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Investigating the Pathogenesis of MYH7 Mutation Gly823Glu in Familial Hypertrophic Cardiomyopathy using a Mouse Model
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Unveiling CTGF and APOA1: key hub genes and therapeutic targets in dilated cardiomyopathy

Ran Wang1, Jinmeng Chen2, Jian Zhu3

  • 1Department of Emergency Internal Medicine, The First Affiliated Hospital of Bengbu Medical University, Bengbu, 233000, China.

Journal of Cardiothoracic Surgery
|May 29, 2026
PubMed

Insights

This study identifies CTGF and APOA1 as potential biomarkers for dilated cardiomyopathy (DCM) risk. These findings offer new directions for understanding DCM and developing diagnostic tools.

Area of Science:

  • Genomics and Bioinformatics
  • Cardiovascular Research
  • Biomarker Discovery

Background:

  • Dilated cardiomyopathy (DCM) is a significant cardiovascular disease affecting over 0.04% of the population.
  • The primary genetic drivers of DCM remain largely unidentified, hindering effective diagnosis and treatment.
  • Identifying key genes is crucial for understanding DCM pathogenesis and developing targeted therapies.

Purpose of the Study:

  • To identify key genes associated with the risk of dilated cardiomyopathy (DCM).
  • To explore potential diagnostic biomarkers for DCM.
  • To investigate the underlying molecular pathways involved in DCM development.

Main Methods:

  • Utilized integrated bioinformatics analysis on three public Gene Expression Omnibus (GEO) datasets (GSE120895, GSE53081, GSE42955).
  • Applied Weighted Gene Co-expression Network Analysis (WGCNA) to identify modules strongly correlated with DCM risk.
  • Constructed a protein-protein interaction (PPI) network and performed Gene Ontology (GO) and KEGG pathway analyses to identify hub genes and associated pathways.

Main Results:

  • Identified 862 differentially expressed genes (DEGs) in DCM.
  • WGCNA highlighted significant associations between DEGs in blue and turquoise modules and DCM risk.
  • KEGG analysis revealed the RTK-RAS pathway's involvement in DCM risk. CTGF and APOA1 emerged as potential biomarkers with high predictive accuracy (AUCs 0.83 and 0.867, respectively), confirmed by Western blot.

Conclusions:

  • CTGF and APOA1 are significantly correlated with DCM risk and show promise as potential diagnostic biomarkers.
  • The study implicates the RTK-RAS pathway in DCM pathogenesis.
  • These findings provide a foundation for future functional studies on DCM and biomarker development.
Abstract

Keywords:
BioinformaticsDilated cardiomyopathyGene expression profiling

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