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Published on: March 22, 2017
Transcriptomics data integration and analysis to uncover hallmark genes in hypertrophic cardiomyopathy
Peng Chen1, Warda Yawar2, Ayesha Rida Farooqui3
1Department of Cardiovascular Medicine, Taiyuan Central Hospital Taiyuan 030000, Shanxi, China.
Insights
This study identifies 8 key hub genes in hypertrophic cardiomyopathy (HCM) by analyzing gene expression data. These findings offer insights into HCM mechanisms and potential therapeutic targets.
Area of Science:
- Genomics
- Molecular Biology
- Cardiovascular Research
Background:
- Hypertrophic cardiomyopathy (HCM) is a complex myocardial disease.
- Understanding the genetic underpinnings of HCM is crucial for effective treatment.
Purpose of the Study:
- To identify novel hypertrophic cardiomyopathy (HCM)-related hub genes.
- To explore the regulatory networks and potential therapeutic targets for HCM.
Main Methods:
- Differential gene expression analysis of public datasets (GSE68316, GSE36961).
- Identification and validation of hub genes using RNA-sequencing and bisulfite sequencing.
- Construction of lncRNA-miRNA-mRNA regulatory networks and pathway enrichment analysis.
Main Results:
- Eight key hub genes (5 upregulated, 3 downregulated) were identified and validated in clinical HCM samples.
- Regulatory networks involving 6 miRNAs and 4 lncRNAs associated with hub genes were elucidated.
- Hub genes were significantly enriched in pathways like Cardiac muscle contraction and Nitrogen metabolism.
Conclusions:
- The identified hub genes and their regulatory networks provide novel insights into HCM pathogenesis.
- These findings may facilitate the development of targeted therapies for hypertrophic cardiomyopathy.
Introduction:
Hypertrophic cardiomyopathy (HCM) is a heterogeneous disease that mainly affects the myocardium. In the current study, we aim to explore HCM-related hub genes through the analysis of differentially expressed genes (DEGs) between HCM and normal sample groups.
Methods:
The GSE68316 and GSE36961 expression profiles were obtained from the Gene Expression Omnibus (GEO) database for the identification of DEGs, to explore hub genes, and to perform their expression analysis. Clinical HCM and control tissue samples were taken for expression and promoter methylation validation analysis via RNA-sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) analyses. Then, other different bioinformatics tools were employed to perform STRING, lncRNA-miRNA-mRNA regulatory networks, gene enrichment, and drug prediction analyses.
Results:
In total, the top 20 DEGs, including 10 up-regulated and 10 down-regulated, were obtained from GSE68316. Out of the 20 DEGs, we subsequently identified the 8 most important hub genes including 5 up-regulated genes (EPB42, UQCRH, CA1, PFDN5, and LSM5) and 3 down-regulated genes (RPS24, TNS1, and RPL26). Expression and promoter methylation dysregulation of these genes were further validated on clinical HCM samples paired with controls. Next, we further investigated hub genes' regulatory 6 miRNAs (has-mir-1-3p, has-mir-129-5p, has-mir-16-5p, has-mir-23b-3p, has-mir-27-3p, and has-mir-182-5p) and miRNAs regulatory 4 lncRNAs (NUTMB2-AS1, NEAT1, XIST, and GABPB1-AS1) in this study via the lncRNA-cricRNA-miRNA-mRNA regulatory network. Later on, gene enrichment analysis revealed that hub genes were enriched in various important pathways including Nitrogen metabolism, Ribosome, RNA degradation, Cardiac muscle contraction, and Coronavirus disease, etc. Finally, the drug prediction analysis highlighted different potential candidate drugs for altering the expression of hub genes in the treatment of HCM.
Conclusion:
In summary, the identification of key hub genes and their enrichment analysis in the current study may shed light on the mechanisms behind the occurrence and development of HCM.
