European Journal of Clinical Pharmacology

, Volume 75, Issue 9, pp 1211–1218 | Cite as

Identification of the caffeine to trimethyluric acid ratio as a dietary biomarker to characterise variability in cytochrome P450 3A activity

  • Madelé van DykEmail author
  • John O. Miners
  • Jean-Claude Marshall
  • Linda S. Wood
  • Ashley Hopkins
  • Michael J. Sorich
  • Andrew Rowland
Pharmacokinetics and Disposition



Cytochrome P450 (CYP) 3A plays an important role in the metabolism of many clinically used drugs and exhibits substantial between-subject variability (BSV) in activity. Current methods to assess variability in CYP3A activity have limitations and there remains a need for a minimally invasive clinically translatable strategy to define CYP3A activity. The purpose of this study was to evaluate the potential for a caffeine metabolic ratio to describe variability in CYP3A activity.


The metabolic ratio 1,3,7-trimethyluric acid (TMU) to caffeine was evaluated as a biomarker to describe variability in CYP3A activity in a cohort (n = 28) of healthy 21 to 35-year-old males. Midazolam, caffeine, and TMU concentrations were assessed at baseline and following dosing of rifampicin (300 mg daily) for 7 days.


At baseline, correlation coefficients for the relationship between apparent oral midazolam clearance (CL/F) with caffeine/TMU ratio measured at 3, 4, and 6 h post dose were 0.82, 0.79, and 0.65, respectively. The strength of correlations was retained post rifampicin dosing; 0.72, 0.87, and 0.82 for the ratios at 3, 4, and 6 h, respectively. Weaker correlations were observed between the change in midazolam CL/F and change in caffeine/TMU ratio post/pre-rifampicin dosing.


BSV in CYP3A activity was well described by caffeine/TMU ratios pre- and post-induction. The caffeine/TMU ratio may be a convenient tool to assess BSV in CYP3A activity, but assessment of caffeine/TMU ratio alone is unlikely to account for all sources of variability in CYP3A activity.


CYP3A Phenotyping Metabolomics Biomarker Between-subject variability Precision medicine 


Author contributions

Participated in research design: MVD, JOM, MJS, and AR.

Recruitment and screening of trial participants: MVD.

Performed sample analysis: MVD and LSW.

Performed data analysis: MVD, JCM, and AR.

Wrote or contributed to the writing of the manuscript: MVD, JOM, JCM, LSW, MJS, and AR.

Funding information

This study was supported by a project grant (1100179) from the National Health and Medical Research Council of Australia.

Compliance with ethical standards

The study protocol was approved by the Southern Adelaide Clinical Human Research Ethics Committee (SAHREC 11.15), and informed written consent was obtained from each participant.

Conflict of interest

All authors declare that there are no conflicts of interest. Linda S Wood and Jean-Claude Marshall are employees and stock holders of Pfizer World Wide Research and Development.

Supplementary material

228_2019_2682_MOESM1_ESM.pdf (564 kb)
Supplementary Table 1 (PDF 564 kb)


