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. 2022 Jan 28:2022:8680178.
doi: 10.1155/2022/8680178. eCollection 2022.

Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy

Yunwen Cui  1 , Cheng Liu  1 , Jian Luo  1 , Jie Liang  1
Affiliations

Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy

Yunwen Cui et al. J Healthc Eng. .

Abstract

Background: Hypertrophic cardiomyopathy (HCM) is a group of heterogeneous diseases that affects the myocardium. It is also a common familial disease. The symptoms are not common and easy to find.

Objective: In this paper, we aim to explore and analyze the dysfunctional gene network related to hypertrophic cardiomyopathy, and the key target genes with diagnostic and therapeutic significance for HCM were screened.

Methods: The gene expression profiles of 37 samples (GSE130036) were downloaded from the GEO database. Differential analysis was used to identify the related dysregulated genes in patients with HCM. Enrichment analysis identified the biological function and signaling pathway of these differentially expressed genes. Then, PPI network was built and verified in the GSE36961 dataset. Finally, the gene of single-nucleotide variants (SNVs) in HCM samples was screened by means of maftools.

Results: In this study, 920 differentially expressed genes were obtained, and these genes were mainly related to metabolism-related signaling pathways. 187 interacting genes were identified by PPI network analysis, and the expression trends of C1QB, F13A1, CD163, FCN3, PLA2G2A, and CHRDL2 were verified by another dataset and quantitative real-time polymerase chain reaction. ROC curve analysis showed that they had certain clinical diagnostic ability, and they were the potential key dysfunctional genes of HCM. In addition, we found that PRMT5 mutation was the most frequent in HCM samples, which may affect the pathogenesis of HCM.

Conclusion: Therefore, the key genes and enrichment results identified by our analysis may provide a reference for the occurrence and development mechanism of HCM. In addition, mutations in PRMT5 may be a useful therapeutic and diagnostic target for HCM. Our results also provide an independent quantitative assessment of functional limitations in patients with unknown history.

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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Figure 1
Figure 1
The differentially expressed genes between hypertrophic cardiomyopathy patients and controls. (a) Volcano plot of differentially expressed genes between 28 HCM patients and 9 controls in GSE130036. Red dots represent upregulated genes, and blue dots represent downregulated genes. (b) Thermogram of differentially expressed genes between 28 HCM patients and 9 controls in GSE130036. The node color changes from blue to red, indicating that the gene expression level changes from low to high.
Figure 2
Figure 2
GO and KEGG enrichment of differentially expressed genes. (a, b) The biological process which differentially expressed genes participate in. (c, d) The cellular component which differentially expressed genes participate in. (e, f) The molecular function which differentially expressed genes participate in. The larger the dot is, the more genes are involved. (g, h) The KEGG pathway enrichment of differentially expressed genes.
Figure 3
Figure 3
PPI network construction and identification of hub genes. (a) PPI network of DEGs. (b) The expression of six common differentially expressed genes in the PPI network in two groups of data. (c) Differential expression of key genes was verified with qRT-PCR. ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001. (d) ROC curves of six genes with common differential expression.
Figure 4
Figure 4
Mutations of the expressed genes in HCM samples. (a) The summary of the mutations in all samples. (b) Mutations in the top 10 genes. Genes are ordered by their mutation frequency and the mutation rate in the samples. (c) Transition and transversion plot displaying the distribution of SNVs in HCM classified into six transition and transversion events. Stacked bar plot shows the distribution of mutation spectra for every sample. (d) Word cloud plot for mutated genes. Size of each gene is proportional to the total number of samples in which it is mutated.
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