Cited by 68

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Prevalent mesenchymal drift in aging and disease is reversed by partial reprogramming

Lu, Jinlong Y., Tu, William B., Li, Ronghui, Weng, Mingxi, Sanketi, Bhargav D., Yuan, Baolei, Reddy, Pradeep, Rodriguez Esteban, Concepcion, Izpisua Belmonte, Juan Carlos·2025·Cell

Abstract

The loss of cellular and tissue identity is a hallmark of aging and numerous diseases, but the underlying mechanisms are not well understood. Our analysis of gene expression data from over 40 human tissues and 20 diseases reveals a pervasive upregulation of mesenchymal genes across multiple cell types, along with an altered composition of stromal cell populations, denoting a "mesenchymal drift" (MD). Increased MD correlates with disease progression, reduced patient survival, and an elevated mortality risk, whereas suppression of key MD transcription factors leads to epigenetic rejuvenation. Notably, Yamanaka factor-induced partial reprogramming can markedly reduce MD before dedifferentiation and gain of pluripotency, rejuvenating the aging transcriptome at the cellular and tissue levels. These findings provide mechanistic insight into the underlying beneficial effects of partial reprogramming and offer a framework for developing interventions to reverse age-related diseases using the partial reprogramming approach.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.cell.2025.07.031

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • Partial epigenetic reprogramming leverages transient expression of Yamanaka factors to rejuvenate cells and reverse senescence markers without inducing cell death, offering a route toward cellular restoration rather than removal.

    “An emerging, conceptually transformative frontier is partial epigenetic reprogramming, which leverages transient expression of Yamanaka factors to rejuvenate cells and reverse senescence markers without inducing cell death, offering a route toward cellular restoration rather than removal143–145.”

