High-intensity interval training (HIIT), in a variety of forms, is one of the most effective time-efficient strategies to improve cardiorespiratory and metabolic function and ultimately optimize physical performance.1 In general, HIIT protocol involves alternate bouts of intense exercise workout (approx 85–90% VO2max) followed by rest or low-intensity recovery periods and may develop both the aerobic and anaerobic system at the same time.1–3 In other words, HIIT is believed as an optimal stimulus to push the threshold limit of maximal cardiovascular and peripheral adaptations by spending several minutes in ‘red zone’ under training in terms of both>90% VO2max and HRmax.1 Gibala and McGee (2008) suggested that HIIT is an effective alternative to traditional endurance training to induce similar or even superior changes in physiological, performance and health-related markers in both healthy and diseased populations.2

Muscle damage is a high-intensity training or over-training induced condition where intramuscular proteins appear in the blood due to microtrauma in the muscle cell membrane with a drop in muscle speed, power and flexibility.4 Creatine kinase (CK) and lactate dehydrogenase (LDH) are suitable indicators of muscle damage since they start to accumulate in the blood due to the exercise-induced regional necroses in muscle fibers.5,6 Previously a significant increase in CK and LDH after acute high-intensity training (≥80% VO2max) was observed where values even remain at an elevated level after 24h of post-exercise.4,5

Interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) induce the inflammatory cascade following any high-intensity workout with sympathetic stimulation.7 IL-6 and TNF-αfound higher immediately after theexercise8,9 even 48h of post-exercise10 than their resting values. The post-exercise IL-6 increase may induce the onset of muscle soreness especially following an eccentric or high-intensity exercise (HIE).8,10

Both short-term and long-term HIIT induced alteration in redox equilibrium has been reported due to continuous production of reactive oxygen species (ROS) in the skeletal muscle bed and this leads to rising in lipid peroxidation by disrupting the scavenging property of antioxidant enzymes.11–13 Evidence suggested that exercise may positively or negatively induce the degree of oxidative stress depending on the specificity, load, intensity, and duration of the training.11–14 On the other hand, Sousa et al. (2016) has reported that regardless of intensity, volume, type of exercise, antioxidant indicators tended to increase with a concomitant decrease in pro-oxidant indicators following training.15

The effect of high-intensity interval exercise on muscle damage, oxidative stress and inflammatory markers, have been reported in earlier studies.4,5,8,12,16 But these studies have documented the single exercise bout induced changes in these parameters. Studies are lacking on the effects of HIIT training period (long-term/longitudinal effect) on these parameters. Therefore, the present study was aimed to investigate the effects of 8 weeks sprint HIIT on muscle damage indices, inflammatory markers, oxidative stress and physical fitness variables in young team-game players. It is hypothesized that HIIT may impose muscle damage, inflammation and oxidative stress condition along with optimizing the athletics performance and may not be beneficial for long-term training adaptations.

Effect of HIIT induced changes on anthropometric parameters have been represented in Table 2. Bodyweight, BMI, and BF% were significantly (p<0.001) decreased in post-training HIIT group when compared with pre-training data. On the other hand, body weight, BMI, and BF% were significantly (p<0.001) increased in the control group after the intervention period Body height increased significantly (p<0.05) in post-intervention data in both the groups. Two-way ANOVA depicted significant result in both the time×treatment effect and time only effect in body weight, BMI and BF%. Additionally, body height revealed the time only effect in a significant manner.

Effect of HIIT induced changes on skeletal muscle damage indices and inflammatory markers have been represented in Table 3. Significant increase in LDH, CK-MB, cortisol, IL-6 and TNF-α were observed in following HIIT in the experimental group. On the other hand, only LDH was found to be significantly (p<0.001) increased in the control group after the intervention period. Two-way ANOVA depicted significant result in both the time×treatment effect and time only effect in LDH, CK-MB, cortisol, IL-6 and TNF-α. Additionally, significant treatment only effect was observed in IL-6 and TNF-α.

Effects of HIIT induced changes on oxidative stress markers have been represented in Table 4. Significant increase in MDA, GPx and decrease in SOD, GR were observed following HIIT in the experimental group. Control group showed a significant (p<0.001) increase in MDA following the intervention period. Two-way ANOVA depicted significant result in all three time×treatment effect, treatment only effect and time only effect in MDA, SOD and GSH.

