Abstract

ObjectiveTo reveal the molecular mechanism underlying the pathogenesis of HCM and find new effective therapeutic strategies using a systematic biological approach.MethodsThe WGCNA algorithm was applied to building the co-expression network of HCM samples. A sample cluster analysis was performed using the hclust tool and a co-expression module was constructed. The WGCNA algorithm was used to study the interactive connection between co-expression modules and draw a heat map to show the strength of interactions between modules. The genetic information of the respective modules was mapped to the associated GO terms and KEGG pathways, and the Hub Genes with the highest connectivity in each module were identified. The Wilcoxon test was used to verify the expression level of hub genes between HCM and normal samples, and the “pROC” R package was used to verify the possibility of hub genes as biomarkers. Finally, the potential functions of hub genes were analyzed by GSEA software.ResultsSeven co-expression modules were constructed using sample clustering analysis. GO and KEGG enrichment analysis judged that the turquoise module is an important module. The hub genes of each module are RPL35A for module Black, FH for module Blue, PREI3 for module Brown, CREB1 for module Green, LOC641848 for module Pink, MYH7 for module Turquoise and MYL6 for module Yellow. The results of the differential expression analysis indicate that MYH7 and FH are considered true hub genes. In addition, the ROC curves revealed their high diagnostic value as biomarkers for HCM. Finally, in the results of the GSEA analysis, MYH7 and FH highly expressed genes were enriched with the “proteasome” and a “PPAR signaling pathway,” respectively.ConclusionsThe MYH7 and FH genes may be the true hub genes of HCM. Their respective enriched pathways, namely the “proteasome” and the “PPAR signaling pathway,” may play an important role in the development of HCM.

Highlights

  • Hypertrophic cardiomyopathy (HCM) is the most common genetic heart disease with a prevalence of approximately 1: 500 [18]

  • The molecular mechanism underlying the pathogenesis of HCM remains unclear, and new advanced analytic strategies and genomic technologies provide opportunities to explore the genetic structure of HCM

  • HCM dataset pre-processing A total amount of 37,846 gene expression values were derived from the raw file.Four thousand genes with the greatest average expression values were chosen for cluster evaluation (Fig. 1)

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Summary

Introduction

Hypertrophic cardiomyopathy (HCM) is the most common genetic heart disease with a prevalence of approximately 1: 500 [18]. HCM is characterized by ventricular hypertrophy, with clinical features in patients ranging from asymptomatic to heart failure and sudden cardiac death. Previous studies have shown that in more than 50% of HCM samples, the disease is caused by mutations in genes encoding cardiac myosin, such as MYH7, TNNI3, MYBPC3 and MYL3. The molecular mechanism underlying the pathogenesis of HCM remains unclear, and new advanced analytic strategies and genomic technologies provide opportunities to explore the genetic structure of HCM. This is an opportunity to reveal the molecular mechanism of HCM and find new effective therapeutic strategies

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