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Am J Clin Nutr. 2017 Mar;105(3):547-554. doi: 10.3945/ajcn.116.144428. Epub 2017 Jan 11.

Metabolomic profiles as reliable biomarkers of dietary composition.

Author information

1
Center for Basic and Translational Obesity Research.
2
Estonian Genome Center, University of Tartu, Tartu, Estonia.
3
Broad Institute of MIT and Harvard, Cambridge, MA; and.
4
Clinical Research Center, and.
5
Metabolomics Platform, Broad Institute, Cambridge, MA.
6
New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, Boston, MA.
7
New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, Boston, MA; david.ludwig@childrens.harvard.edu.

Abstract

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects.Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol.Design: Twenty-one adults with a high body mass index (in kg/m2; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons.Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors.Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.

KEYWORDS:

cardiometabolic risk factors; dietary compliance; dietary composition; glycemic index; low-carbohydrate diet; low-fat diet; metabolomics; obesity

PMID:
28077380
PMCID:
PMC5320413
DOI:
10.3945/ajcn.116.144428
[Indexed for MEDLINE]
Free PMC Article

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