Developing a Diagnostic Model to Predict the Risk of Asthma Based on Ten Macrophage-Related Gene Signatures.
Developing a Diagnostic Model to Predict the Risk of Asthma Based on Ten Macrophage-Related Gene Signatures.
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DOI：
10.1155/2022/3439010
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发表时间：
2022
影响因子：
--
通讯作者：
Zhou, Qing
中科院分区：
文献类型：
--
作者：
Ai, Xiaoshun;Shen, Hong;Wang, Yangyanqiu;Zhuang, Jing;Zhou, Yani;Niu, Furong;Zhou, Qing
哮喘（Asthma，AS）是一种慢性气道炎症性疾病，巨噬细胞参与AS的重塑.我们的研究旨在筛选巨噬细胞相关基因特征，建立风险预测模型并探索其在AS诊断中的预测能力。 从GEO数据库下载三个微阵列数据集。应用Limma软件包筛选AS与对照组的差异表达基因（DEG）。ssGSEA算法用于确定免疫细胞比例。计算Pearson相关系数以选择巨噬细胞相关DEG。采用LASSO和RFE算法对巨噬细胞相关DEG特征进行过滤，建立风险预测模型。受试者工作特征（ROC）曲线用于评估预测模型的诊断能力。最后，采用qPCR方法检测健康人和哮喘患者痰液中差异基因的表达。 我们从组合数据集中获得了AS和对照之间的1，189个DEG。通过评估免疫细胞比例，巨噬细胞在两组之间显示出显著差异，并且发现439个DEG与巨噬细胞相关。这些基因主要富集在免疫和炎症反应的基因本体-生物学过程中，以及嘌呤-细胞因子受体相互作用和抗生素生物合成的KEGG途径中。最后，筛选出10个巨噬细胞相关DEG标签（EARS 2、ATP 2A 2、COLGALT 1、GART、WNT 5A、AK 5、ZBTB 16、CCL 17、ADORA 3和CXCR 4）作为预测AS诊断的优化基因集，它们在组合和验证数据集的ROC曲线中分别显示出AUC为0.968和0.875的诊断能力。对照组EARS 2、ATP 2A 2、COLGALT 1、GART mRNA表达高于AS组，WNT 5A、AK 5、ZBTB 16、CCL 17、ADORA 3、CXCR 4 mRNA表达低于AS组。 我们提出了一个基于10个巨噬细胞相关基因的诊断模型来预测AS的风险。
Asthma (AS) is a chronic inflammatory disease of the airway, and macrophages contribute to AS remodeling. Our study aims at screening macrophage-related gene signatures to build a risk prediction model and explore its predictive abilities in AS diagnosis. Three microarray datasets were downloaded from the GEO database. The Limma package was used to screen differentially expressed genes (DEGs) between AS and controls. The ssGSEA algorithm was used to determine immune cell proportions. The Pearson correlation coefficient was computed to select the macrophage-related DEGs. The LASSO and RFE algorithms were implemented to filter the macrophage-related DEG signatures to establish a risk prediction model. Receiver operating characteristic (ROC) curves were used to assess the diagnostic ability of the prediction model. Finally, the qPCR was used to detect the expression of selected differential genes in sputum from healthy people and asthmatic patients. We obtained 1,189 DEGs between AS and controls from the combined datasets. By evaluating immune cell proportions, macrophages showed a significant difference between the two groups, and 439 DEGs were found to be associated with macrophages. These genes were mainly enriched in the gene ontology-biological process of immune and inflammatory responses, as well as in the KEGG pathways of cytokine-cytokine receptor interaction and biosynthesis of antibiotics. Finally, 10 macrophage-related DEG signatures (EARS2, ATP2A2, COLGALT1, GART, WNT5A, AK5, ZBTB16, CCL17, ADORA3, and CXCR4) were screened as an optimized gene set to predict AS diagnosis, and they showed diagnostic abilities with AUCs of 0.968 and 0.875 in ROC curves of combined and validation datasets, respectively. The mRNA expressions of EARS2, ATP2A2, COLGALT1, and GART in the control group were higher than in AS group, while the expressions of WNT5A, AK5, ZBTB16, CCL17, ADORA3, and CXCR4 in the control group were lower than that in the AS group. We proposed a diagnostic model based on 10 macrophage-related genes to predict AS risk.\.
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影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK
影响因子：
5.8
作者：
Groth EE;Weber M;Bahmer T;Pedersen F;Kirsten A;Börnigen D;Rabe KF;Watz H;Ammerpohl O;Goldmann T
通讯作者：
Goldmann T
替代激活巨噬细胞在哮喘中作用的最新进展
影响因子：
3.2
作者：
Jiang Z;Zhu L
通讯作者：
Zhu L
DOI：
10.14366/usg.16045
发表时间：
2018-01
期刊：
Ultrasonography (Seoul, Korea)
影响因子：
--
作者：
Kim SM;Kim Y;Jeong K;Jeong H;Kim J
通讯作者：
Kim J
影响因子：
5.9
作者：
Nanda, Anil;Wasan, Anita N.
通讯作者：
Wasan, Anita N.