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High-intensity interval training with or without chlorella vulgaris supplementation in obese and overweight women: effects on mitochondrial biogenesis, performance and body composition

Published online by Cambridge University Press:  26 August 2021

Mahzad Sanayei
Affiliation:
Department of Community Nutrition, Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran Student Research Committee, School of Nutrition & Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
Fatemeh Hajizadeh-Sharafabad
Affiliation:
Department of Community Nutrition, Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran Student Research Committee, School of Nutrition & Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
Ramin Amirsasan
Affiliation:
Associate Professor in Exercise Physiology and Sport Nutrition, University of Tabriz, Tabriz, Iran
Ali Barzegar*
Affiliation:
Nutrition Research Center, Department of Community Nutrition, School of Nutrition & Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
*
* Corresponding author: Ali Barzegar, email [email protected]
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Abstract

The beneficial effects of high-intensity interval training (HIIT) and chlorella vulgaris (CV) on body composition and mitochondrial biogenesis have been shown in some mechanistic studies. This study aimed to determine the effects of CV and/or HIIT on mitochondrial biogenesis, performance and body composition among overweight/obese women. There was a significant reduction in the fat mass (FM) of the CV + HIIT group, as compared with the placebo group (P = 0·005). A marginal significant increase in body water (P = 0·050) and PPAR-γ coactivator-1α (P = 0·050) was also found only in the CV + HIIT group, as compared with the placebo. Relative (P < 0·001) and absolute (P < 0·001) VO2max, as well as Bruce MET (P < 0·001), were significantly increased in the HIIT and HIIT + CV groups. Besides, the synergistic effect of CV and HIIT on the Bruce MET increment was found (interaction P-value = 0·029). No significant changes were observed in BMI, fat-free mass, visceral fat, silent information regulator 1 and fibroblast growth factor-21. In this randomised clinical trial, forty-six overweight/obese women were assigned to four groups including CV + HIIT and HIIT + placebo groups that received three capsules of CV (300 mg capsules, three times a day) or corn starch, in combination with three sessions/week of HIIT. CV and placebo groups only received 900 mg of CV or corn starch, daily, for 8 weeks. Biochemical assessments, performance assessment and body composition were obtained at the beginning and end of the intervention. HIIT may be, therefore, effective in improving mitochondrial biogenesis, performance and body composition in overweight/obese women.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society

Total body fat is associated with impaired mitochondrial function, thus indicating a strong relationship between body composition and mitochondrial energy metabolism(Reference Bellissimo, Fleischer and Tran1). Mitochondria, as an important cell organelle, is involved in many crucial cell functions such as metabolism, regulating the maximal oxygen consumption (VO2max), which is important for endurance performance(Reference Vakifahmetoglu-Norberg, Ouchida and Norberg2). VO2max is the maximum (max) amount of oxygen (O2) a person utilises during his/her exercise; it is considered as a common measurement of aerobic power. Some characteristics including sex, age, body composition, exercise history and diet can affect VO2max (Reference Kohrt, Malley and Coggan3).

Endurance exercise-induced adaptations in mitochondrial activity can improve the metabolic health and decrease the risk of obesity and other metabolic disturbances(Reference Warburton, Nicol and Bredin4). Higher mitochondrial biogenesis is associated with aerobic performance as well as muscle oxidative capacity and regulated by transcriptional cofactors such as PPAR-γ coactivator-1α (PGC-1α)(Reference Bishop, Botella and Genders5). Deacetylation of PGC-1α by silent information regulator 1 (SIRT1) which is an NAD-dependent deacetylase increases PGC-1α activity, resulting in the activation of mitochondrial biogenesis(Reference Gerhart-Hines, Rodgers and Bare6,Reference Tang7) . Besides, the gene expression of PGC-1α is up-regulated via fibroblast growth factor-21 (FGF-21)(Reference Ji, Zheng and Lv8).

During exercise, SIRT1 is increased, subsequently activating PGC-1α (Reference Civitarese, Carling and Heilbronn9). High-intensity interval training (HIIT), a time-efficient strategy done above 85 % of the maximal aerobic capacity, can increase the skeletal muscle adaptation and exercise capacity via some cellular pathways including mitochondrial biogenesis(Reference Little, Safdar and Wilkin10). Based on the American College of Sports Medicine’s Worldwide Survey of Fitness Trend for 2019, HIIT was in the five top trends for fitness from 2014 to 2020(Reference Thompson11).

In a comprehensive review, the HIIT’s effect on the body composition was investigated, showing a significant reduction in the whole-body FM and waist circumference in the obese individuals, even in the absence of body weight change(Reference Wewege, Van Den Berg and Ward12). Body fat accumulation could decrease the relative VO2max; thus; more FM could be, therefore, a better predictor of relative VO2max, as compared with exercise performance tests(Reference Shete, Bute and Deshmukh13).

Dietary antioxidants with electron-donor properties such as vitamin C, vitamin E, riboflavin, Q10 and α-lipoic acid can also stimulate mitochondrial biogenesis, as well as VO2max (Reference Valero14). Chlorella vulgaris (CV), as a well-known algae, has been recently considered as a valuable functional food due to the high content of vitamins, minerals and phenolic components(Reference Lee, Kang and Lee15). CV has been shown to have antioxidant, anti-inflammatory and immunomodulatory properties(Reference Lee, Kang and Lee15); its high antioxidant content makes it an appropriate supplement for the exercising people.

According to our research, no previous study had yet investigated the combined effect of HIIT and CV supplementation on mitochondrial biogenesis and performance in the overweight or obese women. Therefore, this study aimed to evaluate the effects of HIIT and/or CV, as well as any synergic effect of these two interventions, on PGC-1α, FGF-21, SIRT1, body composition and performance parameters.

