McFadden Bridget A, Walker Alan J, Arent Michelle A, Bozzini Brittany N, Sanders David J, Cintineo Harry P, Bello Marissa L, Arent Shawn M
Department of Exercise Science, The University of South Carolina, Columbia, SC, United States.
IFNH Center for Health and Human Performance, Rutgers University, New Brunswick, NJ, United States.
Front Sports Act Living. 2020 Jul 2;2:74. doi: 10.3389/fspor.2020.00074. eCollection 2020.
The purpose of this study was to evaluate the effects of a competitive soccer season on biomarkers and performance metrics in order to determine the correlation between changes in biomarkers, body composition, and performance outcomes. Twenty-one Division 1 female collegiate soccer players were monitored throughout the 16-week season. Player workload was measured using heart rate and Global Position Satellite systems at all practices and games. Performance testing, including vertical jump, VO, and 3-repetition maximum testing for bench press, squat and deadlift, occurred prior to pre-season and immediately post-season. Blood draws occurred prior to preseason and every 4-weeks thereafter, following a game. Body composition was assessed prior to the start of season (week 0) and weeks 6, 10, 14, and 17 (post-season). Delta area under the curve was calculated for biomarkers and body composition variables to account for seasonal changes adjusted for baseline. Pearson-product moment correlations were used to assess relationships with significance set at < 0.05. Trends were considered ≤ 0.10. No significant time main effects were seen for anabolic biomarkers ( > 0.05). Significant time effects were seen for catabolic biomarkers throughout the season ( = 0.001). No changes in body weight, VO, vertical jump, and deadlift occurred. Squat and bench press improved ( = 0.01 and = 0.02, respectively) with a decline in percent body fat ( = 0.03) and a trend for increased fat free mass ( = 0.09). Additionally, total cortisol (TCORT) negatively correlated with fat free mass ( = -0.48; = 0.03) and positively correlated with VO ( = 0.47; = 0.04). A trend was shown for a positive correlation between both TCORT and free cortisol (FCORT) and percent body fat ( = 0.39; = 0.40; = 0.08, respectively). IGF-1 and growth hormone positively correlated to deadlift ( = 0.57; = 0.02 and = 0.59; = 0.03), whereas creatine kinase showed a trend for a positive correlation with deadlift ( = 0.49; = 0.06). IL-6 negatively correlated with bench press ( = -0.53; = 0.03). These findings support a relationship between biomarkers, performance outcomes, and body composition. Biomarker monitoring may be useful to detect individual player's physiological response to an athletic season and may help provide insights in efforts to optimize performance outcomes.
本研究的目的是评估一个竞技性足球赛季对生物标志物和表现指标的影响，以确定生物标志物变化、身体成分与表现结果之间的相关性。在为期16周的赛季中，对21名一级女子大学足球运动员进行了监测。在所有训练和比赛中，使用心率和全球定位卫星系统测量运动员的工作量。在季前赛之前和赛季结束后立即进行了包括垂直跳跃、VO₂以及卧推、深蹲和硬拉的3次重复最大值测试在内的表现测试。在季前赛之前以及此后每4周比赛结束后进行采血。在赛季开始前（第0周）以及第6、10、14和17周（赛季结束后）评估身体成分。计算生物标志物和身体成分变量的曲线下面积增量，以考虑根据基线调整后的季节性变化。使用Pearson积矩相关性来评估相关性，显著性设定为<0.05。趋势被认为≤0.10。合成代谢生物标志物未见显著的时间主效应（P>0.05）。整个赛季中分解代谢生物标志物出现了显著的时间效应（P = 0.001）。体重、VO₂、垂直跳跃和硬拉没有变化。深蹲和卧推有所改善（分别为P = 0.01和P = 0.02），体脂百分比下降（P = 0.03），无脂肪质量有增加趋势（P = 0.09）。此外，总皮质醇（TCORT）与无脂肪质量呈负相关（r = -0.48；P = 0.03），与VO₂呈正相关（r = 0.47；P = 0.04）。总皮质醇和游离皮质醇（FCORT）与体脂百分比之间均呈正相关趋势（分别为r = 0.39；P = 0.08；r = 0.40；P = 0.08）。胰岛素样生长因子-1（IGF-1）和生长激素与硬拉呈正相关（分别为r = 0.57；P = 0.02和r = 0.59；P = 0.03），而肌酸激酶与硬拉呈正相关趋势（r = 0.49；P = 0.06）。白细胞介素-6（IL-6）与卧推呈负相关（r = -0.53；P = 0.03）。这些发现支持了生物标志物、表现结果和身体成分之间的关系。生物标志物监测可能有助于检测个体运动员对运动赛季的生理反应，并可能有助于为优化表现结果的努力提供见解。
