Hypertrophic cardiomyopathy: current state of the problem

Lednev, P.V.; Stonogin, A. V.; Lysenko, A. V.; Salagaev, G. I.; Belov, Yu. V.

doi:10.17116/hirurgia201901183

Cited by 8 publications

(2 citation statements)

References 39 publications

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“…Patients with hypertrophic cardiomyopathy were relieved by various physical exercise methods, which had made significant contributions to disease management and were carried out without increasing risk [7]. Surgical treatment was the first choice for HCM, but due to the high morbidity and mortality in the early stage of the disease, some clinicians were still hesitant [8,9].…”

Section: Introductionmentioning

confidence: 99%

Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy

Cui

Liu

Luo

et al. 2022

Journal of Healthcare Engineering

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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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Section: Introductionmentioning

confidence: 99%

Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy

Cui

Liu

Luo

et al. 2022

Journal of Healthcare Engineering

View full text Add to dashboard Cite

show abstract

“…Patients with hypertrophic cardiomyopathy are relieved by various physical exercise methods, which have made signi cant contributions to disease management and are carried out without increasing risk (11). Surgical treatment is the rst choice for HCM, but due to the high morbidity and mortality in the early stage of the disease, some clinicians are still hesitant (12,13).…”

Section: Introductionmentioning

confidence: 99%

Dysfunctional network and mutation genes of hypertrophic cardiomyopathy

Cui

Liu

Liang

2020

Preprint

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Background Hypertrophic cardiomyopathy (HCM) is a group of heterogeneous diseases that affect the myocardium. It is also a common familial disease. The symptoms are not common and easy to find. Methods In this study, gene expression profiles of 37 samples (GSE130036) were downloaded from GEO database. Differential analysis was used to identify the related dysregulated genes in patients with HCM. Enrichment analysis identified the biological function and signal pathway of these differentially expressed genes. Then, we build PPI network and verify it in GSE36961 dataset. Finally, the gene of single nuclear variants (SNVs) in HCM samples was screened by means of maftools. Results Herein, we obtained 920 differentially expressed genes, and found that these genes are mainly related to metabolic 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. 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. Conclusions 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.

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Identification and analysis of key hypoxia- and immune-related genes in hypertrophic cardiomyopathy

et al. 2023

Biol Res

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Background Hypertrophic cardiomyopathy (HCM), an autosomal dominant genetic disease, is the main cause of sudden death in adolescents and athletes globally. Hypoxia and immune factors have been revealed to be related to the pathology of HCM. There is growing evidence of a role for hypoxia and inflammation as triggers and enhancers in the pathology in HCM. However, the role of hypoxia- and immune-related genes in HCM have not been reported. Methods Firstly, we obtained four HCM-related datasets from the Gene Expression Omnibus (GEO) database for differential expression analysis. Immune cells significantly expressed in normal samples and HCM were then screened by a microenvironmental cell population counter (MCP-counter) algorithm. Next, hypoxia- and immune-related genes were screened by the LASSO + support vector machine recursive feature elimination (SVM-RFE) and weighted gene co-expression network analysis (WGCNA). Single-gene enrichment analysis and expression validation of key genes were then performed. Finally, we constructed a competing endogenous RNA (ceRNA) network of key genes. Results In this study, 35 differentially expressed hypoxia genes were found. By using LASSO + SVM-RFE analysis, 10 more targets with differentially expressed hypoxia genes were identified. The MCP-count algorithm yielded five differentially expressed immune cells, and after assessing them for WGCNA characteristics, 612 immune genes were discovered. When hypoxia and immune genes were combined for cross-tabulation analysis, three hypoxia- and immune-related genes (ATP2A2, DDAH1, and OMA1) were identified. Conclusion Based on hypoxia characteristic genes, three key genes were identified. These were also significantly related to immune activation, which proves a theoretical basis and reference value for studying the relationship between HCM and hypoxia and immunity. Graphical Abstract

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Hypertrophic cardiomyopathy: current state of the problem

Cited by 8 publications

References 39 publications

Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy

Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy

Dysfunctional network and mutation genes of hypertrophic cardiomyopathy

Identification and analysis of key hypoxia- and immune-related genes in hypertrophic cardiomyopathy

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