The Effect of 12 Weeks of High Intensity Functional Training (HIFT) on Serum Mitokine and Metabolic Risk Factors in Patients with Metabolic Syndrome: A Randomized Control Trial

The Effect of 12 Weeks of High Intensity Functional Training (HIFT) on Serum Mitokine and Metabolic Risk Factors in Patients with Metabolic Syndrome: A Randomized Control Trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Effect of 12 Weeks of High Intensity Functional Training (HIFT) on Serum Mitokine and Metabolic Risk Factors in Patients with Metabolic Syndrome: A Randomized Control Trial Rasoul Eslami, Mohammad Moayedi, Bakhtiar Tartibian, Ali Aeen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8220619/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background Metabolic syndrome is a disease related to mitochondrial dysfunction. Mitokines such as FGF21 and GDF15, recognized as biomarkers associated with metabolic stress, play crucial roles in regulating energy and inflammation. This study aimed to investigate the effects of High-Intensity Functional Training (HIFT) on the serum levels of FGF21 and GDF15, metabolic risk factors and body composition in middle-aged men with metabolic syndrome. Methods In a randomized controlled trial, 24 men (age = 42.40 ± 6.90 years) with metabolic syndrome were randomly assigned to either the HIFT group or the control group. The HIFT group performed exercise sessions twice a week for 12 weeks, and each session lasted 50–60 minutes. Anthropometric and biochemical assessments were conducted before and after the intervention. Results After the intervention, the FGF21 and GDF15 levels significantly decreased in the HIFT group (P = 0.001). Furthermore, body fat percentage, fasting blood glucose, HbA1c, blood lipids, and LDL-C decreased, whereas skeletal muscle mass and HDL increased (P < 0.001, for all). Conclusion HIFT improved metabolic health by modulating the serum levels of mitokines, metabolic risk factors and body composition. Therefore, this type of training can be recommended as an effective nonpharmacological intervention for prevention and treatment of patients with metabolic syndrome. Trial registry Iranian Registry of Clinical Trials identifier: IRCT20241130063899N1, prospectively registered 10-11- 2025, https://irct.behdasht.gov.ir/trial/80642 Metabolic Syndrome Mitokine Functional Training Figures Figure 1 Figure 2 Figure 3 Introduction Metabolic syndrome (MetS) is a multifaceted metabolic disorder comprising a cluster of risk factors, such as central obesity, dyslipidemia, elevated blood pressure, and insulin resistance, that significantly increase the risk of type 2 diabetes (T2DM) and cardiovascular disease (CVD) (Alberti et al., 2005 ; Motillo et al., 2010 ). The prevalence of this syndrome is increasing worldwide, including in Iran, where factors such as genetics, unhealthy diet, sedentary lifestyle, and rising obesity play significant roles in its onset (Noori et al., 2007 ; DeBoer et al., 2018). In recent years, the role of mitochondrial dysfunction in the pathophysiology of metabolic diseases has gained increasing attention. Mitochondria, as cellular energy production centers, play a vital role in regulating glucose and lipid metabolism and inflammatory responses (Gutierrez et al., 2014 ). Under conditions of metabolic stress, a set of circulating proteins and peptides known as mitokines are secreted. These compounds function similarly to hormones and effectively regulate energy, inflammation, and cellular function (Conte et al., 2018 ; Kim et al., 2015 ). Among the most important mitokines are Fibroblast Growth Factor 21 (FGF21) and Growth Differentiation Factor 15 (GDF15). Fibroblast Growth Factor 21 is primarily secreted by the liver and activates signaling pathways such as the AMPK and PI3K/AKT pathways through FGFR receptors and the β-Klotho cofactor, leading to increased insulin sensitivity and the regulation of energy metabolism (Kharitonenkov et al., 2005 ; Landry et al., 2021). On the other hand, GDF15, which belongs to the TGF-β family, plays a role in regulating inflammatory responses, cell proliferation, and metabolic stress via the SMAD pathway (Britto et al., 2021 ). Elevated levels of these mitokines in disease conditions are considered a compensatory response of the body to metabolic disorders. However, studies have shown that regular physical activity can modulate the levels of these markers and improve metabolic indices (Chang & Namkung, 2021 ; Vizvari and Kovacs, 2018 ). High Intensity Functional Training (HIFT) is a modern training method that combines aerobic, resistance, and functional movements in an interval format. Simultaneous stimulation of anabolic (AKT/mTOR), energy regulatory (AMPK/PGC-1α), and anti-inflammatory pathways can have positive effects on metabolic health (Smith et al., 2022a ; Feito et al., 2018 ). Previous studies have shown that high-intensity combined training can reduce FGF21 and GDF15 levels, improve body composition, increase muscle mass, and reduce insulin resistance (Chang & Namkung, 2021 ; Liu et al., 2024 ). A study by Małkowska et al. ( 2025 ) revealed that trained individuals had lower levels of FGF21 and GDF15 than untrained individuals did, indicating reduced metabolic stress and improved mitochondrial function. Additionally, recent studies have indicated that HIFT can effectively improve body composition. In a study by Cavedon et al. ( 2020 ), participants with more than 10 hours per week of HIFT experience had a significant decrease in body fat percentage and an increase in lean muscle mass. However, the precise impact of HIFT on these markers in populations with metabolic syndrome has not been fully investigated. Therefore, the aim of the present study was to investigate the effects of 12 weeks of HIFT on mitokines (FGF21 and GDF15), metabolic risk factors and body composition in middle-aged men with metabolic syndrome. Accordingly, the research hypothesis was that these exercise training models improve the levels of mitochondrial dysfunction markers (FGF-21, GDF-15) involved in metabolic syndrome in middle-aged men with metabolic syndrome. We also hypothesize that this improvement will coincide with better metabolic health and body composition. Methods Study design This was a randomized controlled trial (two-group design with pretest and posttest) conducted among patients with metabolic syndrome in Tehran, Iran. The experimental procedures and study protocols were approved by the ethics committee (code: IR.ATU.REC.1402.029), and all stages were conducted in accordance with the Helsinki Declaration. To ensure comprehensive and transparent reporting of the study design and results, CONSORT reporting guidelines were used (Iranian Registry of Clinical Trials identifier: IRCT20241130063899N1, https://irct.behdasht.gov.ir/trial/80642). To determine the number of participants, G*Power analysis software was used. Participants were identified through public announcements in medical centers and specialized clinics. Patient referrals were made by treating physicians, and diagnosis confirmation was based on the study's inclusion and exclusion criteria. The inclusion criteria were as follows: no regular physical activity (less than 30 minutes per day, 3 times a week, for 3 months) and the presence of at least 3 out of 5 criteria for diagnosing metabolic syndrome: 1- Central obesity: waist circumference ≥102 cm; 2- Dyslipidemia: TG ≥150 mg/dL; 3- HDL-C <40 mg/dL; 4- Blood pressure ≥130/85 mmHg; and 5- Fasting plasma glucose ≥110 mg/dL (Grundy et al., 2005). The exclusion criteria included individuals with chronic heart diseases (e.g., heart failure or ischemic or coronary artery diseases), pulmonary diseases (e.g., COPD or severe asthma), active cognitive or psychiatric disorders, musculoskeletal or joint injuries limiting physical activity, and a history of advanced renal or hepatic diseases. Additionally, individuals who experienced new clinical symptoms or exercise-related complications during the intervention period were withdrawn from the study (Galván et al., 2025). After initial screening, eligible individuals were selected as research samples. The purpose and procedures of the research were subsequently fully explained to the volunteers. They were then asked to sign an informed consent form if they agreed to participate. Only those who signed the consent form, met the entry criteria, and had none of the exclusion criteria were accepted as final participants in the study. Eligible participants were randomly assigned to either a control group (n=12) or a HIFT group (n=12) through a simple randomization procedure, using a computer-generated random sequence. The initial demographic characteristics of the participants in dif­ferent groups are shown in Table 1. Table 1. Demographic characteristics of subjects with different groups in initial state. HIFT ( n =12) (mean±SD) Control ( n =12) (mean±SD) 43.00±8.27 41.80 ± 5.61 Age (years) 86.90±17.01 99.19±13.29 Weight (kg) 28.87±4.42 30.31±2.94 BMI (kg/m 2 ) 29.28±4.66 29.92±5.53 Body Fat (%) 39.32±5.90 33.76±6.04 SMM (kg) HIFT: High Intensity Functional Training, SMM: Skeletal muscle mass, BMI: Body mass index Participants in the control group were advised to maintain their normal lifestyle and keep a logbook to record physical activity during the study period. The experimental group performed HIFT exercises for 12 weeks. Anthropometric measurements, body composition, and blood sampling (after overnight fasting) were performed 24 hours before the first training session and 48 hours after the completion of the training program. The participants were asked not to change their lifestyle or diet during the study. A schematic of the study design is presented in Fig. 1. Anthropometric indices and body composition Standing height, waist circumference, and hip circumference were measured via a tape meter. An Inbody770 machine (Model: Zuse 9.9, South Korea) was used to measure weight, body mass index (BMI), body fat percentage (BFP), and skeletal muscle mass (SMM). Blood sampling and analysis One day before starting the training protocols and 48 hours after the last training session, blood samples (5 ml) were drawn from the antecubital vein in a fasting state (12 hours fasting) at a specific time of day. Vacutainer tubes containing a clot activator and a serum separator gel were used for sample collection. The samples were left at room temperature for 5 minutes to complete clotting. The samples were then centrifuged at 3000×g for 10 minutes and stored in cryovials at -20°C. The enzyme-linked