In a myokinase reaction, the phosphate moiety moves between two adenosine diphosphate molecules, leading to the formation of one adenosine triphosphate (ATP) molecule and one AMP molecule. Afterward, AMP is deaminated to IMP and ammonia (NH3) by AMP deaminase (AMPd) (21). During high-intensity exercise, metabolic energy-generating systems reach their upper limits of efficiency and an unbalance between ATP supply and demand occurs. Under the circumstances, muscle contents of total adenine nucleotides are degraded to IMP and NH3 by ATP deaminase (24). IMP can be reconverted to AMP via the purine nucleotide cycle or further degraded to hypoxanthine (Hx). In contrast to phosphorylated compounds, NH3 and Hx are capable of passing across the cell membrane, and thus, their plasma concentrations may provide useful data about cellular metabolism and energy sources (26).
Exercise intensity is crucial to purine nucleotide metabolism. It is the main determinant of plasma Hx concentration (17,25,27). After a low- or moderate-intensity exercise, no significant changes in muscle ATP (1,29) or plasma purine concentration (27) have been observed. Sjödin and Hellsten-Westing (27) have revealed that a critical point of plasma Hx concentration exists at 110% of V˙O2max, which indicates an increase in purine formation concurrent with exercise intensity increase.
Hx has been considered to be an indicator of tissue hypoxia for a long time (35). It is also regarded as a marker of adenine nucleotides' degradation in skeletal muscle, an indicator of energetic stress during exercise (26), a parameter of exercise intensity (23), and a criterion of exercise classification (5).
So far, very few studies have been published that raise the problem of training effect on purine metabolism. Hellsten-Westing et al. (15,16) have proved that, after 6 wk of a high-intensity intermittent training, the level of plasma Hx at rest and after exercise decreases considerably, and muscle Hx-guanine phosphoribosyltransferase (HGPRT) activity increases in habitually active males. Spencer et al. (30) have observed a significant decrease in plasma Hx concentration after a 7-wk field hockey-specific training aimed at improving repeated-sprint ability in 18 elite female players. Stathis et al. (32) have demonstrated that inosine concentration, the precursor to Hx, as well as postexercise plasma Hx concentration are lower in the muscle after a 7-wk sprint training.
The aforementioned studies on training effects encompass only a small part of the training cycle, that is, in reality, a long period (at least 1 yr) divided into subphases aimed at specific goals. Furthermore, research is usually based on experimental procedures with nonsport subjects. Recently, Zieliński et al. (40) have demonstrated that resting and postexercise plasma concentrations of xanthine (X) and Hx and erythrocyte HGPRT activity change significantly in competitive long-distance runners during a 1-yr training cycle. As of yet, the changes in purine metabolism after a long-term regular exercise in competitive athletes or other active individuals remain a relatively poorly explored area.
An important issue is the measurement of training loads that are direct stimuli to metabolic changes. Hence, quantitative and qualitative data should be precise and reflect the energetic level of each exercise. In some situations, it is impossible to control training loads the athletes are exposed to, e.g., during team games where exercise stimuli of each subject cannot be controlled because of the differences in positional roles and unexpected variations in game intensity and time (30). This generates the necessity of approximation and does not allow calculating individual loads. A need to use a more precise method for monitoring and recording training loads of each athlete is arising. Moreover, athletes should use loads from the whole spectrum of energy sources for muscle work in their training, from very light exercise to maximum intensity, to determine the effect of exercise intensity on metabolic changes. This is possible in subjects practicing competitive running.
It is stressed that muscle data are a better source of information on purine exercise metabolism than blood samples, but in the face of the impossibility of muscle biopsy, plasma or erythrocyte samples are of great value. For example, red blood cells are relatively easily available, have a simple structure, and synthesize purines only in reutilization reactions; thus, they seem to be a model object in studies on intracellular purine metabolism or markers of training effect.
The purpose of this longitudinal study was to assess the effect of changes in training load intensity in a 1-yr cycle on blood concentration or activity of substances related to purine metabolism in middle-distance runners. A long duration of the cycle allows also observing the effect of detraining. We hypothesize that changes toward a high-intensity training load bring about pre- and postexercise (i) decrease in plasma Hx concentration, (ii) increase in red blood cell HGPRT activity in the competition period, and (iii) reverse changes in the transition period.
Eleven male middle-distance runners, specializing in 800 and 1500 m, competing at the national level, practicing competitive sport for 8.5 ± 1.3 yr, and with a mean age of 22.3 ± 0.7 yr (range = 20-27 yr), body mass of 68.3 ± 5.8 kg, body height of 180 ± 3.6 cm, maximal oxygen consumption (V˙O2max) of 60.1 ± 2.0 mL·kg−1·min−1, maximum HR of 192 ± 3 beats·min−1, and average levels of hemoglobin (Hb) of 15.5 ± 1.2 g·dL−1 at rest and 15.7 ± 1.2 g·dL−1 after exercise at the beginning of the training cycle (October), participated in the study. The control group consisted of 11 healthy men without any prior and current competitive sport experience. At the beginning of the study, their mean age was 24.1 ± 1.9 yr (range = 21-26 yr), body mass was 79.5 ± 3.5 kg, body height was 184 ± 2.9 cm, V˙O2max was 48.4 ± 3.2 mL·kg−1·min−1, maximum HR was 194 ± 4 beats·min−1, and average levels of Hb were 14.8 ± 1.2 g·dL−1 at rest and 15.2 ± 0.4 g·dL−1 after exercise. Controls were not specifically trained. They recreationally practiced typical forms of physical activity (e.g., jogging, swimming, team games) in their leisure time, and they did not exceed the World Health Organization's recommendations, i.e., about 150 min of moderate-intensity physical activity thorough the week (38). The aim of the research and testing methodology was explained to both athletes and controls who gave their informed consent before their inclusion in the study. The project had been approved by the Ethics Committee at the Karol Marcinkowski Medical University in Poznań and performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki.
