Oxidative stress biomarkers responses to physical overtraining: Implications for diagnosis

Free Radical Biology & Medicine 43 (2007) 901 – 910 www.elsevier.com/locate/freeradbiomed

Original Contribution

Oxidative stress biomarkers responses to physical overtraining: Implications for diagnosis Konstantinos Margonis a , Ioannis G. Fatouros a,b,⁎, Athanasios Z. Jamurtas b,c , Michalis G. Nikolaidis b,c,d , Ioannis Douroudos a , Athanasios Chatzinikolaou a , Asimina Mitrakou e , George Mastorakos f , Ioannis Papassotiriou g , Kiriakos Taxildaris a , Dimitrios Kouretas d,⁎ a Department of Physical Education and Sports Science, Democritus University of Thrace, Komotini 69100, Greece Institute of Human Performance and Rehabilitation, Centre for Research and Technology -Thessaly, Trikala, 42100, Greece c Department of Physical Education and Sports Sciences, University of Thessaly, Trikala 42100, Greece d Department of Biochemistry and Biotechnology, University of Thessaly, 41221, Larissa, Greece e Department of Internal Medicine, Henry Dunant Hospital, Athens 11527, Greece Endocrine Unit, Second Department of Obstetrics and Gynecology, “Aretaieion” Hospital, Athens University Medical School, Athens 11526, Greece g Department of Clinical Bochemistry, “Aghia Sophia” Children’s Hospital, Athens 11527, Greece b

f

Received 30 January 2007; revised 7 May 2007; accepted 17 May 2007 Available online 23 May 2007

Abstract Overtraining syndrome is characterized by declining performance and transient inflammation following periods of severe training with major health implications for the athletes. Currently, there is no single diagnostic marker for overtraining. The present investigation examined the responses of oxidative stress biomarkers to a resistance training protocol of progressively increased and decreased volume/intensity. Twelve males (21.3 ± 2.3 years) participated in a 12-week resistance training consisting of five 3-week periods (T1, 2 tones/week; T2, 8 tones/week; T3, 14 tones/week; T4, 2 tones/week), followed by a 3-week period of complete rest. Blood/urine samples were collected at baseline and 96 h following the last training session of each period. Performance (strength, power, jumping ability) increased after T2 and declined thereafter, indicating an overtraining response. Overtraining (T3) induced sustained leukocytosis, an increase of urinary isoprostanes (7-fold), TBARS (56%), protein carbonyls (73%), catalase (96%), glutathione peroxidase, and oxidized glutathione (GSSG) (25%) and a decline of reduced glutathione (GSH) (31%), GSH/GSSG (56%), and total antioxidant capacity. Isoprostanes and GSH/GSSG were highly (r = 0.764–0.911) correlated with performance drop and training volume increase. In conclusion, overtraining induces a marked response of oxidative stress biomarkers which, in some cases, was proportional to training load, suggesting that they may serve as a tool for overtraining diagnosis. © 2007 Elsevier Inc. All rights reserved. Keywords: Overtraining; Resistance exercise; Antioxidant status; Oxidative stress biomarkers

Abbreviations: OTS, overtraining syndrome; RT, resistance training; ROS, reactive oxygen species; TBARS, thiobarbituric acid-reactive substances; F2-IsoP, isoprostanes; PC, protein carbonyls; CAT, catalase; TAC, total antioxidant capacity; GPX, glutathione peroxidase; GSH, reduced glutathione; GSSG; oxidized glutathione; 1RM, one repetition maximal; AP, average power output; DOMS, delayed onset of muscle soreness; KRM, knee joint range of motion. ⁎ Corresponding authors. I.G. Fatouros is to be contacted at Department of Physical Education and Sports Sciences, Ektenepol, Politechniou Str., Parodos 3, Bldg. 1., 69100 Komotini, Greece. Fax: +30 25310 39623. D. Kouretas, Department of Biochemistry and Biotechnology, University of Thessaly, 41221, Larissa, Greece. Fax: +30 2410 565290. E-mail addresses: [email protected] (I.G. Fatouros), [email protected] (D. Kouretas). 0891-5849/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.freeradbiomed.2007.05.022

Introduction Regular physical training is associated with a mild tissue trauma followed by recovery [1]. When adequate recovery is allowed, there is an adaptation and athletic performance improves, a process often called “adaptive microtrauma” [1]. However, when exercise volume and/or intensity are increased, usually abruptly, and the athlete is not sufficiently recovered, a mild trauma could develop into a more chronic, severe form of tissue trauma. Athletes often develop a transient inflammationlike reaction following very intense acute exercise [2] or a

