Evaluation at scale of microbiome-derived metabolites as biomarker of flavan-3-ol intake in epidemiological studies

Javier I Ottaviani, Redmond Fong, Jennifer Kimball, Jodi L Ensunsa, Abigail Britten, Debora Lucarelli, Robert Luben, Philip B Grace, Deborah H Mawson, Amy Tym, Antonia Wierzbicki, Kay-Tee Khaw, Hagen Schroeter, Gunter G C Kuhnle, Javier I Ottaviani, Redmond Fong, Jennifer Kimball, Jodi L Ensunsa, Abigail Britten, Debora Lucarelli, Robert Luben, Philip B Grace, Deborah H Mawson, Amy Tym, Antonia Wierzbicki, Kay-Tee Khaw, Hagen Schroeter, Gunter G C Kuhnle

Abstract

The accurate assessment of dietary intake is crucial to investigate the effect of diet on health. Currently used methods, relying on self-reporting and food composition data, are known to have limitations and might not be suitable to estimate the intake of many bioactive food components. An alternative are nutritional biomarkers, which can allow an unbiased assessment of intake. They require a careful evaluation of their suitability, including: (a) the availability of a precise, accurate and robust analytical method, (b) their specificity (c) a consistent relationship with actual intake. We have evaluated human metabolites of a microbiome-derived flavan-3-ol catabolite, 5-(3',4'-dihydroxyphenyl)-[gamma]-valerolactone (gVL), as biomarker of flavan-3-ol intake in large epidemiological studies. Flavan-3-ols are widely consumed plant bioactives, which have received considerable interest due to their potential ability to reduce CVD risk. The availability of authentic standards allowed the development of a validated high-throughput method suitable for large-scale studies. In dietary intervention studies, we could show that gVL metabolites are specific for flavan-3-ols present in tea, fruits, wine and cocoa-derived products, with a strong correlation between intake and biomarker (Spearman's r = 0.90). This biomarker will allow for the first time to estimate flavan-3-ol intake and further investigation of associations between intake and disease risk.

Conflict of interest statement

H.S. and J.I.O. are employed by Mars, Inc., a company engaged in flavanol research and flavanol-related commercial activities. G.G.C.K. has received an unrestricted research grant from Mars Inc.

Figures

Figure 1
Figure 1
Typical chromatogram of EPIC Norfolk spot urine sample, showing γ-valerolactone-3′/4′-O-glucuronide (top, 3.9 minutes) and γ-valerolactone-3′-sulphate (bottom, 3.8 minutes) in urine.
Figure 2
Figure 2
Distribution of gVLM (sum of γ-valerolactone-3′/4′-sulfate and γ-valerolactone-3′/4′-O-glucuronide) concentrations in 5000 random samples of EPIC Norfolk. The red bar indicates samples with concentration below the lower limit of quantification (0.1 µmol/L).
Figure 3
Figure 3
Urinary excretion of flavan-3-ol biomarker (gVLM, sum of γ-valerolactone-3′/4′-sulphate and O–glucuronide) following the consumption of different flavan-3-ols (error bars show standard error; n = 12–8). *indicate statistically significant differences (p 

Figure 4

Flavan-3-ol precursors of the microbial…

Figure 4

Flavan-3-ol precursors of the microbial metabolite 5-(3′/4′-dihydroxyphenyl)-γ-valerolactone (gVL). Only compounds with intact (epi)catechin…

Figure 4
Flavan-3-ol precursors of the microbial metabolite 5-(3′/4′-dihydroxyphenyl)-γ-valerolactone (gVL). Only compounds with intact (epi)catechin moiety result in the formation of γVL by the intestinal microbiome. ECG, (−)-epicatechin-3-O-gallate; EGCG, (−)-epigallocatechin-3-O-gallate; EGC, (−)-epigallocatechin.

Figure 5

Association between flavan-3-ol intake and…

Figure 5

Association between flavan-3-ol intake and gVLM (sum of 5-(3′/4′-dihydroxyphenyl)-γ-valerolactone-3′/4′-sulphate and O–glucuronide metabolites). Results…

