Background: Differentiating asthma from other causes of chronic airflow limitation, such as chronic obstructive pulmonary disease (COPD), can be difficult in a typical outpatient setting. The inflammation of asthma typically is different than that of COPD, and the degree of inflammation and cellular damage varies with asthma severity. Metabolomics is the study of molecules created by cellular metabolic pathways.
Objectives: We hypothesized that the metabolic activity of adults with asthma would differ from that of adults with COPD. Furthermore, we hypothesized that nuclear magnetic resonance spectroscopy (NMR) would measure such differences in urine samples.
Methods: Clinical and urine-based NMR data were collected on adults meeting the criteria of asthma and COPD before and after an exacerbation (n = 133 and 38, respectively) and from patients with stable asthma or COPD (n = 54 and 23, respectively). Partial least-squares discriminant analysis was performed on the NMR data to create models of separation (86 metabolites were measured per urine sample). Some subjects' metabolomic data were withheld from modeling to be run blindly to determine diagnostic accuracy.
Results: Partial least-squares discriminant analysis of the urine NMR data found unique differences in select metabolites between patients with asthma and those with COPD seen in the emergency department and even in follow-up after exacerbation. By using these select metabolomic profiles, the model could correctly diagnose blinded asthma and COPD with greater than 90% accuracy.
Conclusion: This is the first report showing that metabolomic analysis of human urine samples could become a useful clinical tool to differentiate asthma from COPD.
Keywords: Metabolomics; asthma; biomarkers; chronic obstructive pulmonary disease; nuclear magnetic resonance spectroscopy; urine.
Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.