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ARTICLE Metabolomics of salivary fatigue markers in soccer players after consecutive games Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by YORK UNIV on 07/05/14 For personal use only.

Song-Gyu Ra, Seiji Maeda, Ryota Higashino, Tomoko Imai, and Shumpei Miyakawa

Abstract: Strenuous and consecutive exercise leads to fatigue symptoms in athletes. Metabolomics is a comprehensive method to assess metabolites that involves the measurements of the overall metabolic signature of biological samples. Using metabolomic analysis, we investigated the identification of salivary fatigue markers in soccer players after 3 consecutive days of a game program. One hundred twenty-two male soccer players participated in 3 consecutive days of a game program. To detect fatigued athletes, we measured indices of traditional fatigue symptoms, i.e., heart rate, body mass and mood, before and after the program. We detected 37 fatigued players throughout the program. Before and after the program, the saliva in these players was analyzed using capillary electrophoresis and time-of-flight mass spectrometry (CE-TOFMS) and a multivariate statistical technique, principal component analysis, was used to process the data. CE-TOFMS was used to identify 144 metabolites in the saliva of fatigued players. A significant metabolomic difference was observed before and after 3 consecutive days of a soccer game program. Interestingly, metabolites were all increased after the program (P < 0.001). The identified metabolites, including 3-methylhistidine, glucose 1- and 6-phosphate, taurine, and some amino acids, were involved in skeletal muscle catabolism, glucose metabolism, lipid metabolism, amino acid metabolism, and energy metabolism. Our work demonstrated some salivary metabolites were significantly increased in the fatigued players after consecutive days of short soccer matches. We propose that the detected salivary metabolites may be new fatigue markers in athletes. Key words: metabolomics, saliva, fatigue, CE-TOFMS, soccer, “omics”. Résumé : Des exercices intenses et consécutifs se soldent par des symptômes de fatigue chez les athlètes. La métabolomique est une méthode qui étudie a` fond et répertorie l’ensemble des métabolites présents dans un échantillon biologique. Dans cette étude, on identifie au moyen de l’analyse métabolomique les marqueurs salivaires de la fatigue chez des joueurs de soccer après 3 jours consécutifs a` jouer au soccer. Cent vingt-deux joueurs de soccer masculin participent a` un programme de jeu d’une durée de trois jours. Pour dépister les athlètes fatigués, on évalue les symptômes traditionnels de la fatigue : fréquence cardiaque, masse corporelle, humeur, et ce, avant et après le programme. Tout au long du programme, on dépiste 37 joueurs fatigués. Avant et après le programme, on analyse la salive par électrophorèse capillaire associée a` la spectrométrie de masse a` temps de vol (« CE-TOFMS ») et on compare les résultats au moyen de techniques statistiques d’analyse multivariée telle que l’analyse en composantes principales. La « CE-TOFMS » permet d’identifier 144 métabolites dans la salive des joueurs fatigués. On observe une différence métabolomique significative entre les valeurs précédant et suivant le programme de trois jours consécutifs a` jouer au soccer. Fait a` noter, on observe après le programme une augmentation de tous les métabolites (P < 0,001). Les métabolites identifiés dont la 3-méthylhistidine, le glucose-1 et 6-phosphate, la taurine et quelques acides aminés sont tous impliqués dans le catabolisme du muscle squelettique, les métabolismes du glucose, des lipides, des acides aminés et de l’énergie. Nos travaux révèlent chez des joueurs fatigués une augmentation significative des marqueurs salivaires après des jours consécutifs a` participer a` de brèves parties de soccer. Nous proposons que ces métabolites salivaires constituent de nouveaux marqueurs de la fatigue des athlètes. [Traduit par la Rédaction] Mots-clés : métabolomique, salive, fatigue, « CE-TOFMS », soccer, « omique ».

