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Multi-factor regulatory network and different clusters in hypertrophic obstructive cardiomyopathy

Xianyu Qin1,2, Lei Huang3, Sicheng Chen3,4

  • 1Department of Thoracic Surgery, Thoracic Cancer Center, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.

BMC Medical Genomics
|August 7, 2021
PubMed

Insights

This study identifies key genes and regulatory networks in hypertrophic obstructive cardiomyopathy (HOCM). These findings offer potential new avenues for understanding and treating HOCM mechanisms.

Area of Science:

  • Genomics
  • Biomedical Research
  • Cardiovascular Disease

Background:

  • Hypertrophic obstructive cardiomyopathy (HOCM) lacks practical biosignatures and a complete understanding of its regulatory processes.
  • Current knowledge gaps hinder effective diagnosis and treatment strategies for HOCM.

Purpose of the Study:

  • To identify crucial genes and regulatory networks involved in hypertrophic obstructive cardiomyopathy (HOCM).
  • To establish a foundation for potential mechanistic and therapeutic advancements in HOCM.

Main Methods:

  • Integrated public gene expression datasets (GEO, Gene, OMIM) to form a candidate HOCM gene set.
  • Applied Weighted Gene Co-expression Network Analysis (WGCNA) to identify key co-expressed genes.
  • Constructed a multi-factor regulatory network (lncRNAs, mRNAs, miRNAs, TFs) and performed unsupervised clustering to identify hub genes.

Main Results:

  • Identified 32 crucial co-expressed genes within two significant HOCM modules via WGCNA.
  • Disclosed seven primary regulatory agents, including lncRNAs (XIST, MALAT1, H19), TFs (SPI1, SP1), and miRNAs (hsa-miR-29b-39, has-miR-29a-3p).
  • Discovered four HOCM clusters and four hub genes (COMP, FMOD, AEBP1, SULF1) with significant expression differences, validated by ROC curve analysis.

Conclusions:

  • The identified genes and regulatory networks provide a valuable resource for HOCM research.
  • These findings may facilitate future mechanistic and therapeutic explorations in hypertrophic obstructive cardiomyopathy.
Abstract

Keywords:
Different clustersHypertrophic obstructive cardiomyopathyMulti-factor regulatory networkWeighted gene co-expression network analysis

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