BackgroundRecent studies have begun to identify the molecular determinants of inter-individual variability of cardiorespiratory fitness (CRF) in response to exercise training programs. However, we still have an incomplete picture of the molecular mechanisms underlying trainability in response to exercise training.ObjectiveWe investigated baseline serum and skeletal muscle metabolomics profile and its associations with maximal power output (MPO) gains in response to 8-week of continuous endurance training (ET) and high-intensity interval training (HIIT) programs matched for total units of exercise performed (the TIMES study).MethodsEighty healthy sedentary young adult males were randomized to one of three groups and 70 were defined as completers (> 90% of sessions): ET (n = 30), HIIT (n = 30) and control (CO, n = 10). For the CO, participants were asked to not exercise for 8 weeks. Serum and skeletal muscle samples were analyzed by 1H-NMR spectroscopy. The targeted screens yielded 43 serum and 70 muscle reproducible metabolites (intraclass > 0.75; coefficient of variation < 25%). Associations of baseline metabolites with MPO trainability were explored within each training program via three analytical strategies: (1) correlations with gains in MPO; (2) differences between high and low responders to ET and HIIT; and (3) metabolites contributions to the most significant pathways related to gains in MPO. The significance level was set at P < 0.01 or false discovery rate of 0.1.ResultsThe exercise programs generated similar gains in MPO (ET = 21.4 ± 8.0%; HIIT = 24.3 ± 8.5%). MPO associated baseline metabolites supported by all three levels of evidence were: serum glycerol, muscle alanine, proline, threonine, creatinine, AMP and pyruvate for ET, and serum lysine, phenylalanine, creatine, and muscle glycolate for HIIT. The most common pathways suggested by the metabolite profiles were aminoacyl-tRNA biosynthesis, and carbohydrate and amino acid metabolism.ConclusionWe suggest that MPO gains in both programs are potentially associated with metabolites indicative of baseline amino acid and translation processes with additional evidence for carbohydrate metabolism in ET.

Lack of time is seen as a barrier to maintaining a physically active lifestyle. In this sense, interval training has been suggested as a time-efficient strategy for improving health, mainly due to its potential to increase cardiorespiratory fitness. Currently, the most discussed interval training protocols in the literature are the high-intensity interval training (HIIT) and the sprint interval training (SIT). Objective: We investigated, through a systematic review and meta-analysis, which interval training protocol, HIIT or SIT, promotes greater gain in cardiorespiratory fitness (V˙O2max/peak). The studies were selected from the PubMed (MEDLINE), Scopus and Web of Science databases. From these searches, a screening was carried out, selecting studies that compared the effects of HIIT and SIT protocols on V˙O2max/peak. A total of 19 studies were included in the final analysis. Due to the homogeneity between studies (I2 = 0%), fixed-effects analyses were performed. There was no significant difference in the V˙O2max/peak gains between HIIT and SIT for the standardized mean difference (SMD = 0.150; 95% CI = −0.038 to 0.338; p = 0.119), including studies that presented both measurements in mL·kg−1·min−1 and l·min−1; and raw mean differences (RMD = 0.921 mL·kg−1·min−1; 95% CI = −0.185 to 2.028; p = 0.103) were calculated only with data presented in mL·kg−1·min−1. We conclude that the literature generates very consistent data to confirm that HIIT and SIT protocols promote similar gains in cardiorespiratory fitness. Thus, for this purpose, the choice of the protocol can be made for convenience.

Purpose: High heterogeneity of the response of cardiorespiratory fitness (CRF) to standardized exercise doses has been reported in different training programs, but the associated mechanisms are not widely known. This study investigated whether changes in the metabolic profile and pathways in blood serum and the skeletal muscle are associated with the inter-individual variability of CRF responses to 8-wk of continuous endurance training (ET) or high-intensity interval training (HIIT).Methods: Eighty men, young and sedentary, were randomized into three groups, of which 70 completed 8 wk of intervention (&gt; 90% of sessions): ET, HIIT, or control. Blood and vastus lateralis muscle tissue samples, as well as the measurement of CRF [maximal power output (MPO)] were obtained before and after the intervention. Blood serum and skeletal muscle samples were analyzed by 600 MHz 1H-NMR spectroscopy (metabolomics). Associations between the pretraining to post-training changes in the metabolic profile and MPO gains were explored via three analytical approaches: (1) correlation between pretraining to post-training changes in metabolites' concentration levels and MPO gains; (2) significant differences between low and high MPO responders; and (3) metabolite contribution to significantly altered pathways related to MPO gains. After, metabolites within these three levels of evidence were analyzed by multiple stepwise linear regression. The significance level was set at 1%.Results: The metabolomics profile panel yielded 43 serum and 70 muscle metabolites. From the metabolites within the three levels of evidence (15 serum and 4 muscle metabolites for ET; 5 serum and 1 muscle metabolites for HIIT), the variance in MPO gains was explained: 77.4% by the intervention effects, 6.9, 2.3, 3.2, and 2.2% by changes in skeletal muscle pyruvate and valine, serum glutamine and creatine phosphate, respectively, in ET; and 80.9% by the intervention effects; 7.2, 2.2, and 1.2% by changes in skeletal muscle glycolate, serum creatine and creatine phosphate, respectively, in HIIT. The most changed and impacted pathways by these metabolites were: arginine and proline metabolism, glycine, serine and threonine metabolism, and glyoxylate and dicarboxylate metabolism for both ET and HIIT programs; and additional alanine, aspartate and glutamate metabolism, arginine biosynthesis, glycolysis/gluconeogenesis, and pyruvate metabolism for ET.Conclusion: These results suggest that regulating the metabolism of amino acids and carbohydrates may be a potential mechanism for understanding the inter-individual variability of CRF in responses to ET and HIIT programs.