Proteomic and Metabolomic Analyses of the Blood Samples of Highly Trained Athletes

Kristina A. Malsagova (), Arthur T. Kopylov, Vasiliy I. Pustovoyt, Evgenii I. Balakin, Ksenia A. Yurku, Alexander A. Stepanov, Liudmila I. Kulikova, Vladimir R. Rudnev and Anna L. Kaysheva
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Kristina A. Malsagova: Institute of Biomedical Chemistry, 119121 Moscow, Russia
Arthur T. Kopylov: Institute of Biomedical Chemistry, 119121 Moscow, Russia
Vasiliy I. Pustovoyt: State Research Center—Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, 119435 Moscow, Russia
Evgenii I. Balakin: State Research Center—Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, 119435 Moscow, Russia
Ksenia A. Yurku: State Research Center—Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, 119435 Moscow, Russia
Alexander A. Stepanov: Institute of Biomedical Chemistry, 119121 Moscow, Russia
Liudmila I. Kulikova: Institute of Biomedical Chemistry, 119121 Moscow, Russia
Vladimir R. Rudnev: Institute of Biomedical Chemistry, 119121 Moscow, Russia
Anna L. Kaysheva: Institute of Biomedical Chemistry, 119121 Moscow, Russia

Data, 2024, vol. 9, issue 1, 1-10

Abstract: High exercise loading causes intricate and ambiguous proteomic and metabolic changes. This study aims to describe the dataset on protein and metabolite contents in plasma samples collected from highly trained athletes across different sports disciplines. The proteomic and metabolomic analyses of the plasma samples of highly trained athletes engaged in sports disciplines of different intensities were carried out using HPLC-MS/MS. The results are reported as two datasets (proteomic data in a derived mgf-file and metabolomic data in processed format), each containing the findings obtained by analyzing 93 mass spectra. Variations in the protein and metabolite contents of the biological samples are observed, depending on the intensity of training load for different sports disciplines. Mass spectrometric proteomic and metabolomic studies can be used for classifying different athlete phenotypes according to the intensity of sports discipline and for the assessment of the efficiency of the recovery period.

Keywords: athletes; metabolite; protein; omics studies; metabolomic studies; dataset (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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