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prolonged period of severe training which is often called “overtraining syndrome” (OTS) and is characterized by declining performance despite an extended rest period, accompanied by physiological, biochemical, immunological, and psychological symptoms [3,4]. Interestingly, b 0.1% of the general population [5] and 37% of a group of elite athletes from various sport disciplines have been reported to experience OTS at least once in their athletic career [6]. An overtrained athlete usually sustains a more diffuse, widespread, low-grade trauma that cannot be identified as an acute injury and resembles an overuse injury or a repetitivemotion injury resulting from high-volume training [3] and is accompanied by soreness, edema, performance deterioration, and protein release into plasma [7,8]. Recent work from our laboratory [8] demonstrates that overtraining induces a significant rise in inflammatory and apoptotic markers. Muscle microtrauma induces reductions in strength [8] and range of motion [9] due to swelling in the injured area as well as a local inflammatory response with activated circulating monocytes and systemic inflammation and possibly immunosuppression [10]. Overtraining-induced muscle damage is associated with an inflammatory response characterized by increased susceptibility to infections attributable to changes in the functional status of immune cells [2]. Intense physical exercise has been reported to generate reactive oxygen species (ROS), resulting in oxidative stress [11]. Furthermore, ROS have been linked to mechanisms related to postexercise inflammatory response and possibly with propagation of muscle damage [12]. An inflammatory response during the repair of overtraininginduced muscle damage promotes neutrophil and macrophage infiltration of muscles, most likely initiated by ROS [13,14]. Following exercise, neutrophil and macrophage counts are increased in muscle for several days [14,15]. Neutrophils and macrophages generate superoxide, which may be converted to hydrogen peroxide, which then reacts with superoxide in the presence of a transition metal to form hydroxyl radical [12]. However, information regarding ROS generation in OTS is scarce. Overtraining effects on oxidative stress markers have been examined by only one animal study [16] and currently there are no available data from human studies. Ogonovszky et al. [16] reported that although aerobic exercise overtraining induced an oxidative damage to nuclear DNA in rats, there were no signs of lipid peroxidation. However, the authors questioned whether an overtraining response was induced in that study. Moreover, no single reliable diagnostic marker of OTS is currently available apart from a declined performance. Oxidative stress biomarkers could be significant and complementary with other biochemical indices since several links exist between oxidative stress and OTS. This is the first human study that investigated the possible role of oxidative stress in overtraining response. We tested the hypothesis that exercise of progressively increased and decreased training volume and intensity, which potentially could lead to overtraining, may induce oxidative damage to lipids and proteins as evidenced by changes in indirect blood markers of oxidative stress.

Materials and methods Human subjects Twelve healthy, recreationally trained men (22.4 ± 2.1 years, 75.5 ± 6.9 kg, 1.78 ± 2.5 m, 11.9 ± 2.4% body fat, 49.4 ± 5.1 ml/ kg/min VO2max) volunteered to participate in the present study. A written informed consent was signed by all participants. Procedures were in accordance with the Helsinki Declaration for the Ethical Treatment of Human Subjects. Ethics approval was given by the institutional review board. Participants abstained from resistance training for at least 8 weeks prior to the study. Study design After an initial week of familiarization training, subjects participated in a 12-week resistance training (RT) regimen (7 resistance, multijoint exercises were selected to stress the entire musculature: bench press, squat, snatch, hang clean, dead lifts, barbell arm curls, and rowing) consisting of four 3-week training periods (T1, T2, T3, and T4). The first and fourth training periods (T1, T4) included low-volume training: two training days/week, two sets/exercise, 10–12 repetitions/set at 70% of their maximal strength (1 repetition maximum, 1RM). T2 included high-volume training: four training days/week, four sets/exercise, 6–10 repetitions/set at 75–85% 1RM. T3 included very-high volume training: six training days/week, six sets/exercise, and 1–6 repetitions/set at 85–100% of 1RM. Consecutive training periods were separated by a 4-day rest period. T4 was followed by a 3-week period of complete rest (R). The training and testing protocol is illustrated in Fig. 1. Subjects underwent performance (muscle strength, anaerobic capacity, and jumping ability) and muscle damage (delayed onset of muscle soreness [DOMS] and knee joint range of motion [KRM]) assessments as well as blood and urine sampling at baseline and at 96 h following the last training

Fig. 1. Training and testing protocol. B, baseline; T1–T4, the four training periods; R, rest period; F, familiarization period; S1–S5, five sampling points (96 h following the last exercise session of each training period).

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session of each period (in order to avoid the “last training bout effect” and determine changes that reflect chronic, and not acute, exercise-induced adaptation). Diet and training records In order to examine whether dietary changes influenced oxidative stress variables and antioxidant status outcomes, 5day diet recalls were completed before and during training. A trained dietician taught the subjects how to complete diet-recall questionnaires and determine food serving and sizes. Diet records were analyzed using the computerized nutritional analysis system Science Fit Diet 200A (Science Technologies, Athens, Greece) [8]. Training volumes were calculated with ScienceTech 140A (Science Technologies).

