The ability to accurately quantify the physiological impact of an exercise session on the human body is crucial for understanding recovery needs and for allowing adequate rest before a second bout of exercise. This is an essential consideration when building training programs because it can allow coaches to more accurately develop a program that stresses the body and also allows adequate recovery time, limiting the potential for overtraining while maximizing the intensity of the workout to achieve meaningful performance improvements. The current understanding of exercise recovery in terms of biomarkers is limited. Thus, functional tests that evaluate strength (36), peak power output, and fatigue (9) remain the primary tools to assess recovery, despite the time requirements needed to observe noticeable alterations. Alternatively, the use of blood biomarkers offers a faster and potentially more accurate method for evaluating muscle damage and inflammation caused by an exercise session, which may reflect the relative state of recovery. Despite the high accuracy of these markers, there is still no consensus about their time course and the magnitude of their appearance and clearance from the blood after various types/intensities of exercise (5–7).
More recently, biomarkers of muscle damage and inflammation (5) have been more commonly used as measures of exertion because they may present an indication of exercise stress independent of factors that may confound the results of strictly functional or subjective measures. Many studies have assessed the appearance of muscle proteins (including the muscle-specific enzymes lactate dehydrogenase [LDH], aspartate aminotransferase, carbonic anhydrase isoenzyme II, and creatine kinase [CK]) in the blood after exercise to provide indirect evidence of muscle damage. Although all these proteins have been shown to be elevated after damage-inducing exercise, CK is the most commonly used marker, probably because it offers the response of the greatest magnitude compared with other muscle-specific enzymes and because it is relatively cost effective to measure.
Muscle damage is associated with an inflammatory response; it initiates a rapid and sequential invasion of muscle fibers by inflammatory cell populations that may persist for days or weeks. These inflammatory cells and signaling molecules produced by inflammatory cells, including reactive oxygen species (ROS) and cytokines, are thought to mediate the repair process that occurs during recovery from high-intensity or damaging exercise. Thus, the inflammatory response induced by muscle damage may be a functionally beneficial response (35).
For the purpose of identifying biomarkers to monitor exercise recovery status, we assumed that inflammation is a fundamental part of muscle repair (35). Therefore, we hypothesized that the appearance of leukocyte subpopulations and cytokines in the blood stream could serve as biomarkers of an individual's recovery state. There are specific temporal patterns for specific subpopulations of leukocytes involved in the recovery process: neutrophils migrate most rapidly, and lymphocytes migrate toward the end of the recovery period. Hence, the neutrophil/lymphocyte ratio (NLR) can be measured easily from whole blood and can be used as an indication of the magnitude of systemic inflammation and the severity of muscle damage incurred by a given bout of exercise (39).
Although the inflammatory response is necessary for muscle repair, it also has deleterious effects on exercise performance because of the increased production of ROS (29), which contribute to oxidative stress and muscle fatigue. The relationship between oxidative stress and exercise has been the focus of many research studies over the past decade. Despite the initial view that ROS could potentially damage cells, it now seems possible that these substances have important roles in the regulation of cell signaling (31), although their role in muscle adaptation remains controversial (29).
Characterizing the response patterns of the biomarkers of muscle damage and inflammation mentioned above and understanding the effects of ROS production and oxidative stress among athletes are fundamental to our understanding of cellular processes of recovery from exercise. To this end, we used combined training (CT) in lieu of aerobic or anaerobic training alone. Combined training is commonly used in conditioning for a wide variety of athletes because it imposes demands on multiple energy systems to generate adenosine triphosphate for exercise performance (38). Because these biomarkers and ROS may be involved in signaling, they may act as markers of recovery status, and understanding their specific time courses during the exercise recovery period may help elucidate the cellular mechanisms involved in the athletic gains that accrue during the recovery period. With regard to their potential for signifying recovery status, a clear model of physiological recovery is needed to establish guidelines about the relative levels of biomarkers so that overtraining can be avoided.
Therefore, the purpose of this study was twofold: (a) to investigate the time-course response of markers of muscle damage and inflammation in the blood 3, 6, 12, 24, 48, and 72 hours after a CT exercise protocol, and (b) to establish the role of ROS production during high-intensity exercise in the development of oxidative damage in elite athletes.
