Literature DB >> 19317510

Predictive metabolomics evaluation of nutrition-modulated metabolic stress responses in human blood serum during the early recovery phase of strenuous physical exercise.

Elin Chorell1, Thomas Moritz, Stefan Branth, Henrik Antti, Michael B Svensson.   

Abstract

We have investigated whether postexercise ingestion of carbohydrates in combination with proteins generates a different systemic metabolic response, as compared to the sole ingestion of carbohydrate or water, in the early recovery phase following exercise. In addition, metabolic patterns related to fitness level were studied together with individual responses to nutritional modulation. Twenty-four male subjects were exposed to 90 min of ergometer-cycling. Each participant was subject to four identical test-sessions, including ingestion of one of four beverages (water, low-carbohydrate beverage, high-carbohydrate beverage, and low-carbohydrate-protein beverage (LCHO-P)) immediately after cycling. Blood was collected at six time points, one pre- and five postexercise. Extracted blood serum was subject to metabolomic characterization by gas chromatography/time-of-flight mass spectrometry (GC-TOF MS). Data was processed using hierarchical multivariate curve resolution (HMCR), and multivariate statistical analysis was carried out using orthogonal partial least-squares (OPLS). Predictive metabolomics, including predictive HMCR and OPLS classification, was applied to ensure efficient sample processing and validation of detected metabolic patterns. Separation of subjects in relation to ingested beverage was detected and interpreted. Pseudouridine was suggested as a novel marker for pro-anabolic effect following LCHO-P ingestion, which was supported by the detected decrease of the catabolic marker 3-methylhistidine. Separation of subjects according to fitness level was achieved, and nutritional modulation by LCHO-P was shown to improve the metabolic status of less fit subjects in the recovery phase. In addition, the potential of the methodology for detection of early signs of insulin resistance was also demonstrated.

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Year:  2009        PMID: 19317510     DOI: 10.1021/pr900081q

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  37 in total

1.  Web-enabled and improved software tools and data are needed to measure nutrient intakes and physical activity for personalized health research.

Authors:  Phyllis J Stumbo; Rick Weiss; John W Newman; Jean A Pennington; Katherine L Tucker; Paddy L Wiesenfeld; Anne-Kathrin Illner; David M Klurfeld; Jim Kaput
Journal:  J Nutr       Date:  2010-10-27       Impact factor: 4.798

2.  Metabolic signatures of exercise in human plasma.

Authors:  Gregory D Lewis; Laurie Farrell; Malissa J Wood; Maryann Martinovic; Zoltan Arany; Glenn C Rowe; Amanda Souza; Susan Cheng; Elizabeth L McCabe; Elaine Yang; Xu Shi; Rahul Deo; Frederick P Roth; Aarti Asnani; Eugene P Rhee; David M Systrom; Marc J Semigran; Ramachandran S Vasan; Steven A Carr; Thomas J Wang; Marc S Sabatine; Clary B Clish; Robert E Gerszten
Journal:  Sci Transl Med       Date:  2010-05-26       Impact factor: 17.956

3.  Skeletal muscle interstitial fluid metabolomics at rest and associated with an exercise bout: application in rats and humans.

Authors:  Jie Zhang; Sudeepa Bhattacharyya; Robert C Hickner; Alan R Light; Christopher J Lambert; Bruce K Gale; Oliver Fiehn; Sean H Adams
Journal:  Am J Physiol Endocrinol Metab       Date:  2018-11-06       Impact factor: 4.310

Review 4.  Metabolomics, physical activity, exercise and health: A review of the current evidence.

Authors:  Rachel S Kelly; Michael P Kelly; Paul Kelly
Journal:  Biochim Biophys Acta Mol Basis Dis       Date:  2020-08-19       Impact factor: 5.187

5.  Gas chromatography-mass spectrometry for metabolite profiling of Japanese medaka (Oryzias latipes) juveniles exposed to malathion.

Authors:  Seiichi Uno; Aoi Shintoyo; Emiko Kokushi; Masataka Yamamoto; Kei Nakayama; Jiro Koyama
Journal:  Environ Sci Pollut Res Int       Date:  2012-07-21       Impact factor: 4.223

6.  Metabolite profiling of obese individuals before and after a one year weight loss program.

Authors:  N Geidenstam; M Al-Majdoub; M Ekman; P Spégel; M Ridderstråle
Journal:  Int J Obes (Lond)       Date:  2017-05-22       Impact factor: 5.095

7.  Medium chain acylcarnitines dominate the metabolite pattern in humans under moderate intensity exercise and support lipid oxidation.

Authors:  Rainer Lehmann; Xinjie Zhao; Cora Weigert; Perikles Simon; Elvira Fehrenbach; Jens Fritsche; Jürgen Machann; Fritz Schick; Jiangshan Wang; Miriam Hoene; Erwin D Schleicher; Hans-Ulrich Häring; Guowang Xu; Andreas M Niess
Journal:  PLoS One       Date:  2010-07-12       Impact factor: 3.240

8.  Metabolomics investigation of exercise-modulated changes in metabolism in rat liver after exhaustive and endurance exercises.

Authors:  Chi-Chang Huang; Wan-Teng Lin; Feng-Lin Hsu; Pi-Wen Tsai; Chia-Chung Hou
Journal:  Eur J Appl Physiol       Date:  2009-10-29       Impact factor: 3.078

Review 9.  Nutritional lipidomics: molecular metabolism, analytics, and diagnostics.

Authors:  Jennifer T Smilowitz; Angela M Zivkovic; Yu-Jui Yvonne Wan; Steve M Watkins; Malin L Nording; Bruce D Hammock; J Bruce German
Journal:  Mol Nutr Food Res       Date:  2013-07-01       Impact factor: 5.914

Review 10.  Metabolomics for assessment of nutritional status.

Authors:  Angela M Zivkovic; J Bruce German
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2009-09       Impact factor: 4.294

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