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使用WGCNA和机器学习算法识别和验证与COPD免疫透相关的线粒体相关基因生物标志物

Meijuan Peng¹, Chen Jiang¹, Ziyu Dai¹

¹Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha, 410008, Hunan, China.

Scientific reports

|April 24, 2025

概括

线粒体功能障碍是慢性阻塞性肺病 (COPD) 的关键. 这项研究确定了用于诊断COPD的五个关键线粒体基因 (MitoDEGs),并揭示了它们与免疫细胞的联系,提供了新的治疗途径.

科学领域:

线粒体生物学线粒体生物学
生物信息学是一种生物信息学.
免疫学免疫学免疫学

背景情况:

线粒体功能障碍是慢性阻塞性肺病 (COPD) 病原体的核心.
了解线粒体基因与COPD免疫微环境之间的相互作用至关重要.

研究的目的:

使用生物信息学和机器学习识别与COPD相关的关键线粒体相关基因 (MitoDEGs).
开发一种基于这些MitoDEGs的COPD诊断模型.
探索MitoDEGs,免疫细胞透和COPD潜在治疗点之间的关系.

主要方法:

基因表达综合 (GEO) 数据集 (GSE57148) 的分析,使用limma和权重基因共同表达网络分析 (WGCNA).
应用12个机器学习算法,从12个关键的MitoDEG中确定一个预测诊断模型.
在独立队列上使用接收器操作特征 (ROC) 曲线验证诊断模型 (GSE76925,GSE151052,GSE239897).
表达式分析和斯皮尔曼相关性,以评估与免疫细胞透的MitoDEG关联.

主要成果:

确定了12个关键的MitoDEGs,其中ERN1,FASTK,HIGD1B,NDUFA7和NDUFB7形成了一个最佳的诊断模型.
该模型在验证队列中显示出高特异性.
在COPD患者中,ERN1是上调的,而FASTK,HIGD1B,NDUFA7和NDUFB7是下调的.
线性DEG与免疫细胞透有显著的相关性,尤其是中性粒细胞.
安德罗醇被确定为潜在的治疗候选物;体内研究证实了COPD小鼠的减少HIGD1B和NDUFB7mRNA.

结论:

在COPD病变发生过程中阐明了关键的线粒体-免疫相互作用.
突出了用于COPD诊断的新型五基因线粒体特征.
确定了COPD潜在的诊断生物标志物和治疗点,包括安德罗醇.

关键词:

慢性慢性肺炎是一种慢性慢性肺炎,COPD是一种慢性肺炎.免疫系统的透.机器学习是机器学习.与线粒体相关的基因

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