Evidence map›Paper›PMID 38643460›Full record

ArticleAging2024

A novel deep proteomic approach in human skeletal muscle unveils distinct molecular signatures affected by aging and resistance training.

Michael D Roberts, Bradley A Ruple, Joshua S Godwin, Mason C McIntosh, Shao-Yung Chen, Nicholas J Kontos, Anthony Agyin-Birikorang, Max Michel, Daniel L Plotkin, Madison L Mattingly and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 18 citations in OpenAlex.

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  15. Omics Sciences in Regular Physical Activity.International journal of molecular sciences · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 1 institution in 1 country.

Michael D RobertsSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Bradley A RupleSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Joshua S GodwinSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Mason C McIntoshSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Shao-Yung ChenSeer, Inc., Redwood City, CA 94065, USA.
Nicholas J KontosSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Anthony Agyin-BirikorangSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Max MichelSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Daniel L PlotkinSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Madison L MattinglySchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Brooks MobleySchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Tim N ZiegenfussThe Center for Applied Health Sciences, Canfield, OH 44406, USA.
Andrew D FrugeCollege of Nursing, Auburn University, Auburn, AL 36849, USA.
Andreas N KavazisSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Auburn University · US

Funding

G-RISE at Auburn UniversityT32GM141739 · NIGMS · AUBURN UNIVERSITY AT AUBURN · PI CLAYTON, TAFFYE BENSON, RUSSELL, MELODY L · 2021 to 2024
$1.2M
NIGMS NIH HHS T32 GM141739
6 · The paper itself

Abstract

The skeletal muscle proteome alterations to aging and resistance training have been reported in prior studies. However, conventional proteomics in skeletal muscle typically yields wide protein abundance ranges that mask the detection of lowly expressed proteins. Thus, we adopted a novel deep proteomics approach whereby myofibril (MyoF) and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS). Specifically, we investigated MyoF and non-MyoF proteomic profiles of the vastus lateralis muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6). Additionally, MA muscle was analyzed following eight weeks of resistance training (RT, 2d/week). Across all participants, the number of non-MyoF proteins detected averaged to be 5,645±266 (range: 4,888-5,987) and the number of MyoF proteins detected averaged to be 2,611±326 (range: 1,944-3,101). Differences in the non-MyoF (8.4%) and MyoF (2.5%) proteomes were evident between age cohorts, and most differentially expressed non-MyoF proteins (447/543) were more enriched in MA versus Y. Biological processes in the non-MyoF fraction were predicted to be operative in MA versus Y including increased cellular stress, mRNA splicing, translation elongation, and ubiquitin-mediated proteolysis. RT in MA participants only altered ~0.3% of MyoF and ~1.0% of non-MyoF proteomes. In summary, aging and RT predominantly affect non-contractile proteins in skeletal muscle. Additionally, marginal proteome adaptations with RT suggest more rigorous training may stimulate more robust effects or that RT, regardless of age, subtly alters basal state skeletal muscle protein abundances.

Indexed as

AgingMuscle, SkeletalProteomicsResistance TrainingAdultFemaleHumansMaleMiddle AgedMuscle ProteinsProteomeYoung AdultMuscle ProteinsProteomeagingdeep proteomicsresistance trainingskeletal muscle

Identifiers

PMID38643460
PMCPMC11087122
OpenAlexW4394963881

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.