ArticleESC heart failure2025
Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns.
Article in ESC heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Identification of MTURN as a trained immunity-related biomarker for heart failureFrontiers in immunology · 2026Article
- Multi-omics approach reveals CCND1, GABPA, HIF1A, and SOX6 as key regulators and prognostic markers in heart failure.Hereditas · 2025Article
- Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns.ESC heart failure · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
aimsHeart failure (HF) is an important public health problem worldwide, and programmed cell death (PCD) plays a crucial role in its pathologic process. This study aims to identify the hub genes associated with HF through PCD in order to better understand the pathogenesis of HF and improve its diagnosis and treatment. METHODS AND
resultsThe gene expression dataset of HF was obtained from the GEO database. Bioinformatics and machine learning algorithms were utilized to screen the HF key genes and PCD-related HF hub genes, and an HF diagnostic model was constructed on this. Functional enrichment analysis clarified the gene ontology and signalling pathways of HF. The immune infiltration analysis of HF was performed to explore the expression levels of immune cells in each hub gene. Through bioinformatics analysis, 95 HF key genes were obtained. Functional enrichment analysis showed that they were mainly involved in inflammation, immunomodulation and other mechanisms. DHRS11 and LRKK2 were identified as PCD-associated HF hub genes by machine learning algorithms. The hub genes were confirmed as significant biomarkers of HF in the training and validation datasets, and their constructed nomogram had effective diagnostic value. Immune infiltration analysis showed significant immune imbalance of T-cell populations, monocytes and macrophages M2 in HF.
conclusionsIn this study, DHRS11 and LRKK2 were identified as hub genes. HF diagnostic model construction and immune infiltration analyses were performed, which provided new ideas for the molecular mechanisms of HF development and treatment.
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