Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

ROCK-dependent mechanotransduction of macroscale forces drives fibrosis in degenerative spinal disease

Abstract

Chronic repetitive forces on the spinal column promote the development of degenerative spinal disease. Yet the mechanisms linking such macroscale mechanical forces to tissue hypertrophy remain unknown. Here we show that fibrotic regions in human ligamentum flavum naturally exposed to high stress display elevated Rho-associated kinase (ROCK) signalling and an increased density of myofibroblasts expressing smooth muscle actin α. The myofibroblasts were localized in regions of elevated stiffness and microstress, such accumulation was ROCK dependent, and ROCK inhibition partially reduced the stress-driven transcriptional responses. Our findings support the further investigation of ROCK inhibitors for the treatment of degenerative spinal disease.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Spinal fusion exposes LF to opposite extremes of macroscale stress and strain.
Fig. 2: LF exposed to high levels of stress in vivo shows significantly increased hypertrophy, myofibroblasts and ROCK signalling.
Fig. 3: Myofibroblasts localize within LF to regions of higher stiffness and higher simulated stress.
Fig. 4: Mechanical force causes LF myofibroblast accumulation in a stress-dependent manner and increases ROCK signalling.
Fig. 5: ROCK inhibition but not TGFβR inhibition protects against strain-induced increases in SMAα cells.
Fig. 6: Mechanical stress on LF causes hyperacute transcriptional changes altered by ROCK inhibition.

Similar content being viewed by others

Data availability

The data supporting the results in this study are available within the paper and its Supplementary Information. De-identified patient data may be made available on request from the corresponding author, subject to approval from the Institutional Review Board of Massachusetts General Hospital. Source data for the figures are provided with this paper.

Code availability

Code used to implement finite-element models of lumbar spine/pelvis is available on request. Details of the implemented model have been previously published in ref. 45. The MATLAB code used to analyse the AFM data is also available on request. The code implemented standard statistical methods, as described in Methods, and the R code used to analyse gene expression is also available on request. The code implemented standard methods using open-source packages, as described in Methods.

References

  1. Kushchayev, S. V. et al. ABCs of the degenerative spine. Insights Imaging 9, 253–274 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Tschumperlin, D. J., Ligresti, G., Hilscher, M. B. & Shah, V. H. Mechanosensing and fibrosis. J. Clin. Invest. 128, 74–84 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Ravindra, V. M. et al. Degenerative lumbar spine disease: estimating global incidence and worldwide volume. Glob. Spine J. 8, 784–794 (2018).

    Article  Google Scholar 

  4. Austevoll, I. M. et al. Decompression with or without fusion in degenerative lumbar spondylolisthesis. N. Engl. J. Med. 385, 526–538 (2021).

    Article  PubMed  Google Scholar 

  5. Yoshiiwa, T. et al. Analysis of the relationship between ligamentum flavum thickening and lumbar segmental instability, disc degeneration, and facet joint osteoarthritis in lumbar spinal stenosis. Asian Spine J. 10, 1132–1140 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Kim, Y. U. et al. The role of the ligamentum flavum area as a morphological parameter of lumbar central spinal stenosis. Pain Physician 20, E419–E424 (2017).

    PubMed  Google Scholar 

  7. Benzel, E. C. & American Association of Neurological Surgeons. Biomechanics of Spine Stabilization (Thieme, 2001).

  8. Jang, S. Y. et al. Radiographic parameters of segmental instability in lumbar spine using kinetic MRI. J. Korean Neurosurg. Soc. 45, 24–31 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Lee, C. K. Accelerated degeneration of the segment adjacent to a lumbar fusion. Spine 13, 375–377 (1988).

    Article  CAS  PubMed  Google Scholar 

  10. Huang, Y. P. et al. Preserving posterior complex can prevent adjacent segment disease following posterior lumbar interbody fusion surgeries: a finite element analysis. PLoS ONE 11, e0166452 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hur, J. W. et al. Myofibroblast in the ligamentum flavum hypertrophic activity. Eur. Spine J. 26, 2021–2030 (2017).

    Article  PubMed  Google Scholar 

  12. Hayashi, F. et al. Myofibroblasts are increased in the dorsal layer of the hypertrophic ligamentum flavum in lumbar spinal canal stenosis. Spine J. 22, 697–704 (2022).

