COPD phenotype description using principal components analysis

Background: Airway inflammation in COPD can be measured using biomarkers such as induced sputum and FeNO. This study set out to explore the heterogeneity of COPD using biomarkers of airway and systemic inflammation and pulmonary function by principal components analysis (PCA).Subjects and Methods: In 127 COPD patients (mean FEV1 61%), pulmonary function, FeNO, plasma CRP and TNF-α, sputum differential cell counts and sputum IL8 (pg/ml) were measured. Principal components analysis as well as multivariate analysis was performed.Results: PCA identified four main components (% variance): (1) sputum neutrophil cell count and supernatant IL8 and plasma TNF-α (20.2%), (2) Sputum eosinophils % and FeNO (18.2%), (3) Bronchodilator reversibility, FEV1 and IC (15.1%) and (4) CRP (11.4%). These results were confirmed by linear regression multivariate analyses which showed strong associations between the variables within components 1 and 2.Conclusion: COPD is a multi dimensional disease. Unrelated components of disease were identified, including neutrophilic airway inflammation which was associated with systemic inflammation, and sputum eosinophils which were related to increased FeNO. We confirm dissociation between airway inflammation and lung function in this cohort of patients. © 2009 Roy et al; licensee BioMed Central Ltd.