The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Cluster analysis tests the importance of myogenic gene expression during myofiber hypertrophy in humans
Abstract
We applied K-means cluster analysis to test the hypothesis that muscle-specific factors known to modulate protein synthesis and satellite cell activity would be differentially expressed during progressive resistance training (PRT, 16 wk) in 66 human subjects experiencing extreme, modest, and failed myofiber hypertrophy. Muscle mRNA expression of IGF-I isoform Ea (IGF-IEa), mechanogrowth factor (MGF, IGF-IEc), myogenin, and MyoD were assessed in muscle biopsies collected at baseline (T1) and 24 h after the first (T2) and last (T3) loading bouts from previously untrained subjects clustered as extreme responders (Xtr, n=17), modest responders (Mod, n=32), and nonresponders (Non, n=17) based on mean myofiber hypertrophy. Myofiber growth averaged 2,475 microm2 in Xtr, 1,111 microm2 in Mod, and -16 microm2 in Non. Main training effects revealed increases in all transcripts (46-83%, P<0.005). For the entire cohort, IGF-IEa, MGF, and myogenin mRNAs were upregulated by T2 (P<0.05), while MyoD did not increase significantly until T3 (P<0.001). Within clusters, MGF and myogenin upregulation was robust in Xtr (126% and 65%) and Mod (73% and 41%) vs. no changes in Non. While significant in all clusters by T3, IGF-IEa increased most in Xtr (105%) and least in Non (44%). Although MyoD expression increased overall, no changes within clusters were detected. We reveal for the first time that MGF and myogenin transcripts are differentially expressed in subjects experiencing varying degrees of PRT-mediated myofiber hypertrophy. The data strongly suggest the load-mediated induction of these genes may initiate important actions necessary to promote myofiber growth during PRT, while the role of MyoD is less clear.
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“revealing that high responders are not characterized by unique circulating hormone profiles or superior dietary protein intakes, but rather by distinct transcriptomic and cellular architectural adaptations [95].”
From Ribosome Biogenesis as a Putative Bottleneck to Skeletal Muscle Hypertrophy: Mechanisms, Human Evidence, and Practical Modulators (2026) · cites this paper as [95]
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“Human subjects universally exhibit vast heterogeneity in hypertrophic outcomes following standardized training protocols, which are broadly categorized as extreme (high), moderate, and non-responders [95].”
From Ribosome Biogenesis as a Putative Bottleneck to Skeletal Muscle Hypertrophy: Mechanisms, Human Evidence, and Practical Modulators (2026) · cites this paper as [95]
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A Role for Nitric Oxide in Muscle Repair: Nitric Oxide–mediated Activation of Muscle Satellite Cells
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Mauritzson, E., & Olsson, D. (2014) · Gothenburg University Publications Electronic Archive (Gothenburg University)
Phillips, S. M. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735535309.793571148
Ben‐Zaken, S. (2021) · doi:10.1093/oso/9780197512494.003.0010
Effects of Resistance Exercise Training on Aged Skeletal Muscle: Potential Role of Muscle Stem Cells
Kim, D., Kang, N., & Park, Y.-M. (2023) · Exercise Science · doi:10.15857/ksep.2023.00234
Michel, J. M., Norton, S. C., Bergamasco, J. G. A., Scarpelli, M. C., Chaves, T. S., da Silva, D. G., Bittencourt, D., Ugochukwu, C. G., Boersma, M., Mobley, C. B., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.04.686603
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Proteomic profiling of ribosomes from higher vs. lower responders to 10 weeks of resistance training
Michel, J. M., Norton, S. C., Bergamasco, J. G. A., Scarpelli, M. C., Chaves, T. S., da Silva, D. G., Bittencourt, D., Ugochukwu, C. G., Boersma, M., Mobley, C. B., et al. (2026) · Translational Exercise Biomedicine · doi:10.1515/teb-2026-0004
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Παπανικολάου, Κ., Jamurtas, A. Z., Draganidis, D., Baloyiannis, I., Poulios, A., Rosvoglou, A., Papadopoulos, C., Papadimas, G., Chrysanthou‐Piterou, M., Havaki, S., et al. (2026) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2026.10.010
Metadata
- Authors
- Bamman, M. M., Petrella, J. K., Kim, J.-S., Mayhew, D. L., & Cross, J. M.
- Affiliations
- University of Alabama at Birmingham (US)
- Venue
- Journal of Applied Physiology
- Publisher
- American Physiological Society
- Published
- 2007-06
- Volume
- 102
- Issue
- 6
- Pages
- 2232-2239
- ISSN
- 0161-7567 (ISSN-L)
- 8750-7587
- 1522-1601
- OpenAlex
- W2116499762
- Cited by
- 216
- References
- 50
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 7 · 2023: 7 · 2022: 7 · 2021: 10 · 2020: 15 · 2019: 15 · 2018: 22 · 2017: 10 · 2016: 13 · 2015: 13 · 2014: 10 · 2013: 15 · 2012: 13
- FWCI
- 4.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Applied Physiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Veterans Affairs
- University of Alabama at Birmingham
- National Institute on Aging (R01AG017896)
- National Center for Research Resources (M01RR00032, M01RR000032)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Health Sciences › Nursing › Nutrition and Dietetics › Muscle metabolism and nutrition
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- muscle fiber hypertrophy, progressive resistance training, myogenin, MyoD, satellite cells, muscle protein synthesis, gene expression
- MeSH terms
- Adult, Aged, Physical Exertion, Female, Gene Expression Regulation, Humans, Hypertrophy, Male, Middle Aged, Muscle Contraction, Muscle Proteins, Biomarkers, Gene Expression, Cluster Analysis, Muscle, Skeletal, Gene Expression Profiling
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