Effects of HIIT induced changes on some selected physical fitness parameters have been represented in Table 5. Significant (p<0.001) increase in VO2max, Wpeak and VJ were observed following training in post-training HIIT group in comparison to their respective pre-training values. Two-way ANOVA depicted significant result in both time×treatment effect and time only effect in VO2max, Wpeak and VJ. Additionally, significant treatment only effect was observed in VO2max only.

The correlation coefficient of muscle damage indices, inflammatory variables and oxidative stress markers with physical fitness variables has been presented in Table 6. VO2max showed significant (p<0.01) positive correlation with LDH, IL-6, MDA and significant negative correlation with GSH. VJ had significant (p<0.01) positive correlation with LDH, TNF-α, MDA, GPx (p<0.05) and significant negative correlation with GSH. Whereas Wpeak was found to be the less correlated variables among all physical fitness variables and only found to be negatively and significantly (p<0.05) correlated with GSH.

The regression equations for prediction of VO2max and Wpeak from LDH, CK-MB and cortisol have been presented in Table 7. First regression prediction model represents Durbin-Watson=1.692, Std. Residual=−1.765/1.686, F=3.217, Sig=0.008 (Dependent variable – VO2max; Predictors – GPx, CK, Cortisol, IL-6, Sod, GSH, LDH, TNF and MDA). Whereas the second model represents the Durbin-Watson=1.945, Std. Residual=−1.676/1.876, F=1.683, Sig=1.37 (Dependent variable – Wpeak; Predictors – GPx, CK, Cortisol, IL-6, Sod, GSH, LDH, TNF and MDA).

The main aim of the present study was to find the effect of HIIT induced alterations in muscle damage indices, inflammatory markers, antioxidant status and physical fitness variables of young team-game athletes. The present investigation revealed that 8 weeks HIIT can significantly (p<0.001) increase the muscle damage indices [LDH (15.0%), CK (14.4%)], cortisol (9.4%), inflammatory markers [IL-6 (15.7%), TNF-α (18.2%)]; antioxidant indicators [MDA (29.5%), GPx (0.4%)]; and physical fitness variables [VO2max (13.6%), Wpeak (11.6%), VJ (11.2%)] with significantly (p<0.001) decrease the BF% (7.6%) and plasma concentration of SOD (11.1%), GSH (10.8%) among young players.

The present HIIT intervention improved the body composition by significantly (p<0.001) reducing BF% (7.6%) and increasing BMI (1.1%). This observation agrees with Musa et al. (2009) where they reported 1.3% and 15.8% reduction in both body mass and BF% respectively after 8 weeks of HIIT (90% HRmax).25 High-intensity training generally hypothesized a reduction in body weight but instead of that, the present study depicted a significant increase in both weight and BMI which might due to the muscular hypertrophy.26 Previous finding suggested that HIIT increased the rate of fat oxidation due to increased catecholamine level which controls over the β-adrenergic receptors in adipose tissue and increased fatty acid-binding protein (FABPpm) content in skeletal muscle.27 On the other hand, the increase in the skeletal muscle fat oxidation likely resulted from several adaptations, including an increase in mitochondrial volume and altering several regulatory steps, e.g., adipose tissue lipolysis of TG to fatty acids (FA), transport of FA into the cell, intramuscular lipolysis of TG to FA and ultimately FA into the mitochondria.28–30

The LDH and CK are well known potential markers used for assessing both cardio-metabolic responses and the degree of skeletal muscle damage.4,5 Present study depicted a significant (p<0.001) rise in LDH (15.0%) and CK-MB (14.4%) which corroborates with Callegari et al. (2017) and Tesema et al. (2019), where CK and LDH both reported ∼100–200-fold increase after moderate/acute (60–70% HRmax for 45min) and high intensity/chronic (70–80% HRmax for 30min) training which gradually rises till 24h post-exercise.4,5 Wiewelhove et al. (2016) have reported that short intervals of sprint protocols under HIIT induce highest muscle damage and muscle soreness in comparison to the submaximal intensity of longer intervals.31 All these muscle damages may result due to the stretch-shortening cycle mechanism of muscle contraction during short duration high-intensity exercise.4,5 The development of stress-tension characteristics in skeletal muscle fibres leads to severe microdamage in the sarcolemma and finally cause the leakage of CK and LDH in bloodstream as a damage indicator.6 Increase in muscle damage markers may also result from the immunological and hormonal changes due to stress-tension association with high-intensity training.32 Interestingly muscle damage indices (i.e., LDH, CK)were only significantly increased against the short-period of exhaustive or HIE bouts and not against prolonged period workouts or low-intensity exercises.4,5

