Skip to main content

Research Repository

Advanced Search

A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED

Khuo, Chih-Hsi Scott; Pavlidis, Stelios; Loza, Matthew; Baribaud, Fred; Rowe, Anthony; Pandis, Ioannis; Hoda, Uruj; Rossios, Christos; Sousa, Ana; Wilson, Susan J.; Howarth, Peter; Dahlen, Barbro; Dahlen, Sven-Erik; Chanez, Pascal; Shaw, Dominick E.; Krug, Norbert; Sandstr�m, Thomas; De Meulder, Betrand; Lefaudeux, Diane; Fowler, Stephen; Fleming, Louise; Corfield, Julie; Auffray, Charles; Sterk, Peter J.; Djukanovic, Ratko; Guo, Yike; Adcock, Ian M.; Chung, Kian Fan

Authors

Chih-Hsi Scott Khuo

Stelios Pavlidis

Matthew Loza

Fred Baribaud

Anthony Rowe

Ioannis Pandis

Uruj Hoda

Christos Rossios

Ana Sousa

Susan J. Wilson

Peter Howarth

Barbro Dahlen

Sven-Erik Dahlen

Pascal Chanez

Dominick E. Shaw

Norbert Krug

Thomas Sandstr�m

Betrand De Meulder

Diane Lefaudeux

Stephen Fowler

Louise Fleming

Julie Corfield

Charles Auffray

Peter J. Sterk

Ratko Djukanovic

Yike Guo

Ian M. Adcock

Kian Fan Chung



Abstract

Rationale and objectives: Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms. We used transcriptomic profiling of airway tissues to help define asthma phenotypes. Methods: The transcriptome from bronchial biopsies and epithelial brushings of 107 moderate-to-severe asthmatics were annotated by gene-set variation analysis (GSVA) using 42 gene-signatures relevant to asthma, inflammation and immune function. Topological data analysis (TDA) of clinical and histological data was used to derive clusters and the nearest shrunken centroid algorithm used for signature refinement. Results: 9 GSVA signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper type 2 (Th-2) cytokines and lack of corticosteroid response (Group 1 and Group 3). Group 1 had the highest submucosal eosinophils, high exhaled nitric oxide (FeNO) levels, exacerbation rates and oral corticosteroid (OCS) use whilst Group 3 patients showed the highest levels of sputum eosinophils and had a high BMI. In contrast, Group 2 and Group 4 patients had an 86% and 64% probability of having non-eosinophilic inflammation. Using machine-learning tools, we describe an inference scheme using the currently-available inflammatory biomarkers sputum eosinophilia and exhaled nitric oxide levels along with OCS use that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity. Conclusion: This analysis demonstrates the usefulness of a transcriptomic-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target Th2-mediated inflammation and/or corticosteroid insensitivity.

Citation

Khuo, C. S., Pavlidis, S., Loza, M., Baribaud, F., Rowe, A., Pandis, I., …Chung, K. F. (2017). A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED. American Journal of Respiratory and Critical Care Medicine, 195(4), https://doi.org/10.1164/rccm.201512-2452OC

Journal Article Type Article
Acceptance Date Aug 20, 2016
Online Publication Date Aug 31, 2016
Publication Date Feb 15, 2017
Deposit Date Oct 24, 2016
Publicly Available Date Mar 29, 2024
Journal American Journal of Respiratory and Critical Care Medicine
Print ISSN 1073-449X
Electronic ISSN 1535-4970
Publisher American Thoracic Society
Peer Reviewed Peer Reviewed
Volume 195
Issue 4
DOI https://doi.org/10.1164/rccm.201512-2452OC
Keywords severe asthma, bronchial briushing, corticosteroid, insensitivity, T-helper Type 2 (Th2)
Public URL https://nottingham-repository.worktribe.com/output/803651
Publisher URL http://www.atsjournals.org/doi/abs/10.1164/rccm.201512-2452OC?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dpubmed&#.WA24_PkrJph

Files





You might also like



Downloadable Citations