Experimental Approach to the Problem
Biomarkers of muscle injury, inflammation, and oxidative stress are known to respond to high-intensity exercise. However, the time course and the magnitude of this response remain unclear because the response is affected by the intensity and the type of exercise and the physical condition of the athlete. The independent variable in this experiment was a single bout of high-intensity combined exercise performed by 1 group of amateur male cyclists. The dependent variables assessed in the subjects were blood markers of muscle damage, inflammation, and oxidative stress, which were measured immediately before and 3, 6, 12, 24, 48, and 72 hours after exercise.
Written informed consent was obtained from all the subjects. This study was approved by the ethics committee for human research of the Universidade Federal de Uberlândia and conformed to the requirements for conducting research with human subjects (Health National Council, Brazil, 1996). The authors confirm that this study complies with the American College of Sports Medicine regulations for the use of human subjects and informed consent.
Nineteen top-level amateur male cyclists (characteristics, mean ± SE: age, 28 ± 2.5 years; body mass, 81.3 ± 2.9 kg; height, 184.6 ± 2.5 cm; V[Combining Dot Above]O2peak, 61.2 ± 1.7 ml O2·kg−1·min−1; maximum heart rate (max), 178 ± 4.6 b·min−1) volunteered for this study. The subjects underwent pretesting in the laboratory and denied the use of any ergogenic aids.
Two weeks before the exercise protocol, V[Combining Dot Above]O2peak was established using a commercially available system (Fitmate, Cosmed, Italy). The HR was measured continuously with an HR monitor (Polar Electro Oy, Kempele, Finland), and blood samples (25 μl) were obtained from the earlobe at the end of each stage to determine the lactate threshold. The test began with a 50-W load, which was increased by 50 W every 2 minutes until exhaustion. The 1-repetition maximum (1RM) for a deep squat and bench press was used to determine the maximum muscle strength 1 week before the exercise protocol. The subjects warmed up with 2 sets of 10 repetitions of each exercise using light loads (20% of the expected 1RM as reported by the athlete) 5 minutes before the test to avoid injuries. Three minutes of rest was allowed between sets, and all the participants successfully completed the test within 3 attempts. Upper extremity strength was assessed as isometric handgrip strength using a Jamar Hydraulic Hand Dynamometer (Sammons Preston, Bolingbrook, IL, USA). The subjects were instructed to exert maximum effort with their dominant hand for 3 seconds during 2 trials, each separated by a 1-minute rest. The maximum force achieved was used for analysis.
The subjects refrained from exercise for 1 week before the exercise test and for 72 hours after the exercise protocol, when the postexercise blood samples were taken. The exercise protocol consisted of a strength workout of 6 sets of maximum repetitions of deep squats performed with 85% of their 1RM alternating with 6 sets of maximum repetitions of bench presses performed with 85% of their 1RM. The subjects were given 5 minutes of rest between sets. This strength workout was immediately followed by 1 hour of cycling at 85% of their V[Combining Dot Above]O2peak.
Blood Sample Collection, Handling, and Storage
We collected blood samples immediately before and 3, 6, 12, 24, 48, and 72 hours after the exercise protocol. The blood was collected via venipuncture by a certified phlebotomist into 10-ml of ethylenediaminetetraacetic acid (EDTA), sodium heparin, and serum separator vacuum tubes (Vacutainer). All serum samples were allowed to clot and were then separated into serum by centrifugation at 4° C for 15 minutes at 2,000g. After removal of the plasma and buffy coat layers, the erythrocytes were washed 3 times with 2 volumes of isotonic saline. Erythrocytes were lysed with cold distilled water. Blood serum or plasma was aliquoted and stored at −80° C for later analysis. All subject samples were analyzed in duplicate, and the results were averaged.
Hematological Parameters, Injury Markers, and White Cell Count
Biochemical analysis was performed using commercial kits in an automatic device (Autolab 18—Boehringer Mannheim) to assess CK, LDH, cardiac troponin T (cTnT), γ-glutamyltransferase (γGT), and C-reactive protein (CRP). Hematological analysis was performed immediately after collection by automated analysis (KX-21N, Sysmex) using blood collected into tubes containing EDTA. Total and differential white cell counts, and red blood cell and platelet counts, were determined.