IL-6 and TNF-α are major markers to measure and limit pro-inflammatory cellular cascade to maintain homeostasis. They induce the inflammatory cascade following any HIE causing sympathetic stimulation.7 Present study depicted significant (p<0.001) increase in both IL-6 (15.7%) and TNF-α (18.2%) which corroborates with studies of Zebrowska et al. (2019) and Gerosa-Neto et al. (2016).8,9 Where Zebrowska et al. (2019) have reported that 3 weeks HIIT (5min 30W cycling) can elevate both the resting and maximum levels of IL-6 (approx. 46% and 50%) and TNF-α (approx. 47% and 15%) respectively.8 Gerosa-Neto et al. (2016) have reported 16 weeks HIIT (90% HRmax) induced a significant rise in TNF-α (104%).9 The HIIT induced temporary hypoxic conditions may cause to persuade an inflammatory response that increases IL-6 and TNF-α, mediated by leukocytes and manifested by elevated concentrations of proinflammatory cytokines.8,9 Contrarily, Brown et al. (2018) suggested that even after 48h of exercise the level of IL-6 and TNF-α were still higher than the resting condition.10 Collectively past studies have suggested that the post-exercise IL-6 increase in skeletal muscle may induce the onset of muscle soreness, reduced glycogen availability and alteration in calcium and stress hormone secretion and all those effects were much less in concentric contractions in comparison to eccentric exercises.8,10 However, a contradictory finding reported that TNF-α returned to baseline level faster than other cytokines like IL-6.33

Previously acute HIE of both short-term and long-term exercise was reported to create a redox imbalance and an increase in oxidative stress markers (i.e., SOD, catalase, sulfhydryl group).11–13 In the present study, HIIT induced a significant increase in MDA (29.5%, p<0.001), GPx (0.5%, p<0.05) and a significant decrease in SOD (11.1%, p<0.001), GSH (10.8%, p<0.001) were corroborated with studies of Miyazaki et al. (2001), Bogdanis et al. (2013) and Ugras (2013).13,16,34 Bogdanis et al. (2013) has reported 3 weeks HIIT (high-intensity cycling) induced a significant increase in oxidative stress markers i.e., protein carbonyl (PC), TBARS, GPx, catalase, total antioxidant capacity (TAC) and even reported to last for 24–48h after exercise.16 Similarly, Miyazaki et al. (2001) and Ugras (2013) have reported a significant increase only in MDA (approx. 40%), a marker for lipid peroxidation against longitudinal HIIT period.13,34 Although Azizbeigi et al. (2014) has reported training induced significant increase only against SOD and GPx but not in the MDA level.35 Excessive HIE or overtraining leads to a temporary hypoxic condition which confers the overproduction of ROS, creates oxidative stress and challenges redox equilibrium which further disrupts the cellular homeostasis and confers the disturbance in scavenging property of antioxidant enzymes to lead the rise in lipid peroxidation.13,36 Several studies have reported that even a single bout of intense exercise can alter the antioxidant equilibrium and increase MDA level.34,37 Antioxidant adaptations in the present study may be due to HIIT induced excess ROS generation within mitochondria which diffuse into the cytoplasm and activate AMP-activated protein kinase (AMPK) that transcriptionally co-activates the PGC-1 α and mitochondrial biogenesis via activating Peroxisome Proliferator Activated Receptor-gamma (PPARγ) and PPARγ Coactivator-1α (PGC-1 α).38 Alternatively, ROS may act as a key mediator for exercise-induced cytokine response through the stimulation of inflammation regulating NF-κB and data proved the possible interaction between increased lipid peroxidation and cytokine secretion.10 Although there are studies like Rahnama et al. (2007) and Vezzoli et al. (2014) where slight or no significant changes was observed against high-intensity physical training-induced oxidative stress marker variables.39,40 Additionally, Sousa et al. (2016) has reported by summarizing 38 studies that pro-oxidants i.e., TBARS/MDA, PC, myeloperoxidase, H2O2 etc tended to decrease significantly in association with an increase in SOD, GPx, catalase, TAC and GSH as a physical training-induced effect.15

