Wang Yonggang, Li Zhihao, Xu Xiaolong, Li Xin, Huang Rongxiang, Wu Guofeng
Department of Spinal Surgery, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou, Hubei, China.
Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Sci Rep. 2024 Dec 30;14(1):31862. doi: 10.1038/s41598-024-83268-9.
The aim of this study is to screen key target genes of osteoarthritis associated with aging and to preliminarily explore the associated immune infiltration cells and potential drugs. Differentially expressed senescence-related genes (DESRGs) selected from Cellular senescence-related genes (SRGs) and differentially expressed genes (DEGs) were analyzed using Gene Ontology enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interaction networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. CIBERSORTx and ssGSEA algorithms were then used to assess immune cell infiltration and to analyse the correlation between key DESRGs and immune infiltration. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed. Combined with the DEGs and SRGs, we screened 19 DESRGs for further study. Five diagnostic genes were ultimately identified: CDKN1A, VEGFA, MCL1, SNAI1 and MYC. ROC analysis showed that the area under the curve (AUC). Correlation analysis showed that the five hub genes were closely associated with neutrophil, plasmacytoid dendritic cell, activated CD4 T-cell and type 2 T-helper cell infiltration in the development of Osteoarthritis (OA). Finally, we found that drugs such as lithium chloride, acetaminophen, curcumin, celecoxib and resveratrol could be targeted for the treatment of senescence-related OA. The results of this study indicate that CDKN1A, VEGFA, MCL1, SNAI1, and MYC are key biomarkers that can be used to predict and prevent early aging-related OA. Lithium chloride, acetaminophen, curcumin, celecoxib, and resveratrol can be used for personalized treatment of aging-related OA.
本研究旨在筛选与衰老相关的骨关节炎关键靶基因，并初步探索相关的免疫浸润细胞及潜在药物。从细胞衰老相关基因（SRGs）和差异表达基因（DEGs）中筛选出的差异表达衰老相关基因（DESRGs），利用基因本体论富集分析、京都基因与基因组百科全书（KEGG）通路分析及蛋白质-蛋白质相互作用网络进行分析。基于度值从DESRGs中选择枢纽基因，并通过基因表达和受试者工作特征（ROC）曲线进一步筛选诊断基因。然后使用CIBERSORTx和ssGSEA算法评估免疫细胞浸润，并分析关键DESRGs与免疫浸润之间的相关性。最后，构建诊断基因的miRNA-基因网络并进行靶向药物预测。结合DEGs和SRGs，我们筛选出19个DESRGs进行进一步研究。最终确定了5个诊断基因：CDKN1A、VEGFA、MCL1、SNAI1和MYC。ROC分析显示曲线下面积（AUC）。相关性分析表明，这5个枢纽基因与骨关节炎（OA）发展过程中的中性粒细胞、浆细胞样树突状细胞、活化CD4 T细胞和2型辅助性T细胞浸润密切相关。最后，我们发现氯化锂、对乙酰氨基酚、姜黄素、塞来昔布和白藜芦醇等药物可作为治疗衰老相关OA的靶点。本研究结果表明，CDKN1A、VEGFA、MCL1、SNAI1和MYC是可用于预测和预防早期衰老相关OA的关键生物标志物。氯化锂、对乙酰氨基酚、姜黄素、塞来昔布和白藜芦醇可用于衰老相关OA的个性化治疗。
