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. 2022 May 23:2022:8787782.
doi: 10.1155/2022/8787782. eCollection 2022.

Identification of Potential Biomarkers for Ryanodine Receptor 1 (RYR1) Mutation-Associated Myopathies Using Bioinformatics Approach

Xi Wang  1   2 , Chang Kong  1   3 , Pan Liu  1   2 , Wujun Geng  1   2 , Hongli Tang  1   2
Affiliations

Identification of Potential Biomarkers for Ryanodine Receptor 1 (RYR1) Mutation-Associated Myopathies Using Bioinformatics Approach

Xi Wang et al. Dis Markers. .

Abstract

Background: Myopathies related to Ryanodine receptor 1 (RYR1) mutation are the most common nondystrophy muscle disorder in humans. Early detection and diagnosis of RYR1 mutation-associated myopathies may lead to more timely treatment of patients, which contributes to the management and preparation for malignant hyperthermia. However, diagnosis of RYR1 mutation-associated myopathies is delayed and challenging. The absence of diagnostic morphological features in muscle biopsy does not rule out the possibility of pathogenic variations in RYR1. Accordingly, it is helpful to seek biomarkers to diagnose RYR1 mutation-associated myopathies.

Methods: Skeletal muscle tissue microarray datasets of RYR1 mutation-associated myopathies or healthy persons were built in accordance with the gene expression synthesis (GEO) database. Differentially expressed genes (DEGs) were identified on the basis of R software. Genes specific to tissue/organ were identified through BioGPS. An enrichment analysis of DEGs was conducted in accordance with the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). We also built protein-protein interaction (PPI) networks to explore the function and enrichment pathway of DEGs and the identification of hub genes. Lastly, the ROC curve was drawn for hub genes achieving specific expressions within skeletal muscle. Moreover, the area under the curve (AUC) was obtained to calculate the predictive value of key genes. The transcription factors of hub genes achieving specific expressions within skeletal muscle were predicted with the use of the iRegulon plugin.

Results: We identified 170 DEGs among 11 muscle biopsy samples of healthy subjects and 17 muscle biopsy samples of RYR1 mutation-associated myopathy patients in the dataset. Among the above DEGs, 30 genes achieving specific expressions within tissues/organs were found. GO and KEGG enrichment analysis of DEGs mainly focused on muscle contraction, actin-mediated cell contraction, actin filament-based movement, and muscular sliding. 12 hub genes were identified with the use of Cytoscape. Four hub genes were specifically expressed in skeletal muscle tissue, including MYH1 (AUC: 0.856), TNNT3 (AUC: 0.840), MYLPF (AUC: 0.786), and ATP2A1 (AUC: 0.765). The iRegulon predicted results suggested that the transcription factor MYF6 was found with the highest reliability.

Conclusions: Four skeletal muscle tissue-specific genes were identified, including MYH1, TNNT3, MYLPF, and ATP2A1, as the potential biomarkers for diagnosing and treating RYR1 mutation-associated myopathies, which provided insights into the transcriptome-level development mechanism. The transcription factor MYF6 may be a vital upstream regulator of the above biomarkers.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors report no proprietary or commercial interest in this article.

Figures

Figure 1
Figure 1
Data processing and screening of differentially expressed genes in the GSE103854 dataset. (a) PCA between RYR1 mutation-associated myopathies and normal samples. (b, c) Volcano plot and heatmap of the differentially expressed genes. (d) Rank of differentially expressed genes in GSE103854.
Figure 2
Figure 2
KEGG and GO enrichment analyses of DEGs. (a) The result of the biological process, molecular function, and cellular component-associated GO terms. (b–d) The size of the dot showed count number of enriched genes in the biological process, molecular function, and cellular component. (e) The result of KEGG pathway analysis.
Figure 3
Figure 3
Network analysis of DEGs. (a) Protein-protein interaction network constructed with the differentially expressed genes. Red indicates that gene expression is upregulated; blue indicates that gene expression is downregulated. (b–d) Top 15 genes with the highest MCC, Degree, and Closeness. (e) UpSet diagram summarizing overlapped genes in three sections. (f) Venn diagram of hub genes and skeletal muscle-specific expressed gene overlap.
Figure 4
Figure 4
ROC curve of the 4 specifically expressed hub genes. AUC: area under the ROC curve.
Figure 5
Figure 5
Common TFs among MYH1, ATP2A1, TNNT3, and MYLPF were screened by the iRegulon plugin of Cytoscape software.
See this image and copyright information in PMC

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