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were collected and stored at − 30°C until GSH and GSSG analysis. Another portion of blood (10 ml) was collected in plain tubes, left on ice for 20 min to clot, and then centrifuged at 1500g for 10 min at 4°C for serum separation. Serum was transferred in Eppendorf tubes and used for the determination of thiobarbituric acid-reactive substances (TBARS), protein carbonyls (PC), catalase, and total antioxidant capacity (TAC). Another portion of blood (1 ml) was collected in heparin-coated tubes for the determination of glutathione peroxidase activity (GPX). A blood aliquot (1 ml) was immediately mixed with EDTA to prevent clotting for hematology. Complete blood count was determined via matching duplicate counts using an automated hematology analyzer (Sysmex K-1000 autoanalyzer, TOA Electronics, Japan). Blood samples were stored in multiple aliquots at − 30°C and thawed only once before analysis.

Performance measurements Measurement of GSH and GSSG Maximal strength (1RM) was measured for all exercises as previously described [8]. Prior to maximal strength testing at baseline, subjects underwent a familiarization period in order to learn proper lifting techniques. The mean intraclass correlation coefficient estimated for test-retest trials within the same week was 0.95. Anaerobic capacity was determined with Wingate testing on a cycle ergometer (Monark, 834E, Sweden) as previously described [17]. Briefly, tension was applied and subjects pedaled as fast as they could against a flywheel resistance set at 0.075 kg/kg of body weight for 30 s and average power output (AP) was recorded. Jumping ability was measured by the stand and reach test as previously described [7]. The mean intraclass correlation coefficient estimated for test-retest trials within the same week was 0.92. Assessment of delayed onset of muscle soreness DOMS was determined by palpation of the muscle belly and the distal region of the vastus medialis, vastus lateralis, and rectus femoris in a seated position with the muscles relaxed. Perceived soreness was then rated on a scale ranging from 1 (normal) to 10 (very, very sore) as previously described [7] Knee joint range of motion (KRM) was measured as an index of muscle edema as previously described [8]. The coefficient of variation for test-retest trials for knee flexion/extension was 2.5%. Blood collection and handling Peripheral blood samples were drawn from an antecubital vein in a seated position at 7:00 a.m. after an overnight fast. Subjects abstained from alcohol and caffeine consumption for at least 24 h, and did not exercise for the last 96 h before testing. Immediately following blood sampling, 1 ml 5% trichloroacetic acid (TCA) was added to 1 ml whole blood collected in EDTA tubes. The samples were centrifuged at 4000g for 20 min at 4°C. The amount of 200 μl of the supernatant was dispensed in tubes and mixed with 60 μl 5% TCA. The samples were centrifuged again at 28,000g for 5 min at 4°C and the clear supernatants

GSH was assayed according to Reddy et al. [18]. Twenty microliters of whole blood treated with TCA was mixed with 660 μl 67 mM sodium-potassium phosphate (pH 8.0) and 330 μl 1 mM 5,5′-dithiobis-2-nitrobenzoate (DTNB). The samples were incubated in the dark at room temperature for 45 min and the absorbance was read at 412 nm. GSSG was assayed according to Tietze [19]. Two-hundred and sixty microliters whole blood treated with TCA was neutralized up to pH 7.0–7.5 with NaOH. Four microliters of 2-vinylpyridine was added and the samples were incubated for 2 h at room temperature. Five microliters of whole blood treated with TCA was mixed with 600 μl 143 mM sodium phosphate (6.3 mM EDTA, pH 7.5), 100 μl 3 mM NADPH, 100 μl 10 mM DTNB, and 194 μl distilled water. The samples were incubated for 10 min at room temperature. After addition of 1 μl glutathione reductase the change in absorbance at 412 nm was read for 3 min. Measurement of lipid peroxidation indices TBARS was assayed according to Keles et al. [20] Onehundred microliters of serum was mixed with 500 μl TCA 35% and 500 μl Tris-HCl (200 mM, pH 7.4) and incubated for 10 min at room temperature. One milliliter of 2 M Na2SO4 and 55 mM thiobarbituric acid solution was added and the samples were incubated at 95°C for 45 min. The samples cooled on ice for 5 min and vortexed after the addition of 1 ml TCA 70%. Finally, the samples were centrifuged at 15,000g for 3 min and the absorbance of the supernatant was read at 530 nm. Urinary isoprostanes were measured with a commercial EIA assay (Northwest Life Sciences Specialties, USA, NWK-ISOO2) as previously described [21]. The sensitivity of the 15-F2t-isoprostane assay was 12.3 pg/ml. Measurement of protein carbonyls PC were assayed according to Patsoukis et al. [22]. In 50 μl serum 50 μl 20% TCA was added, incubated in ice bath for

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and urine samples were collected on the same time and day. Five milliliters of urine aliquots was kept at − 75°C until analysis for free 15-isoprostane-F2t. Each assay was determined spectrophotometrically (Hitachi 2001 UV/VIS spectrophotometer, Hitachi Instruments Inc., USA) in triplicates (except for GPX and isoprostanes that were measured in duplicate). The interand intracoefficients of variation were 7.0 and 10.1% for catalase, 4.8 and 3.8% for GPX, 3.4 and 5.0% for TAC, 4.1 and 5.9% for GSH, 6.1 and 8.1% for GSSG, 4.7 and 7.4% for TBARS, 4.4 and 7.2% for protein carbonyls, and 3.5 and 7.5% for isoprostanes, respectively.

