Evidence map›Paper›PMID 34732242›Full record

ArticleClinical epigenetics2021

Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism.

Shanie Landen, Macsue Jacques, Danielle Hiam, Javier Alvarez-Romero, Nicholas R Harvey, Larisa M Haupt, Lyn R Griffiths, Kevin J Ashton, Séverine Lamon, Sarah Voisin and 1 more

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 4 pooled it
4.9field-weighted citation impact, top 3% 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

31 citing papers in PubMed, 4 syntheses or guidelines pooled it, 60 citations in OpenAlex.

  1. Pooled it
  2. Molecular Effects of Physical Activity and Body Composition: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2025
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Science advances · 2025
    Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
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

11 authors at 4 institutions in 1 country.

Shanie LandenInstitute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.
Macsue JacquesInstitute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.
Danielle HiamInstitute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.
Javier Alvarez-RomeroInstitute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.
Nicholas R HarveyFaculty of Health Sciences and Medicine, Bond University, Gold Coast, QLD, 4226, Australia.
Larisa M HauptCentre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia.
Lyn R GriffithsCentre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia.
Kevin J AshtonFaculty of Health Sciences and Medicine, Bond University, Gold Coast, QLD, 4226, Australia.
Séverine LamonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.
Sarah Voisin *Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.
Nir Eynon *Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia. Nir.Eynon@vu.edu.au.ORCID 0000-0003-4046-8276
Victoria University · AUBond University · AUDeakin University · AUQueensland University of Technology · AU

Funding

australian research council DP190103081national health and medical research council APP11577321national health and medical research council APP1194159
6 · The paper itself

Abstract

Nearly all human complex traits and diseases exhibit some degree of sex differences, with epigenetics being one of the main contributing factors. Various tissues display sex differences in DNA methylation; however, this has not yet been explored in skeletal muscle, despite skeletal muscle being among the tissues with the most transcriptomic sex differences. For the first time, we investigated the effect of sex on autosomal DNA methylation in human skeletal muscle across three independent cohorts (Gene SMART, FUSION, and GSE38291) using a meta-analysis approach, totalling 369 human muscle samples (222 males and 147 females), and integrated this with known sex-biased transcriptomics. We found 10,240 differentially methylated regions (DMRs) at FDR < 0.005, 94% of which were hypomethylated in males, and gene set enrichment analysis revealed that differentially methylated genes were involved in muscle contraction and substrate metabolism. We then investigated biological factors underlying DNA methylation sex differences and found that circulating hormones were not associated with differential methylation at sex-biased DNA methylation loci; however, these sex-specific loci were enriched for binding sites of hormone-related transcription factors (with top TFs including androgen (AR), estrogen (ESR1), and glucocorticoid (NR3C1) receptors). Fibre type proportions were associated with differential methylation across the genome, as well as across 16% of sex-biased DNA methylation loci (FDR < 0.005). Integration of DNA methylomic results with transcriptomic data from the GTEx database and the FUSION cohort revealed 326 autosomal genes that display sex differences at both the epigenome and transcriptome levels. Importantly, transcriptional sex-biased genes were overrepresented among epigenetic sex-biased genes (p value = 4.6e-13), suggesting differential DNA methylation and gene expression between male and female muscle are functionally linked. Finally, we validated expression of three genes with large effect sizes (FOXO3A, ALDH1A1, and GGT7) in the Gene SMART cohort with qPCR. GGT7, involved in antioxidant metabolism, displays male-biased expression as well as lower methylation in males across the three cohorts. In conclusion, we uncovered 8420 genes that exhibit DNA methylation differences between males and females in human skeletal muscle that may modulate mechanisms controlling muscle metabolism and health.

Indexed as

Sex FactorsAgedEpigenomeFemaleGene Expression ProfilingHumansMaleMiddle AgedMuscle, SkeletalSubstrate CyclingDNA methylationEpigenome-wide study (EWAS)Gene expressionSex differencesSkeletal muscle

Identifiers

PMID34732242
PMCPMC8567658
OpenAlexW3209032884

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.