Multimodal combination of GC × GC-HRTOFMS and SIFT-MS for asthma phenotyping using exhaled breath

Abstract

Chronic inflammatory lung diseases impact more than 300 million of people worldwide. Because they are not curable, these diseases have a high impact on both the quality of life of patients and the healthcare budget. The stability of patient condition relies mostly on constant treatment adaptation and lung function monitoring. However, due to the variety of inflammation phenotypes, almost one third of the patients receive an ineffective treatment. To improve phenotyping, we evaluated the complementarity of two techniques for exhaled breath analysis: full resolving comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC × GC-HRTOFMS) and rapid screening selected ion flow tube MS (SIFT-MS). GC × GC-HRTOFMS has a high resolving power and offers a full overview of sample composition, providing deep insights on the ongoing biology. SIFT-MS is usually used for targeted analyses, allowing rapid classification of samples in defined groups. In this study, we used SIFT-MS in a possible untargeted full-scan mode, where it provides pattern-based classification capacity. We analyzed the exhaled breath of 50 asthmatic patients. Both techniques provided good classification accuracy (around 75%), similar to the efficiency of other clinical tools routinely used for asthma phenotyping. Moreover, our study provides useful information regarding the complementarity of the two techniques.

Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD

“…For example, sputum inflammatory profiles were able to predict both neutrophilic and eosinophilic asthma [47]. Another method that can be used for asthma phenotyping is sputum cell count [125,126]. However, other interactions of leukocytes, epithelial and stromal cells, proved their contribution to inflammatory processes in asthmatic patients [127].…”

Noninvasive monitoring of fibre fermentation in healthy volunteers by analyzing breath volatile metabolites: lessons from the FiberTAG intervention study

“…15 If target components are not known, SIFT-MS is used in untargeted scan mode, where it provides pattern-based classification capacity, the identification of probable biomarkers, and retrospective quantification of target components. 16 …”

Feasibility study on exhaled-breath analysis by untargeted Selected-Ion Flow-Tube Mass Spectrometry in children with cystic fibrosis, asthma, and healthy controls: Comparison of data pretreatment and classification techniques

“…Important to notice is that the "raw data" X matrix was already normalized by the Syft Technologies proprietary algorithm before other data pretreatment methods were applied. This normalisation includes for every individual ion channel a correction based on a linear quantitative signal, considering both reagent and product ion, as a function of lens voltage, temperature and molecular weight [24].…”

“…These last data preprocessing approaches (12)(13)(14)(15) were also applied in combination with Dong's Algorithm (16)(17)(18)(19). Approaches 12-15 were found to be suitable in untargeted full-scan SIFT-MS analyses, as a diagnostic tool, for asthma phenotyping [24].…”