  1. 1.
    Zanger UM, Schwab M (2013) Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol Ther 138(1):103–141Google Scholar
  2. 2.
    Lamba JK, Lin YS, Schuetz EG, Thummel KE (2002) Genetic contribution to variable human CYP3A-mediated metabolism. Adv Drug Deliv Rev 54(10):1271–1294Google Scholar
  3. 3.
    Wang Z, Lin YS, Zheng XE, Senn T, Hashizume T, Scian M, Dickmann LJ, Nelson SD, Baillie TA, Hebert MF, Blough D, Davis CL, Thummel KE (2012) An inducible cytochrome P450 3A4-dependent vitamin D catabolic pathway. Mol Pharmacol 81(4):498–509Google Scholar
  4. 4.
    Paine MF, Hart HL, Ludington SS, Haining RL, Rettie AE, Zeldin DC (2006) The human intestinal cytochrome P450 “pie”. Drug Metab Dispos 34(5):880–886Google Scholar
  5. 5.
    Lamba V, Panetta JC, Strom S, Schuetz EG (2010) Genetic predictors of interindividual variability in hepatic CYP3A4 expression. J Pharmacol Exp Ther 332(3):1088–1099Google Scholar
  6. 6.
    Bosilkovska M, Samer CF, Déglon J, Rebsamen M, Staub C, Dayer P, Walder B, Desmeules JA, Daali Y (2014) Geneva cocktail for cytochrome P450 and P-glycoprotein activity assessment using dried blood spots. Clin Pharmacol Ther 96(3):10Google Scholar
  7. 7.
    de Wit D, Guchelaar HJ, den Hartigh J, Gelderblom H, van Erp NP (2015) Individualized dosing of tyrosine kinase inhibitors: are we there yet? Drug Discov Today 20(1):18–36Google Scholar
  8. 8.
    Sim SC, Kacevska M, Ingelman-Sundberg M (2013) Pharmacogenomics of drug-metabolizing enzymes: a recent update on clinical implications and endogenous effects. Pharm J 13(1):1–11Google Scholar
  9. 9.
    Rowland A, van Dyk M, Mangoni AA, Miners JO, McKinnon RA, Wiese MD, Rowland A, Kichenadasse G, Gurney H, Sorich MJ (2017) Kinase inhibitor pharmacokinetics: comprehensive summary and roadmap for addressing inter-individual variability in exposure. Expert Opin Drug Metab Toxicol 13(1):31–49Google Scholar
  10. 10.
    Malaty LI, Kuper JJ (1999) Drug interactions of HIV protease inhibitors. Drug Saf 20(2):147–169Google Scholar
  11. 11.
    Rahmioglu N, Heaton J, Clement G, Gill R, Surdulescu G, Zlobecka K, Hodgkiss D, Ma Y, Hider RC, Smith NW, Ahmadi KR (2011) Genetic epidemiology of induced CYP3A4 activity. Pharmacogenet Genomics 21(10):642–651Google Scholar
  12. 12.
    van Dyk M et al (2016) A novel approach for the simultaneous quantification of 18 small molecule kinase inhibitors in human plasma. J Chromatogr B 1033:17–26Google Scholar
  13. 13.
    Smith, B., et al.,(2015) Across the continuum: DMPK experiences from preclinical to market. Proc 2015 APSA-ASCEPT JSM, O112Google Scholar
  14. 14.
    Goulooze SC, Galettis P, Boddy AV, Martin JH (2016) Monte Carlo simulations of the clinical benefits from therapeutic drug monitoring of sunitinib. Cancer Chemother Pharmacol 78(1):209–216Google Scholar
  15. 15.
    Kim HY, Martin JH, Mclachlan AJ, Boddy AV (2017) Precision dosing of targeted anticancer drugs—challenges in the real world. Transl Cancer Res 6:S1500–S1511Google Scholar
  16. 16.
    Hohmann N, Kocheise F, Carls A, Burhenne J, Haefeli WE, Mikus G (2015) Midazolam microdose to determine systemic and pre-systemic metabolic CYP3A activity in humans. Br J Clin Pharmacol 79(2):278–285Google Scholar
  17. 17.
    Jurica, J. and A. Sulcova,2012 Determination of cytochrome P450 metabolic activity using selective markers, in Topics on drug metabolism, J. Paxton, Editor., InTech: Rijeka. p. Ch. 8Google Scholar
  18. 18.
    Rowland A, van Dyk M, Hopkins AM, Mounzer R, Polasek TM, Rostami-Hodjegan A, Sorich MJ (2018) Physiologically based pharmacokinetic modeling to identify physiological and molecular characteristics driving variability in drug exposure. Clin Pharmacol Ther 104:1219–1228. Google Scholar
  19. 19.
    Streetman DS, Bertino JS Jr, Nafziger AN (2000) Phenotyping of drug-metabolizing enzymes in adults: a review of in-vivo cytochrome P450 phenotyping probes. Pharmacogenetics 10(3):187–216Google Scholar
  20. 20.
    Shin KH, Choi MH, Lim KS, Yu KS, Jang IJ, Cho JY (2013) Evaluation of endogenous metabolic markers of hepatic CYP3A activity using metabolic profiling and midazolam clearance. Clin Pharmacol Ther 94(5):601–609Google Scholar
  21. 21.
    Fuhr U, Jetter A, Kirchheiner J (2007) Appropriate phenotyping procedures for drug metabolizing enzymes and transporters in humans and their simultaneous use in the “cocktail” approach. Clin Pharmacol Ther 81(2):270–283Google Scholar
  22. 22.
    Galteau MM, Shamsa F (2003) Urinary 6beta-hydroxycortisol: a validated test for evaluating drug induction or drug inhibition mediated through CYP3A in humans and in animals. Eur J Clin Pharmacol 59(10):713–733Google Scholar
  23. 23.
