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Platelet polyphosphate and energy metabolism in professional male athletes (soccer players): A cross-sectional pilot study.

Takashi UshikiTomoharu MochizukiKatsuya SuzukiMasami KamimuraHajime IshiguroSatoshi WatanabeGo OmoriNoriaki YamamotoTomoyuki Kawase
Published in: Physiological reports (2022)
Human platelet polyphosphate (polyP) is a multifunctional molecule; however, its functions are not yet fully understood. A recent study demonstrated that similar to skeletal muscle, polyP is involved in energy metabolism in platelets, which suggests that well-trained athletes may exhibit elevated platelet polyP levels for energy storage. To test this hypothesis, we quantified platelet polyP along with NADH, a component involved in ATP production in non-trained and well-trained male Japanese participants of the same generation. Washed platelets were prepared from the venous blood of young, healthy, non-athletes, and professional soccer players (pro-athletes). NADH and polyP levels were spectrophotometrically determined using tetrazolium reduction and fluorometrically determined using 4',6-diamidino-2-phenylindole at the excitation/emission wavelengths of 425/525 nm. Body weight and impedances were measured simultaneously. Statistical analyses were performed using the Mann-Whitney U test and Spearman correlation coefficient. Although basal metabolic rate levels were significantly higher, platelet polyP levels were significantly lower in pro-athletes than in that in non-athletes. No significant differences were detected in other body compositions or platelet indices between the two groups. The pro-athlete group showed a moderate, nearly significant correlation (R = 0.439; p = 0.0512) between platelet polyP and NADH levels. Taken together with the weak correlation data between polyP and body mass index, it is suggested that platelet polyP levels may be influenced by platelet and body energy metabolic activity. Further biochemical studies are needed to elucidate this mechanism.
Keyphrases
  • body mass index
  • skeletal muscle
  • body weight
  • endothelial cells
  • type diabetes
  • metabolic syndrome
  • machine learning
  • physical activity
  • magnetic resonance
  • resistance training
  • computed tomography
  • cancer therapy