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Metabolites 2016, 6(1), 9; doi:10.3390/metabo6010009

Metabolomic Profiling of Submaximal Exercise at a Standardised Relative Intensity in Healthy Adults

1
Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, The John Arbuthnott Building, 161 Cathedral Street, Glasgow G4 0RE, UK; ali.muhsen.ali@strath.ac.uk (A.M.A.); evangelia.daskalaki@strath.ac.uk (E.D.); Tong.Zhang@glasgow.ac.uk (T.Z.)
2
College of Science, Thi-Qar University, Nassiriya, Thi-Qar, Iraq
3
Institute for Clinical Exercise and Health Science, University of the West of Scotland, Hamilton ML3 0JB, UK; miacburleigh@outlook.com (M.B.); chris.easton@uws.ac.uk (C.E.)
*
Author to whom correspondence should be addressed.
Academic Editor: Peter Meikle
Received: 22 December 2015 / Revised: 18 February 2016 / Accepted: 22 February 2016 / Published: 26 February 2016
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Abstract

Ten physically active subjects underwent two cycling exercise trials. In the first, aerobic capacity (VO2max) was determined and the second was a 45 min submaximal exercise test. Urine samples were collected separately the day before (day 1) , the day of (day 2), and the day after (day 3) the submaximal exercise test (12 samples per subject). Metabolomic profiling of the samples was carried out using hydrophilic interaction chromatography (HILIC) coupled to an Orbitrap Exactive mass spectrometer. Data were extracted, database searched and then subjected to principle components (PCA) and orthogonal partial least squares (OPLSDA) modelling. The best results were obtained from pre-treating the data by normalising the metabolites to their mean output on days 1 and 2 of the trial. This allowed PCA to separate the day 2 first void samples (D2S1) from the day 2 post-exercise samples (D2S3) PCA also separated the equivalent samples obtained on day 1 (D1S1 and D1S3). OPLSDA modelling separated both the D2S1 and D2S3 samples and D1S1 and D1S3 samples. The metabolites affected by the exercise samples included a range of purine metabolites and several acyl carnitines. Some metabolites were subject to diurnal variation these included bile acids and several amino acids, the variation of these metabolites was similar on day 1 and day 2 despite the exercise intervention on day 2. Using OPLS modelling it proved possible to identify a single abundant urinary metabolite provisionally identified as oxo-aminohexanoic acid (OHA) as being strongly correlated with VO2max when the levels in the D2S3 samples were considered. View Full-Text
Keywords: exercise metabolomics; high resolution mass spectrometry; purines; acylcarnitines; VO2max exercise metabolomics; high resolution mass spectrometry; purines; acylcarnitines; VO2max
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Muhsen Ali, A.; Burleigh, M.; Daskalaki, E.; Zhang, T.; Easton, C.; Watson, D.G. Metabolomic Profiling of Submaximal Exercise at a Standardised Relative Intensity in Healthy Adults. Metabolites 2016, 6, 9.

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