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作 者:赵威 魏广友[2] Zhao Wei;Wei Guangyou(College of Medicine,Anhui University of Science and Technology,Huainan232000,China)
机构地区:[1]安徽理工大学医学院,安徽淮南232000 [2]亳州市人民医院儿科
出 处:《华北理工大学学报(医学版)》2023年第4期253-259,282,共8页Journal of North China University of Science and Technology:Health Sciences Edition
基 金:国家卫生计生委医药卫生科技发展研究课题(编号:WA2020HK60);白求恩医学科学研究基金支持项目(编号:SCE159EN)。
摘 要:目的在幼年皮肌炎(JDM)患者通过生物信息联合免疫分析筛选幼年皮肌炎基因,构建预测模型、绘制列线图并验证,旨在探索其在JDM诊断中的潜在价值。方法通过基因表达综合数据库(GEO)下载的GSE11083和GSE11971数据集为基因表达阵列进行合并,利用R语言筛选差异表达基因。通过ssGSEA计算数据集的免疫评分,随后分别进行疾病组与正常组之间免疫的差异分析。作PPI网络并筛选Hub基因,通过Hub基因与免疫分析选出最相关基因。利用筛选基因构建预测模型、绘制列线图及选取独立GSE100152数据集验证。结果两个数据集合并共获得29个差异表达的基因。免疫细胞差异分析显示JDM患者的激活树突状细胞表达水平较高,免疫功能差异分析显示JDM患者的树突状细胞的抗原提呈细胞、非经典炎症、I型干扰素反应这三种免疫功能表达水平较高。通过PPI网络选出10个Hub基因,再次筛选出5个与免疫最为相关的基因,分别为GBP1、IFIT3、IFIT1、OAS2、MX2。利用5个基因构建模型及独立数据集验证,发现OAS2基因与JDM具有较高的预测诊断价值。结论本研究认为的OAS2基因可能成为JDM诊断的生物标记物及潜在的治疗靶点,并提出I型干扰素的反应可能是调节JDM的潜在分子途径。Objective This study aimed to explore the potential value of related genes in the diagnosis of juvenile dermatomyositis(JDM)by using biological information combined with immunoassay to screen genes,construct prediction models,draw nomogram and validate them.Methods The GSE11083 and GSE11971 datasets downloaded from GEO were merged into gene expression arrays,and R was used to screen differentially expressed genes.The immunity score of the dataset was calculated by ssGSEA,and then the difference of immunity between the disease group and the normal group was analyzed.PPI network and Hub gene screening,Hub gene and immunoassay to identify the most relevant genes.Prediction model was constructed by screening genes,nomogram was drawn,and independent GSE100152 dataset was selected for verification.Results Twenty-nine genes were differentially expressed in the two data sets.The difference analysis of immune cells showed that JDM patients had higher levels of activated dendritic cells,and the difference of immune function showed that JDM patients had higher levels of dendritic cells antigen presenting cells,non-classical inflammation,and type 1 interferon response.Ten Hub genes were selected through PPI network,and five genes most related to immunity were screened out again,which were GBP1,IFIT3,IFIT1,OAS2 and MX2.The OAS2 gene and JDM have high predictive and diagnostic value by using five gene models and independent data sets.Conclusion The OAS2 gene identified in this study may be a biomarker for the diagnosis of JDM and a potential therapeutic target,and the type I interferon response may be a potential molecular pathway to regulate JDM.
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