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 90

  1. Gorelov, 2024, A cellular identity crisis? Plasticity changes during aging and rejuvenation, Genes Dev., 38, 823, 10.1101/gad.351728.124 · DOI
  2. Ho, 2019, Remodeling of Bone Marrow Hematopoietic Stem Cell Niches Promotes Myeloid Cell Expansion during Premature or Physiological Aging, Cell Stem Cell, 25, 407, 10.1016/j.stem.2019.06.007 · DOI · Paper page
  3. Izgi, 2022, Inter-tissue convergence of gene expression during ageing suggests age-related loss of tissue and cellular identity, eLife, 11, 10.7554/eLife.68048 · DOI
  4. Li, 2020, Aging-Associated Alterations in Mammary Epithelia and Stroma Revealed by Single-Cell RNA Sequencing, Cell Rep., 33, 10.1016/j.celrep.2020.108566 · DOI · Paper page
  5. Salzer, 2018, Identity Noise and Adipogenic Traits Characterize Dermal Fibroblast Aging, Cell, 175, 1575, 10.1016/j.cell.2018.10.012 · DOI
  6. Patrick, 2024, The activity of early-life gene regulatory elements is hijacked in aging through pervasive AP-1-linked chromatin opening, Cell Metab., 36, 1858, 10.1016/j.cmet.2024.06.006 · DOI
  7. Takahashi, 2006, Induction of Pluripotent Stem Cells from Mouse Embryonic and Adult Fibroblast Cultures by Defined Factors, Cell, 126, 663, 10.1016/j.cell.2006.07.024 · DOI · Paper page
  8. Chen, 2021, Reversible reprogramming of cardiomyocytes to a fetal state drives heart regeneration in mice, Science, 373, 1537, 10.1126/science.abg5159 · DOI · Paper page
  9. Zhang, 2020, The ageing epigenome and its rejuvenation, Nat. Rev. Mol. Cell Biol., 21, 137, 10.1038/s41580-019-0204-5 · DOI · Paper page
  10. Li, 2010, A mesenchymal-to-epithelial transition initiates and is required for the nuclear reprogramming of mouse fibroblasts, Cell Stem Cell, 7, 51, 10.1016/j.stem.2010.04.014 · DOI · Paper page
  11. Samavarchi-Tehrani, 2010, Functional genomics reveals a BMP-driven mesenchymal-to-epithelial transition in the initiation of somatic cell reprogramming, Cell Stem Cell, 7, 64, 10.1016/j.stem.2010.04.015 · DOI · Paper page
  12. Lu, 2022, Comparative transcriptomics reveals circadian and pluripotency networks as two pillars of longevity regulation, Cell Metab., 34, 836, 10.1016/j.cmet.2022.04.011 · DOI
  13. Ferrucci, 2018, Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty, Nat. Rev. Cardiol., 15, 505, 10.1038/s41569-018-0064-2 · DOI · Paper page
  14. Jaffar, 2022, Matrix metalloproteinase-7 is increased in lung bases but not apices in idiopathic pulmonary fibrosis, ERJ Open Res., 8, 10.1183/23120541.00191-2022 · DOI
  15. Adams, 2020, Single-cell RNA-seq reveals ectopic and aberrant lung-resident cell populations in idiopathic pulmonary fibrosis, Sci. Adv., 6, 10.1126/sciadv.aba1983 · DOI · Paper page
  16. Pfister, 2021, NASH limits anti-tumour surveillance in immunotherapy-treated HCC, Nature, 592, 450, 10.1038/s41586-021-03362-0 · DOI · Paper page
  17. Ramachandran, 2019, Resolving the fibrotic niche of human liver cirrhosis at single-cell level, Nature, 575, 512, 10.1038/s41586-019-1631-3 · DOI · Paper page
  18. Liu, 2022, Multi-Scalar Data Integration Links Glomerular Angiopoietin-Tie Signaling Pathway Activation With Progression of Diabetic Kidney Disease, Diabetes, 71, 2664, 10.2337/db22-0169 · DOI
  19. Saaoud, 2023, Chronic Kidney Disease Transdifferentiates Veins into a Specialized Immune–Endocrine Organ with Increased MYCN-AP1 Signaling, Cells, 12, 10.3390/cells12111482 · DOI
  20. Abedini, 2024, Single-cell multi-omic and spatial profiling of human kidneys implicates the fibrotic microenvironment in kidney disease progression, Nat. Genet., 56, 1712, 10.1038/s41588-024-01802-x · DOI
  21. Tan, 2020, Epigenomes of Human Hearts Reveal New Genetic Variants Relevant for Cardiac Disease and Phenotype, Circ. Res., 127, 761, 10.1161/CIRCRESAHA.120.317254 · DOI
