bioRxivBioinformaticsPreprint
Identification of senescence-related hub genes and potential therapeutic agents for chronic heart failure
Hao XieiD, Zuyuan You, Bin LiaoiD, Juyi WaniD, Mingbin DengiD, Qi YangiD
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Abstract
BackgroundChronic heart failure (CHF), the terminal phase of cardiovascular disease progression, has emerged as an increasingly severe global public health concern. Despite current therapeutic approaches aimed at symptom relief, their long-term effectiveness remains limited, urgently necessitating the exploration of novel treatment strategies. This study endeavored to explore the role of cellular senescence in CHF, identify the characteristic genes linked to cellular senescence, and predict potential therapeutic agents. MethodsWe acquired CHF-related datasets from the Gene Expression Omnibus database and cell senescence-related genes from the CellAge database to identify differentially expressed cell senescence-related genes. We then conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to elucidate the functions of these differentially expressed genes, constructed a protein-protein interaction network, and screened hub genes. Using receiver operating curve (ROC) analysis, we developed a diagnostic model based on these hub genes. Furthermore, we constructed networks for the hub genes involving miRNAs, lncRNAs, transcription factors, and drugs. Subsequently, we explored the potential mechanism of action of metformin in the treatment of CHF through molecular docking studies. Lastly, we verified the expression of the hub genes in a doxorubicin-induced CHF model in rats. Results We ultimately identified nine hub genes associated with cellular senescence: STAT1, MMP9, MAP2K1, SOCS1, SDC1, MET, EIF4EBP1, ATF3, and NAMPT. These genes exhibited significant differential expression between CHF and normal tissues. The constructed diagnostic model demonstrated robust diagnostic performance in ROC curve analysis, with an area under the curve exceeding 0.7, thereby providing biomarker support for early CHF diagnosis. Furthermore, we identified a regulatory network comprising 94 lncRNAs, 63 miRNAs, and 11 transcription factors and screened 42 potential therapeutic drugs. Subsequent molecular docking simulations revealed that metformin could effectively bind to the hub genes. Finally, we validated the expression of some hub genes in a rodent CHF model, in which gene expression regulation varied across diverse experimental settings. ConclusionsOur research identified nine genes cellular senescence-related genes with potential roles in CHF pathogenesis, offering fresh perspectives concerning the diagnosis and treatment of CHF.
- organism: rat
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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