    Article  PubMed  Google Scholar 

  13. Kendall, R. T. & Feghali-Bostwick, C. A. Fibroblasts in fibrosis: novel roles and mediators. Front. Pharm. 5, 123 (2014).

    Article  Google Scholar 

  14. Lederer, D. J. & Martinez, F. J. Idiopathic pulmonary fibrosis. N. Engl. J. Med. 378, 1811–1823 (2018).

    Article  CAS  PubMed  Google Scholar 

  15. Plikus, M. V. et al. Fibroblasts: origins, definitions, and functions in health and disease. Cell 184, 3852–3872 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Zent, J. & Guo, L. W. Signaling mechanisms of myofibroblastic activation: outside-in and inside-out. Cell. Physiol. Biochem. 49, 848–868 (2018).

    Article  CAS  PubMed  Google Scholar 

  17. Gibb, A. A., Lazaropoulos, M. P. & Elrod, J. W. Myofibroblasts and fibrosis: mitochondrial and metabolic control of cellular differentiation. Circ. Res. 127, 427–447 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Klingberg, F., Hinz, B. & White, E. S. The myofibroblast matrix: implications for tissue repair and fibrosis. J. Pathol. 229, 298–309 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Frangogiannis, N. Transforming growth factor-β in tissue fibrosis. J. Exp. Med. 217, e20190103 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Shi, J. et al. Distinct roles for ROCK1 and ROCK2 in the regulation of cell detachment. Cell Death Dis. 4, e483 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Knipe, R. S., Tager, A. M. & Liao, J. K. The Rho kinases: critical mediators of multiple profibrotic processes and rational targets for new therapies for pulmonary fibrosis. Pharm. Rev. 67, 103–117 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Rieder, F. ROCKing the field of intestinal fibrosis or between a ROCK and a hard place? Gastroenterology 153, 895–897 (2017).

    Article  PubMed  Google Scholar 

  23. Gomes, R. N., Manuel, F. & Nascimento, D. S. The bright side of fibroblasts: molecular signature and regenerative cues in major organs. npj Regen. Med. 6, 43 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Martinez-Vidal, L. et al. Causal contributors to tissue stiffness and clinical relevance in urology. Commun. Biol. 4, 1011 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Nia, H. T. et al. Solid stress and elastic energy as measures of tumour mechanopathology. Nat. Biomed. Eng. 1, 0004 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Hilibrand, A. S. & Robbins, M. Adjacent segment degeneration and adjacent segment disease: the consequences of spinal fusion? Spine J. 4, 190s–194s (2004).

    Article  PubMed  Google Scholar 

  27. Park, P., Garton, H. J., Gala, V. C., Hoff, J. T. & McGillicuddy, J. E. Adjacent segment disease after lumbar or lumbosacral fusion: review of the literature. Spine 29, 1938–1944 (2004).

    Article  PubMed  Google Scholar 

  28. Sun, C., Zhang, H., Wang, X. & Liu, X. Ligamentum flavum fibrosis and hypertrophy: molecular pathways, cellular mechanisms, and future directions. FASEB J. 34, 9854–9868 (2020).

    Article  CAS  PubMed  Google Scholar 

  29. Malakoutian, M. et al. Do in vivo kinematic studies provide insight into adjacent segment degeneration? A qualitative systematic literature review. Eur. Spine J. 24, 1865–1881 (2015).

    Article  PubMed  Google Scholar 

  30. McMains, M. C. et al. A biomechanical analysis of lateral interbody construct and supplemental fixation in adjacent-segment disease of the lumbar spine. World Neurosurg. 128, e694–e699 (2019).

    Article  PubMed  Google Scholar 

  31. Lindsey, D. P., Kiapour, A., Yerby, S. A. & Goel, V. K. Sacroiliac joint fusion minimally affects adjacent lumbar segment motion: a finite element study. Int. J. Spine Surg. 9, 64 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Srinivas, G. R., Kumar, M. N. & Deb, A. Adjacent disc stress following floating lumbar spine fusion: a finite element study. Asian Spine J. 11, 538–547 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Ohtori, S. et al. Change of lumbar ligamentum flavum after indirect decompression using anterior lumbar interbody fusion. Asian Spine J. 11, 105–112 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Limthongkul, W. et al. Indirect decompression effect to central canal and ligamentum flavum after extreme lateral lumbar interbody fusion and oblique lumbar interbody fusion. Spine 45, E1077–e1084 (2020).

