Back

Large increases in resistance training volume do not impair skeletal muscle hypertrophy or anabolic-catabolic molecular signalling in trained individuals

Camargo, J. B. B.; Bittencourt, D.; Michel, J. M.; Silva, D. G.; Bergamasco, J. G. A.; Tiede, D. R.; Lewis, D.; Nacafucasaco, E. T. d. A.; Ferrari, O.; Melo, A. C. C.; Iasulaitis, M.; Rebelato, M.; Roberts, M. D.; Libardi, C. A.

2026-02-24 physiology
10.64898/2026.02.23.707462 bioRxiv
Show abstract

Skeletal muscle hypertrophy results from the integrated regulation of anabolic and proteolytic processes in response to mechanical loading. Although increases in resistance training (RT) volume are used to increase mechanical stress, it remains uncertain whether large and abrupt volume progressions could exceed muscle adaptive capacity by disrupting the balance between anabolic and catabolic signaling. The present study investigated whether a large increase in weekly RT volume (+120%) leads to impaired hypertrophic outcomes and intracellular regulatory responses compared with a modest increase (+20%). Twenty-five resistance-trained men and women (18-35 years old) completed an 8-week randomized, single-blind, within-subject unilateral intervention. Each participant trained both legs twice weekly, with one leg assigned to the large (VOL120) and the contralateral leg to the modest (VOL20) weekly volume progressions relative to habitual training volume. Vastus lateralis muscle cross-sectional area (mCSA) was assessed by ultrasonography before and after training. Muscle biopsies were obtained at baseline, post-intervention, and 24 h after the last session to quantify muscle fiber cross-sectional area (fCSA), satellite cell myonuclear content, and anabolic/catabolic signaling markers. Both protocols induced increases in mCSA over time (p<0.001), with no protocol vs. time interaction. No significant effects were observed for fCSA nor satellite cell number or myonuclear content. Additionally, molecular responses related to translational regulation and protein degradation were largely similar between protocols. Collectively, these data indicate that a large, abrupt increase in weekly set volume does not impair hypertrophic adaptations or meaningfully alter the anabolic-catabolic signaling profile in resistance-trained individuals.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Experimental Physiology
19 papers in training set
Top 0.1%
16.9%
2
The Journal of Physiology
134 papers in training set
Top 0.1%
14.2%
3
Frontiers in Physiology
93 papers in training set
Top 0.4%
6.9%
4
Physiological Reports
35 papers in training set
Top 0.1%
6.1%
5
Journal of Applied Physiology
29 papers in training set
Top 0.1%
6.1%
50% of probability mass above
6
PLOS ONE
4510 papers in training set
Top 35%
4.1%
7
Journal of Experimental Biology
249 papers in training set
Top 0.8%
4.0%
8
American Journal of Physiology-Cell Physiology
34 papers in training set
Top 0.1%
4.0%
9
The FASEB Journal
175 papers in training set
Top 0.3%
3.5%
10
Scientific Reports
3102 papers in training set
Top 48%
2.3%
11
Function
15 papers in training set
Top 0.1%
2.0%
12
Skeletal Muscle
14 papers in training set
Top 0.1%
2.0%
13
eLife
5422 papers in training set
Top 37%
2.0%
14
JCI Insight
241 papers in training set
Top 3%
1.7%
15
Medicine & Science in Sports & Exercise
15 papers in training set
Top 0.2%
1.6%
16
American Journal of Physiology-Endocrinology and Metabolism
34 papers in training set
Top 0.2%
1.4%
17
European Journal of Applied Physiology
12 papers in training set
Top 0.1%
1.4%
18
Aging Cell
144 papers in training set
Top 2%
1.3%
19
Journal of Cachexia, Sarcopenia and Muscle
27 papers in training set
Top 0.2%
1.2%
20
Frontiers in Endocrinology
53 papers in training set
Top 2%
1.2%
21
American Journal of Physiology-Heart and Circulatory Physiology
32 papers in training set
Top 0.9%
1.1%
22
Cells
232 papers in training set
Top 6%
0.8%
23
eBioMedicine
130 papers in training set
Top 5%
0.7%
24
Molecular Metabolism
105 papers in training set
Top 2%
0.7%
25
Acta Physiologica
13 papers in training set
Top 0.3%
0.7%
26
Redox Biology
64 papers in training set
Top 1%
0.6%