Academic Journal

Skeletal Muscle Transcriptomic Responses to Concurrent Training With Polyphenols in Ageing Adults: A Randomized Trial.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Skeletal Muscle Transcriptomic Responses to Concurrent Training With Polyphenols in Ageing Adults: A Randomized Trial.
Συγγραφείς: Guadalupe-Grau A; GENUD Toledo Research Group, Faculty of Sport Sciences, University of Castilla-La Mancha, Toledo, Spain.; Centro de Investigación Biomédica en Red Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain.; Grupo Mixto de Fragilidad y Envejecimiento Exitoso UCLM-SESCAM (TEC2022-007), Instituto de Investigación Sanitaria de Castilla-La Mancha (IDISCAM), Junta de Comunidades de Castilla-La Mancha (JCCM), Toledo, Spain., Gudra D; Scientific Laboratory of Molecular Genetics, Riga Stradiņš University, Riga, Latvia., Lismane D; Laboratory of Sports and Nutrition Research, Riga Stradiņš University, Riga, Latvia., Raudeniece J; Laboratory of Sports and Nutrition Research, Riga Stradiņš University, Riga, Latvia.; Department of Human Physiology and Biochemistry, Riga Stradiņš University, Riga, Latvia., Akuratere G; Laboratory of Sports and Nutrition Research, Riga Stradiņš University, Riga, Latvia., Viksne K; Scientific Laboratory of Molecular Genetics, Riga Stradiņš University, Riga, Latvia., Gailite L; Scientific Laboratory of Molecular Genetics, Riga Stradiņš University, Riga, Latvia., Vilne B; Bioinformatics Group, Riga Stradiņš University, Riga, Latvia., Pivovarova-Ramich O; Department of Molecular Metabolism and Precision Nutrition, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.; Department of Endocrinology and Metabolism, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.; German Center for Diabetes Research (DZD), München-Neuherberg, Germany., Flensted-Jensen M; Xlab, Department of Biomedical Sciences, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark., Dela F; Xlab, Department of Biomedical Sciences, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark., Reihmane D; Laboratory of Sports and Nutrition Research, Riga Stradiņš University, Riga, Latvia.; Department of Human Physiology and Biochemistry, Riga Stradiņš University, Riga, Latvia.
Πηγή: Journal of cachexia, sarcopenia and muscle [J Cachexia Sarcopenia Muscle] 2026 Oct; Vol. 17 (5), pp. e70391.
Τύπος έκδοσης: Journal Article; Randomized Controlled Trial
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders Country of Publication: Germany NLM ID: 101552883 Publication Model: Print Cited Medium: Internet ISSN: 2190-6009 (Electronic) Linking ISSN: 21905991 NLM ISO Abbreviation: J Cachexia Sarcopenia Muscle Subsets: MEDLINE
Imprint Name(s): Publication: 2015- : Berlin : John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders
Original Publication: Heidelburg : Springer-Verlag
Ιατρικοί όροι (MeSH): Polyphenols*/pharmacology , Polyphenols*/administration & dosage , Muscle, Skeletal*/metabolism , Muscle, Skeletal*/drug effects , Transcriptome*/drug effects , Aging*/genetics, Resistance Training/methods ; Humans ; Aged ; Female ; Male ; Middle Aged ; Gene Expression Profiling ; Double-Blind Method
Περίληψη: Background: Transcriptomic adaptations of ageing skeletal muscle to concurrent resistance training (RT) and high-intensity interval training (HIIT) remain insufficiently characterized. We investigated the effects of a 12-week concurrent RT + HIIT intervention on the vastus lateralis transcriptome in middle-aged and older adults and whether polyphenol supplementation modulated these responses.
Methods: Thirty-eight adults (55-70 years; 17 polyphenol [PP], 21 placebo [PLA]) with paired skeletal muscle RNA-sequencing data participated in a randomized, double-blind trial. Participants completed a 30-day supplementation phase followed by a 12-week supervised RT + HIIT programme with continued supplementation. Muscle biopsies were obtained before (PRE) and after (POST) training. Differential expression analyses were adjusted for age, sex and muscle fibre type composition. Differential expression was assessed using FDR ≤ 0.05, with |log2FC| > 1 applied as an additional effect-size criterion.
Results: Baseline transcriptomic differences between PP and PLA groups were minimal, with three FDR-significant transcripts, of which only HMOX1 additionally exceeded |log2FC| > 1 (FDR = 0.011; log2FC = 1.16). The group-by-time interaction analysis identified 14 FDR-significant transcripts, of which eight additionally exceeded |log2FC| > 1; these signals were characterized by low or sparse expression and high inter-individual variability, without a coherent supplementation-related transcriptional response. In the pooled paired PRE-POST analysis, 60 transcripts reached FDR significance, of which seven additionally exceeded |log2FC| > 1, including upregulation of CLLU1 (log2FC = 3.10; FDR = 0.0155), PRND (log2 log2FC = 2.60; FDR = 0.02) and LOX, and downregulation of MYH1 (log2FC = -1.3; FDR = 0.0001). Most FDR-significant transcripts showed relatively small estimated effect sizes, and functional enrichment analyses did not identify robust pathway-level adaptations.