The levels of interleukin-6 (IL-6), MCP-1, and tumor necrosis factor (TNF)-alpha in the serum were determined using an enzyme-linked immunosorbent assay (ELISA) with specific monoclonal antibody (MAb) pairs. Microplates (Nunc, Roskilde, Denmark) were sensitized overnight with purified antihuman IL-6 capture antibody, purified antihuman MCP-1 capture antibody, or purified antihuman TNF-alpha capture antibody. Nonspecific binding was prevented by incubating the plates with 2% bovine serum albumin (Sigma, St. Louis, MO, USA) in phosphate-buffered saline (PBS). The plates were incubated overnight with 100 μl of a 1:2 dilution of serum samples in PBS, 1% bovine serum albumin, and standard cytokines. The plates were then washed 4 times with 0.05% Tween in PBS and incubated with detection antibody biotin antihuman IL-6, MCP-1, or TNF-alpha for 2 hours. The plates were washed and incubated for 2 hours with the enzyme reagent streptavidin-horseradish peroxidase conjugate. Finally, the plates were washed 5 times and incubated with p-nitrophenyl phosphate (BD). The A 450 − A 630 was read in a microplate reader. The BD OptEIA ELISA sets were used for all analyses.
Oxidative Stress Parameters
We assayed erythrocytes for antioxidant enzyme activities and plasmatic total antioxidant status (TAS). Catalase (CAT) activity was assayed spectrophotometrically by monitoring hydrogen peroxide decomposition at 240 nm (1). Superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities and TAS were assessed using a Trolox equivalent antioxidant capacity commercial kit (Randox NX2332, Crumlin, United Kingdom).
The levels of lipid peroxidation products in plasma were measured by determining the levels of thiobarbituric acid-reacting substance (TBARS) with a commercially available kit (Cayman Chemical, Ann Arbor, MI, USA). Lipid peroxide concentrations were expressed in terms of the malonaldehyde concentration (micromolar). The levels of plasma protein-bound sulfhydryls (PBSH) were determined using 5,5-dithiobis(2-nitrobenzoic acid) as previously described by Faure and Lafond (12).
All data were normalized to preexercise values and are expressed as means ± SE. Statistical significance was determined using a 1-way analysis of variance followed by Tukey's post hoc test after the Kolmogorov-Smirnov test was carried out to assess the normality of the variable distribution. All tests were 2-tailed, and a p value ≤ 0.05 was considered statistically significant.
Nineteen subjects completed the protocol. Compared with the baseline values, there was no significant change in the hematological parameters in response to the high-intensity exercise protocol (Table 1). Therefore, any observed changes in the markers of muscle damage, inflammation, and oxidative stress cannot be attributed to changes in hemoconcentration.
Upper extremity strength dropped 14% (p < 0.02) 3-hour postexercise and returned to baseline values between 12 and 24 hours postexercise (Figure 4).
Both biomarkers of muscle damage were elevated compared with the preexercise values, but they did not follow the same temporal pattern. Creatine kinase was elevated twofold (p < 0.01) 3 hours postexercise, reaching a peak level of 3 times the baseline value (p < 0.01) at 12 hours. Creatine kinase remained elevated 24 hours postexercise and returned to baseline levels by 48 hours postexercise. Lactate dehydrogenase activity was elevated 25% (p < 0.02) at 3 hours and 56% (p < 0.02) at 6 hours postexercise and returned to baseline levels by 12 hours postexercise (Figure 1).
The markers of myocardial and hepatic damage, cTnT and γGT, respectively, remained unchanged throughout the duration of the recovery period at levels of 0.01 ± 0.1 ng·ml−1 and 20.5 ± 3.3 U·L−1, respectively.
Leukocyte levels were 50% higher (p < 0.05) 3 hours after exercise compared with preexercise values and remained elevated (p < 0.05) at 12 hours postexercise, returning to baseline values by 24 hours (Figure 2A).
To assess the extent of the influence of exercise on leukocytes, we performed a differential white blood cell count to establish relative subpopulations of leukocytes. There were no significant changes in monocytes in the postexercise period (Figure 2B). Neutrophils made the largest contribution to the leukocyte increase 3 hours after exercise, when they were 70% higher than the baseline value (p < 0.05), and they returned to baseline values after 6 hours (Figure 2C). Lymphocytes increased by up to 55% (p < 0.05) after 12 hours and returned to baseline levels within 24 hours (Figure 2D).
