Related Experiment Video
Updated: Aug 12, 2026
Assessing Cardiomyocyte Subtypes Following Transcription Factor-mediated Reprogramming of Mouse Embryonic Fibroblasts
Published on: March 22, 2017
Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning
1Department of Cardiovascular Medicine, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.
Insights
Researchers identified four novel gene biomarkers (RASD1, CDC42EP4, MYH6, FCN3) for hypertrophic cardiomyopathy (HCM). These findings offer potential for earlier diagnosis and improved understanding of HCM pathogenesis.
Area of Science:
- Cardiovascular Genetics
- Molecular Pathology
- Bioinformatics
Background:
- Hypertrophic cardiomyopathy (HCM) is a primary cause of heart failure and sudden cardiac death.
- Early diagnosis and effective treatment are crucial for managing HCM.
- Understanding the molecular mechanisms underlying HCM is essential for developing targeted therapies.
Purpose of the Study:
- To investigate the pathogenesis of hypertrophic cardiomyopathy (HCM).
- To identify potential diagnostic gene biomarkers for HCM.
- To explore novel therapeutic targets for HCM.
Main Methods:
- Bioinformatic analysis of myocardial tissue transcriptomic profiles from HCM patients (GSE36961).
- Identification of differentially expressed genes (DEGs), enrichment analysis, and protein-protein interaction (PPI) network construction.
- Application of LASSO regression and support vector machine recursive feature elimination for biomarker selection, validated in an external dataset (GSE141910).
Main Results:
- 156 DEGs were identified, with 109 downregulated and 47 upregulated.
- DEGs are implicated in inflammatory response, platelet activity, complement and coagulation cascades, extracellular matrix organization, and VEGFA-VEGFR2 signaling.
- RASD1, CDC42EP4, MYH6, and FCN3 were identified as potential diagnostic biomarkers for HCM.
Conclusions:
- RASD1, CDC42EP4, MYH6, and FCN3 demonstrate potential as diagnostic gene biomarkers for HCM.
- These biomarkers may offer insights into the pathogenesis of hypertrophic cardiomyopathy.
- Further research is warranted to validate these findings and explore their clinical utility.
Objectives:
Hypertrophic cardiomyopathy (HCM), a leading cause of heart failure and sudden death, requires early diagnosis and treatment. This study investigated the underlying pathogenesis and explored potential diagnostic gene biomarkers for HCM.
Methods:
Transcriptional profiles of myocardial tissues from patients with HCM (dataset GSE36961) were downloaded from the Gene Expression Omnibus database and subjected to bioinformatics analyses, including differentially expressed gene (DEG) identification, enrichment analyses, and protein-protein interaction (PPI) network analysis. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination were performed to identify candidate diagnostic gene biomarkers. mRNA expression levels of candidate biomarkers were tested in an external dataset (GSE141910); area under the receiver operating characteristic curve (AUC) values were obtained to validate diagnostic efficacy.
Results:
Overall, 156 DEGs (109 downregulated, 47 upregulated) were identified. Enrichment and PPI network analyses indicated that the DEGs were involved in biological functions and molecular pathways including inflammatory response, platelet activity, complement and coagulation cascades, extracellular matrix organization, phagosome, apoptosis, and VEGFA-VEGFR2 signaling. RASD1, CDC42EP4, MYH6, and FCN3 were identified as diagnostic biomarkers for HCM.
Conclusions:
RASD1, CDC42EP4, MYH6, and FCN3 might be diagnostic gene biomarkers for HCM and can provide insights concerning HCM pathogenesis.
