耐力运动中的生物标志物:个性化调节和预测价值

IF 1.2 Q3 SPORT SCIENCES
Sebastian Hacker, Johannes Keck, Thomas Reichel, Klaus Eder, R. Ringseis, Karsten Krüger, Britta Krüger
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引用次数: 0

摘要

运动反应的个体间差异很大,这使得在体育运动中有效使用基于血液的生物标志物变得更加复杂。为解决这一问题,我们将开发一种有用的算法,用于描述不同候选标志物的个体调节和预测价值。49 名参与者完成了两项相同的运动试验。分别在运动前、运动后、运动后 3 小时和运动后 24 小时采集血液样本。测量血浆中白细胞介素 (IL-) 1RA、IL-6、IL-8、IL-10、IL-15、肌酸激酶 (CK)、皮质醇、c 反应蛋白 (CRP)、乳酸脱氢酶 (LDH) 和硫代巴比妥酸活性物质 (TBARS) 的浓度。使用 k-means 聚类和组分配质量(GAQ)评分对个体化调节进行了分析。采用自引导聚合法的回归树评估了标记物的预测性。对于所研究的大多数标记物,可以区分出对特定耐力训练计划反应较强或较弱的个体。IL-6、IL-8、IL-10 和 CK 的调节在个体内部表现出高度的稳定性。关于标记物的预测能力,对于所有因变量,皮质醇和 IL-8 的预测最准确的依据是基线值。对于 CK,可以很好地预测最大力量的恢复情况和主观疲惫感。对于 IL-1RA 和 TBARS,如果知道基线水平,尤其可以预测它们的重新调节。针对生物标志物反应的个体差异,我们的研究结果表明,可以综合利用 IL-6、IL-8、IL-10 和 CK 对耐力运动后的压力和恢复周期进行个性化管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biomarkers in Endurance Exercise: Individualized Regulation and Predictive Value
The high interindividual variability of exercise response complicates the efficient use of blood-based biomarkers in sports. To address this problem, a useful algorithm to characterize the individual regulation and predictive value of different candidate markers will be developed. Forty-nine participants completed two identical exercise trials. Blood samples were collected before, immediately after, 3 hours after, and 24 hours after completion of exercise. Plasma concentrations of interleukin (IL-) 1RA, IL-6, IL-8, IL-10, IL-15, creatine kinase (CK), cortisol, c-reactive protein (CRP), lactate dehydrogenase (LDH), and thiobarbituric acid reactive substances (TBARS) were measured. Individualized regulation was analyzed using k-means clustering and a Group Assignment Quality (GAQ) score. Regression trees with a bootstrapped-aggregated approach were used to assess the predictive qualities of the markers. For most of the markers studied, a distinction can be made between individuals who show a stronger or weaker response to a particular endurance training program. The regulation of IL-6, IL-8, IL-10, and CK exhibited a high degree of stability within the individuals. Regarding the predictive power of the markers, for all dependent variables, the most accurate predictions were obtained for cortisol and IL-8 based on the baseline value. For CK, a good prediction of recovery of maximal strength and subjective feeling of exhaustion can be made. For IL-1RA and TBARS, especially their reregulation can be predicted if the baseline level is known. Focusing individual variations in biomarker responses, our results suggest the combined use of IL-6, IL-8, IL-10, and CK for the personalized management of stress and recovery cycles following endurance exercise.
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CiteScore
3.00
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