Proinflammatory and anti-inflammatory cytokines were measured to determine whether inflammatory cell signaling in response to exercise contributes to leukocyte trafficking. The MCP-1 increased 40% 6 hours postexercise and decreased 37% 72 hours postexercise (Figure 3A). Tumor necrosis factor-alpha was lower than the baseline level for the duration of the recovery period; it decreased exponentially to almost 0% at 72 hours postexercise (Figure 3B). The IL-6 and CRP levels remained unchanged for the duration of the monitored postexercise recovery period (Figures 3C, D).
The NLR was 60% higher than baseline levels 3 hours postexercise, returned to preexercise levels 6 hours postexercise, and then dropped by 36% compared with the baseline 24 hours after exercise. The NLR returned to baseline values within 48 hours postexercise (Figure 4).
Regarding antioxidant defenses, SOD, GSH-Px, and TAS levels remained unchanged across all time points. Only CAT activity changed in response to exercise, increasing 35% (p < 0.05) at 3 and 24 hours after exercise (Table 2). Compared with the baseline values, there were no significant changes in TBARS and PBSH levels (Table 2).
This study investigated the appearance and clearance of markers of muscle damage, inflammation, and oxidative stress in the blood after high-intensity CT. The exercise protocol was designed to simulate an athlete's typical training session, which combines endurance and strength training. Our protocol mimicked a typical training session because the majority of the current research in this field uses only real or simulated competition as the exercise stressor (5,20). Although understanding the response to competition is important for understanding recovery needs, the adaptations contributing to performance improvements occur during recovery from the training sessions that precede the competition. In addition, this study aimed to identify the biomarkers that could be easily measured and routinely used by elite athletes and coaches to assess exercise intensity and recovery status.
The CK level was highly elevated from 12 to 24 hours after exercise and returned to preexercise values within 48 hours. The pattern of this enzyme's response suggests that it may be an appropriate indicator of the intensity of an exercise performed 1 day before measurement. Lactate dehydrogenase displayed more rapid appearance and clearance rates than CK, with elevated values observed in the blood from 3 to 6 hours postexercise. Thus, LDH may be useful as a more immediate indicator of the intensity of a training session. The larger increase in CK compared with that of LDH suggests that CK may be a more appropriate biomarker for quantifying the intensity of a medium-intensity exercise session. However, the rapid clearance of both CK and LDH from the blood makes them poor choices for monitoring the intensity of a period of training >1 day (e.g., to avoid overreaching  and overtraining ).
In this study, the appearance and clearance rates of CK and LDH in the blood after exercise were faster than the rates typically described in the literature (6). Previous studies have reported appearance windows of 24–72 hours (7), and even though more recent publications have reported faster appearance kinetics (5), to our knowledge, elevated levels of both CK and LDH have never been demonstrated 3 hours after exercise.
Another novel aspect of this article is the use of cTnT as a cardiac muscle-specific marker. The absence of detectable levels of cTnT in the blood stream after exercise suggests that no significant myocardial damage (15) was caused by the high-intensity CT protocol. Taking the cTnT results together with the γGT (26), hematocrit, and platelet levels, the increases in the blood concentrations of CK and LDH were caused only by skeletal muscle damage and not by exercise-induced changes in hemoconcentration.
Leukocyte levels were elevated in the blood 3 hours after exercise and returned to preexercise levels within 24 hours. At 12 hours postexercise, the average leukocyte count was still 30% higher than the preexercise level; however, this change was not statistically significant.
Leukocyte trafficking can be attributed to the migration of 2 white blood cell subpopulations. Neutrophils displayed the most rapid response, appearing in the blood at 3 hours and disappearing from the blood by 24 hours postexercise. This observation is in accordance with the findings in the literature (4,13); neutrophils are important for the removal of cellular debris (18,35), but their long-term presence in the tissue may delay tissue repair because they may compound tissue damage by excessively generating ROS (25,33). Of the leukocyte subpopulations studied, lymphocytes displayed the slowest response to exercise stress. They were absent in the blood until 12 hours postexercise, at which point, they remained elevated for the duration of the recovery period.