15 min, and centrifuged at 15,000g for 5 min at 4°C. The supernatant was discarded and 500 μl 10 mM 2,4-dinitrophenylhydrazine (in 2.5 N HCl) for the sample or 500 μl 2.5 N HCl for the blank was added in the pellet. The samples incubated in the dark at room temperature for 1 h with intermittent vortexing every 15 min and centrifuged at 15,000g for 5 min at 4°C. The supernatant was discarded, and 1 ml 10% TCA was added, vortexed, and centrifuged at 15,000g for 5 min at 4°C. The supernatant was discarded, and 1 ml ethanol-ethyl acetate (1:1 v/v) was added, vortexed, and centrifuged at 15,000g for 5 min at 4°C. The washing step was repeated two more times. The supernatant was discarded, and 1 ml 5 M urea (pH 2.3) was added, vortexed, and incubated at 37°C for 15 min. The samples were centrifuged at 15,000g for 3 min at 4°C and the absorbance was read at 375 nm.

Statistical analysis Data are presented as mean ± SE. The distribution of all dependent variables was examined by the Shapiro-Wilk test and was found not to differ significantly from normal. Data were analyzed through one-way ANOVA with repeated measurements. When a significant effect was found, post hoc was performed through the Bonferonni test. Additionally, Pearson product correlations were performed between the change of oxidative stress biomarkers following overtraining (T3 vs baseline) and: (a) the drop in each performance variable observed at overtraining (T2 vs T3), and (b) the magnitude of increase in exercise volume (tonnage lifted/week) during overtraining (T3 vs baseline). The level of statistical significance was set at α = 0.05. The SPSS version 13.0 was used for all analyses (SPSS Inc., USA).

Measurement of antioxidant enzymes Catalase activity was assayed according to Aebi [23]. In 20 μl serum, 2975 μl 67 mM sodium-potassium phosphate (pH 7.4) was added and the samples were incubated at 37°C for 10 min. Five microliters of 30% hydrogen peroxide was added in the samples and the change in absorbance was immediately read at 240 nm for 1.5 min. Whole-blood GPX activity was measured spectophotometricaly, at 37°C, using cumene hydroperoxide as the oxidant of glutathione (Ransel RS 505, Randox, Crumlin, UK). Measurement of total antioxidant capacity

Results TAC was assayed according to Janaszewska and Bartosz [24]. In 20 μl serum 480 μl 10 mM sodium-potassium phosphate (pH 7.4) and 500 μl 0.1 mM 2,2-diphenyl-1picrylhydrazyl were added and incubated in the dark for 30 min at room temperature. The samples were centrifuged for 3 min at 20,000g and the absorbance was read at 520 nm. Total protein in serum was assayed using a Bradford reagent. Each assay in whole-blood lysates, serum, and urine was performed on the same day to eliminate variation in assay conditions and within 1 month of the blood collection. Blood

Performance and muscle damage indices Training responses following each experimental period are displayed in Table 1. Training volume increased 4-fold in T2 and 7-fold in T3. Power clean 1RM and MP increased following T1 [6.6% (P b 0.000), and 2% (P = 0.032), respectively], T2 [18.4% (P = 0.000), 8.3% (P = 0.001), respectively], T3 [10.8% (P = 0.000), 4.8% (P = 0.001), respectively], and T4 [11.5% (P = 0.000), 4.7% (P = 0.004), respectively] compared to

Table 1 Training volume and performance changes at baseline (B), and following low- (T1 and T4), high- (T2), and very-high-volume (T3) resistance training as well as the recovery period (R)

Mean training volume (tonnage/week) 1 Maximal strength) (kg) 2 Jumping ability (cm) Anaerobic power (Watt/kg) DOMS Knee range of motion (degrees) 1 2 a b c d e

B

T1

T2

T3

T4

R

N/A 70.2 ± 10.4 40.6 ± 3.8 9.3 ± 0.7 0.0 ± 0.0 141.3 ± 7.7

2.1 ± 0.4 74.9 ± 9.5 a 41.0 ± 3.6 9.5 ± 0.7 a 0.5 ± 0.5 140.1 ± 8.9

7.6 ± 0.9 b, e 83.2 ± 8.6 a, b 42.6 ± 3.3 a, b 10.1 ± 1.1 a, b 2.3 ± 1.4 a, b 138.3 ± 6.4 a, b

