THE ROLE OF FOOD METABOLOME IN BIOMARKER DISCOVERY: EVIDENCE FROM CLINICAL AND OBSERVATIONAL STUDIES
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1 THE ROLE OF FOOD METABOLOME IN BIOMARKER DISCOVERY: EVIDENCE FROM CLINICAL AND OBSERVATIONAL STUDIES M Garcia-Aloy*, R Llorach, M Urpi-Sarda, R Vázquez-Fresno, O Jáuregui, C Andres-Lacueva Biomarkers & Nutrimetabolomic Lab. (University of Barcelona) margarcia@ub.edu
2 NUTRIMETABOLOMICS
3
4 The main aim of this work was to contribute to the identification of biomarkers related to food ingestion (biomarkers of intake), as well as their potential association with health (biomarkers of effect) through the application of an untargeted HPLC-q-ToF-MS metabolomic approach in nutritional studies with different designs.
5 HPLC-q-ToF-MS UNTARGETED METABOLOMIC ANALYSIS
6 HPLC-q-ToF-MS UNTARGETED METABOLOMIC ANALYSIS
7 Garcia-Aloy M et al., [en proceso de publicación]
8
9 AGL C02-01 RANDOMIZATION PREDIMED COHORT (n=7447) INTERVENTION PERIOD (12 weeks) W0 W12 n = 20 CONTROL GROUP Subsample 1 (n=275) [cross-sectional analysis] Subsample 2 (n=327) [cross-sectional analysis] WALNUT consumption stratification n = 22 NUTS GROUP Excluded (n=80) Excluded (n=141) Nonconsumers (n=128) Habitual consumers (n=67) Nonconsumers (n=104) Habitual consumers (n=82)
10 Consumers Non-consumers
11 RT (min) DETECTED MASS (m/z) ASSIGNATION IDENTIFICATION [M H] - 10-Hydroxy-decene-4, [M H sulfate] - diynoic acid sulfate [M H] - Tridecadienoic/tridecynoic C[M H] - acid glucuronide [M + H] [M + H GlcA] [M + H GlcA H 2 O] [M H] - Dodecanedioic acid C[M H] [M H H 2 O] [M H H 2 O CO 2 ] [M H] - Pyrogallol sulfate [HSO 3 H] [M H] - p-coumaryl alcohol C[M H] - glucuronide [M H] - Urolithin A glucuronide C[M H] [M H GlcA] [M + H] [M + H GlcA] [M H] - Urolithin A sulfoglucuronide [M H] - p-coumaryl alcohol sulfate C[M H] [M H sulfate] C[M H sulfate] [M H] - Urolithin A sulfate [M H] - N-Acetylserotonin sulfate [M H] - Hydroxyindoleacetic acid [M H CO 2 ] [M + H] [M + H H 2 O] [M + H CH 2 O 2 ] + RT (min) DETECTED MASS (m/z) ASSIGNATION IDENTIFICATION [M H] - 10-Hydroxy-decene-4,6-diynoic acid sulfate [M H] - Tridecadienoic/tridecynoic acid C[M H] - glucuronide [M + H] C[M + H] [M + H GlcA] [M H] - Urolithin C glucuronide [M H] - Urolithin A glucuronide C[M H] [M H GlcA] C[M H GlcA] [M + H] [M + NH 4 ] [M + H GlcA] [M H] - Urolithin A sulfoglucuronide [M H] - Urolithin B glucuronide [M H GlcA] C[M H GlcA] [M + H] [M + H GlcA] [M H] - Enterolactone glucuronide C[M H] [M H GlcA] [M + NH 4 ] [M H sulfate] - Urolithin C sulfate [M H] - Urolithin A sulfate [M H sulfate] [M H] - 3-Indolecarboxylic acid [M + H] + glucuronide [M H] - Hydroxyindoleacetic acid sulfate [M H] - N-Acetylserotonin sulfate
12 Introduction Objective
13 Introduction Objective Theobromine metabolism Polyphenol metabolism Cocoa taste and flavour Endogenous markers
14 Introduction Objective Acute Intervention Long-term intervention AMMU AMMU isomer 3-Methyluric acid 7-Metilxanthine 3-Metilxanthine 3,7-Dimethyluric acid Theobromine Free-living population Methoxyhydroxyphenylvalerolactone 5-(3,4 -Dihydroxiphenyl)-valerolactone glucuronide 5-(3,4 - Dihydroxiphenyl)-valerolactone sulfate
15 AMMU AMMU isomer 3-Methyluric acid 7-Metilxanthine 3-Metilxanthine 3,7-Dimethyluric acid Theobromine Methoxyhydroxyphenylvalerolactone 5-(3,4 -Dihydroxiphenyl)-valerolactone GlcA 5-(3,4 - Dihydroxiphenyl)-valerolactone sulfate 88.18% (79.47%-96.90%) 76.66% (65.05%-88.27%) 82.23% (71.23%-93.22%) 88.28% (80.09%-96.48%) 85.16% (75.59%-94.72%) 83.59% (73.28%-93.91%) 69.82% (56.45%-83.20%) 73.44% (60.63%-86.24%) 68.26% (55.02%-81.51%) 71.09% (58.27%-83.92%) 90%-100% = excellent; ; 70%-80% = fair; 60%-70% = poor; y 50%-60% = fail
16 AMMU AMMU isomer 3-Methyluric acid 7-Metilxanthine 5,563 1,899 0,003 3-Metilxanthine 3,7-Dimethyluric acid Theobromine Methoxyhydroxyphenylvalerolactone 5-(3,4 -Dihydroxiphenyl)-valerolactone GlcA 4,081 1,559 0,009 5-(3,4 - Dihydroxiphenyl)-valerolactone sulfate
17 ; 80%-90% = good; 70%-80% = fair; 60%-70% = poor; y 50%-60% = fail
18 Diet-related differences in urinary metabolome are associated with food digestion, microbiota metabolism and endogenous metabolism. Discriminating metabolites of metabolic fingerprint were replicated among studies with different design. Multi-metabolite models are a more accurate measurement of food intake as nutritional biomarkers than individual compounds. Non-targeted metabolomics approach allows to access unexplored pathways that are affected by diet.
19 ACKNOWLEDGMENTS Biomarkers & Nutrimetabolomic Lab. IP Cristina Andrés-Lacueva Postdoctoral Scientists Rafael Llorach Mireia Urpi-Sardà Raúl Zamora-Ros Sara Tulipani Mar Garcia-Aloy Nina Görner PhD students Montse Rabassa Bonet Lyda Ximena Mora Enrique Almanza Aguilera Fco. Javier Madrid Gambín Sheila Estruel Amades Maria Trinidad Soria florido Magalí Palau Rodríguez Collaborators Olga Jauregui Alexandre Perera Lluna Location Dept. of Nutrition & Food Science Pharmacy School University of Barcelona (Spain) Diagonal Campus. Av. Diagonal, 643 Av. Joan XXIII s/n (Barcelona)
20 FUNDING COLLABORATIONS Project AGL C02-01 Program Ingenio-Consolider FUN-C-FOOD (CDS ) Complementary Action AGL E Grants for universities and research centres for the recruitment of new research personnel (FI-DGR 2011).
21 THANK YOU VERY MUCH FOR YOUR ATTENTION! M Garcia-Aloy, R Llorach, M Urpi-Sarda, R Vázquez-Fresno, O Jáuregui, C Andres-Lacueva Biomarkers & Nutrimetabolomic Lab. (University of Barcelona)
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