Conclusions: In middle-aged and older adults, 12 weeks of concurrent RT + HIIT induced a predominantly low-magnitude skeletal muscle transcriptional response. Selected transcript-level changes were consistent with processes related to extracellular matrix remodelling and contractile regulation; however, the absence of robust pathway-level enrichment limits conclusions regarding coordinated biological pathway adaptations. Polyphenol supplementation did not meaningfully influence the transcriptional response to exercise training.
(© 2026 The Author(s). Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.)
References: L. Carollo, E. A. Lawson, T. L. Stanley, et al., “Muscle Movement and Metabolism: Exercise and Skeletal Muscle as Mediators of Health. A Report From the 26th Annual Harvard Nutrition Obesity Symposium, 2025,” American Journal of Clinical Nutrition 123 (2026): 101262.
P. R. Biga, J. E. Duan, T. E. Young, et al., “Hallmarks of Aging: A User's Guide for Comparative Biologists,” Ageing Research Reviews 104 (2025): 102616.
C. Lopez‐Otin, M. A. Blasco, L. Partridge, et al., “Hallmarks of Aging: An Expanding Universe,” Cell 186, no. 2 (2023): 243–278.
J. Alcazar, J. Losa‐Reyna, C. Rodriguez‐Lopez, et al., “Effects of Concurrent Exercise Training on Muscle Dysfunction and Systemic Oxidative Stress in Older People With COPD,” Scandinavian Journal of Medicine & Science in Sports 29, no. 10 (2019): 1591–1603.
M. Flensted‐Jensen, C. M. Weinreich, A. S. Kleis‐Olsen, et al., “Effects of Resistance‐Based Training and Polyphenol Supplementation on Physical Function, Metabolism, and Inflammation in Aging Individuals,” Geroscience 48, no. 2 (2026): 2945–2968.
M. Flensted‐Jensen, C. M. Weinreich, A. S. Kleis‐Olsen, et al., “Resistance‐Based Training Improves Mitochondrial Capacity and Redox Balance in Aging Adults, Independent of Polyphenol Supplementation,” Redox Biology 89 (2026): 103972.
L. Zhao, H. Li, D. Li, L. Luo, and S. Hu, “Transcriptomic Analysis Reveals the Impact of Concurrent, Resistance, and Endurance Training on Skeletal Muscle,” PLoS ONE 21, no. 2 (2026): e0340309.
X. Wang, C. Liu, Y. Chen, M. Wang, K. Zhao, and W. Jiang, “Metabolomic Signatures of Recovery: A Secondary Analysis of Public Longitudinal LC‐MS Datasets Shows Polyphenol‐Rich Interventions Attenuate Purine Degradation and Oxidative Stress Following Exhaustive Exercise,” Metabolites 16, no. 1 (2026): 79.
H. Jiang, R. Lei, S. W. Ding, and S. Zhu, “Skewer: A Fast and Accurate Adapter Trimmer for Next‐Generation Sequencing Paired‐End Reads,” BMC Bioinformatics 15 (2014): 182.
S. Andrews, “FastQC: A Quality Control Tool for High Throughput Sequence Data,” (2010).
A. Dobin, C. A. Davis, F. Schlesinger, et al., “STAR: Ultrafast Universal RNA‐Seq Aligner,” Bioinformatics 29, no. 1 (2013): 15–21.
T. Van der Stede, R. Moreno‐Justicia, S. Moesgaard, Y. Gidron, G. D'Hulst, and W. Derave, “Deconvoluting Fibre Type Proportions From Human Skeletal Muscle Transcriptomics and Proteomics Data Using FibeRtypeR,” Journal of Physiology 604, no. 7 (2026): 2624–2641.
Y. Chen, L. Chen, A. T. L. Lun, P. L. Baldoni, and G. K. Smyth, “edgeR v4: Powerful Differential Analysis of Sequencing Data With Expanded Functionality and Improved Support for Small Counts and Larger Datasets,” Nucleic Acids Research 53, no. 2 (2025): gkaf018.
Z. Gu, R. Eils, and M. Schlesner, “Complex Heatmaps Reveal Patterns and Correlations in Multidimensional Genomic Data,” Bioinformatics 32, no. 18 (2016): 2847–2849.
S. Durinck, P. T. Spellman, E. Birney, and W. Huber, “Mapping Identifiers for the Integration of Genomic Datasets With the R/Bioconductor Package biomaRt,” Nature Protocols 4, no. 8 (2009): 1184–1191.
S. Xu, E. Hu, Y. Cai, et al., “Using clusterProfiler to Characterize Multiomics Data,” Nature Protocols 19, no. 11 (2024): 3292–3320.
M. Carlson, “Genome Wide Annotation for Human,” (2023).
G. Yu and Q. Y. He, “ReactomePA: An R/Bioconductor Package for Reactome Pathway Analysis and Visualization,” Molecular BioSystems 12, no. 2 (2016): 477–479.