14.2 ± 1.2 c, e 77.8 ± 9.6 a, b, c 38.5 ± 4.2 c 9.8 ± 0.9 a, b, c 7.2 ± 1.6 a, b, c, d, e 135.4 ± 9.6 a, b, c

1.8 ± 0.2 d 78.3 ± 8.8 a, b, c 40.0 ± 3.8 c 9.7 ± 0.8 a, b, c 3.8 ± 1.7 a, b, d 137.7 ± 10.2 a, b, d

N/A 73.9 ± 10.0 a, c, d, e 40.5 ± 3.6 c 9.5 ± 1.0 a, b, c, d, e 1.1 ± 0.4 e 140.2 ± 12.2 d, e

Mean number of tons lifted per week for all resistance exercises employed in the protocol. Mean maximal strength in one representative exercise (power clean). Significant difference with baseline (B). Significant difference with T1. Significant difference with T2. Significant difference with T3. Significant difference with T4.

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baseline while CMJ increased only following T2 (4.8%, P = 0.000). However, there was a marked decline of performance following T3 compared to T2 in all measures [− 6.4% (P = 0.024) for power clean 1RM, − 3.2% (P = 0.036) for MP, and −9.6% (P = 0.002) for CMJ] without recovering thereafter. DOMS and KJM increased following T2, T3, and T4 (P = 0.000) (with T3 inducing the greatest response) and declined thereafter. There were no differences in diet composition across time (data not shown). Leukocytes Training increased leukocyte count (Fig. 2) following T2 (18.7%) and T3 (43.7%) and T4 (15.6%), indicating that leukocytosis persisted for several hours (96) after the last exercise session of these training periods. Oxidative damage biomarkers The responses of oxidative stress markers to the training protocol are shown in Fig. 3. Isoprostane levels increased 2.4fold following T1 (P = 0.000), 4-fold following T2 (P = 0.000), 7-fold following T3 (P = 0.000), 2.6-fold following T4 (P = 0.02), and 1.9-fold following R (P = 0.009) compared to B. Isoprostane concentration in urine reached its highest value following T2 and T3. PC concentration increased only after (P = 0.004) T2 and T3 (P = 0.000) by 50 and 73%, respectively, without any other changes noted. TBARS increased (P = 0.001) only after T3 by 56%, and declined thereafter. Glutathione status Changes in glutathione status are depicted in Fig. 4. GSH levels declined (Pb0.000) only after T3 by 31% and returned to baseline values thereafter. In contrast, GSSG increased (P = 0.001) following T3 by 25% and returned to baseline thereafter. The ratio GSH/GSSG, a valid oxidative stress marker, decreased (P = 0.01) only after T3 by 56% and was normalized thereafter.

Fig. 3. Oxidative stress biomarkers (isoprostanes, TBARS, protein carbonyls) responses during training. B, baseline; T1–T4, the four training periods; R, rest period; ⁎denotes significant difference with baseline; #denotes significant difference between T3 and T2. Shaded areas denote the onset of overtraining.

Antioxidant biomarkers Fig. 5 illustrates TAC, CAT, and GPX changes. TAC demonstrated a biphasic response by increasing following T1 (P = 0.000) and T2 (P = 0.003) and declining following T3 (P = 0.002). In contrast, CAT increased following T3 (96%, P = 0.015) only. GPX increased following T2 (P = 0.0001) and T3 (P = 0.000) and returned to baseline values thereafter. Correlations between oxidative stress biomarkers and exercise volume as well as performance

Fig. 2. Leukocyte responses with training. B, baseline; T1–T4, the four training periods; R, rest period; ⁎denotes significant difference with baseline. Shaded area denotes the onset of overtraining.

Table 2 shows the correlation of each parameter with: (a) magnitude of change in during overtraining, and (b) magnitude of performance variable following overtraining.

oxidative stress exercise volume decline in each Exercise volume

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Fig. 4. GSH, GSSG, and GSH/GSSG responses during training. B, baseline; T1–T4, the four training periods; R, rest period; GSH, reduced glutathione; GSSG, oxidized glutathione; ⁎denotes significant difference with baseline. Shaded areas denote the onset of overtraining.