General study design.
Several physiological and biochemical variables were measured four times, in four characteristic training subphases of an annual training cycle in both athletes and the control group, except for the last examination when the control data were not obtained because of treadmill failure. Biochemical parameters were measured at rest as well as after exercise. Performance characteristics were monitored during exercise. An incremental running treadmill test until volitional exhaustion, as described below, was used to assess the changes in postexercise values between training subphases. In athletes, the changes in exercise loads between training subphases were precisely monitored to show their relation to metabolic changes. In control subjects, the level of physical activity remained unchanged during the whole study.
The study procedure was adapted to the 1-yr training cycle of examined runners. It included three main phases: the preparatory, competitive, and transition phases (6). A training cycle with two competitive phases was used. The preparatory phase included two general subphases alternating with two specific subphases, which made it possible to obtain the first peak of athletic condition before indoor contests in the winter season and the second peak for outdoor contests in the summer season (Fig. 1).
FIGURE 1-Consecutive...Image Tools
The aim of the first general subphase (3 months) was the development of general endurance on the basis of aerobic training, the improvement of running technique, and the progress in general fitness. The first specific subphase (2 months) enabled athletes to develop specific endurance and specific physical fitness with anaerobic interval and speed runs. At the end of this subphase, athletes competed in the 5000 m at the Polish Indoor Athletics Championships. However, indoor competition was merely a kind of test because their best distances (800 and 1500 m) were much shorter.
Afterward, general (2 months) and specific (1 month) subphases were repeated with more intense training than before to prepare athletes for outdoor competition. The main competitive phase was characterized by decreasing training volume and increasing training intensity. Runners competed in their specialized and related distances peaking their athletic condition. This phase lasted 3 months and was divided into three subphases: (i) first competitive subphase (decreased training volume, competition), (ii) camp subphase (preparation for the second part of the season), and (iii) second competitive subphase (competition in specialized and related distances).
During a 1-month transition phase, athletes had no training sessions in the first 2 wk. Physical and psychological regeneration and recovery from injuries were the training aim. In the next 2 wk, training loads were small, and athletes played team games, swam, and did activity forms other than typical endurance running.
An exercise test was made at the beginning of the 1-yr cycle to measure ventilatory threshold (VT) and HR corresponding to VT of each athlete. On this basis, training loads were planned individually. The same procedure was repeated in successive examinations to update training parameters. Every exercise was assigned to one of five energetic zones that corresponded with estimates of energy sources for ATP resynthesis (6): Z1 (aerobic compensation (low intensity, HR ≍ 130-150 beats·min−1)), Z2 (aerobic threshold (medium intensity, HR ≍ 150-160 beats·min−1)), Z3 (anaerobic threshold (high intensity, HR ≍ 160-170 beats·min−1)), Z4 (V˙O2max zone (very high intensity, HR ≍ 170-180 beats·min−1)), and Z5 (lactic acid (LA) tolerance training (maximum intensity, HR > 180 beats·min−1)). HR was recorded during each training session (every 5 s) with the Polar Accurex Plus HR monitor (Polar Electro, Kempele, Finland). Training loads were expressed as the net time (h:min) an athlete spent in each energetic zone defined by the aforementioned HR ranges. The times were counted up and presented as absolute values for each energetic zone as well as a percentage share of each zone within the total training time in each training phase.
Four consecutive examinations had been planned and performed in four characteristic points of the annual training cycle (Fig. 1): (a) the first examination in January, at the end of the first general subphase of the preparatory phase, 116 ± 6.6 training sessions from the beginning of the 1-yr training cycle and, in total, with a net training time of 189.3 ± 13.2 h; (b) the second examination in March, at the end of the first specific subphase of the preparatory phase, 105 ± 2.4 training sessions and, in total, with a net training time of 204.1 ± 7.7 h since the first examination; (c) the third examination in June, at the end of the second specific subphase of the preparatory phase, at the beginning of the competitive phase, 119 ± 5.7 training sessions and, in total, with a net training time of 108.2 ± 8.2 h since the second examination; and (d) the fourth examination in October, at the end of the transition phase, 116 ± 4.0 training sessions and, in total, with a net training time of 184.5 ± 11.5 h since the third examination.
Maximal oxygen uptake.
Subjects underwent an incremental running treadmill test (WOODWAY ES1; Waukesha, WI). The initial speed of the moving strip was 10 km·h−1. Subsequently, the speed was progressively increased by 2 km·h−1 every 3 min until volitional exhaustion. Respiratory parameters (V˙E, V˙O2, V˙CO2) were monitored continuously with the CPX-D computer system (Medical Graphics Corporation, St. Louis, MO). HR was recorded every 5 s with a Polar Accurex Plus device (Polar Electro). All tests were conducted in the laboratory of the Department of Physiology of the University School of Physical Education in Poznań, in the morning, 2 h after consuming a light breakfast (bread and butter, water, without coffee or tea).
