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基于GEO数据库对类风湿关节炎和骨关节炎之间差异表达基因和生物信息的分析

Zeli Li¹, Li Guohai², Qianwen Xiong³

¹Dongguan Hospital of Guangzhou University of Chinese Medicine (Dongguan Traditional Chinese Medicine Hospital), Dongguan, Guangdong Province, People's Republic of China.

Nucleosides, nucleotides & nucleic acids

|August 20, 2025

概括

这项研究利用生物信息学发现了类风湿性关节炎 (RA) 中的关键基因,揭示了免疫和炎症途径. CD3D,CD27,KLRB1,CCL5和GZMB与RA的发展有显著的联系.

科学领域:

生物信息学
基因组学
免疫学

背景情况:

风湿性关节炎是一种慢性炎症疾病.
了解RA的分子机制对于开发向疗法至关重要.
骨关节炎 (OA) 有一些共同的炎症途径,促使研究共同的遗传因素.

研究的目的:

通过生物信息学识别类型关节炎的差异表达基因 (DEGs).
探索RA的潜在生物过程和分子机制.
确定与RA发病相关的潜在关键基因 (枢纽基因).

主要方法:

从基因表达综合数据库 (GEO) 获取和分析RA和骨关节炎 (OA) 基因表达数据集 (GSE55584,GSE153015).
使用R语言识别差异表达基因 (DEG).
基因本体学 (GO) 和基因和基因组的京都百科全书 (KEGG) 丰富分析.
使用STRING和Cytoscape构建蛋白与蛋白相互作用 (PPI) 网络并选核心基因 (枢纽基因).

主要成果:

共有665个DEG被确定,包括324个上调和341个下调的基因.
丰富分析表明DEGs在信号转导,免疫反应,炎症反应和G蛋白结合受体信号传递中具有显著的参与.
关键的丰富途径包括细胞因子-细胞因子受体相互作用,化学因子信号传递和细胞亡.
确定了10个枢纽基因,其中CD3D,CD27,KLRB1,CCL5和GZMB与RA发生和发展的相关性最强.

结论:

生物信息学分析成功地确定了关键的生物过程和参与RA病变的候选基因.
已识别的枢纽基因,特别是CD3D,CD27,KLRB1,CCL5和GZMB,代表了RA的潜在治疗点.
这项研究为在RA研究中进一步实验验证这些发现提供了基础.

关键词:

不同表达的基因地质数据库膝关节关节炎类风湿性关节炎

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