Introduction In many soccer competitions (e.g., World Cup and Olympic Games), the games are consecutively performed in a short period. The ability to maintain physiological performance throughout a soccer match is considered to be crucial in determining the outcome of the competition. However, a common observation in many competitive sporting situations is that decreases in both physical and mental performances occur toward the later stages of a competitive event. Otherwise, prolonged physiological and mental

stresses with inadequate recovery lead to declined performance, accelerated fatigability, and subjective symptoms of stress. Although many parameters, including noninvasive behavioral and biological markers, biochemical markers, and hormonal and immunological markers, have been studied to evaluate an athlete's physical status (Lac and Maso 2004; Rietjens et al. 2005), a universal marker was not available for diagnosis and monitoring. To obtain optimal results in competitions, it is important to find fatigued players as soon as possible. Many researchers have tried

Received 27 November 2013. Accepted 18 April 2014. SG. Ra. Division of Sports Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8574, Japan; Japan Society for the Promotion of Science, 5-3-1 Kojimachi, Chiyoda-ku, Tokyo 102-0083, Japan. S. Maeda and S. Miyakawa. Division of Sports Medicine, Faculty of Health and Sport Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8574, Japan. R. Higashino. Division of Sports Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8574, Japan. T. Imai. Sports Research and Development Core, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8574, Japan. Corresponding author: Seiji Maeda (e-mail: [email protected]). Appl. Physiol. Nutr. Metab. 39: 1–7 (2014) dx.doi.org/10.1139/apnm-2013-0546

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to determine the symptoms of fatigue during competitions of short and (or) long duration by measuring the changes in heart rate (HR) (Dressendorfer et al. 1985), body mass (BM) (Budgett 1998), and psychological condition (Koutedakis et al. 1990). However, a single reliable physiological, biological, or immunological marker of fatigue symptoms has not been established (Purvis et al. 2010). Therefore, there is a great need to find a new marker that can comprehensively capture these symptoms in athletes. Metabolomics is a new “omics” discipline in addition to genomics and proteomics. It involves the determination of comprehensive metabolite profiles in biological matrices (Holmes et al. 2006). Great achievements have been obtained in metabolomics research, especially in biomedical sciences. Among biological factors, acute and (or) chronic physical exercise are known to generate many metabolic changes in humans (Yan et al. 2009; Lee et al. 2010; Santone et al. 2014) and should definitely be investigated in the context of metabolomics. The aim of this study was to identify, in fatigued athletes, salivary metabolites that changed after short consecutive games.

Materials and methods Subjects and experimental protocol A total of 122 male soccer players volunteered to participate in our study. All the players were intercollegiate athletes who belonged to a soccer team. The characteristics of the subjects are presented in Table 1. All measurements were performed at the same time of the day (in the morning, starting at 0600 h) to minimize diurnal variation. The subjects were asked to avoid alcohol and any physical activities the day before the first measurements. To eliminate as much of the interference from diet as possible, all the subjects had the same meals in the same restaurant during the consecutive days of the game program until the end of the experiment. Figure 1 shows a flow diagram of the progress of the subjects throughout the study. This study was conducted before and after 3 consecutive days (90 min game per day) of a game program. It has been reported that the stress response has already occurred at the beginning of the match season (Alix-Sy et al. 2008). Hence, HR, BM, psychological test (Profile of Mood States (POMS)), and the saliva of each subject were collected more than a month before the game program began as the “not fatigue” condition (pre-measurements). Similarly, on the day after the game program ended, the above parameters were measured as the “fatigue” condition (postmeasurements). On both measurement days, the subject's HR was measured immediately after waking up in the morning, using the HR monitor while the subject was in a sitting position. Thereafter, BM and POMS were measured and the saliva was collected. The study was performed in accordance with the Declaration of Helsinki and was approved by the Institutional Review Broad at the University of Tsukuba. All the subjects gave written informed consent to participate in the study. Physiological and psychological parameters Immediately after awakening, the HR was objectively measured using an HR monitor (SM-66; Skynie, Tokyo, Japan) attached to the top of the forefinger while the subject was in a sitting position. The HR was measured thrice, and the mean of the 3 values was used for further analysis. The BM was measured to the nearest 0.1 kg by using a digital scale (HD-661; Tanita, Tokyo, Japan), and height was measured to the nearest 0.1 cm by using a wall-mounted stadiometer (AD-6227R; A&D Co., Ltd., Tokyo, Japan). For these measurements, the participants were barefooted and they had been fasting for at least 8 h. The body mass index (BMI) was calculated as mass (in kilograms) divided by height (in metres) squared. The POMS is a standardized questionnaire that quantifies transient mood state (Rietjens et al. 2005). We monitored mental conditions at the time of each measurement using the POMS–