Capillary blood samples were obtained from the fingertip at rest and 3 min after exercise. LA concentration was assayed enzymatically using a spectrophotometric Warburg method (9) that measured the increase in absorbance of NADH at a wavelength of 365 nm (Marcel Media spectrophotometer, Zielonka, Poland).
Hx, X, uric acid, and HGPRT.
To obtain plasma and red blood cells, venous blood samples (5 mL) were taken from an antecubital vein at rest, immediately before and 5 min after exercise. The plasma obtained was deproteinized with 1.2 mol·L−1 HClO4 and centrifuged. An acid supernatant was neutralized with 1 mol·L−1 K2CO3, centrifuged, and stored at −80°C before analysis. Blood cells were bathed three times in an isotonic salt solution (0.9% NaCl) then hemolyzed with a hypotonic solution of Tris buffer (hydroxymethylaminomethane), 10 mmol·L−1, pH 7.4. The prepared hemolysate was stored at −20°C before analysis for HGPRT activity.
Hx, X, and uric acid (UA) were assayed in a neutralized plasma extract using high-performance liquid chromatography according to the methodology of Wung and Howell (39) modified by Banaszak (2). A Hewlett-Packard 1050 apparatus with a UV detector (Ramsey, NJ) was used. Separation was achieved by a Hypersil ODS 100 mm × 4.6 mm × 5 μm column and 20 mm × 4 mm × 5 μm precolumn manufactured by Alltech (Deerfield, IL). The carrier phase was a buffer consisting of 1% methanol and 4% 100 mmol·L−1 KH2PO4 (potassium phosphate), pH 5.8. The flow rate was 1.0 mL·min−1. Substances were identified by comparing retention times with model UA, Hx, X, and IMP compounds at known standard concentrations. In this system, UA, Hx, and X were separated at retention times of 2, 3, and 4 min, respectively. The measurement was done at a wavelength of 254 nm for Hx and X and 280 nm for UA. The quantitative sample analysis was performed on the basis of a comparison of retention times and concentrations with standardized solutions.
The red blood cell HGPRT activity was measured with a method described by Stolk et al. (34), modified by Banaszak (2). The incubation buffer consisted of 50 mmol·L−1 Tris, pH 7.4; 10 mmol·L−1 phosphoribosyl pyrophosphate (PRPP); 7 mmol·L−1 NaF; and 5 mmol·L−1 MgCl2. The preincubation of hemolyzate (100 μL) and buffer lasted for 5 min in a 37°C water bath. The incubation started after addition of 100 μL of a 2.0 mmol·L−1 Hx solution into a preincubation mixture to initiate the enzymatic reaction. Immediately after Hx was added, 100 μL of the incubation mixture was taken and added to 100 μL of 1.2 mol·L−1 HClO4 (perchloric acid). This sample served as a "zero time" sample. The incubation was stopped after 15 min by renewed addition of 100 μL of mixture to 1.2 mol·L−1 HClO4. Acid extracts were neutralized with 1 mol·L−1 K2CO3 and then used for HGPRT activity measurement using the high-performance liquid chromatography method. The buffer used as a carrier phase consisted of 100 mmol·L−1 KH2PO4 with the addition of TBAS (tetrabutylammonium sulfate), a final concentration 5 mmol·L−1, and pH 3.1. Separation was conducted at a flow rate of 1.2 mL·min−1. The mobile phase consisted of 15% methanol and 50% buffer, pH 3.1. A Hypersil ODS 150 mm × 4.6 mm × 5 μm column and 20 mm × 4 mm × 5 μm precolumn manufactured by Alltech (Deerfield) were used. The separation time was about 2.0 min for Hx and 5.0 min for IMP. The quantitative sample analysis was performed on the basis of a comparison of retention times with model Hx and IMP solutions at a wavelength of 254 nm. HGPRT activity was expressed as the amount of produced IMP (nm IMP·mg−1 Hb·h−1). The blood concentration of Hb was measured by a cobas b121 apparatus (Roche, Mannheim, Germany).
All values were presented as mean ± SD. A multiple ANOVA/multivariate ANOVA (MANOVA) for repeated measures was used to evaluate the significance of changes of variables. In athletes, the statistical power and effect size of ANOVA/MANOVA at α = 0.05 exceeded 0.80 and 0.14, respectively, in the majority of variables, except for HR values (0.20-0.30), maximum distance (Distmax, 0.20), and Hb levels (0.19-0.31). In control subjects, the values were lower. Statistical power ranged from 0.12 to 0.67, and the effect size was between 0.06 and 0.29 (medium and large effects). The only exception was Distmax with a statistical power of 0.86 and an effect size of 0.40. The Scheffé post hoc test was performed to assess the significance of differences between consecutive examinations. A t-test procedure was used to compare the differences between pre- and postexercise values in each training subphase. All calculations were made using STATISTICA 9.0 software (StatSoft, Inc., Tulsa, OK).
Athletes were shorter, weighed less, and had a lower body mass index (BMI) than control subjects. Body mass, body height, and BMI did not change significantly between examinations in both runners and controls. BMI value was maintained in a normal range (18.5-25.0 kg·m−2) in both groups (Table 1).
