da Cruz João Pedro, Dos Santos Fábio Neves, Rasteiro Felipe Marroni, Marostegan Anita Brum, Manchado-Gobatto Fúlvia Barros, Gobatto Claudio Alexandre
Laboratory of Applied Sport Physiology-LAFAE, School of Applied Sciences, University of Campinas, UNICAMP, Limeira, São Paulo 13484-350, Brazil.
Institute of Chemistry, University of Campinas, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Biology (Basel). 2022 Jul 25;11(8):1103. doi: 10.3390/biology11081103.
The purpose of this study was to use traditional physical assessments combined with a metabolomic approach to compare the anthropometric, physical fitness level, and serum fasting metabolic profile among U22 soccer players at different competitive levels. In the experimental design, two teams of male U22 soccer were evaluated (non-elite = 20 athletes, competing in a regional division; elite = 16 athletes, competing in the first division of the national U22 youth league). Earlobe blood samples were collected, and metabolites were extracted after overnight fasting (12 h). Untargeted metabolomics through Liquid Chromatograph Mass Spectrometry (LC-MS) analysis and anthropometric evaluation were performed. Critical velocity was applied to determine aerobic (CV) and anaerobic (ARC) capacity. Height (non-elite = 174.4 ± 7.0 cm; elite = 176.5 ± 7.0 cm), body mass index (non-elite = 22.1 ± 2.4 kg/m2; elite = 21.9 ± 2.3 kg/m2), body mass (non-elite = 67.1 ± 8.8 kg; elite = 68.5 ± 10.1 kg), lean body mass (non-elite = 59.3 ± 7.1 kg; elite = 61.1 ± 7.9 kg), body fat (non-elite = 7.8 ± 2.4 kg; elite = 7.3 ± 2.4 kg), body fat percentage (non-elite = 11.4 ± 2.4%; elite = 10.5 ± 1.7%), hematocrit (non-elite = 50.2 ± 4.0%; elite = 51.0 ± 4.0%), CV (non-elite = 3.1 ± 0.4 m/s; elite = 3.0 ± 0.2 m/s), and ARC (non-elite = 129.6 ± 55.7 m; elite = 161.5 ± 61.0 m) showed no significant differences between the elite and non-elite teams, while the multivariate Partial Least Squares Discriminant Analysis (PLS-DA) model revealed a separation between the elite and non-elite athletes. Nineteen metabolites with importance for projection (VIP) >1.0 were annotated as belonging to the glycerolipid, sterol lipid, fatty acyl, flavonoid, and glycerophospholipid classes. Metabolites with a high relative abundance in the elite group were related in the literature to a better level of aerobic power, greater efficiency in the recovery process, and improvement of mood, immunity, decision making, and accuracy, in addition to acting in mitochondrial preservation and electron transport chain maintenance. In conclusion, although classical physical assessments were not able to distinguish the teams at different competitive levels, the metabolomics approach successfully indicated differences between the fasting metabolic profiles of elite and non-elite teams.
本研究的目的是运用传统身体评估方法并结合代谢组学方法，比较不同竞技水平的U22足球运动员的人体测量学指标、身体素质水平和血清空腹代谢谱。在实验设计中，对两支男子U22足球队进行了评估（非精英组 = 20名运动员，参加地区联赛；精英组 = 16名运动员，参加全国U22青年联赛的甲级联赛）。采集耳垂血样，经过12小时过夜禁食后提取代谢物。通过液相色谱 - 质谱联用（LC-MS）分析进行非靶向代谢组学研究并进行人体测量学评估。应用临界速度来确定有氧能力（CV）和无氧能力（ARC）。身高（非精英组 = 174.4 ± 7.0厘米；精英组 = 176.5 ± 7.0厘米）、体重指数（非精英组 = 22.1 ± 2.4千克/平方米；精英组 = 21.9 ± 2.3千克/平方米）、体重（非精英组 = 67.1 ± 8.8千克；精英组 = 68.5 ± 10.1千克）、瘦体重（非精英组 = 59.3 ± 7.1千克；精英组 = 61.1 ± 7.9千克）、体脂（非精英组 = 7.8 ± 2.4千克；精英组 = 7.3 ± 2.4千克）、体脂百分比（非精英组 = 11.4 ± 2.4%；精英组 = 10.5 ± 1.7%）、血细胞比容（非精英组 = 50.2 ± 4.0%；精英组 = 51.0 ± 4.0%）、CV（非精英组 = 多变量偏最小二乘判别分析（PLS-DA）模型显示精英组和非精英组运动员之间存在分离。19种投影重要性（VIP）>1.0的代谢物被注释为属于甘油脂、甾醇脂、脂肪酰基、黄酮类和甘油磷脂类。精英组中相对丰度较高的代谢物在文献中与更好的有氧能力水平、恢复过程中更高的效率以及情绪、免疫力、决策和准确性的改善有关，此外还作用于线粒体保存和电子传递链维持。总之，尽管经典身体评估无法区分不同竞技水平的球队，但代谢组学方法成功地指出了精英组和非精英组球队空腹代谢谱之间的差异。 3.1 ± 0.4米/秒；精英组 = 3.0 ± 0.2米/秒）和ARC（非精英组 = 129.6 ± 55.7米；精英组 = 161.5 ± 61.0米）在精英组和非精英组球队之间没有显著差异，而
