Detecting Beer Intake by Unique Metabolite Patterns

Area of Science:

• Metabolomics
• Biomarker Discovery
• Nutritional Science

Background:

• Assessing beer intake accurately is challenging due to a lack of reliable biomarkers.
• Understanding beer consumption is crucial for evaluating its health-related effects.

Purpose of the Study:

• To identify plasma and urine metabolites linked to recent beer consumption.
• To develop a qualitative biomarker for detecting beer intake.

Main Methods:

• Untargeted metabolomics was used to analyze plasma and urine samples from a controlled meal study.
• Participants consumed different beverages, including various beers and a soft drink.
• Liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF) analyzed metabolites in beverages, wort, and hops extract.

Main Results:

• A unique metabolite pattern, including compounds from raw materials (e.g., N-methyl tyramine sulfate, iso-α-acids) and production (e.g., pyro-glutamyl proline), was identified.
• A biomarker model based on this pattern accurately predicted beer intake in a separate study group (AUC = 1).
• The model demonstrated high specificity and accuracy in detecting beer consumption up to 12 hours post-intake.

Conclusions:

• A novel biomarker model comprising four key metabolites can accurately measure recent beer consumption.
• This biomarker reflects both the raw materials and production process of beer.
• The developed tool offers a specific and accurate method for quantifying beer intake.