Materials and methods

Participants

This study was performed in Tabriz, Iran, from June 2019 to November 2019. Participants were recruited from Tabriz area via flyers throughout the community and healthcare centres. Obese or overweight women, aged 18–35 years, with a BMI ranging from 25 to 35 kg/m2 were included in the study. Main exclusion criteria were weight fluctuations more than 3 kg during the last 6 months, continuous physical activity, joint disabilities, severe health conditions, consumption of antioxidant supplements and a particular diet. The study protocol was approved by the ethics committee of Tabriz University of Medical Sciences (IR.TBZMED.REC.1397·922). In an awareness condition, participants signed the informed consent. This clinical trial was registered at the Iranian Registry of Clinical Trials, (https://www.irct.ir/trial/37816, with the Registration number: IRCT20190224042821N1).

Study design

This study was an 8-week randomised, double-blind, placebo-controlled trial involving four treatment groups: CV, HIIT+placebo, CV + HIIT and placebo. CV group received CV powder with 98 % purity (300 mg capsules, three times a day); placebo group got the corn starch powder (300 mg capsules, three times a day); HIIT + CV group received a similar amount of the CV powder in combination with three sessions/week of HIIT; and also HIIT+placebo group received similar amounts of the placebo in combination with three sessions/week of HIIT in daily manner, for 8 weeks. Randomisation for individual assignments in each group was done using computer-generated random numbers by a statistician. The intervention allocation was blinded for participants and investigators. The blinding was maintained throughout the study as well as during statistical analysis. The codes for the jars were kept under locked storage by a researcher with no involvement in the trial or statistical analyses. Pure CV powder (with the purity of 98 % net weight) was supplied from a knowledge-based company (Riz Jolbaki Parsian). Each CV capsule was filled with 300-mg CV powder and placebo of corn starch; this was done in a pharmacological laboratory, under a sterile condition (Baharan pharmacology company). The dosage of CV was determined based on the previous studies that had shown the proper tolerability, safety and the effectiveness of CV in improving the metabolic parameters(Reference Ebrahimi-Mameghani, Sadeghi and Farhangi16Reference Panahi, Pishgoo and Jalalian18).

The dietitian visited the participants at the baseline and biweekly; this was done till the end of intervention to evaluate the compliance of the participants to the supplements; they were asked about possible adverse effects. In these intervals, volunteers were asked to bring their jars back and the remaining capsules were counted. The participants with a compliance below 90 % were omitted. In addition, the dietary intake was evaluated using the dietary food record (three non-consecutive days) before and after the intervention by Nutritionist 4 software; the subjects were requested not to change their dietary pattern. Participants were instructed to record the amount of the consumed foods and beverages in the portion size and volumes, so that they could be defined correctly.

Anthropometric and body composition measures

The anthropometric parameters were assessed at the beginning and after the 8-week intervention. Height measurement was done via a wall-mounted Stadiometer (Seca) with 0·1-cm accuracy. Body weight was measured after some overnight fasting with the least clothing, using an identical scale (Seca) with 0·1-kg accuracy. Body composition comprising fat mass (FM) and fat-free mass (FFM) was assessed using a bioimpedance analyser (Tanita MC-780 S MA).

Blood sampling and analysis

Blood samples from the medial cubital vein were taken after some overnight 8- to 12-h fasting and centrifuged at 4°C for 15 min to isolate the plasma from whole blood. Plasma samples were aliquoted and stored at −80°C until the biochemical analyses. Plasma levels of PGC-1α, SIRT-1 and FGF-21 were assessed using the ELISA method via commercial kits (Shanghai Crystal Day Biotech Company). According to an excellent correlation between muscle and serum PGC-1α levels, the minimally invasive method of assessment (blood sampling instead of biopsy) was chosen(Reference Fabregat-Andrés, Ridocci-Soriano and Estornell-Erill19,Reference Ghasemi, Afzalpour and Nayebifar20) .

Bruce performance test

The Bruce protocol is a maximal exercise test developed by Robert A. Bruce; it can evaluate the cardiac health status(Reference Luong, Ignaszewski and Taylor21). Before the study, subject’s familiarisation with the HIIT protocol was ensured. The protocol consisted of multiple three min exercise stages in which the gradient and speed of each stage were increased in the treadmill. For example, stage 1 was 1·7 mph at a 10 % gradient; the second one was 2·5 mph at a 12 % gradient and the third one was 3·4 mph at a 14 % gradient; they were increased in a step-by-step manner. Before the test started, subjects warmed up with the help of an expert trainer. During the test, the trainer reminded the subjects to have normal breath and encouraged them till the point of exhaustion, such that they could not continue and treadmill was stopped. The instrument used in this study was Technogym treadmill (Cesena) without oxygen mask, with a computer program for the test performance. Relative VO2max, absolute VO2max and Metabolicequivalent of task (MET), max heart rate (HR), total energy burn and time were the outputs calculated via the computer program-defined formula.

High-intensity interval training protocol

In this study, HIIT was a running-based prescription aimed to achieve a target max HR per week. Throughout the study, an expert trainer supervised the HIIT programme. Three exercise sessions per week were conducted over the 8 weeks of trial, giving a total of twenty-four scheduled sessions. Individualisation of the training programme was performed using the max HR of the participants; the progression of the exercise intensity was provided by an increase in the HR in the course of the study (Table 4).

Exercise intensity was determined based on Bruce test outcomes, which included the max HR and VO2max of the participants. Weekly target HR zone for each participant was calculated using the Karvonen formula, as follows:

$\begin{align*}{\rm{Target}}\,{\rm{heart}}\,{\rm{rate}} & = [(\max {\rm{HR}} - {\rm{resting}}\,{\rm{HR}}) \times \% \,{\rm{Intensity}}]\\ &\quad + {\rm{resting}}\,{\rm{HR}}{\rm{.}}\end{align*}$

To control the individualised max HR during exercise, telemetry (Pollar) was applied. Each session began and ended with 10-min warming up and 10-min cooling down. The intensity of the HIIT sessions was designed to increase gradually over 8 weeks. Accordingly, HIIT, done three times per week, was commenced with 20 × 40 s protocol (intensity of 50–60 % max HR) at the first week; this was followed by 20 × 35 s (intensity of 60–70 % max HR) in the second week, 16 × 30 s (intensity of 70–80 % max HR) in the third week, 16 × 25 s (intensity of 80–90 % max HR) in the fourth week and 12 × 20 s (intensity of 90–100 % max HR) in the last month (online Supplementary Table 1).

