A Genotype-Phenotype Model for Predicting Resistance Training Effects on Leg Press Performance

Abstract

This study develops a comprehensive genotype-phenotype model for predicting the effects of resistance training on leg press performance. A cohort of physically inactive adults (N=193) underwent 12 weeks of resistance training, and measurements of maximum isokinetic leg press peak force, muscle mass, and thickness were taken before and after the intervention. Whole-genome genotyping was performed, and genome-wide association analysis identified 85 novel SNPs significantly associated with changes in leg press strength after training. A prediction model was constructed using stepwise linear regression, incorporating seven lead SNPs that explained 40.4% of the training effect variance. The polygenic score showed a significant positive correlation with changes in leg press strength. By integrating genomic markers and phenotypic indicators, the comprehensive prediction model explained 75.4% of the variance in the training effect. Additionally, five SNPs were found to potentially impact muscle contraction, metabolism, growth, and development through their association with REACTOME pathways. Individual responses to resistance training varied, with changes in leg press strength ranging from −55.83% to 151.20%. The study highlights the importance of genetic factors in predicting training outcomes and provides insights into the potential biological functions underlying resistance training effects. The comprehensive model offers valuable guidance for personalized fitness programs based on individual genetic profiles and phenotypic characteristics.

Key words

genome-wide association study - strength training effects - isokinetic strength - personalized exercise - predictive model

