通过机器学习和多omics分析来探索脊髓损伤中NETosis相关基因的潜在生物标志物
Xinliao Sun1, Yuchang Gui1, Yuting Lu1
1Department of Rehabilitation Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530000, China.
Biochemistry and biophysics reports
|February 2, 2026
概括
这项研究确定了像NLRP3,LRG1和TLR8这样的关键中性细胞外细胞陷相关基因 (NRG),作为脊髓损伤 (SCI) 的潜在生物标志物. 这些发现为SCI治疗提供了新的诊断和治疗途径.
科学领域:
- * 神经科学是一门神经科学.
- * 免疫学 免疫学
- * 生物信息学是一门学科.
背景情况:
- *脊髓损伤 (SCI) 由于有效治疗方法有限而带来了重大挑战,由初级和二级损伤机制复杂化.
- * 中性细胞外细胞陷 (NETs) 通过增加炎症和阻碍神经修复,使二次SCI恶化.
- *了解SCI中NET的分子基础对于开发向疗法至关重要.
研究的目的:
- * 用综合生物信息学方法阐明脊髓损伤 (SCI) 中与中性粒细胞外陷相关的基因 (NRG) 的分子基础.
- * 确定SCI的潜在诊断生物标志物和治疗点.
- * 探索NRG与SCI病理过程之间的关系.
主要方法:
- *使用GSE151371数据集 (38名SCI患者,10名对照组) 进行基因表达分析.
- *识别了差异表达基因 (DEGs) 并进行了功能丰富分析 (GO,KEGG).
- * 采用权重基因协同表达网络分析 (WGCNA),用于预测建模的机器学习,以及在老鼠SCI模型和临床样本中验证的多omics分析.
主要成果:
- *确定了4878个DEG和免疫细胞透的显著差异 (中性粒细胞,B细胞记忆,巨细胞M0).
- *从与SCI相关的WGCNA识别模块中选择了12个候选基因.
- * 开发了一个预测模型,确定NLRP3,LRG1和TLR8作为具有高诊断潜力的关键基因 (AUC>0.9).
结论:
- * 中性细胞外细胞陷相关基因 (NRG),特别是NLRP3,LRG1和TLR8,在SCI中显示出显著的诊断潜力.
- *这些NRG与SCI病原和免疫细胞动态密切相关.
- * 针对NETs形成是一个有前途的治疗策略,可以改善SCI的结果.
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