基于生物信息学分析冻结肩的基因表达及信号传导通路

Bioinformatics Analysis of Gene Expression and Signaling Pathways in Frozen Shoulder

摘要: 目的：应用生物信息学方法，研究冻结肩与肩关节不稳患者关节囊基因表达谱芯片数据，挖掘冻结肩关节囊中关键表达的基因。方法：选择GEO数据库中冻结肩基因表达谱芯片数据集(GSE140731)，筛选出冻结肩及肩关节不稳两组患者数据中的差异表达基因。将GO和KEGG分析应用于冻结肩中差异表达基因，并利用STRING和Cytoscape软件构建蛋白质–蛋白质相关作用网络(PPI)。结果：冻结肩患者关节囊中有545个差异表达基因，其中上调420个，下调125个。对差异基因进行GO富集分析，发现差异基因的生物学功能及分子功能主要富集在炎症反应、细胞对TNF及IL-1的反应、细胞外基质分解与重构，细胞因子及趋化因子活化、细胞黏附。KEGG信号通路富集分析表明这些差异基因主要与PI3K/Akt、细胞因子与细胞因子受体间相互作用、细胞外基质与受体间相互作用等信号通路有关。PPI分析筛选了3个关键基因：IL6、COL1A1、COL1A2。结论：应用生物信息学分析冻结肩患者关节囊中基因表达谱发现，炎症反应及纤维化机制在冻结肩的发病过程中发挥重要作用并揭示了潜在的关键调控基因及相关信号通路。

Abstract: Objective: By applying bioinformatics methods, to investigate differential genes (DEGs) between frozen shoulder and shoulder instability. Method: The raw gene expression data was downloaded from the Gene Expression Omnibus (GEO) database. Go and KEGG analysis were applied for differentially expressed genes in frozen shoulder, and a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape software. Result: A total of 545 DEGs were obtained, of which 420 genes were up-regulated and 125 genes were down-regulated in frozen shoulder. GO showed that the biological function and molecular function of DEGs were mainly involved in inflammatory response, cell response to TNF and IL-1, extracellular matrix decomposition and remodeling, activation of cytokines and chemokines, and cell adhesion. KEGG pathway involved PI3K/Akt pathway, protein digestion and absorption, ECM-receptor interaction, cytokine-cytokine receptor interaction, focal adhesion. Three hub genes were recognized by PPI analysis, including IL6, COL1A1, COL1A2. Conclusion: Bioinformatics analysis of gene expression profiles in the frozen shoulder patients revealed that inflammatory response and fibrosis mechanisms play an important role in the pathogenesis of frozen shoulder and revealed potential key regulatory genes and related signaling pathways.