Publication History

Received: 01 July 2023

Accepted: 20 December 2023

Accepted Manuscript online:
20 December 2023

Article published online:
29 January 2024

• References

• 1 Westcott WL. Resistance training is medicine: Effects of strength training on health. Curr Sports Med Rep 2012; 11: 209-216
• 2 Volkers KM, de Kieviet JF, Wittingen HP. et al. Lower limb muscle strength (LLMS): Why sedentary life should never start? A review. Arch Gerontol Geriatr 2012; 54: 399-414
• 3 Nascimento CM, Ingles M, Salvador-Pascual A. et al. Sarcopenia, frailty and their prevention by exercise. Free Radic Biol Med 2019; 132: 42-49
• 4 Li R, Xia J, Zhang XI. et al. Associations of Muscle Mass and Strength with All-Cause Mortality among US Older Adults. Med Sci Sports Exerc 2018; 50: 458-467
• 5 Garber CE, Blissmer B, Deschenes MR. et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med Sci Sports Exerc 2011; 43: 1334-1359
• 6 Herold F, Torpel A, Hamacher D. et al. Causes and Consequences of Interindividual Response Variability: A Call to Apply a More Rigorous Research Design in Acute Exercise-Cognition Studies. Front Physiol 2021; 12: 682891
• 7 Zapparoli FY, Riberto M. Isokinetic Evaluation of the Hip Flexor and Extensor Muscles: A Systematic Review. J Sport Rehabil 2017; 26: 556-566
• 8 Park YH, Park SH, Kim SH. et al. Relationship Between Isokinetic Muscle Strength and Functional Tests in Chronic Ankle Instability. J Foot Ankle Surg 2019; 58: 1187-1191
• 9 Undheim MB, Cosgrave C, King E. et al. Isokinetic muscle strength and readiness to return to sport following anterior cruciate ligament reconstruction: Is there an association? A systematic review and a protocol recommendation. Br J Sports Med 2015; 49: 1305-1310
• 10 Dauty M, Menu P, Fouasson-Chailloux A. Hamstring Muscle Injury Prediction by Isokinetic Ratios Depends on the Method Used. Clin J Sport Med 2020; 30: 40-45
• 11 Zvijac JE, Toriscelli TA, Merrick S. et al. Isokinetic concentric quadriceps and hamstring strength variables from the NFL Scouting Combine are not predictive of hamstring injury in first-year professional football players. Am J Sports Med 2013; 41: 1511-1518
• 12 Sugiura Y, Saito T, Sakuraba K. et al. Strength deficits identified with concentric action of the hip extensors and eccentric action of the hamstrings predispose to hamstring injury in elite sprinters. J Orthop Sports Phys Ther 2008; 38: 457-464
• 13 Gentil P, Pereira RW, Leite TK. et al. ACTN3 R577X Polymorphism and Neuromuscular Response to Resistance Training. J Sports Sci Med 2011; 10: 393-399
• 14 Dawson EA, Sheikhsaraf B, Boidin M. et al. Intra-individual differences in the effect of endurance versus resistance training on vascular function: A cross-over study. Scand J Med Sci Sports 2021; 31: 1683-1692
• 15 Clarkson PM, Devaney JM, Gordish-Dressman H. et al. ACTN3 genotype is associated with increases in muscle strength in response to resistance training in women. J Appl Physiol (1985) 2005; 99: 154-163
• 16 Riechman SE, Balasekaran G, Roth SM. et al. Association of interleukin-15 protein and interleukin-15 receptor genetic variation with resistance exercise training responses. J Appl Physiol (1985) 2004; 97: 2214-2219
• 17 Kittilsen HT, Goleva-Fjellet S, Freberg BI. et al. Responses to Maximal Strength Training in Different Age and Gender Groups. Front Physiol 2021; 12: 636972
• 18 Chung HC, Keiller DR, Roberts JD. et al. Do exercise-associated genes explain phenotypic variance in the three components of fitness? a systematic review & meta-analysis. PLoS One 2021; 16: e0249501
• 19 Pickering C, Kiely J, Grgic J. et al. Can Genetic Testing Identify Talent for Sport?. Genes (Basel) 2019; 10: 972
• 20 Dehghan A. Genome-Wide Association Studies. Methods Mol Biol 2018; 1793: 37-49
• 21 Kim DS, Wheeler MT, Ashley EA. The genetics of human performance. Nat Rev Genet 2022; 23: 40-54
• 22 Kullo IJ, Lewis CM, Inouye M. et al. Polygenic scores in biomedical research. Nat Rev Genet 2022; 23: 524-532
• 23 Plomin R, von Stumm S. Polygenic scores: Prediction versus explanation. Mol Psychiatry 2022; 27: 49-52
• 24 Nelson ME, Rejeski WJ, Blair SN. et al. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007; 39: 1435-1445
• 25 Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: A systematic review. Am J Prev Med 2012; 42: e3-e28
• 26 Keating XD, Zhou K, Liu X. et al. Reliability and Concurrent Validity of Global Physical Activity Questionnaire (GPAQ): A Systematic Review. Int J Environ Res Public Health 2019; 16: 4128
