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基于单细胞RNA-seq数据的骨关节炎相关基因和潜在药物的鉴定

Ning Wang¹, Kun Liu¹, Jia-Li Li¹

¹Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China.

Molecular medicine (Cambridge, Mass.)

|November 26, 2025

概括

这项研究通过分析基因表达数据和斑马鱼模型,确定Pitavastatin作为骨关节炎 (OA) 的潜在治疗方法. 相反,Cabazitaxel被发现增加了关节炎的风险,突出了明显的治疗潜力.

科学领域:

基因组学和生物信息学
药理学药理学是指药理学的学科.
翻译医学是一种翻译医学.

背景情况:

骨关节炎 (OA) 是一个重大的全球健康挑战,有效治疗方法有限.
对于用于预防和治疗OA的新型治疗药物的需求尚未得到满足.

研究的目的:

使用多omics数据识别与OA相关的关键基因.
选潜在的候选药物用于OA治疗.
在临床前模型中评估候选药物的治疗效果.

主要方法:

单细胞和大批RNA测序 (scRNA-seq,大批RNA-seq) 数据分析.
高维加权相关联网络分析 (hdWGCNA),随机森林和蛋白质与蛋白质相互作用 (PPI) 网络分析.
门德尔随机化 (MR),药物预测算法 (SAVERUNNER) 和斑马鱼OA模型.

主要成果:

已经确定了五个关键的OA相关基因 (CXCL8,CCL20,MMP3,BIRC3,ICAM1).
门德尔随机化表明,增加TUBB1表达减少了OA风险,卡巴西塔克塞尔通过抑制TUBB1增加了OA风险.
斑马鱼实验表明,通过增加关节空间,Pitavastatin在OA中的治疗作用是显著的,而Cabazitaxel则使OA恶化.
通过RT-qPCR证实皮塔瓦斯塔丁抑制了HMGCR,卡巴西塔克塞尔抑制了斑马鱼的TUBB1表达.

结论:

皮塔瓦斯塔丁对骨关节炎具有治疗潜力.
卡巴西塔克塞尔可能会增加骨关节炎的风险.
本研究提供了一种多学科和实验验证方法,用于识别OA治疗方法.

关键词:

药物重新定位药物重新定位门德尔的随机化基于网络的分析.骨关节炎是一种骨关节炎.

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