G. Korotkevich, V. Sukhov, N. Budin, et al., “Fast Gene Set Enrichment Analysis,” bioRxiv: The Preprint Server for Biology (2021): 060012.
I. Dolgalev, “msigdbr: MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format,” (2026).
Molecular Transducers of Physical Activity Consortium Study Group, “Temporal Dynamics of the Multi‐Omic Response to Endurance Exercise Training,” Nature 629, no. 8010 (2024): 174–183.
N. J. Pillon, B. M. Gabriel, L. Dollet, et al., “Transcriptomic Profiling of Skeletal Muscle Adaptations to Exercise and Inactivity,” Nature Communications 11, no. 1 (2020): 470.
M. Hansen, J. E. R. Grothen, A. Karlsen, et al., “The Skeletal Muscle Response to High‐Intensity Training Assessed by Single‐Nucleus RNA‐Sequencing Is Blunted in Individuals With Type 2 Diabetes,” Journal of Physiology 603, no. 11 (2025): 3357–3377.
Z. D. Von Ruff, M. J. Miller, T. Moro, et al., “Resistance Exercise Training in Older Men Reduces ATF4‐Activated and Senescence‐Associated mRNAs in Skeletal Muscle,” Geroscience 47, no. 3 (2025): 4601–4622.
M. Kjaer, “Role of Extracellular Matrix in Adaptation of Tendon and Skeletal Muscle to Mechanical Loading,” Physiological Reviews 84, no. 2 (2004): 649–698.
R. P. Wohlgemuth, S. E. Brashear, and L. R. Smith, “Alignment, Cross Linking, and Beyond: A Collagen Architect's Guide to the Skeletal Muscle Extracellular Matrix,” American Journal of Physiology. Cell Physiology 325, no. 4 (2023): C1017–C1030.
M. Flensted‐Jensen, A. S. Kleis‐Olsen, C. M. Weinreich, et al., “Advanced Glycation End‐Products Accumulate Preferentially in Type I Muscle Fibers of Aging Adults but Are Unchanged by Training and Polyphenol Supplementation,” Journal of Applied Physiology 140, no. 4 (2026): 1019–1027, https://doi.org/10.1152/japplphysiol.01093.2025.
J. M. Wilson, P. J. Marin, M. R. Rhea, S. M. Wilson, J. P. Loenneke, and J. C. Anderson, “Concurrent Training: A Meta‐Analysis Examining Interference of Aerobic and Resistance Exercises,” Journal of Strength and Conditioning Research 26, no. 8 (2012): 2293–2307.
V. C. Figueiredo, R. F. D'Souza, D. W. van Pelt, et al., “Ribosome Biogenesis and Degradation Regulate Translational Capacity During Muscle Disuse and Reloading,” Journal of Cachexia, Sarcopenia and Muscle 12, no. 1 (2021): 130–143.
G. Santulli, G. Sabatelli, B. Wang, et al., “Interplay Between Frailty and Cardiometabolic Disorders: From Pathophysiology to Clinical Implications,” Cardiovascular Diabetology 25, no. 1 (2025): 1.
P. Mone and A. Pansini, “Gait Speed Test and Cognitive Decline in Frail Women With Acute Myocardial Infarction,” American Journal of the Medical Sciences 360, no. 5 (2020): 484–488.
P. Mone, A. Pansini, F. Calabrò, et al., “Global Cognitive Function Correlates With P‐Wave Dispersion in Frail Hypertensive Older Adults,” Journal of Clinical Hypertension (Greenwich, Conn.) 24, no. 5 (2022): 638–643.
T. Van der Stede, R. Moreno‐Justicia, S. Moesgaard, Y. Gidron, G. D'Hulst, and W. Derave, “Deconvoluting Fiber Type Proportions From Human Skeletal Muscle Transcriptomics and Proteomics Data Using FibeRtypeR,” bioRxiv, (2025): 2025.09.17.676778.
A. M. Kemfack, I. Hernandez‐Morato, Y. Moayedi, and M. J. Pitman, “An Optimized Method for High‐Quality RNA Extraction From Distinctive Intrinsic Laryngeal Muscles in the Rat Model,” Scientific Reports 12, no. 1 (2022): 21665.
Grant Information: 5.2.1.1.i.0/2/24/I/CFLA/005 RSU internal and RSU with LSPA external consolidation; RSU/LSPA-PA-2024/1-0007 RSU internal and RSU with LSPA external consolidation; 01.04.2024.-31.03.2026 Systemic and muscle tissue-specific metabolic adaptations to EXercise and POlyphenol supplementation in ageing: modulatory effects of SEstrins (EXPOSE); Center for Healthy Aging and from Asiros Nordic (Sorø, Denmark)
Contributed Indexing: Keywords: ageing; polyphenols; skeletal muscle transcriptomics; training
Substance Nomenclature: 0 (Polyphenols)
Entry Date(s): Date Created: 20260925 Date Completed: 20260925 Latest Revision: 20261005
Update Code: 20261006
PubMed Central ID: PMC13613424
DOI: 10.1002/jcsm.70391
PMID: 42788414
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:2190-6009
DOI:10.1002/jcsm.70391