title: Molecular phenotyping of severe asthma using pattern recognition of bronchoalveolar lavage-derived cytokines.
abstract: BACKGROUND
  Asthma is a heterogeneous clinical disorder. Methods for objective identification of disease subtypes will focus on clinical interventions and help identify causative pathways. Few studies have explored phenotypes at a molecular level.
  
  
  OBJECTIVE
  We sought to discriminate asthma phenotypes on the basis of cytokine profiles in bronchoalveolar lavage (BAL) samples from patients with mild-moderate and severe asthma.
  
  
  METHODS
  Twenty-five cytokines were measured in BAL samples of 84 patients (41 severe, 43 mild-moderate) using bead-based multiplex immunoassays. The normalized data were subjected to statistical and informatics analysis.
  
  
  RESULTS
  Four groups of asthmatic profiles could be identified on the basis of unsupervised analysis (hierarchical clustering) that were independent of treatment. One group, enriched in patients with severe asthma, showed differences in BAL cellular content, reductions in baseline pulmonary function, and enhanced response to methacholine provocation. Ten cytokines were identified that accurately predicted this group. Classification methods for predicting methacholine sensitivity were developed. The best model analysis predicted hyperresponders with 88% accuracy in 10 trials by using a 10-fold cross-validation. The cytokines that contributed to this model were IL-2, IL-4, and IL-5. On the basis of this classifier, 3 distinct hyperresponder classes were identified that varied in BAL eosinophil count and PC20 methacholine.
  
  
  CONCLUSIONS
  Cytokine expression patterns in BAL can be used to identify distinct types of asthma and identify distinct subsets of methacholine hyperresponders. Further biomarker discovery in BAL may be informative.
authors.affiliation: Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555-1060, USA. arbrasie@utmb.edu
authors.forename: Allan R
authors.initials: AR
authors.lastname: Brasier
authors.forename: Sundar
authors.initials: S
authors.lastname: Victor
authors.forename: Gary
authors.initials: G
authors.lastname: Boetticher
authors.forename: Hyunsu
authors.initials: H
authors.lastname: Ju
authors.forename: Chang
authors.initials: C
authors.lastname: Lee
authors.forename: Eugene R
authors.initials: ER
authors.lastname: Bleecker
authors.forename: Mario
authors.initials: M
authors.lastname: Castro
authors.forename: William W
authors.initials: WW
authors.lastname: Busse
authors.forename: William J
authors.initials: WJ
authors.lastname: Calhoun
mesh_terms: D001249:Asthma / Q000276:immunology* / Q000503:physiopathology*; D001985:Bronchial Provocation Tests; D001992:Bronchoalveolar Lavage Fluid / Q000276:immunology*; D019295:Computational Biology; D016207:Cytokines / Q000235:genetics* / Q000378:metabolism*; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D006801:Humans; D007249:Inflammation / Q000276:immunology / Q000503:physiopathology; D008297:Male; D016210:Methacholine Chloride / Q000494:pharmacology; D010641:Phenotype; D012720:Severity of Illness Index
chemical_list: D016207:Cytokines; D016210:Methacholine Chloride