NDLI: Personalized Metabolomics for Predicting Glucose Tolerance Changes in Sedentary Women After High-Intensity Interval Training

Content Provider	PubMed Central
Author	Kuehnbaum, Naomi L. Gillen, Jenna B. Gibala, Martin J. Philip, Britz-mckibbin
Copyright Year	2014
Abstract	High-intensity interval training (HIIT) offers a practical approach for enhancing cardiorespiratory fitness, however its role in improving glucose regulation among sedentary yet normoglycemic women remains unclear. Herein, multi-segment injection capillary electrophoresis-mass spectrometry is used as a high-throughput platform in metabolomics to assess dynamic responses of overweight/obese women (BMI > 25, n = 11) to standardized oral glucose tolerance tests (OGTTs) performed before and after a 6-week HIIT intervention. Various statistical methods were used to classify plasma metabolic signatures associated with post-prandial glucose and/or training status when using a repeated measures/cross-over study design. Branched-chain/aromatic amino acids and other intermediates of urea cycle and carnitine metabolism decreased over time in plasma after oral glucose loading. Adaptive exercise-induced changes to plasma thiol redox and orthinine status were measured for trained subjects while at rest in a fasting state. A multi-linear regression model was developed to predict changes in glucose tolerance based on a panel of plasma metabolites measured for naïve subjects in their untrained state. Since treatment outcomes to physical activity are variable between-subjects, prognostic markers offer a novel approach to screen for potential negative responders while designing lifestyle modifications that maximize the salutary benefits of exercise for diabetes prevention on an individual level.
Related Links	http://dx.doi.org/10.1038/srep06166
Starting Page	6166
File Format	PDF
ISSN	20452322
e-ISSN	20452322
Journal	Scientific Reports
Volume Number	4
Language	English
Publisher	Nature Publishing Group
Publisher Date	2014-08-01
Access Restriction	Open
Rights Holder	Nature Publishing Group
Subject Keyword	Science and technology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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Personalized Metabolomics for Predicting Glucose Tolerance Changes in Sedentary Women After High-Intensity Interval Training

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