Susceptibility of human metabolic phenotypes to dietary modulation |
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Authors: | Stella Cinzia Beckwith-Hall Bridgette Cloarec Olivier Holmes Elaine Lindon John C Powell Jonathan van der Ouderaa Frans Bingham Sheila Cross Amanda J Nicholson Jeremy K |
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Institution: | Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics (SORA), Faculty of Medicine, Imperial College London, and MRC Dunn Human Nutrition Unit, Addenbrookes Hospital, Cambridge, United Kingdom. |
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Abstract: | Dietary composition has been shown to influence metabolism and to impact on the prevalence and risk for certain diseases, but hitherto, there have been no systematic studies on the effects of dietary modulation of human metabolic phenotype (metabotype). Here, we have applied 1H NMR spectroscopy in combination with multivariate statistical analysis to characterize the effects of three diets: "vegetarian", "low meat", and "high meat" on the metabotype signature of human participants. Twelve healthy male participants (age range of 25-74 years) consumed each of these diets, in a randomized order, for continuous 15-day-periods with an intervening washout period between each diet of 7 days duration. Each participant provided three consecutive 24-hour urine collections on days 13, 14, and 15 of each dietary period, and 1H NMR spectra were acquired on all samples. Pattern recognition analysis allowed differentiation of the characteristic metabolic signatures of the diets with creatine, carnitine, acetylcarnitine, and trimethylamine-N-oxide (TMAO) being elevated in the high-meat consumption period. Application of orthogonal projection to latent structure discriminant analysis (O-PLS-DA) allowed the low-meat diet and vegetarian diet signatures to be characterized, and p-hydroxyphenylacetate (a microbial mammalian cometabolite) was higher in the vegetarian than meat diet samples, signaling an alteration of the bacterial composition or metabolism in response to diet. This work shows the potential for the routine use of metabonomics in nutritional and epidemiological studies, in characterizing and predicting the metabolic effects and the influence of diet on human metabotypes. |
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