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解释超耐力运动后生物标志物变异性的创新方法:多因素分析

Innovative approach to interpret the variability of biomarkers after ultra-endurance exercise: the multifactorial analysis.

作者信息

Vassalle Cristina, Piaggi Paolo, Weltman Nathan, Prontera Concetta, Garbella Erika, Menicucci Danilo, Lubrano Valter, Piarulli Andrea, Castagnini Cinzia, Passera Mirko, Pellegrini Silvia, Metelli Maria Rosa, Bedini Remo, Gemignani Angelo, Pingitore Alessandro

机构信息

CNR Clinical Physiology Institute, Pisa, Italy.

出版信息

Biomark Med. 2014;8(6):881-91. doi: 10.2217/bmm.13.152.

Abstract

AIMS

We assessed the inter-relationship that exists between variations of different biochemical and hematological parameters following strenuous endurance exercise in Ironmen by using multiple factor analysis (MFA). MFA was used to estimate the associations among groups of parameters in order to identify concurrent changes in many different biochemical variables.

MATERIALS & METHODS: In total, 14 Ironman athletes were followed before and early after a race. MFA was applied to the parameters that showed a significant variation after the race, as we previously described in detail. Specifically, MFA standardizes data in each group and calculates the global axes (GAs), which are the linear combination of original parameters that maximize the global data variance.

RESULTS

MFA identified three global axes (GAs) as significant, explaining approximately 62% of the global data variance. The first GA contained NT-proBNP, IL-1ra, IL-6, IL-8 and the oxidative index. The second and third GAs included calcium, creatinine, potassium, uric acid, hemoglobin, hematocrit and glucose. Analysis of the first two GAs showed that changes in the oxidative index were associated with variations in IL-8 and NT-proBNP.

CONCLUSION

Among all the variables considered, MFA evidenced a close relationship between variations in oxidative stress, IL-8 and NT-proBNP, which may have a meaning in the mechanisms related to the physiological response after strenuous acute exercise.

摘要

目的

我们通过多因素分析(MFA)评估了铁人三项运动员进行高强度耐力运动后不同生化和血液学参数变化之间存在的相互关系。多因素分析用于估计参数组之间的关联,以识别许多不同生化变量的同时变化。

材料与方法

总共对14名铁人三项运动员在比赛前和比赛刚结束后进行了跟踪研究。如我们之前详细描述的那样,对比赛后显示出显著变化的参数应用了多因素分析。具体而言,多因素分析对每组数据进行标准化,并计算全局轴(GA),全局轴是原始参数的线性组合,可使全局数据方差最大化。

结果

多因素分析确定了三个显著的全局轴,解释了约62%的全局数据方差。第一个全局轴包含N末端B型利钠肽原(NT-proBNP)、白细胞介素-1受体拮抗剂(IL-1ra)、白细胞介素-6(IL-6)、白细胞介素-8(IL-8)和氧化指数。第二个和第三个全局轴包括钙、肌酐、钾、尿酸、血红蛋白、血细胞比容和葡萄糖。对前两个全局轴的分析表明,氧化指数的变化与IL-8和NT-proBNP的变化相关。

结论

在所有考虑的变量中,多因素分析证明氧化应激、IL-8和NT-proBNP的变化之间存在密切关系,这可能在与剧烈急性运动后生理反应相关的机制中具有意义。

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