The difference in the migration time of neutrophils and lymphocytes indicates different stages of muscle repair (35) and therefore can be used to monitor recovery status. The NLR (39) is a marker of systemic inflammatory response that indicates the mobilization of these 2 leukocyte subpopulations in a single marker that can easily be measured. The change in the NLR was inversely correlated with the supercompensation of antioxidants and with upper extremity strength in this experiment. Thus, NLR can be an alternative to physical tests that evaluate strength (17,36) as a tool to predict the end of the postexercise recovery period.
The main advantage of using NLR instead of functional tests is that it requires no exertion from the athlete and can be done in a relatively short time period. Conversely, functional tests such as 1RM or isokinetic dynamometry involve substantial physical exertion by the athlete, which, combined with the fatigue experienced during the recovery period, may prolong recovery or predispose the athlete to injury.
Because cytokines may mediate the immune response to exercise, measuring them facilitates a more thorough understanding of the postexercise immune response. The kinetic behavior of MCP-1 shows that the apparently steady blood level of monocytes is actually a dynamic equilibrium between bone marrow secretion and damaged tissue mobilization. The elevated levels of MCP-1 6 hours postexercise reflect the period when macrophages are required to aid in the repair of the damaged tissue (3,34). The immunosuppression observed at 72 hours postexercise, indicated by the depression of both MCP-1 and TNF-alpha in the blood, indicates that inflammation is no longer necessary at this time (21) and that muscle recovery may be complete.
Based on the combination of the MCP-1 and TNF-alpha results and the levels of inflammatory markers IL-6 (28) and CRP (16), we concluded that the high-intensity exercise protocol we used generated localized inflammation of skeletal muscle but not systemic inflammation.
We did not observe any significant changes in the levels of the antioxidant enzymes SOD, GSH-Px and CAT on the TAS or in the levels of the oxidative stress damage markers TBARS and PBSH. This result is in accordance with the hypothesis that the antioxidant enzymes are regulated by redox status and not by exercise itself (14). The exercise protocol used in this research did not generate oxidative stress, even though it has previously been stated that intense exercise is a powerful stimulator of ROS production (24). Because the subjects demonstrated high basal levels of antioxidant enzymes, which are commonly observed in athletes (10,11), it is possible that the increase in ROS production during exercise was not sufficient to alter the redox status enough to initiate the upregulation of these antioxidant enzymes.
Previous studies that used well-trained volunteers (22,30) produced similar results showing no oxidative stress after intense exercise, but these reports have been criticized (14) for the following 2 reasons: (a) the samples were acquired only immediately after exercise (2,32,37); and (b) no changes were observed in injury markers after the exercise protocol, suggesting that low-intensity exercise had been performed (23,30). Our results address both of these issues. The elevation of the CK and LDH levels suggests that the intensity of our exercise protocol was sufficiently high, and samples were acquired up to 72 hours after exercise. Thus, we may conclude that the lack of a change observed in oxidative stress was a result of the subjects' basal antioxidant status and not because of methodological limitations.
We used CT to simulate a typical training session for a high-level athlete. The CK and LDH responses in the blood occurred faster than previous studies have reported. The NLR assesses the mobilization of 2 leukocyte subpopulations in a single measure and may be used to indicate the relative postexercise recovery status of an individual. Further analysis of the immune response using serum cytokines indicated that the high-intensity exercise performed by highly trained athletes only generates inflammation localized to the skeletal muscle and does not appear to influence systemic inflammation.
The values of biomarkers after training vary drastically depending on the type and intensity of the exercise performed and on the physiological differences between athletes. The best way to use biomarkers to monitor athletes is to perform a screening test like the test we have performed in this experiment, using the type and intensity of exercise commonly practiced by the athletes. Consequently, the response of the selected biomarkers will be directly applicable to the individual athlete, potentially helping coaches to understand why some athletes respond differently to the same type of training. The use of biomarkers is not a substitute for performance tests, but the combination of biological indicators and performance tests offers a more thorough understanding of the physiological responses to exercise. Therefore, the use of biomarkers can improve coaches' abilities to assess the recovery period after an exercise session and to establish the intensity of subsequent training sessions in the most effective way.
This work was supported by grants from Fundação de Amparo a Pesquisa de Minas Gerais (PPSUS-FAPEMIG, EDT 3273/06). The authors would like to thank Dr. Marcelo Simão Ferreira and Dr. Enivaldo Donizete Tavares from the Hospital de Clínicas da Universidade Federal de Uberlândia.
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