indicating a prolonged inflammation despite a significant decline of exercise overload. These results corroborate previous findings of delayed leukocytosis (5 days) following unaccustomed strenuous exercise [15]. Immune cells generate ROS that promote postexercise inflammation, removal of traumatized tissue, and healing [15]. Although previous research indicates an upregulation of oxidative stress following extreme exercise (increased F2-IsoP and TBARS) [26], only one investigation attempted to study endurance exercise overtraining in rats but failed to observe significant alterations in oxidative stress responses probably because the training protocol was not strenuous enough [16]. Weight lifting exercises increase ROS production in a biphasic manner [27]. The first peak is caused by a repeated ischemiareperfusion injury during exercise and the second is dependent on the accumulation of infiltrated phagocytic cells at the

increase was highly correlated with F2-IsoP (r = 0.812, P = 0.026) and GSH/GSSG (r = 0.809, P = 0.026) changes. CMJ drop was correlated with F2-IsoP (r = 0.786, P = 0.036), GSSG (r = 0.808, P = 0.028), and GSH/GSSG (r = 0.911, P = 0.004) changes. MP decline demonstrated a significant correlation with F2-IsoP (r = 0.773, P = 0.041) and GSH/GSSG (r = 0.856, P = 0.014) changes. Chest press 1RM drop was significantly correlated with only GSH/GSSG (r = 0.764, P b 0.046) changes. Power clean 1RM decrease was correlated with F2-IsoP (r = 0.928, P = 0.003) and GSH/GSSG (r = 0.894, P = 0.007) changes. Discussion The present investigation demonstrated that exerciseinduced overtraining elicits a significant response of oxidative stress biomarkers and antioxidant status indices in humans, which, in some instances, was proportional to the training load imposed on the subjects indicating a dose-response relationship. Performance deteriorated following T3 (overtraining) compared to T2 (when all performance indices were significantly improved) while muscle soreness and inflammation symptoms developed (DOMS, muscle swelling as evidenced by reduced KJM), indicating onset of overtraining [4]. Work from our laboratory indicated that this protocol induced a significant delayed response of inflammatory markers (plasma DNA, Creactive protein, creatine kinase) [8]. Prolonged muscle strength deterioration, usually seen in overtrained athletes, may be associated with ROS-induced muscle damage [25]. In fact, a significant correlation was found between the decline of maximal strength performance following overtraining (T3 vs T2) and oxidative stress biomarkers (GSH/GSSG and F2-IsoP). Overtraining-induced trauma is followed by an inflammatory response that includes muscle infiltration by immune cells and leukocytosis [15]. In the present investigation, sustained leukocytosis was observed 96 h following intense (T2) and very intense (T3) training. Leukocytosis was not suppressed following a regeneration period of low-volume training (T4),

Fig. 5. Antioxidant status biomarkers (TAC, catalase, GPX) responses during training. B, baseline; T1–T4, the four training periods; R, rest period; TAC, total antioxidant capacity; GPX, glutathione peroxidase. ⁎denotes significant difference with baseline; #denotes significant difference between T3 and T2. Shaded areas denote the onset of overtraining.

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Table 2 Correlation coefficients of oxidative stress biomarkers with the magnitude of change in exercise volume during overtraining, and the magnitude of decline in each performance variable following overtraining (compared to T2)

Exercise volume (tonnage lifted/week) CMJ drop MP drop Chest Press 1RM Power clean 1RM

TBARS

F2-IsoP

r = 0.391 P b 0.298 r = − 0.612 P b 0.180 r = − 0.428 P b 0.250 r = − 0.469 P b 0.203 r = − 0.250 P b 0.516

r = 0.812 ⁎ P b 0.026 r = 0.786 ⁎ P b 0.036 r = 0.773 ⁎ P b 0.041 r = 0.568 P b 0.184 r = 0.928 ⁎ P b 0.003

PC r = 0.236 P b 0.573 r = 0.374 P b 0.361 r = − 0.482 P b 0.227 r = − 0.602 P b 0.114 r = − 0.639 P b 0.088

GSH r = 0.060 P b 0.899 r = − 0.103 P b 0.826 r = 0.092 P b 0.844 r = − 0.227 P b 0.624 r = 0.050 P b 0.916

GSSG

GSH/GSSG

TAC

CAT

GPX

r = − 0.743 P b 0.071 r = 0.808 ⁎ P b 0.028 r = − 0.710 P b 0.074 r = − 0.705 P b 0.077 r = − 0.665 P b 0.103

r = − 0.809 ⁎ P b 0.026 r = 0.911 ⁎ P b 0.004 r = 0.856 ⁎ P b 0.014 r = 0.764 ⁎ P b 0.046 r = 0.894 ⁎ P b 0.007

r = 0.318 P b 0.487 r = − 0.577 ⁎ P b 0.134 r = − 0.670 P b 0.069 r = − 0.406 ⁎ P b 0.312 r = − 0.686 P b 0.081

r = − 0.208 P b 0.592 r = − 0.156 P b 0.688 r = − 0.035 P b 0.929 r = 0.073 P b 0.853 r = − 0.175 P b 0.652

r = 0.233 P b 0.546 r = 0.062 P b 0.856 r = 0.015 P b 0.966 r = 0.006 P b 0.986 r = − 0.022 P b 0.949