In athletes, the number of training sessions was noticeably lower in the second (105 ± 2) examination compared with the first (116 ± 7), third (119 ± 6), and fourth (116 ± 4; ANOVA/MANOVA: F = 12.2, P < 0.001) examinations, because of a shorter duration of the first specific subphase (Fig. 1). In the general preparation, five exercise zones were used in the following proportion: 74.4% in Z1, 21.1% in Z2, 2.9% in Z3, 0.9% in Z4, and 0.7% in Z5. The training was based mainly on aerobic zones Z1 and Z2 that made up 95.5% of total training time. The whole contribution of anaerobic training in Z3-Z5 to the total load was 4.5%. In the specific preparation, the exercise zones' proportion was 70.7%:18.8%:8.4%:1.1%:1.0%, respectively, and was similar to that in the previous subphase. Aerobic zones Z1 and Z2 were predominant (89.5%), and anaerobic zones Z4 and Z5 reached 2.1% of the total time. The contribution of Z3 and Z5 increased significantly 3.1-fold (+210.1%) and 1.4-fold (+39.7%), respectively, compared with the first examination. At the start of the competition phase, the proportion changed rapidly and was 46.1%:28.3%:17.4%:5.0%:3.2%, and in the fourth examination, it was 58.0%:27.3%:11.8%:1.8%:1.1%, respectively. ANOVA/MANOVA revealed significant changes in all energetic zones between four examinations (F = 41.7-271.3, P < 0.001). The most dramatic changes occurred between the specific and competition phases. In the competition period, training times in Z1 and Z2 decreased by 94.26 h (from 144.2 to 49.9 h, 2.89-fold, −65.4%) and 7.92 h (from 38.6 to 30.6 h, 1.26-fold, −20.5%), respectively. At the same time, training loads in Z4 and Z5 increased by 3.06 h (from 2.31 h to 5.37 h, 2.32-fold, +132.5%) and 1.47 h (from 1.97 to 3.44 h, 1.75-fold, +74.6%), respectively. In the transition phase, training loads did not reach the level from specific preparation; however, training times in Z1 and Z2 increased compared with the competition phase by 57.09 h (to 107.0 h, 2.14-fold, +114.4%) and 19.81 h (to 50.5 h, 1.65-fold, +64.7%), respectively. Training times in Z4 and Z5 decreased by 2.08 h (to 3.3 h, 1.63-fold, −38.7%) and 1.41 h (to 2.0 h, 1.69-fold, −41.0%), respectively. Training time in Z3 changed significantly between general and specific preparation and increased by 11.69 h (from 5.5 to 17.1 h, 3.12-fold, +210.1%) (Figs. 2 and 3).
In runners, time of VT (tVT), oxygen uptake at VT (V˙O2VT), and V˙O2max decreased significantly by 178.7 s (1.46-fold, 31.3%), 4.2 mL·kg−1·min−1 (1.09-fold, 8.0%), and 3.5 mL·kg−1·min−1 (1.06-fold, 5.7%), respectively, in the transition phase, compared with the competition phase (Table 1). In other exercise parameters, i.e., HR at the time of the VT (HRVT), HRmax, and Distmax, significant changes were not observed between phases, although Distmax in the transition phase was 246-316 m (1.09- to 1.12-fold, 8.4%-10.5%) shorter than in previous examinations. In controls, a significant increase in Distmax (ANOVA/MANOVA: F = 6.7, P < 0.01) and HRVT (F = 4.2, P < 0.05) was observed. In general, athletes performed much better in the exercise test than controls in each training phase (longer tVT, higher V˙O2VT, longer Distmax, higher V˙O2max, P < 0.001). No differences between groups were noted in HRVT and HRmax.
The changes in pre- and postexercise LA levels were not significant during the training cycle in either athletes or controls (Table 1). LA differences between pre- and postexercise concentrations were significant in all examinations (P < 0.001) in both groups. The trend toward lower postexercise LA values from the general to the competition phase was visible in runners; however, it was without statistical significance. Postexercise LA concentration was lower in athletes than in control subjects (P < 0.001) in each comparison.
Although the ANOVA/MANOVA showed significant changes in plasma postexercise concentration of X between examinations (P < 0.05) in runners, it was not confirmed in post hoc tests (Table 1). X changes remained insignificant during the whole study period in athletes as well as in controls. Lower levels were always revealed in runners (P < 0.001-0.01). Postexercise X concentration was significantly higher in each examination in both groups (P < 0.001).
The preexercise UA level was stable during the whole study in both athletes and controls (Table 1). In runners, the postexercise UA concentration changed significantly (ANOVA/MANOVA: F = 4.4, P < 0.05). A significant increase by 54 μmol·L−1 (1.22-fold, +21.9%, P < 0.05) was revealed between the competition and transition phases. Pre- and postexercise UA differences were significant in athletes in each examination ranging from 49 to 104 μmol·L−1 (P < 0.001) as well as in the control group (P < 0.001). Both pre- and postexercise values were lower in runners (P < 0.001) every time.
In athletes, the preexercise Hx level was invariable during the 1-yr cycle and ranged between 2.9 and 3.7 μmol·L−1 (Fig. 4). The postexercise Hx concentration changed significantly (ANOVA/MANOVA: F = 27.5, P < 0.001). A significant decrease by 6.2 μmol·L−1 (from 16.1 to 9.9 μmol·L−1, 1.63-fold, −38.5%, P < 0.01) was revealed between the specific preparation and the competition phases, and a significant increase by 17.4 μmol·L−1 (to 27.3 μmol·L−1, 2.76-fold, +175.8%, P < 0.01) was revealed between the competition and transition phases. In contrast, both pre- and postexercise concentrations did not change in the control group in three consecutive examinations. Moreover, significant differences between runners and controls were revealed in the specific preparation and competition phases (P < 0.001). Pre- and postexercise Hx levels differed significantly in each examination in both groups (P < 0.001). In runners, the differences ranged between 7.0 μmol·L−1 in the third and 23.6 μmol·L−1 in the fourth examination (P < 0.01).
