Abstract

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.

Keywords

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

Published in

Metabolomics
2010, Volume: 6, number: 1, pages: 56-66
Publisher: SPRINGER

SLU Authors

• Moritz, Thomas

  • Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

SDG3 Ensure healthy lives and promote well-being for all at all ages


UKÄ Subject classification

Endocrinology and Diabetes


Publication identifier

DOI: https://doi.org/10.1007/s11306-009-0177-z

Permanent link to this page (URI)

https://res.slu.se/id/publ/48454