Phenotyping COPD by 1H NMR metabolomics of exhaled breath condensate

Abstract

Spirometry is used to establish the diagnosis of chronic obstructive pulmonary disease (COPD) and to assess disease progression, but it seems inadequate to characterize COPD phenotypes. Metabolomics has been introduced for molecular fingerprinting of biosamples in a variety of clinical disorders. The aim of the study was to establish whether exhaled breath condensate (EBC) in COPD features a distinct metabolic fingerprint, and to identify the metabolites that characterize the EBC profile in COPD. EBC was collected using a home-made glass condenser in 37 stable COPD patients, and 25 non-obstructed controls. Samples were analyzed using proton nuclear magnetic resonance spectroscopy (1H NMR). Random forest was applied for both supervised and unsupervised learning, using spectral buckets as input variables. Metabolomics of EBC discriminated COPD patients from controls with an overall accuracy of 86 %. As compared to controls, EBC from COPD featured significantly lower (p < 0.05) levels of acetone, valine and lysine, and significantly higher (p < 0.05) levels of lactate, acetate, propionate, serine, proline, and tyrosine. Based on unsupervised analysis of NMR spectra, the COPD sample was split in three clusters, one of which had the highest prevalence of radiologic emphysema. NMR spectroscopy of EBC holds promise in COPD fingerprinting. It may prove valuable in outcome studies, and in assessing the efficacy of therapeutic interventions.