    Article  PubMed  Google Scholar 

  35. Wang, T. et al. Cyclic mechanical stimulation rescues Achilles tendon from degeneration in a bioreactor system. J. Orthop. Res. 33, 1888–1896 (2015).

    Article  CAS  PubMed  Google Scholar 

  36. Hayashi, K. et al. Fibroblast growth factor 9 is upregulated upon intervertebral mechanical stress-induced ligamentum flavum hypertrophy in a rabbit model. Spine 44, E1172–E1180 (2019).

    Article  PubMed  Google Scholar 

  37. Hayashi, K. et al. Mechanical stress induces elastic fibre disruption and cartilage matrix increase in ligamentum flavum. Sci. Rep. 7, 13092 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Joannes, A. et al. FGF9 and FGF18 in idiopathic pulmonary fibrosis promote survival and migration and inhibit myofibroblast differentiation of human lung fibroblasts in vitro. Am. J. Physiol. Lung Cell. Mol. Physiol. 310, L615–L629 (2016).

    Article  PubMed  Google Scholar 

  39. Mead, T. J. ADAMTS6: emerging roles in cardiovascular, musculoskeletal and cancer biology. Front. Mol. Biosci. 9, 1023511 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hou, J. et al. TNF-α-induced NF-κB activation promotes myofibroblast differentiation of LR-MSCs and exacerbates bleomycin-induced pulmonary fibrosis. J. Cell. Physiol. 233, 2409–2419 (2018).

    Article  CAS  PubMed  Google Scholar 

  41. Weiss, J. A., Gardiner, J. C. & Bonifasi-Lista, C. Ligament material behavior is nonlinear, viscoelastic and rate-independent under shear loading. J. Biomech. 35, 943–950 (2002).

    Article  PubMed  Google Scholar 

  42. Komeili, A., Rasoulian, A., Moghaddam, F., El-Rich, M. & Li, L. P. The importance of intervertebral disc material model on the prediction of mechanical function of the cervical spine. BMC Musculoskelet. Disord. 22, 324 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kiapour, A. et al. Biomechanical analysis of stand-alone lumbar interbody cages versus 360° constructs: an in vitro and finite element investigation. J. Neurosurg. Spine 36, 928–936 (2021).

    Article  PubMed  Google Scholar 

  44. Joukar, A. et al. Biomechanics of the sacroiliac joint: surgical treatments. Int. J. Spine Surg. 14, 355–367 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Kiapour, A. et al. Biomechanical analysis of stand-alone lumbar interbody cages versus 360° constructs: an in vitro and finite element investigation. J. Neurosurg. Spine 36, 928–936 (2022).

    Article  PubMed  Google Scholar 

  46. Mihara, A. et al. Tensile test of human lumbar ligamentum flavum: age-related changes of stiffness. Appl. Sci. 11, 3337 (2021).

  47. Kirby, M. C., Sikoryn, T. A., Hukins, D. W. & Aspden, R. M. Structure and mechanical properties of the longitudinal ligaments and ligamentum flavum of the spine. J. Biomed. Eng. 11, 192–196 (1989).

    Article  CAS  PubMed  Google Scholar 

  48. Patwardhan, A. G., Havey, R. M., Meade, K. P., Lee, B. & Dunlap, B. A follower load increases the load-carrying capacity of the lumbar spine in compression. Spine 24, 1003–1009 (1999).

    Article  CAS  PubMed  Google Scholar 

  49. Remus, R., Selkmann, S., Lipphaus, A., Neumann, M. & Bender, B. Muscle-driven forward dynamic active hybrid model of the lumbosacral spine: combined FEM and multibody simulation. Front. Bioeng. Biotechnol. 11, 1223007 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Article  CAS  PubMed  Google Scholar 

  51. Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).

