Co‐Expression Transcriptomic Profiling Identifies Sex‐Universal Molecular Markers of Muscle Atrophy

Figures

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  FIGURE 1. Flowchart to identify MDA biomarkers, including data extraction, processing, and analysis.

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  FIGURE 2. Identification of differentially expressed genes (DEGs) in female and male muscle samples. (A, B) Volcano plots of the DEGs. The orange dots represent significantly upregulated genes, and the green dots represent significantly downregulated genes. The grey dots represented nonsignificantly changed genes. (A) Female. (B) Male. (C, D) Heatmap showing the gene names and expression profiles of some DEGs in different samples. (C) Female. (D) Male.

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  FIGURE 3. Weighted gene co‐expression network analysis (WGCNA) revealing gene co‐expression networks in samples from MDA patients (A, B) WGCNA analysis of muscle samples. The left dendrogram represents the clusters of differentially expressed genes based on different metrics. Each branch represents one gene, and each colour below branches represents one co‐expression module. The right heatmap shows the correlation between gene modules and MDA. The correlation coefficient in each cube represents the correlation between gene modules and traits. (A) Female. (B) Male.

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  FIGURE 4. Common hub gene selection and validation of nongender‐specific MDA biomarker (A) The common hub genes shared between DEGs and hub genes are visualised in a Venn diagram. (B–D) Box plots representing expression levels of CD36 in the discovery and validation cohorts. (E–G) Receiver operating characteristic (ROC) curves of CD36 for the discovery and validation cohorts. (B, E) Female discovery cohorts; (C, F) Male discovery cohorts; (D, G) Validation cohorts. (*p < 0.05; ***p < 0.001).

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  FIGURE 5. Least absolute shrinkage and selection operator (LASSO) analysis and Validation of MDA biomarker. The number of factors was determined by LASSO analysis. (A) Female. (B) Male. The procedure of LASSO Cox model fitting is shown on the left panel. One curve represented a gene. The coefficient of each gene against the LC‐norm was plotted with the lambda change. L1‐norm represented the total absolute value of nonzero coefficients. A coefficient profile generated against the log (lambda) sequence is shown on the right panel. Continuous upright lines are the partial likelihood deviance ± standard error (SE); the optimal values were depicted, based on the minimum criteria (lambda.min, left vertical dotted line) and 1‐SE criteria (lambda.1se, right vertical dotted line). (C) Box plots representing expression levels of C21orf33 in the discovery (left) and validation (right) cohorts. (D) ROC curves of C21orf33 in the discovery (left) and validation (right) cohorts. (***p < 0.001).

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  FIGURE 6. Identification the biomarkers for MDA in tenotomy model (A) Flowchart of the Tenotomy Model. (B) The mRNA level of Cd36 and C21orf33 in female and male mice after tenotomy modelling, respectively. (ns No significance, **p < 0.01, ****p < 0.001).

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  FIGURE 7. Evaluation of immune cell infiltration. Violin plots indicating the difference in infiltration proportion of 28 different immune cells between control and MDA samples. (A) Female. (B) Male.

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  FIGURE 8. Immune infiltration evaluation of female and male MDA biomarker. Correlation heatmap demonstrating the relationship between CD36/C21orf33 and immune cells infiltration. (A) CD36. (B) C21orf33.