Boudry Félix, Durand Fabienne, Goossens Corentine
Espace Dev, Université de Perpignan Via Domitia, 66860 Perpignan, France.
UMR Espace Dev (228), Université Montpellier, IRD, 34093 Montpellier, France.
Metabolites. 2025 Jun 17;15(6):408. doi: 10.3390/metabo15060408.
: Respiratory pathologies, such as COVID-19 and bronchitis, pose significant challenges for high-level athletes, particularly during demanding altitude training camps. Metabolomics offers a promising approach for early detection of such pathologies, potentially minimizing their impact on performance. This study investigates the metabolic differences between athletes with and without respiratory illnesses during an altitude training camp using urine samples and multivariate analysis. : Twenty-seven elite rowers (15 males, 12 females) participated in a 12-day altitude training camp at 1850 m. Urine samples were collected daily, with nine athletes developing respiratory pathologies (8 COVID-19, 1 bronchitis). Nuclear Magnetic Resonance spectroscopy was used to analyze the samples, followed by data processing with Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), allowing to use Variable Importance in Projection (VIP) scores to identify key metabolites contributing to group separation. : The PLS-DA model for respiratory illness showed good performance (R = 0.89, Q = 0.35, < 0.05). Models for altitude training achieved higher predictive power (Q = 0.51 and 0.72, respectively). Metabolites kynurenine, -methylnicotinamide, pyroglutamate, propionate, -formyltryptophan, tryptophan and glucose were significantly highlighted in case of respiratory illness while trigonelline, 3-hydroxyphenylacetate, glutamate, creatine, citrate, urea, o-hydroxyhippurate, creatinine, hippurate and alanine were correlated to effort in altitude. This distinction confirms that respiratory illness induces a unique metabolic profile, clearly separable from hypoxia and training-induced adaptations. : This study highlights the utility of metabolomics in identifying biomarkers of respiratory pathologies in athletes during altitude training, offering the potential for improved monitoring and intervention strategies. These findings could enhance athlete health management, reducing the impact of illness on performance during critical training periods. Further research with larger cohorts is warranted to confirm these results and explore targeted interventions.
呼吸道疾病,如新冠肺炎和支气管炎,给高水平运动员带来了重大挑战,尤其是在要求严苛的高原训练营期间。代谢组学为早期检测此类疾病提供了一种很有前景的方法,有可能将其对运动表现的影响降至最低。本研究使用尿液样本和多变量分析,调查了高原训练营期间患有和未患有呼吸道疾病的运动员之间的代谢差异。27名精英赛艇运动员(15名男性,12名女性)参加了在海拔1850米处进行的为期12天的高原训练营。每天收集尿液样本,其中9名运动员出现呼吸道疾病(8例新冠肺炎,1例支气管炎)。使用核磁共振波谱分析样本,随后用主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)进行数据处理,通过投影变量重要性(VIP)得分来识别有助于组间分离的关键代谢物。呼吸道疾病的PLS-DA模型表现良好(R = 0.89,Q = 0.35,P < 0.05)。高原训练的模型具有更高的预测能力(Q分别为0.51和0.72)。在患有呼吸道疾病的情况下,犬尿氨酸、N-甲基烟酰胺、焦谷氨酸、丙酸盐、N-甲酰基色氨酸、色氨酸和葡萄糖等代谢物显著突出,而葫芦巴碱、3-羟基苯乙酸、谷氨酸、肌酸、柠檬酸盐、尿素、邻羟基马尿酸盐、肌酐、马尿酸盐和丙氨酸与高原训练中的运动强度相关。这种差异证实,呼吸道疾病会诱发独特的代谢特征,明显有别于缺氧和训练引起的适应性变化。本研究强调了代谢组学在识别高原训练期间运动员呼吸道疾病生物标志物方面的实用性,为改进监测和干预策略提供了可能性。这些发现可以加强运动员的健康管理,减少疾病在关键训练期对运动表现的影响。有必要进行更大样本量的进一步研究以证实这些结果并探索针对性干预措施。