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A Transcriptome-driven Analysis of Epithelial Brushings and Bronchial Biopsies to Define Asthma Phenotypes in U-BIOPRED.
Kuo, 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; Krug, Norbert; SandstrÓ§m, Thomas; De Meulder, Bertrand; Lefaudeux, Diane; Fowler, Stephen; Fleming, Louise; Corfield, Julie; Auffray, Charles; Sterk, Peter J; Djukanovic, Ratko; Guo, Yike; Adcock, Ian M; Chung, Kian Fan.
Afiliação
  • Kuo CS; 1 Department of Computing.
  • Pavlidis S; 2 Data Science Institute, and.
  • Loza M; 3 Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Baribaud F; 1 Department of Computing.
  • Rowe A; 2 Data Science Institute, and.
  • Pandis I; 4 Janssen Research and Development, High Wycombe, United Kingdom.
  • Hoda U; 4 Janssen Research and Development, High Wycombe, United Kingdom.
  • Rossios C; 4 Janssen Research and Development, High Wycombe, United Kingdom.
  • Sousa A; 4 Janssen Research and Development, High Wycombe, United Kingdom.
  • Wilson SJ; 1 Department of Computing.
  • Howarth P; 2 Data Science Institute, and.
  • Dahlen B; 3 Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Dahlen SE; 5 Biomedical Research Unit, Royal Brompton & Harefield National Health Service Trust, London, United Kingdom.
  • Chanez P; 3 Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Shaw D; 6 Respiratory Therapeutic Unit, GlaxoSmithKline, Stockley Park, United Kingdom.
  • Krug N; 7 Faculty of Medicine, Southampton University, Southampton, United Kingdom.
  • SandstrÓ§m T; 7 Faculty of Medicine, Southampton University, Southampton, United Kingdom.
  • De Meulder B; 8 Centre for Allergy Research, Karolinska Institute, Stockholm, Sweden.
  • Lefaudeux D; 8 Centre for Allergy Research, Karolinska Institute, Stockholm, Sweden.
  • Fowler S; 9 Université de la Méditerranee, Marseille, France.
  • Fleming L; 10 Centre for Respiratory Research, University of Nottingham, Nottingham, United Kingdom.
  • Corfield J; 11 Fraunhofer Institute of Toxicology and Experimental Medicine, Hannover, Germany.
  • Auffray C; 12 Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
  • Sterk PJ; 13 European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, University of Lyon, Lyon, France.
  • Djukanovic R; 13 European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, University of Lyon, Lyon, France.
  • Guo Y; 14 Centre for Respiratory Medicine and Allergy, University of Manchester, Manchester, United Kingdom.
  • Adcock IM; 3 Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Chung KF; 5 Biomedical Research Unit, Royal Brompton & Harefield National Health Service Trust, London, United Kingdom.
Am J Respir Crit Care Med ; 195(4): 443-455, 2017 Feb 15.
Article em En | MEDLINE | ID: mdl-27580351
ABSTRACT
RATIONALE Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms.

OBJECTIVES:

Using transcriptomic profiling of airway tissues, we sought to define the molecular phenotypes of severe asthma.

METHODS:

The transcriptome derived from bronchial biopsies and epithelial brushings of 107 subjects with moderate to severe asthma were annotated by gene set variation analysis using 42 gene signatures relevant to asthma, inflammation, and immune function. Topological data analysis of clinical and histologic data was performed to derive clusters, and the nearest shrunken centroid algorithm was used for signature refinement. MEASUREMENTS AND MAIN

RESULTS:

Nine gene set variation analysis signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper cell type 2 cytokines and lack of corticosteroid response (group 1 and group 3). Group 1 had the highest submucosal eosinophils, as well as high fractional exhaled nitric oxide levels, exacerbation rates, and oral corticosteroid use, whereas group 3 patients showed the highest levels of sputum eosinophils and had a high body mass index. In contrast, group 2 and group 4 patients had an 86% and 64% probability, respectively, of having noneosinophilic inflammation. Using machine learning tools, we describe an inference scheme using the currently available inflammatory biomarkers sputum eosinophilia and fractional exhaled nitric oxide levels, along with oral corticosteroid use, that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity.

CONCLUSIONS:

This analysis demonstrates the usefulness of a transcriptomics-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target T-helper cell type 2-mediated inflammation and/or corticosteroid insensitivity.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Asma / Brônquios / Corticosteroides Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Asma / Brônquios / Corticosteroides Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article