PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

 

e-ISSN 2231-8526
ISSN 0128-7680

Home / Regular Issue / JST Vol. 31 (2) Mar. 2023 / JST-3600-2022

 

The Predictive Ability of Total Genotype Score and Serum Metabolite Markers in Power-Based Sports Performance Following Different Strength Training Intensities — A Pilot Study

Elin Elisa Khairul, Wan Atiyyah Ab Wahab, Lay Kek Teh, Mohd Zaki Salleh, Mohd Salleh Rofiee, Raja Mohammed Firhad Raja Azidin and Sarina Md. Yusof

Pertanika Journal of Science & Technology, Volume 31, Issue 2, March 2023

DOI: https://doi.org/10.47836/pjst.31.2.23

Keywords: Genetics, metabolomics, single nucleotide polymorphism, strength training, training response

Published on: 20 March 2023

Muscular power is one of the factors that contribute to an athlete’s performance. This study aimed to explore the predictive ability of total genotype score (TGS) and serum metabolite markers in power-based sports performance following different strength training (ST) intensities. We recruited 15 novice male field hockey players (age = 16.27 ± .12 years old, body mass index = 22.57 ± 2.21 kg/m2) and allocated them to; high-intensity strength training (HIST, n=5), moderate intensity strength (MIST, n=5), and control group (C, n=5). Both training groups completed an eight-week ST intervention. Pre- and post-training muscular power (vertical jump) was measured. The participants were genotyped for; ACE (rs1799752), ACTN3 (rs1815739), ADRB3 (rs4994), AGT (rs699), BDKRB2 (rs1799722), PPARA (rs4253778), PPARGC1A (rs8192678), TRHR (rs7832552), and VEGF (rs1870377). TGS was calculated to annotate for strength-power (STP) and endurance (END) qualities. Subsequently, serum metabolomics analysis was conducted using Liquid chromatography-mass spectrometry Quadrupole-Time-of-Flight (LC-MS QTOF) to profile differentially expressed metabolite changes induced by training. Multiple regression analysis was conducted to explore the ability of TGS and differentially expressed metabolite markers to predict muscular power changes following the intervention. Multiple Regression revealed that only TGS STP might be a significant predictor of muscular power changes following MIST (adjusted R2=.906, p<.05). Additionally, ST also resulted in significant muscular power improvement (p<.05) and perturbation of the sphingolipid metabolism pathway (p<.05). Therefore, selected gene variants may influence muscular power. Therefore, STP TGS might be able to predict muscular power changes following MIST.

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