Research

COPD phenotype description using principal components analysis

Kay Roy , Jacky Smith , Umme Kolsum , Zöe Borrill , Jørgen Vestbo and Dave Singh

University of Manchester, North West Lung Research Centre, University Hospital of South Manchester Foundation Trust, Wythenshawe, Manchester, M33 9LT, UK

author email corresponding author email

Respiratory Research 2009, 10:41doi:10.1186/1465-9921-10-41

Published:	29 May 2009

Abstract

Background

Airway inflammation in COPD can be measured using biomarkers such as induced sputum and Fe_NO. 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, Fe_NO, 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 Fe_NO (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 Fe_NO. We confirm dissociation between airway inflammation and lung function in this cohort of patients.