Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis

肌萎缩 骨关节炎 微阵列分析技术 生物信息学 转录因子 微阵列 基因 疾病 生物 计算生物学 DNA微阵列 医学 基因表达 遗传学 内科学 病理 替代医学
作者
Jinghong Yang,Jun Zhong,Y. Y. Du,Zi Wang,Lujun Jiang,Zhong Li,Yanshi Liu
出处
期刊:Frontiers in Medicine [Frontiers Media]
卷期号:11: 1380210-1380210 被引量:2
标识
DOI:10.3389/fmed.2024.1380210
摘要

Sarcopenia, a geriatric syndrome characterized by progressive loss of muscle mass and strength, and osteoarthritis, a common degenerative joint disease, are both prevalent in elderly individuals. However, the relationship and molecular mechanisms underlying these two diseases have not been fully elucidated. In this study, we screened microarray data from the Gene Expression Omnibus to identify associations between sarcopenia and osteoarthritis. We employed multiple statistical methods and bioinformatics tools to analyze the shared DEGs (differentially expressed genes). Additionally, we identified 8 hub genes through functional enrichment analysis, protein–protein interaction analysis, transcription factor-gene interaction network analysis, and TF-miRNA coregulatory network analysis. We also discovered potential shared pathways between the two diseases, such as transcriptional misregulation in cancer, the FOXO signalling pathway, and endometrial cancer. Furthermore, based on common DEGs, we found that strophanthidin may be an optimal drug for treating sarcopenia and osteoarthritis, as indicated by the Drug Signatures database. Immune infiltration analysis was also performed on the sarcopenia and osteoarthritis datasets. Finally, receiver operating characteristic (ROC) curves were plotted to verify the reliability of our results. Our findings provide a theoretical foundation for future research on the potential common pathogenesis and molecular mechanisms of sarcopenia and osteoarthritis.

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