Changes in gene expression and protein levels in the gastrocnemius muscle following denervation

This study employed dynamic assessment to investigate transcriptional and protein-level changes in the gastrocnemius muscle following denervation. A denervation mouse model was utilized to examine RNA and protein alterations at 3 days, 2 weeks, and 4 weeks post-sciatic nerve disconnection. Gastrocnemius muscle tissue was collected and subjected to analysis for changes in wet weight ratio and muscle fibrosis using Masson staining (Fig. 1A). A comprehensive analysis identified a total of 54,534 transcripts and 3,218 proteins through transcriptomic and proteomic approaches at various time points. Statistical analysis identified 23,282 transcripts and 1,852 proteins exhibiting statistically significant variances across the three time points (Fig. 1B, C). Principal component analysis delineated discernible expression patterns between denervated muscle tissue and normal muscle tissue, with resemblances noted between the 2-week and 4-week post-injury time points (Fig. 1B). Additionally, proteomic analysis corroborated substantial distinctions in expression patterns between the denervated and control groups throughout the three time points (Fig. 1C). Heatmap analysis visually depicted both similarities and heterogeneity within the transcriptome and proteome profiles. (Fig. 1D, E).

Fig. 1

Transcriptomic and proteomic analysis of the gastrocnemius muscles in a denervated mouse model at various time point. A Appearance and wet weight ratio of gastrocnemius muscles at 3 days, 2 weeks, and 4 weeks post-denervation. Bars represent the average ± S.D. of 3 groups (n = 10). Muscle tissues show significant atrophy at 2 weeks and 4 weeks post-denervation. Masson's trichrome staining indicates a progressive increase in muscle fibrosis as denervation progresses. B RNA-seq analysis identified a total of 54,534 transcripts, with 23,282 transcripts common across the three time points; Principal component analysis (PCA) revealed that the first principal component explained 34.83% of the variance in the data, while the second component accounted for 31.29% of the variance. C 4D-Label free proteomics identified a total of 3,218 proteins, with 1,852 proteins common across the three time points. PCA results revealed that the first principal component explained 51% of the data variance, and the second component explained 11% of the data variance. D Heatmap of differentially expressed genes in the transcriptome at 3 days, 2 weeks, and 4 weeks compared to normal. E Heatmap of differential protein expression in proteomics at 3 days vs. normal, 2 weeks vs. normal, and 4 weeks vs. normal

Filtering key genes for muscle atrophy using multi-omics

A multi-omics approach was employed to ascertain pivotal genes linked to denervation-induced muscle atrophy, utilizing a threshold of padj < 0.05 |log2FoldChange|≥ 1.0 to discern differential genes and padj < 0.05 |log2FoldChange|≥ 0.26 to differential proteins. This screening criterion is consistent with the criteria for subsequent integrated analysis of proteomics and transcriptomics. Transcriptome analysis unveiled 2730 significantly altered genes (1284 up-regulated, 1436 down-regulated) following 3 days of denervation in contrast to normal muscle tissue, 2796 genes (1392 up-regulated, 1404 down-regulated) after 2 weeks, and 3053 genes (1664 up-regulated, 1389 down-regulated) after 4 weeks. (Fig. 2A) The proteomic analysis revealed differential expression of 244 proteins (166 up-regulated, 78 down-regulated) following 3 days of denervation, 1095 proteins (705 up-regulated, 390 down-regulated) after 2 weeks, and 1065 proteins (705 up-regulated, 360 down-regulated) after 4 weeks. (Fig. 2B) Integration of the proteomic data with gene expression analysis identified 97 genes with consistent expression patterns after 3 days, 251 genes after 2 weeks, and 223 genes after 4 weeks, underscoring the significance of cross-referencing omics datasets. The study revealed 24 genes, consisting of 15 up-regulated and 9 down-regulated genes, that displayed consistent expression patterns at three distinct time points following denervation: 3 days, 2 weeks, and 4 weeks. (Fig. 2C–E) These genes demonstrated alterations at both the protein and transcriptional levels, indicating their potential significance in the development of muscle denervation atrophy.

