基于生物信息学分析活动期溃疡性结肠炎铜死亡相关基因及调控中药预测

Analysis of cuproptosis-related genes in active ulcerative colitis based on bioinformatics and prediction of regulatory traditional Chinese medicine

目的基于生物信息学探究铜死亡相关基因在活动期溃疡性结肠炎(ulcerative colitis,UC)中的表达及作用机制,并筛选可对铜死亡相关基因起调控作用的中药。方法从GEO数据库中获取活动期UC相关数据集;以GSE11223数据集为训练集提取差异表达的铜死亡相关基因(differentially expressed cuproptosis-related genes,DECRGs),分析DECRGs之间的相关性及DECRGs相关的免疫浸润和生物学功能。根据DECRGs的表达量对活动期UC患者进行共识聚类分型,基于分型进行加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)来识别核心基因。构建机器学习模型筛选活动期UC特征基因并验证其对活动期UC患病风险的预测能力。最后进行中药预测并通过中医传承计算平台(V3.5)统计中药的出现频次、性味归经和药物分类。结果共获得11个DECRGs,DECRGs具有相互调控和免疫调节作用。共识聚类将活动期UC分为2个亚型,WGCNA获得核心基因234个。机器学习模型预测人中胚层特异性转录基因(mesoderm-specific transcript,MEST)、跨膜蛋白98(transmembrane protein 98,TMEM98)、晶状体蛋白λ1(crystallin lambda 1,CRYL1)、染色体14开放阅读框(chromosome 14 open reading frame 147,C14orf147)和跨膜蛋白141(transmembrane protein 141,TMEM141)是活动性UC的特征基因。预测得到的中药四气以温、寒、平为主;五味以苦、甘、辛为主;归经以肝、脾经居多;高频中药为白术、丹参、莪术、紫草等;以清热药、补虚药和活血化瘀药为主。结论铜死亡在活动期UC的发生、发展和诊断中起重要作用。白术、丹参、莪术、紫草等高频中药可能通过调节铜死亡相关基因治疗活动期UC,可为活动期UC的临床治疗提供参考依据。

Objective To explore the expression and mechanism of cuproptosis-related genes in active ulcerative colitis(UC)based on bioinformatics,and to screen traditional Chinese medicine with function of regulateing cuproptosis-related genes.Methods Data sets related to active UC were obtained from Gene Expression Omnibus(GEO)database.Using GSE11223 datasets set as training set,differentially expressed cuproptosis-related genes(DECRGs)were extracted.The correlation between DECRGs and the immune infiltration and biological function of DECRGs were analyzed.According to the expression of DECRGs,active UC patients were classified by consensus clusters,and the core genes were identified by weighted gene co-expression network analysis(WGCNA)based on the classification.Machine-learning models were constructed to screen genes most related to the characteristics of active UC.Then,the predictive ability of these genes for the risk of active UC was tested.Finally,the prediction of traditional Chinese medicine was carried out and the frequency,nature,flavors and channel entry and function classification of traditional Chinese medicine were counted through the Traditional Chinese Medicine Inheritance Computer System(V3.5).Results A total of 11 DECRGs were obtained,and DECRGs had the function of mutual regulation and immune regulation.Consensus clusters divided active UC patients into two isoforms.A total of 234 core genes were obtained by WGCNA.The machine-learning model predicted that mesoderm-specific transcript(MEST),transmembrane protein 98(TMEM98),crystallin lambda 1(CRYL1),chromosome 14 open reading frame 147(C14orf147)and transmembrane protein 141(TMEM141)were the most relevant genes for active UC.The prediction results of traditional Chinese medicine showed that the nature and flavors were mainly warm,cold,peaceful,bitter,sweet and pungent,and channel entry was mostly liver and spleen.The high-frequency traditional Chinese medicines are Baizhu(Atractylodis Macrocephalae Rhizoma),Danshen(Salviae Miltiorrhizae Radix et Rhizoma),Ezhu(Curcumae Rhizoma)and Zicao(Arnebiae Radix).The categories were mainly clearing heat herbs,deficiency supplementing herbs,and blood invigorating and stasis dissolving herbs.Conclusion Cuproptosis plays an important role in the occurrence,development and diagnosis of active UC.Atractylodis Macrocephalae Rhizoma,Salviae Miltiorrhizae Radix et Rhizoma,Curcumae Rhizoma,Arnebiae Radix and other high-frequency traditional Chinese medicines may treat active UC by regulating cuproptosis-associated genes,which can provide reference for the clinical treatment of active UC.