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A Metabolomic Approach and Traditional Physical Assessments to Compare U22 Soccer Players According to Their Competitive Level.

ABSTRACT: The purpose of this study was to use traditional physical assessments combined with a metabolomic approach to compare the anthropometric, physical fitness level, and serum fasting metabolic profile among U22 soccer players at different competitive levels. In the experimental design, two teams of male U22 soccer were evaluated (non-elite = 20 athletes, competing in a regional division; elite = 16 athletes, competing in the first division of the national U22 youth league). Earlobe blood samples were collected, and metabolites were extracted after overnight fasting (12 h). Untargeted metabolomics through Liquid Chromatograph Mass Spectrometry (LC-MS) analysis and anthropometric evaluation were performed. Critical velocity was applied to determine aerobic (CV) and anaerobic (ARC) capacity. Height (non-elite = 174.4 ± 7.0 cm; elite = 176.5 ± 7.0 cm), body mass index (non-elite = 22.1 ± 2.4 kg/m²; elite = 21.9 ± 2.3 kg/m²), body mass (non-elite = 67.1 ± 8.8 kg; elite = 68.5 ± 10.1 kg), lean body mass (non-elite = 59.3 ± 7.1 kg; elite = 61.1 ± 7.9 kg), body fat (non-elite = 7.8 ± 2.4 kg; elite = 7.3 ± 2.4 kg), body fat percentage (non-elite = 11.4 ± 2.4%; elite = 10.5 ± 1.7%), hematocrit (non-elite = 50.2 ± 4.0%; elite = 51.0 ± 4.0%), CV (non-elite = 3.1 ± 0.4 m/s; elite = 3.0 ± 0.2 m/s), and ARC (non-elite = 129.6 ± 55.7 m; elite = 161.5 ± 61.0 m) showed no significant differences between the elite and non-elite teams, while the multivariate Partial Least Squares Discriminant Analysis (PLS-DA) model revealed a separation between the elite and non-elite athletes. Nineteen metabolites with importance for projection (VIP) >1.0 were annotated as belonging to the glycerolipid, sterol lipid, fatty acyl, flavonoid, and glycerophospholipid classes. Metabolites with a high relative abundance in the elite group were related in the literature to a better level of aerobic power, greater efficiency in the recovery process, and improvement of mood, immunity, decision making, and accuracy, in addition to acting in mitochondrial preservation and electron transport chain maintenance. In conclusion, although classical physical assessments were not able to distinguish the teams at different competitive levels, the metabolomics approach successfully indicated differences between the fasting metabolic profiles of elite and non-elite teams.

SUBMITTER: da Cruz JP

PROVIDER: S-EPMC9331507 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PURPOSE:The aim of this study was to quantify changes in physical capacities of thirty-eight basketball players selected from different teams, as well as from varying competitive levels (i.e. Division I, Division II and Division III) during the preparation and in-season periods. METHODS:Pre (T1) and post (T2) preparation period and during regular season (T3), the players completed a Yo-Yo Intermittent Recovery test-level 1. Following a 3 to 8 days-break, players performed a 6-min continuous running test (Mognoni's test), a counter-movement jump test and a 5-min high-intensity intermittent running test. RESULTS:Blood lactate concentration measured after the Mognoni's test was significantly reduced from T1 to T2, and from T2 to T3 (P<0.001, ƞ2 = 0.424). The distance covered during the Yo-Yo Intermittent Recovery test was significantly increased only from T1 to T2 in Division II and III (P<0.001, ƞ2 = 0.789). Similarly, the physiological responses to high-intensity intermittent running test were improved only from T1 to T2 (all P<0.001, ƞ2 = 0.495 to 0.652). Despite significant changes observed in running tests from T1 to T2, at individual level 35-55% of players did not show a very likely improvement. Relative peak power produced during vertical jumps at T3 by Division I players was increased compared to T1 (ANOVA interaction, P = 0.037, ƞ2 = 0.134). CONCLUSIONS:The main improvements in physical capacities occurred during the preparation period, when the aerobic fitness and the ability to sustain high-intensity intermittent efforts were moderately-to-largely improved. However, it appears that the preparation period does not consistently impact on vertical jump variables. Aerobic fitness and force/power production during vertical jumps appear to improve across the competitive season (slightly-to-moderately). Physical tests should be used to identify weaknesses in physical performance of players and to monitor their fatigue status, with the aim to develop individualized training programs.

Project description:The main objective of this study is to analyse sub-maximum intensity periods (SubMIP's) manifested by professional soccer players during official matches (number of events and time spent in each event), according to the player position, match halve and match, and also to group the players according to their SubMip values during the competition.MethodsWe collected a total of 247 individual records of 14 players using Global Positioning System (GPS) during 15 official league matches (Azerbaijan Premier League 2019-2020). We calculated both the number of SubMIPs events and the time each player spent in the SubMIPs zone (threshold of 85% MIP). We analysed the possible independence of the variables with the Kruskal-Wallis test and the possible specific relationships between the groups using a post-hoc analysis with Dunn's test. In order to explore the possible distribution of physical demands in homogeneous groups, a cluster analysis was performed.ResultsThe statistical analysis showed significant differences between the individual variables in the number of events and in the time spent by the player above the threshold in distance covered at speed >19.8 km/h (HSR), distance covered at speed >25.2 km/h (Sprint), acceleration density (AccDens), mean metabolic power (MetPow), metres per minute (Mmin) and high metabolic load distance >25.5 W/kg (HMLD). Differences were also found according to the playing position in MetPow, Mmin and between halves in AccDens, MetPow, Mmin. In the clustering based on the time spent by the player in SubMIPs, three main groups were described: (1) the centroid was located in lower values in each of the variables; (2) there were an accentuation of the AccDens variable; (3) all the variables, except AccDens, were accentuated.ConclusionsThe main differences with regard to SubMIPs were related to the player's individual physical performance and not to position. However, the player's position could act as an attractor and show significant differences during matches.

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A Metabolomic Approach and Traditional Physical Assessments to Compare U22 Soccer Players According to Their Competitive Level.

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