Fig. 2

Multi-omics analysis to identify differentially expressed genes with consistent expression trends. A With a threshold of padj < 0.05 and |log2FoldChange|> 1.0, transcriptome analysis unveiled 2,730 significantly altered genes (1,284 up-regulated, 1,436 down-regulated) after 3 days of denervation compared to normal muscle tissue, 2,796 genes (1,392 up-regulated, 1,404 down-regulated) after 2 weeks, and 3,053 genes (1,664 up-regulated, 1,389 down-regulated) after 4 weeks. B With padj < 0.05 and |log2FoldChange|> = 0.26, the proteomic analysis revealed differential expression of 244 proteins (166 up-regulated, 78 down-regulated) following 3 days of denervation, 1,095 proteins (705 up-regulated, 390 down-regulated) after 2 weeks, and 1,065 proteins (705 up-regulated, 360 down-regulated) after 4 weeks; C The quadrant chart depicting the correlation analysis between proteins and transcripts illustrates the differential expression observed at the proteomic and transcriptomic levels. The horizontal and vertical coordinates correspond to log2-transformed fold changes in the transcriptome and proteome, respectively, demonstrating instances in which expression patterns are concordant, discordant, or uniquely altered at either the protein or transcript level. For non-expressed results in proteins or transcripts, expression values are set to zero by default in the plot, thus points on the Y-axis represent expressions only found in the transcriptome, and points on the X-axis represent expressions only found in the proteome. D The comparison of Venn diagrams illustrating the counts of differentially expressed proteins and transcripts reveals that there are 97 genes exhibiting consistent expression trends in the 3d.vs.normal group, 251 genes in the 2w.vs.normal group, and 223 genes in the 4w.vs.normal group. Notably, 24 genes are found to be consistently expressed across all three time points. E A heatmap was generated through hierarchical clustering analysis utilizing differential protein and associated transcriptomic data. Each row in the heatmap corresponds to a differentially intersected gene, with the tree structure on the left illustrating the clustering of expression patterns of these intersected genes

Spatiotemporal dynamic analysis of differential proteins and genes

The R software package Mfuzz was employed for bioinformatics analysis to investigate the temporal changes of differential proteins and genes in denervation-induced muscle atrophy in a specific model. A total of 1127 differential genes and 566 proteins were identified using the screening criteria of at least one time point meeting a significance level of P < 0.05 and Fold Change > 2. (Supplementary file1-2)The analysis classified the 566 proteins and 1127 genes into 6 clusters according to their spatiotemporal expression patterns (Fig. 3A, B). 24 common gene-proteins and transcriptional data are categorized into four groups according to their temporal expression patterns. (Fig. 3C).

Fig. 3

Analysis of the spatiotemporal trends in the progression of muscle denervation. A 566 proteins and (B) 1127 mRNAs were respectively clustered into 6 distinct expression clusters using fuzzy c-means clustering to demonstrate the dynamic expression changes at the transcriptional and protein levels during denervation progression. Each cluster highlights the top 3 significantly enriched pathways. In the multi-omics dataset, proteins or genes exhibiting persistent upregulation during muscle atrophy caused by denervation are highlighted in red, whereas those displaying persistent downregulation are highlighted in blue. C 24 common gene-proteins and transcriptional data are clustered into 4 categories based on their temporal expression patterns. D The Mfuzz analysis method was utilized to identify key genes and proteins that exhibit continuous upregulation or downregulation. The results revealed that proteins showing continuous upregulation were enriched in 18 KEGG pathways, while genes showing continuous upregulation were enriched in 17 KEGG pathways, with two pathways being common to both. Conversely, proteins exhibiting continuous downregulation were enriched in 32 KEGG pathways, and genes showing continuous downregulation were enriched in 38 KEGG pathways, with 12 pathways being common to both. Notably, among the genes and proteins enriched in common pathways, 18 genes (9 upregulated marked in red and 9 downregulated marked in green) displayed consistent expression patterns at both the protein and transcriptional levels

Notably, The proteins that are consistently up-regulated in denervation-induced muscle atrophy are predominantly linked to pathways involving cellular stress response, cytoskeletal dynamics, signal transduction, and intercellular communication. These pathways encompass processes such as protein processing in the endoplasmic reticulum, regulation of the actin cytoskeleton, and RNA transport and processing. At the transcriptional level, denervated muscle atrophy is characterized by the continuous up-regulation of differential genes enriched in pathways such as NF-κB signaling and apoptosis. This up-regulation indicates the presence of an inflammatory state and heightened apoptosis during the process of denervation-induced muscle atrophy, resulting in increased apoptosis, activation of the immune response, and disruption of signaling pathways.

