Abstract :
[en] In the galaxy of Omics Science, breathomics (i.e., exhaled breath analysis) knows an exponential growth. The full characterization of the breath composition and the understanding of the origin of these chemicals could have a gigantic impact for clinical research. Indeed, the potential of using non-invasive breath testing for patient status evaluation could be a game changer in disease monitoring and personalized medicine.
Following that goal, there are numerous applications under development from cancer detection to diet adjustment. However, the complete characterization of the exhaled breath composition represents a complex analytical quest. From the exhaustive and reliable sampling, through robust untargeted analysis, to validated markers identification, the playground is large and require the development of new analytical workflows. To ensure the robustness of the entire process, every step must be carefully optimized and controlled with a robust QA/QC system.
In order to resolve the complex composition of such samples, a powerful analytical technique is required. To obtain an untargeted screening of exhaled breath sample comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) is a go to analytical solution. GC×GC-MS provides high separation resolution and orthogonal compounds identification metrics. Indeed, the retention times combined to the MS fragmentogram and potentially to the high-resolution MS provide strong identification confidence, which can reach level 2 MSI (metabolomics standard initiative) classification in a single analysis.
The organic and biological analytical chemistry group (OBiAChem) from Liège University has been dedicating a lot of effort to tackle the challenges on the road of robust breath test. In this webinar, we will cover the different technological aspects of exhaled breath research including sampling, analysis, data processing, and QA/QC. In addition, we will cover some clinical applications and discuss the transferability of breath testing for large scale population screening.
