Insights into the Serum Metabolic Adaptations in Response to Inspiratory Muscle Training: A Metabolomic Approach Based on 1H NMR and UHPLC-HRMS/MS

International Journal of Molecular Sciences(2023)

引用 0|浏览11
暂无评分
摘要
Inspiratory muscle training (IMT) is known to promote physiological benefits and improve physical performance in endurance sports activities. However, the metabolic adaptations promoted by different IMT prescribing strategies remain unclear. In this work, a longitudinal, randomized, double-blind, sham-controlled, parallel trial was performed to investigate the effects of 11 weeks (3 daysweek(-1)) of IMT at different exercise intensities on the serum metabolomics profile and its main regulated metabolic pathways. Twenty-eight healthy male recreational cyclists (30.4 +/- 6.5 years) were randomized into three groups: sham (6 cmH2O of inspiratory pressure, n = 7), moderate-intensity (MI group, 60% maximal inspiratory pressure (MIP), n = 11) and high-intensity (HI group, 85-90% MIP, n = 10). Blood serum samples were collected before and after 11 weeks of IMT and analyzed by H-1 NMR and UHPLC-HRMS/MS. Data were analyzed using linear mixed models and metabolite set enrichment analysis. The H-1 NMR and UHPLC-HRMS/MS techniques resulted in 46 and 200 compounds, respectively. These results showed that ketone body metabolism, fatty acid biosynthesis, and aminoacyl-tRNA biosynthesis were upregulated after IMT, while alpha linolenic acid and linoleic acid metabolism as well as biosynthesis of unsaturated fatty acids were downregulated. The MI group presented higher MIP, Tryptophan, and Valine levels but decreased 2-Hydroxybutyrate levels when compared to the other two studied groups. These results suggest an increase in the oxidative metabolic processes after IMT at different intensities with additional evidence for the upregulation of essential amino acid metabolism in the MI group accompanied by greater improvement in respiratory muscle strength.
更多
查看译文
关键词
metabolome,metabolism,omic sciences,breathing exercises,H-1 NMR,LC-HRMS
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要