Literature DB >> 11761118

Urinary biomarkers for assessing dietary exposure to caffeine.

H M Crews1, L Olivier, L A Wilson.   

Abstract

The feasibility of using metabolites specific to caffeine as urinary biomarkers to be employed in the estimation of dietary caffeine intake is reported. The influence of inter-individual differences in the metabolism of caffeine and the effect of volunteer phenotype on the interpretation of potential biomarkers has been investigated using urinary caffeine metabolite data. This method of phenotype determination accurately reflected the rate constant for the cytochrome P4501A2 (CYP1A2)-catalysed 3-demethylation of caffeine in vivo. Three studies with up to 20 human volunteers demonstrated that a 24-h urine collection after a caffeine dose allows quantification of the metabolites excreted; that the ratios of selected metabolites used to classify the volunteers into fast, intermediate or slow caffeine metabolizers by CYP1A2 phenotype gave a similar result (2:7:3, slow:intermediate:fast) to that found in the general population (1:7:2); and that three metabolites, 1,7-dimethylxanthine, 1,7-dimethyluric acid and 1-methylxanthine, could be studied further as potential biomarkers for caffeine dietary intake.

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Year:  2001        PMID: 11761118     DOI: 10.1080/02652030110056630

Source DB:  PubMed          Journal:  Food Addit Contam        ISSN: 0265-203X


  9 in total

1.  Urine excretion of caffeine and select caffeine metabolites is common in the U.S. population and associated with caffeine intake.

Authors:  Michael E Rybak; Maya R Sternberg; Ching-I Pao; Namanjeet Ahluwalia; Christine M Pfeiffer
Journal:  J Nutr       Date:  2015-02-04       Impact factor: 4.798

2.  A genome-wide association study of caffeine-related sleep disturbance: confirmation of a role for a common variant in the adenosine receptor.

Authors:  Enda M Byrne; Julie Johnson; Allan F McRae; Dale R Nyholt; Sarah E Medland; Philip R Gehrman; Andrew C Heath; Pamela A F Madden; Grant W Montgomery; Georgia Chenevix-Trench; Nicholas G Martin
Journal:  Sleep       Date:  2012-07-01       Impact factor: 5.849

3.  Sources of Variation in Food-Related Metabolites during Pregnancy.

Authors:  Talha Rafiq; Sandi M Azab; Sonia S Anand; Lehana Thabane; Meera Shanmuganathan; Katherine M Morrison; Stephanie A Atkinson; Jennifer C Stearns; Koon K Teo; Philip Britz-McKibbin; Russell J de Souza
Journal:  Nutrients       Date:  2022-06-16       Impact factor: 6.706

Review 4.  Dietary biomarkers: advances, limitations and future directions.

Authors:  Valisa E Hedrick; Andrea M Dietrich; Paul A Estabrooks; Jyoti Savla; Elena Serrano; Brenda M Davy
Journal:  Nutr J       Date:  2012-12-14       Impact factor: 3.271

5.  Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM.

Authors:  N Amin; E Byrne; J Johnson; G Chenevix-Trench; S Walter; I M Nolte; J M Vink; R Rawal; M Mangino; A Teumer; J C Keers; G Verwoert; S Baumeister; R Biffar; A Petersmann; N Dahmen; A Doering; A Isaacs; L Broer; N R Wray; G W Montgomery; D Levy; B M Psaty; V Gudnason; A Chakravarti; P Sulem; D F Gudbjartsson; L A Kiemeney; U Thorsteinsdottir; K Stefansson; F J A van Rooij; Y S Aulchenko; J J Hottenga; F R Rivadeneira; A Hofman; A G Uitterlinden; C J Hammond; S-Y Shin; A Ikram; J C M Witteman; A C J W Janssens; H Snieder; H Tiemeier; B H R Wolfenbuttel; B A Oostra; A C Heath; E Wichmann; T D Spector; H J Grabe; D I Boomsma; N G Martin; C M van Duijn
Journal:  Mol Psychiatry       Date:  2011-08-30       Impact factor: 15.992

6.  Relation of 24-hour urinary caffeine and caffeine metabolite excretions with self-reported consumption of coffee and other caffeinated beverages in the general population.

Authors:  Dusan Petrovic; Sandrine Estoppey Younes; Menno Pruijm; Belén Ponte; Daniel Ackermann; Georg Ehret; Nicolas Ansermot; Markus Mohaupt; Fred Paccaud; Bruno Vogt; Antoinette Pechère-Bertschi; Pierre-Yves Martin; Michel Burnier; Chin B Eap; Murielle Bochud; Idris Guessous
Journal:  Nutr Metab (Lond)       Date:  2016-11-17       Impact factor: 4.169

7.  Urine caffeine metabolites and hearing threshold shifts in US adults: a cross-sectional study.

Authors:  Lili Long; Yuedi Tang
Journal:  Sci Rep       Date:  2021-11-03       Impact factor: 4.379

8.  Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology.

Authors:  Shu-Yu Hsu; Mohamed B Bayati; Chenhui Li; Hsin-Yeh Hsieh; Anthony Belenchia; Jessica Klutts; Sally A Zemmer; Melissa Reynolds; Elizabeth Semkiw; Hwei-Yiing Johnson; Trevor Foley; Chris G Wieberg; Jeff Wenzel; Marc C Johnson; Chung-Ho Lin
Journal:  medRxiv       Date:  2022-03-15

9.  Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology.

Authors:  Shu-Yu Hsu; Mohamed Bayati; Chenhui Li; Hsin-Yeh Hsieh; Anthony Belenchia; Jessica Klutts; Sally A Zemmer; Melissa Reynolds; Elizabeth Semkiw; Hwei-Yiing Johnson; Trevor Foley; Chris G Wieberg; Jeff Wenzel; Marc C Johnson; Chung-Ho Lin
Journal:  Water Res       Date:  2022-08-15       Impact factor: 13.400

  9 in total

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