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基于机器学习,识别铜死亡相关的分子和腰椎间盘的免疫学概况

Haipeng Xu¹, Yaheng Jiang¹, Ya Wen¹

¹Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310000, China.

Scientific reports

|August 20, 2024

概括

这项研究探讨了腰椎间盘 (LDH) 中的cuproptosis相关基因,确定了潜在的诊断生物标志物. 结果揭示了与LDH相关的特定基因群和免疫透,提供了一个新的预测模型.

科学领域:

生物化学生物化学
遗传学是一个遗传学.
免疫学免疫学免疫学

背景情况:

腰椎间盘 (LDH) 是一种普遍存在的脊髓疾病,病因不明.
与cuproptosis相关的基因 (CRG) 和它们在细胞过程中的作用越来越被认可.
了解LDH的分子基础对于开发诊断工具至关重要.

研究的目的:

调查与cuproptosis相关的基因 (CRGs) 和腰椎椎间盘 (LDH) 之间的关联.
根据CRG表达特征识别LDH的潜在诊断生物标志物.
探索与CRG相关的LDH患者的免疫微环境特征.

主要方法:

使用公共数据集 (GSE124272,GSE150408) 进行CRG的差异基因表达分析.
对LDH样本进行分子聚类,以识别不同的CRG相关群.
权重基因共同表达网络分析 (WGCNA) 以确定关键的CRG.
用于诊断生物标志物选择和验证的机器学习模型 (XGBoost).

主要成果:

在LDH中,九个CRG被确定与铜调节细胞死亡有显著的关联.
在LDH样本中检测到两个不同的与铜相关的分子.
在LDH患者中观察到CRG表达和免疫细胞透的增加,特别是在C2.
一个包含五个基因的诊断模型实现了0.715的AUC.

结论:

这项研究强调了铜调节的细胞死亡途径和腰椎间盘椎间盘之间的重要联系.
CRG和相关的免疫透模式可以作为LDH的有价值的诊断指标.
开发的预测模型对LDH的早期检测和管理充满希望.

关键词:

铜与死亡相关的分子团.免疫学概况免疫学概况腰椎椎间盘的发生机器学习机器学习

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