Identification of DEGs between the young and aging skin
To gain insights on aging skins, the modular transcriptional signature of skins from the aged women (> 50-year-old) was compared to that of the young controls (< 30-year-old). A total of 79 genes were identified to be differentially expressed with the threshold of P < 0.001. The top 10 up- and down-regulated genes for aging skins are listed in Table 1 and Figure 1. KEGG and GO analyses of DEGs between the young and aging skin
To further analyze the biological functions of the DEGs from the aging skins versus young controls, we performed KEGG and GO analysis. Our study showed the top ten enriched KEGG pathways including “PI3K-Akt signaling pathway”, “Human papillomavirus infection”, “Focal adhesion”, “Proteoglycans in cancer”, “Calcium signaling pathway”, “Regulation of actin cytoskeleton”, “Phospholipase D signaling pathway”, “Platelet activation”, “Protein digestion and absorption”, and “ECM−receptor interaction” (Figure 1).
We identified the top ten cellular components including “collagen−containing extracellular matrix”, “cell−cell junction”, “apical part of cell”, “focal adhesion”, “cell−substrate junction”, “cell leading edge”, “apical plasma membrane”, “sarcolemma”, “collagen trimer”, and “platelet alpha granule” (Figure 2). We then identified the top ten biological processes: “extracellular matrix organization”, “extracellular structure organization”, “cell-substrate adhesion”, “cell-cell adhesion via plasma-membrane adhesion molecules”, “regulation of actin filament-based process”, “regulation of actin cytoskeleton organization”, “homophilic cell adhesion via plasma membrane adhesion molecules”, “cell-matrix adhesion”, “regulation of cell-substrate adhesion”, and “collagen fibril organization” (Figure 2).
We identified the top ten molecular functions: “actin binding”, “extracellular matrix structural constituent”, “glycosaminoglycan binding”, “actin filament binding”, “integrin binding”, “growth factor binding”, “heparin binding”, “collagen binding”, “fibronectin binding”, and “platelet-derived growth factor binding” (Figure 2).
PPI networks and Reactome
The PPI networks were created by using the String and the top two clusters were selected by using the Cytoscape (Figure 3). We set the criterion of combined score > 0.7 and constructed the PPI network by using the 73 nodes and 38 interactions. Among these nodes, the top ten genes with the highest scores are shown in Table 2. We identified several signaling pathways by using Reactome. We identified top ten signaling pathways including: “Extracellular matrix organization”, “Elastic fibre formation”, “Crosslinking of collagen fibrils”, “Post-translational protein phosphorylation”, “Assembly of collagen fibrils and other multimeric structures”, “Regulation of Insulin-like Growth Factor (IGF) transport and uptake by Insulin-like Growth Factor Binding Proteins (IGFBPs)”, “Defective CHST14 causes EDS, musculocontractural type”, “Defective CHST3 causes SEDCJD”, “ECM proteoglycans”, and “Platelet degranulation” (Supplemental Table S1). We then created the reaction map according to the signaling pathways (Figure 4).
Potential inhibitors between the young and aging skin
To further know the potential regulator inhibitors, we introduced the L1000FDW tool to predict the potential inhibitors. We selected the top ten molecules according to the DEGs and the inhibitor map: “WZ-3105”, “BRD-K33045404”, “trametinib”, “forskolin”, “mycophenolic-acid”, “BRD-K60297835”, “HG-6-64-01”, “BRD-K68548958”, “mocetinostat”, and “palbociclib” (Figure 5 and Supplemental Table S2).