Proteins and genes that exhibit sustained down-regulation in denervated muscle atrophy are enriched in critical pathways related to energy metabolism, carbohydrate metabolism, amino acid biosynthesis, glucose regulation, hypoxic response, and nucleotide metabolism. These extensive perturbations in metabolic pathways indicate inadequate energy provision, diminished capacity for protein synthesis and repair, aberrant glucose metabolism, compromised DNA and RNA synthesis and repair. These findings imply that reducing oxidative stress and stabilizing energy metabolism could play a significant role in mitigating or reversing the progression of the disease.

After conducting trend analysis, we focused on one type of continuously up-regulated gene set (C1, C3) and one type of continuously down-regulated gene set (C2, C4) at both protein and transcription levels. Enrichment analysis revealed that the C1 gene set was enriched in 18 KEGG pathways, while the C3 gene set was enriched in 17 pathways, with two pathways overlapping between C1 and C3, involving 17 gene symbols. On the other hand, the C2 gene set showed enrichment in 32 KEGG pathways, and the C4 gene set in 38 KEGG pathways, with 12 pathways common to both gene sets, covering 71 gene symbols. Ultimately, we identified a total of 18 genes exhibiting consistent expression trends at both protein and transcription levels, with 9 genes up-regulated and 9 genes down-regulated (Fig. 3D).

Filter Hubgene by PPI network diagram

Utilizing cytoscape software, we constructed a PPI network diagram incorporating 24 differential genes identified from the multi-omics joint analysis and 18 genes from the Mfuzz analysis, totaling 42 key genes (Fig. 4A). CytoHubba was then used to filter critical nodes and subnetworks, revealing the top 6 genes as Hsp90aa1, Eno3, Tpi1, Pkm, Sdha, and Sod2. Subsequently, the MCODE plug-in identified 3 key subnetworks (Fig. 4B, D). The top 30 proteins were analyzed using the TRRUST website to predict upstream regulated transcription factors, resulting in the prediction of Nfe2l2(also name as NRF2), Rela, and Nfkb1. (Fig. 4C).

Fig. 4

Selection of hub genes through the PPI network diagram. A 24 differential genes were identified through a multi-omics combined analysis, and 18 differential genes were identified by Mfuzz analysis; both sets were integrated into a collection of 42 key genes. B A PPI network diagram was constructed using the 42 key genes, and the top 30 hub genes were selected based on degree values. C In the TRRUST network, transcription factors such as Nfe2l2, Rela, and Nfkb1 are predicted to regulate the top 30 hub genes upstream. D NRF2 was chosen for inclusion in the group of 42 essential genes, which were subsequently categorized into three distinct sub-networks. The protein–protein interaction (PPI) network visualization illustrates the interactions between NRF2 and Fn1, Sod2, Hsp90aa1, and Pdg. E, G Significantly activated and inhibited upstream pathways and top15 regulatory molecules in IPA analysis. F The map of Mitochondrial Dysfunction pathway

A total of 251 genes exhibiting consistent expression patterns in both transcriptomic and proteomic data across the 2-week and normal groups were chosen for Ingenuity Pathway Analysis (IPA). (Supplementary file 3) The investigation focused on the overlap between molecules within the dataset and those associated with specific pathways to determine the potential activation or inhibition of these pathways. Pathway activation following denervation was evaluated utilizing a z-score metric, with a z-score ≥ 2 signifying substantial activation and a z-score ≤ -2 indicating significant inhibition. (Fig. 4E, Supplementary file 4) Based on the results obtained from the Ingenuity Pathway Analysis (IPA), the three pathways that exhibited the highest levels of activation were Mitochondrial Dysfunction (z-score = 3), Synaptogenesis Signaling Pathway (z-score = 2.714), and mTOR (z-score = 2.646). Conversely, the pathways that were most significantly inhibited included Electron Transport, ATP Synthesis, and Heat Production by Uncoupling Proteins (z-score = −4.69), Oxidative Phosphorylation (z-score = −4.359), and The Citric Acid (TCA) Cycle and Respiratory(z-score = −3.606). IPA results indicate that reduced energy metabolism and mitochondrial dysfunction are the primary upstream regulatory factors for muscle denervation atrophy, suggesting that stabilizing mitochondria to enhance energy metabolism levels is essential for delaying muscle atrophy. In the map of Mitochondrial Dysfunction pathway, key activating factors identified include oxidative stress and endoplasmic reticulum stress, with green indicating activation and red indicating inhibition. In the map, we identified the transcription factor NRF2 as a crucial node for alleviating oxidative stress and stabilizing mitochondrial function. In the prediction of upstream transcription factors within the hubgenes set, NRF2 also showed significant enrichment. This further emphasizes the potential of NRF2 as an important target for delaying muscle denervation atrophy. (Fig. 4F).

