Cross-validation of the peppermint benchmarking experiment across three analytical platforms.

Abstract

The Peppermint Experiment is a breath analysis benchmarking initiative that seeks to address the lack of inter-comparability of outcomes across independent breath biomarker studies. In this experiment, the washout profiles of volatile terpene constituents of encapsulated peppermint oil (mainlyα-pinene,β-pinene, limonene and 1,8-cineole) in exhaled breath are characterized through a series of measurements at defined sampling intervals up to 6 h after ingestion of the capsule. In the present work, the Peppermint Experiment was carried out on a cohort of volunteers (n= 11) that provided breath samples in three sittings on different days (i.e. triplicates per volunteer) for concurrent analysis by three different analytical platforms. These platforms were proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOFMS) interfaced with a buffered end-tidal (BET) breath sampler, gas chromatography-ion mobility spectrometry (GC-IMS) in conjunction with a compatible handheld direct breath sampler, and thermal desorption comprehensive two-dimensional gas chromatography-time-of-flight-mass spectrometry (TD-GC×GC-TOFMS) with a Respiration Collection forin-vitroAnalysis (ReCIVA) system for trapping breath volatiles onto adsorbent tubes. Regression analysis yielded mean washout times across the cohort of 448 min (PTR-TOFMS and GC-IMS) and 372 min (TD-GC×GC-TOFMS), which are in good alignment with published benchmark values. Large variations in washout profiles were observed at the individuals level, both between (inter-individual) and within (intra-individual) participants, indicating high variability in the degree of absorption, distribution, metabolism and excretion of volatile terpenes in the body within individuals and across the cohort. The comparably low inter-instrument variability indicates that differences in benchmark values from independent studies reported in the literature are driven by biological variability rather than different performances between sampling methods or analytical platforms.