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pmid:41063917
401-Gene Signature of Myocardial Dysfunction in Human Heart Failure: A Transcriptomic Analysis.
Kiki J Estes-Schmalzl · Amy J Marcano-Reik · Kristin M Lefebvre
Cureus · 2025 doi:10.7759/cureus.91745
Paper
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Experiment
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Analysis
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Complete file
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Transcriptomic analysis offers powerful tools to identify disease-specific gene expression signatures and potential therapeutic targets. Methods We analyzed publicly available gene expression data from the Gene Expression Omnibus (GEO) dataset GSE57345, comprising 313 left ventricular tissue samples (295 controls, 18 heart failure) profiled using Affymetrix Human Gene 1.1 ST Arrays (Thermo Fisher Scientific, Waltham, Massachusetts, United States). Differential expression analysis was performed using limma with Benjamini-Hochberg multiple testing correction. Results We identified 401 significantly differentially expressed genes (adjusted p<0.05) between heart failure and control samples. The molecular signature showed balanced dysregulation with 198 genes upregulated and 203 genes downregulated in heart failure. Pathway analysis revealed significant enrichment in mitochondrial dysfunction, immune activation, and extracellular matrix remodeling pathways. Top dysregulated genes included AIDC1, SECA1, PVRL2, PLD1, and KTR3CL3, with high statistical significance (p<1×10⁻⁶) despite modest fold changes characteristic of complex disease pathophysiology. Cross-validation with established heart failure signatures showed significant overlap (31.7% concordance), confirming biological relevance. Conclusions This 401-gene transcriptomic signature provides insights into heart failure molecular mechanisms and represents a potential resource for biomarker development and therapeutic target identification. The balanced pattern of gene dysregulation reflects the comprehensive transcriptional remodeling underlying cardiac dysfunction and supports precision medicine approaches for heart failure diagnosis and treatment stratification.", "claims": [{"id": "claim-method", "statement": "Differential expression analysis was performed using the limma package (version 3.54.0) [18] in R statistical software version 4.5.0 (R Foundation for Statistical Computing, Vienna, Austria) [19].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41063917", "locator": "sections[2] \"Materials and methods\" paragraph 8", "quote": "Differential expression analysis was performed using the limma package (version 3.54.0) [18] in R statistical software version 4.5.0 (R Foundation for Statistical Computing, Vienna, Austria) [19]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Primary data are publicly accessible through the GEO dataset GSE57345 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57345). 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