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2024-5-25
Vol 32, issue 5

ISSUE

2023 年3 期 第31 卷

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基于生物信息学技术筛选缺血性脑卒中相关转录因子及中药活性成分研究

ScreeningofIschemicStroke-RelatedTranscriptionFactorsandActiveIngredientsofChineseMedicineBasedonBioinformaticsTechnology

作者:魏汝恒,苗珠月,戴瑶瑶,刘可心,韩光远,张海飞,宋丽娟,马东,马存根

单位:
1.山西中医药大学神经生物学研究中心国家中医药管理局多发性硬化益气活血重点研究室2.山西大同大学脑科学研究所大同市第五人民医院大同大学附属第一临床医院神经科3.国药同煤集团总医院神经外科山西省卫生健康委员会神经疾病防治重点实验室4.山西医科大学细胞生理学省部共建教育部重点实验室
Units:
1.TheKeyResearchLaboratoryofBenefitingQiforActingBloodCirculationMethodtoTreatMultipleSclerosisofStateAdministrationofTraditionalChineseMedicine/ResearchCenterofNeurobiology,ShanxiUniversityofChineseMedicine,Jinzhong030619,China2.ShanxiDatongUniversityInstituteofBrainScience/DepartmentofNeurology,DatongFifthPeople'sHospital/theFirstAffiliatedClinicalHospitalofDatongUniversity,Datong037009,China3.DepatmentofNeurosurgery,GeneralHospitalofSinopharmTongliangGroup/ShanxiProvincialHealthCommissionKeyLaboratoryofNeurologicalDiseaseControl,Datong037003,China4.MinistryofEducationKeyLaboratoryofCellPhysiology,ShanxiMedicalUniversity,Taiyuan030001,China
关键词:
卒中; 缺血性脑卒中; 生物信息学; 转录因子; 中药;
Keywords:
Stroke;Ischemicstroke;Bioinformatics;Transcriptionfactors;TraditionalChinesedrugs
CLC:
R743
DOI:
10.12114/j.issn.1008-5971.2023.00.044
Funds:
国家自然科学基金资助项目( 81473577?,82004028?);中国博士后科学基金面上资助项目( 2020M680912?);山西省?应用基础研究计划项目( 201901D211538?); 山西中医药大学学科建设经费、山西省卫健委医学科技领军团队( 2020TD05?); 中枢?神经炎症变性疾病新药创制省市共建山西省重点实验室培育基地立项建设项目( 201805D111009?);山西省教育厅高等学校科技创新 项目( 2019L0734?); 2021年山西中医药大学附属医院国家区域中医医疗中心心血管专项基金项目( XGZX202115?);山西中医药大?学青年科学家培育项目( 2021PY-QN-09?);山西省研究生创新项目( 2021Y733?,2021Y732?);山西中医药大学2021年研究生创新 创业项目( 2021CX036,2021CX037?)

摘要:

目的 基于生物信息学技术筛选缺血性脑卒中(IS)相关转录因子(TF)及中药活性成分。方法 在基因表达综合数据库(GEO)中选择GSE16561、GSE58294、GSE162955芯片数据集,使用R 4.0.5软件对GSE16561、GSE58294数据集进行预处理并筛选差异表达基因(DEGs),然后进行基因集富集分析(GSEA)。通过STRING平台构建DEG的蛋白质-蛋白质相互作用(PPI)网络并筛选关键DEG,通过GSE162955数据集绘制ROC曲线,以评估关键DEG对IS的诊断价值;然后通过TRRUST平台构建TF-miRNA-核心DEG调控网络,筛选枢纽TF、主要miRNA及核心DEG。通过Coremine Medical及Uniprot平台预测并筛选IS相关中药活性成分。结果 韦恩图结果显示,GSE16561数据集和GSE58294数据集的交集DGEs共220个,包括130个上调DGEs和90个下调DEGs。GSEA结果显示,KEGG通路主要富集在MAPK信号通路、神经营养因子信号通路和趋化因子信号通路;GO功能生物过程主要富集在中心粒细胞外渗,细胞成分主要富集在细胞器内膜,分子功能主要富集在电子传递活动。通过PPI网络共筛选出10个关键DEG,其中Janus激酶(JAK)2[AUC=0.944,95%CI(0.816,1.000)]、Toll样受体(TLR)4[AUC=0.833,95%CI(0.580,1.000)]、CD247[AUC=0.667,95%CI(0.309,1.000)]、CC趋化因子受体(CCR)7[AUC=0.639,95%CI(0.273,1.000)]、基质金属蛋白酶(MMP)9[AUC=0.861,95%CI(0.641,1.000)]、FCGR2A[AUC=0.722,95%CI(0.361,1.000)]对IS具有一定诊断价值。TF-miRNA-核心DEG调控网络分析结果显示,枢纽TF为SPI1、信号转导因子和转录激活因子(STAT)3、缺氧诱导因子(HIF)1A、RELA,主要miRNA为hsa-miR-8085、hsamiR-183、hsa-miR-324-3p,核心DEG为JAK2、TLR4、CCR7、MMP9。通过Coremine Medical及Uniprot平台筛选出的IS相关主要中药活性成分为槲皮素、山柰酚、β-谷甾醇、豆甾醇、黄芩苷、人参皂甙rh2。结论 IS相关的枢纽TF为RELA、SPI1、HIF1A和STAT3,主要miRNA为hsa-miR-8085、hsa-miR-183-5p和hsa-miR-324-3p,核心DEG为JAK2、TLR4、CCR7、MMP9,中药活性成分为槲皮素、山柰酚、β-谷甾醇、豆甾醇、黄芩苷、人参皂甙rh2。