Appl. Physiol. Nutr. Metab. Vol. 39, 2014

Table 1. Subject characteristics (n = 122). Characteristic

Mean±SE

Age, y Height, cm Body mass, kg Body mass index, kg/m2 Heart rate at rest, beats/min

20.6±0.04 173.8±0.06 65.8±0.07 21.7±0.01 57.9±0.09

Brief Japanese Version. The POMS contains 6 subscales: vigor, fatigue, depression, confusion, tension–anxiety, and anger. At each measurement time, the subjects used a scale of 1 (not at all) to 5 (extremely) to answer the question “How are you feeling right now?” The score was computed by adding 5 negative mood states and subtracting 1 positive mood state. Saliva sampling To avoid acute physiological effects, the subjects refrained from alcohol consumption and intense physical activity for 24 h prior to the premeasurements. Before and after 3 consecutive days of a game program, after an overnight fast, saliva samples were obtained between 0600–0700 h in a quiet, temperature-controlled room, as described in previous studies (Fox et al. 1985; Akimoto et al. 2003). The subjects sat, rinsed their mouth with sterilized water (30 s × 3 times), then rested for at least 5 min. Saliva production was stimulated by the chewing of sterilized cotton (Salimetrics oral swab; Salimetrics LCC, USA) for 1 min at a rate of 1 chew/s. The amount of saliva in grams was converted to millilitres assuming a saliva density of 1 g/mL, as described in a previous study (Miletic et al. 1996). The obtained saliva samples were separated from the cotton by centrifugation (1500g), and the samples were frozen at –80 °C until analysis. Selection of fatigued subjects To detect the fatigued soccer players among all the subjects, we measured HR, BM, and POMS before and after 3 consecutive days of the game program. As can be seen in Fig. 1, we identified fatigued subjects on the basis of previous studies, setting the cutoff values as follows: increase in awakening HR (5 beats/min) (Dressendorfer et al. 1985), decrease in BM (5 pounds (i.e., 2.27 kg)) (Johnson and Thiese 1992; Budgett 1998), and increase in the fatigue score (5 score) and decrease in the vigor score (5 score) (Koutedakis et al. 1990). In this study, we defined a fatigued athlete as one that exceeded the above-mentioned cut-off values. In the measurements of the 3 parameters, 20, 9, and 15 athletes showed changes that were greater than or equal to the cut-off values for HR, BM, and fatigue and vigor scores, respectively (Fig. 1). There were 2, 3, and 2 athletes who showed changes that were greater than or equal to the cut-off values for 2 parameters (HR-BM, BM-POMS, and HR-POMS, respectively). As illustrated in Fig. 2, in each subject's group who showed changes the respective parameters (HR, BM, and POMS), there is a significant difference in the pre- and post-measurement values of each parameter. Finally, we analyzed the saliva of 37 athletes who satisfied any of the above criteria with a global analysis of the endogenous fatigue markers in saliva by using capillary electrophoresis and time-of-flight mass spectrometry (CE-TOFMS) analysis. There were no differences in subject characteristics between all subjects (n = 122) and selected 37 subjects in the premeasurements. CE-TOFMS analysis and quantification of endogenous salivary metabolites Sample collection and preparation Salivary samples (25 ␮L) were combined with 25 ␮L of Milli-Q water, including 400 ␮mol/L of commercial Internal Standard Solution 1 (Solution ID: H3304-1002; Human Metabolome Technologies, Published by NRC Research Press

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Fig. 1. Flow diagram of the progress of the subjects throughout the whole experiment. HR, heart rate; BM, body mass; POMS, profiles of mood state test.