FIGURE 4-Plasma Hx c...Image Tools
Both pre- and postexercise erythrocyte HGPRT activity changed significantly during the 1-yr cycle in athletes (ANOVA/MANOVA: F = 9.4, P < 0.001 and F = 10.2, P < 0.001, respectively). A significant increase by 9.3 nmol·mg−1·h−1 (from 52.5 to 61.8 nmol·mg−1·h−1, 1.18-fold, +17.7%, P < 0.01) in preexercise activity and by 4.9 nmol·mg−1·h−1 (from 65.0 to 69.9 nmol·mg−1·h−1, 1.08-fold, +7.5%, P < 0.01) in postexercise activity was revealed between the general preparation and competition phases (Fig. 5). Pre- and postexercise erythrocyte HGPRT activity decreased considerably between the competition and transition phases by 10.6 (to 51.2) nmol·mg−1·h−1 and by 12.0 (to 57.9) nmol·mg−1·h−1, respectively (1.21-fold, −17.2% in both cases, P < 0.01). Pre- and postexercise HGPRT activity differences were significant in each examination and ranged from 6.7 nmol·mg−1·h−1 in the transition phase to 12.5 nmol·mg−1·h−1 in specific preparation (P < 0.01). In the control group, no significant changes in pre- and postexercise HGPRT activity were observed during the study. Runners had significantly higher resting and postexercise HGPRT activity compared with controls in the competition phase (P < 0.001).
FIGURE 5-Red blood c...Image Tools
We showed significant changes in plasma concentrations of purine derivatives (X, Hx, and UA) and erythrocyte HGPRT activity involved in their metabolism concurrently with changes in training load structure, monitored during a 1-yr cycle in competitive middle-distance runners. Purine metabolism has not yet been described in competitive athletes in a long-lasting training cycle, except for our previous attempt with long-distance runners (40). However, the effect of training loads was not analyzed there in detail. In this study, we reveal a cause-and-effect relationship, i.e., the increase in anaerobic exercise in the specific preparation phase and at the start of the competitive phase brings about the decrease in postexercise Hx and UA plasma concentrations and the increase in both pre- and postexercise HGPRT activity. The training cessation in the transition phase, in turn, leads to an opposite effect: an increase in Hx and UA plasma concentrations and a decrease in HGPRT activity. It should also be noted that the total percentage of anaerobic exercise (Z4 + Z5) in the competitive phase is very low (only 8.2% of the total time), but its character (high intensity) contributes to the aforementioned changes. In support of our findings, all the analyzed parameters of purine metabolism remained invariable in the control group during the study period. This seems to be a reliable evidence despite some study imperfections: treadmill problems and difficulties with matching athletes and controls by anthropometric characteristics. However, the constant level of physical activity and biochemical parameters in the control group allow us to expect that no changes would occur in the fourth examination. Body mass, height, and BMI were within the normal healthy range in both groups and probably did not affect the overall results of our research.
Some studies on sprint training have revealed the reduction in resting muscle ATP and/or adenine nucleotides' content after training (12,16,32), which indicates adaptation changes aimed at more economical energy sources management. We suppose that the adenine nucleotide content in our subjects at rest could be possibly lower after training in specific preparation and competition phases. This has an effect on the turnover of Hx that is one of links in adenine nucleotides' degradation chain. In line with our results, Stathis et al. (32) have reported that sprint training reduced both muscle and plasma Hx during recovery after sprint exercise. This may be an evidence that the reduced plasma Hx concentration results, inter alia, from reduced muscle Hx efflux into the blood.
Hx does not accumulate in plasma to a very high level because it is continuously processed. After release from muscle, it is reconverted to IMP through a salvage pathway by erythrocyte HGPRT. No Hx uptake has been measured in muscle after high-intensity exercise (11). This indicates that once in the plasma, Hx can no longer be a precursor to purine salvage by the muscle; however, purine salvage in erythrocyte still occurs. The liver extracts Hx from the blood, oxidizes it to urate, and releases UA into the blood (13,14).
A certain Hx loss and plasma Hx concentration change are connected with renal clearance. Hx is excreted with urine at rest (10). The clearance of Hx and its urinary excretion are considerably increased (even 20-fold) in the recovery phase after an intensive and longer exercise in nontrained healthy individuals (10,18) as well as in athletes (35). Thus, a postexercise increase in plasma Hx, like in our study, seems to occur despite increased Hx clearance. Also, the exercise training seems to affect Hx clearance. Urinary purine excretion in 24 h after a performance test is reduced after sprint training (31) and may be best explained by a decreased delivery of purine to the kidney due to lower plasma concentration. The clearance of Hx is a delayed echo of muscle and blood concentrations. To our knowledge, no studies have been published that would explain the effect of training on the mechanism responsible for removing Hx from blood via the kidney and gut.