immunosorbent assay (ELISA) method was used to measure the serum levels of FGF21 and GDF-15. All factors were assessed by ELISA via a ZellBio Germany kit with the following catalog numbers: FGF21: ZB-11983C-H9648; GDF15: ZB-10037C-H9648. Measurement of metabolic indices The serum glucose concentration was measured via the enzymatic-colorimetric GOD-PAP method with commercial Pars Azmun kits (Tehran, Iran) on an autoanalyzer. The intra-assay coefficient of variation for this method was reported to be less than 2.2%. Triglyceride (TG) and total cholesterol levels were measured via enzymatic-colorimetric methods (GPO-PAP and CHOD-PAP, respectively), and HDL and LDL values were determined via direct enzymatic methods via commercial Pars Azmun kits (Tehran, Iran) on an autoanalyzer. The intra- and interassay coefficients of variation for these tests were reported to be less than 3%. HIFT protocol In this study, participants in the training group performed HIFT training twice a week for 12 weeks. The 12-week training program consisted of three 4-week phases. In each phase, exercise duration, intensity, volume, and recovery time gradually increased, and in the final week of each phase, the training volume decreased by 60–70% (Turner, 2011; Murach & Bagley, 2015). Each training session included a 10-minute warm-up (5 minutes of jogging or brisk walking and 5 minutes of low-intensity active movements and stretching), followed by four sets of HIFT exercises. Each set included four movements from different categories in the following order: aerobic exercise, lower body strength, upper body strength, and core strength exercises (Smith et al., 2022a,b). Exercises were designed on the basis of the AMRAP (As Many Rounds As Possible) system, and exercise intensity was controlled using the RPE scale (at a level ≥7-10). Heart rate (HR) and the session Rating of Perceived Exertion (sRPE) were recorded after each set (Crawford et al., 2018). The duration of each exercise bout was initially 6 minutes, with 3 minutes of rest between them (work:rest ratio of 1:2). In subsequent weeks, exercise time increased, but the work:rest ratio remained constant. The tempo of movements was controlled, with one second for the concentric phase and two seconds for the eccentric phase. The total time of each training session, including warm-up and cool-down, was less than 60 minutes (Smith et al., 2022a,b) (Tables 2, 3, and 4). All training protocol was executed by an exercise physiologist. Table 2. High-Intensity Functional Training (HIFT) Protocol Rest time Exercise time Exercise description Exercise time(m) 8 min Dynamic exercises Warm up 1-8 min 3 min 6 min Jumping Jacks, Goblet Squat, Push-Up, Russian Twist Amrap Set1 9-16 min 3 min 6 min Skaters, Lunge, TRX Row, Plank Amrap Set 2 19-25 min 3 min 6 min High knees, Deadlift, Overhead Press, Bicycle Crunch Amrap Set 3 28-34 min 3 min 6 min Kickboxers, Box Step-Ups, Bent-Over Row, Exercise Ball Crunches Amrap Set 4 37-43 min 5 min Cool down 43-48 min Table 3. Progression Characteristics of the 12-Week Training Period Sets Rest Interval (min) Work Interval (min) Work: Rest Ratio Recovery Time (min) Exercise Time (min) Total Duration (min) Weeks Phase 4 3 6 2 : 1 12 24 36 Week 1-3 Phase 1 4 2 4 2 : 1 8 16 24 Week 4 Phase 1 4 3 6.5 2.5:1 12 26 38 Week 5-7 Phase 2 4 2 4.5 2.5:1 8 18 26 Week 8 Phase 2 4 2.5 7 3:1 10 28 38 Week 9-11 Phase 3 4 1.5 5 3:1 6 20 26 Week 12 Phase 3 Table 4. Examples of HIFT exercises in each Category Category Exercises Aerobic Jumping Jacks, Skaters, High Knees Jog, Fast Feet with Box, Kickboxers, Jumping Jack Tuck, Burpees Lower Body Strength Goblet Squat, Lunge, Curtsy Lunge, Jump Squat, Deadlift, Box Step-Ups, Back/Front Squat, Wall Sit, TRX Pistol Squat, Jump Tuck Upper Body Strength TRX Chest Press, Push-Up, TRX Row, TRX Biceps Curl, Overhead Press, TRX Triceps Dips, TRX Chest Fly, Lateral/Front Raise, Bent-Over Row, Negative Push-Ups Abdominal/Core Strength Plank, Plank Knee Drives, Side Plank, Russian Twist, Bicycle Crunch, Lateral Bends, Log Lifts, Farmers Carry, TRX Plank Roll-Out, Exercise Ball Crunches, Aero Frog Hops Statistical methods The number of participants was estimated via G*Power analysis software (version 3.1). On the basis of α = 0.05 and a power (1 − β) of 0.80, the sample size needed for this project to detect significant changes in the blood factors between groups was at least 30 participants (n=15 for each group). The normality of the data was assessed via the Shapiro‒Wilk test. To examine between‑group differences following the 12‑week training program, the ANCOVA test was used, where the pretest was used as a covariate factor. All analyses were performed via SPSS (version 21). Statistical significance was accepted if p ≤ 0.05. Results Participants One month before the program started, 168 elderly individuals were screened for eligibility. Based on the study's inclusion criteria, 50 non-athlete men with metabolic syndrome were recruited. All participants provided informed consent. However, 20 individuals withdrew their consent and decided not to participate before the study began (Fig. 1 ). Additionally, due to personal reasons, several other eligible candidates declined to take part in the exercise intervention. Consequently, only those who voluntarily agreed to join were enrolled in the final participant group. Therefore, Eligible participants were randomly assigned to either a control group (n = 12) or a HIFT group (n = 12). Body composition indices ANCOVA was performed to examine differences in post-test scores between the HIFT and control groups, adjusting for pre-test scores. For weight, there was a significant effect of group on post-test scores after controlling for pre-test performance [F(1, 23) = 79.135, P < 0.001, partial η² =0.82]. HIFT training also had a significant effect on BMI [F(1, 23) = 97.10, P < 0.001, partial η²=0.85], fat percentage [F(1, 23) = 81.80, P < 0.001, partial η² =0.82), and muscle mass [F(1, 23) = 45.68, P < 0.001, partial η² =0.72] (Table 2 ). Therefore, HIFT could decrease weight, BMI, and fat percentage while increasing muscle mass in men with metabolic syndrome. Table 5 Body composition statistical analysis results Variables Time Control ( n = 12) (mean ± SD) HIFT ( n = 12) (mean ± SD) ANCOVA test (group difference) P value Weight (kg) Pre : Post : 86.90 ± 17.01 87.85 ± 17.25 99.19 ± 13.29 95.80 ± 12.29 *P < 0.001 Eta-s quared = 0.823 BMI (kg/m 2 ) Pre : Post : 28.87 ± 4.42 29.13 ± 4.52 30.31 ± 2.94 29.20 ± 2.73 *P < 0.001 Eta-squared = 0.851 Fat percent (%) Pre : Post : 29.28 ± 4.66 30.07 ± 4.73 29.92 ± 5.53 27.23 ± 4.97 *P < 0.001 Eta-squared = 0.828 Muscle mass (kg) Pre : Post : 33.76 ± 6.04 33.82 ± 5.94 39.32 ± 5.90 41.91 ± 6.09 *P < 0.001 Eta-squared = 0.729 *: Significant difference between groups Mitokine factors For Mitokine factors, ANCOVA was conducted to assess the effect of HIFT training on FGF-21 and GDF-15 serum levels, with baseline as the covariate. A significant difference was found between the two groups for FGF-21 [F(1, 23) = 97.54, P < 0.001, η2 = 0.852] and GDF-15 [F(1, 23) = 93.09, P < 0.001, η2 = 0.846] (Fig. 2 ). Metabolic indices Compared with the results of the control group, our results revealed that HIFT can decrease fasting blood glucose [F(1, 23) = 6.33, p = 0.022, η2 = 0.272], HbA1c [F(1, 23) = 26.852, P < 0.001, η2 = 0.599], cholesterol [F(1, 23) = 50.77, P < 0.001, η2 = 0.749], triglycerides [F(1, 23) = 58.18, P < 0.001, η2 = 0.774], and LDL-c [F(1, 23) = 60.35, P < 0.001, η2 = 0.780], whereas HDL-c was increased [F(1, 23) = 44.57, P < 0.001, η2 = 0.724] (Fig. 3 ). Discussion To the best of our knowledge, this is the first study to investigate the effects of high-intensity functional training (HIFT) on mitokines and related metabolic risk factors in patients with metabolic syndrome. Our hypotheses were confirmed: A 12-week HIFT intervention led to a significant reduction in the serum levels of the mitokines FGF-21 and GDF-15, alongside an improvement in metabolic risk factors (blood glucose, cholesterol, TG, LDL, and HDL) in patients with metabolic syndrome. Mitokines are recognized as emerging biomarkers for assessing inflammatory status and mitochondrial function and play crucial roles in regulating energy and stress responses and metabolic health (Zhang et al., 2024 ). From a biological perspective, GDF-15, a cytokine responsive to metabolic and inflammatory stress, increases under conditions such as insulin resistance, tissue damage, and mitochondrial disorders (Britto et al., 2021 ). Its reduction following exercise may indicate decreased systemic inflammation, improved pancreatic beta-cell function, and better-regulated energy homeostasis. In the present study, the decrease in GDF-15 was likely due to improved mitochondrial function, reduced oxidative load, and modulation of the GDF15–GFRAL–RET axis—a pathway recently identified as key in regulating appetite, lipid, and glucose metabolism (Landry & Smith, 2021 ). In this context, numerous studies have been conducted on the improvement of mitokines through exercise training, most of which have yielded results that are consistent with the present findings. For example, Moghaddami et al. (2019) reported that 12 weeks of moderate-intensity aerobic training significantly reduced GDF-15 levels and insulin resistance in elderly women. Furthermore, a study by Chang and Namkung ( 2021 ) revealed that a 12-week combined exercise program led to a reduction in circulating GDF-15 levels and improved physical fitness in patients with metabolic syndrome. These changes were associated with decreased insulin resistance and increased skeletal muscle mass, indicating the regulatory role of combined exercise in inflammatory and metabolic pathways. Furthermore, GDF-15 activates the SMAD signaling pathway by binding to type I (ALK4/7) and type II (ActRII/ActRIIB) serine/threonine kinase receptors. In this pathway, SMAD2 and SMAD3 are phosphorylated, then form a complex with SMAD4 and translocate to the cell nucleus. The resulting complex regulates the expression of target genes involved in processes such as the stress response, inflammation, metabolism, and cell proliferation (Ibáñez, 2021 ). From this perspective, the reduction in serum GDF-15 levels following the exercise intervention in the present study may indicate reduced stimulation of inflammatory pathways or an improved metabolic status in individuals with metabolic syndrome (Britto et al., 2021 ). The present study also revealed that 12 weeks of HIFT significantly reduced serum FGF-21 