  22. Alsaigh, 2022, Decoding the transcriptome of calcified atherosclerotic plaque at single-cell resolution, Commun. Biol., 5, 10.1038/s42003-022-04056-7 · DOI
  23. Solé-Boldo, 2020, Single-cell transcriptomes of the human skin reveal age-related loss of fibroblast priming, Commun. Biol., 3, 10.1038/s42003-020-0922-4 · DOI · Paper page
  24. Smillie, 2019, Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis, Cell, 178, 714, 10.1016/j.cell.2019.06.029 · DOI
  25. Fisch, 2018, Identification of transcription factors responsible for dysregulated networks in human osteoarthritis cartilage by global gene expression analysis, Osteoarthr. Cartil., 26, 1531, 10.1016/j.joca.2018.07.012 · DOI
  26. Yang, 2020, Guidelines and definitions for research on epithelial–mesenchymal transition, Nat. Rev. Mol. Cell Biol., 21, 341, 10.1038/s41580-020-0237-9 · DOI · Paper page
  27. Malecova, 2018, Dynamics of cellular states of fibro-adipogenic progenitors during myogenesis and muscular dystrophy, Nat. Commun., 9, 10.1038/s41467-018-06068-6 · DOI
  28. Pardali, 2017, TGF-β-Induced Endothelial-Mesenchymal Transition in Fibrotic Diseases, Int. J. Mol. Sci., 18, 10.3390/ijms18102157 · DOI
  29. Brabletz, 2018, EMT in cancer, Nat. Rev. Cancer, 18, 128, 10.1038/nrc.2017.118 · DOI · Paper page
  30. Engelbrecht, 2022, The Vasculature in Pulmonary Fibrosis. Curr tissue microenviron, Rep 3. Curr. Tissue Microenviron. Rep., 3, 83, 10.1007/s43152-022-00040-9 · DOI
  31. Graupera, 2022, Molecular characterization of chronic liver disease dynamics: From liver fibrosis to acute-on-chronic liver failure, JHEP Rep., 4
  32. Dobie, 2019, Single-Cell Transcriptomics Uncovers Zonation of Function in the Mesenchyme during Liver Fibrosis, Cell Rep., 29, 1832, 10.1016/j.celrep.2019.10.024 · DOI · Paper page
  33. Honda, 2020, Elastography Techniques for the Assessment of Liver Fibrosis in Non-Alcoholic Fatty Liver Disease, Int. J. Mol. Sci., 21, 10.3390/ijms21114039 · DOI
  34. Flam, 2022, Integrated landscape of cardiac metabolism in end-stage human nonischemic dilated cardiomyopathy, Nat CardioVasc Res., 1, 817
  35. Lehallier, 2019, Undulating changes in human plasma proteome profiles across the lifespan, Nat. Med., 25, 1843, 10.1038/s41591-019-0673-2 · DOI · Paper page
  36. Monteiro, 2021, MIR503HG Loss Promotes Endothelial-to-Mesenchymal Transition in Vascular Disease, Circ. Res., 128, 1173, 10.1161/CIRCRESAHA.120.318124 · DOI
  37. Walker, 2019, Transcriptomic changes during TGF-β-mediated differentiation of airway fibroblasts to myofibroblasts, Sci. Rep., 9, 10.1038/s41598-019-56955-1 · DOI
  38. Gao, 2024, Knockdown of HSPA13 Inhibits TGFβ1-Induced Epithelial-Mesenchymal Transition of RPE by Suppressing the PI3K/Akt Signaling Pathway, Invest. Ophthalmol. Vis. Sci., 65, 1, 10.1167/iovs.65.11.1 · DOI
  39. Diez Benavente, 2024, Atherosclerotic Plaque Epigenetic Age Acceleration Predicts a Poor Prognosis and Is Associated With Endothelial-to-Mesenchymal Transition in Humans, Arterioscler. Thromb. Vasc. Biol., 44, 1419, 10.1161/ATVBAHA.123.320692 · DOI
  40. Deng, 2021, Single-cell RNA-seq reveals fibroblast heterogeneity and increased mesenchymal fibroblasts in human fibrotic skin diseases, Nat. Commun., 12, 10.1038/s41467-021-24110-y · DOI
  41. Andrews, 2016, Keloids: The paradigm of skin fibrosis - Pathomechanisms and treatment, Matrix Biol., 51, 37, 10.1016/j.matbio.2016.01.013 · DOI
  42. Radeke, 2015, Restoration of mesenchymal retinal pigmented epithelial cells by TGFβ pathway inhibitors: implications for age-related macular degeneration, Genome Med., 7, 10.1186/s13073-015-0183-x · DOI
  43. Huang, 2023, Protocadherin 20 maintains intestinal barrier function to protect against Crohn’s disease by targeting ATF6, Genome Biol., 24, 10.1186/s13059-023-02991-0 · DOI
  44. Prasse, 2019, BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis, Am. J. Respir. Crit. Care Med., 199, 622, 10.1164/rccm.201712-2551OC · DOI · Paper page
