Abstract
Background and objectivesObstructive 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. MethodsIn 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). ResultsHere, 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. ConclusionsThus, 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.
Highlights
Obstructive sleep apnea (OSA) is a highly prevalent sleeprelated breathing disorder [1]
Conclusions: our results suggest that breath analysis by SESI-HRMS might be useful to screen for OSA as an objective measure
Offline gas-chromatography coupled to mass spectrometry, or enzyme immunoassays to analyze exhaled breath condensate have achieved promising results regarding the distinction between OSA patients and controls without OSA from exhaled breath [3]
Summary
Obstructive sleep apnea (OSA) is a highly prevalent sleeprelated breathing disorder [1]. Recent studies revealed evidence for the potential of breath analysis for the diagnosis of OSA based on a disease-specific metabolic pattern. None of these findings were validated in a larger and broader cohort, an essential step for its application in clinics. These markers were previously identified in our group by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). 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.
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