Evidence map›Paper›PMID 31980607›Full record

SynthesisNature communications2020

Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity.

Nicolas J Pillon, Brendan M Gabriel, Lucile Dollet, Jonathon A B Smith, Laura Sardón Puig, Javier Botella, David J Bishop, Anna Krook, Juleen R Zierath

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 261 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
261citing papers in PubMed, 8 pooled it
27.8field-weighted citation impact, top 1% 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

261 citing papers in PubMed, 8 syntheses or guidelines pooled it, 430 citations in OpenAlex.

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  5. PROKR1-CREB-NR4A2 axis for oxidative muscle fiber specification and improvement of metabolic function.Proceedings of the National Academy of Sciences of the United States of America · 2024
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201 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 3 countries.

Nicolas J PillonDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-1107-9490
Brendan M GabrielDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-6878-8779
Lucile DolletDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
Jonathon A B SmithDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-2452-1655
Laura Sardón PuigDepartment of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0481-4023
Javier BotellaInstitute for Health and Sport, Victoria University, Melbourne, Australia.ORCID http://orcid.org/0000-0001-9722-8519
David J BishopInstitute for Health and Sport, Victoria University, Melbourne, Australia.ORCID http://orcid.org/0000-0002-6956-9188
Anna KrookDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0891-0258
Juleen R ZierathDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden. Juleen.Zierath@ki.se.ORCID http://orcid.org/0000-0001-6891-7497
Karolinska Institutet · SEVictoria University · AUUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The molecular mechanisms underlying the response to exercise and inactivity are not fully understood. We propose an innovative approach to profile the skeletal muscle transcriptome to exercise and inactivity using 66 published datasets. Data collected from human studies of aerobic and resistance exercise, including acute and chronic exercise training, were integrated using meta-analysis methods (www.metamex.eu). Here we use gene ontology and pathway analyses to reveal selective pathways activated by inactivity, aerobic versus resistance and acute versus chronic exercise training. We identify NR4A3 as one of the most exercise- and inactivity-responsive genes, and establish a role for this nuclear receptor in mediating the metabolic responses to exercise-like stimuli in vitro. The meta-analysis (MetaMEx) also highlights the differential response to exercise in individuals with metabolic impairments. MetaMEx provides the most extensive dataset of skeletal muscle transcriptional responses to different modes of exercise and an online interface to readily interrogate the database.

Indexed as

Sedentary BehaviorAdaptation, PhysiologicalDNA-Binding ProteinsExerciseGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansMuscle, SkeletalReceptors, SteroidReceptors, Thyroid HormoneResistance TrainingDNA-Binding ProteinsNR4A3 protein, humanReceptors, SteroidReceptors, Thyroid Hormone

Identifiers

PMID31980607
PMCPMC6981202
OpenAlexW3002380642

What OpenQuestion 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 OpenQuestion graph.