Arulvasan Wisenave, Greenwood Julia, Ball Madeleine L, Chou Hsuan, Coplowe Simon, Birch Owen, Gordon Patrick, Ratiu Andreea, Lam Elizabeth, Tardelli Matteo, Szkatulska Monika, Swann Shane, Levett Steven, Mead Ella, van Schooten Frederik-Jan, Smolinska Agnieszka, Boyle Billy, Allsworth Max
Owlstone Medical Ltd., Cambridge, UK.
Faculty of Health, Medicine and Life Sciences, Pharmacology and Toxicology, Maastricht University, Maastricht, Netherlands.
Metabolomics. 2025 Jan 20;21(1):17. doi: 10.1007/s11306-024-02218-8.
Breath Volatile organic compounds (VOCs) are promising biomarkers for clinical purposes due to their unique properties. Translation of VOC biomarkers into the clinic depends on identification and validation: a challenge requiring collaboration, well-established protocols, and cross-comparison of data. Previously, we developed a breath collection and analysis method, resulting in 148 breath-borne VOCs identified.
To develop a complementary analytical method for the detection and identification of additional VOCs from breath. To develop and implement upgrades to the methodology for identifying features determined to be "on-breath" by comparing breath samples against paired background samples applying three metrics: standard deviation, paired t-test, and receiver-operating-characteristic (ROC) curve.
A thermal desorption (TD)-gas chromatography (GC)-mass spectrometry (MS)-based analytical method utilizing a PEG phase GC column was developed for the detection of biologically relevant VOCs. The multi-step VOC identification methodology was upgraded through several developments: candidate VOC grouping schema, ion abundance correlation based spectral library creation approach, hybrid alkane-FAMES retention indexing, relative retention time matching, along with additional quality checks. In combination, these updates enable highly accurate identification of breath-borne VOCs, both on spectral and retention axes.
A total of 621 features were statistically determined as on-breath by at least one metric (standard deviation, paired t-test, or ROC). A total of 38 on-breath VOCs were able to be confidently identified from comparison to chemical standards.
The total confirmed on-breath VOCs is now 186. We present an updated methodology for high-confidence VOC identification, and a new set of VOCs commonly found on-breath.
呼吸挥发性有机化合物（VOCs）因其独特性质，有望成为临床应用的生物标志物。将VOC生物标志物转化应用于临床取决于识别和验证：这是一项需要多方协作、完善方案以及数据交叉比较的挑战。此前，我们开发了一种呼吸采集与分析方法，已识别出148种呼出的VOCs。
开发一种补充分析方法，用于检测和识别呼出气体中的其他VOCs。通过将呼吸样本与配对的背景样本进行比较，应用标准差、配对t检验和受试者工作特征（ROC）曲线这三个指标，开发并实施对被确定为“呼吸中存在”特征的识别方法的升级。
开发了一种基于热脱附（TD）-气相色谱（GC）-质谱（MS）的分析方法，使用聚乙二醇（PEG）相GC柱来检测具有生物学相关性的VOCs。通过多项改进对多步骤VOC识别方法进行了升级：候选VOC分组方案、基于离子丰度相关性的光谱库创建方法、混合烷烃-脂肪酸甲酯保留指数、相对保留时间匹配以及额外的质量检查。综合起来，这些更新能够在光谱和保留轴上高度准确地识别呼出的VOCs。
共有621个特征通过至少一个指标（标准差、配对t检验或ROC）在统计学上被确定为呼吸中存在。通过与化学标准品比较，共能可靠识别出38种呼吸中存在的VOCs。
目前确认的呼吸中存在的VOCs总数为186种。我们展示了一种用于高可信度VOC识别的更新方法，以及一组新的常见于呼吸中的VOCs。