• 27 TAOM, Xiaoxia L, Jian W et al. The Prediction Model of Individual Differences in Health Promotion by Strength Training. China Sport Science 2021; 41: 35-45
• 28 Berger J, Bunout D, Barrera G. et al. Rectus femoris (RF) ultrasound for the assessment of muscle mass in older people. Arch Gerontol Geriatr 2015; 61: 33-38
• 29 Fessl I, Dirnberger J, Kroll J. et al. Isokinetic Leg-Press Power-Force-Velocity Profiles Are Reliable in Male and Female Elite Athletes but Not Interchangeable With Vertical Jump Profiles. Int J Sports Physiol Perform 2022; 17: 1614-1620
• 30 Anderson CA, Pettersson FH, Clarke GM. et al. Data quality control in genetic case-control association studies. Nat Protoc 2010; 5: 1564-1573
• 31 van Leeuwen EM, Kanterakis A, Deelen P. et al. Population-specific genotype imputations using minimac or IMPUTE2. Nat Protoc 2015; 10: 1285-1296
• 32 Marees AT, de Kluiver H, Stringer S. et al. A tutorial on conducting genome-wide association studies: Quality control and statistical analysis. Int J Methods Psychiatr Res 2018; 27: e1608
• 33 Wang MH, Cordell HJ, Van Steen K. Statistical methods for genome-wide association studies. Semin Cancer Biol 2019; 55: 53-60
• 34 Watanabe K, Taskesen E, van Bochoven A. et al. Functional mapping and annotation of genetic associations with FUMA. Nat Commun 2017; 8: 1826
• 35 Euesden J, Lewis CM, O’Reilly PF. PRSice: Polygenic Risk Score software. Bioinformatics 2015; 31: 1466-1468
• 36 Oscanoa J, Sivapalan L, Gadaleta E. et al. SNPnexus: a web server for functional annotation of human genome sequence variation (2020 update). Nucleic Acids Res 2020; 48: W185-W192
• 37 Gillespie M, Jassal B, Stephan R. et al. The reactome pathway knowledgebase 2022. Nucleic Acids Res 2022; 50: D687-D692
• 38 Eid MA, Aly SM, Huneif MA. et al. Effect of isokinetic training on muscle strength and postural balance in children with Down’s syndrome. Int J Rehabil Res 2017; 40: 127-133
• 39 Oliveira PF, Gadelha AB, Gauche R. et al. Resistance training improves isokinetic strength and metabolic syndrome-related phenotypes in postmenopausal women. Clin Interv Aging 2015; 10: 1299-1304
• 40 Kemmler W, Kohl M, Frohlich M. et al. Effects of High-Intensity Resistance Training on Osteopenia and Sarcopenia Parameters in Older Men with Osteosarcopenia-One-Year Results of the Randomized Controlled Franconian Osteopenia and Sarcopenia Trial (FrOST). J Bone Miner Res 2020; 35: 1634-1644
• 41 Alvarez C, Ramirez-Campillo R, Ramirez-Velez R. et al. Effects and prevalence of nonresponders after 12 weeks of high-intensity interval or resistance training in women with insulin resistance: A randomized trial. J Appl Physiol (1985) 2017; 122: 985-996
• 42 Hubal MJ, Gordish-Dressman H, Thompson PD. et al. Variability in muscle size and strength gain after unilateral resistance training. Med Sci Sports Exerc 2005; 37: 964-972
• 43 Androulakis-Korakakis P, Fisher JP, Steele J. The Minimum Effective Training Dose Required to Increase 1RM Strength in Resistance-Trained Men: A Systematic Review and Meta-Analysis. Sports Med 2020; 50: 751-765
• 44 Clark LA, Russ DW, Tavoian D. et al. Heterogeneity of the strength response to progressive resistance exercise training in older adults: Contributions of muscle contractility. Exp Gerontol 2021; 152: 111437
• 45 Ahmetov II, Hall ECR, Semenova EA. et al. Advances in sports genomics. Adv Clin Chem 2022; 107: 215-263
• 46 Martel GF, Roth SM, Ivey FM. et al. Age and sex affect human muscle fibre adaptations to heavy-resistance strength training. Exp Physiol 2006; 91: 457-464
• 47 Mayhew JL, Brechue WF, Smith AE. et al. Impact of testing strategy on expression of upper-body work capacity and one-repetition maximum prediction after resistance training in college-aged men and women. J Strength Cond Res 2011; 25: 2796-2807
• 48 Zempo H, Miyamoto-Mikami E, Kikuchi N. et al. Heritability estimates of muscle strength-related phenotypes: A systematic review and meta-analysis. Scand J Med Sci Sports 2017; 27: 1537-1546
• 49 Alvarez-Romero J, Voisin S, Eynon N. et al. Mapping Robust Genetic Variants Associated with Exercise Responses. Int J Sports Med 2021; 42: 3-18
• 50 Lou W, Ding B, Fu P. Pseudogene-Derived lncRNAs and Their miRNA Sponging Mechanism in Human Cancer. Front Cell Dev Biol 2020; 8: 85
• 51 Chan JJ, Tay Y. Noncoding RNA:RNA Regulatory Networks in Cancer. Int J Mol Sci 2018; 19: 1310
• 52 Kovalenko TF, Patrushev LI. Pseudogenes as Functionally Significant Elements of the Genome. Biochemistry (Mosc) 2018; 83: 1332-1349