Statistical analysis

Considering α = 0·05, 95 % confidence and power of 80 %, the sample size was calculated to be nine subjects in each group, based on the fasting blood sugar (as secondary outcome) extracted from the previous investigations(Reference Ebrahimi-Mameghani, Sadeghi and Farhangi16). By anticipating a 20 % dropout rate, totally, we included forty-six subjects in the study: twelve and eleven participants in every two arms. Data analyses were performed using the intention-to-treat method on all subjects who were included (n 46) in the study. To run intention-to-treat analyses, missing data were imputed based on the Last-Observation-Carried-Forward (LOCF) method. To examine the normal distribution of the variables, the Kolmogorov–Smirnov test was applied. For the analysis of the categorical variables comparison, χ 2 test was used. As all quantitative variables had normal distribution, paired samples t test and one-way ANOVA with Bonferroni post hoc pairwise analyses were used for within-group and between-group comparisons, respectively. ANCOVA adjusted for baseline values were applied to evaluate the absolute effect of treatments on body composition constituents, biogenesis biomarkers and performance parameters.

Moreover, to evaluate the effects of CV and HIIT independently (the main effects of CV or HIIT), as well as the possible synergistic effects of these treatments (interactions between CV and HIIT), a 2 × 2 factorial design was applied:

  • – CV (CV and CV + HIIT groups) v. no CV (HIIT+ placebo and placebo groups)

  • – HIIT (HIIT and CV + HIIT groups) v. no HIIT (CV and placebo groups). SPSS software, version 23, was used for statistical analyses and significance level was assumed at P-values less than 0·05.

Results

Participants’ characteristics

A flow diagram of the study subjects is presented in Fig. 1. Of the forty-six participants initially enrolled in the study, two in the CV group did not complete the study because of poor compliance and abdominal cramps. Also, two subjects in the placebo group did not complete the study due to personal reasons either. Therefore, forty-two participants finished the 8-week intervention period. Eventually, based on the intention-to-treat principle, all of forty-six participants were included in the analyses. No serious adverse effects following CV supplementation were reported by the subjects. Only one person reported abdominal cramps.

Fig. 1. Flow diagram of study participants.

Body composition

Baseline values of body weight, FM, FFM, lean body mass (LBM), body water and visceral fat were not different among the groups. Based on the ANOVA or ANCOVA tests, CV intake or HIIT had no significant effect on FM, while the combination of CV and HIIT significantly decreased FM, as compared with the placebo group (–5 % in CV + HIIT v. 1 % in the placebo, P = 0·005). The 2 × 2 factorial analysis adjusted for the baseline values also demonstrated that CV supplementation decreased FM, as compared with no CV (–3 % in CV v. 0·4 % in no CV, P = 0·003). Similarly, the HIIT group showed a significant reduction in FM, as compared with the one getting no HIIT (–3 % in the HIIT group v. 0 % in the one getting no HIIT, P = 0·015). However, the interaction effect was not statistically significant.

The combination of CV and HIIT led to a marginal significant increase in the body water percentage, as compared with the placebo group (28 % in CV + HIIT v. −16·4 % in the placebo, P = 0·050). The 2 × 2 factorial analysis adjusted for the baseline values also showed a significant increase in the body water of the HIIT group, as compared with the one getting no HIIT (1·33 % in HIIT v. −1·01 % in the one getting no HIIT, P = 0·043), while the interaction effect between CV and HIIT was not significant. Neither ANOVA/ANCOVA nor factorial analysis, however, showed any significant between-group differences in body weight, FFM, LBM and visceral fat (Table 1).

Table 1. Body composition characteristics of study participants at baseline and after 8 weeks of intervention

(Mean values and standard deviations; mean difference and 95 % confidence interval)

CV, chlorella vulgaris; Plc, placebo; FFM, fat-free mass; FM, fat mass; LBM, lean body mass; HIIT, high-intensity interval training.

* P-value significance level < 0·05.

P based on for two-way ANOVA adjusted for baseline values.

P based on ANCOVA test adjusted for baseline values.

§ P based on paired samples t test for intragroup comparisons.

Mitochondrial biogenesis factors

Baseline values of PGC-1α, SIRT1 and FGF-21 were not different in the groups. ANOVA and ANCOVA showed a marginal significant increase in the PGC-1α level in CV (64 %), HIIT (54 %) and CV + HIIT (73 %) groups, as compared with the placebo (3 %). The 2 × 2 factorial analysis adjusted for the baseline values also indicated that HIIT significantly increased the PGC-1α levels in comparison with the no HIIT one (63 % in HIIT v. 33 % in no HIIT, P = 0·047), while CV supplementation did not lead to any significant changes in PGC-1α levels, as compared with no CV. In addition, the synergistic effects of CV and HIIT on PGC-1α levels were not significant due to the lack of a significant interaction effect (P = 0·290). In fact, neither ANOVA nor 2 × 2 factorial analysis indicated any significant between-group differences in SIRT1 and FGF-21 changes (Table 2).

Table 2. Mitochondrial biogenesis factors of study participants at baseline and after 8 weeks of intervention

(Mean values and standard deviations; mean difference and 95 % confidence interval)

CV, chlorella vulgaris; Plc, placebo FGF-21, fibroblast growth factor 21; HIIT, high-intensity interval training; PGC-1α, PPAR-γ coactivator-1α; SIRT-1, sirtuin 1.

* P-value significance level < 0·05.

P based on for two-way ANOVA adjusted for baseline values.

