Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma
Year: 2015
Type: article
Study design: Observational Study
Abstract: RATIONALE: The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma. OBJECTIVES: We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA), gene signatures that discriminate phenotypes of disease. METHODS: Gene expression in the sputum and blood of patients with asthma was measured using Affymetrix microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma to replicate clinical phenotypes. MEASUREMENTS AND MAIN RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) compared with the other TEA clusters. TEA cluster 2, the smallest cluster, had the most subjects that were hospitalized for asthma (P = 0.04). TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 × 10(-6)) and hospitalization (P = 0.01), respectively. CONCLUSIONS: There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near-fatal, severe, and milder asthma.
Authors: Xiting Yan, Jen-Hwa Chu, Jose Gomez, Maria Koenigs, Carole Holm, Xiaoxuan He, Mario F. Perez, Hongyu Zhao, Shrikant Mane, Fernando D. Martinez, Carole Ober, Dan L. Nicolae, Kathleen C. Barnes, Stephanie J. London, Frank Gilliland, Scott T. Weiss, Benjamin A. Raby, Lauren Cohn, Geoffrey L. Chupp
Institutions: Brigham and Women's Hospital, Harvard University, Yale University, University of Arizona, BIO5 Institute, University of Chicago, Johns Hopkins University, Johns Hopkins Medicine, National Institutes of Health, National Institute of Environmental Health Sciences, University of Southern California
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G1180506732, G1305138335, G1583036818, G2455859204, G2669520013, G3258572180, G5434902180, G65513578, G782798174, Yale University Clinical and Translational Science Award Program, G8047873292, G8065952620, Longitudinal Analysis of Transcriptomic Endophenotypes in Asthma, G9000084062, Biomedical Informatics and Data Science Training at Yale, G9000326834, Environmental Exposures, Host Factors and Human Disease
OpenAlex ID: W2136241314