Validation of breath biomarkers for obstructive sleep apnea
dc.contributor.author
Nowak, Nora
dc.contributor.author
Engler, Anna
dc.contributor.author
Thiel, Sira
dc.contributor.author
Stöberl, Anna S.
dc.contributor.author
Sinues, Pablo
dc.contributor.author
Kohler, Malcolm
dc.date.accessioned
2021-07-29T12:40:51Z
dc.date.available
2021-07-29T03:31:14Z
dc.date.available
2021-07-29T12:40:51Z
dc.date.issued
2021-09
dc.identifier.issn
1389-9457
dc.identifier.other
10.1016/j.sleep.2021.06.040
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/498281
dc.identifier.doi
10.3929/ethz-b-000498281
dc.description.abstract
Background and objectives
Obstructive sleep apnea (OSA) is an underdiagnosed respiratory disease with negative metabolic and cardiovascular effects. The current gold standard for diagnosing OSA is in-hospital polysomnography, a time-consuming and costly procedure, often inconvenient for the patient. Recent studies revealed evidence for the potential of breath analysis for the diagnosis of OSA based on a disease-specific metabolic pattern. However, none of these findings were validated in a larger and broader cohort, an essential step for its application in clinics.
Methods
In the present study, we validated a panel of breath biomarkers in a cohort of patients with possible OSA (N = 149). These markers were previously identified in our group by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS).
Results
Here, we could confirm significant differences between metabolic patterns in exhaled breath from OSA patients compared to control subjects without OSA as well as the association of breath biomarker levels with disease severity. Our prediction of the diagnosis for the patients from this completely independent validation study using a classification model trained on the data from the previous study resulted in an area under the receiver operating characteristic curve of 0.66, which is comparable to questionnaire-based OSA screenings.
Conclusions
Thus, our results suggest that breath analysis by SESI-HRMS might be useful to screen for OSA as an objective measure. However, its true predictive power should be tested in combination with OSA screening questionnaires.
Clinical trial
“Mass Spectral Fingerprinting in Obstructive Sleep Apnoea”, NCT02810158, www.ClinicalTrials.gov.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Obstructive sleep apnea
en_US
dc.subject
Biomarkers
en_US
dc.subject
Validation study
en_US
dc.subject
Breath analysis
en_US
dc.subject
Metabolomics
en_US
dc.subject
Secondary electrospray ionization mass spectrometry
en_US
dc.title
Validation of breath biomarkers for obstructive sleep apnea
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2021-07-03
ethz.journal.title
Sleep Medicine
ethz.journal.volume
85
en_US
ethz.pages.start
75
en_US
ethz.pages.end
86
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02020 - Dep. Chemie und Angewandte Biowiss. / Dep. of Chemistry and Applied Biosc.::02514 - Laboratorium für Organische Chemie / Laboratory of Organic Chemistry::03430 - Zenobi, Renato / Zenobi, Renato
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02020 - Dep. Chemie und Angewandte Biowiss. / Dep. of Chemistry and Applied Biosc.::02514 - Laboratorium für Organische Chemie / Laboratory of Organic Chemistry::03430 - Zenobi, Renato / Zenobi, Renato
ethz.relation.isSupplementedBy
10.3929/ethz-b-000456155
ethz.date.deposited
2021-07-29T03:31:17Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-07-29T12:40:58Z
ethz.rosetta.lastUpdated
2022-03-29T10:48:44Z
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true
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true
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