P based on ANCOVA test adjusted for baseline values.

§ P based on paired samples t test for intragroup comparisons.

Performance parameters

At the baseline, no significant differences were observed in HR, Bruce MET, relative VO2max and absolute VO2max. However, ANCOVA adjusted for the baseline values showed significant between-group differences in Bruce MET, relative VO2max and absolute VO2max after 8 weeks. Based on the results obtained from Bonferroni post hoc pairwise comparisons, only CV + HIIT significantly increased the Bruce MET (19 % in CV + HIIT v. 3 % in the placebo, P < 0·001), as compared with the placebo group. The 2 × 2 factorial analysis adjusted for the baseline values also revealed the synergistic effect of HIIT and CV on the Bruce MET due to a significant interaction effect (P = 0·029).

Regarding the relative VO2max, CV + HIIT (18 % in CV + HIIT v. –0·3 % in the placebo) and HIIT (14 % in CV + HIIT v. –0·3 % in the placebo) groups showed a significant increase, as compared with the placebo. Furthermore, CV + HIIT (17 % in CV + HIIT v. 1 % in the placebo) and HIIT (14 % in CV + HIIT v. 1 % in the placebo) groups displayed a significant increase in absolute VO2max, as compared with the placebo. Based on 2 × 2 factorial analyses, HIIT showed a significant increase in relative VO2max (18 % in HIIT v. 3 % in no HIIT, P < 0·001) and absolute VO2max (18 % in HIIT v. 0·6 % in no HIIT, P < 0·001), as compared with no HIIT. The synergistic effects of HIIT and CV on relative VO2max (P = 0·846) and absolute VO2max (P = 0·323) were, however, not significant due to the lack of significant interaction effects. Neither ANOVA nor 2 × 2 factorial analysis showed any significant between-group differences in HR changes (Table 3).

Table 3. Performance parameters of study participants at baseline and after 8 weeks of intervention

(Mean values and standard deviations; mean difference and 95 % confidence interval)

CV, chlorella vulgaris; Plc, placebo; HIIT, high-intensity interval training; HR, heart rate.

* P-value significance level < 0·05.

P based on for two-way ANOVA adjusted for baseline values.

P based on ANCOVA test adjusted for baseline values.

§ P based on paired samples t test for intragroup comparisons.

Table 4. Training programme in 8 weeks

Discussion

To the best of our knowledge, the present clinical trial is the first one assessing the effect of HIIT (running protocol), alone or in combination with CV, on the body composition, performance test outputs and some mitochondrial biomarkers in the overweight and obese subjects. First, we hypothesised that HIIT and CV supplementation would improve body composition. In this regard, a significant reduction in FM was observed following CV supplementation plus HIIT, as compared with other groups. In addition, body water was significantly increased in the HIIT group, in comparison with the placebo. However, neither CV nor HIIT, alone or in combination with each other, led to any significant changes in FFM. In an RCT, as done by Mizoguchi et al., supplemented with CV (40 tablets/d) for 16 weeks, the reducing effect of CV on body fat reduction was attributed to a gene named protein tyrosine phosphatase 1B (PTP-1B), a negative regulator of insulin pathway and leptin(Reference Mizoguchi, Takehara and Masuzawa22). Besides this, the chlorophyll content of CV may decrease the FM via suppressing adipogenesis and activating white adipose tissue browning(Reference Li, Cui and Hu23,Reference Seo, Kim and Choi24) . The chlorophyll-containing parts of CV possess various antioxidants like carotenoids; they have a regulatory role in the adipose tissue biology, such as adipogenesis, adipocytes metabolism and secretory actions, as confirmed in several studies(Reference Bonet, Canas and Ribot25,Reference Mounien, Tourniaire and Landrier26) . Polyphenolic contents of CV, such as catechins, epigallocatechin gallate, flavonols and flavones, may also inhibit preadipocyte differentiation and decrease the fat accumulation(Reference Akhlaghi, Ghobadi and Hosseini27,Reference Akhlaghi and Kohanmoo28) . Meanwhile, the magnitude of reduction in the FM following the supplementation of CV alone was smaller than that required to reach a significance level, which could be due to supplementing the low dose of CV for the relatively short intervention period. Regarding the effect of HIIT on body composition, a systematic review and meta-analysis indicated that the average 10 weeks of HIIT could reduce FM about 2·6 kg (˜ 10 % decrease), even in the absence of body mass changes(Reference Wewege, Van Den Berg and Ward12). Interestingly, the recent investigation also showed significant improvements in body composition and aerobic capacity in the overweight men when following HIIT once a week, which was much less than the usual levels (the usual protocol for HIIT consists of running three times a week)(Reference Chin, Yu and Lai29).

Energetic restriction is the most effective way for weight loss, while exercise is more influential on the visceral fat reduction(Reference Ismail, Keating and Baker30). In addition, a greater weight loss was observed during energy restriction, which was partly related to a marked reduction in LBM and muscle wasting. Considering that LBM is the most metabolic active part determining energy expenditure, LBM reduction resulted in a significant reduction of the BMR, making it hard to reach the appropriate weight loss(Reference Most and Redman31). Thus, all weight loss plans should be judged in terms of their success in achieving the body fat loss instead of body weight or BMI. In this regard, HIIT-induced weight loss, which was accompanied by fat loss and preservation of lean mass, led to great health benefits(Reference Kerksick, Thomas and Campbell32). The mechanisms underlying FM reduction following HIIT are not fully known; despite this, one of the most probable ones is an increase in the excess post-exercise oxygen consumption (EPOC), also known as HIIT-induced EPOC, which is unique to this form of exercise(Reference Boutcher33). In a study investigating the EPOC differences between continuous and interval training, the higher EPOC in interval training, in comparison with the continuous one, was detected, thus suggesting that the former led to more body fat loss for a given amount of energy expenditure. This also showed that the magnitude of EPOC and its duration depended on exercise intensity, which was much higher in the interval training(Reference Børsheim and Bahr34).

