Abstract

Background: We attempted to identify a regulatory competing endogenous RNA (ceRNA) network and a hub gene of Hypertrophic Cardiomyopathy (HCM). Methods: Microarray datasets of HCM tissue were obtained from NCBI Gene Expression Omnibus (GEO) database. The R package “limma” was used to identify differentially expressed genes. Online search databases were utilized to match the relation among differentially expressed long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs. Weighted correlation network analysis (WGCNA) was used to identify the correlations between key modules and HCM. STRING database was applied to construct PPI networks. Gene Set Enrichment Analysis (GSEA) was used to perform functional annotations and verified the hub genes. Results: A total of 269 DE-lncRNAs, 63 DE-miRNAs and 879 DE-mRNAs were identified in myocardial tissues from microarray datasets GSE130036, GSE36946 and GSE36961, respectively. According to online databases, we found 1 upregulated miRNA hsa-miR-184 that was targeted by 2 downregulated lncRNAs (SNHG9, AC010980.2), potentially targeted 2 downregulated mRNAs (LRRC8A, SLC7A5). 3 downregulated miRNAs (hsa-miR-17-5p, hsa-miR-876-3p, hsa-miR-139-5p) that were targeted by 9 upregulated lncRNAs, potentially targeted 21 upregulated mRNAs. Black and blue modules significantly related to HCM were identified by WGCNA. Hub gene IGFBP5 regulated by hsa-miR-17-5p, AC007389.5, AC104667.1, and AC002511.2 was identified. GSEA indicated that IGFBP5 might involve in the synthesis of myosin complex, participate in kinesin binding, motor activity and function via the regulation of actin cytoskeleton. Conclusion: The results provide a potential molecular regulatory mechanism for the diagnosis and treatment of HCM. IGFBP5 might play an important role in the progression of HCM.

Highlights

  • Hypertrophic Cardiomyopathy (HCM) is one of the most common autosomal-dominant cardiomyopathies with a prevalence of 1:200 to 1:500 (Maron and Maron, 2013; Semsarian et al, 2015)

  • We found 1 upregulated miRNA hsa-miR-184 that was targeted by 2 downregulated long non-coding RNAs (lncRNAs) (SNHG9, AC010980.2), potentially targeted 2 downregulated mRNAs (LRRC8A, SLC7A5). 3 downregulated miRNAs that were targeted by 9 upregulated lncRNAs, potentially targeted 21 upregulated mRNAs

  • Black and blue modules significantly related to HCM were identified by Weighted correlation network analysis (WGCNA)

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Summary

Methods

Microarray datasets of HCM tissue were obtained from NCBI Gene Expression Omnibus (GEO) database. The R package “limma” was used to identify differentially expressed genes. Online search databases were utilized to match the relation among differentially expressed long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs. Weighted correlation network analysis (WGCNA) was used to identify the correlations between key modules and HCM. STRING database was applied to construct PPI networks. Gene Set Enrichment Analysis (GSEA) was used to perform functional annotations and verified the hub genes

Results
Conclusion
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DATA AVAILABILITY STATEMENT
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