Feng Bin, Zhou Tong, Guo Zhiyi, Jin Jieyu, Zhang Sheng, Qiu Jun, Cao Jun, Li Jia, Peng Xia, Wang Juan, Xing Yanru, Ji Renxin, Qiao Longwei, Liang Yuting
Center for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Medical College of Soochow University Suzhou 215006, Jiangsu, China.
Am J Transl Res. 2023 Feb 15;15(2):1052-1062. eCollection 2023.
To determine the effects of immune-related genes (IRGs) and immune landscape of induced sputum, and develop novel, non-invasive diagnostic molecular therapeutic targets for asthma.
GSE76262 datasets were used to identify differentially expressed IRGs in asthma. Key IRGs were detected using a protein-protein interaction network. Receiver operating characteristic (ROC) curves were analyzed to investigate the diagnostic value of key IRGs. Gene set enrichment analysis (GSEA) was performed with WebGestalt. Single-sample gene set enrichment analysis and CIBERSORT were used to investigate the immune landscape of induced sputum.
A total of 75 potential IRGs were associated with asthma, most of which were involved in the NF-kappa B signaling pathway. ROC analysis showed AUC values for the hub pathway ranging from 0.676-0.767, with moderate diagnostic value for asthma. We also identified IRGs-related cytokines (TNF-α, IL-1β, IL-8 and IL-6) in 76 asthma and 91 control serum samples to further explore diagnostic efficacy, showing a cumulative AUC of 0.998 for these four related cytokines. Analysis of immune cell infiltration levels showed that follicular helper T cells, activated dendritic cells, activated mast cells and eosinophils were significantly higher and macrophages M0 and macrophages M2 were significantly reduced in sputum from patients with asthma.
IRGs-related cytokines and immune infiltration may contribute to the diagnosis and immune classification of asthma.
确定免疫相关基因(IRGs)及诱导痰的免疫格局,并开发用于哮喘的新型非侵入性诊断分子治疗靶点。
使用GSE76262数据集来识别哮喘中差异表达的IRGs。通过蛋白质-蛋白质相互作用网络检测关键IRGs。分析受试者工作特征(ROC)曲线以研究关键IRGs的诊断价值。使用WebGestalt进行基因集富集分析(GSEA)。采用单样本基因集富集分析和CIBERSORT来研究诱导痰的免疫格局。
共有75个潜在的IRGs与哮喘相关,其中大多数参与NF-κB信号通路。ROC分析显示中心通路的AUC值在0.676至0.767之间,对哮喘具有中等诊断价值。我们还在76份哮喘血清样本和91份对照血清样本中鉴定了与IRGs相关的细胞因子(TNF-α、IL-1β、IL-8和IL-6),以进一步探索诊断效能,这四种相关细胞因子的累积AUC为0.998。免疫细胞浸润水平分析显示,哮喘患者痰液中的滤泡辅助性T细胞、活化树突状细胞、活化肥大细胞和嗜酸性粒细胞显著升高,而M0巨噬细胞和M2巨噬细胞显著减少。
与IRGs相关的细胞因子和免疫浸润可能有助于哮喘的诊断和免疫分类。