The second hypothesis regarding the effect of HIIT and CV on performance capacity was confirmed only for HIIT and HIIT plus CV supplementation, which significantly increased the Bruce MET, and relative and absolute VO2max levels. The synergistic effect of HIIT and CV on the Bruce MET was also observed. In the obese or overweight subjects, especially in those with central obesity, mechanical power was decreased, thus preventing the individuals from reaching the maximal ability in the VO2max test. Unbalanced body composition could also decrease VO2max in the obese subjects(Reference Alonso-Fernández, Fernández-Rodríguez and Taboada-Iglesias35).

Training intensity can determine the alteration in the electron transport system. On the other hand, the maximal electron transfer via flavoproteins can increase the fat oxidation(Reference Pesta, Hoppel and Macek36). In the present study, HIIT increased the absolute VO2max up to 14 %. Although VO2max was increased in response to the HIIT (more common in training up to 60 min with more than 65 % intensity), according to physiological improvements, the skeletal muscle respiratory capacity was increased primarily in the fat oxidation capacity area(Reference Jacobs, Díaz and Meinild37).

Consistent with the present study, the results obtained from a systematic review indicated that 2 to 15 weeks HIIT in healthy young and older adults significantly increased VO2max (from 4 % to 46 %). While the mechanisms of HIIT that lead to modulating this aerobic fitness improvement are unclear, the most likely one is phosphocreatine degradation during these intervals. The major energy source for this kind of exercise is ATP; repeated intervals in HIIT can lead to the progressive increase in oxidative ATP generation(Reference Putman, Jones and Lands38). Due to the short period of high-intensity exercise with rest intervals in HIIT, local metabolic capacities including creatine phosphate, ATP and mitochondrial enzymes can supply the growing energy demands, and the recovery times may compensate the depleted energy. Another probable mechanism of HIIT is related to the increased stroke volume that is induced by cardiac contractility enhancement, mitochondrial oxidative capacity improvement and skeletal muscle diffusive ability(Reference Slørdahl, Wang and Hoff39). This aerobic capacity encasement is also related to AMP-mediated PGC-1α up-regulation, which is responsible for oxidative adaptation and the remarkable increase in the maximal oxygen uptake after HIIT(Reference Harmer, Chisholm and McKenna40).

The synergistic effect of CV supplementation on HIIT is probably due to the decreased FM. In other words, the significant improvement in body composition that resulted from CV supplementation led to an increase in energy expenditure during the exercise. Considering that obese or overweight individuals often experience cell hunger, which is a kind of malnourishment, CV with a variety of nutrients can also compensate this deficiency and increase the aerobic capacity(Reference Umemoto and Otsuki41).

The third hypothesis was that HIIT and CV might improve the serum levels of PGC-1α, SIRT-1 and FGF-21 as the mitochondrial biogenesis indicators. Our interventions did not result in any statistically significant improvement in SIRT-1 and FGF-21 v. placebo; despite this, we did demonstrate the efficacy of using CV in enhancing the PGC-1α level in combination with exercise. Antioxidant stimulus may be required to go along with training to stimulate PGC-1α, as the previous studies had demonstrated that an antioxidant compound could be useful to up-regulate the gene expression of PGC-1α during exercise(Reference Azhar, Parmar and Miller42,Reference Ferrara, Joksimovic and D’Angelo43,Reference Ghasemi, Afzalpour and Nayebifar20) . Overall, for HIIT or CV supplementation to have enough efficacy on mitochondrial biogenesis, it should be intervened for a time interval longer than that used in the current study. In addition, the lack of a significant effect on mitochondrial biogenesis parameters following CV or HIIT was presumably due to the within-normal range of baseline values among the participants.

No study had yet investigated the combined effect of CV and HIIT on the mitochondrial biogenesis; despite this, there are some studies on the individual effect of CV or HIIT. PGC-1α has been considered as the main contributor to oxidative adaptation following exercise; the recent studies have also shown that the acute HIIT can increase PGC-1α mRNA(Reference Lee, Lee and Jung44). In a study on obese individuals, the 12-week HIIT intervention induced an approximately threefold increase in PGC-1α (Reference Za’don, Kamal and Ismail45). In another study, subjects performed normal intensity training for 4 weeks; this was then followed by 40 sessions of HIIT, twice, in a daily manner, for 20 consecutive days; however, there was no significant change in the nuclear or cytosolic content of PGC-1α. The authors cited the much larger number of training sessions and a more reduction in the relative exercise intensity between the pre- and post-HIIT trials as a possible reason for the insignificant changes in PGC-1α (Reference Granata, Oliveira and Little46).

In the present study, SIRT-1 change, after 8 weeks of HIIT and/or CV, was insignificant; this was similar to the results of another study on recreationally active men under a 6-week low-volume HIIT(Reference Scribbans, Edgett and Vorobej47). However, in the study done by Little et al., the 2 weeks HIIT significantly enhanced the SIRT-1content. Similar to our results, Jasmin et al. showed a significant increase in PGC-1α, without any marked change in SIRT-1 level following the 4-week HIIT(Reference Ma, Scribbans and Edgett48). In another study, the 6-week HIIT increased the mitochondrial enzymes activity, PGC-1α and SIRT-1(Reference Gurd, Perry and Heigenhauser49).