Figure 5
Association between flavan-3-ol intake and gVLM (sum of 5-(3′/4′-dihydroxyphenyl)-γ-valerolactone-3′/4′-sulphate and O–glucuronide metabolites). Results from the intake-amount escalation study and regression analysis (R2 = 0.66; 95% CI 0.49; 0.80). The intake amount used is comparable with the estimated habitual intake in EPIC Norfolk. For comparison, Pearson and Spearman correlation coefficients for other biomarkers are shown (†; ‡).
Figure 4
Figure 4
Flavan-3-ol precursors of the microbial metabolite 5-(3′/4′-dihydroxyphenyl)-γ-valerolactone (gVL). Only compounds with intact (epi)catechin moiety result in the formation of γVL by the intestinal microbiome. ECG, (−)-epicatechin-3-O-gallate; EGCG, (−)-epigallocatechin-3-O-gallate; EGC, (−)-epigallocatechin.
Figure 5
Figure 5
Association between flavan-3-ol intake and gVLM (sum of 5-(3′/4′-dihydroxyphenyl)-γ-valerolactone-3′/4′-sulphate and O–glucuronide metabolites). Results from the intake-amount escalation study and regression analysis (R2 = 0.66; 95% CI 0.49; 0.80). The intake amount used is comparable with the estimated habitual intake in EPIC Norfolk. For comparison, Pearson and Spearman correlation coefficients for other biomarkers are shown (†; ‡).

