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基于生物信息学和机器学习分析鉴定 TXN 和 F5 作为严重哮喘的新型诊断基因生物标志物。

Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis.

作者信息

Shou Lu, He Haidong, Wei Yi, Xu Xianrong, Wang Wenmin, Zheng Jisheng

机构信息

Tongde Hospital of Zhejiang Province, Pulmonary and Critical Care Medicine, Hangzhou, Zhejiang, China.

The Yangtze River Delta Biological Medicine Research and Development Center of Zhejiang Province, Yangtze Delta Region Institution of Tsinghua University, Hangzhou, Zhejiang, China.

出版信息

Autoimmunity. 2024 Dec;57(1):2427085. doi: 10.1080/08916934.2024.2427085. Epub 2024 Nov 12.

DOI:10.1080/08916934.2024.2427085
PMID:39531229
Abstract

Asthma poses a major threat to human health. The aim of this study was to identify genetic markers of severe asthma and analyze the relationship between key genes and immune infiltration. Differentially expressed genes (DEGs) were first screened by downloading the training set GSE69683 and validation set GSE137268 from the GEO dataset. SVM-RFE analysis and the LASSO regression model were used to screen key genes, and CIBERSORT was used to assess immune infiltration in the samples. A total of 20 DEGs were identified in this study, mainly enriched for lymph node-like receptors, b-cell receptors, and neutrophil extracellular trap pathway. Comparative validation set GSE137268 identified thioredoxin (TXN) and coagulation factor V (F5) were identified as diagnostic markers of severe asthma. CIBERSORT analysis revealed that TXN and F5 are associated with multiple immune cell infiltrates. In addition, we identified miRNA and TF at the transcriptional level that may regulate F5 and TXN, and found that several commonly used drugs may exert therapeutic effects by targeting F5 and TXN. Taken together, TXN and F5 may be key genes in the development of severe asthma and are associated with immune infiltration. Our study can help to better understand the pathogenesis of asthma and provide new ideas for clinical treatment.

摘要

哮喘严重威胁人类健康。本研究旨在鉴定严重哮喘的遗传标志物,并分析关键基因与免疫浸润之间的关系。首先通过下载 GEO 数据集的训练集 GSE69683 和验证集 GSE137268,筛选差异表达基因(DEGs)。采用 SVM-RFE 分析和 LASSO 回归模型筛选关键基因,并用 CIBERSORT 评估样本中的免疫浸润。本研究共鉴定出 20 个 DEGs,主要富集于淋巴结样受体、B 细胞受体和中性粒细胞胞外诱捕途径。在比较验证集 GSE137268 中,鉴定出硫氧还蛋白(TXN)和凝血因子 V(F5)可作为严重哮喘的诊断标志物。CIBERSORT 分析表明,TXN 和 F5 与多种免疫细胞浸润有关。此外,我们还在转录水平鉴定出可能调节 F5 和 TXN 的 miRNA 和 TF,并发现几种常用药物可能通过靶向 F5 和 TXN 发挥治疗作用。总之,TXN 和 F5 可能是严重哮喘发展的关键基因,与免疫浸润有关。我们的研究有助于更好地理解哮喘的发病机制,并为临床治疗提供新的思路。

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