Cited by 218Muscle Physiology and DisordersSingle-cell and spatial transcriptomicsNutrition and Health in Aging

Human skeletal muscle aging atlas

Open access
Kedlian, Veronika R., Wang, Yaning, Liu, Tianliang, Chen, Xiaoping, Bolt, Liam, Tudor, Catherine, Shen, Zhuojian, Fasouli, Eirini S. +24 more·2024·Nature Aging

Abstract

Skeletal muscle aging is a key contributor to age-related frailty and sarcopenia with substantial implications for global health. Here we profiled 90,902 single cells and 92,259 single nuclei from 17 donors to map the aging process in the adult human intercostal muscle, identifying cellular changes in each muscle compartment. We found that distinct subsets of muscle stem cells exhibit decreased ribosome biogenesis genes and increased CCL2 expression, causing different aging phenotypes. Our atlas also highlights an expansion of nuclei associated with the neuromuscular junction, which may reflect re-innervation, and outlines how the loss of fast-twitch myofibers is mitigated through regeneration and upregulation of fast-type markers in slow-twitch myofibers with age. Furthermore, we document the function of aging muscle microenvironment in immune cell attraction. Overall, we present a comprehensive human skeletal muscle aging resource ( https://www.muscleageingcellatlas.org/ ) together with an in-house mouse muscle atlas to study common features of muscle aging across species.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s43587-024-00613-3

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • This gradual aging-related reduction in SM mass contributes towards an overall decline in SM strength, function, and regenerative capacity, and is a key contributor to aging-related frailty.

    “This gradual aging-related reduction in SM mass (trending towards a state of sarcopenia) contributes towards an overall decline in SM strength, function, and regenerative capacity, and is a key contributor to aging-related frailty with important implications for global health and economics [29,30,31,32].”

    From Optimised Skeletal Muscle Mass as a Key Strategy for Obesity Management (2025) · cites this paper as [32]

    The Main section reports age-related loss of muscle mass and strength, sarcopenia, and reduced muscle stem-cell activation and proliferation. It does not establish that loss of mass itself causes the declines in strength, function, or regenerative capacity; nor does the cited passage address economic implications. The Main section links skeletal muscle aging to falls and fractures, but does not directly characterize loss of mass as a key cause of frailty. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 70