As shown above, plasma Hx concentration during and after exercise is affected by several factors. The main of them are (i) muscle Hx production, directly proportional to exercise intensity; (ii) muscle Hx reconversion to IMP by muscle HGPRT activity; (iii) plasma Hx reconversion to IMP by erythrocyte HGPRT; (iv) extracting by the liver from blood; and (v) excretion. To sum up, after training, less Hx is produced in the muscle and released into the blood, more Hx is reconverted to IMP (increased HGPRT activity) in both muscle and plasma, and less Hx is excreted with urine. It seems that plasma Hx concentration may be considered as an indirect parameter of muscle metabolism. The posttraining decrease in plasma Hx provides indirect evidence that training reduces Hx production and its efflux from the muscle in the recovery (32). Attenuated plasma purine is a likely result of lower muscle purine base production and efflux into the plasma (31).
To our knowledge, HGPRT postexercise activity has not been studied as of yet. The values obtained in this study are very similar to our previous research (40) and comparable with those revealed by other authors in healthy nontrained controls at rest, where HGPRT activity ranged between 70 and 160 nmol·mg−1·h−1 (7,19,36). In a research of Stolk et al. (33), a tendency, although not significant, toward increasing activity of HGPRT with age has been revealed. This may explain the lower HGPRT activity in our athletes (range = 50-60 nmol·mg−1·h−1 at rest and 60-70 nmol·mg−1·h−1 after exercise). Probably, in young well-trained individuals in a good health status, HGPRT activity is lowered because of more efficient metabolic mechanisms.
The increase in postexercise HGPRT activity, revealed in our study, does not seem to be surprising. It is known that the rate of an enzymatic reaction depends on environment and is affected by pH, temperature, substrate concentration, enzyme concentration, the presence of inhibitors, changes in the structure of the protein part of the enzyme, etc. Berman et al. (3) have revealed that the uptake of Hx and accumulation of IMP markedly increase at acid pH, high external phosphate concentrations, and low PO2. These conditions accompany a high-intensity exercise. The pH decrease in red blood cells results in a decrease in 2,3-bisphosphoglycerate and adenosine diphosphate concentrations (allosteric inhibitors of PRPP synthetase activity) accompanied by an increase in intraerythrocyte inorganic phosphate (an activator of PRPP synthetase). Intensive exercise could favor increased synthesis of PRPP that is a cosubstrate in reactions catalyzed by adenine phosphoribosyltransferase and HGPRT. Thus, HGPRT activity should increase during and after exercise. We suppose that a similar process occurred in our subjects. In our study, however, HGPRT activity was measured in vitro in a standard reaction medium where pH, temperature, and other factors were controlled. Therefore, we assume that the increase in activity from before to after exercise resulted from a prior in vivo change to the structure of the enzyme.
Muscle HGPRT was not measured in our study. It is a limitation because it seems that HGPRT plays a different role in erythrocytes (they do not have a de novo capacity) compared with muscle (15). At rest, HGPRT is estimated to be responsible for the recovery of approximately 75% of the intramuscular Hx production (8). Hellsten-Westing et al. (16) have revealed an increased maximum muscle resting HGPRT activity after training, which may support the reduced Hx efflux into the blood (posttraining plasma Hx is reduced). In our study, we have shown that posttraining erythrocyte HGPRT activity increases, probably contributing to the reduction in plasma Hx. It seems that the increase in erythrocyte HGPRT activity could well be an indicator of metabolic stress in muscle and extracellular environment.
However, it is not known how erythrocyte purine salvage can affect or contribute to muscle metabolism. ATP cannot be resynthesized via the Hx-IMP-AMP pathway because a mature erythrocyte does not have enzymes transforming IMP into AMP (28). The problem needs further study on the link between erythrocyte and muscle purine metabolism.
We have found UA to be a nonsensible parameter to training load changes, despite a certain trend toward lower values in the competition phase. In support of our results, Lombardi et al. (20) have also noticed no significant changes in resting plasma UA during a 4-yr observation of top-level alpine skiers in different training phases. The authors conclude that this parameter is not useful for marking high physical demand or overtraining; however, its role as a powerful antioxidant is very important. UA in blood may be extracted by exercised muscle to replenish the muscle urate stores, used as a free radical scavenger, and oxidized to allantoin during exercise (13,14). It should be noticed that in our study, both pre- and postexercise UA concentrations were significantly lower in runners than in controls in each examination. Because UA is the end point of purine metabolism and can accumulate in the plasma, the differences in UA level seem to be an indirect evidence of between-group differences in Hx efflux from the muscle.
The usefulness of our findings consists, in our opinion, in the possibility to use purine derivatives, especially Hx concentration and HGPRT activity as a measure of training status or, in general, the adaptation of energetic processes in different training phases. It is particularly important in light of the fact that either resting or postexercise LA concentration does not change along with training phases in our study, i.e., LA is of limited diagnostic value in competitive athletes. Also V˙O2max has limitations because information about adaptation to exercise in anaerobic zones in competitive athletes is needed. V˙O2max becomes a less sensitive predictor of performance when its values are in a high range in runners (22). Purine metabolism seems to be more sensitive to changes in training status. It provides a coach or an athlete with data related to anaerobic abilities that determine sport performance in elite runners.
From the practical point of view, a field sampling would be favorable to provide immediately an athlete/coach with useful information. Although the biochemical analysis we have done is currently not possible in the sports field, the technological development could make possible such analyses in the future thanks to portable devices (like in the case of LA, creatine kinase, or UA), supposing that analyzed parameters would be recognized as valuable and widely accepted by researchers, physicians, and coaches. In that case, an instant exercise modification in one session would be possible depending on metabolic response.
