Bioinformatics and machine learning approaches to explore key biomarkers in muscle aging linked to adipogenesis.

ABSTRACT: Adipogenesis is intricately linked to the onset and progression of muscle aging; however, the relevant biomarkers remain unclear. This study sought to identify key genes associated with adipogenesis in the context of muscle aging. Firstly, gene expression profiles from biopsies of the vastus lateralis muscle in both young and elderly population were retrieved from the GEO database. After intersecting with the results of differential gene analysis, weighted gene co-expression network analysis, and sets of adipogenesis-related genes, 29 adipogenesis-related differential expressed genes (ARDEGs) were selected. Connectivity Map (cMAP) analysis identified tamsulosin, fraxidin, and alaproclate as key target compounds. In further, using three machine learning algorithms and the friends analysis,

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC11929359 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature