Clinical and inflammatory phenotyping by breathomics in chronic airway diseases irrespective of the diagnostic label

Eur Respir J. 2018 Jan 11;51(1):1701817. doi: 10.1183/13993003.01817-2017. Print 2018 Jan.

Abstract

Asthma and chronic obstructive pulmonary disease (COPD) are complex and overlapping diseases that include inflammatory phenotypes. Novel anti-eosinophilic/anti-neutrophilic strategies demand rapid inflammatory phenotyping, which might be accessible from exhaled breath.Our objective was to capture clinical/inflammatory phenotypes in patients with chronic airway disease using an electronic nose (eNose) in a training and validation set.This was a multicentre cross-sectional study in which exhaled breath from asthma and COPD patients (n=435; training n=321 and validation n=114) was analysed using eNose technology. Data analysis involved signal processing and statistics based on principal component analysis followed by unsupervised cluster analysis and supervised linear regression.Clustering based on eNose resulted in five significant combined asthma and COPD clusters that differed regarding ethnicity (p=0.01), systemic eosinophilia (p=0.02) and neutrophilia (p=0.03), body mass index (p=0.04), exhaled nitric oxide fraction (p<0.01), atopy (p<0.01) and exacerbation rate (p<0.01). Significant regression models were found for the prediction of eosinophilic (R2=0.581) and neutrophilic (R2=0.409) blood counts based on eNose. Similar clusters and regression results were obtained in the validation set.Phenotyping a combined sample of asthma and COPD patients using eNose provides validated clusters that are not determined by diagnosis, but rather by clinical/inflammatory characteristics. eNose identified systemic neutrophilia and/or eosinophilia in a dose-dependent manner.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Asthma / complications*
  • Bacterial Infections / diagnosis*
  • Breath Tests / instrumentation
  • Cluster Analysis
  • Cross-Sectional Studies
  • Electronic Nose*
  • Eosinophilia / metabolism
  • Exhalation
  • Female
  • Humans
  • Leukocyte Count
  • Linear Models
  • Lung / microbiology
  • Male
  • Middle Aged
  • Netherlands
  • Phenotype*
  • Pulmonary Disease, Chronic Obstructive / complications*
  • Volatile Organic Compounds / analysis

Substances

  • Volatile Organic Compounds