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Updated: May 10, 2025

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综合生物信息学分析揭示了STAT1,ORC2和GTF2B作为狼性炎与病毒感染中的关键生物标志物

Yaojun Wang¹, Qiang Li²

¹Clinical Medical College, Affiliated Hospital, Hebei University, Baoding, 071000, Hebei, China. 16585260@qq.com.

Scientific reports

|April 19, 2025

概括

这项研究探讨了病毒 (MPXV) 感染如何影响狼性炎 (LN). 它识别了参与衰老和免疫功能障碍的关键基因 (STAT1,ORC2,GTF2B),为这种共感染提供了潜在的诊断标.

科学领域:

免疫学免疫学免疫学
病毒学病毒学
基因组学就是基因组学.

背景情况:

病毒 (MPXV) 的全球传播引发了人们对其与狼性炎 (LN) 等自身免疫性疾病的潜在相互作用的担忧.
影响MPXV对LN病变的机制在很大程度上仍未被探索.

研究的目的:

在狼性炎的背景下调查MPXV感染的作用和潜在机制.
为了确定关键的分子参与者和潜在的诊断生物标志物共感染患者.

主要方法:

使用了差异基因表达分析 (Limma) 和权重基因同表达网络分析 (WGCNA).
进行了KEGG和基因本体学 (GO) 丰富分析,蛋白质-蛋白质相互作用 (PPI) 网络构建和LASSO回归.
诺莫图,ROC曲线,免疫透分析,GSEA和miRNA-mRNA-TF网络构建被用于验证和进一步探索.

主要成果:

在LN中确定了5707个差异表达基因 (DEG),在MPXV数据中确定了737个DEG.
确定了STAT1,ORC2和GTF2B作为与衰老和免疫失调相关的关键基因.
预测模型证明了这些关键基因的良好诊断价值;观察到免疫细胞障碍和通路激活.

结论:

STAT1,ORC2和GTF2B被确定为MPXV感染的LN患者细胞衰老和免疫失调的关键因素.
这些基因代表潜在的预测生物标志物,用于诊断和管理共感染.
这项研究强调了MPXV和LN之间的复杂相互作用,为治疗策略提供了洞察力.

关键词:

生物标志物生物标志物机器学习机器学习的水是一种天花.衰老; 狼性炎

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