  1. [1]Tidball JG Regulation of muscle growth and regeneration by the immune system Nat. Rev. Immunol. 2017 17 165 178 10.1038/nri.2016.150 28163303 PMC5452982 · DOI · Paper page
  2. [2]Pedersen BK Febbraio MA Muscles, exercise and obesity: skeletal muscle as a secretory organ Nat. Rev. Endocrinol. 2012 8 457 465 10.1038/nrendo.2012.49 22473333 · DOI · Paper page
  3. [4]Siparsky PN Kirkendall DT Garrett WE Jr. Muscle changes in aging: understanding sarcopenia Sports Health 2014 6 36 40 10.1177/1941738113502296 24427440 PMC3874224 · DOI
  4. [7]Gopinath SD Rando TA Stem cell review series: aging of the skeletal muscle stem cell niche Aging Cell 2008 7 590 598 10.1111/j.1474-9726.2008.00399.x 18462272 · DOI
  5. [9]Kuswanto W Poor repair of skeletal muscle in aging mice reflects a defect in local, interleukin-33-dependent accumulation of regulatory T cells Immunity 2016 44 355 367 10.1016/j.immuni.2016.01.009 26872699 PMC4764071 · DOI
  6. [10]Larsson L Sarcopenia: aging-related loss of muscle mass and function Physiol. Rev. 2019 99 427 511 10.1152/physrev.00061.2017 30427277 PMC6442923 · DOI · Paper page
  7. [12]Barruet E Functionally heterogeneous human satellite cells identified by single cell RNA sequencing eLife 2020 9 e51576 10.7554/eLife.51576 32234209 PMC7164960 · DOI
  8. [14]De Micheli AJ Spector JA Elemento O Cosgrove BD A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations Skelet. Muscle 2020 10 19 10.1186/s13395-020-00236-3 32624006 PMC7336639 · DOI
  9. [15]McKellar DW Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration Commun. Biol. 2021 4 1280 10.1038/s42003-021-02810-x 34773081 PMC8589952 · DOI
  10. [17]Dos Santos M Single-nucleus RNA-seq and FISH identify coordinated transcriptional activity in mammalian myofibers Nat. Commun. 2020 11 5102 10.1038/s41467-020-18789-8 33037211 PMC7547110 · DOI · Paper page
  11. [18]Kim M Single-nucleus transcriptomics reveals functional compartmentalization in syncytial skeletal muscle cells Nat. Commun. 2020 11 6375 10.1038/s41467-020-20064-9 33311457 PMC7732842 · DOI
  12. [19]Orchard P Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits Genome Res. 2021 31 2258 2275 10.1101/gr.268482.120 34815310 PMC8647829 · DOI
  13. [20]Perez K Single nuclei profiling identifies cell specific markers of skeletal muscle aging, frailty, and senescence Aging (Albany NY) 2022 14 9393 9422 36516485 PMC9792217
  14. [21]Petrany MJ Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers Nat. Commun. 2020 11 6374 10.1038/s41467-020-20063-w 33311464 PMC7733460 · DOI
  15. [24]Schaum N Ageing hallmarks exhibit organ-specific temporal signatures Nature 2020 583 596 602 10.1038/s41586-020-2499-y 32669715 PMC7757734 · DOI · Paper page
  16. [25]Mangiola, S. et al. Whole body cell map tracks tissue-specific immune cell accumulation and plasticity loss through ageing. Preprint at bioRxiv10.1101/2023.06.08.542671 (2023).
  17. [26]Tintignac LA Brenner HR Ruegg MA Mechanisms regulating neuromuscular junction development and function and causes of muscle wasting Physiol. Rev. 2015 95 809 852 10.1152/physrev.00033.2014 26109340 · DOI
  18. [27]Ungvari Z Tarantini S Donato AJ Galvan V Csiszar A Mechanisms of vascular aging Circ. Res. 2018 123 849 867 10.1161/CIRCRESAHA.118.311378 30355080 PMC6248882 · DOI · Paper page
  19. [28]Tabula Sapiens Consortium The Tabula Sapiens: a multiple-organ, single-cell transcriptomic atlas of humans Science 2022 376 eabl4896 10.1126/science.abl4896 35549404 PMC9812260 · DOI · Paper page
  20. [29]Dell’Orso S Single cell analysis of adult mouse skeletal muscle stem cells in homeostatic and regenerative conditions Development 2019 146 dev174177 10.1242/dev.174177 30890574 PMC6602351 · DOI · Paper page
  21. [30]Machado L In situ fixation redefines quiescence and early activation of skeletal muscle stem cells Cell Rep. 2017 21 1982 1993 10.1016/j.celrep.2017.10.080 29141227 · DOI · Paper page
  22. [31]Sharifi S da Costa HFR Bierhoff H The circuitry between ribosome biogenesis and translation in stem cell function and ageing Mech. Ageing Dev. 2020 189 111282 10.1016/j.mad.2020.111282 32531294 · DOI
  23. [32]Giordani L High-dimensional single-cell cartography reveals novel skeletal muscle-resident cell populations Mol. Cell 2019 74 609 621 10.1016/j.molcel.2019.02.026 30922843 · DOI
  24. [33]Kimmel JC Hwang AB Scaramozza A Marshall WF Brack AS Aging induces aberrant state transition kinetics in murine muscle stem cells Development 2020 147 dev183855 10.1242/dev.183855 32198156 PMC7225128 · DOI · Paper page