The Activation z-score algorithm was employed to forecast the activation or inhibition of upstream regulators, thereby reducing the occurrence of significant predictions arising from random data. In this investigation, metribolone (activation z-score = −5.395), PPARGC1A (activation z-score = −4.953), and mono-(2-ethylhexyl) phthalate (activation z-score = −4.372) emerged as the most notably inhibited upstream regulators. Conversely, Torin1 (activation z-score = 4.025), CLPP (activation z-score = 3.9), and WNT3A (activation z-score = 3.713) were identified as the most significantly activated upstream regulators. (Fig. 4G, Supplementary file 5).

Hubgene parallel reaction monitoring (PRM) verification

The top 30 hubgenes were selected to investigate their protein expression differences. A denervated muscle atrophy model was created using C57 mice, and PRM testing was conducted at various time points. Results showed that 12 genes exhibited expression variances compared to normal tissues across all three time points, while 11 genes showed differences at each time point. Notably, 2 proteins had significant expression disparities at 2 weeks and 4 weeks post-injury, while 8 proteins did not display differences across the three time points. Consequently, these 23 differentially expressed genes were identified as core targets in denervated muscle atrophy. (Fig. 5A-F) GO and KEGG analyses revealed that these key proteins primarily function in the pathways associated with carbohydrate catabolic process, glycolytic process, monosaccharide biosynthesis process. These are all biological processes closely related to energy metabolism. (Fig. 5G–H, Supplementary file 6).

Fig. 5

4D-PRM confirms protein level changes in the top 30 hub genes during denervation, with 23 genes showing significant differences. A ENO3, Fbp2, GMPR, Pkm, and Pgam2 consistently demonstrate downregulation during the progression of denervation-induced muscle atrophy. These genes primarily participate in glycolysis and gluconeogenesis, suggesting a notable reduction in the functionality of these metabolic pathways following denervation. The persistent upregulation of Pgd and Tpi1 reflects compensatory adjustments made by muscle tissue in response to oxidative stress. Bars represent the average ± S. D of 3 independent experiments (n = 3) (B) Eef1a1, Eif4a1, and Rpl3, key components in the protein synthesis pathway, exhibit sustained upregulation following denervation, indicative of the muscle tissue's adaptive response to stress. Bars represent the average ± S. D of 3 independent experiments (n = 3) (C) Art3 is primarily involved in intracellular signal transduction, while Auh is a mitochondrial protein associated with fatty acid metabolism; both proteins exhibit consistent downregulation. Additionally, Klc1, a constituent of the kinesin motor complex responsible for material transport, demonstrates persistent upregulation. Bars represent the average ± S. D of 3 independent experiments (n = 3) (D) The sustained elevation of hspb8, hspb7, and hsp90aa1 gene expression signifies stress-induced injury in muscle tissue subsequent to denervation. The persistent upregulation of Hsp90b1, associated with endoplasmic reticulum oxidative stress, implies the occurrence of endoplasmic reticulum stress. Bars represent the average ± S. D of 3 independent experiments (n = 3) (E) Flnc, Klhl41, Sync, and Tubb6, proteins related to maintaining muscle structural integrity, are persistently upregulated during the pathological process. Bars represent the average ± S. D of 3 independent experiments (n = 3) (F) The continuous upregulation of Fn1 and Tnc reflects the development of muscle fibrosis following denervation. Bars represent the average ± S. D of 3 independent experiments (n = 3) * for p < 0.05, ** for p < 0.01, *** for p < 0.001, and **** for p < 0.0001. G–H GO/KEGG analysis of the 23 gene

The results above indicate that oxidative stress damage, endoplasmic reticulum stress, and disruptions in energy and glucose metabolism play significant roles in the development of muscle denervation atrophy, ultimately resulting in atrophy and fibrosis. Furthermore, mitochondrial dysfunction is identified as the primary factor contributing to these pathological changes. Therefore, stabilizing mitochondrial function could be a crucial therapeutic approach to delay muscle denervation atrophy.In our study, we identified NRF2 as a potential therapeutic target. Activation of NRF2 alleviates cellular oxidative stress and stabilizes mitochondrial dysfunction, thereby enhancing energy metabolism pathways to improve muscle denervation atrophy. To confirm this hypothesis, we assessed the therapeutic effects of the targeted activator omaveloxone on denervation muscle atrophy in our subsequent research.

