Exhaled volatile organic compounds for phenotyping chronic obstructive pulmonary disease: a cross-sectional study

Maria Basanta,Dave Singh,Rachel Dockry,David Douce,Baharudin Ibrahim,Stephen J Fowler,Mike Morris,Ashley Woodcock

doi:10.1186/1465-9921-13-72

Abstract

BackgroundNon-invasive phenotyping of chronic respiratory diseases would be highly beneficial in the personalised medicine of the future. Volatile organic compounds can be measured in the exhaled breath and may be produced or altered by disease processes. We investigated whether distinct patterns of these compounds were present in chronic obstructive pulmonary disease (COPD) and clinically relevant disease phenotypes.MethodsBreath samples from 39 COPD subjects and 32 healthy controls were collected and analysed using gas chromatography time-of-flight mass spectrometry. Subjects with COPD also underwent sputum induction. Discriminatory compounds were identified by univariate logistic regression followed by multivariate analysis: 1. principal component analysis; 2. multivariate logistic regression; 3. receiver operating characteristic (ROC) analysis.ResultsComparing COPD versus healthy controls, principal component analysis clustered the 20 best-discriminating compounds into four components explaining 71% of the variance. Multivariate logistic regression constructed an optimised model using two components with an accuracy of 69%. The model had 85% sensitivity, 50% specificity and ROC area under the curve of 0.74. Analysis of COPD subgroups showed the method could classify COPD subjects with far greater accuracy. Models were constructed which classified subjects with ≥2% sputum eosinophilia with ROC area under the curve of 0.94 and those having frequent exacerbations 0.95. Potential biomarkers correlated to clinical variables were identified in each subgroup.ConclusionThe exhaled breath volatile organic compound profile discriminated between COPD and healthy controls and identified clinically relevant COPD subgroups. If these findings are validated in prospective cohorts, they may have diagnostic and management value in this disease.

Highlights

Non-invasive phenotyping of chronic respiratory diseases would be highly beneficial in the personalised medicine of the future
Previous work has suggested that patterns of volatile organic compounds (VOCs) in breath gas may be useful in identifying patients with chronic obstructive pulmonary disease (COPD) [7], [8], and that individual compounds correlate with inflammatory cell numbers and markers of activation [9], whilst another method for metabolomic analysis has employed nuclear magnetic resonance spectroscopy of exhaled breath condensate to classify COPD and healthy controls [10]
Breath samples were collected from a total of 71 subjects (39 COPD and 32 healthy controls), including 23 COPD subjects recruited from the ECLIPSE cohort

Summary

Introduction

Non-invasive phenotyping of chronic respiratory diseases would be highly beneficial in the personalised medicine of the future. We investigated whether distinct patterns of these compounds were present in chronic obstructive pulmonary disease (COPD) and clinically relevant disease phenotypes. Chronic obstructive pulmonary disease (COPD) is defined clinically on the basis of airflow obstruction [1,2]. This simple definition does not reflect the heterogeneous nature of COPD with individual variations in pathophysiology, aetiology, symptoms, prognosis and treatment response. VOCs can be altered by processes within the airways, both physical (e.g. adsorption into surface liquid) and biochemical (e.g. oxidation) Controlled measurement of these exhaled compounds could potentially give us novel insights into airway biology, physiology and pharmacology, and provide us with phenotype-specific biomarkers. To our knowledge the possibility of identifying clinically relevant disease phenotypes, such the eosinophilic or exacerbation-prone phenotypes, has not been investigated

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