John van Geest Centre for Brain Repair, Department of Clinical Neuroscience, University of Cambridge, Forvie Site, Cambridge, UK.
Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa, Israel.
J Parkinsons Dis. 2022;12(3):993-1002. doi: 10.3233/JPD-213133.
The analysis of volatile organic compounds (VOCs) collected in breath samples has the potential to be a rapid, non-invasive test to aid in the clinical diagnosis and tracking of chronic conditions such as Parkinson's disease (PD).
To assess the feasibility and utility of breath sample analysis done, both at point of collection in clinic and when sent away to be analyzed remotely, to diagnose, stratify and monitor disease course in a moderately large cohort of patients with PD.
Breath samples were collected from 177 people with PD and 37 healthy matched control individuals followed over time. Standard clinical data (MDS-UPDRS & cognitive assessments) from the PD patients were collected at the same time as the breath sample was taken, these measures were then correlated with the breath test analysis of exhaled VOCs.
The breath test was able to distinguish patients with PD from healthy control participants and correlated with disease stage. The off-line system (remote analysis) gave good results with overall classification accuracies across a range of clinical measures of between 73.6% to 95.6%. The on-line (in clinic) system showed comparable results but with lower levels of correlation, varying between 33.5% to 82.4%. Chemical analysis identified 29 potential molecules that were different and which may relate to pathogenic pathways in PD.
Breath analysis shows potential for PD diagnostics and monitoring. Both off-line and on-line sensor systems were easy to do and provided comparable results which will enable this technique to be easily adopted in clinic if larger studies confirm our findings.
分析呼出气样本中的挥发性有机化合物（VOCs）有可能成为一种快速、非侵入性的检测方法，辅助临床诊断和跟踪帕金森病（PD）等慢性疾病。
评估在临床现场和远程分析时进行呼出气样本分析，以诊断、分层和监测相当大规模 PD 患者队列中疾病进程的可行性和实用性。
从 177 名 PD 患者和 37 名健康匹配的对照个体中收集呼出气样本，并随时间进行随访。在采集呼出气样本的同时，收集 PD 患者的标准临床数据（MDS-UPDRS 和认知评估），然后将这些测量值与呼出气 VOC 分析进行相关分析。
该呼气测试能够区分 PD 患者和健康对照参与者，并与疾病阶段相关。离线系统（远程分析）在一系列临床测量中具有良好的整体分类准确率，为 73.6%至 95.6%。在线系统（临床现场）显示出可比的结果，但相关性较低，范围为 33.5%至 82.4%。化学分析确定了 29 种可能不同的潜在分子，这些分子可能与 PD 中的致病途径有关。
呼出气分析显示出在 PD 诊断和监测方面的潜力。离线和在线传感器系统都易于操作，并提供可比的结果，如果更大规模的研究证实我们的发现，这将使该技术能够在临床中轻松采用。
Zotero 插件