ArticleGenes2025
Identification of Metabolism-Related Hub Genes in Heart Failure via Comprehensive Transcriptome Analysis.
Article in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Innovative Advances in Non-Invasive Detection Technologies for Heart Failure: Synergistic Application of Multimodal Sensing and Intelligent Algorithms.Reviews in cardiovascular medicine · 2026Review
- Toxicological investigation of mycotoxin contaminants and antibiotic residues associated with the poultry industry and their impact on human health.RSC advances · 2026Article
- Revealing the Diagnostic Potential of Three RHO GTPase-Related Genes in Osteoarthritis Based on Single-Cell RNA Sequencing and GEO Dataset Analysis.International journal of genomics · 2026Article
- Multi-omics approach reveals CCND1, GABPA, HIF1A, and SOX6 as key regulators and prognostic markers in heart failure.Hereditas · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundMetabolic dysfunction is a key driver of heart failure (HF) progression. Identifying metabolic hub genes in HF may reveal novel therapeutic targets.
methodsTranscriptomic datasets from HF patients (GEO database) and metabolism-related genes (PathCards) were analyzed. Differentially expressed genes (DEGs) were intersected with metabolism-related genes, followed by the application of the LASSO, Random Forest, and XGBoost algorithms to prioritize hub genes. Candidate genes were validated via WGCNA, an HF mouse model, and plasma metabolomics. Diagnostic performance and metabolic associations were assessed using ROC analysis and ssGSEA.
resultsWe identified 1115 HF-associated DEGs (701 upregulated, 414 downregulated), with 119 linked to metabolism. The machine learning algorithms prioritized five genes, including
conclusionsSDC2 emerges as a central regulator bridging metabolic dysfunction and HF pathogenesis, showing potential as a diagnostic biomarker and therapeutic target.
Indexed as
Identifiers
What OpenQuestion holds
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.