levels compared with those in the control group. FGF21 is primarily secreted by liver cells and plays a key role in regulating energy, glucose, and lipid metabolism (Chen et al., 2022 ). By binding to FGFR1c receptors and the β-Klotho cofactor, it activates intracellular signaling pathways such as the AMPK and PI3K/AKT pathways, leading to increased insulin sensitivity, reduced lipogenesis, and increased lipolysis (Yang et al., 2023 ). In metabolic syndrome, FGF21 levels are typically elevated, which is considered a compensatory response to insulin resistance and chronic inflammation (Zhang et al., 2025 ). Exercise interventions, particularly high-intensity interval training such as HIFT, can increase FGF21 receptor sensitivity, reduce metabolic stress, and contribute to better-regulated energy homeostasis (Yang et al., 2023 ). Interestingly, other studies have also demonstrated a reduction in the expression of FGF-21, a marker of mitochondrial stress, following exercise training. For example, Chang and Namkung ( 2021 ) reported that a 12-week combined aerobic and resistance exercise program significantly reduced serum FGF21 levels in women with metabolic syndrome. These changes were associated with improved insulin resistance, increased skeletal muscle mass, and reduced leptin levels, indicating the efficacy of combined training in modulating pathways related to inflammation, mitochondrial function, and energy metabolism. Additionally, a systematic review and meta-analysis by Liu et al. ( 2024 ) revealed that concurrent training (combining aerobic and resistance exercise), particularly programs lasting more than 10 weeks, led to a significant reduction in FGF21 levels in adults. This reduction was specifically observed in individuals with obesity, type 2 diabetes, and nonalcoholic fatty liver disease and was associated with improved cardiovascular health indicators; increased muscle strength; and reductions in body weight, BMI, and body fat percentage. From a metabolic standpoint, the reduction in FGF21 following regular moderate- to high-intensity exercise was associated with improvements in biological profiles, including glucose, insulin, HOMA-IR, HbA1c, cholesterol, triglycerides, HDL, LDL, and FFAs. These findings suggest that the expression of FGF21, a hormone responsive to metabolic stress, increases in disease states and that its reduction after exercise training may be an indicator of improved liver function, energy regulation, and reduced systemic inflammation. Dun et al. (2019) demonstrated that high-intensity interval training (HIIT) was more effective than moderate-intensity continuous training (MICT) in improving metabolic syndrome indicators and body composition in cardiac patients. In that study, HIIT led to significant reductions in waist circumference, fasting blood glucose, triglycerides, and diastolic blood pressure, whereas MICT did not produce significant changes. In the present study, the reduction in FGF21 levels following high-intensity HIFT was also associated with improved body composition, blood glucose, and lipid profiles. Our training design, which incorporated aerobic and resistance stimuli within a high-intensity functional framework, likely activated energy regulation pathways (AMPK/PGC-1α) and anabolic pathways (AKT/mTOR) and reduced inflammatory signaling (Zhang et al., 2025 ). This alignment with the findings of Liu et al. strengthens the validity of our results and highlights FGF21 as a reliable biomarker for assessing the efficacy of exercise interventions. Most studies examining the effects of exercise training on mitokines have concurrently reported improvements in body composition (reduced fat, increased muscle mass, improved BMI) and lipid profiles (Chang & Namkung, 2021 ; Liu et al., 2024 ; Dun et al., 2019). The findings of the present study are consistent with these results; participants experienced significant improvements in blood glucose, body composition (reduced fat, increased muscle mass), and lipid profile (reduced cholesterol, TG, and LDL; increased HDL) following the HIFT protocol. The multifaceted structure of HIFT, which includes functional movements, resistance, and interval training, appears to simultaneously stimulate aerobic and anaerobic pathways, thereby facilitating the concurrent activation of the anabolic (AKT/mTOR) and energy regulation (AMPK/PGC-1α) pathways (Smith et al., 2022a ). By applying intermittent and multifaceted stress to energy systems, HIFT was able to concurrently reduce body fat, increase lean muscle mass, and improve the lipid profile and blood glucose. These characteristics highlight the importance of multimodal exercise design in improving metabolic syndrome and establish HIFT as an effective option for its management. This study has several limitations that should be considered when interpreting the results. The relatively small sample size and the restriction of participants to middle-aged men limit the generalizability of the findings. Furthermore, complete control over diet and other lifestyle factors was not feasible. Therefore, future research should investigate the effects of HIFT in more diverse populations, such as women, elderly individuals, and patients with varying degrees of metabolic syndrome. A direct comparison of HIFT with other training methods, such as HIIT, moderate-intensity continuous training (MICT), or isolated resistance training, could provide a more precise assessment of its relative efficacy. Interventions longer than 12 weeks are necessary to examine the sustainability of biological and functional changes. Additionally, stricter control of variables such as nutrition, sleep, and other lifestyle aspects would allow for a more precise analysis of the independent effects of HIFT. Conclusion In general, the findings of this study revealed that 12 weeks of high-intensity functional training (HIFT) in middle-aged men with metabolic syndrome led to a significant reduction in serum mitokine levels and concurrent improvements in blood glucose levels, lipid profiles, and body composition. These changes likely reflect the positive effects of HIFT on improving metabolic status and reducing insulin resistance in patients, which are likely mediated through the modulation of pathways related to inflammation, oxidative stress, and energy regulation, which are typically altered in disease states. Ultimately, these findings suggest that HIFT can be considered an effective nonpharmacological approach for the prevention and rehabilitation of metabolic syndrome. Limitations and suggestions Among the limitations of this study were the small sample size and the restriction to middle-aged men. Future studies should investigate the effects of this type of training on women and different age groups. Additionally, examining the long-term effects of HIFT and its impact on other inflammatory and metabolic biomarkers could provide deeper insights into the underlying mechanisms involved. Declarations Acknowledgments The authors would like to thank all the participants in this study. Author contributions Dr. Rasoul Eslami, Mohammad Moayedi, and Dr. Bakhtyar Tartibian conceived and designed research. Mohammad Moayedi and Dr. Ali Aeen recruited the subjects and conducted the performance tests and body composition test. Mohammad Moayedi trained the subjects. Dr. Rasoul Eslami and Dr. Ali Aeen interpreted results of experiments. Dr. Rasoul Eslami analyzed data. Mohammad Moayedi prepared figures and tables. Mohammad Moayedi Wrote the manuscript. Dr. Rasoul Eslami and Dr. Bakhtyar Tartibian edited and revised manuscript. Dr. Rasoul Eslami and Dr. Bakhtyar Tartibian approved final version of manuscript. Funding This work is based upon research funded by the Iran National Science Foundation (INSF) under project No. 4025997. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate The experimental procedures and study protocols were approved by the Ethics Committee of Allameh Tabataba’i University: https://ethics.research.ac.ir/EthicsProposalView.php?&code=IR.ATU.REC.1402.029 Informed consent was obtained. All experimentation was carried out in accordance with the Declaration of Helsinki. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Authors’ information RE: RE has a Ph.D. in exercise physiology and He is an associate professor of physical education and sport science college of Allameh Tabataba’i University. His research interest is in neuromuscular adaptation to exercise training and he is the chief of a health center at Allameh Tabataba’i University. MM: A researcher who recently received his Master’s degree in Exercise Physiology from Allameh Tabaaba’i University. His research focuses on studying mechanisms related to skeletal muscle mass and function and how exercise training, nutrition and other stimuli could affect them. BT: BT has a Ph.D. in exercise physiology and He is a professor of physical education and sport science college of Allameh Tabataba’i University. His research is on exercise nutrition, exercise immunology, and investigating the effect of exercise at the cellular and molecular levels. AA: AA has a Ph.D. in medical science and He is a professor of medical science college of Isfahan Medical Science University. His research is on health, metabolic disorder, and investigating the effect of nondrug methods at the cellular and molecular levels. 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1","display":"","copyAsset":false,"role":"figure","size":162763,"visible":true,"origin":"","legend":"\u003cp\u003eA schematic of the study design. Anthropometric, Body composition, blood tests were performed before and after of the intervention with 8h of fasting at 9 – 10 AM. Abbreviations: HIFT: High Intensity Functional training, C: control, H: height, W: weight, BMI: Body mass index, BFP: Body fat percentage, SMM, skeletal muscle mass, FGF-21: Fibroblast Growth Factor-21, GDF-15: growth differentiation factor 15.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8220619/v1/5333d237c4fbf9a54a205f7f.png"},{"id":100070320,"identity":"033c5aaf-d14e-4b17-9bda-b46a1204e12a","added_by":"auto","created_at":"2026-01-12 16:17:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15787,"visible":true,"origin":"","legend":"\u003cp\u003eFGF-21 and GDF-15 contents in the two groups (HIFT and Control) before and after training.\u003c/p\u003e\n\u003cp\u003e*: significant difference between the training group andthe control group.