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Effects of acute dietary intake on metabolomic profiles

Effects of acute dietary intake on metabolomic profiles. John Mathers Human Nutrition Research Centre Newcastle University UK. The MEDE Study: MEtabolomics to characterise Dietary Exposure . The MEDE Study. Test meal approach: Volunteers consumed carefully designed meals

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Effects of acute dietary intake on metabolomic profiles

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  1. Effects of acute dietary intake on metabolomic profiles John Mathers Human Nutrition Research Centre Newcastle University UK

  2. The MEDE Study: MEtabolomics to characterise Dietary Exposure The MEDE Study

  3. Test meal approach: Volunteers consumed carefully designed meals Biofluids: Collected at predetermined times ►Blood fractions ► Urine ► Saliva Controlled experimental conditions: ► Behavioural restrictions on pre-test day ►Same fixed meal consumed on evening before test days ►Fluid intake monitored ►Undertaken in Clinical Research Facility The MEDE Study Experimental approach

  4. The MEDE Study Standardised protocol PRE-TEST DAY TEST DAY Test breakfast Standardised evening meal VAS VAS VAS VAS VAS 20 18 19 0 1 2 3 Blood/Urine/Saliva ‘FASTING’ samples Blood/Urine/Saliva ‘FED’ samples Urine ‘PRE’ sample Empty bladder + discard urine Anthropometry

  5. The MEDE Study Test meal paradigm Standard Breakfast: 200ml orange juice 190ml tea + 12g sugar + 14g skimmed milk 35g butter croissant 25g cornflakes + 125g semi-skimmed milk Replaced by test foods in experimental meals

  6. Biomarkers of intake of foods of high public health importance • Cruciferous vegetable: broccoli • Fruit: raspberry • Oily fish: smoked salmon • Wholegrain food: weetabix Each replaced cornflakes + milk in standard breakfast

  7. The MEDE Study Study design • 24 volunteers • Four 6*6 Latin Squares • Standard Breakfast (SB) twice

  8. The MEDE Study GC-tof-MS metabolite profiling in urine: 3h after test breakfast

  9. The MEDE Study Test food Towards potential single biomarkers 1. Salmon

  10. The MEDE Study Test Food Towards potential single biomarkers 2. Broccoli

  11. The MEDE Study Test Food Towards potential single biomarkers 3. Weetabix

  12. -3 x 10 2 1.5 1 DF2(Tw: 21.95) 0.5 0 -0.5 -3 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 x 10 DF1(Tw: 49.52) Strong, consistent inter-individual differences in metabolite profiles - plasma Open Symbols = Visit 1 Closed Symbols = Visit 2

  13. Volunteers consuming Weetabix appear to have different metabotypes (A) PCA on FIE-MS fingerprints in urine (3h after weetabix consumption) (B) (D) (C)

  14. (A) Robust discrimination between Weetabix and cornflakes for those with metabotype ‘A’ only Metabotype (A) only ALL Volunteers

  15. Diet*Genotype interactions determine metabolic phenotype Metabolic Phenotype • How important are inter-individual differences in metabolite responses?

  16. Understanding inter-individual differences in metabolite responses to foods • Assumptions: • Due largely to genotypic variation • Non-nutrients in plant foods are metabolised via xenobiotic-metabolising pathways • May be able to characterise “metabotypes”

  17. Xenobiotic metabolism Borrowed from

  18. Genetic basis of inter-individual variation in xenobiotic metabolism • Underpins “personalisation” of drugs (for both efficacy and safety) • Equally applicable to food-derived molecules • “Genomics meets metabolomics” approach

  19. Isoflavone absorption and metabolism

  20. SoyabeanIsoflavone Metabolism Study • 100 Healthy premenopausal women • Prospectively genotyped for SNP in UGT1A1 (UGT1A1 *28 A(TA)7TAA) • 29 given single oral dose of soyabeanisoflavone B-glucosides • Blood samples at 3h and • 24h urine collection Wakeling LA & Ford D (2010) Proc. Nutr. Soc. [In press]

  21. UGT1A1 genotype influences isoflavonemetabolism ↓ Glucuronidation → ↑ proportion of sulphated metabolite P=0.023 Total isoflavone as sulphate (%) Wakeling LA & Ford D (2010) Proc. Nutr. Soc. [In press] 50.00 10 40.00 30.00 16 20.00 10.00 0.00 AA Aa or aa n = 16 n = 13 UGT1A1*28

  22. The MEDE Study Lessons from the MEDE Study • Standardisation of experimental protocols resulted in highly reproducible metabolomics data • Metabolite profiles in biofluids collected at different times of the day are distinctly different • Urine (and plasma) samples collected 2-4h after meals are highly informative • Have identified potential novel exposure biomarkers for foods of high public health importance as single compounds or as metabolite “barcodes” • Potentially important inter-individual differences in metabotypewhich may be genotype-dependent

  23. The MEDE Study Acknowledgements Newcastle University GaëlleFavé Long Xie Graham Harold Julie Coaker University of Aberystwyth John H. Draper Manfred E. Beckmann Wanchang Lin Shaobo Zhou Kathleen Tailliart Newcastle University LoiusaWakeling Dianne Ford

  24. Frequently consumed foods

  25. Foods consumed occasionally

  26. Infrequently consumed foods – but nutritionally important

  27. Sequestration of metabolites in bone, fat and other tissues Plasma pool

  28. Kinetics of metabolite appearance and disappearance in plasma • Kinetics are metabolite specific • Influenced by host genotype • Does concentration fall to zero? • Impact of repeated exposure?

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