Detecting beer intake by unique metabolite patterns

TY - JOUR

T1 - Detecting beer intake by unique metabolite patterns

AU - Gürdeniz, Gözde

AU - Jensen, Morten Georg

AU - Meier, Sebastian

AU - Bech, Lene

AU - Lund, Erik

AU - Dragsted, Lars Ove

N1 - CURIS 2016 NEXS 317

PY - 2016/12/2

Y1 - 2016/12/2

N2 - Evaluation of the health related effects of beer intake is hampered by the lack of accurate tools for assessing intakes (biomarkers). Therefore, we identified plasma and urine metabolites associated with recent beer intake by untargeted metabolomics and established a characteristic metabolite pattern representing raw materials and beer production as a qualitative biomarker of beer intake. In a randomized, crossover, single-blinded meal study (MSt1), 18 participants were given, one at a time, four different test beverages: strong, regular, and nonalcoholic beers and a soft drink. Four participants were assigned to have two additional beers (MSt2). In addition to plasma and urine samples, test beverages, wort, and hops extract were analyzed by UPLC-QTOF. A unique metabolite pattern reflecting beer metabolome, including metabolites derived from beer raw material (i.e., N-methyl tyramine sulfate and the sum of iso-α-acids and tricyclohumols) and the production process (i.e., pyro-glutamyl proline and 2-ethyl malate), was selected to establish a compliance biomarker model for detection of beer intake based on MSt1. The model predicted the MSt2 samples collected before and up to 12 h after beer intake correctly (AUC = 1). A biomarker model including four metabolites representing both beer raw materials and production steps provided a specific and accurate tool for measurement of beer consumption.

AB - Evaluation of the health related effects of beer intake is hampered by the lack of accurate tools for assessing intakes (biomarkers). Therefore, we identified plasma and urine metabolites associated with recent beer intake by untargeted metabolomics and established a characteristic metabolite pattern representing raw materials and beer production as a qualitative biomarker of beer intake. In a randomized, crossover, single-blinded meal study (MSt1), 18 participants were given, one at a time, four different test beverages: strong, regular, and nonalcoholic beers and a soft drink. Four participants were assigned to have two additional beers (MSt2). In addition to plasma and urine samples, test beverages, wort, and hops extract were analyzed by UPLC-QTOF. A unique metabolite pattern reflecting beer metabolome, including metabolites derived from beer raw material (i.e., N-methyl tyramine sulfate and the sum of iso-α-acids and tricyclohumols) and the production process (i.e., pyro-glutamyl proline and 2-ethyl malate), was selected to establish a compliance biomarker model for detection of beer intake based on MSt1. The model predicted the MSt2 samples collected before and up to 12 h after beer intake correctly (AUC = 1). A biomarker model including four metabolites representing both beer raw materials and production steps provided a specific and accurate tool for measurement of beer consumption.

KW - Faculty of Science

KW - Beer

KW - Barley

KW - Hops

KW - Biomarker model

KW - Metabolomics

KW - Plasma

KW - Urine

KW - UPLC-QTOF

U2 - 10.1021/acs.jproteome.6b00635

DO - 10.1021/acs.jproteome.6b00635

M3 - Journal article

C2 - 27781435

SN - 1535-3893

VL - 15

SP - 4544

EP - 4556

JO - Journal of Proteome Research

JF - Journal of Proteome Research

IS - 12

ER -