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Updated: Jul 11, 2025

The Creation of a Rat Model for Osteosarcopenia via Ovariectomy
Published on: February 21, 2025
Exploring molecular mechanisms underlying the pathophysiological association between knee osteoarthritis and
Jiyong Yang1, Tao Jiang2, Guangming Xu3
1The Fifth Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, China.
Objectives:
Accumulating evidence indicates a strong link between knee osteoarthritis (KOA) and sarcopenia. However, the mechanisms involved have not yet been elucidated. This study primarily aims to explore the molecular mechanisms that explain the connection between these 2 disorders.
Methods:
The gene expression profiles for KOA and sarcopenia were obtained from the Gene Expression Omnibus database, specifically from GSE55235, GSE169077, and GSE1408. Various bioinformatics techniques were employed to identify and analyze common differentially expressed genes (DEGs) across the 3 datasets. The techniques involved the analysis of Gene Ontology and pathways to enhance understanding, examining protein-protein interaction (PPI) networks, and identifying hub genes. In addition, we constructed the network of interactions between transcription factors (TFs) and genes, the co-regulatory network of TFs and miRNAs for hub genes, and predicted potential drugs.
Results:
In total, 14 common DEGs were found between KOA and sarcopenia. Detailed information on biological processes and signaling pathways of common DEGs was obtained through enrichment analysis. After performing PPI network analysis, we discovered 4 hub genes (FOXO3, BCL6, CDKN1A, and CEBPB). Subsequently, we developed coregulatory networks for these hub genes involving TF-gene and TF-miRNA interactions. Finally, we identified 10 potential chemical compounds.
Conclusions:
By conducting bioinformatics analysis, our study has successfully identified common gene interaction networks between KOA and sarcopenia. The potential of these findings to offer revolutionary understanding into the common development of these 2 conditions could lead to the identification of valuable targets for therapy.
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