Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry.

Adults Breath analysis Cystic fibrosis Proton mass spectrometry Volatile organic compounds

Journal

Clinica chimica acta; international journal of clinical chemistry
ISSN: 1873-3492
Titre abrégé: Clin Chim Acta
Pays: Netherlands
ID NLM: 1302422

Informations de publication

Date de publication:
20 May 2024
Historique:
received: 08 01 2024
revised: 07 03 2024
accepted: 14 05 2024
medline: 23 5 2024
pubmed: 23 5 2024
entrez: 22 5 2024
Statut: aheadofprint

Résumé

Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF). To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS. 102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z). PTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing. PTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

Sections du résumé

BACKGROUND BACKGROUND
Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF).
OBJECTIVE OBJECTIVE
To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS.
METHODS METHODS
102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z).
RESULTS RESULTS
PTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing.
CONCLUSION CONCLUSIONS
PTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

Identifiants

pubmed: 38777246
pii: S0009-8981(24)01985-5
doi: 10.1016/j.cca.2024.119733
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

119733

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Malika Mustafina (M)

Department of Cardiology, Functional and Ultrasound Diagnostics, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; Pulmonology Research Institute Under Federal Medical and Biological Agency of Russia, 115682 Moscow, Russia; Research Institute for Systemic Analysis of the Russian Academy of Sciences, 117218 Moscow, Russia. Electronic address: mustafina_m_kh@staff.sechenov.ru.

Artemiy Silantyev (A)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia.

Stanislav Krasovskiy (S)

Pulmonology Research Institute Under Federal Medical and Biological Agency of Russia, 115682 Moscow, Russia.

Alexander Chernyak (A)

Pulmonology Research Institute Under Federal Medical and Biological Agency of Russia, 115682 Moscow, Russia.

Zhanna Naumenko (Z)

Pulmonology Research Institute Under Federal Medical and Biological Agency of Russia, 115682 Moscow, Russia.

Alexander Suvorov (A)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia.

Daria Gognieva (D)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; Research Institute for Systemic Analysis of the Russian Academy of Sciences, 117218 Moscow, Russia.

Magomed Abdullaev (M)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; Research Institute for Systemic Analysis of the Russian Academy of Sciences, 117218 Moscow, Russia.

Alina Bektimirova (A)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia.

Aleksandra Bykova (A)

Department of Cardiology, Functional and Ultrasound Diagnostics, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; Research Institute for Systemic Analysis of the Russian Academy of Sciences, 117218 Moscow, Russia.

Vasilisa Dergacheva (V)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia.

Vladimir Betelin (V)

Research Institute for Systemic Analysis of the Russian Academy of Sciences, 117218 Moscow, Russia.

Philipp Kopylov (P)

World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; Research Institute for Systemic Analysis of the Russian Academy of Sciences, 117218 Moscow, Russia.

Classifications MeSH