Header

UZH-Logo

Maintenance Infos

Real-time mass spectrometric identification of metabolites characteristic of chronic obstructive pulmonary disease in exhaled breath


Bregy, Lukas; Nussbaumer-Ochsner, Yvonne; Martinez-Lozano Sinues, Pablo; García-Gómez, Diego; Suter, Yannick; Gaisl, Thomas; Stebler, Nina; Gaugg, Martin Thomas; Kohler, Malcolm; Zenobi, Renato (2018). Real-time mass spectrometric identification of metabolites characteristic of chronic obstructive pulmonary disease in exhaled breath. Clinical Mass Spectrometry, 7:29-35.

Abstract

Background New mass spectrometry (MS) techniques analysing exhaled breath have the potential to better define airway diseases. Here, we present our work to profile the volatile organic compounds (VOCs) in exhaled breath from patients with chronic obstructive pulmonary disease (COPD), using real-time MS, and relate this disease-specific breath profile to functional disease markers. Methods In a matched cohort study, patients with COPD, according to GOLD criteria, were recruited. Exhaled breath analysis by untargeted MS was performed using secondary electrospray ionization – high-resolution MS (SESI-HRMS). Results Exhaled breath from 22 patients with COPD (mean age 58.6 ± 6.9 years, FEV1 58.5 ± 19.9% predicted, 32.4 ± 19.2 pack years smoking) and 14 controls (mean age 58.1 ± 8.1 years, FEV1 102.5 ± 11.3% predicted, 23.6 ± 12.5 pack years smoking) was analysed using SESI-HRMS. From 1441 different features, 43 markers were identified that allowed discrimination between the two groups with an accuracy of 89% (CI 74–97%), a sensitivity of 93%, and a specificity of 86%. The markers were determined to be metabolites of oxidative stress processes, such as fatty acids, aldehydes and amino acids, resulting from lung muscle degradation. Conclusion Real-time breath analysis by SESI-MS allows molecular profiling of exhaled breath, can distinguish patients with COPD from matched healthy controls and provides insights into the disease pathogenesis.

Abstract

Background New mass spectrometry (MS) techniques analysing exhaled breath have the potential to better define airway diseases. Here, we present our work to profile the volatile organic compounds (VOCs) in exhaled breath from patients with chronic obstructive pulmonary disease (COPD), using real-time MS, and relate this disease-specific breath profile to functional disease markers. Methods In a matched cohort study, patients with COPD, according to GOLD criteria, were recruited. Exhaled breath analysis by untargeted MS was performed using secondary electrospray ionization – high-resolution MS (SESI-HRMS). Results Exhaled breath from 22 patients with COPD (mean age 58.6 ± 6.9 years, FEV1 58.5 ± 19.9% predicted, 32.4 ± 19.2 pack years smoking) and 14 controls (mean age 58.1 ± 8.1 years, FEV1 102.5 ± 11.3% predicted, 23.6 ± 12.5 pack years smoking) was analysed using SESI-HRMS. From 1441 different features, 43 markers were identified that allowed discrimination between the two groups with an accuracy of 89% (CI 74–97%), a sensitivity of 93%, and a specificity of 86%. The markers were determined to be metabolites of oxidative stress processes, such as fatty acids, aldehydes and amino acids, resulting from lung muscle degradation. Conclusion Real-time breath analysis by SESI-MS allows molecular profiling of exhaled breath, can distinguish patients with COPD from matched healthy controls and provides insights into the disease pathogenesis.

Statistics

Citations

Dimensions.ai Metrics
37 citations in Web of Science®
42 citations in Scopus®
Google Scholar™

Altmetrics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Pneumology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Spectroscopy
Language:English
Date:1 January 2018
Deposited On:04 Jan 2019 09:32
Last Modified:20 Sep 2023 01:47
Publisher:Elsevier
ISSN:2376-9998
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.clinms.2018.02.003
Full text not available from this repository.