Evidence map›Paper›PMID 37494090›Full record

ArticleeLife2023

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance.

Stewart W C Masson, Søren Madsen, Kristen C Cooke, Meg Potter, Alexis Diaz Vegas, Luke Carroll, Senthil Thillainadesan, Harry B Cutler, Ken R Walder, Gregory J Cooney and 3 more

Abstract read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Fifteen years of the Diversity Outbred mouse model: a review.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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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

13 authors.

Stewart W C MassonCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.ORCID 0000-0003-4514-7009
Søren MadsenCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.
Kristen C CookeCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.
Meg PotterCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.
Alexis Diaz VegasCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.
Luke CarrollAustralian Proteome Analysis Facility, Macquarie University, Macquarie Park, Australia.
Senthil ThillainadesanCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.
Harry B CutlerCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.ORCID 0000-0002-2074-8599
Ken R WalderSchool of Medicine, Deakin University, Geelong, Australia.ORCID 0000-0002-6758-4763
Gregory J CooneyCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.ORCID 0000-0003-0012-2529
Grant MorahanCentre for Diabetes Research, Harry Perkins Institute of Medical Research, Murdoch, Australia.
Jacqueline StöckliCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.
David E JamesCharles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.ORCID 0000-0001-5946-5257

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. 'Diversity Outbred in Australia (DOz)' is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscle's contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focusing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complementary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin-resistant mouse muscle and palmitate-induced insulin-resistant myotubes demonstrated potent insulin action restoration, potentially via upregulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems-level analysis by identifying potential therapeutics for insulin resistance.

Indexed as

Insulin ResistanceAnimalsGenetic VariationInsulinMiceMuscle Fibers, SkeletalMuscle, SkeletalProteinsInsulinProteinscomputational biologyDiversity Outbreddrug repurposinginsulin resistancemouseskeletal musclesystems biologythiostrepton

Identifiers

PMID37494090
PMCPMC10371229

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.