RESUMEN
Volatile metabolites in exhaled air have promising potential as diagnostic biomarkers. However, the combination of low mass, similar chemical composition, and low concentrations introduces the challenge of sorting the data to identify markers of value. In this paper, we report the development of pyAIR, a software tool for searching for volatile organic compounds (VOCs) markers in multi-group datasets, tailored for Thermal-Desorption Gas-Chromatography High Resolution Mass-Spectrometry (TD-GC-HRMS) output. pyAIR aligns the compounds between samples by spectral similarity coupled with retention times (RT), and statistically compares the groups for compounds that differ by intensity. This workflow was successfully tested and evaluated on gaseous samples spiked with 27 model VOCs at six concentrations, divided into three groups, down to 0.3 nL/L. All analytes were correctly detected and aligned. More than 80% were found to be significant markers with a p-value < 0.05; several were classified as possibly significant markers (p-value < 0.1), while a few were removed due to background level. In all group comparisons, low rates of false markers were found. These results showed the potential of pyAIR in the field of trace-level breathomics, with the capability to differentially examine several groups, such as stages of illness.
Asunto(s)
Pruebas Respiratorias , Compuestos Orgánicos Volátiles , Biomarcadores/análisis , Pruebas Respiratorias/métodos , Cromatografía de Gases y Espectrometría de Masas/métodos , Programas Informáticos , Compuestos Orgánicos Volátiles/análisisRESUMEN
This study demonstrates the adverse effects of water in exhaled breath samples on the accuracy of breath biomarker analysis when using gas chromatography. The presence of water in exhaled breath significantly modifies the retention times and peak areas of compounds, particularly for low-boiling, early eluting compounds. To tackle this issue, a two-step approach is introduced. The process begins with thorough desorption of the sorbent tube using a high split ratio and a short analysis duration, followed by a secondary analysis of the same tube. The efficacy of the new, straightforward approach was illustrated using humid breath samples and 57 compound standard mixture. This study highlights the importance of proper sample pretreatment and analysis to ensure reliable and accurate results in clinical research.