Nutrivolatilomics of Urinary and Plasma Samples to Identify Candidate Biomarkers after Cheese, Milk, and Soy-Based Drink Intake in Healthy Humans

• DOI: 10.1021/acs.jproteome.0c00324
• Publication Date: 2020-09-03T10:48:00Z
• Authors: Pascal Fuchsmann; Mireille Tena Stern; Linda H. Münger; Grégory Pimentel; Kathryn J. Burton; Nathalie Vionnet; Guy Vergères
• Keywords: 0301 basic medicine; 2. Zero hunger; 03 medical and health sciences; Milk; Cheese; Metabolome; Humans; Metabolomics; Biomarkers; Gas Chromatography-Mass Spectrometry; 6. Clean water; 3. Good health

The characterization of volatile compounds in biological fluids offers a distinct approach to study the metabolic imprint of foods on the human metabolome, particularly to identify novel biomarkers of food intake (BFIs) that are not captured by classic metabolomics. Using a combination of dynamic headspace vacuum transfer In Trap extraction and gas chromatography coupled with mass spectrometry, we measured volatile compounds (the "volatilome") in plasma and urine samples from a randomized controlled crossover intervention study in which 11 healthy subjects ingested milk, cheese, or a soy-based drink. More than 2000 volatile compounds were detected in plasma, while 1260 compounds were detected in urine samples. A postprandial response in plasma was confirmed for 697 features. Univariate and multivariate analyses identified four molecules in plasma and 31 molecules in urine samples differentiating the ingestion of the foods, of which three metabolites in plasma and nine in urine were specific to the dairy products. Among these molecules, heptan-2-one, 3,5-dimethyloctan-2-one, and undecan-2-one in plasma and 3-ethylphenol, heptan-2-one, 1-methoxy-2-propyl acetate, and 9-decenoic acid were highly discriminative for dairy or cheese intake. In urine, 22 volatile compounds were highly discriminative for soy-based drink intake. The majority of these molecules have not been reported in humans. Our findings highlight the potential of plasma and urinary volatilomics for detection of novel dietary biomarkers.