While obesity can increase FGF-21, a browning mediator in the adipose tissue, exercise may reduce its level; nevertheless, neither HIIT nor CV caused a significant change in plasma FGF-21 in the current study. In the study of some overweight and obese young men, a 6-week HIIT did not lead to any significant changes in FGF-21. In contrast, the 8-week HIIT in the obese men decreased FGF-21 along with insulin resistance(Reference Azali Alamdari and Khalafi50). Surprisingly, in another study on sedentary obese women, the same intervention resulted in a significant increase in FGF-21(Reference Toloueiazar, Tofighi and Alizadeh51). These discrepancies may be related to the much greater difference in exercise protocols and its duration, the baseline physical fitness of the individuals, health status, and sex. In the muscle cells, PGC-1α expression is induced in response to Ca signalling by Ca2+/calmodulin-dependent protein kinase 4 (CaKMIV) and calcineurin A (CnA). Phosphorylation of CaMKIV and the subsequent activation of the cAMP response element (CRE)-binding protein (CREB) can stimulate PGC-1α expression during exercise(Reference Fernandez-Marcos and Auwerx52). On the other hand, phosphorylation of activated protein kinase (AMPK) can not only directly activate PGC-1α but may also cause SIRT1-mediated PGC-1α activation(Reference Cantó, Gerhart-Hines and Feige53). The activation of this pathway results in the adipocyte size reduction, lipid oxidation in mitochondria and mitochondrial density increment, which can all promote the max oxygen consumption(Reference Torma, Gombos and Jokai54). The other exercise-induced mechanism for PGC-1α expression is the activation of p38 mitogen-activated protein kinase (p38 MAPK)(Reference Zhao, New and Kravchenko55).

Strengths and limitations

The regular attendance of subjects in exercise sessions and individualised exercise protocol according to the max HR and in compliance with supplementation can be assumed as the strengths of this study. However, there were some limitations as well. We did not have any access to dual-energy X-ray absorptiometry as the gold standard for body composition measurements; therefore, BIA was applied to measure body composition. Further, BIA has been previously validated; so, it was strongly consistent with the results obtained from dual-energy X-ray absorptiometry. Although participants were asked to maintain their regular diets and physical activities, it was not unlikely that they had manipulated their regular life style according to our intervention. Moreover, mitochondrial biogenesis consists of many blood and muscle markers that cannot be assessed because of the financial restrictions. For example, AMPK, calmodulin and PPAR can be assessed as upstream and downstream factors to determine the regulating pathways or muscle biopsies for the fibres alteration assessment.

Conclusion

The present study, for the first time, provided strong evidence showing the effects of HIIT and/or CV on the body composition, performance parameters and mitochondrial biogenesis in the obese women. It seems that HIIT plus CV could reduce body fat percentage, without any synergistic effect of CV and HIIT. Using CV in combination with HIIT also resulted in a marginal significant increase in PGC-1α level and body water compared with placebo group. There were significant increases in the Bruce MET in HIIT plus CV and HIIT plus placebo compared with placebo group. Beside this, the synergistic effect of CV and HIIT on the Bruce MET increment was found. Furthermore, CV + HIIT and HIIT groups displayed a significant increase in relative VO2max and absolute VO2max, as compared with the placebo; nevertheless, the synergistic effects of CV and HIIT on these parameters were not significant. No significant changes were, however, observed in BMI, FFM, visceral fat, SIRT-1 and FGF-21. These results may, thus, provide new options in the recommended exercise approach for the subjects seeking better performance and body composition. Longer-term clinical trials are also warranted with endpoints associated with mitochondrial adaptation.

Acknowledgements

The authors thank all participants taking part in this study. This article was got from a PhD thesis with a registered number at Tabriz University of Medical Sciences. The results of the study are presented clearly and honestly, without fabrication, falsification or inappropriate data manipulation; they do not constitute endorsement by ACSM.

The present study was funded by the vice chancellor for research at Tabriz University of Medical Sciences (grant number 61691). Founders had, however, no role in the design, analysis or writing of this article.

M. S. contributed to the conception, design, statistical analysis and drafting of the manuscript. A. B. helped in designing and drafting the manuscript, as well as supervising the study. R. A. also supervised the exercise program and F. H. S. contributed to the statistical analysis and manuscript drafting. All authors approved the final version for submission.

None of the authors had any conflict of interest.

