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Release date：2018-11-13

Clinical & Experimental Allergy

[IF:5.158]

Genetic Profiles of Transcriptomic Clusters of Childhood Asthma Determine Specific Severe Subtype
DOI: 10.1111/cea.13175
Abstract:
Background: Previous studies have defined transcriptomic subtypes of adult asthma using samples of induced sputum and bronchial epithelium; however, those procedures are not readily applicable in the clinic,especially for childhood asthma.
Methods: Gene expression of PBMC from 133 asthmatic children and 11 healthy controls was measured with Illumina microarrays. We applied the k-means clustering algorithm of 2048 genes to assign asthmatic children into clusters. Genes with differential expression between asthma clusters and healthy controls were used to investigate whether they could identify severe asthma of children and adults.
Results: We identified three asthma clusters with distinct inflammatory profiles in peripheral blood. Cluster 1 had the highest eosinophil count. Cluster 2 showed lower counts of both eosinophils and neutrophils.Cluster 3 had the highest neutrophil count, and the poorest treatment control. Compared with other patients, Cluster 3 exhibited a unique gene expression pattern which was associated with changes in the glucocorticoid signaling and activation of the T helper 1/T helper 17 (TH1/TH17) immune pathways. In the validation studies, an 84-gene signature could identify severe asthma in children on leukocytes, as well as severe asthma in adults on CD8+ T cells.
Conclusions: Gene expression profiling of PBMC is useful for the identification of TH1/TH17-mediated asthma with poor treatment control. PBMC and CD8+ T cells could be important targets for the investigation and identification of severe asthma.
First Author:
Y.-L. Yeh
Correspondence:
Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University
All Authors:
Y.-L. Yeh, M.-W. Su, B.-L. Chiang, Y.-H. Yang, C.-H. Tsai, Y. L. Lee

2018-10-25 Article