Pre measurements (n=122)

4 weeks prior to starting game program

1 day after last game program

Post measurements (n=122)

HR

+5 beat / min (n=20)

BM

POMS

+5 fatigue score and -5 vigor score (n=15)

-2.27 kg (n=9)

Salivary metabolome analysis (n=37)

(A)

(B)

∗

90 85 80 75 70 65 60 55

∗

70

Body mass (kg)

Heart rate (beat / min)

Fig. 2. Changes in the heart rate (A, n = 20), body mass (B, n = 9), and fatigue (C, n = 15) and vigor (D, n = 15) scores of Profile of Mood States (POMS) between pre- (Pre; open bar) and post-measurements (Post; filled bar). Values are the mean ± SE. *, Significant difference from Pre (P < 0.001).

68 66 64 62 60

Pre

(C)

Post

Pre

18 16 14 12 10 8 6 4 2 0 Pre

Post

Tsuruoka, Japan), and were mixed thoroughly. The mixtures were filtered with a 5 kDa cut-off filter to remove proteins and macromolecules. The filtrate was analyzed using CE-TOFMS. Instrumentation CE-TOFMS was performed using an Agilent CE (capillary electrophoresis) system equipped with an Agilent 6210 Time of Flight

Post

∗

(D)

∗ Vigor (score)

Fatigue (score)

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3 consecutive days of game program

16 14 12 10 8 6 4 2 0 Pre

Post

mass spectrometer, Agilent 1100 isocratic high-performance liquid chromatography pump, Agilent G1603A CE-MS adaptor kit, and Agilent G1607A CE electrospray ionization-mass spectrometry (ESI-MS) sprayer kit (Agilent Technologies, Waldbronn, Germany). The system was controlled using the Agilent G2201AA ChemStation software version B.03.01 for CE (Agilent Technologies, Waldbronn, Germany). Published by NRC Research Press

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Fig. 3. Principal component analysis (PCA) score plots (PC1, PC2) of premeasurements (Pre) and postmeasurements (Post) of salivary metabolites. The x axis and y axis were labeled with PC1 (the first principal component) and PC2 (the second principal component), respectively. A clear movement of the data points with accumulating soccer game loads was shown, indicating that consecutive days of short soccer games had a significant impact on salivary metabolites. Pre

10

Post

PC2 (10.43%)

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5

0

-5

-10

-15

-10

0

10

20

30

40

50

PC1 (39.87%)

CE-TOFMS conditions Cationic metabolites were analyzed using a fused silica capillary (internal diameter (ID), 50 ␮m; total length, 80 cm) with a commercial cation electrophoresis buffer (Solution ID: H33011001; Human Metabolome Technologies, Tsuruoka, Japan) as the electrolyte. The sample was injected at a pressure of 5 mbar for 10 s (approximately 10 nL). The applied voltage was set at 27 kV. ESI-MS was conducted in the positive ion mode, and the capillary voltage was set at 4000 V. The spectrometer was scanned from mass-to-charge ratio (m/z) 50 to 1000. Other conditions were those used in the cation analysis (Soga and Heiger 2000; Soga et al. 2003). Anionic metabolites were analyzed using a fused silica capillary (ID, 50 ␮m; total length, 80 cm) with a commercial anion electrophoresis buffer (Solution ID: H3302-1021; Human Metabolome Technologies) as the electrolyte. The sample was injected at a pressure of 50 mbar for 25 s (approximately 25 nL). The applied voltage was set at 30 kV. ESI-MS was conducted in the negative ion mode, and the capillary voltage was set at 3500 V. The spectrometer was scanned from m/z 50 to 1000. Other conditions followed those used in the anion analysis (Soga et al. 2002, 2003, 2007). Data analysis Raw data obtained using CE-TOFMS were processed with MasterHands (Sugimoto et al. 2010). Signal peaks corresponding to isotopomers, adduct ions, and other product ions of known metabolites were excluded, and all signal peaks potentially corresponding to authentic compounds were extracted and their migration time (MT) was normalized using those of the internal standards. Thereafter, the alignment of peaks was performed according to the m/z values and normalized MT values. Finally, peak areas were normalized against those of the internal standards: methionine sulfone (MetSul) and camphorsulfonic acid (CSA) for cations and anions, respectively. The resultant relative area values were further normalized by the sample amount. Annotation tables were produced from CE-ESI-TOFMS measurements of standard compounds and were aligned with the datasets according to similar m/z values and normalized MT values. Statistical analysis The data are expressed as the mean ± SEM values. Before multivariate data analysis, all the peak areas were normalized by an internal standard. The data were reduced to a few principal components (PCs) that described the maximum variation of different groups or samples. Principal component analysis (PCA) was used