  25. [34]Li H Muscle-secreted granulocyte colony-stimulating factor functions as metabolic niche factor ameliorating loss of muscle stem cells in aged mice EMBO J. 2019 38 e102154 10.15252/embj.2019102154 31736098 PMC6912059 · DOI
  26. [36]Dann E Henderson NC Teichmann SA Morgan MD Marioni JC Differential abundance testing on single-cell data using k-nearest neighbor graphs Nat. Biotechnol. 2022 40 245 253 10.1038/s41587-021-01033-z 34594043 PMC7617075 · DOI · Paper page
  27. [37]Alexander MS CD82 is a marker for prospective isolation of human muscle satellite cells and is linked to muscular dystrophies Cell Stem Cell 2016 19 800 807 10.1016/j.stem.2016.08.006 27641304 PMC5135584 · DOI
  28. [38]Relaix F Perspectives on skeletal muscle stem cells Nat. Commun. 2021 12 692 10.1038/s41467-020-20760-6 33514709 PMC7846784 · DOI
  29. [39]Lessard F Senescence-associated ribosome biogenesis defects contributes to cell cycle arrest through the Rb pathway Nat. Cell Biol. 2018 20 789 799 10.1038/s41556-018-0127-y 29941930 · DOI · Paper page
  30. [41]Bengal E Perdiguero E Serrano AL Munoz-Canoves P Rejuvenating stem cells to restore muscle regeneration in aging F1000Res. 2017 6 76 10.12688/f1000research.9846.1 28163911 PMC5271918 · DOI
  31. [42]Thompson WL Van Eldik LJ Inflammatory cytokines stimulate the chemokines CCL2/MCP-1 and CCL7/MCP-3 through NFκB and MAPK dependent pathways in rat astrocytes [corrected] Brain Res. 2009 1287 47 57 10.1016/j.brainres.2009.06.081 19577550 PMC2725204 · DOI
  32. [44]Van de Sande B A scalable SCENIC workflow for single-cell gene regulatory network analysis Nat. Protoc. 2020 15 2247 2276 10.1038/s41596-020-0336-2 32561888 · DOI · Paper page
  33. [45]Petit CS Roczniak-Ferguson A Ferguson SM Recruitment of folliculin to lysosomes supports the amino acid-dependent activation of Rag GTPases J. Cell Biol. 2013 202 1107 1122 10.1083/jcb.201307084 24081491 PMC3787382 · DOI · Paper page
  34. [46]Tsun ZY The folliculin tumor suppressor is a GAP for the RagC/D GTPases that signal amino acid levels to mTORC1 Mol. Cell 2013 52 495 505 10.1016/j.molcel.2013.09.016 24095279 PMC3867817 · DOI · Paper page
  35. [47]Ratnayake D Macrophages provide a transient muscle stem cell niche via NAMPT secretion Nature 2021 591 281 287 10.1038/s41586-021-03199-7 33568815 · DOI
  36. [48]Moresi V Adamo S Berghella L The JAK/STAT pathway in skeletal muscle pathophysiology Front. Physiol. 2019 10 500 10.3389/fphys.2019.00500 31114509 PMC6502894 · DOI
  37. [49]Caldow MK Steinberg GR Cameron-Smith D Impact of SOCS3 overexpression on human skeletal muscle development in vitro Cytokine 2011 55 104 109 10.1016/j.cyto.2011.03.012 21478033 · DOI
  38. [50]Sun L JAK1–STAT1–STAT3, a key pathway promoting proliferation and preventing premature differentiation of myoblasts J. Cell Biol. 2007 179 129 138 10.1083/jcb.200703184 17908914 PMC2064742 · DOI
  39. [51]Sato S Ogura Y Kumar A TWEAK/Fn14 signaling axis mediates skeletal muscle atrophy and metabolic dysfunction Front. Immunol. 2014 5 18 10.3389/fimmu.2014.00018 24478779 PMC3902304 · DOI
  40. [52]Li L Xiong WC Mei L Neuromuscular junction formation, aging, and disorders Annu. Rev. Physiol. 2018 80 159 188 10.1146/annurev-physiol-022516-034255 29195055 · DOI
  41. [53]Bonanomi D Ret is a multifunctional coreceptor that integrates diffusible- and contact-axon guidance signals Cell 2012 148 568 582 10.1016/j.cell.2012.01.024 22304922 PMC3286831 · DOI
  42. [54]Hallock PT Chin S Blais S Neubert TA Glass DJ Sorbs1 and -2 interact with CrkL and are required for acetylcholine receptor cluster formation Mol. Cell. Biol. 2016 36 262 270 10.1128/MCB.00775-15 26527617 PMC4719301 · DOI
  43. [55]Hippenmeyer S Huber RM Ladle DR Murphy K Arber S ETS transcription factor Erm controls subsynaptic gene expression in skeletal muscles Neuron 2007 55 726 740 10.1016/j.neuron.2007.07.028 17785180 · DOI
  44. [56]Kummer TT Misgeld T Lichtman JW Sanes JR Nerve-independent formation of a topologically complex postsynaptic apparatus J. Cell Biol. 2004 164 1077 1087 10.1083/jcb.200401115 15037598 PMC2172060 · DOI
  45. [57]Lin H Decoding the transcriptome of denervated muscle at single-nucleus resolution J. Cachexia Sarcopenia Muscle 2022 13 2102 2117 10.1002/jcsm.13023 35726356 PMC9398230 · DOI
  46. [58]Murgia M Single muscle fiber proteomics reveals fiber-type-specific features of human muscle aging Cell Rep. 2017 19 2396 2409 10.1016/j.celrep.2017.05.054 28614723 · DOI · Paper page
