Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma. Homo sapiens

Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes identified TEA clusters. Clinical characteristics were compared. Overall design: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.

对气道转录组进行分析，可揭示与哮喘临床表型相关的基因表达模式。为明确哮喘转录组内型（transcriptomic endotypes of asthma, TEA），我们分析了与疾病表型相关的诱导痰样本中的基因表达情况。研究采用Affymetrix HuGene ST 1.0基因表达微阵列（Affymetrix HuGene ST 1.0 microarrays）对哮喘受试者的痰液样本进行基因表达量检测。通过对基因开展无监督聚类分析，成功识别出哮喘转录组内型聚类簇，并对受试者的临床特征进行了比较分析。
整体实验设计如下：研究仍采用Affymetrix HuGene ST 1.0基因表达微阵列对哮喘受试者的痰液样本进行基因表达量检测；通过对从京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路中筛选出的基因开展无监督聚类分析，识别出哮喘转录组内型聚类簇；对临床特征进行比较，并对匹配的血液样本开展逻辑回归分析，以此构建表达特征谱，用于在儿童哮喘队列中验证哮喘转录组内型聚类簇的分配结果。