Expression of 23 genes in different cell types of muscle tissue

After a series of processes including standardization, PCA dimensionality reduction, and cell clustering, mononuclear cell data were ultimately annotated into 13 cell types (Fig. 6A, C): Type I (n = 185), Type IIa (n = 1276), Type IIx (n = 1376), Type IIb (n = 15,204), NMJ (n = 130), MTJ (n = 374), MuSCs (n = 239), FAPs (n = 4428), Macrophage (n = 435), Endothelial (n = 534), Pericyte (n = 356), Adipocyte (n = 157), and Others (n = 5042). Cells annotated as Others were excluded (Fig. 6B), and the distribution of different cells between disease and normal groups was displayed (Fig. 6D, E). The results showed a significant increase in FAPs cells and a significant decrease in Type IIx cells in the Denervation group. A violin plot was created to trace the expression of 23 key validated genes across 12 cell types between groups (Fig. 6F). The results revealed that Eno3, Gmpr, Pkm, Pgam2, and Tpi1 showed the most significant differential expression in Type II muscle cells, especially in Type IIb fibers, followed by FAPs cells. Eno3, Gmpr, and Pgam2 showed a downward trend in expression in Type II fibers and FAPs, consistent with PRM results. Hspb7 and Hspb8 genes showed the most significant differential expression in Type II fibers. Klc1, Eef1a1, Eif4a1, and Tubb6 showed significant differential expression in Type IIb cells. Flnc and Klhl41 showed significant differential expression in Type IIa, IIx, and IIb muscle fibers, with an upward trend consistent with PRM results. Art3 and Auh showed differential expression in almost all cell types, with downregulated expression in Type IIa and IIb cells, consistent with PRM results. In summary, Type II muscle fibers, especially Type IIb fibers, are the most affected cell types in denervation-induced muscle atrophy.

Fig. 6

A Annotation of cells into 13 subpopulations; B Visualization of 12 cell subpopulations after excluding unannotated cell types; C Bubble plot of different cell markers corresponding to various cell types; D, E Comparison of the distribution proportions of different cell types between the Denervation and normal groups; F Violin plots showing the expression levels of 23 PRM-validated genes in different cell types, with intergroup comparisons calculated for significance using the Wilcoxon test. * for p < 0.05, ** for p < 0.01, *** for p < 0.001, and **** for p < 0.0001

Omaveloxolone reduces oxidative stress and endoplasmic reticulum stress

Omaveloxolone, a targeted activator sourced from the DrugBank database, received FDA approval in 2023 for treating Friedreich's Ataxia. While studies have examined the role of NRF2 in various neurodegenerative diseases, research on its specific impact on denervated muscle atrophy remains scarce. To address this gap, a mouse denervation model was utilized, with omaveloxolone administered intraperitoneally at 10 mg/kg dosage 30 min post-membrane creation. Gastrocnemius muscles were collected after 4 weeks of continuous injection. Results indicated a higher wet weight ratio and muscle fiber area in the omaveloxolone group compared to the control group. (Fig. 7A–C) The mean cross-sectional area and diameter of muscle fibers in the omaveloxolone group exhibited a statistically significant increase compared to those in the control group. (Fig. 7D) Immunohistochemistry revealed increased levels of Sod2, Sdha, and NRF2 proteins in the omaveloxolone group, suggesting a reduction in oxidative stress damage. (Fig. 7E–I) Additionally, up-regulation of glycolysis-related proteins PKM in the omaveloxolone group hinted at enhanced energy supply through the glycolysis pathway. TEM analysis of muscle tissue revealed significant mitochondrial matrix edema in the gastrocnemius muscle of the control group, characterized by the presence of vacuoles, disappearance of mitochondrial cristae shape, and damage to the mitochondrial membrane integrity. (Fig. 7J) Conversely, in the Omaveloxolone experimental group, a less pronounced degree of mitochondrial swelling was observed compared to the control group, with the mitochondrial morphology largely preserved. Although the mitochondrial cristae were disordered, the fundamental shape was still discernible. This indicates that Omaveloxolone plays a role in maintaining the stability of mitochondrial morphology.