to process the acquired CE-TOFMS data. PCA involved a mathematical procedure that transformed a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components). Each PC was a linear combination of the original data parameters, whereby each successive PC explained the maximum amount of variance possible but was not accounted for by the previous PCs. Each PC was orthogonal and, therefore, independent of any other PCs. Thus, the comparative analysis of the CE-TOFMS data was facilitated by reducing the dimensionality of the cross-validation groups that was used throughout the process to determine the number of PCs. Differences in the HR, BM, and POMS scores were analyzed using Student's t test, and differences in salivary metabolites at 2 time points (pre- and post-measurements) were analyzed using Wilcoxon single-rank test. The mean difference was reported as significant at the 0.05, 0.01, and 0.001 levels. The statistical analysis was conducted using SPSS software version 20.0 for Windows (SPSS Japan Inc., Tokyo, Japan).

Results Multivariate data analysis According to PCA, identification of the deconvoluted peaks revealed that many endogenous metabolites, such as amino acids, fatty acids, skeletal muscle components, and precursor or intermediate metabolites of energy metabolism, can be detected using CE-TOFMS. Two-dimensional figures were generated to characterize the metabolites (Fig. 3). Figure 3 shows metabolomics movement between the pre- and post-measurements during 3 consecutive days of a game program. In these score plots, the x axis and y axis were labeled as PC 1 and 2, respectively, and each dot point represented 1 subject. The result of PCA was displayed as score plots to represent the scatter of samples, which clustered closely to indicate a similar metabolomics composition and clustered far apart to indicate different metabolomics compositions. The pre- and post-measurements could be separated. This two-dimensional figure indicates that 3 consecutive days of a soccer game program had a significant impact on the metabolites in the saliva of male football players. Metabolic profile changes induced by 3 consecutive days of a game program Three consecutive days of a soccer game program induced changes in the metabolites of the soccer players. We obtained 144 endogenous salivary metabolites by using the CE-TOFMS analPublished by NRC Research Press

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Table 2. Salivary metabolites for which significant differences were detected between premeasurements and postmeasurements.

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Relative areas Related metabolic pathway

Metabolites

Premeasurements

Postmeasurements

Factor loading (PC1)

Skeletal muscle component Glucose metabolism Glucose metabolism Precursor of Pyr, glucose metabolism Precursor of Pyr Precursor of Ace-C Precursor of Ace-C and Pyr Precursor of Ace-C and Fum Precursor of Ace-C and Fum Precursor of Ace-C and Suc-C Precursor of Suc-C Sulfur-containing amino acid

3-Methylhistidine Glucose 1-phosphate Glucose 6-phosphate Ala Gly Leu (branched-chain amino acid) Trp (aromatic amino acid) Phe (aromatic amino acid) Tyr (aromatic amino acid) Ile (branched-chain amino acid) Val (branched-chain amino acid) Taurine

5.40±0.17 2.11±0.05 9.72±0.25 179.64±3.21 463.30±9.36 178.22±3.41 10.30±2.10 265.88±4.09 194.64±2.97 83.62±1.81 140.15±2.64 225.19±3.72

8.07±0.16* 5.17±0.13* 16.99±0.38* 282.80±5.59* 676.55±11.30* 350.39±9.74* 16.56±4.00* 343.64±4.49* 235.20±3.40* 175.61±5.00* 290.84±7.95* 394.18±7.36*

0.8456 0.7472 0.8271 0.9257 0.5317 0.8857 0.8227 0.6528 0.4405 0.8048 0.9445 0.9019

Note: Relative area of metabolites are given as the mean ± SE (10–5). *, Mean difference between premeasurement and postmeasurement metabolites (relative area) at 0.01 levels. All factor loading were significantly correlated with PC1 at 0.001 levels. PC1, principal component 1; Pyr, pyruvate; Ace-C, acetyl-CoA; Fum, fumarate; Suc-C, succinyl-CoA; Ala, alanine; Gly, glycine; Leu, leucine; Trp, tryptophan; Phe, phenylalanine; Tyr, tyrosine; Ile, isoleucine; Val, valine.