The potential limitation of our study is a single blood sampling point at 5 min of recovery. Earlier studies revealed that Hx concentration reaches maximum value after 10-20 min (10,25,37), and UA concentration, even later (31,32). Sahlin et al. (26) have reported no significant changes after 5 min of recovery in plasma Hx concentration during a moderate-intensity exercise. It seems that further postexercise samples during 15-20 min would have been optimal. However, data obtained after ≥5 min of recovery may be of greater importance in the context of sport training. Such a procedure allows assessing differences in metabolic response to exercise in athletes specializing in different sports (5), inter alia, in short-, middle-, and long-distance runners (4), and may serve as an indicator of exercise intensity in athletes (23). A serious limitation of our study is the impossibility of a muscle biopsy that would provide more information. This procedure is forbidden in Poland for purposes other than strictly medical. Moreover, competitive athletes rarely consent to muscle biopsy.
The presented study has some advantages. First of all, a control group was included, whereas other studies on the effect of training on purine metabolism did not use such a design (16,30,32). Besides, mainly habitually active subjects were examined so far (15,16,32) and not competitive or elite athletes. Second, the monitoring of training loads in a 1-yr cycle made it possible to follow long-term adaptation changes in purine metabolism in competitive athletes, which was not done so far. In a known study, the duration of the training cycle was 6-7 wk, and the effect of training loads was not analyzed there in detail (30). Until now, there were only two studies that encompassed cycles of longer duration: our article on long-distance runners (40) and the recent study of Lombardi et al. (20) on alpine skiers embracing a 4-yr period. The second one, however, analyzed only resting UA concentration. Third, our group was very homogenous and included exclusively competitive athletes on the national level with a relatively long sport history. Their training loads were planned and structured very precisely, which enabled us exact measurement of training loads in all energetic zones, especially the share of anaerobic exercise within the whole training load. Thus, one may exclude any spontaneous "disruptions" in the adaptation process. Fourth, middle-distance runners used a very wide range of training loads, from very mild (aerobic compensation) to very intensive (LA tolerance), which gave us a good picture of the role of each specific exercise type. Lastly, consecutive examination times were carried out on turning points in the training cycle, showing both training and detraining effects.
The increase in anaerobic training load during the specific preparation phase of a 1-yr training cycle in middle-distance competitive runners resulted in (i) a significant decrease in postexercise plasma Hx concentration and (ii) a significant increase in both pre- and postexercise erythrocyte HGPRT activity. The effect was noticeable despite a very short total duration of anaerobic training loads. Elevated preexercise HGPRT activity in the competition phase suggests adaptation changes consisting in a "permanent readiness" for purine salvage. Moreover, the detraining in the transition phase was the cause of reverse adaptation changes. Plasma Hx concentration and erythrocyte HGPRT activity may be considered as useful parameters, sensitive to metabolic adaptation to anaerobic exercise in advanced competitive athletes.
The authors thank the athletes for their full cooperation.
This work was funded by the Polish Ministry of Science and Higher Education from financial resources destined for scientific activity in the year 2010-2011 (application and grant N N404 191536).
The results of the present study do not constitute endorsement of the product by the authors or by the American College of Sports Medicine.
1. Baldwin J, Snow RJ, Gibala MJ, Garnham A, Howarth K, Febbraio MA. Glycogen availability does not affect the TCA cycle or TAN pools during prolonged, fatiguing exercise. J Appl Physiol
2. Banaszak F. The Metabolism of Purine and Pyrimidine Nucleotides in Essential Hypertension. The Assessment of Influence of Antihypertensive Drugs
. Poznań (Poland): University School of Physical Education; 1999. p. 133. Polish.
3. Berman PA, Black DA, Human L, Harley EH. Oxypurine cycle in human erythrocytes regulated by pH, inorganic phosphate, and oxygen. J Clin Invest
4. Bhattacharya AK, Panda PK, Das Gupta PK, De AK. Pattern of venous lactate and pyruvate after submaximal exercise in athletes training in different disciplines. Int J Sports Med
5. Bianchi GP, Grossi G, Bargossi AM, Fiorella PL, Marchesini G. Can oxypurines plasma levels classify the type of physical exercise? Sports Med Phys Fitness
6. Bompa T. Periodization: Theory and Methodology of Training
. Champaign (IL): Human Kinetics; 1999. p. 391.
7. Chen YC, Wang PW, Pan TL, Wallace CG, Chen CJ. Proteomic analysis of Down's syndrome patients with gout. Clin Chim Acta
8. Edwards NL, Recker D, Fox IH. Overproduction of uric acid in hypoxanthine-guanine phosphoribosyltransferase deficiency. Contribution by impaired purine salvage. J Clin Invest
9. Gutmann J, Wahlenfeld AW. L−/± lactate determination with lactate dehydrogenase and NAD. In: Bergmayer HU, editor. Methods of Enzymatic Analysis
. New York (NY): Academic Press; 1974. p. 1586-7.
10. Harkness RA, Simmonds RJ, Coade SB. Purine transport and metabolism in man: the effect of exercise on concentrations of purine bases, nucleosides and nucleotides in plasma urine, leucocytes and erythrocytes. Clin Sci (Lond)
11. Hellsten Y, Sjödin B, Richter EA, Bangsbo J. Urate uptake and lowered ATP levels in human muscle after high-intensity intermittent exercise. Am J Physiol
. 1998;274(4 Pt 1):E600-6.