Fig. 7

A Comparison of gross photographs, Masson staining, and WGA staining of the gastrocnemius muscles between the omaveloxolone group and the control group. B The wet weight of the gastrocnemius muscle treated with omaveloxolone was significantly higher than that of the control control group (n = 11). C In the omaveloxolone group, the proportion of collagen fibers (blue) to muscle fibers (red) was lower than in the control group, indicating a lower degree of fibrosis (n = 5). D The average area and diameter of muscle fibers in the omaveloxolone group were greater than those in the control group (n = 5). E ICH was performed on the affected side of the gastrocnemius muscle to detect the expression of Sod2, Sdha, NRF2, and PKM proteins (n = 5). F-I The results showed that the average optical density values (IOD/Area) of Sod2, Sdha, NRF2, and PKM in the omaveloxolone group were significantly higher than those in the control group. J TEM revealed significant mitochondrial swelling and damage in the control group, while the Omaveloxolone group showed less severe swelling and maintained better mitochondrial integrity. Green arrows show mitochondria

RNA-seq and GSEA analyses reveal the protective mechanism of Omaveloxolone in denervation muscle atrophy model

RNA-seq sequencing was performed on the affected gastrocnemius muscles of mice in the Omaveloxolone and Control groups. Using a threshold of p-adj < 0.05 and |log2(FC)|> 1, a total of 474 differentially expressed genes were identified (188 significantly upregulated and 286 significantly downregulated) (Fig. 8A). GSEA analysis, with significance thresholds of |NES|> 1, NOM p-val < 0.05, and FDR q-val < 0.25, revealed 17 significantly activated pathways, including Autophagy, Glutathione metabolism, Mitophagy, and PPAR signaling pathway (Fig. 8B). These findings suggest that Omaveloxolone may enhance tissue antioxidant capacity by improving glutathione metabolism, and maintain mitochondrial quality and energy metabolism through promoting mitophagy and activating the PPAR signaling pathway. Although denervation-induced muscle atrophy is not classified as a neurodegenerative disease, the functional degradation of the neuromuscular junction plays a key role in disease progression. The pathways of Huntington's disease and Parkinson's disease were significantly inhibited, suggesting that Omaveloxolone may help maintain neuromuscular junction function. (Fig. 8C) The suppression of the Natural killer cell mediated cytotoxicity and Antigen processing and presentation pathways may reflect Omaveloxolone's role in modulating immune responses, reducing inflammation and oxidative stress, thereby protecting neuromuscular junctions and delaying muscle atrophy. (Fig. 8C) Western blot analysis of GSR and MuSK expression showed that GSR levels and the GSH/GSSH ratio were significantly higher in the Omaveloxolone group compared to the control group (Fig. 8D, F, G), indicating that the drug intervention significantly enhanced the antioxidant capacity of muscle tissue. In normal muscle tissue, MuSK is highly concentrated in the specialized motor endplate region of the sarcolemma and exhibits a granular distribution, which is crucial for NMJ development and maintenance. After denervation, MuSK expression in the target muscle significantly increases and shows a diffuse distribution on the sarcolemma. The expression of MuSK was significantly lower in the Omaveloxolone group suggesting that Omaveloxolone has a protective effect on maintaining the motor endplate in denervated muscle. (Fig. 8D, F).

Fig. 8

A 474 differentially expressed genes were identified with188 significantly upregulated and 286 significantly downregulated. The volcano plot and heatmap to visualize DEGs distribution and expression; B GSEA analysis indicated that Autophagy, Mitophagy, Glutathione metabolism, PPAR signaling pathway were activated; C Huntington disease, Parkinson disease, Natural killer cell mediated cytotoxicity, Antigen processing and presentatior were inhibited; D Western blot analysis of the expression trends of GSR and MuSK proteins; E, F results show a significant increase in GSR expression in the Omaveloxolone group and a significant decrease in MuSK expression in the Omaveloxolone group; G GSH/GSSH is significantly higher in the Omaveloxolone group than in the Control group, indicating a higher antioxidant capacity in muscle tissue