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8220619/v1/8a53f5f277e5101bb263fbdd.png"},{"id":100070384,"identity":"8124e1b1-e815-4b6a-b0b2-64698454831d","added_by":"auto","created_at":"2026-01-12 16:17:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":34820,"visible":true,"origin":"","legend":"\u003cp\u003eFasting Blood Glucose (FBS), Cholesterol, Triglyceride, LDL-c and HDL-c contents in the two groups (HIFT and Control) before and after training.\u003c/p\u003e\n\u003cp\u003e*: a significant difference in the training group compared with the control group\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8220619/v1/83b92154d0ba949d8a86fff3.png"},{"id":100070977,"identity":"cfd4ce2c-bf52-4b3b-b070-caae228efc8f","added_by":"auto","created_at":"2026-01-12 16:18:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":974781,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8220619/v1/d6a6fd2b-3a1a-439e-a30b-c7d1d7780db8.pdf"},{"id":100070403,"identity":"d4549dcc-6e6a-4871-b048-c044f080cdd3","added_by":"auto","created_at":"2026-01-12 16:17:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":32723,"visible":true,"origin":"","legend":"","description":"","filename":"CONSORT2025editablechecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-8220619/v1/79b0b4d084f2249482764f3c.docx"},{"id":100070494,"identity":"a7cc3920-066f-4513-a46d-4a4138a22101","added_by":"auto","created_at":"2026-01-12 16:17:55","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":596721,"visible":true,"origin":"","legend":"","description":"","filename":"IRCTwebpagepicture.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8220619/v1/31d6b3ef38a73281630cdba2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Effect of 12 Weeks of High Intensity Functional Training (HIFT) on Serum Mitokine and Metabolic Risk Factors in Patients with Metabolic Syndrome: A Randomized Control Trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMetabolic syndrome (MetS) is a multifaceted metabolic disorder comprising a cluster of risk factors, such as central obesity, dyslipidemia, elevated blood pressure, and insulin resistance, that significantly increase the risk of type 2 diabetes (T2DM) and cardiovascular disease (CVD) (Alberti et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Motillo et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The prevalence of this syndrome is increasing worldwide, including in Iran, where factors such as genetics, unhealthy diet, sedentary lifestyle, and rising obesity play significant roles in its onset (Noori et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; DeBoer et al., 2018).\u003c/p\u003e \u003cp\u003eIn recent years, the role of mitochondrial dysfunction in the pathophysiology of metabolic diseases has gained increasing attention. Mitochondria, as cellular energy production centers, play a vital role in regulating glucose and lipid metabolism and inflammatory responses (Gutierrez et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Under conditions of metabolic stress, a set of circulating proteins and peptides known as mitokines are secreted. These compounds function similarly to hormones and effectively regulate energy, inflammation, and cellular function (Conte et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Among the most important mitokines are Fibroblast Growth Factor 21 (FGF21) and Growth Differentiation Factor 15 (GDF15). Fibroblast Growth Factor 21 is primarily secreted by the liver and activates signaling pathways such as the AMPK and PI3K/AKT pathways through FGFR receptors and the β-Klotho cofactor, leading to increased insulin sensitivity and the regulation of energy metabolism (Kharitonenkov et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Landry et al., 2021). On the other hand, GDF15, which belongs to the TGF-β family, plays a role in regulating inflammatory responses, cell proliferation, and metabolic stress via the SMAD pathway (Britto et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Elevated levels of these mitokines in disease conditions are considered a compensatory response of the body to metabolic disorders. However, studies have shown that regular physical activity can modulate the levels of these markers and improve metabolic indices (Chang \u0026amp; Namkung, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vizvari and Kovacs, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHigh Intensity Functional Training (HIFT) is a modern training method that combines aerobic, resistance, and functional movements in an interval format. Simultaneous stimulation of anabolic (AKT/mTOR), energy regulatory (AMPK/PGC-1α), and anti-inflammatory pathways can have positive effects on metabolic health (Smith et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Feito et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Previous studies have shown that high-intensity combined training can reduce FGF21 and GDF15 levels, improve body composition, increase muscle mass, and reduce insulin resistance (Chang \u0026amp; Namkung, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A study by Małkowska et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) revealed that trained individuals had lower levels of FGF21 and GDF15 than untrained individuals did, indicating reduced metabolic stress and improved mitochondrial function. Additionally, recent studies have indicated that HIFT can effectively improve body composition. In a study by Cavedon et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), participants with more than 10 hours per week of HIFT experience had a significant decrease in body fat percentage and an increase in lean muscle mass. However, the precise impact of HIFT on these markers in populations with metabolic syndrome has not been fully investigated. Therefore, the aim of the present study was to investigate the effects of 12 weeks of HIFT on mitokines (FGF21 and GDF15), metabolic risk factors and body composition in middle-aged men with metabolic syndrome. Accordingly, the research hypothesis was that these exercise training models improve the levels of mitochondrial dysfunction markers (FGF-21, GDF-15) involved in metabolic syndrome in middle-aged men with metabolic syndrome. We also hypothesize that this improvement will coincide with better metabolic health and body composition.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a randomized controlled trial (two-group design with pretest and posttest) conducted among patients with metabolic syndrome in Tehran, Iran. The experimental procedures and study protocols were approved by the ethics committee (code: IR.ATU.REC.1402.029), and all stages were conducted in accordance with the Helsinki Declaration. To ensure comprehensive and transparent reporting of the study design and results, CONSORT reporting guidelines were used (Iranian Registry of Clinical Trials identifier: IRCT20241130063899N1, https://irct.behdasht.gov.ir/trial/80642).\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eTo determine the number of participants, G*Power analysis software was used. Participants were identified through public announcements in medical centers and specialized clinics. Patient referrals were made by treating physicians, and diagnosis confirmation was based on the study\u0026apos;s inclusion and exclusion criteria. The inclusion criteria were as follows: no regular physical activity (less than 30 minutes per day, 3 times a week, for 3 months) and the presence of at least 3 out of 5 criteria for diagnosing metabolic syndrome: 1- Central obesity: waist circumference \u0026ge;102 cm; 2- Dyslipidemia: TG \u0026ge;150 mg/dL; 3- HDL-C \u0026lt;40 mg/dL; 4- Blood pressure \u0026ge;130/85 mmHg; and 5- Fasting plasma glucose \u0026ge;110 mg/dL (Grundy et al., 2005). The exclusion criteria included individuals with chronic heart diseases (e.g., heart failure or ischemic or coronary artery diseases), pulmonary diseases (e.g., COPD or severe asthma), active cognitive or psychiatric disorders, musculoskeletal or joint injuries limiting physical activity, and a history of advanced renal or hepatic diseases. Additionally, individuals who experienced new clinical symptoms or exercise-related complications during the intervention period were withdrawn from the study (Galv\u0026aacute;n et al., 2025).\u003c/p\u003e\n\u003cp\u003eAfter initial screening, eligible individuals were selected as research samples. The purpose and procedures of the research were subsequently fully explained to the volunteers. They were then asked to sign an informed consent form if they agreed to participate. Only those who signed the consent form, met the entry criteria, and had none of the exclusion criteria were accepted as final participants in the study.\u0026nbsp;Eligible participants were randomly assigned to either\u0026nbsp;a control group (n=12) or a HIFT group (n=12)\u0026nbsp;through a simple randomization procedure,\u0026nbsp;using a computer-generated random sequence. The initial demographic characteristics of the participants in dif\u0026shy;ferent groups are shown in Table 1.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable dir=\"rtl\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eDemographic characteristics of subjects with different groups in initial state.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.145%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHIFT (\u003cem\u003en\u003c/em\u003e=12)\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(mean\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2443%;\"\u003e\n \u003cp dir=\"LTR\"\u003eControl (\u003cem\u003en\u003c/em\u003e=12)\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(mean\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.6107%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.145%;\"\u003e\n \u003cp dir=\"LTR\"\u003e43.00\u0026plusmn;8.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2443%;\"\u003e\n \u003cp dir=\"LTR\"\u003e41.80 \u0026plusmn; 5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.6107%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.145%;\"\u003e\n \u003cp dir=\"LTR\"\u003e86.90\u0026plusmn;17.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2443%;\"\u003e\n \u003cp dir=\"LTR\"\u003e99.19\u0026plusmn;13.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.6107%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eWeight (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.145%;\"\u003e\n \u003cp dir=\"LTR\"\u003e28.87\u0026plusmn;4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2443%;\"\u003e\n \u003cp dir=\"LTR\"\u003e30.31\u0026plusmn;2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.6107%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.145%;\"\u003e\n \u003cp dir=\"LTR\"\u003e29.28\u0026plusmn;4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2443%;\"\u003e\n \u003cp dir=\"LTR\"\u003e29.92\u0026plusmn;5.