• 53 Ulitsky I, Bartel DP. lincRNAs: Genomics, evolution, and mechanisms. Cell 2013; 154: 26-46
• 54 Panni S, Lovering RC, Porras P. et al. Non-coding RNA regulatory networks. Biochim Biophys Acta Gene Regul Mech 2020; 1863: 194417
• 55 Ali Syeda Z, Langden SSS, Munkhzul C. et al. Regulatory Mechanism of MicroRNA Expression in Cancer. Int J Mol Sci 2020; 21: 1723
• 56 Alexander RP, Fang G, Rozowsky J. et al. Annotating non-coding regions of the genome. Nature Reviews Genetics 2010; 11: 559-571
• 57 Tak YG, Farnham PJ. Making sense of GWAS: Using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome. Epigenetics & chromatin 2015; 8: 1-18
• 58 Fischer AW, Albers K, Schlein C. et al. PID1 regulates insulin-dependent glucose uptake by controlling intracellular sorting of GLUT4-storage vesicles. Biochim Biophys Acta Mol Basis Dis 2019; 1865: 1592-1603
• 59 Fresch R, Courtney J, Brockway H. et al. HAND1 knockdown disrupts trophoblast global gene expression. Physiol Rep 2023; 11: e15553
• 60 Lim CS, Park ES, Kim DJ. et al. SPIN90 (SH3 protein interacting with Nck, 90 kDa), an adaptor protein that is developmentally regulated during cardiac myocyte differentiation. J Biol Chem 2001; 276: 12871-12878
• 61 Satoh S, Tominaga T. mDia-interacting protein acts downstream of Rho-mDia and modifies Src activation and stress fiber formation. J Biol Chem 2001; 276: 39290-39294
• 62 Jeng SF, Rau CS, Liliang PC. et al. Profiling muscle-specific microRNA expression after peripheral denervation and reinnervation in a rat model. J Neurotrauma 2009; 26: 2345-2353
• 63 Cochet-Bissuel M, Lory P, Monteil A. The sodium leak channel, NALCN, in health and disease. Front Cell Neurosci 2014; 8: 132
• 64 Geering K. Function of FXYD proteins, regulators of Na, K-ATPase. J Bioenerg Biomembr 2005; 37: 387-392
• 65 Hostrup M, Lemminger AK, Thomsen LB. et al. High-Intensity Training Represses FXYD5 and Glycosylates Na,K-ATPase in Type II Muscle Fibres, Which Are Linked with Improved Muscle K(+) Handling and Performance. Int J Mol Sci 2023; 24: 5587
• 66 Masiakowski P, Breathnach R, Bloch J. et al. Cloning of cDNA sequences of hormone-regulated genes from the MCF-7 human breast cancer cell line. Nucleic Acids Res 1982; 10: 7895-7903
• 67 Samson MH, Abildgaard AM, Espelund U. et al. Circulating trefoil factors in relation to lung cancer, age and lung function: A cross-sectional study in patients referred for suspected lung cancer. Scand J Clin Lab Invest 2021; 81: 446-450
• 68 Qian Z, Jiang Y, Shou C. et al. Validation of the DNA Methylation Landscape of TFF1/TFF2 in Gastric Cancer. Cancers (Basel) 2022; 14: 5474
• 69 Yi J, Ren L, Li D. et al. Trefoil factor 1 (TFF1) is a potential prognostic biomarker with functional significance in breast cancers. Biomed Pharmacother 2020; 124: 109827
• 70 Ghanemi A, Melouane A, Mucunguzi O. et al. Energy and metabolic pathways in trefoil factor family member 2 (Tff2) KO mice beyond the protection from high-fat diet-induced obesity. Life Sci 2018; 215: 190-197
• 71 Kokabu S, Nakatomi C, Matsubara T. et al. The transcriptional co-repressor TLE3 regulates myogenic differentiation by repressing the activity of the MyoD transcription factor. J Biol Chem 2017; 292: 12885-12894
• 72 Konuma T, Okada Y. Statistical genetics and polygenic risk score for precision medicine. Inflamm Regen 2021; 41: 18
• 73 Cross B, Turner R, Pirmohamed M. Polygenic risk scores: An overview from bench to bedside for personalised medicine. Front Genet 2022; 13: 1000667
• 74 Kassiano W, Costa B, Nunes JP. et al. Weaker older women gain more lower body strength than their stronger counterparts, but not muscle mass, following 12 weeks of resistance training. J Sports Sci 2022; 40(24): 2714-2721
• 75 Vikmoen O, Raastad T, Ellefsen S. et al. Adaptations to strength training differ between endurance-trained and untrained women. Eur J Appl Physiol 2020; 120: 1541-1549
• 76 Petre H, Hemmingsson E, Rosdahl H. et al. Development of Maximal Dynamic Strength During Concurrent Resistance and Endurance Training in Untrained, Moderately Trained, and Trained Individuals: A Systematic Review and Meta-analysis. Sports Med 2021; 51: 991-1010
• 77 Coratella G, Longo S, Ce E. et al. Sex-Related Responses to Eccentric-Only Resistance Training in Knee-Extensors Muscle Strength and Architecture. Res Q Exerc Sport 2018; 89: 347-353
• 78 Gentil P, Steele J, Pereira MC. et al. Comparison of upper body strength gains between men and women after 10 weeks of resistance training. PeerJ 2016; 4: e1627