Review
- Identification of glycolysis-related genes and analysis of potential prognostic clinical application in oral squamous cell carcinoma.Translational cancer research · 2025Article
- Multi-Omic Analysis Reveals the Potential Anti-Disease Mechanism of Disease-Resistant Grass Carp.International journal of molecular sciences · 2025Article
- Methylations in dilated cardiomyopathy and heart failure.Frontiers in cardiovascular medicine · 2025Review
- Discovery of Glucose Metabolism-Associated Genes in Neuropathic Pain: Insights from Bioinformatics.International journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Dilated cardiomyopathy (DCM) is a prevalent condition with diverse etiologies, including viral infection, autoimmune response, and genetic factors. Despite the crucial role of energy metabolism in cardiac function, therapeutic targets for key genes in DCM's energy metabolism remain scarce. Methods: Our study employed the GSE79962 and GSE42955 datasets from the Gene Expression Omnibus (GEO) database for myocardial tissue sample collection and target gene identification via differential gene expression screening. Using various R packages, GSEA software, and the STRING database, we conducted data analysis, gene set enrichment, and protein-protein interaction predictions. The least absolute shrinkage and selection operator (LASSO) and Support Vector Machine (SVM) algorithms aided in feature gene selection, while the predictive model's efficiency was evaluated via the receiver operating characteristic (ROC) curve analysis. We used the non-negative matrix factorization (NMF) method for molecular typing and the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm for predicting immune cell infiltration. Results: The Conclusions:
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.