Characterisation of Fasting and Postprandial NMR Metabolites: Insights from the ZOE PREDICT 1 Study.

Autor:	Bermingham KM; Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK.; Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK., Mazidi M; Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK.; Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX1 3QR, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK., Franks PW; Department of Clinical Sciences, Lund University, 21428 Malmö, Sweden.; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA., Maher T; Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK., Valdes AM; School of Medicine, University of Nottingham, Nottingham NG5 1PB, UK.; Nottingham NIHR Biomedical Research Centre, Nottingham NG7 2UH, UK., Linenberg I; Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK.; ZOE Ltd., London SE1 7RW, UK., Wolf J; ZOE Ltd., London SE1 7RW, UK., Hadjigeorgiou G; ZOE Ltd., London SE1 7RW, UK., Spector TD; Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK., Menni C; Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK., Ordovas JM; Jean Mayer USDA Human Nutrition Research Centre on Aging (JM-USDA-HNRCA), Tufts University, Boston, MA 02111, USA.; IMDEA Food Institute, CEI UAM + CSIC, 28049 Madrid, Spain.; Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain., Berry SE; Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK., Hall WL; Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK.
Jazyk:	angličtina
Zdroj:	Nutrients [Nutrients] 2023 Jun 05; Vol. 15 (11). Date of Electronic Publication: 2023 Jun 05.
DOI:	10.3390/nu15112638
Abstrakt:	Background: Postprandial metabolomic profiles and their inter-individual variability are not well characterised. Here, we describe postprandial metabolite changes, their correlations with fasting values and their inter- and intra-individual variability, following a standardised meal in the ZOE PREDICT 1 cohort. Methods: In the ZOE PREDICT 1 study ( n = 1002 (NCT03479866)), 250 metabolites, mainly lipids, were measured by a Nightingale NMR panel in fasting and postprandial (4 and 6 h after a 3.7 MJ mixed nutrient meal, with a second 2.2 MJ mixed nutrient meal at 4 h) serum samples. For each metabolite, inter- and intra-individual variability over time was evaluated using linear mixed modelling and intraclass correlation coefficients (ICC) were calculated. Results: Postprandially, 85% (of 250 metabolites) significantly changed from fasting at 6 h (47% increased, 53% decreased; Kruskal-Wallis), with 37 measures increasing by >25% and 14 increasing by >50%. The largest changes were observed in very large lipoprotein particles and ketone bodies. Seventy-one percent of circulating metabolites were strongly correlated (Spearman's rho >0.80) between fasting and postprandial timepoints, and 5% were weakly correlated (rho <0.50). The median ICC of the 250 metabolites was 0.91 (range 0.08-0.99). The lowest ICCs (ICC <0.40, 4% of measures) were found for glucose, pyruvate, ketone bodies (β-hydroxybutyrate, acetoacetate, acetate) and lactate. Conclusions: In this large-scale postprandial metabolomic study, circulating metabolites were highly variable between individuals following sequential mixed meals. Findings suggest that a meal challenge may yield postprandial responses divergent from fasting measures, specifically for glycolysis, essential amino acid, ketone body and lipoprotein size metabolites.
Databáze:	MEDLINE
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