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.6107%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eBody Fat (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.145%;\"\u003e\n \u003cp dir=\"LTR\"\u003e39.32\u0026plusmn;5.90\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2443%;\"\u003e\n \u003cp dir=\"LTR\"\u003e33.76\u0026plusmn;6.04\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.6107%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eSMM (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHIFT: High Intensity Functional Training, SMM: Skeletal muscle mass, BMI: Body mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eParticipants in the control group were advised to maintain their normal lifestyle and keep a logbook to record physical activity during the study period. The experimental group performed HIFT exercises for 12 weeks. Anthropometric measurements, body composition, and blood sampling (after overnight fasting) were performed 24 hours before the first training session and 48 hours after the completion of the training program. The participants were asked not to change their lifestyle or diet during the study. A schematic of the study design is presented in Fig. 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnthropometric indices and body composition\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Standing height, waist circumference, and hip circumference were measured via a tape meter. An Inbody770 machine (Model: Zuse 9.9, South Korea) was used to measure weight, body mass index (BMI), body fat percentage (BFP), and skeletal muscle mass (SMM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood sampling and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne day before starting the training protocols and 48 hours after the last training session, blood samples (5 ml) were drawn from the antecubital vein in a fasting state (12 hours fasting) at a specific time of day. Vacutainer tubes containing a clot activator and a serum separator gel were used for sample collection. The samples were left at room temperature for 5 minutes to complete clotting. The samples were then centrifuged at 3000\u0026times;g for 10 minutes and stored in cryovials at -20\u0026deg;C.\u003c/p\u003e\n\u003cp\u003eThe enzyme-linked immunosorbent assay (ELISA) method was used to measure the serum levels of FGF21 and GDF-15. All factors were assessed by ELISA via a ZellBio Germany kit with the following catalog numbers: FGF21: ZB-11983C-H9648; GDF15: ZB-10037C-H9648.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of metabolic indices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe serum glucose concentration was measured via the enzymatic-colorimetric GOD-PAP method with commercial Pars Azmun kits (Tehran, Iran) on an autoanalyzer. The intra-assay coefficient of variation for this method was reported to be less than 2.2%.\u003cbr\u003e\u0026nbsp;Triglyceride (TG) and total cholesterol levels were measured via enzymatic-colorimetric methods (GPO-PAP and CHOD-PAP, respectively), and HDL and LDL values were determined via direct enzymatic methods via commercial Pars Azmun kits (Tehran, Iran) on an autoanalyzer. The intra- and interassay coefficients of variation for these tests were reported to be less than 3%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHIFT protocol\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, participants in the training group performed HIFT training twice a week for 12 weeks. The 12-week training program consisted of three 4-week phases. In each phase, exercise duration, intensity, volume, and recovery time gradually increased, and in the final week of each phase, the training volume decreased by 60\u0026ndash;70% (Turner, 2011; Murach \u0026amp; Bagley, 2015). Each training session included a 10-minute warm-up (5 minutes of jogging or brisk walking and 5 minutes of low-intensity active movements and stretching), followed by four sets of HIFT exercises. Each set included four movements from different categories in the following order: aerobic exercise, lower body strength, upper body strength, and core strength exercises (Smith et al., 2022a,b).\u003cbr\u003e\u0026nbsp;Exercises were designed on the basis of the AMRAP (As Many Rounds As Possible) system, and exercise intensity was controlled using the RPE scale (at a level \u0026ge;7-10). Heart rate (HR) and the session Rating of Perceived Exertion (sRPE) were recorded after each set (Crawford et al., 2018). The duration of each exercise bout was initially 6 minutes, with 3 minutes of rest between them (work:rest ratio of 1:2). In subsequent weeks, exercise time increased, but the work:rest ratio remained constant. The tempo of movements was controlled, with one second for the concentric phase and two seconds for the eccentric phase. The total time of each training session, including warm-up and cool-down, was less than 60 minutes (Smith et al., 2022a,b) (Tables 2, 3, and 4). All training protocol was executed by an exercise physiologist. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. High-Intensity Functional Training (HIFT) Protocol\u003c/p\u003e\n\u003cdiv align=\"right\"\u003e\n \u003ctable dir=\"rtl\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003eRest time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003eExercise time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"LTR\"\u003eExercise description\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eExercise time(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eDynamic exercises\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWarm up\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e1-8 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"LTR\"\u003eJumping Jacks, Goblet Squat, Push-Up, Russian Twist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAmrap Set1\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e9-16 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSkaters, Lunge, TRX Row, Plank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAmrap Set 2\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;19-25 min\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHigh knees, Deadlift, Overhead Press, Bicycle Crunch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAmrap Set 3\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e28-34 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"LTR\"\u003eKickboxers, Box Step-Ups, Bent-Over Row, Exercise Ball Crunches\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAmrap Set 4\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e37-43 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9831%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8305%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.0085%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.178%;\"\u003e\n \u003cp dir=\"LTR\"\u003eCool down\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e43-48 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Progression Characteristics of the 12-Week Training Period\u003c/p\u003e\n\u003cdiv align=\"right\"\u003e\n \u003ctable dir=\"rtl\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003eRest Interval (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWork Interval (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWork: Rest Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003eRecovery Time (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003eExercise Time (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTotal Duration (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003cspan dir=\"RTL\"\u003e:\u003c/span\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeek 1-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003cspan dir=\"RTL\"\u003e:\u003c/span\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeek \u0026nbsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;2.5:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeek 5-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;2.5:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeek \u0026nbsp;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeek 9-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9568%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4585%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.794%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1296%;\"\u003e\n \u003cp dir=\"LTR\"\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9635%;\"\u003e\n \u003cp dir=\"LTR\"\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.13621%;\"\u003e\n \u003cp dir=\"LTR\"\u003eWeek 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.13953%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePhase 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable 4. Examples of HIFT exercises in each Category\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75%;\"\u003e\n \u003cp\u003eExercises\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAerobic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75%;\"\u003e\n \u003cp\u003eJumping Jacks, Skaters, High Knees Jog, Fast Feet with Box, Kickboxers, Jumping Jack Tuck, Burpees\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eLower Body Strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75%;\"\u003e\n \u003cp\u003eGoblet Squat, Lunge, Curtsy Lunge, Jump Squat, Deadlift, Box Step-Ups, Back/Front Squat, Wall Sit, TRX Pistol Squat, Jump Tuck\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eUpper Body Strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75%;\"\u003e\n \u003cp\u003eTRX Chest Press, Push-Up, TRX Row, TRX Biceps Curl, Overhead Press, TRX Triceps Dips, TRX Chest Fly, Lateral/Front Raise, Bent-Over Row, Negative Push-Ups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAbdominal/Core Strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75%;\"\u003e\n \u003cp\u003ePlank, Plank Knee Drives, Side Plank, Russian Twist, Bicycle Crunch, Lateral Bends, Log Lifts, Farmers Carry, TRX Plank Roll-Out, Exercise Ball Crunches, Aero Frog Hops\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe number of participants was estimated via G*Power analysis software (version 3.1). On the basis of \u0026alpha; = 0.05 and a power (1 \u0026minus; \u0026beta;) of 0.80, the sample size needed for this project to detect significant changes in the blood factors between groups was at least 30 participants (n=15 for each group). The normality of the data was assessed via the Shapiro‒Wilk test. To examine between‑group differences following the 12‑week training program, the ANCOVA test was used, where the pretest was used as a covariate factor. All analyses were performed via SPSS (version 21). Statistical significance was accepted if p \u0026le; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eOne month before the program started, 168 elderly individuals were screened for eligibility. Based on the study\u0026apos;s inclusion criteria, 50 non-athlete men with metabolic syndrome were recruited. All participants provided informed consent. However, 20 individuals withdrew their consent and decided not to participate before the study began (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, due to personal reasons, several other eligible candidates declined to take part in the exercise intervention. Consequently, only those who voluntarily agreed to join were enrolled in the final participant group. Therefore, Eligible participants were randomly assigned to either a control group (n\u0026thinsp;=\u0026thinsp;12) or a HIFT group (n\u0026thinsp;=\u0026thinsp;12).