Cited by 201Muscle Physiology and DisordersGenetics and Physical PerformanceNutrition and Health in Aging

Molecular Networks of Human Muscle Adaptation to Exercise and Age

Open access
Phillips, Bethan E., Williams, John P., Gustafsson, Thomas, Bouchard, Claude, Rankinen, Tuomo, Knudsen, Steen, Smith, Kenneth, Timmons, James A. +1 more·2013·PLoS Genetics

Abstract

Physical activity and molecular ageing presumably interact to precipitate musculoskeletal decline in humans with age. Herein, we have delineated molecular networks for these two major components of sarcopenic risk using multiple independent clinical cohorts. We generated genome-wide transcript profiles from individuals (n = 44) who then undertook 20 weeks of supervised resistance-exercise training (RET). Expectedly, our subjects exhibited a marked range of hypertrophic responses (3% to +28%), and when applying Ingenuity Pathway Analysis (IPA) up-stream analysis to ~580 genes that co-varied with gain in lean mass, we identified rapamycin (mTOR) signaling associating with growth (P = 1.4 × 10(-30)). Paradoxically, those displaying most hypertrophy exhibited an inhibited mTOR activation signature, including the striking down-regulation of 70 rRNAs. Differential analysis found networks mimicking developmental processes (activated all-trans-retinoic acid (ATRA, Z-score = 4.5; P = 6 × 10(-13)) and inhibited aryl-hydrocarbon receptor signaling (AhR, Z-score = -2.3; P = 3 × 10(-7))) with RET. Intriguingly, as ATRA and AhR gene-sets were also a feature of endurance exercise training (EET), they appear to represent "generic" physical activity responsive gene-networks. For age, we found that differential gene-expression methods do not produce consistent molecular differences between young versus old individuals. Instead, utilizing two independent cohorts (n = 45 and n = 52), with a continuum of subject ages (18-78 y), the first reproducible set of age-related transcripts in human muscle was identified. This analysis identified ~500 genes highly enriched in post-transcriptional processes (P = 1 × 10(-6)) and with negligible links to the aforementioned generic exercise regulated gene-sets and some overlap with ribosomal genes. The RNA signatures from multiple compounds all targeting serotonin, DNA topoisomerase antagonism, and RXR activation were significantly related to the muscle age-related genes. Finally, a number of specific chromosomal loci, including 1q12 and 13q21, contributed by more than chance to the age-related gene list (P = 0.01-0.005), implying possible epigenetic events. We conclude that human muscle age-related molecular processes appear distinct from the processes regulated by those of physical activity.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pgen.1003389

Cites

90 of 90 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Low responders to each exercise stimulus may be as high as 25% in studies of individuals undertaking resistance and endurance training in isolation.

    “The characterisation of individual responses is not a new phenomenon, but the results of studies of individuals undertaking resistance and endurance training in isolation suggest that 'low responders' to each exercise stimulus may be as high as 25% (Timmons et al., 2005;Phillips et al., 2013;Gurd et al., 2016).”

    From Concurrent exercise training: do opposites distract? (2017) · cites this paper as Phillips et al., 2013

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Phillips, B. E., Williams, J. P., Gustafsson, T., Bouchard, C., Rankinen, T., Knudsen, S., Smith, K., Timmons, J. A., & Atherton, P. J.
Affiliations
  • Royal Derby Hospital (GB)
  • Karolinska Institutet (SE)
  • Pennington Biomedical Research Center (US)
  • Medical Prognosis Institute (Denmark) (DK)
  • Loughborough University (GB)
Corresponding author
Timmons, James A.
Venue
PLoS Genetics
Published
2013-03-21
Volume
9
Issue
3
Pages
e1003389
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
OpenAlex
W2094388228
Cited by
199
References
90
Citations by year
2026: 6 · 2025: 6 · 2024: 14 · 2023: 13 · 2022: 18 · 2021: 22 · 2020: 13 · 2019: 17 · 2018: 17 · 2017: 9 · 2016: 16 · 2015: 23 · 2014: 18 · 2013: 6
FWCI
9.41
Type
journal article
Language
en
Open access
Locations
  • PLoS Genetics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Nottingham ePrints (University of Nottingham) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
  • University of Stirling
  • National Institutes of Health (HL- 47317, HL- 47327, HL- 47323)
  • Directorate for Biological Sciences
  • Medical Research Council (MR/K00414X/1)
  • Biotechnology and Biological Sciences Research Council (BB/X5106971, BB/C516779/1)
  • National Heart, Lung, and Blood Institute (R01HL047327, HL 47321, HL 45670, HL47323, R01HL047317, HL 47327, R01HL047323, HL47317, R01HL045670, R01HL047321)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
  • Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
Keywords
muscle aging, resistance training, endurance training, sarcopenia, mTOR signaling, rapamycin, muscle hypertrophy, lean body mass, all-trans retinoic acid, aryl hydrocarbon receptor signaling, age-related gene expression, post-transcriptional regulation, ribosomal genes, gene regulatory networks
MeSH terms
Adaptation, Physiological, Adolescent, Adult, Aged, Aging, Female, Humans, Male, Middle Aged, Signal Transduction, Exercise, Down-Regulation, Muscle, Skeletal, Gene Expression Profiling, Gene Regulatory Networks, Ribosome Subunits, TOR Serine-Threonine Kinases

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review