  45. Horvath, 2018, DNA methylation-based biomarkers and the epigenetic clock theory of ageing, Nat. Rev. Genet., 19, 371, 10.1038/s41576-018-0004-3 · DOI · Paper page
  46. Waryah, 2023, Synthetic Epigenetic Reprogramming of Mesenchymal to Epithelial States Using the CRISPR/dCas9 Platform in Triple Negative Breast Cancer, Adv. Sci. (Weinh), 10
  47. Horvath, 2013, DNA methylation age of human tissues and cell types, Genome Biol., 14, R115, 10.1186/gb-2013-14-10-r115 · DOI · Paper page
  48. Levine, 2018, An epigenetic biomarker of aging for lifespan and healthspan, Aging, 10, 573, 10.18632/aging.101414 · DOI · Paper page
  49. Kiourtis, 2024, Hepatocellular senescence induces multi-organ senescence and dysfunction via TGFβ, Nat. Cell Biol., 26, 2075, 10.1038/s41556-024-01543-3 · DOI
  50. Li, 2016, GDF15 promotes EMT and metastasis in colorectal cancer, Oncotarget, 7, 860, 10.18632/oncotarget.6205 · DOI
  51. Perez-Pinera, 2006, Pleiotrophin disrupts calcium-dependent homophilic cell-cell adhesion and initiates an epithelial-mesenchymal transition, Proc. Natl. Acad. Sci. USA, 103, 17795, 10.1073/pnas.0607299103 · DOI
  52. Huang, 2022, Cancer-Associated Fibroblasts Promote Tumor Aggressiveness in Head and Neck Cancer through Chemokine Ligand 11 and C-C Motif Chemokine Receptor 3 Signaling Circuit, Cancers (Basel), 14
  53. Nomura, 2014, β2-Microglobulin-mediated signaling as a target for cancer therapy, Anti-Cancer Agents Med. Chem., 14, 343, 10.2174/18715206113139990092 · DOI
  54. Goeminne, 2025, Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems, Cell Metab., 37, 205, 10.1016/j.cmet.2024.10.005 · DOI
  55. Buechler, 2021, Cross-tissue organization of the fibroblast lineage, Nature, 593, 575, 10.1038/s41586-021-03549-5 · DOI
  56. Malik, 2019, Pluripotency reprogramming by competent and incompetent POU factors uncovers temporal dependency for Oct4 and Sox2, Nat. Commun., 10, 10.1038/s41467-019-11054-7 · DOI · Paper page
  57. Weng, 2023, An engineered Sox17 induces somatic to neural stem cell fate transitions independently from pluripotency reprogramming, Sci. Adv., 9, 10.1126/sciadv.adh2501 · DOI
  58. Sahu, 2024, Targeted partial reprogramming of age-associated cell states improves markers of health in mouse models of aging, Sci. Transl. Med., 16, 10.1126/scitranslmed.adg1777 · DOI
  59. Kim, 2023, Partial in vivo reprogramming enables injury-free intestinal regeneration via autonomous Ptgs1 induction, Sci. Adv., 9, 10.1126/sciadv.adi8454 · DOI
  60. Chondronasiou, 2022, Deciphering the roadmap of in vivo reprogramming toward pluripotency, Stem Cell Rep., 17, 2501, 10.1016/j.stemcr.2022.09.009 · DOI · Paper page
  61. Trogisch, 2024, Endothelial cells drive organ fibrosis in mice by inducing expression of the transcription factor SOX9, Sci. Transl. Med., 16, 10.1126/scitranslmed.abq4581 · DOI
  62. Wang, 2017, Macrophage-to-Myofibroblast Transition Contributes to Interstitial Fibrosis in Chronic Renal Allograft Injury, J. Am. Soc. Nephrol., 28, 2053, 10.1681/ASN.2016050573 · DOI
  63. Haider, 2019, Transition of Macrophages to Fibroblast-Like Cells in Healing Myocardial Infarction, J. Am. Coll. Cardiol., 74, 3124, 10.1016/j.jacc.2019.10.036 · DOI
  64. Vicanolo, 2025, Matrix-producing neutrophils populate and shield the skin, Nature, 641, 740, 10.1038/s41586-025-08741-5 · DOI
  65. Jia, 2025, Macrophage-to-Myofibroblast Transition Contributes to Cutaneous Scarring Formation Through the TGF-β/Smad3 Signaling Pathways, Cell Biol. Int., 49, 494, 10.1002/cbin.70002 · DOI
  66. Gao, 2024, Cross-tissue human fibroblast atlas reveals myofibroblast subtypes with distinct roles in immune modulation, Cancer Cell, 42, 1764, 10.1016/j.ccell.2024.08.020 · DOI
  67. Kousa, 2024, Age-related epithelial defects limit thymic function and regeneration, Nat. Immunol., 25, 1593, 10.1038/s41590-024-01915-9 · DOI