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eBody composition indices\u003c/h2\u003e\n \u003cp\u003eANCOVA was performed to examine differences in post-test scores between the HIFT and control groups, adjusting for pre-test scores. For weight, there was a significant effect of group on post-test scores after controlling for pre-test performance [F(1, 23)\u0026thinsp;=\u0026thinsp;79.135, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, partial \u0026eta;\u0026sup2; =0.82]. HIFT training also had a significant effect on BMI [F(1, 23)\u0026thinsp;=\u0026thinsp;97.10, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, partial \u0026eta;\u0026sup2;=0.85], fat percentage [F(1, 23)\u0026thinsp;=\u0026thinsp;81.80, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, partial \u0026eta;\u0026sup2; =0.82), and muscle mass [F(1, 23)\u0026thinsp;=\u0026thinsp;45.68, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, partial \u0026eta;\u0026sup2; =0.72] (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Therefore, HIFT could decrease weight, BMI, and fat percentage while increasing muscle mass in men with metabolic syndrome.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBody composition statistical analysis results\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables Time\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHIFT (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eANCOVA test\u003c/p\u003e\n \u003cp\u003e(group difference)\u003c/p\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg) Pre\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePost\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.90\u0026thinsp;\u0026plusmn;\u0026thinsp;17.01\u003c/p\u003e\n \u003cp\u003e87.85\u0026thinsp;\u0026plusmn;\u0026thinsp;17.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.19\u0026thinsp;\u0026plusmn;\u0026thinsp;13.29\u003c/p\u003e\n \u003cp\u003e95.80\u0026thinsp;\u0026plusmn;\u0026thinsp;12.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003eEta-s quared\u0026thinsp;=\u0026thinsp;0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) Pre\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePost\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.87\u0026thinsp;\u0026plusmn;\u0026thinsp;4.42\u003c/p\u003e\n \u003cp\u003e29.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94\u003c/p\u003e\n \u003cp\u003e29.20\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003eEta-squared\u0026thinsp;=\u0026thinsp;0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFat percent (%) Pre\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePost\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.28\u0026thinsp;\u0026plusmn;\u0026thinsp;4.66\u003c/p\u003e\n \u003cp\u003e30.07\u0026thinsp;\u0026plusmn;\u0026thinsp;4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.53\u003c/p\u003e\n \u003cp\u003e27.23\u0026thinsp;\u0026plusmn;\u0026thinsp;4.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003eEta-squared\u0026thinsp;=\u0026thinsp;0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMuscle mass (kg) Pre\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePost\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.76\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e\n \u003cp\u003e33.82\u0026thinsp;\u0026plusmn;\u0026thinsp;5.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.90\u003c/p\u003e\n \u003cp\u003e41.91\u0026thinsp;\u0026plusmn;\u0026thinsp;6.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003eEta-squared\u0026thinsp;=\u0026thinsp;0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e*: Significant difference between groups\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eMitokine factors\u003c/h2\u003e\n \u003cp\u003eFor Mitokine factors, ANCOVA was conducted to assess the effect of HIFT training on FGF-21 and GDF-15 serum levels, with baseline as the covariate. A significant difference was found between the two groups for FGF-21 [F(1, 23)\u0026thinsp;=\u0026thinsp;97.54, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.852] and GDF-15 [F(1, 23)\u0026thinsp;=\u0026thinsp;93.09, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.846] (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eMetabolic indices\u003c/h2\u003e\n \u003cp\u003eCompared with the results of the control group, our results revealed that HIFT can decrease fasting blood glucose [F(1, 23)\u0026thinsp;=\u0026thinsp;6.33, p\u0026thinsp;=\u0026thinsp;0.022, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.272], HbA1c [F(1, 23)\u0026thinsp;=\u0026thinsp;26.852, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.599], cholesterol [F(1, 23)\u0026thinsp;=\u0026thinsp;50.77, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.749], triglycerides [F(1, 23)\u0026thinsp;=\u0026thinsp;58.18, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.774], and LDL-c [F(1, 23)\u0026thinsp;=\u0026thinsp;60.35, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.780], whereas HDL-c was increased [F(1, 23)\u0026thinsp;=\u0026thinsp;44.57, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.724] (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first study to investigate the effects of high-intensity functional training (HIFT) on mitokines and related metabolic risk factors in patients with metabolic syndrome. Our hypotheses were confirmed: A 12-week HIFT intervention led to a significant reduction in the serum levels of the mitokines FGF-21 and GDF-15, alongside an improvement in metabolic risk factors (blood glucose, cholesterol, TG, LDL, and HDL) in patients with metabolic syndrome.\u003c/p\u003e \u003cp\u003eMitokines are recognized as emerging biomarkers for assessing inflammatory status and mitochondrial function and play crucial roles in regulating energy and stress responses and metabolic health (Zhang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). From a biological perspective, GDF-15, a cytokine responsive to metabolic and inflammatory stress, increases under conditions such as insulin resistance, tissue damage, and mitochondrial disorders (Britto et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Its reduction following exercise may indicate decreased systemic inflammation, improved pancreatic beta-cell function, and better-regulated energy homeostasis. In the present study, the decrease in GDF-15 was likely due to improved mitochondrial function, reduced oxidative load, and modulation of the GDF15\u0026ndash;GFRAL\u0026ndash;RET axis\u0026mdash;a pathway recently identified as key in regulating appetite, lipid, and glucose metabolism (Landry \u0026amp; Smith, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this context, numerous studies have been conducted on the improvement of mitokines through exercise training, most of which have yielded results that are consistent with the present findings. For example, Moghaddami et al. (2019) reported that 12 weeks of moderate-intensity aerobic training significantly reduced GDF-15 levels and insulin resistance in elderly women. Furthermore, a study by Chang and Namkung (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) revealed that a 12-week combined exercise program led to a reduction in circulating GDF-15 levels and improved physical fitness in patients with metabolic syndrome. These changes were associated with decreased insulin resistance and increased skeletal muscle mass, indicating the regulatory role of combined exercise in inflammatory and metabolic pathways.\u003c/p\u003e \u003cp\u003eFurthermore, GDF-15 activates the SMAD signaling pathway by binding to type I (ALK4/7) and type II (ActRII/ActRIIB) serine/threonine kinase receptors. In this pathway, SMAD2 and SMAD3 are phosphorylated, then form a complex with SMAD4 and translocate to the cell nucleus. The resulting complex regulates the expression of target genes involved in processes such as the stress response, inflammation, metabolism, and cell proliferation (Ib\u0026aacute;\u0026ntilde;ez, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). From this perspective, the reduction in serum GDF-15 levels following the exercise intervention in the present study may indicate reduced stimulation of inflammatory pathways or an improved metabolic status in individuals with metabolic syndrome (Britto et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study also revealed that 12 weeks of HIFT significantly reduced serum FGF-21 levels compared with those in the control group. FGF21 is primarily secreted by liver cells and plays a key role in regulating energy, glucose, and lipid metabolism (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By binding to FGFR1c receptors and the β-Klotho cofactor, it activates intracellular signaling pathways such as the AMPK and PI3K/AKT pathways, leading to increased insulin sensitivity, reduced lipogenesis, and increased lipolysis (Yang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In metabolic syndrome, FGF21 levels are typically elevated, which is considered a compensatory response to insulin resistance and chronic inflammation (Zhang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Exercise interventions, particularly high-intensity interval training such as HIFT, can increase FGF21 receptor sensitivity, reduce metabolic stress, and contribute to better-regulated energy homeostasis (Yang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, other studies have also demonstrated a reduction in the expression of FGF-21, a marker of mitochondrial stress, following exercise training. For example, Chang and Namkung (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that a 12-week combined aerobic and resistance exercise program significantly reduced serum FGF21 levels in women with metabolic syndrome. These changes were associated with improved insulin resistance, increased skeletal muscle mass, and reduced leptin levels, indicating the efficacy of combined training in modulating pathways related to inflammation, mitochondrial function, and energy metabolism. Additionally, a systematic review and meta-analysis by Liu et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) revealed that concurrent training (combining aerobic and resistance exercise), particularly programs lasting more than 10 weeks, led to a significant reduction in FGF21 levels in adults. This reduction was specifically observed in individuals with obesity, type 2 diabetes, and nonalcoholic fatty liver disease and was associated with improved cardiovascular health indicators; increased muscle strength; and reductions in body weight, BMI, and body fat percentage.