Bregy Lukas, Nussbaumer-Ochsner Yvonne, Martinez-Lozano Sinues Pablo, García-Gómez Diego, Suter Yannick, Gaisl Thomas, Stebler Nina, Gaugg Martin Thomas, Kohler Malcolm, Zenobi Renato
Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland.
Department of Pulmonology, University Hospital Zurich, Zurich, Switzerland.
Clin Mass Spectrom. 2018 Feb 8;7:29-35. doi: 10.1016/j.clinms.2018.02.003. eCollection 2018 Jan.
New mass spectrometry (MS) techniques analysing exhaled breath have the potential to better define airway diseases. Here, we present our work to profile the volatile organic compounds (VOCs) in exhaled breath from patients with chronic obstructive pulmonary disease (COPD), using real-time MS, and relate this disease-specific breath profile to functional disease markers.
In a matched cohort study, patients with COPD, according to GOLD criteria, were recruited. Exhaled breath analysis by untargeted MS was performed using secondary electrospray ionization - high-resolution MS (SESI-HRMS).
Exhaled breath from 22 patients with COPD (mean age 58.6 ± 6.9 years, FEV 58.5 ± 19.9% predicted, 32.4 ± 19.2 pack years smoking) and 14 controls (mean age 58.1 ± 8.1 years, FEV 102.5 ± 11.3% predicted, 23.6 ± 12.5 pack years smoking) was analysed using SESI-HRMS. From 1441 different features, 43 markers were identified that allowed discrimination between the two groups with an accuracy of 89% (CI 74-97%), a sensitivity of 93%, and a specificity of 86%. The markers were determined to be metabolites of oxidative stress processes, such as fatty acids, aldehydes and amino acids, resulting from lung muscle degradation.
Real-time breath analysis by SESI-MS allows molecular profiling of exhaled breath, can distinguish patients with COPD from matched healthy controls and provides insights into the disease pathogenesis.
分析呼出气的新型质谱（MS）技术有潜力更好地界定气道疾病。在此，我们展示了我们的工作，即使用实时质谱对慢性阻塞性肺疾病（COPD）患者呼出气中的挥发性有机化合物（VOCs）进行分析，并将这种疾病特异性的呼吸谱与功能性疾病标志物相关联。
在一项匹配队列研究中，招募了符合GOLD标准的COPD患者。使用二次电喷雾电离-高分辨率质谱（SESI-HRMS）对呼出气进行非靶向质谱分析。
使用SESI-HRMS分析了22例COPD患者（平均年龄58.6±6.9岁，FEV为预测值的58.5±19.9%，吸烟史32.4±19.2包年）和14例对照者（平均年龄58.1±8.1岁，FEV为预测值的102.5±11.3%，吸烟史23.6±12.5包年）的呼出气。从1441个不同特征中，鉴定出43个标志物，这些标志物能够区分两组，准确率为89%（CI 74-97%），灵敏度为93%，特异性为86%。这些标志物被确定为氧化应激过程的代谢产物，如脂肪酸、醛类和氨基酸，由肺肌降解产生。
通过SESI-MS进行实时呼吸分析可对呼出气进行分子分析，能够将COPD患者与匹配的健康对照者区分开来，并为疾病发病机制提供见解。