Supplementary material

For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S0007114521003287

References

Bellissimo, M, Fleischer, C, Tran, P, et al. (2019) Mitochondrial bioenergetic metabolism is associated with total body composition and influenced by normal weight obesity (P21–039–19). Curr Dev Nutr 3, nzz041.CrossRefGoogle Scholar
Vakifahmetoglu-Norberg, H, Ouchida, AT & Norberg, E (2017) The role of mitochondria in metabolism and cell death. Biochem Biophys Res Commun 482, 426431.CrossRefGoogle ScholarPubMed
Kohrt, WM, Malley, MT, Coggan, AR, et al. (1991) Effects of gender, age, and fitness level on response of VO2max to training in 60–71 years old. J Appl Physiol 71, 20042011.CrossRefGoogle Scholar
Warburton, DE, Nicol, CW & Bredin, SS (2006) Health benefits of physical activity: the evidence. CMAJ 174, 801809.CrossRefGoogle ScholarPubMed
Bishop, DJ, Botella, J, Genders, AJ, et al. (2019) High-intensity exercise and mitochondrial biogenesis: current controversies and future research directions. Physiology 34, 5670.CrossRefGoogle ScholarPubMed
Gerhart-Hines, Z, Rodgers, JT, Bare, O, et al. (2007) Metabolic control of muscle mitochondrial function and fatty acid oxidation through SIRT1/PGC-1α . EMBO J 26, 19131923.CrossRefGoogle ScholarPubMed
Tang, BL (2016) Sirt1 and the mitochondria. Mol Cell 39, 87.Google ScholarPubMed
Ji, K, Zheng, J, Lv, J, et al. (2015) Skeletal muscle increases FGF21 expression in mitochondrial disorders to compensate for energy metabolic insufficiency by activating the mTOR–YY1–PGC1α pathway. Free Radical Biol Med 84, 161170.CrossRefGoogle ScholarPubMed
Civitarese, AE, Carling, S, Heilbronn, LK, et al. (2007) Calorie restriction increases muscle mitochondrial biogenesis in healthy humans. PLoS Med 4, e76.CrossRefGoogle ScholarPubMed
Little, JP, Safdar, A, Wilkin, GP, et al. (2010) A practical model of low-volume high-intensity interval training induces mitochondrial biogenesis in human skeletal muscle: potential mechanisms. J Physiol 588, 10111022.CrossRefGoogle ScholarPubMed
Thompson, WR (2019) Worldwide survey of fitness trends for 2020. ACSM’s Health Fitness J 23, 1018.CrossRefGoogle Scholar
Wewege, M, Van Den Berg, R, Ward, R, et al. (2017) The effects of high-intensity interval training v. moderate-intensity continuous training on body composition in overweight and obese adults: a systematic review and meta-analysis. Obes Rev 18, 635646.CrossRefGoogle Scholar
Shete, AN, Bute, SS & Deshmukh, PR (2014) A study of VO2 max and body fat percentage in female athletes. J Clin Diagnostic Res: JCDR 8, BC01BC03.Google ScholarPubMed
Valero, T (2014) Editorial (thematic issue: mitochondrial: mitochondrial biogenesis: pharmacological: pharmacological approaches) Curr Pharm Des 20, 55075509.CrossRefGoogle Scholar
Lee, SH, Kang, HJ, Lee, H-J, et al. (2010) Six-week supplementation with Chlorella has favorable impact on antioxidant status in Korean male smokers. Nutrition 26, 175183.CrossRefGoogle ScholarPubMed
Ebrahimi-Mameghani, M, Sadeghi, Z, Farhangi, MA, et al. (2017) Glucose homeostasis, insulin resistance and inflammatory biomarkers in patients with non-alcoholic fatty liver disease: beneficial effects of supplementation with microalgae Chlorella vulgaris: a double-blind placebo-controlled randomized clinical trial. Clin Nutr 36, 10011006.CrossRefGoogle ScholarPubMed
Panahi, Y, Badeli, R, Karami, G-R, et al. (2015) A randomized controlled trial of 6-week Chlorella vulgaris supplementation in patients with major depressive disorder. Complementary Ther Med 23, 598602.CrossRefGoogle ScholarPubMed
Panahi, Y, Pishgoo, B, Jalalian, HR, et al. (2012) Investigation of the effects of Chlorella vulgaris as an adjunctive therapy for dyslipidemia: results of a randomised open-label clinical trial. Nutr Diet 69, 1319.CrossRefGoogle Scholar
Fabregat-Andrés, Ó, Ridocci-Soriano, F, Estornell-Erill, J, et al. (2015) Blood PGC-1α concentration predicts myocardial salvage and ventricular remodeling after ST-segment elevation acute myocardial infarction. Rev Española Cardiología 68, 408416.CrossRefGoogle ScholarPubMed
Ghasemi, E, Afzalpour, ME & Nayebifar, S (2020) Combined high-intensity interval training and green tea supplementation enhance metabolic and antioxidant status in response to acute exercise in overweight women. J Physiol Sci 70, 19.CrossRefGoogle ScholarPubMed
Luong, MW, Ignaszewski, M & Taylor, C (2016) Stress testing: a contribution from Dr Robert A. Bruce, father of exercise cardiology. Br Columbia Med J 58, 7076.Google Scholar
Mizoguchi, T, Takehara, I, Masuzawa, T, et al. (2008) Nutrigenomic studies of effects of Chlorella on subjects with high-risk factors for lifestyle-related disease. J Med Food 11, 395404.CrossRefGoogle ScholarPubMed
Li, Y, Cui, Y, Hu, X, et al. (2019) Chlorophyll supplementation in early life prevents diet-induced obesity and modulates gut microbiota in mice. Mol Nutr Food Res 63, 1801219.CrossRefGoogle ScholarPubMed
Seo, Y-J, Kim, K-J, Choi, J, et al. (2018) Spirulina maxima extract reduces obesity through suppression of adipogenesis and activation of browning in 3T3-L1 cells and high-fat diet-induced obese mice. Nutrients 10, 712.CrossRefGoogle ScholarPubMed
Bonet, ML, Canas, JA, Ribot, J, et al. (2015) Carotenoids and their conversion products in the control of adipocyte function, adiposity and obesity. Arch Biochem Biophys 572, 112125.CrossRefGoogle ScholarPubMed
Mounien, L, Tourniaire, F & Landrier, J-F (2019) Anti-obesity effect of carotenoids: direct impact on adipose tissue and adipose tissue-driven indirect effects. Nutrients 11, 1562.CrossRefGoogle ScholarPubMed
Akhlaghi, M, Ghobadi, S, Hosseini, MM, et al. (2018) Flavanols are potential anti-obesity agents, a systematic review and meta-analysis of controlled clinical trials. NutrMetab Cardiovasc Dis 28, 675690.CrossRefGoogle ScholarPubMed
Akhlaghi, M & Kohanmoo, A (2018) Mechanisms of anti-obesity effects of catechins: a review. Int J Nutr Sci 3, 127132.Google Scholar
