Serum Metabolome Signature Response to Different Types of Resistance Training

Abstract

Pneumatic resistance training (PRT) facilitates a longer time under tension that might lead to greater changes in body composition when compared to traditional resistance training (TRT), possibly enhancing serum metabolite concentrations indicative of healthy metabolic function. To assess the impact of PRT and TRT on muscular strength, body composition, and serum metabolome, 69 men (age: 31.8±7.2 years, height: 179.7±5.4 cm, weight: 81.1±9.9 kg) were randomized into two 10-week intervention groups (PRT:n=24 and TRT:n=24) and one control group (CON:n=21). Serum metabolite concentrations were assessed before and after the training intervention by high-throughput nuclear magnetic resonance. Fat mass and lean mass were obtained by bioimpedance analysis. The training intervention resulted in an increase in lean mass for both PRT (1.85±2.69%; p=0.003) and TRT (2.72±4.53%; p=0.004), while only PRT reduced statistically significantly in body fat percentage (PRT: −5.08±10.76%; p=0.019). Only in PRT and TRT significant increases in small high-density lipoproteins (S-HDL-L) and small HDL particles (S-HDL-P) were observed. When controlling for fat and lean mass, the effects on S-HDL-L/S-HDL-P diminished. Network analysis may suggest that PRT and TRT result in an increase in network connectivity and robustness. It appears that the observed improvements are associated with changes in body composition.

Keywords

body composition - metabolites - strength training

Publication History

Received: 08 January 2024

Accepted: 10 September 2024

Accepted Manuscript online:
10 September 2024

Article published online:
07 November 2024

• References

• 1 Westcott WL. Resistance Training is Medicine. Curr Sports Med Rep 2012; 11: 209-216
• 2 Cornelissen VA, Fagard RH, Coeckelberghs E. et al. Impact of Resistance Training on Blood Pressure and Other Cardiovascular Risk Factors. Hypertension 2011; 58: 950-958
• 3 Kelley GA, Kelley KS. Impact of progressive resistance training on lipids and lipoproteins in adults: A meta-analysis of randomized controlled trials. Prev Med (Baltim) 2009; 48: 9-19
• 4 Mann S, Beedie C, Jimenez A. Differential Effects of Aerobic Exercise, Resistance Training and Combined Exercise Modalities on Cholesterol and the Lipid Profile: Review, Synthesis and Recommendations. Sports Medicine 2014; 44: 211-221
• 5 Delgado-Floody P, Álvarez C, Lusa Cadore E. et al. Preventing metabolic syndrome in morbid obesity with resistance training: Reporting interindividual variability. Nutrition, Metabolism and Cardiovascular Diseases 2019; 29: 1368-1381
• 6 Sarin HV, Ahtiainen JP, Hulmi JJ. et al. Resistance Training Induces Antiatherogenic Effects on Metabolomic Pathways. Med Sci Sports Exerc 2019; 51: 1866-1875
• 7 Frost DM, Cronin JB, Newton RU. A comparison of the kinematics, kinetics and muscle activity between pneumatic and free weight resistance. Eur J Appl Physiol 2008; 104: 937-956
• 8 Schoenfeld BJ, Contreras B, Krieger J. et al. Resistance Training Volume Enhances Muscle Hypertrophy but Not Strength in Trained Men. Med Sci Sports Exerc 2019; 51: 94-103
• 9 Garber CE, Blissmer B, Deschenes MR. et al. Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory, Musculoskeletal, and Neuromotor Fitness in Apparently Healthy Adults. Med Sci Sports Exerc 2011; 43: 1334-1359
• 10 Papandreou C, García-Gavilán J, Camacho-Barcia L. et al. Circulating Metabolites Associated with Body Fat and Lean Mass in Adults with Overweight/Obesity. Metabolites 2021; 11: 317
• 11 National Nutrition Council. Finnish Nutrition Recommendations. Ministry of Agriculture and Forestry, 1999.
• 12 World Health Organization. WHO Guidelines on Drawing Blood: Best Practices in Phlebotomy. Geneva: 2010
• 13 Soininen P, Kangas AJ, Würtz P. et al. High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism. Analyst 2009; 134: 1781-1785
• 14 Tukiainen T, Kettunen J, Kangas AJ. et al. Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci. Hum Mol Genet 2012; 21: 1444-1455
• 15 Kettunen J, Demirkan A, Würtz P. et al. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nat Commun 2016; 7: 11122
• 16 Xia J, Wishart DS. Metabolomic Data Processing, Analysis, and Interpretation Using MetaboAnalyst. Curr Protoc Bioinformatics 2011; 14 14.10 1-14 10.48
• 17 van der Vorst EPC. High-Density Lipoproteins and Apolipoprotein A1. 2020; 399-420
• 18 Zhang Y, Gordon SM, Xi H. et al. HDL subclass proteomic analysis and functional implication of protein dynamic change during HDL maturation. Redox Biol 2019; 24: 101222
• 19 Camont L, Lhomme M, Rached F. et al. Small, Dense High-Density Lipoprotein-3 Particles Are Enriched in Negatively Charged Phospholipids. Arterioscler Thromb Vasc Biol 2013; 33: 2715-2723
• 20 Duparc T, Ruidavets J-B, Genoux A. et al. Serum level of HDL particles are independently associated with long-term prognosis in patients with coronary artery disease: The GENES study. Sci Rep 2020; 10: 8138
• 21 Harbaum L, Ghataorhe P, Wharton J. et al. Reduced plasma levels of small HDL particles transporting fibrinolytic proteins in pulmonary arterial hypertension. Thorax 2019; 74: 380-389
• 22 Prabhakaran B, Dowling EA, Branch JD. et al. Effect of 14 weeks of resistance training on lipid profile and body fat percentage in premenopausal women. Br J Sports Med 1999; 33: 190-195
• 23 Sheikholeslami Vatani D, Ahmadi S, Ahmadi Dehrashid K. et al. Changes in cardiovascular risk factors and inflammatory markers of young, healthy, men after six weeks of moderate or high intensity resistance training. J Sports Med Phys Fitness 2011; 51: 695-700
• 24 Aristizabal JC, Freidenreich DJ, Volk BM. et al. Effect of resistance training on resting metabolic rate and its estimation by a dual-energy X-ray absorptiometry metabolic map. Eur J Clin Nutr 2015; 69: 831-836
• 25 Qiao Q, Bouwman FG, van Baak MA. et al. Plasma Levels of Triglycerides and IL-6 Are Associated With Weight Regain and Fat Mass Expansion. J Clin Endocrinol Metab 2022; 107: 1920-1929
• 26 Sun J, Zhang Z, Liu Z. et al. The Correlation of Total Percent Fat With Alterations in Cholesterol and Triglycerides in Adults. Front Nutr 2022; 9: 881729
• 27 Laclaustra M, Corella D, Ordovas JM. Metabolic syndrome pathophysiology: The role of adipose tissue. Nutrition, Metabolism and Cardiovascular Diseases 2007; 17: 125-139
• 28 Cheng R, Wang L, Le S. et al. A randomized controlled trial for response of microbiome network to exercise and diet intervention in patients with nonalcoholic fatty liver disease. Nat Commun 2022; 13: 2555
• 29 Vignoli A, Tenori L, Luchinat C. et al. Age and Sex Effects on Plasma Metabolite Association Networks in Healthy Subjects. J Proteome Res 2018; 17: 97-107
• 30 Vignoli A, Tenori L, Giusti B. et al. Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death. J Proteome Res 2020; 19: 949-961