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Dilated cardiomyopathy (DCM) is one of the most common causes of sudden cardiac arrest and ranks as the second most frequent cause of heart failure. The objective of this study was to identify potential biomarkers and explore the underlying mechanisms involved in DCM, using various bioinformatics approaches. The GSE3585 microarray datachip from GEO omnibus database was analyzed using the Limma function in RStudio and identified 101 differentially expressed genes (DEGs). The results showed 68 up-regulated and 33 down-regulated DEGs. All DEGs were functionally enriched and pathway analyzed using DAVID and Metascape. The PPI network was created in STRING and visualized in Cytoscape. Hub genes were retrieved using CytoHUBBA plug-in, and GeneMANIA determined their roles and co-expressed genes. From 101 DEGs, 10 were hub genes: STAT3, HSP90AB1, SMAD7, CCN2, H2AZ1, H1–0, SMAD6, EEF1A1, HMGN2, XPO1. STAT3, SMAD6, SMAD7, HSP90AB1, and CTGF play complex molecular roles in TGF-β signalling, cardiac fibrosis advancement, heart response to high oxidative stress, and cardiac muscle contraction weakness. Histone genes H1–0, H2AZ1 and non-histone gene HMGN2 play a role in epigenetic modelling of gene expression. EEF1A1 is expressed in the heart, although its effect on DCM pathophysiology is unknown. XPO1 mediates nucleocytoplasmic transport and affects DCM cardiac remodeling. Despite valuable insights, this study has limitations. The microarray data, sourced from a public database, has a small sample size, and experimental validation is needed to confirm the obtained results. These findings may lead to therapeutic biomarkers and a deeper understanding of DCM pathophysiology.

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Identification of Potential Biomarkers and Pathways in Dilated Cardiomyopathy Using Bioinformatics Analysis

  • 会议论文

  • 发表日期：

    2025年

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  • Tamara Mladenović,
  • Sanja Matić,
  • Jelena Pavić,
  • Katarina Virijević,
  • Nenad Filipović

摘要

Dilated cardiomyopathy (DCM) is one of the most common causes of sudden cardiac arrest and ranks as the second most frequent cause of heart failure. The objective of this study was to identify potential biomarkers and explore the underlying mechanisms involved in DCM, using various bioinformatics approaches. The GSE3585 microarray datachip from GEO omnibus database was analyzed using the Limma function in RStudio and identified 101 differentially expressed genes (DEGs). The results showed 68 up-regulated and 33 down-regulated DEGs. All DEGs were functionally enriched and pathway analyzed using DAVID and Metascape. The PPI network was created in STRING and visualized in Cytoscape. Hub genes were retrieved using CytoHUBBA plug-in, and GeneMANIA determined their roles and co-expressed genes. From 101 DEGs, 10 were hub genes: STAT3, HSP90AB1, SMAD7, CCN2, H2AZ1, H1–0, SMAD6, EEF1A1, HMGN2, XPO1. STAT3, SMAD6, SMAD7, HSP90AB1, and CTGF play complex molecular roles in TGF-β signalling, cardiac fibrosis advancement, heart response to high oxidative stress, and cardiac muscle contraction weakness. Histone genes H1–0, H2AZ1 and non-histone gene HMGN2 play a role in epigenetic modelling of gene expression. EEF1A1 is expressed in the heart, although its effect on DCM pathophysiology is unknown. XPO1 mediates nucleocytoplasmic transport and affects DCM cardiac remodeling. Despite valuable insights, this study has limitations. The microarray data, sourced from a public database, has a small sample size, and experimental validation is needed to confirm the obtained results. These findings may lead to therapeutic biomarkers and a deeper understanding of DCM pathophysiology.