    Article  CAS  PubMed  Google Scholar 

  52. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Dimitriadis, E. K., Horkay, F., Maresca, J., Kachar, B. & Chadwick, R. S. Determination of elastic moduli of thin layers of soft material using the atomic force microscope. Biophys. J. 82, 2798–2810 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We acknowledge the master craftsmanship of J. (R.) McConnell and the MGH Biomedical Engineering Model Shop for assistance in fabrication of the loading device used in this study. All images were created by authors of this manuscript. We thank D. Glazer for critical review of the manuscript. North America Spine Society (NASS) Basic Science Research Grant provided funding for the study. M.H. received salary support from an NIH R25 Research Grant.

Author information

Authors and Affiliations

Authors

Contributions

G.M.S., M.H., M.S.S. and J.H.S. conceptualized the project. M.S.S., M.H., L.R. and B.D.C. performed wet lab investigation. G.P.N., J.-V.C.C., J.H.S., G.M.S., M.S.S. and M.H. performed patient sample collection. E.M. conducted RNA-seq analysis. A.K. performed finite-element modelling. G.N. and M.A.S. conducted clinical data collection. J.B., I.D.C., E.E., R.B., S.S. and B.D.C. provided technical support. G.M.S., M.H. and M.S.S. acquired funding. G.M.S., A.J.G., H.T.N., L.F.B., J.H.S. and B.D.C. supervised the project. M.S.S. and M.H. analysed data. M.S.S. and M.H. wrote the original manuscript draft. G.M.S., A.J.G., H.T.N. and L.F.B. reviewed and edited the manuscript.

Corresponding author

Correspondence to Ganesh M. Shankar.

Ethics declarations

Competing interests

A provisional patent application related to this work (63/322,621; G.M.S. and M.H.) was filed on 22 March 2022. The other authors declare no competing interests.

Peer review

Peer review information

Nature Biomedical Engineering thanks Mazda Farshad, Chiseung Lee, Christopher McCulloch and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Patterns of motion and stress on LF remain consistent across multiple FEMs derived from three additional patients (one female and two male) when compared to the previously analyzed model.

a, Hybrid loading ranging from 0 to 30 degrees of flexion from L1 to the sacrum was applied to all four models. Resulting L3/4 segmental motion and b, L3/4 LF stress were quantified and compared. c, Representative error (in standard deviation) of L3/4 segmental motion was calculated and plotted. d, Representative error (in standard deviation) of L3/4 LF stress was calculated and plotted. e, Data from the four models derived from the four different patients was combined on singular plots to demonstrate the precision of the calculations of L3/4 segmental motion and of f, L3/4 LF stress despite the varying geometries.

Source data

Extended Data Fig. 2 Ligamentum flavum (LF) measurement on MRI.

On a patient’s T2 weighted spine MRI, the desired vertebral level was identified on the sagittal scan (A) and used to identify the ligamentum flavum at the desired level on the axial scan (B). The axial slice of the MRI with the thickest section of the ligamentum flavum was identified. Using Visage, the ligamentum flavum was circled (B, yellow outline), the area was calculated and recorded, and a screenshot was saved for future reference.

Source data

Extended Data Fig. 3 Globally, there is progressive, stepwise loss of elastin from non-DSD to DSD to ASD and locally, thorough examination of tissue reveals small regions of torn elastin and loosened elastin present in all clinical conditions.

A, LF from non-DSD, DSD, and ASD patients was stained for elastin by EVG. B, Percent elastin was quantified by using a standard color thresholding protocol for all images; elastin was significantly reduced from non-DSD (n = 3) levels in both DSD (n = 3, p = 0.020) and ASD (n = 3, p = 0.008) conditions. C, Representative images (elastin stain, top; schematic, bottom) demonstrating normal matrix (i), elastin tears (ii), and loosened matrix (iii), which were seen across non-DSD, DSD, and ASD conditions. Quantitative data are shown as mean ± sem, all tests are two-sided, unpaired t-tests.

Source data

Extended Data Fig. 4 By trichrome staining, ratio of blue to red increases stepwise from non-DSD to DSD to ASD.