Chin, EC, Yu, AP, Lai, CW, et al. (2020) Low-frequency HIIT improves body composition and aerobic capacity in overweight men. Med Sci Sport Exerc 52, 5666.CrossRefGoogle ScholarPubMed
Ismail, I, Keating, S, Baker, M, et al. (2012) A systematic review and meta-analysis of the effect of aerobic v. resistance exercise training on visceral fat. Obes Rev 13, 6891.CrossRefGoogle Scholar
Most, J & Redman, LM (2020) Impact of calorie restriction on energy metabolism in humans. Exp Gerontol 133, 110875.CrossRefGoogle ScholarPubMed
Kerksick, C, Thomas, A, Campbell, B, et al. (2009) Effects of a popular exercise and weight loss program on weight loss, body composition, energy expenditure and health in obese women. Nutr Metab 6, 117.CrossRefGoogle ScholarPubMed
Boutcher, SH (2011) High-intensity intermittent exercise and fat loss. J of Obes 2011, 868305.CrossRefGoogle ScholarPubMed
Børsheim, E & Bahr, R (2003) Effect of exercise intensity, duration and mode on post-exercise oxygen consumption. Sport Med 33, 10371060.CrossRefGoogle ScholarPubMed
Alonso-Fernández, D, Fernández-Rodríguez, R, Taboada-Iglesias, Y, et al. (2019) Impact of a HIIT protocol on body composition and VO2max in adolescents. Sci Sport 34, 341347.CrossRefGoogle Scholar
Pesta, D, Hoppel, F, Macek, C, et al. (2011) Similar qualitative and quantitative changes of mitochondrial respiration following strength and endurance training in normoxia and hypoxia in sedentary humans. Am J Physiology-Regulatory, Integr Comparative Physiol 301, R1078R1087.CrossRefGoogle ScholarPubMed
Jacobs, RA, Díaz, V, Meinild, AK, et al. (2013) The C57Bl/6 mouse serves as a suitable model of human skeletal muscle mitochondrial function. Exp Physiol 98, 908921.CrossRefGoogle ScholarPubMed
Putman, C, Jones, N, Lands, L, et al. (1995) Skeletal muscle pyruvate dehydrogenase activity during maximal exercise in humans. Am J Physiol-Endocrinol Metab 269, E458E468.CrossRefGoogle ScholarPubMed
Slørdahl, SA, Wang, E, Hoff, J, et al. (2005) Effective training for patients with intermittent claudication. Scand Cardiovasc J 39, 244249.CrossRefGoogle ScholarPubMed
Harmer, AR, Chisholm, DJ, McKenna, MJ, et al. (2008) Sprint training increases muscle oxidative metabolism during high-intensity exercise in patients with type 1 diabetes. Diabetes Care 31, 20972102.CrossRefGoogle ScholarPubMed
Umemoto, S & Otsuki, T (2014) Chlorella-derived multicomponent supplementation increases aerobic endurance capacity in young individuals. J of Clin Biochem Nutr 55, 143146.CrossRefGoogle ScholarPubMed
Azhar, Y, Parmar, A, Miller, CN, et al. (2016) Phytochemicals as novel agents for the induction of browning in white adipose tissue. Nutr Metab 13, 111.CrossRefGoogle ScholarPubMed
Ferrara, L, Joksimovic, M & D’Angelo, S (2021) Modulation of mitochondrial biogenesis: action of physical activity and phytochemicals. J Physical Educ Sport 21, 425433.Google Scholar
Lee, MC, Lee, SK, Jung, SY, et al. (2018) New insight of high-intensity interval training on physiological adaptation with brain functions. J Exerc Nutr Biochem 22, 1.Google Scholar
Za’don, NHA, Kamal, A, Ismail, F, et al. (2019) High-intensity interval training induced PGC-1α and Adipor1 gene expressions and improved insulin sensitivity in obese individuals. Med J Malaysia 74, 461467.Google Scholar
Granata, C, Oliveira, RS, Little, JP, et al. (2020) Forty high-intensity interval training sessions blunt exercise-induced changes in the nuclear protein content of PGC-1α and p53 in human skeletal muscle. Am J Physiol-Endocrinol Metab 318, E224E236.CrossRefGoogle ScholarPubMed
Scribbans, TD, Edgett, BA, Vorobej, K, et al. (2014) Fibre-specific responses to endurance and low volume high intensity interval training: striking similarities in acute and chronic adaptation. PloS One 9, e98119.CrossRefGoogle ScholarPubMed
Ma, JK, Scribbans, TD, Edgett, BA, et al. (2013) Extremely low-volume, high-intensity interval training improves exercise capacity and increases mitochondrial protein content in human skeletal muscle. Open J Mol Integr Physiol 3, 9.Google Scholar
Gurd, BJ, Perry, CG, Heigenhauser, GJ, et al. (2010) High-intensity interval training increases SIRT1 activity in human skeletal muscle. Appl Physiol Nutr Metab 35, 350357.CrossRefGoogle ScholarPubMed
Azali Alamdari, K & Khalafi, M (2019) The effects of high intensity interval training on serum levels of FGF21 and insulin resistance in obese men. Iranian J Diabetes Metab 18, 4148.Google Scholar
Toloueiazar, J, Tofighi, A & Alizadeh, R (2019) The effect of high intensity interval training on serum levels of FGF21, insulin resistance and lipid profile in sedentary obese women. J Sport Biosci 10, 449464.Google Scholar
Fernandez-Marcos, PJ & Auwerx, J (2011) Regulation of PGC-1α, a nodal regulator of mitochondrial biogenesis. Am J Clin Nutr 93, 884S890S.CrossRefGoogle ScholarPubMed
Cantó, C, Gerhart-Hines, Z, Feige, JN, et al. (2009) AMPK regulates energy expenditure by modulating NAD+ metabolism and SIRT1 activity. Nature 458, 10561060.CrossRefGoogle ScholarPubMed
Torma, F, Gombos, Z, Jokai, M, et al. (2019) High intensity interval training and molecular adaptive response of skeletal muscle. Sports Med Health Sci 1, 2432.CrossRefGoogle ScholarPubMed
Zhao, M, New, L, Kravchenko, VV, et al. (1999) Regulation of the MEF2 family of transcription factors by p38. Mol Cell Biol 19, 2130.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Flow diagram of study participants.

Figure 1

Table 1. Body composition characteristics of study participants at baseline and after 8 weeks of intervention(Mean values and standard deviations; mean difference and 95 % confidence interval)

Figure 2

Table 2. Mitochondrial biogenesis factors of study participants at baseline and after 8 weeks of intervention(Mean values and standard deviations; mean difference and 95 % confidence interval)

Figure 3

Table 3. Performance parameters of study participants at baseline and after 8 weeks of intervention(Mean values and standard deviations; mean difference and 95 % confidence interval)

Figure 4

Table 4. Training programme in 8 weeks

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