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A Metabolomic Study of Biomarkers of Habitual Coffee Intake in Four European Countries
Author(s) -
Rothwell Joseph A.,
KeskiRahkonen Pekka,
Robinot Nivonirina,
Assi Nada,
Casagrande Corinne,
Jenab Mazda,
Ferrari Pietro,
BoutronRuault MarieChristine,
MahamatSaleh Yahya,
Mancini Francesca Romana,
Boeing Heiner,
Katzke Verena,
Kühn Tilman,
Niforou Katerina,
Trichopoulou Antonia,
Valanou Elisavet,
Krogh Vittorio,
Mattiello Amalia,
Palli Domenico,
Sacerdote Carlotta,
Tumino Rosario,
Scalbert Augustin
Publication year - 2019
Publication title -
molecular nutrition and food research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.495
H-Index - 131
eISSN - 1613-4133
pISSN - 1613-4125
DOI - 10.1002/mnfr.201900659
Subject(s) - trigonelline , caffeine , metabolomics , food science , quinic acid , european prospective investigation into cancer and nutrition , biomarker , population , medicine , roasting , chemistry , prospective cohort study , biochemistry , environmental health , chromatography
Scope The goal of this work is to identify circulating biomarkers of habitual coffee intake using a metabolomic approach, and to investigate their associations with coffee intake in four European countries. Methods and results Untargeted mass spectrometry‐based metabolic profiling is performed on serum samples from 451 participants of the European Prospective Investigation on Cancer and Nutrition (EPIC) originating from France, Germany, Greece, and Italy. Eleven coffee metabolites are found to be associated with self‐reported habitual coffee intake, including eight more strongly correlated ( r = 0.25–0.51, p < 10E −07 ). Trigonelline shows the highest correlation, followed by caffeine, two caffeine metabolites (paraxanthine and 5‐Acetylamino‐6‐amino‐3‐methyluracil), quinic acid, and three compounds derived from coffee roasting (cyclo(prolyl‐valyl), cyclo(isoleucyl‐prolyl), cyclo(leucyl‐prolyl), and pyrocatechol sulfate). Differences in the magnitude of correlations are observed between countries, with trigonelline most highly correlated with coffee intake in France and Germany, quinic acid in Greece, and cyclo(isoleucyl‐prolyl) in Italy. Conclusion Several biomarkers of habitual coffee intake are identified. No unique biomarker is found to be optimal for all tested populations. Instead, optimal biomarkers are shown to depend on the population and on the type of coffee consumed. These biomarkers should help to further explore the role of coffee in disease risk.