Y-L Yeh1,2,3, M-W Su1,2, B-L Chiang4, Y-H Yang4, C-H Tsai1, Y L Lee1,2. 1. Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan. 2. Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. 3. School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. 4. Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan.
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. OBJECTIVE: We aim to dissect the transcriptomic clusters of childhood asthma using highly variably expressed genes of peripheral blood mononuclear cells (PBMC) among patients. 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 3 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 signalling and activation of the T helper 1/T helper 17 (TH 1/TH 17) immune pathways. In the validation studies, an 84-gene signature could identify severe asthma in children on leucocytes, as well as severe asthma in adults on CD8+ T cells. CONCLUSIONS AND CLINICAL RELEVANCE: Gene expression profiling of PBMC is useful for the identification of TH 1/TH 17-mediated asthma with poor treatment control. PBMC and CD8+ T cells could be important targets for the investigation and identification of severe asthma.
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. OBJECTIVE: We aim to dissect the transcriptomic clusters of childhood asthma using highly variably expressed genes of peripheral blood mononuclear cells (PBMC) among patients. 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 3 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 signalling and activation of the T helper 1/T helper 17 (TH 1/TH 17) immune pathways. In the validation studies, an 84-gene signature could identify severe asthma in children on leucocytes, as well as severe asthma in adults on CD8+ T cells. CONCLUSIONS AND CLINICAL RELEVANCE: Gene expression profiling of PBMC is useful for the identification of TH 1/TH 17-mediated asthma with poor treatment control. PBMC and CD8+ T cells could be important targets for the investigation and identification of severe asthma.
Authors: Gopal Krishna R Dhondalay; Bryan Bunning; Rebecca N Bauer; Elliot S Barnathan; Christopher Maniscalco; Frédéric Baribaud; Kari C Nadeau; Sandra Andorf Journal: Allergy Date: 2020-01-21 Impact factor: 13.146
Authors: Priyanka Banerjee; Premanand Balraj; Nilesh Sudhakar Ambhore; Sarah A Wicher; Rodney D Britt; Christina M Pabelick; Y S Prakash; Venkatachalem Sathish Journal: Sci Rep Date: 2021-07-13 Impact factor: 4.379