  47. [59]Schiaffino S Rossi AC Smerdu V Leinwand LA Reggiani C Developmental myosins: expression patterns and functional significance Skelet. Muscle 2015 5 22 10.1186/s13395-015-0046-6 26180627 PMC4502549 · DOI
  48. [60]Webster C Silberstein L Hays AP Blau HM Fast muscle fibers are preferentially affected in Duchenne muscular dystrophy Cell 1988 52 503 513 10.1016/0092-8674(88)90463-1 3342447 · DOI
  49. [61]Lin JR High-plex immunofluorescence imaging and traditional histology of the same tissue section for discovering image-based biomarkers Nat. Cancer 2023 4 1036 1052 10.1038/s43018-023-00576-1 37349501 PMC10368530 · DOI
  50. [62]Krasniewski LK Single-cell analysis of skeletal muscle macrophages reveals age-associated functional subpopulations eLife 2022 11 e77974 10.7554/eLife.77974 36259488 PMC9629833 · DOI
  51. [63]Fuertes-Alvarez S Izeta A Terminal Schwann cell aging: implications for age-associated neuromuscular dysfunction Aging Dis. 2021 12 494 514 10.14336/AD.2020.0708 33815879 PMC7990373 · DOI
  52. [64]Fukada K Kajiya K Age-related structural alterations of skeletal muscles and associated capillaries Angiogenesis 2020 23 79 82 10.1007/s10456-020-09705-1 31993832 · DOI
  53. [65]Hirata A Expression profiling of cytokines and related genes in regenerating skeletal muscle after cardiotoxin injection: a role for osteopontin Am. J. Pathol. 2003 163 203 215 10.1016/S0002-9440(10)63644-9 12819025 PMC1868192 · DOI
  54. [66]Warren GL Role of CC chemokines in skeletal muscle functional restoration after injury Am. J. Physiol. Cell Physiol. 2004 286 C1031 C1036 10.1152/ajpcell.00467.2003 15075201 · DOI
  55. [67]Efremova M Vento-Tormo M Teichmann SA Vento-Tormo R CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes Nat. Protoc. 2020 15 1484 1506 10.1038/s41596-020-0292-x 32103204 · DOI · Paper page
  56. [68]Zhuang J Comparison of multi-tissue aging between human and mouse Sci. Rep. 2019 9 6220 10.1038/s41598-019-42485-3 30996271 PMC6470208 · DOI
  57. [69]Zhang MJ Pisco AO Darmanis S Zou J Mouse aging cell atlas analysis reveals global and cell type-specific aging signatures eLife 2021 10 e62293 10.7554/eLife.62293 33847263 PMC8046488 · DOI
  58. [71]Forcina L Miano C Scicchitano BM Musaro A Signals from the niche: insights into the role of IGF-1 and IL-6 in modulating skeletal muscle fibrosis Cells 2019 8 232 10.3390/cells8030232 30862132 PMC6468756 · DOI
  59. [73]Zou Z A single-cell transcriptomic atlas of human skin aging Dev. Cell 2021 56 383 397 10.1016/j.devcel.2020.11.002 33238152 · DOI · Paper page
  60. [74]Yi W A single-cell transcriptome atlas of the aging human and macaque retina Natl Sci. Rev. 2021 8 nwaa179 34691611 PMC8288367
  61. [75]Lee NYS Li M Ang KS Chen J Establishing a human bone marrow single cell reference atlas to study ageing and diseases Front. Immunol. 2023 14 1127879 10.3389/fimmu.2023.1127879 37006302 PMC10050687 · DOI
  62. [76]Hepple RT Rice CL Innervation and neuromuscular control in ageing skeletal muscle J. Physiol. 2016 594 1965 1978 10.1113/JP270561 26437581 PMC4933121 · DOI
  63. [79]Fleming SJ Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender Nat. Methods 2023 20 1323 1335 10.1038/s41592-023-01943-7 37550580 · DOI · Paper page
  64. [82]Raudvere U g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update) Nucleic Acids Res. 2019 47 W191 W198 10.1093/nar/gkz369 31066453 PMC6602461 · DOI · Paper page
  65. [83]Zhou Y Metascape provides a biologist-oriented resource for the analysis of systems-level datasets Nat. Commun. 2019 10 1523 10.1038/s41467-019-09234-6 30944313 PMC6447622 · DOI · Paper page
  66. [85]Yoshida M Local and systemic responses to SARS-CoV-2 infection in children and adults Nature 2022 602 321 327 10.1038/s41586-021-04345-x 34937051 PMC8828466 · DOI · Paper page
  67. [86]Young AMH A map of transcriptional heterogeneity and regulatory variation in human microglia Nat. Genet. 2021 53 861 868 10.1038/s41588-021-00875-2 34083789 PMC7610960 · DOI · Paper page
  68. [87]van der Walt S scikit-image: image processing in Python PeerJ 2014 2 e453 10.7717/peerj.453 25024921 PMC4081273 · DOI
  69. [88]Stringer C Wang T Michaelos M Pachitariu M Cellpose: a generalist algorithm for cellular segmentation Nat. Methods 2021 18 100 106 10.1038/s41592-020-01018-x 33318659 · DOI · Paper page
  70. [89]Berg S ilastik: interactive machine learning for (bio)image analysis Nat. Methods 2019 16 1226 1232 10.1038/s41592-019-0582-9 31570887 · DOI

