Specific circulating phospholipids, acylcarnitines, amino acids and biogenic amines are aerobic exercise markers. Issue 7 (July 2017)

• Record Type: Journal Article
• Authors: Felder, Thomas K.; Ring-Dimitriou, Susanne; Auer, Simon; Soyal, Selma M.; Kedenko, Ludmilla; Rinnerthaler, Mark; Cadamuro, Janne; Haschke-Becher, Elisabeth; Aigner, Elmar; Paulweber, Bernhard; Patsch, Wolfgang
• Is Part Of: Journal of science and medicine in sport. Volume 20:Issue 7(2017)
• Page Start: 700
• Page End: 705
• Publication Date: 2017-07
• Subjects: Exercise -- Metabolomics -- Serine metabolism -- Sarcosine -- LysoPC; Sports sciences -- Periodicals; Sports medicine -- Periodicals; Exercise -- Physiological aspects -- Periodicals; Sports -- physiology -- Periodicals; Sports Medicine -- Periodicals; Sportgeneeskunde; 617.102705
• DOI: 10.1016/j.jsams.2016.11.011
• Languages: English
• ISSNs: 1440-2440

Abstract

Abstract: Objectives: Regular aerobic exercise provides beneficial effects on human health and reduces all-cause mortality. Aerobic exercise has profound metabolic effects, and specific metabolites may reflect physiological changes. We aimed to identify endogenous metabolites that distinguish the trained from the untrained state to increase the spectrum of analytes amenable for hypothesis testing and to expand understanding of putative beneficial pathways. Design: Cross sectional laboratory repeated measures study. Methods: Exercise testing was performed in 37 healthy male participants and serum samples were obtained before and after completion of a ten-week standardized exercise program. Samples were analyzed for routine clinical parameters and for 188 endogenous metabolites by LC–MS/MS. Results: Indicating the effectiveness of the intervention program, parameters of sport physiology were different after training. After correcting for multiple testing, serum concentrations of several metabolites differed between the trained and untrained state. Serine and glutamate decreased in response to exercise, whereas sarcosine and kynurenine increased. Phosphatidylcholines showed a mixed response in that four species increased and three decreased. However, all seven lysophosphatidylcholines and all four plasmalogens that differed between the trained and untrained state, increased. One short-chain acylcarnitine also decreased. In receiver operator characteristics analyses, sarcosine displayed the highest AUC value (0.839; 95% CI: 0.734–0.926) in discriminating the pre- from the post-trained state. Conclusions: Our study detected metabolites that clearly differentiate the trained from the untrained state. These metabolites may be targeted in mechanistic studies to understand underlying biochemical pathways and could serve to improve the design, monitoring and individualization of training programs.