References

    1. Schroeter H, et al. Recommending flavanols and procyanidins for cardiovascular health: Current knowledge and future needs. Molecular Aspects of Medicine. 2010;31:546–557. doi: 10.1016/j.mam.2010.09.008.
    1. Ottaviani, J. I., Heiss, C., Spencer, J. P. E., Kelm, M. & Schroeter, H. Recommending flavanols and procyanidins for cardiovascular health: Revisited. Mol. Aspects Med. 10.1016/j.mam.2018.02.001 (2018).
    1. Weintraub WS, Lüscher TF, Pocock S. The perils of surrogate endpoints. Eur Heart J. 2015;36:2212–2218. doi: 10.1093/eurheartj/ehv164.
    1. Bikdeli B, et al. Two Decades of Cardiovascular Trials With Primary Surrogate Endpoints: 1990-2011. J Am Heart Assoc. 2017;6:e005285. doi: 10.1161/JAHA.116.005285.
    1. Yetley EA, et al. Options for basing Dietary Reference Intakes (DRIs) on chronic disease endpoints: report from a joint US-/Canadian-sponsored working group. Am J Clin Nutr. 2017;105:249S–285S. doi: 10.3945/ajcn.116.139097.
    1. Vogiatzoglou A, et al. Associations between flavan-3-ol intake and CVD risk in the Norfolk cohort of the European Prospective Investigation into Cancer (EPIC-Norfolk) Free Radic Biol Med. 2015;84:1–10. doi: 10.1016/j.freeradbiomed.2015.03.005.
    1. Prentice RL, et al. Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers. Am J Epidemiol. 2011;174:591–603. doi: 10.1093/aje/kwr140.
    1. Subar AF, et al. Addressing Current Criticism Regarding the Value of Self-Report Dietary Data. J Nutr. 2015;145:2639–2645. doi: 10.3945/jn.115.219634.
    1. Potischman N, Freudenheim JL. Biomarkers of nutritional exposure and nutritional status: an overview. J Nutr. 2003;133(Suppl 3):873S–874S. doi: 10.1093/jn/133.3.873S.
    1. Kaaks, R., Riboli, E. & Sinha, R. Biochemical markers of dietary intake. IARC Sci Publ 103–126 (1997).
    1. Jenab M, Slimani N, Bictash M, Ferrari P, Bingham SA. Biomarkers in nutritional epidemiology: applications, needs and new horizons. Hum. Genet. 2009;125:507–525. doi: 10.1007/s00439-009-0662-5.
    1. Kuhnle GGC. Nutritional biomarkers for objective dietary assessment. J. Sci. Food Agric. 2012;92:1145–1149. doi: 10.1002/jsfa.5631.
    1. Keogh RH, White IR, Bingham SA. Using surrogate biomarkers to improve measurement error models in nutritional epidemiology. Stat Med. 2013;32:3838–3861. doi: 10.1002/sim.5803.
    1. Bingham SA, Cummings JH. Urine nitrogen as an independent validatory measure of dietary intake: a study of nitrogen balance in individuals consuming their normal diet. Am J Clin Nutr. 1985;42:1276–1289. doi: 10.1093/ajcn/42.6.1276.
    1. Ward H, et al. Breast cancer risk in relation to urinary and serum biomarkers of phytoestrogen exposure in the European Prospective into Cancer-Norfolk cohort study. Breast Cancer Res. 2008;10:R32. doi: 10.1186/bcr1995.
    1. Ward H, Chapelais G, Kuhnle GG, Luben R. Lack of prospective associations between plasma and urinary phytoestrogens and risk of prostate or colorectal cancer in the European Prospective into Cancer-Norfolk study. Cancer Epidemiology. 2008;17:2891–2894.
    1. Ottaviani JI, et al. The metabolome of [2-14C](−)-epicatechin in humans: implications for the assessment of efficacy, safety, and mechanisms of action of polyphenolic bioactives. Sci Rep. 2016;6:1–10. doi: 10.1038/s41598-016-0001-8.
    1. Das NP. Studies on flavonoid metabolism. Absorption and metabolism of (+)-catechin in man. Biochem Pharmacol. 1971;20:3435–3445. doi: 10.1016/0006-2952(71)90449-7.
    1. Unno T, Tamemoto K, Yayabe F, Kakuda T. Urinary excretion of 5-(3′,4′-dihydroxyphenyl)-gamma-valerolactone, a ring-fission metabolite of (−)-epicatechin, in rats and its in vitro antioxidant activity. J Agric Food Chem. 2003;51:6893–6898. doi: 10.1021/jf034578e.
    1. Borges, G., Ottaviani, J. I., van der Hooft, J. J. J., Schroeter, H. & Crozier, A. Absorption, metabolism, distribution and excretion of (−)-epicatechin: A review of recent findings. Mol. Aspects Med. 10.1016/j.mam.2017.11.002 (2017).
    1. Institute of Medicine (US) Committee on Qualification of Biomarkers and Surrogate Endpoints in Chronic Disease, Micheel, C. M. & Ball, J. R. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. (National Academies Press (US), 2010).
    1. Zhang M, Erik Jagdmann G, Jr, Van Zandt M, Beckett P, Schroeter H. Enantioselective synthesis of orthogonally protected (2R,3R)-(−)-epicatechin derivatives, key intermediates in the de novo chemical synthesis of (−)-epicatechin glucuronides and sulfates. Tetrahedron: Asymmetry. 2013;24:362–373. doi: 10.1016/j.tetasy.2013.02.012.
    1. Zhang M, et al. Chemical Synthesis and Characterization of Epicatechin Glucuronides and Sulfates: Bioanalytical Standards for Epicatechin Metabolite Identification. J Nat Prod. 2013;76:157–169. doi: 10.1021/np300568m.
    1. Vogiatzoglou A, et al. Assessment of the dietary intake of total flavan-3-ols, monomeric flavan-3-ols, proanthocyanidins and theaflavins in the European Union. Br J Nutr. 2014;111:1463–1473. doi: 10.1017/S0007114513003930.
    1. Day N, et al. EPIC-Norfolk: study design and characteristics of the cohort. European Prospective Investigation of Cancer. Br J Cancer. 1999;80(Suppl 1):95–103.
    1. R Core Team. R: A Language and Environment for Statistical Computing. (2017).
    1. Canty, A. & Ripley, B. boot: Bootstrap R (S-Plus) Functions. (2017).
    1. Ottaviani JI, et al. The stereochemical configuration of flavanols influences the level and metabolism of flavanols in humans and their biological activity in vivo. Free Radic Biol Med. 2011;50:237–244. doi: 10.1016/j.freeradbiomed.2010.11.005.
