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Gut Microbiome and Effect on Metabolome, 3 rd NUGO workshop “Nutritional Metabolomics”

Metabolomics to characterize gastrointestinal disorders / diseases Daryl Rowan Plant & Food Research. Gut Microbiome and Effect on Metabolome, 3 rd NUGO workshop “Nutritional Metabolomics” July 1-2, 2010. Gastrointestinal disorders / diseases

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Gut Microbiome and Effect on Metabolome, 3 rd NUGO workshop “Nutritional Metabolomics”

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  1. Metabolomics to characterize gastrointestinal disorders / diseasesDaryl RowanPlant & Food Research Gut Microbiome and Effect on Metabolome, 3rd NUGO workshop “Nutritional Metabolomics” July 1-2, 2010

  2. Gastrointestinal disorders / diseases • Irritable bowel syndrome – non-specific diagnosis by exclusion (IBS-D, IBS-C, IBS-A or IBS-PI) • Inflammatory bowel diseases (Ulcerative Colitis, Crohn’s disease) – defined disease with strong genetic and environmental effects • Colorectal cancer Metabolomics to characterize gastrointestinal disorders / diseases

  3. Experimental Design Humans or animal models – genetic diversity / gene knockouts / environmental control Practical Constraints Human availability - ethics Sample type and availability Biopsy or remote sampling (urine) Repeat sampling Metabolomics to characterize gastrointestinal disorders / diseases

  4. What we can learn from ‘disease vs. healthy’ human metabolite comparisons • Some 6 studies - mainly NMR using mucosal biopsy, urine and faeces • Descriptors used: • diagnosis and discrimination of CD and UC, active and inactive disease states • diagnostic metabolites • identify differences gut microbiota • Starting point for longitudinal and retro-analysis for early indicators of ‘disease’ • Consistency individual urinary metabolites (Williams, 2009, Amer.J.Grastro) Metabolomics to characterize gastrointestinal disorders / diseases

  5. Beyond ‘disease vs. health’ metabolite comparisons Understanding metabolomics of disease development and progression Moderate experimental inflammation in IL10 deficient mouse model - time course analysis of disease development by NMR (Martin,  J. Prot. Res. 2009; Murdoch, Anal. Chem. 2008) and by GCMS (Lin, J. Prot. Res. 2009) Metabolomics to characterize gastrointestinal disorders / diseases

  6. Finding early biomarkers of disease • predictive/prognostic • time course analysis to track responses of individuals • identification of metabolites • experimental validation of prospective biomarkers Koulman, A.B.Chem, 2009 Metabolomics to characterize gastrointestinal disorders / diseases

  7. IL10-/- mice Wild type mice Specific pathogen free (SPF) conditions Dosed, conventional conditions Compare urinary metabolite profiles Reduced (progressive) inflammation IL10-/- Inflammation Wild type No inflammation No inflammation Validation of 37 candidate biomarkers of intestinal inflammation in the IL10-/- mouse (Lin, J. Prot. Res. 2010)

  8. Discrimination between types of biomarkers Markers IL10-deficient genotype (n = 12) Markers of inflammation (n = 15) wild type IL10-/- IL10-/- conventional

  9. Markers of microbial exposure (n = 10) conventional (dosed) mice SPF mice Only 15 of 37 differences (40%) were related to inflammation Metabolomics will find differences but interpret with caution

  10. Nutrigenomics New Zealand

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