Cited by

Sorted by citations

Authors
Kedlian, V. R., Wang, Y., Liu, T., Chen, X., Bolt, L., Tudor, C., Shen, Z., Fasouli, E. S., Prigmore, E., Kleshchevnikov, V., Pett, J. P., Li, T., Lawrence, J. E. G., Perera, S., Prete, M., Huang, N., Guo, Q., Zeng, X., Yang, L., Polański, K., Chipampe, N.-J., Dabrowska, M., Li, X., Bayraktar, O. A., Patel, M., Kumasaka, N., Mahbubani, K. T., Xiang, A. P., Meyer, K. B., Saeb-Parsy, K., Teichmann, S. A., & Zhang, H.
Affiliations
  • Wellcome Sanger Institute (GB)
  • Sun Yat-sen University (CN)
  • University of Cambridge (GB)
Corresponding author
  • Teichmann, Sarah A.
  • Zhang, Hongbo
Venue
Nature Aging
Published
2024-04-15
Volume
4
Issue
5
Pages
727-744
ISSN
2662-8465 (ISSN-L)
OpenAlex
W4394812780
Cited by
218
References
17
Citations by year
2026: 107 · 2025: 87 · 2024: 23 · 2022: 1
FWCI
29.54
Type
journal article
Language
en
Open access
Locations
  • Nature Aging (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • BOA (University of Milano-Bicocca) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
Funders
  • Wellcome Trust (WT211276/Z/18/Z, WT206194, 220540/Z/20/A)
  • National Natural Science Foundation of China (32000840, 31871370)
  • Natural Science Foundation of Guangdong Province (2021A1515012065)
  • EC | Horizon 2020 Framework Programme (101026233)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
Keywords
skeletal muscle aging, intercostal muscles, single-cell atlas, single-nucleus RNA sequencing, muscle stem cells, ribosome biogenesis, MCP-1, neuromuscular junction, reinnervation, myofiber regeneration, muscle microenvironment, sarcopenia, age-related frailty
MeSH terms
Adult, Aged, Aging, Animals, Female, Humans, Male, Middle Aged, Neuromuscular Junction, Muscle, Skeletal, Mice, Sarcopenia

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review