Network-based analysis identifies key regulatory transcription factors involved in skin aging

Skin aging is a complex process involving intricate genetic and environmental factors. In this study, we performed a comprehensive analysis of the transcriptional regulatory landscape of skin aging in canines. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to identify aging-related gene modules. We subsequently validated the expression changes of these module genes in single-cell RNA sequencing (scRNA-seq) data of human aging skin. Notably, basal cell (BC), spinous cell (SC), mitotic cell (MC), and fibroblast (FB) were identified as the cell types with the most significant gene expression changes during aging. By integrating GENIE3 and RcisTarget, we constructed gene regulation networks (GRNs) for aging-related modules and identified core transcription factors (TFs) by intersecting significantly enriched TFs within the GRNs with hub TFs from WGCNA analysis, revealing key regulators of skin aging. Furthermore, we demonstrated the conserved role of CTCF and RAD21 in skin aging using an H2O2-stimulated cell aging model in HaCaT cells. Our findings provide new insights into the transcriptional regulatory landscape of skin aging and unveil potential targets for future intervention strategies against age-related skin disorders in both canines and humans.