    1. Saha S, et al. Human O-sulfated metabolites of (−)-epicatechin and methyl-(−)-epicatechin are poor substrates for commercial aryl-sulfatases: Implications for studies concerned with quantifying epicatechin bioavailability. Pharmacological Research. 2012;65:592–602. doi: 10.1016/j.phrs.2012.02.005.
    1. Ottaviani JI, Momma TY, Kuhnle GG, Keen CL, Schroeter H. Structurally related (−)-epicatechin metabolites in humans: assessment using de novo chemically synthesized authentic standards. Free Radic Biol Med. 2012;52:1403–1412. doi: 10.1016/j.freeradbiomed.2011.12.010.
    1. Taylor JI, Grace PB, Bingham SA. Optimization of conditions for the enzymatic hydrolysis of phytoestrogen conjugates in urine and plasma. Anal Biochem. 2005;341:220–229. doi: 10.1016/j.ab.2005.03.053.
    1. Xiao JF, Zhou B, Ressom HW. Metabolite identification and quantitation in LC-MS/MS-based metabolomics. Trends Analyt Chem. 2012;32:1–14. doi: 10.1016/j.trac.2011.08.009.
    1. Stokvis E, Rosing H, Beijnen JH. Stable isotopically labeled internal standards in quantitative bioanalysis using liquid chromatography/mass spectrometry: necessity or not? Rapid Commun. Mass Spectrom. 2005;19:401–407. doi: 10.1002/rcm.1790.
    1. Wang S, Cyronak M, Yang E. Does a stable isotopically labeled internal standard always correct analyte response? J Pharm Biomed Anal. 2007;43:701–707. doi: 10.1016/j.jpba.2006.08.010.
    1. Valleix A, Carrat S, Caussignac C, Léonce E, Tchapla A. Secondary isotope effects in liquid chromatography behaviour of 2H and 3H labelled solutes and solvents. Journal of Chromatography A. 2006;1116:109–126. doi: 10.1016/j.chroma.2006.03.078.
    1. Administration, F. Guidance for Industry - Bioanalytical Method Validation. Tobacco Smoke Exposure Biomarkers 247–264, 10.1201/b18276-17 (2001).
    1. Sun Q, et al. Urinary Excretion of Select Dietary Polyphenol Metabolites Is Associated with a Lower Risk of Type 2 Diabetes in Proximate but Not Remote Follow-Up in a Prospective Investigation in 2 Cohorts of US Women. Journal of Nutrition. 2015;145:1280–1288. doi: 10.3945/jn.114.208736.
    1. Achaintre D, et al. Differential Isotope Labeling of 38 Dietary Polyphenols and Their Quantification in Urine by Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry. Anal Chem. 2016;88:2637–2644. doi: 10.1021/acs.analchem.5b03609.
    1. Spencer JPE. Metabolism of tea flavonoids in the gastrointestinal tract. J Nutr. 2003;133:3255S–3261S. doi: 10.1093/jn/133.10.3255S.
    1. Rechner AR, et al. The metabolic fate of dietary polyphenols in humans. Free Radic Biol Med. 2002;33:220–235. doi: 10.1016/S0891-5849(02)00877-8.
    1. Kuhnle, G. G. Nutrition epidemiology of flavan-3-ols: the known unknowns. Molecular Aspects of Medicine (2017).
    1. Kuhnle GG, Dell’Aquila C, Runswick SA, Bingham SA. Variability of phytoestrogen content in foods from different sources. Food Chemistry. 2009;113:1184–1187. doi: 10.1016/j.foodchem.2008.08.004.
    1. Hedrick VE, et al. Dietary biomarkers: advances, limitations and future directions. Nutr J. 2012;11:1–1. doi: 10.1186/1475-2891-11-109.
    1. Lampe JW, et al. Dietary biomarker evaluation in a controlled feeding study in women from the Women’s Health Initiative cohort. Am J Clin Nutr. 2017;105:466–475. doi: 10.3945/ajcn.116.144840.
    1. Lampe JW, Chang J-L. Interindividual differences in phytochemical metabolism and disposition. Semin. Cancer Biol. 2007;17:347–353. doi: 10.1016/j.semcancer.2007.05.003.
    1. Setchell K, Cole S. Method of defining equol-producer status and its frequency among vegetarians. J Nutr. 2006;136:2188–2193. doi: 10.1093/jn/136.8.2188.
    1. Rodriguez-Mateos A, et al. Influence of age on the absorption, metabolism, and excretion of cocoa flavanols in healthy subjects. Molecular Nutrition and Food Research. 2015;59:1504–1512. doi: 10.1002/mnfr.201500091.
    1. Rowland IR, Wiseman H, Sanders TA, Adlercreutz H, Bowey EA. Interindividual variation in metabolism of soy isoflavones and lignans: influence of habitual diet on equol production by the gut microflora. Nutr Cancer. 2000;36:27–32. doi: 10.1207/S15327914NC3601_5.
    1. Lampe JW. Isoflavonoid and lignan phytoestrogens as dietary biomarkers. J Nutr. 2003;133(Suppl 3):956S–964S. doi: 10.1093/jn/133.3.956S.
    1. Vought RL, London WT, Lutwak L, Dublin TD. Reliability of Estimates of Serum Inorganic Iodine and Daily Fecal and Urinary Iodine Excretion from Single Casual Specimens. Journal of Clinical Endocrinology and Metabolism. 1963;23:1218–1228. doi: 10.1210/jcem-23-12-1218.
    1. Kuijsten A, Arts ICW, Vree TB, Hollman PCH. Pharmacokinetics of Enterolignans in Healthy Men and Women Consuming a Single Dose of Secoisolariciresinol Diglucoside. Journal of Nutrition. 2005;135:795–801. doi: 10.1093/jn/135.4.795.
    1. Mennen LI, et al. Urinary excretion of 13 dietary flavonoids and phenolic acids in free-living healthy subjects - variability and possible use as biomarkers of polyphenol intake. Eur J Clin Nutr. 2007;62:519–525. doi: 10.1038/sj.ejcn.1602744.
    1. Rothwell JA, et al. Phenol-Explorer 3.0: a major update of the Phenol-Explorer database to incorporate data on the effects of food processing on polyphenol content. Database. 2013;2013:bat070–bat070. doi: 10.1093/database/bat070.
    1. Vogiatzoglou A, et al. Flavonoid intake in European adults (18 to 64 years) PLoS One. 2015;10:e0128132–22. doi: 10.1371/journal.pone.0128132.
    1. Bingham SA, et al. Validation of dietary assessment methods in the UK arm of EPIC using weighed records, and 24-hour urinary nitrogen and potassium and serum vitamin C and carotenoids as biomarkers. Int J Epidemiol. 1997;26(Suppl 1):S137–51. doi: 10.1093/ije/26.suppl_1.S137.

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