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Characterisation of...
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Bermingham, Kate M.King's College London
(author)
Characterisation of Fasting and Postprandial NMR Metabolites : Insights from the ZOE PREDICT 1 Study
- Article/chapterEnglish2023
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LIBRIS-ID:oai:lup.lub.lu.se:756b3155-c9a3-4608-9909-87fce930e342
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https://lup.lub.lu.se/record/756b3155-c9a3-4608-9909-87fce930e342URI
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https://doi.org/10.3390/nu15112638DOI
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Language:English
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Summary in:English
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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.
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Mazidi, MohsenKing's College London,University of Oxford
(author)
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Franks, Paul W.Lund University,Lunds universitet,Genetisk och molekylär epidemiologi,Forskargrupper vid Lunds universitet,Genetic and Molecular Epidemiology,Lund University Research Groups,Harvard University(Swepub:lu)med-plf
(author)
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Maher, TylerKing's College London
(author)
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Valdes, Ana M.University of Nottingham
(author)
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Linenberg, InbarKing's College London
(author)
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Wolf, Jonathan
(author)
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Hadjigeorgiou, George
(author)
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Spector, Tim D.King's College London
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Menni, CristinaKing's College London
(author)
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Ordovas, Jose M.CIBER de Fisiopatología Obesidad y Nutricion (CIBEROBN),Madrid Institute For Advanced Studies (IMDEA) Food Institute,Jean Mayer USDA Human Nutrition Research Center on Aging
(author)
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Berry, Sarah E.King's College London
(author)
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Hall, Wendy L.King's College London
(author)
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King's College LondonUniversity of Oxford
(creator_code:org_t)
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In:Nutrients15:112072-6643
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Mazidi, Mohsen
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Franks, Paul W.
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Maher, Tyler
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Valdes, Ana M.
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Linenberg, Inbar
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Wolf, Jonathan
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Hadjigeorgiou, G ...
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Spector, Tim D.
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Menni, Cristina
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Ordovas, Jose M.
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Berry, Sarah E.
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Hall, Wendy L.
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