  68. Youssef, 2024, Epithelial-mesenchymal transition in tissue repair and degeneration, Nat. Rev. Mol. Cell Biol., 25, 720, 10.1038/s41580-024-00733-z · DOI
  69. Aggarwal, 2024, SOX9 switch links regeneration to fibrosis at the single-cell level in mammalian kidneys, Science, 383, 10.1126/science.add6371 · DOI
  70. Fedintsev, 2020, Stochastic non-enzymatic modification of long-lived macromolecules - A missing hallmark of aging, Ageing Res. Rev., 62, 10.1016/j.arr.2020.101097 · DOI · Paper page
  71. Selman, 2021, Fibroageing: An ageing pathological feature driven by dysregulated extracellular matrix-cell mechanobiology, Ageing Res. Rev., 70, 10.1016/j.arr.2021.101393 · DOI · Paper page
  72. Rice, 2017, Matrix stiffness induces epithelial-mesenchymal transition and promotes chemoresistance in pancreatic cancer cells, Oncogenesis, 6, e352, 10.1038/oncsis.2017.54 · DOI
  73. Doeser, 2018, Reduction of Fibrosis and Scar Formation by Partial Reprogramming In Vivo, Stem Cells, 36, 1216, 10.1002/stem.2842 · DOI · Paper page
  74. de Lázaro, 2019, Non-viral, Tumor-free Induction of Transient Cell Reprogramming in Mouse Skeletal Muscle to Enhance Tissue Regeneration, Mol. Ther., 27, 59, 10.1016/j.ymthe.2018.10.014 · DOI
  75. Wang, 2024, Therapeutic potential of the secreted Kazal-type serine protease inhibitor SPINK4 in colitis, Nat. Commun., 15
  76. Chen, 2018, fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, 34, i884, 10.1093/bioinformatics/bty560 · DOI · Paper page
  77. Patro, 2017, Salmon provides fast and bias-aware quantification of transcript expression, Nat. Methods, 14, 417, 10.1038/nmeth.4197 · DOI · Paper page
  78. Heinz, 2010, Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities, Mol. Cell, 38, 576, 10.1016/j.molcel.2010.05.004 · DOI · Paper page
  79. Chen, 2025, edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets, Nucleic Acids Res., 53, 10.1093/nar/gkaf018 · DOI
  80. Love, 2014, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol., 15, 550, 10.1186/s13059-014-0550-8 · DOI · Paper page
  81. Hao, 2024, Dictionary learning for integrative, multimodal and scalable single-cell analysis, Nat. Biotechnol., 42, 293, 10.1038/s41587-023-01767-y · DOI · Paper page
  82. Choudhary, 2022, Comparison and evaluation of statistical error models for scRNA-seq, Genome Biol., 23, 27, 10.1186/s13059-021-02584-9 · DOI · Paper page
  83. Street, 2018, Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics, BMC Genomics, 19, 477, 10.1186/s12864-018-4772-0 · DOI · Paper page
  84. Ianevski, 2022, Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data, Nat. Commun., 13, 1246, 10.1038/s41467-022-28803-w · DOI
  85. Frankish, 2019, GENCODE reference annotation for the human and mouse genomes, Nucleic Acids Res., 47, D766, 10.1093/nar/gky955 · DOI
  86. Tarhan, 2023, Single Cell Portal: an interactive home for single-cell genomics data, bioRxiv
  87. Hao, 2021, Integrated analysis of multimodal single-cell data, Cell, 184, 3573, 10.1016/j.cell.2021.04.048 · DOI · Paper page
  88. Ewels, 2020, The nf-core framework for community-curated bioinformatics pipelines, Nat. Biotechnol., 38, 276, 10.1038/s41587-020-0439-x · DOI
  89. Dobin, 2013, STAR: ultrafast universal RNA-seq aligner, Bioinformatics, 29, 15, 10.1093/bioinformatics/bts635 · DOI · Paper page
  90. Kuleshov, 2016, Enrichr: a comprehensive gene set enrichment analysis web server 2016 update, Nucleic Acids Res., 44, W90, 10.1093/nar/gkw377 · DOI · Paper page

Cited by

Sorted by citations

Metadata

Authors
Lu, J. Y., Tu, W. B., Li, R., Weng, M., Sanketi, B. D., Yuan, B., Reddy, P., Rodriguez Esteban, C., & Izpisua Belmonte, J. C.
Venue
Cell
Publisher
Elsevier BV
Published
2025-10
Volume
188
Issue
21
Pages
5895-5911.e17
ISSN
0092-8674
Cited by
68
References
18
Language
en

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