Human breath analysis may support the existence of individual metabolic phenotypes

Abstract

The metabolic phenotype varies widely due to external factors such as diet and gut microbiome composition, among others. Despite these temporal fluctuations, urine metabolite profiling studies have suggested that there are highly individual phenotypes that persist over extended periods of time. This hypothesis was tested by analyzing the exhaled breath of a group of subjects during nine days by mass spectrometry. Consistent with previous metabolomic studies based on urine, we conclude that individual signatures of breath composition exist. The confirmation of the existence of stable and specific breathprints may contribute to strengthen the inclusion of breath as a biofluid of choice in metabolomic studies. In addition, the fact that the method is rapid and totally non-invasive, yet individualized profiles can be tracked, makes it an appealing approach.

Figure 1. Real-time analysis allows for the rapid breathprinting of subjects.

During the 1.5 hours experiment shown above, nine subjects breathed into the mass spectrometer. The subjects' label codes are indicated at the top of each of the three replicate measurements in the top trace. The three traces correspond to the ion intensity as a function of time for m/z 59, 151 and 207. Each subject breathed in triplicate, which is illustrated by the three steps of the signal above the background per subject. This snapshot already illustrates the high inter-subject breathprint variability.

Figure 2. Temporal variability of the three compounds shown in figure 1 over the nine days of measurements for the eleven subjects (left).

The central mark of each box corresponds to the median, the edges of the box are the 25^th and 75^th percentiles, the whiskers extend to the most extreme data points not considered outliers, and outliers are plotted individually (beyond +/–2.7σ). The P values resulting from the Kruskal-Wallis test are quoted on top of the box-plots. Further multicomparison tests (right) showed that, with some exceptions, in most of the cases inter-subject variability was not significantly different (overlapping intervals).

Figure 3. Projection of the 193 breath mass spectra onto the first three dimensions obtained by supervised Kruskal-Wallis/PCA/CA.

Grouping according to breath donor (represented by different colors and symbols) becomes apparent. The inset displays the blind classification results upon a cross-validation (average of 500 Monte Carlo repartitions). The overall breath-mass spectrum to breath-donor recognition score was 76%.