4.4 Article

Metabolomic analysis of a human oral glucose tolerance test reveals fatty acids as reliable indicators of regulated metabolism

Journal

METABOLOMICS
Volume 6, Issue 1, Pages 56-66

Publisher

SPRINGER
DOI: 10.1007/s11306-009-0177-z

Keywords

Metabolomics; Orthogonal projections to latent structures; Oral glucose tolerance test; Gas chromatography; Mass spectrometry

Funding

  1. Swedish Research Council
  2. Crafoord Foundation
  3. European Foundation for the Study of Diabetes
  4. Lars Hiertas Minne
  5. Fredrik och Ingrid Thurings Foundation
  6. O.E. och Edla Johanssons Vetenskapliga Stiftelse
  7. Knut and Alice Wallenbergs Foundation
  8. Royal Physiographic Society

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Gas chromatography/mass spectrometry-based metabolomics was applied to investigate dynamic changes in the plasma metabolome upon an oral glucose tolerance test (OGTT). The OGTT is a frequently used diagnostic test of glucose homeostasis and diabetes. Diabetes is diagnosed either when glucose levels a parts per thousand yen7.0 mM in the fasting state or a parts per thousand yen11.0 mM at 2 h after oral glucose intake. The accuracy of the OGTT would, however, most likely improve if additional variables could be identified. In the present study, plasma samples were drawn every 15 min for 2 h after an oral glucose load of 75 g preceded by an overnight fast in healthy individuals. Blood plasma levels of more than 200 putative metabolites were measured. Multivariate modelling was used to distinguish metabolic regulation due to the glucose challenge from that of other variability. Two data scaling methods were applied, yielding similar results when evaluated by appropriate diagnostic tools. Fatty acid levels were found to be strongly decreased during the OGTT. Also, the levels of amino acids were shown to decrease. However, technical and uninduced biological variations were found to affect the amino acid levels to a greater extent than the fatty acid levels, making the fatty acids more reliable as indicators of metabolic regulation. Levels of several metabolites correlated with the quadratic glucose profile and two were found having an inverse correlation. Raw data plots of all identified significantly altered metabolites confirmed the excellent performance of the multivariate models. Using this approach, a better understanding of the metabolic response to an OGTT can be achieved, paving the way for inclusion of other variables describing appropriate metabolic control.

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