Abstract:

ObjectiveToscreenischemicstroke(IS)-relatedtranscriptionfactors(TF)andactiveingredientsof Chinesemedicinebasedonbioinformaticstechnology.MethodsTheGSE16561,GSE58294andGSE162955datasetswereselectedintheGeneExpressionOmnibus(GEO)database,andtheGSE16561andGSE58294datasetswerepreprocessedandscreenedfordifferentiallyexpressedgenes(DEGs)usingR4.0.5software,followedbygenesetenrichmentanalysis(GSEA).Theprotein-proteininteractions(PPI)networkofDEGwasconstructedbytheSTRINGplatformandscreenedforkeyDEG,andROCcurvewasdrawnbytheGSE162955datasettoevaluatethediagnosticvalueofkeyDEGforIS;andthentheTF-miRNA-hubDEGnetworkwasconstructedthroughTRRUSTplatformtoscreenthekeyTF,primarymiRNAsandhubDEG.TheactiveingredientsofIS-relatedChinesemedicineswerepredictedandfilteredbyCoremineMedicalandUniprotplatforms.Results Venndiagramresultsshowedthattherewere220intersectingDGEsbetweentheGSE16561datasetandtheGSE58294dataset,including130upregulatedDGEsand90downregulatedDEGs.GSEAresultsshowedthatKEGGpathwaywasmainlyenrichedinMAPKsignalingpathway,neurotrophicfactorsignalingpathwayandchemokinesignalingpathway;GOfunctionalbiologicalprocesseswasmainlyenrichedincentralgranulocyteextravasation,cellcomponentswasmainlyenrichedintheinnermembraneoforganelles,andmolecularfunctionswasmainlyenrichedinelectrontransportactivities.Atotalof10keyDEGswerescreenedbythePPInetwork,amongthem,Januskinase(JAK)2[AUC=0.944,95%CI(0.816,1.000)],Toll-likereceptor(TLR)4[AUC=0.833,95%CI(0.580,1.000)],CD247[AUC=0.667,95%CI(0.309,1.000)],CCchemokinereceptor(CCR)7[AUC=0.639,95%CI(0.273,1.000)],matrixmetallopeptidase(MMP)9[AUC=0.861,95%CI(0.641,1.000)],FCGR2A[AUC=0.722,95%CI(0.361,1.000)]hadsomediagnosticvalueforIS.TF-miRNA-hubDEGnetworkanalysisshowedthatthehubTFwasSPI1,signaltransducerandactivatoroftranscription(STAT)3,hypoxiainduciblefactor(HIF)1AandRELA,theprimarymiRNAswerehsa-miR-8085,hsa-miR-183andhsa-miR-324-3p,andthekeyDEGswereJAK2,TLR4,CCR7andMMP9.ThemainactiveingredientsofIS-relatedChinesemedicinesscreenedthroughCoremineMedicalandUniprotplatformwerequercetin,kaempferol,β-sitosterol,dousterol,baicalin,andginsenosiderh2.ConclusionIS-relatedkeyTFsareRELA,SPI1,HIF1AandSTAT3,primarymiRNAsarehsa-miR-8085,hsa-miR-183andhsa-miR-324-3p,hubDEGareJAK2,TLR4, CCR7,andMMP9,andtheactiveingredientsofChinesemedicinearequercetin,kaempferol,β-sitosterol,dousterolbaicalinandginsenosiderh2.

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