ysis. Of the 144 metabolites, we listed the metabolites for which significant differences were detected between 2 time points (preand post-measurements) (Table 2). Interestingly, these metabolites were significantly increased in the postmeasurement than in the premeasurement. Factor loading with respect to changes in the endogenous saliva metabolites Factor loadings are presented in Table 2. Factor loading is defined as the correlation coefficient in the PCA. In Table 2, we marked the factor loadings for PC1 because PC1 had the most impact on the changes in the metabolites during the 3 consecutive days of a game program. Furthermore, all factor loadings were significantly correlated with PC1 (P < 0.001). Particularly, the factor loadings of alanine (Ala), valine (Val), and taurine were greater than 0.9. In addition, the metabolites with factor loading values that exceeded 0.8 were detected. This means that changes in these metabolites have a strong influence on the changes of whole metabolites between pre- and post-measurements in male soccer players.

Discussion In the present study, some salivary metabolites were significantly increased in soccer players after 3 consecutive days of a soccer match program. Using CE-TOFMS–based metabolomic analysis, we measured the variation in metabolites in soccer players before and after consecutive days of a game program. In this study, fatigue symptoms in soccer players in consecutive soccer games were assessed by changes in HR, BM, and POMS measurements. Interestingly, some of the salivary metabolites in the male soccer players increased after 3 consecutive days of a game program. We propose that the detected salivary metabolites may be new fatigue markers in athletes. Soccer is a type of strength–endurance sport, and performance in competitions depends heavily on factors such as aerobic and sprint ability, ball control, body contact and jump, and tactics. An international top-class player performs approximately 1350 activities during a game, including approximately 220 runs at high speed (Mohr et al. 2003), indicating that the rates of creatinephosphate utilization and glycolysis are frequently high during a game. This high strength–endurance sport is sure to stimulate the metabolic profile remarkably. Thus, metabolomics technology is extremely suitable for monitoring the changes in the physiological state of soccer players to help achieve a good result in the competition. The total concentrations of most of these compounds are much lower in saliva than in serum or plasma. However, metabolite

concentrations in the saliva can provide a reliable reference for their respective blood concentrations (Sannikka et al. 1983; Cadore et al. 2008). Saliva has been used as a diagnostic tool in many clinical situations, in which it has provided valuable information about the biochemical, metabolic, and functional status of the individual (Mandel 1990). Saliva sampling has the advantage over venous or capillary sampling by causing less stress and sparing the uncomfortable and sometimes traumatic experience of repeated venepunctures or skin prickings. Saliva sampling also does not require special training and offers the possibility of the subjects collecting their own samples, saving the time of technicians, and being economical. These features make repeated sampling more acceptable to the individual, allowing a more detailed and accurate estimation of the biochemical changes related to a particular exercise test, particularly in field studies. In the present study, salivary 3-methylhistidine (3M-His) was increased 1.3-fold in fatigued subjects after the program. The measurement of 3M-His provides an index for the rate of muscle protein breakdown because free 3M-His is not used in protein resynthesis. When proteins are broken down in the body, the 3M-His levels increase in the urine (Tiao et al. 1997) and the blood (Nagasawa et al. 1998). In addition, this metabolite has a high factor loading value (0.8456, P < 0.001). It is possible that fatigued subjects have enhanced protein catabolism. Similarly, salivary taurine concentration was significantly increased after 3 days of a consecutive soccer match program. Taurine is the most abundant amino acid-like compound found in the skeletal muscle and other organs (Jacobsen and Smith 1968; Huxtable 1980). The taurine is released in the blood from contracting muscles, to control osmotic pressure (Cuisinier et al. 2002) and owing to increased reactive oxygen species (ROS) (Ørtenblad et al. 2003). In fact, it has been reported that ROS in the body fluid increased after a soccer match (Ferrer et al. 2009). Furthermore, the factor loading of taurine was greater than 0.9 (P < 0.001). Thereby, we inferred that 3 days of a consecutive soccer match program increased salivary taurine concentration. During exercise, glucose metabolism is activated in the skeletal muscles and myocardium. In fact, average blood lactate concentrations of 7 to 8 mmol/L have been observed during soccer games (Ekblom 1986). High blood lactate concentrations in soccer players suggested that glycolysis and demand for glucose are increased during a soccer game. In the process of glycolysis, both glucose-1-phosphate (G-1-P) and glucose-6-phosphate (G-6-P) are phosphorylated from glycogen and glucose, respectively (Fig. 4A). Likewise, Ala plays an important role in the Ala–glucose cycle to accelerate gluconeogenesis. In the present study, increasing glycolysis- and gluconeogenesis-related substances (G-1-P, G-6-P, and Published by NRC Research Press

