Fig. 2

Selection of network parameters, module identification, and functional enrichment analysis in T2D- and SA-related datasets. (A) Scale-free topology model fit for T2D samples, depicting the relationship between the soft-thresholding power (x-axis) and the squared correlation coefficient of log(k) vs. log(p(k)) (y-axis). The red line marks the threshold at which the correlation coefficient square reaches 0.9. (B) Mean gene connectivity at various power settings in T2D samples, with the red line indicating the point where average node connectivity equals 1, corresponding to the selected power in panel (A). (C) Gene dendrogram for T2D samples, with modules identified by distinct colors based on hierarchical clustering. (D) Module-trait heatmap in T2D, quantifying correlations between each module and the phenotype (disease/control). (E) Scale-free topology model fit for SA samples, showing the squared correlation coefficient of log(k) vs. log(p(k)) across increasing power values. The red line indicates the 0.9 threshold used for power selection. (F) Mean gene connectivity across power settings in SA, with the red line denoting the point where average node connectivity equals 1, as determined in panel (E). (G) Gene dendrogram for SA samples, with modules labeled by color to represent distinct co-expression clusters. (H) Heatmap of module-trait correlations in SA, indicating the degree of association between individual modules and disease phenotype. (I) Intersection plot of genes within phenotype-associated modules and previously identified DEGs across T2D and SA, highlighting shared candidates. (J) Functional enrichment results for 30 core candidate genes, illustrating significantly enriched GO biological processes and KEGG pathways. T2D, type 2 diabetes; SA, sarcopenia.