12. Hellsten Y, Skadhauge L, Bangsbo J. Effect of ribose supplementation on resynthesis of adenine nucleotides after intense intermittent training in humans. Am J Physiol Regul Integr Comp Physiol
13. Hellsten Y, Svensson M, Sjödin B, et al. Allantoin formation and urate and glutathione exchange in human muscle during submaximal exercise. Free Radic Biol Med
14. Hellsten Y, Tullson PC, Richter EA, Bangsbo J. Oxidation of urate in human skeletal muscle during exercise. Free Radic Biol Med
15. Hellsten-Westing Y, Balsom PD, Norman B, Sjödin B. The effect of high-intensity training on purine metabolism in man. Acta Physiol Scand
16. Hellsten-Westing Y, Norman B, Balsom PD, Sjödin B. Decreased resting levels of adenine nucleotides in human skeletal muscle after high-intensity training. J Appl Physiol
17. Hellsten-Westing Y, Sollevi A, Sjödin B. Plasma accumulation of hypoxanthine, uric acid and creatine kinase following exhausting runs of differing durations in man. Eur J Appl Physiol Occup Physiol
18. Kaya M, Moriwaki Y, Ka T, et al. Plasma concentrations and urinary excretion of purine bases (uric acid, hypoxanthine, and xanthine) and oxypurinol after rigorous exercise. Metabolism
19. Laróvere LE, Romero N, Fairbanks LD, et al. A novel missense mutation, c.584A > C (Y195S), in two unrelated Argentine patients with hypoxanthine-guanine phosphoribosyl-transferase deficiency, neurological variant. Mol Genet Metab
20. Lombardi G, Colombini A, Ricci C, Freschi M, Lippi G, Banfi G. Serum uric acid in top-level alpine skiers over four consecutive competitive seasons. Clin Chim Acta
21. Löwenstein JM. Ammonia production in muscle and other tissues: the purine nucleotide cycle. Physiol Rev
22. Prommer N, Thoma S, Quecke L, et al. Total hemoglobin mass and blood volume of elite Kenyan runners. Med Sci Sport Exerc
23. Rychlewski T, Banaszak F, Szczęśniak Ł, Konys L, Jastrzębski A. Plasma hypoxanthine as an indicator of exercise intensity. Sportonomics.
24. Sahlin K, Broberg S. Adenine nucleotide depletion in human muscle during exercise: causality and significance of AMP deamination. Int J Sports Med
. 1990;11(2 suppl):S62-7.
25. Sahlin K, Ekberg K, Cizinsky S. Changes in plasma hypoxanthine and free radical markers during exercise in man. Acta Physiol Scand
26. Sahlin K, Tonkonogi M, Söderlund K. Plasma hypoxanthine and ammonia in humans during prolonged exercise. Eur J Appl Physiol Occup Physiol
27. Sjödin B, Hellsten Westing Y. Changes in plasma concentration of hypoxanthine and uric acid in man with short-distance running at various intensities. Int J Sports Med
28. Smoleński RT, Fabianowska-Majewska K, Montero C, et al. A novel route of ATP synthesis. Biochem Pharmacol
29. Snow RJ, Carey MF, Stathis CG, Febbraio MA, Hargreaves M. Effect of carbohydrate ingestion on ammonia metabolism during exercise in humans. J Appl Physiol
30. Spencer M, Bishop D, Lawrence S. Longitudinal assessment of the effects of field hockey training on repeated sprint ability. J Sci Med Sport
31. Stathis CG, Carey MF, Hayes A, Garnham AP, Snow RJ. Sprint training reduces urinary purine loss following intense exercise in humans. App Physiol Nutr Metab
32. Stathis CG, Febbraio MA, Carey MF, Snow RJ. Influence of sprint training on human skeletal muscle purine nucleotide metabolism. J Appl Physiol
33. Stolk JN, Boerbooms AM, De Abreu RA, et al. Purine enzyme activities in recent onset rheumatoid arthritis: are there differences between patients and healthy controls? Ann Rheum Dis
34. Stolk JN, De Abreu RA, Boerbooms AM, et al. Purine enzyme activities in peripheral blood mononuclear cells: comparison of a new non-radiochemical high-performance liquid chromatography procedure and a radiochemical thin-layer chromatography procedure. J Chromatogr B Biomed Appl
35. Sutton JR, Toews CJ, Ward GR, Fox IH. Purine metabolism during strenuous muscular exercise in man. Metabolism
36. van Dael CM, Pierik LJ, Reijngoud DJ, Niezen-Koning KE, van Diggelen OP, van Spronsen FJ. Partial hypoxanthine-guanine phosphoribosyltransferase deficiency without elevated urinary hypoxanthine excretion. Mol Genet Metab
37. Westing YH, Ekblom B, Sjödin B. The metabolic relation between hypoxanthine and uric acid in man following maximal short-distance running. Acta Physiol Scand
39. Wung WE, Howell SB. Simultaneous liquid chromatography of 5-fluorouracil, uridine, hypoxanthine, xanthine, uric acid, allopurinol and oxipurinol in plasma. Clin Chem
40. Zieliński J, Rychlewski T, Kusy K, Domaszewska K, Laurentowska M. The effect of endurance training on changes in purine metabolism: a longitudinal study of competitive long-distance runners. Eur J Appl Physiol