The Integration of Bioinformatics with Experimental Validation Has Uncovered Shared Molecular Characteristics Between Sarcopenia and Osteoarthritis

Sarcopenia and osteoarthritis are common degenerative diseases in the elderly that often occur together, and result in reduced motor function. Previous work suggests a molecular link between SP and OA, but their gene regulation is not known. Here, we explore common molecular features and gene regulation of SP and OA by using bioinformatics with animal experiments. The SP data set (GSE226151) and the OA data set (GSE55235) were retrieved from GEO database. Differential analysis and crosstalk gene screening were performed using the package limma in R. GO, KEGG functional enrichment and PPI network analyses were performed on the screened results, and key differential genes (Core-DEGs) were identified using Cytoscape. The TRRUST database was used to predict upstream transcription factors (TFs), and coexpression and functional association network was constructed with GeneMANIA. SP and OA mouse models were developed and behavioral and histological tests were performed. Core gene and TF expression levels were assessed by qRTPCR and Western Blot to verify bioinformatics results. We identified 246 crosstalk genes shared by SP and OA, mainly rich in mitochondrial oxidative phosphorylation, electron transport chains, and inflammatory response pathways. PPI network analysis identified 15 key genes, CXCL8, ITGB2, and PTPRC recognized as Core-DEGs. TRRUST analysis identified DEK and SFPQ as upstream TFs. GeneMANIA analysis revealed significant co-expression in energy metabolism and immune regulation. Behavior and histology demonstrated successful model building with typical muscle atrophy and cartilage degeneration. qRT-PCR and Western Blot results were consistent with bioinformatics trends. This study elucidates the shared molecular network between SP and OA. Disorders in energy metabolism and inflammatory activation may contribute to the common pathological mechanisms underlying both conditions. Core genes, including CXCL8, ITGB2, and PTPRC, along with transcription factors DEK and SFPQ, represent potential diagnostic and therapeutic targets. This research offers new molecular evidence to support combined interventions for senile muscle and joint degeneration.