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Author Lefaudeux, D.; De Meulder, B.; Loza, M.J.; Peffer, N.; Rowe, A.; Baribaud, F.; Bansal, A.T.; Lutter, R.; Sousa, A.R.; Corfield, J.; Pandis, I.; Bakke, P.S.; Caruso, M.; Chanez, P.; Dahlen, S.-E.; Fleming, L.J.; Fowler, S.J.; Horvath, I.; Krug, N.; Montuschi, P.; Sanak, M.; Sandstrom, T.; Shaw, D.E.; Singer, F.; Sterk, P.J.; Roberts, G.; Adcock, I.M.; Djukanovic, R.; Auffray, C.; Chung, K.F. url  doi
openurl 
  Title U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics Type Journal Article
  Year (down) 2017 Publication The Journal of Allergy and Clinical Immunology Abbreviated Journal J Allergy Clin Immunol  
  Volume 139 Issue 6 Pages 1797-1807  
  Keywords Adult; Aged; Algorithms; *Asthma/classification/genetics/metabolism; Biomarkers/metabolism; Female; Gene Expression Profiling; Humans; Leukocyte Count; Male; Middle Aged; Oligonucleotide Array Sequence Analysis; Phenotype; Proteomics; Severity of Illness Index; *Sputum/cytology/metabolism; Severe asthma; clustering; partition-around-medoids algorithm; sputum eosinophilia  
  Abstract BACKGROUND: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. OBJECTIVES: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. METHODS: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. RESULTS: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. CONCLUSION: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.  
  Address National Heart and Lung Institute, Imperial College & Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom. Electronic address: f.chung@imperial.ac.uk  
  Corporate Author U-BIOPRED Study Group Thesis  
  Impact Factor 11,476 First Author Lefaudeux, D. Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Senior Author Chung, K.F.  
  ISSN 0091-6749 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:27773852 Approved no  
  Call Number Serial 356  
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