结核病患者外周血液中分子标志物生物信息学分析

Bioinformatics Analysis of Molecular Markers in Peripheral Blood of Patients with Tuberculosis

结核病(tuberculosis,TB)对人类具有非常大的威胁,感染过结核病的人占世界总人口数的三分之一,而且每年有造成超过一百万人的死亡。为了寻找可用于结核病诊断和治疗的分子标志物,我们从微阵列数据存储中心基因表达综合数据库(gene expression omnibus,GEO)中下载了原始数据,将来源于结核病患者的外周血单核细胞与健康人的基因进行了比较,共分析筛选出310个差异共表达的基因。随后,我们应用DAVID(the database for annotation,visualization and integrated discovery)数据库对这些差异共表达基因进行了GO(gene ontology)功能富集分析和KEGG(kyoto encyclopedia of genes and genomes)通路分析。通过蛋白互作网络,我们找到了CCL20、JAK2、STAT1和IL-1β4个结核病的关键基因。我们的研究表明,数据挖掘和整合能够成为研究结核病诊断标志物及其发生发展机制的有用工具,并可为结核病的诊断和治疗带来新思路。

Tuberculosis （TB） has a very high threat to humans, and people who have been infected with tuberculosis account for one third of the world＇s population, causing more than one million deaths each year. In order to find the molecular markers for the diagnosis and treatment of tuberculosis, in this study, the raw data was downloaded from gene expression omnibus （GEO）, which was in the center of the microarray data storage. The peripheral blood mononuclear cells of tuberculosis patients were compared with the healthy human genes to analyze and screen 310 differentially expressed genes. Subsequently, we used DAVID （the database for annotation, visualization and integrated discovery） to do GO （gene ontology） functional enrichment analysis and KEGG （kyoto encyclopedia of genes and genomes） pathway analysis for those differentially expressed genes. Through the protein interaction network, we had identified 4 genes, including CCL20, JAK2, STA T1 and IL-1β, which might be the key genes in tuberculosis. Our findings suggested that data mining and integration could be a useful tool for the research of tuberculosis diagnosis markers and its development and occurrence mechanisms. It also could provide new insights for the diagnosis and treatment of tuberculosis.