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作 者:李红 穆姣 禹红[1] LI Hong;MU Jiao;YU Hong(Department of Clinical Laboratory,Wuhan Hospital of Traditional Chinese Medicine,Wuhan 430000,Hubei;Department of Clinical Laboratory,Huanggang Central Hospital,Huanggang 438000,Hubei,China)
机构地区:[1]武汉市中医医院检验科,武汉430000 [2]黄冈市中心医院检验科,湖北黄冈438000
出 处:《临床检验杂志》2024年第6期461-465,共5页Chinese Journal of Clinical Laboratory Science
基 金:武汉市卫健委中医药科研项目(WZ22C69);武汉市医学科学研究项目(WX23A19)。
摘 要:目的应用生物信息学方法筛选系统性红斑狼疮(SLE)妊娠并发先兆子痫(PE)的关键基因,并分析其生物学功能。方法从高通量基因表达(GEO)数据库下载SLE妊娠并发PE相关数据集GSE108497,利用R软件筛选差异表达基因(DEGs)。采用在线分析工具对DEGs进行基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)通路富集分析。利用蛋白质相互作用数据库STRING构建DEGs编码蛋白的相互作用(PPI)网络,并筛选关键基因。绘制受试者工作特征(ROC)曲线评估关键基因对SLE妊娠并发PE的诊断效能。结果从GSE108497数据集中筛选出162个DEGs,其中105个上调,57个下调。GO分析显示,DEGs主要参与T淋巴细胞活化与分化、中性粒细胞介导的免疫调节和脱颗粒等生物学过程。KEGG分析表明,DEGs主要调控原发性免疫缺陷、糖酵解和抗原呈递等通路。PPI网络分析获得9个关键基因:HMGN2、EEFIB2、RPL32、BTF3、MRPLI1、EEFID、EEFIA1、RPL6和RPLPI。ROC曲线提示这些基因对SLE妊娠并发PE具有较高诊断价值,ROC曲线下面积(AUCROC)均大于0.9。结论利用生物信息学方法从GEO数据库筛选并鉴定出9个与SLE妊娠并发PE相关的关键基因,为该病的诊断和治疗提供了新的潜在标志物和靶点。Objective To identify the key genes associated with preeclampsia in the pregnant women with systemic lupus erythematosus(SLE)using bioinformatics methods and analyze their biological functions.Methods The gene expression dataset GSE108497 related to preeclampsia in SLE pregnancy was obtained from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were screened using R software.Gene Ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed on the DEGs using online analysis tools.A protein-protein interaction(PPI)network was constructed using the STRING database to identify the key genes.Receiver operating characteristic(ROC)curves were plotted to evaluate the diagnostic efficacy of the key genes for preeclampsia in SLE pregnancy.Results A total of 162 DEGs were i-dentified from the GSE108497 dataset,including 105 upregulated and 57 downregulated genes.GO analysis revealed that the DEGs were mainly involved in T lymphocyte activation and differentiation,neutrophil-mediated immune regulation and degranulation.KEGG analysis indicated that DEGs primarily regulate pathways involved in primary immunodeficiency,glycolysis and antigen presentation.PPI network analysis identified 9 key genes:HMGN2,EEFIB2,RPL32,BTF3,MRPLIl,EEFID,EEFIAl,RPL6 and RPLP1.ROC curve analysis suggested that these genes had high diagnostic value for preeclampsia in SLE pregnancy with areas under the curve(AUCROC)greater than O.9.Conclusion This study identified 9 key genes associated with preeclampsia in SLE pregnancy using bioinformatics analysis of the GEO database.These findings provide potential biomarkers and therapeutic targets for the diagnosis and treatment of preeclampsia in SLE pregnancy.
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