\u003c/p\u003e \u003cp\u003eFrom a metabolic standpoint, the reduction in FGF21 following regular moderate- to high-intensity exercise was associated with improvements in biological profiles, including glucose, insulin, HOMA-IR, HbA1c, cholesterol, triglycerides, HDL, LDL, and FFAs. These findings suggest that the expression of FGF21, a hormone responsive to metabolic stress, increases in disease states and that its reduction after exercise training may be an indicator of improved liver function, energy regulation, and reduced systemic inflammation. Dun et al. (2019) demonstrated that high-intensity interval training (HIIT) was more effective than moderate-intensity continuous training (MICT) in improving metabolic syndrome indicators and body composition in cardiac patients. In that study, HIIT led to significant reductions in waist circumference, fasting blood glucose, triglycerides, and diastolic blood pressure, whereas MICT did not produce significant changes. In the present study, the reduction in FGF21 levels following high-intensity HIFT was also associated with improved body composition, blood glucose, and lipid profiles. Our training design, which incorporated aerobic and resistance stimuli within a high-intensity functional framework, likely activated energy regulation pathways (AMPK/PGC-1α) and anabolic pathways (AKT/mTOR) and reduced inflammatory signaling (Zhang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This alignment with the findings of Liu et al. strengthens the validity of our results and highlights FGF21 as a reliable biomarker for assessing the efficacy of exercise interventions.\u003c/p\u003e \u003cp\u003eMost studies examining the effects of exercise training on mitokines have concurrently reported improvements in body composition (reduced fat, increased muscle mass, improved BMI) and lipid profiles (Chang \u0026amp; Namkung, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Dun et al., 2019). The findings of the present study are consistent with these results; participants experienced significant improvements in blood glucose, body composition (reduced fat, increased muscle mass), and lipid profile (reduced cholesterol, TG, and LDL; increased HDL) following the HIFT protocol. The multifaceted structure of HIFT, which includes functional movements, resistance, and interval training, appears to simultaneously stimulate aerobic and anaerobic pathways, thereby facilitating the concurrent activation of the anabolic (AKT/mTOR) and energy regulation (AMPK/PGC-1α) pathways (Smith et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). By applying intermittent and multifaceted stress to energy systems, HIFT was able to concurrently reduce body fat, increase lean muscle mass, and improve the lipid profile and blood glucose. These characteristics highlight the importance of multimodal exercise design in improving metabolic syndrome and establish HIFT as an effective option for its management.\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be considered when interpreting the results. The relatively small sample size and the restriction of participants to middle-aged men limit the generalizability of the findings. Furthermore, complete control over diet and other lifestyle factors was not feasible. Therefore, future research should investigate the effects of HIFT in more diverse populations, such as women, elderly individuals, and patients with varying degrees of metabolic syndrome. A direct comparison of HIFT with other training methods, such as HIIT, moderate-intensity continuous training (MICT), or isolated resistance training, could provide a more precise assessment of its relative efficacy. Interventions longer than 12 weeks are necessary to examine the sustainability of biological and functional changes. Additionally, stricter control of variables such as nutrition, sleep, and other lifestyle aspects would allow for a more precise analysis of the independent effects of HIFT.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn general, the findings of this study revealed that 12 weeks of high-intensity functional training (HIFT) in middle-aged men with metabolic syndrome led to a significant reduction in serum mitokine levels and concurrent improvements in blood glucose levels, lipid profiles, and body composition. These changes likely reflect the positive effects of HIFT on improving metabolic status and reducing insulin resistance in patients, which are likely mediated through the modulation of pathways related to inflammation, oxidative stress, and energy regulation, which are typically altered in disease states. Ultimately, these findings suggest that HIFT can be considered an effective nonpharmacological approach for the prevention and rehabilitation of metabolic syndrome.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and suggestions\u003c/h2\u003e \u003cp\u003eAmong the limitations of this study were the small sample size and the restriction to middle-aged men. Future studies should investigate the effects of this type of training on women and different age groups. Additionally, examining the long-term effects of HIFT and its impact on other inflammatory and metabolic biomarkers could provide deeper insights into the underlying mechanisms involved.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors would like to thank all the participants in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Rasoul Eslami, Mohammad Moayedi, and Dr. Bakhtyar Tartibian conceived and designed research. Mohammad Moayedi and Dr. Ali Aeen recruited the subjects and conducted the performance tests and body composition test. Mohammad Moayedi trained the subjects. Dr. Rasoul Eslami and Dr. Ali Aeen interpreted results of experiments. Dr. Rasoul Eslami analyzed data. Mohammad Moayedi prepared figures and tables. Mohammad Moayedi Wrote the manuscript. Dr. Rasoul Eslami and Dr. Bakhtyar Tartibian edited and revised manuscript. Dr. Rasoul Eslami and Dr. Bakhtyar Tartibian approved final version of manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is based upon research funded by\u0026nbsp;the\u0026nbsp;Iran National Science Foundation (INSF) under project No.\u0026nbsp;4025997.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental procedures and study protocols were approved by the Ethics Committee of Allameh Tabataba\u0026rsquo;i University:\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003ehttps://ethics.research.ac.ir/EthicsProposalView.php?\u0026amp;code=IR.ATU.REC.1402.029\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained. All experimentation was carried out in accordance with the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRE: RE has a Ph.D. in exercise physiology and He is an associate professor of physical education and sport science college of Allameh Tabataba\u0026rsquo;i University. His research interest is in neuromuscular adaptation to exercise training and he is the chief of a health center at Allameh Tabataba\u0026rsquo;i University.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMM: A researcher who recently received his Master\u0026rsquo;s degree in Exercise Physiology from Allameh Tabaaba\u0026rsquo;i University. His research focuses on studying mechanisms related to skeletal muscle mass and function and how exercise training, nutrition and other stimuli could affect them.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBT: BT has a Ph.D. in exercise physiology and He is a professor of physical education and sport science college of Allameh Tabataba\u0026rsquo;i University. His research is on exercise nutrition, exercise immunology, and investigating the effect of exercise at the cellular and molecular levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAA: AA has a Ph.D. in medical science and He is a professor of medical science college of Isfahan Medical Science University. His research is on health, metabolic disorder, and investigating the effect of nondrug methods at the cellular and molecular levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eI confirm that all authors have approved the manuscript for submission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe content of the manuscript has not been published, or submitted for publication elsewhere.