    Chen Y-C, Gotzkowsky SK, Nafziger AN, Kulawy RW, Rocci ML, Bertino JS, Kashuba ADM (2006) Poor correlation between 6β-hydroxycortisol: cortisol molar ratios and midazolam clearance as measure of hepatic CYP3A activity. Br J Clin Pharmacol 62(2):187–195Google Scholar
  24. 24.
    Diczfalusy U, Kanebratt KP, Bredberg E, Andersson TB, Böttiger Y, Bertilsson L (2009) 4β-Hydroxycholesterol as an endogenous marker for CYP3A4/5 activity. Stability and half-life of elimination after induction with rifampicin. Br J Clin Pharmacol 67(1):38–43Google Scholar
  25. 25.
    Miners JO, Birkett DJ (1996) The use of caffeine as a metabolic probe for human drug metabolizing enzymes. Gen Pharmacol 27(2):245–249Google Scholar
  26. 26.
    Tassaneeyakul W, Mohamed Z, Birkett DJ, McManus ME, Veronese ME, Tukey RH, Quattrochi LC, Gonzalez FJ, Miners JO (1992) Caffeine as a probe for human cytochromes P450: validation using cDNA-expression, immunoinhibition and microsomal kinetic and inhibitor techniques. Pharmacogenetics 2(4):173–183Google Scholar
  27. 27.
    Tassaneeyakul W, Birkett DJ, McManus ME, Tassaneeyakul W, Veronese ME, Andersson T, Tukey RH, Miners JO (1994) Caffeine metabolism by human hepatic cytochromes p450: contributions of 1A2, 2E1 and 3A isoforms. Biochem Pharmacol 47(10):1767–1776Google Scholar
  28. 28.
    Tassaneeyakul, W., 1994 In vivo and vitro probes for human cytochromes P450. PhD thesis. , Flinders University of South AustraliaGoogle Scholar
  29. 29.
    van Dyk M, Marshall JC, Sorich MJ, Wood LS, Rowland A (2018) Assessment of inter-racial variability in CYP3A4 activity and inducibility among healthy adult males. Eur J Clin Pharmacol 74:913–920. Google Scholar
  30. 30.
    Kennedy MJ, Scripture CD, Kashuba AD, Scott CS, Gaedigk A, Kearns GL (2004) Activities of cytochrome P450 1A2, N-acetyltransferase 2, xanthine oxidase, and cytochrome P450 2D6 are unaltered in children with cystic fibrosis. Clin Pharmacol Ther 75(3):163–171Google Scholar
  31. 31.
    Nordmark A, Lundgren S, Cnattingius S, Rane A (1999) Dietary caffeine as a probe agent for assessment of cytochrome P4501A2 activity in random urine samples. Br J Clin Pharmacol 47(4):397–402Google Scholar
  32. 32.
    Rowland A, van Dyk M, Warncken D, Mangoni AA, Sorich MJ, Rowland A (2018) Evaluation of modafinil as a perpetrator of metabolic drug-drug interactions. Br J Clin Pharmacol 84:501–509Google Scholar
  33. 33.
    Hohmann N, Haefeli WE, Mikus G (2016) CYP3A activity: towards dose adaptation to the individual. Expert Opin Drug Metab Toxicol 12(5):479–497Google Scholar
  34. 34.
    Klein K, Zanger UM (2013) Pharmacogenomics of cytochrome P450 3A4: recent progress toward the “missing heritability problem. Front Genet 4:12Google Scholar
  35. 35.
    Elens L, van Gelder T, Hesselink DA, Haufroid V, van Schaik RHN (2013) CYP3A4*22: promising newly identified CYP3A4 variant allele for personalizing pharmacotherapy. Pharmacogenomics 14(1):47–62Google Scholar
  36. 36.
    Tseng E, Walsky RL, Luzietti RA, Harris JJ, Kosa RE, Goosen TC, Zientek MA, Obach RS (2014) Relative contributions of cytochrome CYP3A4 versus CYP3A5 for CYP3A-cleared drugs assessed in vitro using a CYP3A4-selective inactivator (CYP3cide). Drug Metab Dispos 42(7):1163–1173Google Scholar
  37. 37.
    Kinirons MT, O’Shea D, Downing TE, Fitzwilliam AT, Joellenbeck L, Groopman JD, Wilkinson GR, Wood AJJ (1993) Absence of correlations among three putative in vivo probes of human cytochrome P4503A activity in young healthy men. Clin Pharmacol Ther 54(6):621–629Google Scholar
  38. 38.
    Diczfalusy U et al (2011) 4beta-Hydroxycholesterol, an endogenous marker of CYP3A4/5 activity in humans. Br J Clin Pharmacol 71(2):183–189Google Scholar
  39. 39.
    Bjorkhem-Bergman L, Backstrom T, Nylen H, Ronquist-Nii Y, Bredberg E, Andersson TB, Bertilsson L, Diczfalusy U (2013) Comparison of endogenous 4beta-hydroxycholesterol with midazolam as markers for CYP3A4 induction by rifampicin. Drug Metab Dispos 41(8):1488–1493Google Scholar
  40. 40.
    Gu L et al (1992) Biotransformation of caffeine, paraxanthine, theobromine and theophylline by cDNA-expressed human CYP1A2 and CYP2E1. Pharmacogenetics 2(2):73–77Google Scholar
  41. 41.
    Kot M, Daniel WA (2008) The relative contribution of human cytochrome P450 isoforms to the four caffeine oxidation pathways: an in vitro comparative study with cDNA-expressed P450s including CYP2C isoforms. Biochem Pharmacol 76(4):543–551Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Madelé van Dyk
    • 1
    Email author
  • John O. Miners
    • 1
  • Jean-Claude Marshall
    • 2
  • Linda S. Wood
    • 2
  • Ashley Hopkins
    • 1
  • Michael J. Sorich
    • 1
  • Andrew Rowland
    • 1
  1. 1.Department of Clinical Pharmacology, College of Medicine and Public HealthFlinders UniversityAdelaideAustralia
  2. 2.Precision MedicinePfizer Worldwide Research and DevelopmentGrotonUSA

Personalised recommendations