Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD 20910, USA.
Tuberculosis (Edinb). 2011 Sep;91(5):390-9. doi: 10.1016/j.tube.2011.07.002. Epub 2011 Aug 10.
Host responses following exposure to Mycobacterium tuberculosis (TB) are complex and can significantly affect clinical outcome. These responses, which are largely mediated by complex immune mechanisms involving peripheral blood cells (PBCs) such as T-lymphocytes, NK cells and monocyte-derived macrophages, have not been fully characterized. We hypothesize that different clinical outcome following TB exposure will be uniquely reflected in host gene expression profiles, and expression profiling of PBCs can be used to discriminate between different TB infectious outcomes. In this study, microarray analysis was performed on PBCs from three TB groups (BCG-vaccinated, latent TB infection, and active TB infection) and a control healthy group. Supervised learning algorithms were used to identify signature genomic responses that differentiate among group samples. Gene Set Enrichment Analysis was used to determine sets of genes that were co-regulated. Multivariate permutation analysis (p < 0.01) gave 645 genes differentially expressed among the four groups, with both distinct and common patterns of gene expression observed for each group. A 127-probeset, representing 77 known genes, capable of accurately classifying samples into their respective groups was identified. In addition, 13 insulin-sensitive genes were found to be differentially regulated in all three TB infected groups, underscoring the functional association between insulin signaling pathway and TB infection.
宿主在接触结核分枝杆菌 (TB) 后的反应是复杂的,会对临床结果产生重大影响。这些反应主要由涉及外周血细胞(如 T 淋巴细胞、NK 细胞和单核细胞衍生的巨噬细胞)的复杂免疫机制介导,但尚未得到充分表征。我们假设,TB 暴露后不同的临床结果将独特地反映在宿主基因表达谱中,而外周血细胞的表达谱可用于区分不同的 TB 感染结果。在这项研究中,对来自三个 TB 组(BCG 接种、潜伏性 TB 感染和活动性 TB 感染)和一个健康对照组的外周血细胞进行了微阵列分析。使用监督学习算法来识别可区分组样本的特征性基因组反应。基因集富集分析用于确定共同调节的基因集。多元置换分析(p < 0.01)在四组之间鉴定出 645 个差异表达的基因,每个组都观察到了独特和共同的基因表达模式。确定了一个由 127 个探针集代表的 77 个已知基因,能够准确地将样本分类到其各自的组中。此外,发现所有三个 TB 感染组中都有 13 个胰岛素敏感基因存在差异调节,这突显了胰岛素信号通路与 TB 感染之间的功能关联。