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Fig. 4. Pathways of glucose synthesis and catabolism (A) and the tricarboxylic acid (TCA) cycle (B). Both glucose-1-phosphate and glucose6-phosphate are phosphorylated from glycogen and glucose. The amino acids (in the gray boxes) are categorized by the respective compounds in the TCA cycle to which they are precursors. Ace-C precursors: Leu, Trp, Ile, Phe, and Tyr; Suc-C precursors: Ile and Val; Fum precursors: Phe and Tyr; and Pyr precursors: Gly and Ala. Detected salivary fatigue markers (in the gray ellipses and boxes) were significantly increased in the postmeasurements than in the premeasurements (P < 0.001). Ace-C, acetyl-CoA; Suc-C, succinyl-CoA; Fum, fumarate; Pyr, pyruvate; Leu, leucine; Trp, tryptophan; Ile, isoleucine; Phe, phenylalanine; Tyr, tyrosine; Val, valine; Gly, glycine; Ala, alanine.

(B)

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(A)

Leu Trp Ile Phe Tyr

Glycogen

Ile Val α-ketoglutarate

Isocitrate

Glucose 1-phosphate

Suc-C

Citrate

Ace-C

TCA cycle Succinate

Oxaloacetate Glucose 6-phosphate

Pyr Malate

Glucose

Tyr Gly Ala

Ala) were possibly reflected in increasing glucose demands due to the soccer match program. It is generally accepted that energy expenditure will be elevated with increasing exercise loading, and lipolysis and the tricarboxylic acid cycle will be activated accordingly. As shown in Fig. 4B, in the present study, Ala, tryptophan (Trp), phenylalanine (Phe), tyrosine (Tyr), isoleucine (Ile), and Val were significantly increased in the saliva of fatigued soccer players. Particularly, the factor loadings of Ala and Val were greater than 0.9, which indicates that changes in these amino acids were relevant to changes in salivary metabolites in fatigued soccer players. Furthermore, in the some previous studies, these amino acids (Ala, Trp, Phe, Tyr, Ile, and Val) were significantly increased after exercise in the blood (Dohm et al. 1981; Sahlin et al. 1990; Strüder et al. 1999). Therefore, it seems reasonable to conclude that changes in these amino acids in saliva may reflect changes in amino acids in the blood in fatigued subjects. In the present study, some salivary metabolites were increased in soccer players after 3 consecutive days of a soccer match program. The conceivable next steps are a comparison with control subjects (i.e., non-fatigued athletes) and (or) correlation analyses between changes in metabolites and degree of fatigue. The third step is consecutive investigations of the candidates of new marker (metabolites), conventional fatigue markers (HR, BM, POMS, etc.), and actual physical condition (game performance, physical fitness level, risk of injury and (or) disease, etc.). Markers, which can detect fatigue sign earlier and more accurately than conventional markers, are needed. The final step is to establish a convenient and reliable method to measure the metabolite(s). This is an important factor to introduce the new marker(s) for the sport fields.

Fum

Phe Tyr

In conclusion, some salivary metabolites were significantly increased in the fatigued soccer players after 3 consecutive days of soccer matches. It is possible that these increased metabolites are fatigue markers in the saliva during the consecutive days of short soccer games. Conflict of interest The authors declare no conflict of interest.

Acknowledgements We thank Youngju Choi and Shoji Takayanagi for data acquisition in this study. In addition, Hajime Ohmori and Asako ZempoMiyaki are kindly acknowledged for their valuable comments on the study and the manuscript.

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