Evidence map›Paper›PMID 36198295›Full record

ArticleCell metabolism2022

Single-cell dissection of the obesity-exercise axis in adipose-muscle tissues implies a critical role for mesenchymal stem cells.

Jiekun Yang, Maria Vamvini, Pasquale Nigro, Li-Lun Ho, Kyriakitsa Galani, Marcus Alvarez, Yosuke Tanigawa, Ashley Renfro, Nicholas P Carbone, Markku Laakso and 7 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 pooled it
17.0field-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

61 citing papers in PubMed, 1 synthesis or guideline pooled it, 116 citations in OpenAlex.

  1. Guideline
  2. Review
  3. Exercise and Fat: A Primer.Sports medicine - open · 2026
    Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
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  10. Article
  11. Article
  12. Article
  13. Designing 5' UTR sequences improves the capacity of mRNA therapeutics in preclinical models of aging and obesity.Molecular therapy : the journal of the American Society of Gene Therapy · 2026
    Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Exercise benefits in metabolism on cardiovascular disease.Frontiers in cardiovascular medicine · 2026
    Review
  19. Review
  20. Review

1 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

17 authors at 5 institutions in 2 countries.

Jiekun YangComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Maria VamviniSection on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
Pasquale NigroSection on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
Li-Lun HoComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Kyriakitsa GalaniComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Marcus AlvarezDepartment of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA.
Yosuke TanigawaComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Ashley RenfroComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Nicholas P CarboneSection on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
Markku LaaksoInstitute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland; Department of Medicine, Kuopio University Hospital, Kuopio, Finland.
Leandro Z AgudeloComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Päivi PajukantaDepartment of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA; Institute for Precision Health, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA.
Michael F HirshmanSection on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
Roeland J W MiddelbeekSection on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
Kevin GroveNovo Nordisk Research Center, Seattle, WA, USA.
Laurie J GoodyearSection on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA. Electronic address: laurie.goodyear@joslin.harvard.edu.
Manolis KellisComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: manoli@mit.edu.
Broad Institute · USJoslin Diabetes Center · USUniversity of California, Los Angeles · USNovo Nordisk (United States) · USUniversity of Eastern Finland · FI

Funding

SPECIAL ASSAY COREP30DK036836 · NIDDK · JOSLIN DIABETES CENTER · PI ROHIT N. KULKARNI · 1986 to 2026
$50.5M
TRAINING IN DIABETES AND METABOLISMT32DK007260 · NIDDK · JOSLIN DIABETES CENTER · PI LAURIE J GOODYEAR · 1986 to 2026
$13.6M
EDAC: ENCODE Data Analysis CenterU24HG009446 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GERSTEIN, MARK BENDER, WENG, ZHIPING · 2017 to 2022
$10.4M
Novel Mechanisms of Exercise Training Effects on Glucose HomeostasisR01DK099511 · NIDDK · JOSLIN DIABETES CENTER · PI LAURIE J GOODYEAR · 2014 to 2026
$6.5M
Single-Cell Transcriptional and Epigenomic Dissection to Identify Therapeutic Targets for ALS and FTDR01AG067151 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BELZIL, VERONIQUE, KELLIS, MANOLIS · 2021 to 2025
$3.7M
Methods for Genomic Analysis in Heterogeneous TissuesR01HG010505 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HALPERIN, ERAN · 2019 to 2022
$2.6M
Construction of an integrated immune - vascular brain - chip as a platform for the study, drug screening, and treatments of Alzheimer's diseaseUG3NS115064 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BLANCHARD, JOEL WILLIAM, KELLIS, MANOLIS · 2019 to 2020
$2.5M
Genetics of adipose cell-type expression and cardiometabolic traitsR01DK132775 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MOHLKE, KAREN L., PAJUKANTA, PAIVI · 2022 to 2025
$2.4M
Interpreting non-coding variants using epigenomics, regulatory models, & validation experimentsR01HG008155 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2015 to 2017
$2.3M
Harvard Training Program in Bioinformatics Applied to Diabetes, Obesity and Metabolism.T32DK110919 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI FLOREZ, JOSE CARLOS, PATEL, CHIRAG J. · 2017 to 2021
$1.3M
Mechanisms of exercise effects in obese humans: sex-specific regulation of novel adipose tissue functionK23DK114550 · NIDDK · JOSLIN DIABETES CENTER · PI MIDDELBEEK, ROELAND J · 2018 to 2022
$956k
Multi-omics approach to understanding the beneficial effects of exercise in diabetesF32DK126432 · NIDDK · JOSLIN DIABETES CENTER · PI VAMVINI, MARIA · 2020 to 2021
$227k
NHGRI NIH HHS R01 HG008155NHGRI NIH HHS R01 HG010505NHGRI NIH HHS U24 HG009446NIA NIH HHS R01 AG067151NIDDK NIH HHS F32 DK126432NIDDK NIH HHS K23 DK114550NIDDK NIH HHS P30 DK036836NIDDK NIH HHS R01 DK099511NIDDK NIH HHS R01 DK132775NIDDK NIH HHS T32 DK007260NIDDK NIH HHS T32 DK110919NINDS NIH HHS UG3 NS115064
6 · The paper itself

Abstract

Exercise training is critical for the prevention and treatment of obesity, but its underlying mechanisms remain incompletely understood given the challenge of profiling heterogeneous effects across multiple tissues and cell types. Here, we address this challenge and opposing effects of exercise and high-fat diet (HFD)-induced obesity at single-cell resolution in subcutaneous and visceral white adipose tissue and skeletal muscle in mice with diet and exercise training interventions. We identify a prominent role of mesenchymal stem cells (MSCs) in obesity and exercise-induced tissue adaptation. Among the pathways regulated by exercise and HFD in MSCs across the three tissues, extracellular matrix remodeling and circadian rhythm are the most prominent. Inferred cell-cell interactions implicate within- and multi-tissue crosstalk centered around MSCs. Overall, our work reveals the intricacies and diversity of multi-tissue molecular responses to exercise and obesity and uncovers a previously underappreciated role of MSCs in tissue-specific and multi-tissue beneficial effects of exercise.

Indexed as

Adipose TissueMesenchymal Stem CellsAnimalsDiet, High-FatMiceMice, Inbred C57BLMuscle, SkeletalObesitycircadian rhythm pathwayexerciseextracellular matrix remodelingmesenchymal stem cellmulti-tissue crosstalkobesitysingle-cell atlasskeletal musclewhite adipose tissuewithin-tissue crosstalk

Identifiers

PMID36198295
PMCPMC9558082
OpenAlexW4300980012

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.