Evidence map›Paper›PMID 32579934›Full record

ArticleCell reports2020

Skeletal Muscle Transcriptomic Comparison between Long-Term Trained and Untrained Men and Women.

Mark A Chapman, Muhammad Arif, Eric B Emanuelsson, Stefan M Reitzner, Maléne E Lindholm, Adil Mardinoglu, Carl Johan Sundberg

Open access · goldAbstract readComparative Study
PubMed Publisher
In one paragraph

Article in Cell reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 5% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
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  5. The Immune System as a Biosensor of Health and Athletic Performance.Scandinavian journal of medicine & science in sports · 2026
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  17. Fast and slow muscle fiber transcriptome dynamics with lifelong endurance exercise.Journal of applied physiology (Bethesda, Md. : 1985) · 2024
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 3 countries.

Mark A ChapmanDepartment of Integrated Engineering, University of San Diego, San Diego, CA 92110, USA; Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden. Electronic address: markchapman@sandiego.edu.
Muhammad ArifScience for Life Laboratory, KTH-Royal Institute of Technology, 171 65 Solna, Sweden.
Eric B EmanuelssonDepartment of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden.
Stefan M ReitznerDepartment of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden.
Maléne E LindholmDepartment of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden; Department of Medicine, School of Medicine, Stanford University, Stanford CA 94305, USA.
Adil MardinogluScience for Life Laboratory, KTH-Royal Institute of Technology, 171 65 Solna, Sweden; Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London SE1 9RT, UK.
Carl Johan SundbergDepartment of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden; Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, 171 77 Stockholm, Sweden; Department of Laboratory Medicine, Karolinska Institutet, 141 52 Huddinge, Sweden.
Karolinska Institutet · SEKing's College London · GBScience for Life Laboratory · SEUniversity of San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To better understand the health benefits of lifelong exercise in humans, we conduct global skeletal muscle transcriptomic analyses of long-term endurance- (9 men, 9 women) and strength-trained (7 men) humans compared with age-matched untrained controls (7 men, 8 women). Transcriptomic analysis, Gene Ontology, and genome-scale metabolic modeling demonstrate changes in pathways related to the prevention of metabolic diseases, particularly with endurance training. Our data also show prominent sex differences between controls and that these differences are reduced with endurance training. Additionally, we compare our data with studies examining muscle gene expression before and after a months-long training period in individuals with metabolic diseases. This analysis reveals that training shifts gene expression in individuals with impaired metabolism to become more similar to our endurance-trained group. Overall, our data provide an extensive examination of the accumulated transcriptional changes that occur with decades-long training and identify important "exercise-responsive" genes that could attenuate metabolic disease.

Indexed as

Resistance TrainingAdultAerobiosisAthletesBiopsyFemaleGene OntologyGenome, HumanHumansMaleMiddle AgedMuscle, SkeletalPhysical EnduranceRestSedentary BehaviorSequence Analysis, RNAendurance trainingexercise physiologygene expressiongenome-scale metabolic modelhuman subjectsresistance trainingRNA sequencingskeletal muscleskeletal muscle metabolismskeletal muscle transcriptomics

Identifiers

PMID32579934
OpenAlexW3036135130

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.