1RM, one repetition maximal; CMJ, counter-movement jump; MP, mean power in Wingate testing; TBARS, thiobarbituric acid reactive substances; F2-IsoP, isoprostanes; PC: protein carbonyls; GSH, reduced glutathione; GSSG; oxidized glutathione; TAC, total antioxidant capacity; CAT, catalase; GPX, glutathione peroxidase. ⁎ Denotes a significant correlation at P b 0.05.

damaged lesions several hours postexercise [27]. Our data demonstrate that overtraining induced a sustained oxidative stress response. The exercise protocol adapted a 3-step configuration of training volume increments and decrements. Oxidative stress biomarkers changed during periods of intense training and overtraining and were restored when the training load returned to normal levels or it was eliminated. PC increased following intense training (T2, 50%), peaked with overtraining (T3, 73%) and declined thereafter. Relatively few data are available regarding exercise-induced PC responses in humans. Resistance exercise has been shown to increase PC (1.6- to 2.4-fold) 24 h postexercise [28]. Extreme exercise (i.e., ultramarathon) elevated PC levels reaching a plateau 48 h postcompetition [29]. The increased PC postexercise should be mainly derived from albumin (constitutes approximately 60% of total serum protein) oxidation and other serum proteins [30]. Oxidized protein removal from blood may be a time-consuming process since PC levels remained elevated for 96 h following T2 and T3. This PC rise may be attributed mechanistically to phagocytic cells invasion into damaged muscle (typically seen several hours postexercise), that generate a substantial amount of oxygen radical species, and is accompanied by underlying inflammation and soreness [13]. Exercise-induced protein oxidation might also be triggered by iron-containing protein disruption [8,31]. Calcium homeostasis imbalance (that contributes to muscle injury during resistance exercise) may also cause ROS generation through activation of phospholipase and proteolytic enzymes [31,32]. F2-IsoP increased following light (2.4-fold), intense (4-fold), and overtraining (7-fold). Exercise-induced muscle damage elevates urinary F2-IsoP [33] for prolonged periods (72 h) which was reduced after the seventh day [34]. Furthermore, extreme exercise (50-km running) increased F2-IsoP by 57% [26]. F2IsoP are formed while still esterified to phospholipids in cellular membranes and are released through the action of phospholipases to circulate in free form in body fluids [35]. The ramification of exercise-associated increases in these compounds may reflect oxidative damage to cell membranes following muscle damage and neutrophil infiltration.

In contrast, TBARS increased only following overtraining (56%). Although most studies indicate that exercise-induced oxidative stress predominates immediately postexercise, lipid peroxidation may increase later after exercise [36]. MDA levels have been shown to increase for several days following acute resistance exercise [37]. Other studies indicate that, as in the present investigation, strenuous exercise elicits a delayed (N48 h) TBARS elevation (40–70%), probably triggered by leukocyte and macrophage infiltration and/or xanthine oxidase activation due to the ischemia-reperfusion process [34,38]. The higher TBARS concentration in blood is probably caused by lipid peroxidation of low-density lipoproteins and oxygenmediated injury of muscle cell membranes [39]. GSH decreased (31%) while GSSG increased (25%) only following overtraining and returned to normal thereafter. Consequently, their ratio (GSH/GSSG) declined by 56% following T3 and it was normalized thereafter. Intense resistance exercise decreased (21%) GSH and increased (25%) GSSG [28]. Interestingly, lower training volumes/intensities did not affect glutathione redox status. These results denote that during overtraining, GSH supply may not be sufficient to match its enhanced utilization, resulting in its reduction in blood. There might also be an increase in blood GSH clearance (e.g., increased consumption by muscle). GSH may be used either for ascorbic acid and α-tocopherol regeneration or ROS (i.e., superoxide anion, singlet oxygen) scavenging [40]. TAC demonstrated a biphasic response by increasing following light and intense training and decreasing following overtraining. TAC increase suggests that exercise activated the body’s antioxidant defenses in serum [41]. Uric acid elevation has been estimated to account for nearly one-third of TAC increase [42]. The present protocol has been shown to induce a significant uric acid increase following all training stages [8]. Other antioxidants might have contributed to this TAC increase such as GSH which was markedly reduced during the same period. It is unlikely that this TAC rise may be related to antioxidant enzyme increase since CAT and GPX were not elevated during the first two training periods. Mobilization of tissue antioxidant stores into the plasma is a widely accepted

