ETH Zurich, Department of Chemistry and Applied Biosciences, 8093 Zurich, Switzerland.
Department of Pulmonology, University Hospital Zürich, 8091 Zurich, Switzerland.
Cells. 2022 Sep 24;11(19):2982. doi: 10.3390/cells11192982.
Rapid and reliable tools for the diagnosis and monitoring of obstructive sleep apnea (OSA) are currently lacking. Prior studies using a chemical analysis of exhaled breath have suggested the existence of an OSA-specific metabolic signature. Here, we validated this diagnostic approach and the proposed marker compounds, as well as their potential to reliably diagnose OSA. In this cross-sectional observational study, exhaled breath was analyzed using secondary electrospray ionization high-resolution mass spectrometry. The study cohort included untreated OSA patients, OSA patients treated with continuous positive airway pressure and healthy subjects. The robustness of previously reported OSA markers was validated based on detectability, significant differences between groups (Mann-Whitney U test) and classification performance. The breath analysis of 118 participants resulted in 42 previously reported markers that could be confirmed in this independent validation cohort. Nine markers were significantly increased in untreated OSA compared to treated OSA, with a subset of them being consistent with a previous validation study. An OSA prediction based on the confirmed OSA signature performed with an AUC of 0.80 (accuracy 77%, sensitivity 73% and specificity 80%). As several breath markers were clearly found to be repeatable and robust in this independent validation study, these results underscore the clinical potential of breath analysis for OSA diagnostics and monitoring.
目前缺乏用于诊断和监测阻塞性睡眠呼吸暂停(OSA)的快速可靠工具。先前使用呼气化学分析的研究表明存在 OSA 特异性代谢特征。在这里,我们验证了这种诊断方法和提出的标记化合物,以及它们可靠诊断 OSA 的潜力。在这项横断面观察性研究中,使用二级电喷雾电离高分辨率质谱法分析了呼气。研究队列包括未经治疗的 OSA 患者、接受持续气道正压通气治疗的 OSA 患者和健康受试者。基于可检测性、组间差异(Mann-Whitney U 检验)和分类性能,验证了先前报道的 OSA 标志物的稳健性。对 118 名参与者的呼吸分析产生了 42 种先前报道的标志物,这些标志物可在这个独立验证队列中得到证实。与接受治疗的 OSA 相比,未经治疗的 OSA 中 9 种标志物显著增加,其中一部分标志物与先前的验证研究一致。基于确认的 OSA 特征进行的 OSA 预测 AUC 为 0.80(准确性 77%、敏感性 73%和特异性 80%)。由于在这项独立验证研究中,一些呼吸标志物被明确发现是可重复和稳健的,因此这些结果强调了呼吸分析在 OSA 诊断和监测方面的临床潜力。