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlberti, K. G. M. M., Zimmet, P., \u0026amp; Shaw, J. (2005). The metabolic syndrome\u0026mdash;a new worldwide definition. The Lancet, 366(9491), 1059\u0026ndash;1062. https://doi.org/10.1016/S0140-6736(05)67402-8\u003c/li\u003e\n\u003cli\u003eBritto, F. A., Cortade, F., \u0026amp; Ferry, A. (2021). Growth differentiation factor 15 in metabolic diseases: Emerging roles and mechanisms. Journal of Endocrinology, 250 (1), R1\u0026ndash;R15. https://doi.org/10.1530/JOE-21-0082\u003c/li\u003e\n\u003cli\u003eCavedon, V., Zancanaro, C., \u0026amp; Milanese, C. (2020). Physique and performance of CrossFit athletes. PLOS ONE, 15 (8), e0237887. https://doi.org/10.1371/journal.pone.0237887\u003c/li\u003e\n\u003cli\u003eChang, J. S., \u0026amp; Namkung, J. (2021). Effects of exercise intervention on mitochondrial stress biomarkers in metabolic syndrome patients: A randomized controlled trial. International Journal of Environmental Research and Public Health, 18 (5), 2242. https://doi.org/10.3390/ijerph18052242\u003c/li\u003e\n\u003cli\u003eChen, Z., Yang, L., Liu, Y., Huang, P., Song, H., \u0026amp; Zheng, P. (2022). The potential function and clinical application of FGF21 in metabolic diseases. Frontiers in Pharmacology, 13 , 1089214. https://doi.org/10.3389/fphar.2022.1089214\u003c/li\u003e\n\u003cli\u003eConte, M., Martucci, M., Mosconi, G., Chiariello, A., \u0026amp; Salvioli, S. (2018). Mitochondrial dysfunction in aging and metabolic diseases: A role for mitokines. Mechanisms of Aging and Development, 174 , 30\u0026ndash;36. https://doi.org/10.1016/j.mad.2018.02.004\u003c/li\u003e\n\u003cli\u003eCrawford, D. A., Drake, N. B., Carper, M. J., DeBlauw, J., \u0026amp; Heinrich, K. M. (2018). Validity, reliability, and application of the session-RPE method for quantifying training loads during high-intensity functional training. Sports, 6 (3), 84. https://doi.org/10.3390/sports6030084\u003c/li\u003e\n\u003cli\u003eFeito, Y., Hoffstetter, W., Serafini, P., \u0026amp; Mangine, G. (2018). Changes in body composition, bone metabolism, strength, and skill-specific performance resulting from 16-weeks of HIFT. PLOS ONE, 13 (6), e0198324. https://doi.org/10.1371/journal.pone.0198324\u003c/li\u003e\n\u003cli\u003eGalv\u0026aacute;n, B., Enriquez del Castillo, L. A., Flores, L. A., Quintana-Mendias, E., Torres-Rojo, F. I., Villegas-Balderrama, C. V., \u0026amp; Cervantes-Hern\u0026aacute;ndez, N. (2025). Effectiveness of physical exercise on indicators of metabolic syndrome in adults: A systematic review with meta-analysis of clinical trials. Journal of Functional Morphology and Kinesiology, 10 (3), 244. https://doi.org/10.3390/jfmk10030244\u003c/li\u003e\n\u003cli\u003eGrundy, S. M., Cleeman, J. I., Daniels, S. R., Donato, K. A., Eckel, R. H., Franklin, B. A., Gordon, D. J., Krauss, R. M., Savage, P. J., Smith, S. C., \u0026amp; Spertus, J. A. (2005). Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. 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N., \u0026amp; Lee, I. K. (2015). Role of fibroblast growth factor 21 in metabolic regulation and mitochondrial protection. Diabetologia, 58 (4), 809\u0026ndash;818. https://doi.org/10.1007/s00125-015-3505-z\u003c/li\u003e\n\u003cli\u003eLandry, T., \u0026amp; Smith, B. K. (2021). Fibroblast growth factor 21 and its role in metabolic syndrome: Mechanisms and therapeutic potential. Nature Metabolism, 3 (5), 567\u0026ndash;579. https://doi.org/10.1038/s42255-021-00388-6\u003c/li\u003e\n\u003cli\u003eLiu, Y., Zhang, Y., \u0026amp; Wang, L. (2024). Effects of concurrent exercise on FGF21 levels and metabolic health: A meta-analysis. Journal of Clinical Endocrinology \u0026amp; Metabolism, 109 (2), 456\u0026ndash;468. https://doi.org/10.1210/clinem/dgad508\u003c/li\u003e\n\u003cli\u003eMałkowska, A., Słomiński, P., \u0026amp; Zembron-Lacny, A. (2025). Exercise-induced changes in circulating levels of GDF15 and FGF21 in trained and untrained individuals. International Journal of Molecular Sciences, 26 (15), 7115. https://doi.org/10.3390/ijms26157115\u003c/li\u003e\n\u003cli\u003eMotillo, S., Filion, K. B., Genest, J., Joseph, L., Pilote, L., Poirier, P., Rinfret, S., Schiffrin, E. L., \u0026amp; Eisenberg, M. J. (2010). The metabolic syndrome and cardiovascular risk: A systematic review and meta-analysis. Journal of the American College of Cardiology, 56 (14), 1113\u0026ndash;1132. https://doi.org/10.1016/j.jacc.2010.05.034\u003c/li\u003e\n\u003cli\u003eMurach, K. A., \u0026amp; Bagley, J. R. (2015). Skeletal muscle hypertrophy with concurrent exercise training: Contrary evidence for an interference effect. Sports Medicine, 46 (8), 1029\u0026ndash;1039. https://doi.org/10.1007/s40279-015-0366-z\u003c/li\u003e\n\u003cli\u003eNoori, R., Heidari-Beni, M., \u0026amp; Ghaffari, M. (2007). Prevalence of metabolic syndrome and its components in Iranian adults: A population-based study. Iranian Journal of Endocrinology and Metabolism, 9 (4), 315\u0026ndash;323.\u003c/li\u003e\n\u003cli\u003ePerformance Health. (2024). Jamar Hydraulic Hand Dynamometer. Retrieved October 26, 2024, from https://www.performancehealth.com/jamar-hydraulic-hand-dynamometer\u003c/li\u003e\n\u003cli\u003eSmith, L. E., Van Guilder, G. P., Dalleck, L. C., \u0026amp; Harris, N. K. (2022b). The effects of a single session of high-intensity functional training on energy expenditure, VO₂, and blood lactate. Journal of Sports Science and Medicine, 21 (4), 545\u0026ndash;554. https://doi.org/10.52082/jssm.2022.545\u003c/li\u003e\n\u003cli\u003eSmith, L.E., Van Guilder, G.P., Dalleck, L.C. \u0026amp; Harris, N. K. (2022a). The effects of high-intensity functional training on cardiometabolic risk factors and exercise enjoyment in men and women with metabolic syndrome: study protocol for a randomized, 12-week, dose-response trial. Trials 23, 182. https://doi.org/10.1186/s13063-022-06100-7 \u003c/li\u003e\n\u003cli\u003eTurner, A. N. (2011). The science and practice of periodization: A brief review. Strength and Conditioning Journal, 33 (1), 34\u0026ndash;46. https://doi.org/10.1519/SSC.0b013e3182079c5f\u003c/li\u003e\n\u003cli\u003eVizvari, B., \u0026amp; Kovacs, E. (2018). The effect of aerobic exercise on metabolic syndrome markers: A meta-analysis. Journal of Sports Medicine and Physical Fitness, 58 (9), 1234\u0026ndash;1242. https://doi.org/10.23736/S0022-4707.17.07439-3\u003c/li\u003e\n\u003cli\u003eYang, M., Liu, C., Jiang, N., et al. (2023). Fibroblast growth factor 21 in metabolic syndrome. Frontiers in Endocrinology, 14, Article 1220426. https://doi.org/10.3389/fendo.2023.1220426\u003c/li\u003e\n\u003cli\u003eZhang, B., Chang, J. Y., Lee, M. H., Ju, S. H., Yi, H. S., \u0026amp; Shong, M. (2024). Mitochondrial stress and mitokines: Therapeutic perspectives for the treatment of metabolic diseases. Diabetes \u0026amp; Metabolism Journal. Advance online publication. https://doi.org/10.4093/dmj.2023.0411\u003c/li\u003e\n\u003cli\u003eZhang, D., Lu, C., \u0026amp; Sang, K. (2025). Exercise as a metabolic regulator: Targeting AMPK/mTOR-autophagy crosstalk to counteract sarcopenic obesity. Aging and Disease. Advance online publication. https://doi.org/10.14336/AD.2024.1234\u003c/li\u003e\n\u003cli\u003eZhang, H., Zhu, R., Sun, Q., \u0026amp; Du, L. (2025). Research progress on the role of FGF21 in insulin resistance. Frontiers in Endocrinology,16 , Article 1619462. https://doi.org/10.3389/fendo.2025.1619462\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Metabolic Syndrome, Mitokine, Functional Training","lastPublishedDoi":"10.21203/rs.3.rs-8220619/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8220619/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMetabolic syndrome is a disease related to mitochondrial dysfunction. Mitokines such as FGF21 and GDF15, recognized as biomarkers associated with metabolic stress, play crucial roles in regulating energy and inflammation. This study aimed to investigate the effects of High-Intensity Functional Training (HIFT) on the serum levels of FGF21 and GDF15, metabolic risk factors and body composition in middle-aged men with metabolic syndrome.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn a randomized controlled trial, 24 men (age\u0026thinsp;=\u0026thinsp;42.40\u0026thinsp;\u0026plusmn;\u0026thinsp;6.90 years) with metabolic syndrome were randomly assigned to either the HIFT group or the control group. The HIFT group performed exercise sessions twice a week for 12 weeks, and each session lasted 50\u0026ndash;60 minutes. Anthropometric and biochemical assessments were conducted before and after the intervention.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter the intervention, the FGF21 and GDF15 levels significantly decreased in the HIFT group (P\u0026thinsp;=\u0026thinsp;0.001). Furthermore, body fat percentage, fasting blood glucose, HbA1c, blood lipids, and LDL-C decreased, whereas skeletal muscle mass and HDL increased (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, for all).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHIFT improved metabolic health by modulating the serum levels of mitokines, metabolic risk factors and body composition. Therefore, this type of training can be recommended as an effective nonpharmacological intervention for prevention and treatment of patients with metabolic syndrome.\u003c/p\u003e\u003ch2\u003eTrial registry\u003c/h2\u003e \u003cp\u003eIranian Registry of Clinical Trials identifier: IRCT20241130063899N1, prospectively registered 10-11- 2025, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://irct.behdasht.gov.ir/trial/80642\u003c/span\u003e\u003cspan address=\"https://irct.behdasht.gov.ir/trial/80642\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e","manuscriptTitle":"The Effect of 12 Weeks of High Intensity Functional Training (HIFT) on Serum Mitokine and Metabolic Risk Factors in Patients with Metabolic Syndrome: A Randomized Control Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 16:04:33","doi":"10.21203/rs.3.rs-8220619/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-13T10:50:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-09T17:01:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-06T14:37:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238014967166880041240376770305200044286","date":"2026-02-04T06:22:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248124228058584936482772144104762413972","date":"2026-01-31T04:29:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-25T08:41:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195291465534770951657538455678523347247","date":"2026-01-21T14:08:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89383775666232131553120764948166916542","date":"2026-01-07T09:43:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-06T16:08:38+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-22T04:39:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-22T04:36:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-21T03:51:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Sports Science, Medicine and Rehabilitation","date":"2025-12-21T03:44:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d36f17c1-95df-45aa-a745-9e2cda6e5fae","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T05:08:19+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 16:04:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8220619","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8220619","identity":"rs-8220619","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}