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在膝关节骨关节炎 (KOA) 中选TNF信号通路相关基因,使用WGCNA和机器学习

Shaoyang Zhai¹, Rui Wu¹, Shengzhen Fan¹

¹Orthopedic Injury College, Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China.

|August 19, 2025

概括

这项研究揭示了瘤亡因子通路中的关键基因,驱动膝关节骨关节炎 (KOA) 炎症. 研究结果为准确医学方法提供了洞察力,以治疗这种常见的退行性关节疾病.

科学领域:

生物医学科学生物医学科学
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

膝关节骨关节炎 (KOA) 是一种广泛的退行性关节疾病.
它的发病包括复杂的炎症反应和信号通路失调.
瘤亡因子 (TNF) 信号通路在KOA中的作用需要进一步阐明.

研究的目的:

调查TNF信号通路在KOA病变发生过程中的机制性作用.
确定KOA发展的关键基因和分子机制.
为开发针对KOA的向疗法和精准医学提供见解.

主要方法:

不同基因表达分析.
基因本体学 (GO) 和基因和基因组 (KEGG) 丰富分析的京都百科全书.
权重基因共同表达网络分析 (WGCNA).
拉索回归和博鲁塔算法用于基因选择.
免疫透分析.

主要成果:

在KOA中鉴定了222个显著差异表达的基因.
丰富分析强调了参与炎症反应和细胞因子信号传递.
WGCNA确定了一个与KOA相关的关键模块 (MEbrown).
选择了20个关键的TNF信号通路相关基因,包括MCL1,JUN和GADD45B,经过分类验证.
在KOA样本中观察到免疫细胞分布的显著差异.

结论:

这种TNF信号通路在KOA病变发生过程中起着至关重要的作用.
像MCL1,JUN和GADD45B这样的特定基因是KOA中的重要调节者.
炎症和免疫细胞透是KOA进展的核心.
这项研究为KOA个性化治疗策略提供了基础.

关键词:

在TNF信号通路上.在WGCNA中,WGCNA是WGCNA.生物信息学是一种生物信息学.膝盖骨关节炎膝盖骨关节炎机器学习是机器学习.

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