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Identification of potential microRNAs and KEGG pathways in denervation muscle atrophy based on meta-analysis.

ABSTRACT: The molecular mechanism of muscle atrophy has been studied a lot, but there is no comprehensive analysis focusing on the denervated muscle atrophy. The gene network that controls the development of denervated muscle atrophy needs further elucidation. We examined differentially expressed genes (DEGs) from five denervated muscle atrophy microarray datasets and predicted microRNAs that target these DEGs. We also included the differentially expressed microRNAs datasets of denervated muscle atrophy in previous studies as background information to identify potential key microRNAs. Finally, we compared denervated muscle atrophy with disuse muscle atrophy caused by other reasons, and obtained the Den-genes which only differentially expressed in denervated muscle atrophy. In this meta-analysis, we obtained 429 up-regulated genes, 525 down-regulated genes and a batch of key microRNAs in denervated muscle atrophy. We found eight important microRNA-mRNA interactions (miR-1/Jun, miR-1/Vegfa, miR-497/Vegfa, miR-23a/Vegfa, miR-206/Vegfa, miR-497/Suclg1, miR-27a/Suclg1, miR-27a/Mapk14). The top five KEGG pathways enriched by Den-genes are Insulin signaling pathway, T cell receptor signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway and B cell receptor signaling pathway. Our research has delineated the RNA regulatory network of denervated muscle atrophy, and uncovered the specific genes and terms in denervated muscle atrophy.

SUBMITTER: Gu X

PROVIDER: S-EPMC8245453 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Denervation can activate the catabolic pathway in skeletal muscle and lead to progressive skeletal muscle atrophy. At present, there is no effective treatment for muscle atrophy. Histone deacetylase 4 (HDAC4) has recently been found to be closely related to muscle atrophy, but the underlying mechanism of HDAC4 in denervation-induced muscle atrophy have not been described clearly yet. In this study, we found that the expression of HDAC4 increased significantly in denervated skeletal muscle. HDAC4 inhibition can effectively diminish denervation-induced muscle atrophy, reduce the expression of muscle specific E3 ubiquitin ligase (MuRF1 and MAFbx) and autophagy related proteins (Atg7, LC3B, PINK1 and BNIP3), inhibit the transformation of type I fibers to type II fibers, and enhance the expression of SIRT1 and PGC-1 α. Transcriptome sequencing and bioinformatics analysis was performed and suggested that HDAC4 may be involved in denervation-induced muscle atrophy by regulating the response to denervation involved in the regulation of muscle adaptation, cell division, cell cycle, apoptotic process, skeletal muscle atrophy, and cell differentiation. STRING analysis showed that HDAC4 may be involved in the process of muscle atrophy by directly regulating myogenin (MYOG), cell cycle inhibitor p21 (CDKN1A) and salt induced kinase 1 (SIK1). MYOG was significantly increased in denervated skeletal muscle, and MYOG inhibition could significantly alleviate denervation-induced muscle atrophy, accompanied by the decreased MuRF1 and MAFbx. MYOG overexpression could reduce the protective effect of HDAC4 inhibition on denervation-induced muscle atrophy, as evidenced by the decreased muscle mass and cross-sectional area of muscle fibers, and the increased mitophagy. Taken together, HDAC4 inhibition can alleviate denervation-induced muscle atrophy by reducing MYOG expression, and HDAC4 is also directly related to CDKN1A and SIK1 in skeletal muscle, which suggests that HDAC4 inhibitors may be a potential drug for the treatment of neurogenic muscle atrophy. These results not only enrich the molecular regulation mechanism of denervation-induced muscle atrophy, but also provide the experimental basis for HDAC4-MYOG axis as a new target for the prevention and treatment of muscular atrophy.

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Identification of potential microRNAs and KEGG pathways in denervation muscle atrophy based on meta-analysis.

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