Pre-training Skeletal Muscle Fiber Size and Predominant Fiber Type Best Predict Hypertrophic Responses to 6 Weeks of Resistance Training in Previously Trained Young Men.

Cody T Haun,Carlton D Fox,Andreas N Kavazis,Shelby C Osburn,Kaelin C Young,Petey W Mumford,Paul A Roberson,Matthew A Romero,Jordan R Moon,C Brooks Mobley,Michael D Roberts,Hailey A Parry,Christopher G Vann

doi:10.3389/fphys.2019.00297

Abstract

Limited evidence exists regarding differentially expressed biomarkers between previously-trained low versus high hypertrophic responders in response to resistance training. Herein, 30 college-aged males (training age 5 ± 3 years; mean ± SD) partook in 6 weeks of high-volume resistance training. Body composition, right leg vastus lateralis (VL) biopsies, and blood were obtained prior to training (PRE) and at the 3-week (W3) and 6-week time points (W6). The 10 lowest (LOW) and 10 highest (HIGH) hypertrophic responders were clustered based upon a composite hypertrophy score of PRE-to-W6 changes in right leg VL mean muscle fiber cross-sectional area (fCSA), VL thickness assessed via ultrasound, upper right leg lean soft tissue mass assessed via dual x-ray absorptiometry (DXA), and mid-thigh circumference. Two-way ANOVAs were used to compare biomarker differences between the LOW and HIGH clusters over time, and stepwise linear regression was performed to elucidate biomarkers that explained significant variation in the composite hypertrophy score from PRE to W3, W3 to W6, and PRE to W6 in all 30 participants. PRE-to-W6 HIGH and LOW responders exhibited a composite hypertrophy change of +10.7 ± 3.2 and -2.1 ± 1.6%, respectively (p < 0.001). Compared to HIGH responders, LOW responders exhibited greater PRE type II fCSA (+18%, p = 0.022). Time effects (p < 0.05) existed for total RNA/mg muscle (W6 > W3 > PRE), phospho (p)-4EBP1 (PRE > W3&W6), pan-mTOR (PRE > W3 < W6), p-mTOR (PRE > W3 < W6), pan-AMPKα (PRE > W3 < W6), pan-p70s6k (PRE > W3), muscle ubiquitin-labeled proteins (PRE > W6), mechano growth factor mRNA (W6 > W3&PRE), 45S rRNA (PRE > W6), and muscle citrate synthase activity (PRE > W3&W6). No interactions existed for the aforementioned biomarkers and/or other assayed targets (muscle 20S proteasome activity, serum total testosterone, muscle androgen receptor protein levels, muscle glycogen, or serum creatine kinase). Regression analysis indicated PRE type II fiber percentage (R2 = 0.152, β = 0.390, p = 0.033) and PRE type II fCSA (R2 = 0.207, β = -0.455, p = 0.019) best predicted the PRE-to-W6 change in the composite hypertrophy score. While our sample size is limited, these data suggest: (a) HIGH responders may exhibit more growth potential given that they possessed lower PRE type II fCSA values and (b) possessing a greater type II fiber percentage as a trained individual may be advantageous for hypertrophy in response to resistance training.

Highlights

Low and high hypertrophic responders exist following weeks to months of structured resistance training
During the prior to training (PRE), week 3 (W3), and week 6 (W6) testing sessions participants were instructed to arrive for testing batteries in an overnight fasted condition
Our regression analysis suggested that lower PRE type II fiber cross-sectional areas (fCSAs) values and a greater PRE type II fiber percentage were the strongest predictors of the PRE-W6 hypertrophic response

Summary

Introduction

Low and high hypertrophic responders exist following weeks to months of structured resistance training. This interest was initially spurred by Bamman’s laboratory who reported that different hypertrophic response clusters existed following 16 weeks of resistance training (Bamman et al, 2007). Bamman’s laboratory (Kim et al, 2007; Petrella et al, 2008; ThalackerMercer et al, 2013; Stec et al, 2016), our laboratory (Mobley et al, 2018; Roberts et al, 2018b), and others (Davidsen et al, 2011; Ogasawara et al, 2016; Morton et al, 2018) have subsequently examined low and high responders following weeks to months of resistance training with the intent of deciphering biomarkers that exist between each cluster. If low responders demonstrate an enhanced inflammatory or muscle damage profile to training, reducing training stress or providing adjuvant therapies (e.g., anti-inflammatory strategies) may be a viable strategy to optimize training adaptations

Methods

Results

Conclusion