[关键词]
[摘要]
目的 基于生物信息学及机器学习分析溃疡性结肠炎(UC)的免疫微环境特征及免疫相关生物标志物, 并预测治疗 UC 的潜在中药。方法 基于 GEO 数据库训练集 GSE87473 筛选 UC 的差异表达基因(DEGs),结 合免疫浸润、加权基因共表达网络分析(WGCNA)、Immport 数据库的人类免疫基因集(IRGs)来识别 UC 的免疫 特征基因。借助最小绝对收缩和选择算子(LASSO)、支持向量机递归特征消除(SVM-RFE)筛选 UC 生物标志 物,并通过训练集 GSE87473 与验证集 GSE47908 进行验证。采用基因富集分析(GSEA)阐述生物标志物的生物 功能,利用 Herb 数据库预测治疗 UC 的潜在中药,并分析其性味、归经。结果 UC 的 DEGs 显著富集于免疫 相关途径,记忆性 B 细胞、M1 巨噬细胞、激活的肥大细胞、中性粒细胞、M0 巨噬细胞、激活的树突状细胞、 激活的记忆性 CD4+ T 细胞、静息 NK 细胞在 UC 中高表达;M2 巨噬细胞、浆细胞、CD8+ T 细胞、静息肥大细 胞、静息树突状细胞、激活的 NK 细胞在 UC 中低表达。生物标志物包括:ACVR1C、DEFB1、FCGRT、 NR1H4、VIPR1,主要参与细胞免疫代谢调控。紫苏叶、麻黄、沙棘等是重要的治疗 UC 的潜在中药。潜在治 疗 UC 的中药以清热、温里、理气、活血类为主,药味偏甘、苦、辛,药性偏温、寒,多归肝、脾、胃、肺、 肾经。结论 免疫失衡是 UC 发病的核心机制,ACVR1C、DEFB1、FCGRT、NR1H4、VIPR1 作为 UC 的生物 标志物,可能通过调节免疫细胞代谢途径参与 UC 的发生发展。
[Key word]
[Abstract]
Objective To analyze the immune microenvironment characteristics and immune-related biomarkers of ulcerative colitis (UC) based on bioinformatics and machine learning,and to predict potential Chinese medicinals for treating UC. Methods Differentially expressed genes (DEGs) of UC were screened from the training set GSE87473 in the GEO database. Immune infiltration,weighted gene co-expression network analysis (WGCNA),and the human immune-related genes (IRGs) from the Immport database were combined to identify immune signature genes in UC. The least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) were used to screen UC biomarkers, which were validated using the training set GSE87473 and the validation set GSE47908. Gene set enrichment analysis (GSEA) was employed to elucidate the biological functions of the biomarkers. The Herb database was utilized to predict potential Chinese medicinals for treating UC, and their properties,flavors,and meridian tropism were analyzed. Results DEGs of UC were significantly enriched in immunerelated pathways. Memory B cells,M1 macrophages,activated mast cells,neutrophils,M0 macrophages,activated dendritic cells,activated memory CD4+ T cells,and resting NK cells were highly expressed in UC;M2 macrophages, plasma cells,CD8+ T cells,resting mast cells,resting dendritic cells,and activated NK cells were lowly expressed in UC. Biomarkers included ACVR1C, DEFB1, FCGRT, NR1H4, and VIPR1, which are mainly involved in the regulation of cellular immune metabolism. Perillae Folium, Ephedrae Herba, Hippophae Fructus are important potential Chinese medicinals for treating UC. The potential Chinese medicinals for UC treatment are primarily classified as heat-clearing,interior warming,qi-regulating,and blood-activating,with flavors tending to be sweet,bitter, and pungent,and properties tending to be warm and cold,targeting the liver,spleen,stomach,lung,and kidney meridians. Conclusion Immune imbalance is the core mechanism of UC pathogenesis. ACVR1C,DEFB1,FCGRT, NR1H4, and VIPR1, as biomarkers of UC, may participate in the development of UC by regulating immune cell metabolic pathways.
[中图分类号]
R285.5;R857.3
[基金项目]
国家自然科学基金项目(82060850);湖南省自然科学基金项目(2022JJ70031,2024JJ9435);湖南省中医药科研一般课题项目 (B2024047);中药粉体与创新药物省部共建国家重点实验室培育基地开放基金项目(23PTKF1010);湖南省中医重点专科[一类,湘中医药函 (2023)4号]。