首页|基于生物信息学探讨非酒精性脂肪性肝炎铜死亡相关基因及中药预测

基于生物信息学探讨非酒精性脂肪性肝炎铜死亡相关基因及中药预测

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本研究旨在运用生物信息学方法筛选非酒精性脂肪性肝炎(non-alcoholic steatohepatitis,NASH)的铜死亡相关基因和诊断性生物标志物,并预测调控铜死亡基因治疗NASH的潜在中药.从GEO数据库获取GSE89632数据集作为训练数据集,提取 NASH 中差异表达的铜死亡基因(differentially expressed cuproptosis-related genes,DECRGs),运用R4.2.2软件对DECRGs进行相关性分析和富集分析.基于DECRGs对NASH患者进行聚类分型,构建机器学习模型,筛选关键基因并验证.通过COREMINE数据库预测调控铜死亡基因治疗NASH的潜在中药,运用中医传承计算平台(Traditional Chinese Medicine Inheritance Computer System)v3.5 软件挖掘用药规律.筛选得到 9 个 DECRGs,DECRGs 间存在相互调控的作用,富集分析发现DECRGs主要介导硫辛酸代谢、碳代谢、三羧酸循环等途径干预NASH.共识聚类将NASH患者分为3个亚型;支持向量机模型(support vector machine,SVM)为最合适的机器学习模型;NFE2L2、LI-AS、GLS和GCSH和PDHB等5个与NASH最相关的铜死亡基因可作为NASH的诊断性生物标志物.在调控铜死亡基因治疗NASH的中药中,四气以寒、温、平为主,五味以苦、甘、辛味为主,主归肝、脾经,功效方面以补虚、清热、活血化瘀为主.本研究发现了 NASH的铜死亡相关基因、诊断性生物标志物及对应中药的用药规律,可为中医药治疗NASH的临床应用和新药研发提供思路.
Analysis of Cuproptosis-related Genes in Non-alcoholic Steatohepatitis Based on Bioinformatics and Screening Prediction of Traditional Chinese Medicine
This study aims to screen cuproptosis-related genes and diagnostic biomarkers in non-alcoholic steatohepatitis(NASH)by using bioinformatics methods,and to predict the traditional Chinese medicine for the treatment of NASH by regulating cuproptosis-related genes.The GSE89632 data set was obtained from the GEO database as the training set,and differentially expressed cuproptosis-related genes(DECRGs)were extracted.The R4.2.2 software was used to analyze the correlation and enrichment of DECRGs.Based on DECRGs,NASH patients were classified,machine learning models were constructed to screen key genes,and the accuracy of ma-chine learning model was verified.The traditional Chinese medicine that regulates cuproptosis-related genes therapy for NASH was pre-dicted by COREMINE database.Traditional Chinese Medicine Inheritance Computer System v3.5 was used to mine the law of medica-tion.Nine DECRGs were screened,and there were mutual regulation between DECRGs.Enrichment analysis showed that DECRGs mainly mediated lipoic acid metabolism,carbon metabolism and citrate cycle in the treatment of NASH.Consensus clusters divided NASH patients into three clusters.Support vector machine(SVM)model is the most accurate machine learning model.NFE2L2,LIAS,GLS,GCSH and PDHB were the five cuproptosis-related genes most associated with NASH,which can be used as diagnostic biomarkers of NASH.The four qi of traditional Chinese medicine regulating copper death gene therapy for NASH was mainly cold,warm and neu-tral,the five flavors were mainly bitter,sweet and pungent,and mainly belong to the liver and spleen channel.The main efficacy was deficiency supplementing,clearing heat,blood invigorating and stasis dissolving.This study suggests that cuproptosis-related genes,diagnostic biomarkers and the corresponding medication rules of traditional Chinese medicine in NASH are obtained,which provide a new idea for the clinical application and new drug research and development of traditional Chinese medicine in the treatment of NASH.

Non-alcoholic steatohepatitisCuproptosis-related genesBioinformaticsMachine learningTraditional Chinese medicine prediction

高松林、张鹏、梁馨允、梁菲、管晓、温文建、唐嘉扬、黄贵华

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广西中医药大学研究生院,南宁,530000

柳州市中医医院,柳州,545001

广西中医药大学第一附属医院,南宁,530023

非酒精性脂肪性肝炎 铜死亡相关基因 生物信息学 机器学习 中药预测

广西研究生教育创新计划项目国医大师黄瑾明学术思想与临床诊疗传承发展研究中心建设项目黄贵华广西名中医传承工作室项目

YCBZ2023148桂中医大党[2022]24号桂卫中医发[2017]2号

2024

10.13417/j.gab.043.001111

基因组学与应用生物学
广西大学

基因组学与应用生物学

CSTPCD北大核心
影响因子：1.108
ISSN：1674-568X
年,卷(期)：2024.43(6)
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