ETH Zurich, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 3, 8093, Zürich, Switzerland.
University Hospital Zurich, Department of Pulmonology, Rämistrasse 100, 8091, Zürich, Switzerland.
Sleep Med. 2021 Sep;85:75-86. doi: 10.1016/j.sleep.2021.06.040. Epub 2021 Jul 3.
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.
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).
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.
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.
"Mass Spectral Fingerprinting in Obstructive Sleep Apnoea", NCT02810158, www.ClinicalTrials.gov.
阻塞性睡眠呼吸暂停（OSA）是一种诊断不足的呼吸系统疾病，具有负面的代谢和心血管影响。目前，诊断 OSA 的金标准是住院多导睡眠图，这是一项耗时且昂贵的程序，通常对患者不方便。最近的研究表明，基于疾病特异性代谢模式，呼吸分析有可能用于诊断 OSA。然而，这些发现都没有在更大和更广泛的队列中得到验证，这是其在临床应用中的必要步骤。
在本研究中，我们在一组可能患有 OSA 的患者（N=149）中验证了一组呼吸生物标志物。这些标志物是我们小组通过二次电喷雾电离高分辨率质谱（SESI-HRMS）先前确定的。
在这里，我们可以确认 OSA 患者呼出的呼吸代谢模式与无 OSA 的对照组之间存在显著差异，以及呼吸生物标志物水平与疾病严重程度的关联。我们使用基于先前研究数据训练的分类模型对来自这个完全独立验证研究的患者进行诊断预测，其接受者操作特征曲线下的面积为 0.66，与基于问卷的 OSA 筛查相当。
因此，我们的结果表明，SESI-HRMS 呼吸分析可能有助于作为一种客观测量来筛查 OSA。然而，其真正的预测能力应该与 OSA 筛查问卷结合进行测试。
“阻塞性睡眠呼吸暂停的质谱指纹图谱”，NCT02810158，www.ClinicalTrials.gov。
