确定结核病感染的中枢基因并建立诊断模型

IF 3.5 3区生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

AMB Express Pub Date : 2024-04-13 DOI:10.1186/s13568-024-01691-7

Chunli Liu, Xing Li

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引用次数: 0

摘要

结核病（TB）因其在人群中的高传播性和固有的抗药性而带来了巨大的挑战，使其成为一种具有巨大易感负担的可怕的呼吸道疾病。本研究旨在确定肺结核的新潜在治疗靶点并建立诊断模型。肺结核的 mRNA 表达数据来自 GEO 数据库，然后进行差异表达分析。对表达差异最大的 50 个基因进行 GO 和 KEGG 富集分析。为了建立 PPI 网络，研究人员使用了 STRING 数据库，并利用 Cytoscape 软件 cytoHubba 插件中的五种算法（EPC、MCC、MNC、Radiality 和 Stress）确定了中心基因。此外，还利用 GeneMANIA 数据库构建了中枢基因共表达网络。对中枢基因进行一致性聚类，并利用ssGSEA分析不同亚组的免疫浸润程度。利用 LASSO 分析构建诊断模型，并使用 ROC 曲线进行验证。通过分析 GEO 数据，共确定了 159 个差异表达基因。进一步的 GO 和 KEGG 富集分析表明，这些基因主要富集在病毒防御、共生防御和先天免疫反应相关通路中。通过对 PPI 网络的 cytoHubba 分析，确定了包括 DDX58、IFIT2、IFIH1、RSAD2、IFI44L、OAS2、OAS1、OASL、IFIT1、IFIT3、MX1、STAT1 和 ISG15 在内的枢纽基因。GeneMANIA分析发现，枢纽基因的共表达率为81.55%，物理相互作用率为12.27%。一致性聚类将肺结核患者分为两个亚组，ssGSEA 揭示了不同亚组中不同程度的免疫浸润。LASSO 分析确定了 IFIT1、IFIT2、IFIT3、IFIH1、RSAD2、OAS1、OAS2 和 STAT1 这八个与免疫相关的关键基因，并构建了诊断模型。ROC 曲线显示，该模型具有出色的诊断性能。DDX58、IFIT2、IFIH1、RSAD2、IFI44L、OAS2、OAS1、OASL、IFIT1、IFIT3、MX1、STAT1 和 ISG15 是结核病的枢纽基因，基于八个免疫相关关键基因的诊断模型表现出良好的诊断性能。

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Identification of hub genes and establishment of a diagnostic model in tuberculosis infection

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Identification of hub genes and establishment of a diagnostic model in tuberculosis infection

Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.

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来源期刊

AMB Express BIOTECHNOLOGY & APPLIED MICROBIOLOGY-

CiteScore

7.20

自引率

2.70%

发文量

141

审稿时长

13 weeks

期刊介绍： AMB Express is a high quality journal that brings together research in the area of Applied and Industrial Microbiology with a particular interest in ''White Biotechnology'' and ''Red Biotechnology''. The emphasis is on processes employing microorganisms, eukaryotic cell cultures or enzymes for the biosynthesis, transformation and degradation of compounds. This includes fine and bulk chemicals, polymeric compounds and enzymes or other proteins. Downstream processes are also considered. Integrated processes combining biochemical and chemical processes are also published.