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phenomenon that would help maintain antioxidant status in plasma in times of need [43]. Prolonged hard training might have depleted tissue antioxidants producing a second-phase TAC decline. To our knowledge, this study is the first to show such a response under conditions of physical stress which coincides with increased oxidative stress levels. GPX increased after T2 and T3 while CAT increased only after T3. These training periods were characterized by increased training volume/intensity and oxidative stress levels. A significant positive correlation of GPX and CAT activities with weekly training volume has been reported previously [44]. A higher steady-state concentration of cellular H2O2 with excessive training might lead to increased antioxidant enzyme gene expression through posttranscriptional mechanisms [45]. Increased CAT and GPX activities may be dependent upon scavenger cell migration into damaged muscle tissue. Macrophage migration in damaged muscle fibers has been observed 24–72 h following resistance exercise [27]. Furthermore, exhaustive cycling decreased CAT and GPX activities by 40 and 50%, respectively, in neutrophils and increased GPX activity in lymphocytes by 87% while CAT protein levels decreased by 48% in neutrophils postexercise, indicating that intense exercise induces blood cell damage [46]. However, these data were seen only 3 h postexercise with an entirely different training mode. The present protocol employed large volumes of several multijoint resistance exercises that engage a large muscle mass for prolonged periods that may elicit a greater damage and a more sustained antioxidant enzymes’ response. CAT increased only when overtraining and peak oxidative stress levels occurred whereas GPX increased earlier (T2). The substantially lower Km of GPX for H2O2 suggests that GPX scavenges H2O2 efficiently at lower concentrations [47]. At higher training volumes, the increased H2O2 production may exceed GPX capabilities. Therefore, CAT production would be expected to increase in response to training volume demands, to compensate for the GPX inability to scavenge H2O2 in times of greater demand. OTS, a disorder affecting numerous athletes, is characterized by a significant performance decline, excessive fatigue, moodiness, and has major health implications. Today, there is no single biomarker available for OTS diagnosis. Oxidative stress biomarkers seem intriguing for OTS diagnosis due to their association with exercise-induced tissue trauma. The use of blood and/or urine oxidative stress biomarkers for OTS detection appears promising due to its noninvasive nature. In order for these biomarkers to serve as diagnostic tools, it is critical that they are stable, accumulate in detectable concentrations, reflect specific oxidation pathways, and correlate with condition severity. Interestingly, F2-IsoP and GSH/GSSG were significantly correlated with exercise volume increase and/or performance drop, suggesting an association with training severity. F2-IsoP exhibited a dose-response to training, showing graded elevations/decline depending on the intensity and volume of each phase. PC and GPX demonstrated a similar response, increasing with excessive training and decreasing thereafter. In contrast, GSH/GSSG declined while CAT and TBARS increased only with overtraining. Therefore, F2-IsoP,

PC, and GPX exhibit an increased sensitivity to training (changing even at lower training volumes), whereas GSH/ GSSG, CAT, and TBARS demonstrate increased specificity (increased only after overtraining). The biphasic TAC response was also a novel finding of the present study. A combination of these responses could serve as a diagnostic tool for OTS detection but this possibility needs further testing. F2-IsoPs, and possibly PC and GSH/GSSG, are suitable for overtraining biomarkers because their in vivo formation changes as a function of oxidative stress [48], they are measured accurately noninvasively down to picomolar concentrations with nonexpensive analytical techniques, they are stable in isolated samples of body fluids, they do not show diurnal variations [48], they correlate with condition severity [49], and they are present in detectable amounts in biological fluids, thus allowing definition of a reference interval. On the other hand, TAC and TBARS assays have received criticism regarding their specificity and sensitivity. Strenuous training may produce exertional rhabdomyolysis which refers to skeletal muscle breakdown [50]. Rhabdomyolysis increases ROS generation via Fenton/Haber-Weiss reactions inducing lipid peroxidation and protein carbonylation in plasma and other tissues, and altering GSH homeostasis by reducing GSH [51]. However, overtraining-induced rhabdomyolysis has not been studied. In the present study it is possible that overtraining might have induced rhabdomyolysis which in turn exacerbated oxidative stress responses. Nevertheless, the absence of specific clinical features [dark urine, acute renal failure, increased creatine kinase levels exceeding 500 U/L [the present protocol elicited only a 3-fold increase of creatine kinase (8)] that define rhabdomyolysis diagnosis does not support its occurrence in the present investigation. In conclusion, this study demonstrates that exercise overtraining induces a marked oxidative stress response which, in some cases, was proportional to training load. Further research is needed to determine the suitability, sensitivity, and specificity of these methods during physical stress, modifying factors (i.e., lifestyle and dietary intake) [50], their basal concentration and variability in different populations, the inter- and intraindividual variation and the underlying physiological mechanism that elicits this type of response. Acknowledgments The authors thank all the subjects for their participation and commitment to the study and Mr Ioannis Galanis for his technical assistance. References [1] Smith, L. L. Cytokine hypothesis of overtraining: a physiological adaptation to excessive stress? Med. Sci. Sports Exerc. 32:317–331; 2000. [2] Smith, L. L. Overtraining, excessive exercise, and altered immunity: is this a T helper-1 versus T helper-2 lymphocyte response? Sports Med. 33: 347–364; 2003. [3] Fry, A. C.; Kraemer, W. J. Resistance exercise overtraining and overreaching. Sports Med. 23:106–129; 1997. [4] Kreider, R.; Fry, A. C.; O’Toole, M. Over-training in sport: terms,

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