The present study depicted significant (p<0.001) rise in VO2max (13.6%) and Wpeak (11.6%)which corroborates with studies of Fereshtian et al. (2017), Macpherson et al. (2011) and Zychowska et al. (2017) with increase in7.6%, 11.5% of VO2max and 2–4% (approx.) change in anaerobic power output respectively.41–43 The significant increase in VO2peak was mainly attributed to the higher mitochondrial enzyme activities i.e., citrate synthase (CS); cytochrome-c oxidase (COX); COX-II, IV protein content; and β-hydroxyacyl-CoA dehydrogenase (β-HAD).2,28,45 Other studies hypothesized that improvement in stroke volume and maximal cardiac output (Qmax) following HIIT were 15–35% responsible for the improvement in VO2max.2,42 Considerably, the improved Wpeak correspond to an improved anaerobic capacity index which might have happened due to the improved lactate tolerance, developed sprinting ability within the anaerobic zone with higher glycolytic activity level.17,43 It has been reported that HIIT increased glycolytic enzymatic activities (e.g., hexokinase, glycogen phosphorylase, phosphofructokinase), muscle buffering capacity and ionic adaptations including increased Na+-K+-ATPase content to compensate the enlarged energy demand during an anaerobic HIIT.45,46 Alternatively, HIIT induced improvement in anaerobic capacity may due to the adaptations in skeletal muscles (reduced phosphocreatine degradation, enhanced glycogen content) along with increased type IIA ratio and reduced IIB ratio.44,45 Present studied increase in VJ (11.2%) corroborates with Ferrete et al. (2014), where similar high-intensity training induced significant increase (∼6.7%) in jumping capacity has been reported which further suggests the possible transfer from the gain in the leg muscular power into the sprint performance.47 Intense training-induced enhancement in jumping capacity may due to the improved muscular hypertrophy and neuro-muscular coordination.47

In the present study, two separate linear regression models were computed for predicting VO2max and Wpeak where the selected predictors were GPx, CK-MB, Cortisol, IL-6, SOD, GSH, LDH, TNF-α and MDA. Out of all these predictor variables, only LDH (p=0.044) and CK-MB (p=0.023) were found to be the principal predicting variables for Wpeak but the regression model itself was insignificant (F=1.683, Sig=1.37). On the other hand, the regression model significantly predicted VO2max (F=3.217, Sig=0.008) but there was no such variable which can alone significantly predict VO2max. However, Pearson's product-moment correlation identified GSH as one such variable which had significant negative (p<0.01) correlation with VO2max and VJ. VO2max showed a significant positive correlation with LDH, IL-6, MDA and VJ showed significant positive correlation with LDH, TNF-α, MDA, GPx. It may be hypothesized that VO2max and VJ were the most important dependent variables on LDH, IL-6, TNF-α, MDA, GSH and GPx.

It is the limitation of the present study that it was unable to predict the gender variation on the studied parameters as it did not include female participants. Another shortcoming of the is that it only focused on a particular type of sprint HIIT (2min intense sprinting at 90–95% of HRmax, work: rest=1:1) although plenty of training variations are there in terms of training intensities. Therefore, the study is unable to suggest the intensity wise effects of HIIT on the studied parameters.

The present sprint HIIT protocol was found to induce an overall significant rise in oxidative stress level (MDA, GPx, SOD, GSH); inflammatory variables (IL-6, TNF-α); and muscle damage profile (LDH, CK-MB, cortisol) with concomitant improvements in fitness variables (VO2max, Wpeak, VJ). The study concludes that the inflammatory and oxidative stress condition may finally lead to muscle damage, which all may occur due to the development of temporary hypoxic condition resulting from intense/exhaustive workout intervened with insufficient intervals which will contrarily induce the overtraining effect. Correlation and regression study predicts that muscle damage, inflammatory and antioxidant variables can be used to measure and predict the limitation of muscular strengths, endurance capacity and anaerobic power. Although more significant prediction can be done against the endurance capacity in comparison to anaerobic power. However, muscle damage indices (LDH and CK) are the best factors to predict anaerobic power than others. The improved fitness variables surely revealed the effectiveness of HIIT to optimize performance specially in pre-competitive phase. But for long-term use, this HIIT protocol is not recommended in general as it develops ROS generation, alters redox equilibrium and influences variation in enzyme levels, inflammatory markers which simultaneously leads to an oxidative stress condition, inflammation and muscle damage and that may cause muscle soreness causing a burden on athlete's health. Although HIIT must be done under the supervision of scientific experts/trained coaches who can modify or modulate training regimen as per the athlete's individual physical and physiological capacity and response to the training. The association of HIIT with some antioxidant (vitamins, natural products etc.) supplements must be studied in future to reveal whether HIIT induced adverse health effects can be prevented or not.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

All authors have agreed to publish the present article and declare no conflict of interest.