A, Representative images of LF from non-DSD, DSD, and ASD patients stained with trichrome staining. B, Representative images of the color thresholding protocol for quantification. Percent blue and red was quantified using a standard color thresholding protocol for all images; red pixels matching a set range of values were selected (top, selected pixels highlighted red). The remainder of pixels were considered blue and the images were converted to binary images for quantification (bottom, white=red and black=blue). C, The ratio of blue to red significantly increases from non-DSD (n = 2) to DSD (n = 3, p = 0.022) and increases again from DSD to ASD (n = 3). Quantitative data are shown as mean ± sem, all tests are two-sided, unpaired t-tests.

Source data

Extended Data Fig. 5 CD45 cells decrease stepwise from non-DSD to DSD to ASD.

A, Representative images of immunohistochemistry stains for CD45 (brown) with nuclear counterstain (purple) in non-DSD, DSD, and ASD LF. B, Qualitative schematic demonstrating the observation that CD45 cells, when present, seemed to cluster together in regions of abnormal ECM. C, The most CD45 cells were seen in non-DSD samples (n = 3), fewer were seen in DSD samples (n = 3), and significantly fewest were seen in ASD samples (n = 3, p = 0.0254 from non-DSD, p = 0.0196 from DSD). Quantitative data are shown as mean ± sem, all tests are two-sided, unpaired t-tests.

Source data

Extended Data Fig. 6 qPCR and western blots of LF samples by disease group.

A, while overall qPCR analysis of LF from non-DSD, DSD, and ASD patients was highly variable, Fibronectin increased stepwise between non-DSD, DSD, and ASD groups. CYP also significantly decreased from non-DSD levels. B, As quantified by western blots on LF samples, similar levels of latent TGFβ were present in all disease groups but the amount of released, active TGFβ was highest in non-DSD samples and lowest in ASD samples. Quantitative data are shown as mean ± sem.

Source data

Extended Data Fig. 7 Effects of TGFβRI inhibitors, Rho/ROCK inhibitors, and stretch on primary LF cells.

A, Incubation with TGFβ markedly increases SMAD2 nuclear localization, but this effect is abolished by adding the TGFβ inhibitor SB431542 (n = 4). B, in primary LF cells growing on collagen coated FlexCell plates without stretch, incubation for 7 hours with Ripasudil reduced the number of cells with assembled SMAα stress actin fibers. The number of cells positive for SMAα increased after 6 hours of stretch, but this effect was protected against by Ripasudil (n = 3). Quantitative data are shown as mean ± sem.

Source data

Extended Data Fig. 8 FEM functions as both a descriptive and predictive tool: Values of LF stress calculated using FEM for clinical conditions associated with higher SMAα cell densities predicted optimal stresses at which to apply cyclic strain to LF fascicles in the bioreactor to increase SMAα cells.

A, The range of LF degrees of hypertrophy seen among all patients, as measured by LF area on axial cross section on MRI. B, FEMs with predicted stress at maximum spine flexion: 50 kPa when fused across the LF, 206 kPa with no fusion, 271 kPa when fused a vertebral level below the LF. C, LF areas plotted in (A), color-coded in accordance with FEM-predicted force experienced by the measured LF. D, Fold increase in SMAα cells compared to paired, unpulled fascicles (n = 24 pairs), binned by stress in kPa. Below, FEM models are aligned by maximum stress experienced by LF at maximum spine flexion.

Source data

Extended Data Fig. 9 Progressively increased doses of rock inhibitors causes progressingly increased cytoskeletal actin disassembly in LF primary cells; at low concentrations, ripasudil rock inhibition uncouples the LF cell’s sensing and alignment in the direction of experienced stretch and results in fewer SMAα cells in conditions with and without 2-dimensional stretch.

A, LF primary cells treated with increasing doses of rock inhibitors stained for actin (top) or SMAα (bottom). Insets contain schematics emphasizing morphology observed with each level of treatment: full-length fibers in untreated cells (i,iv) dissolve into fragments (ii), then into sparse granules on the periphery of the cell cytoplasm (iii,v). B, LF primary cells were assigned conditions of ‘no stretch’ or ‘stretch’ and then treated with vehicle control or ripasudil. After stretch regimen, cells were stained for actin and SMAα (i-iv; insets contain representative schematics of the actin fibers directions of cells) and the percentage of SMAα cells was quantified (v). Percent SMAα cells increased with stretch, and decreased with ripasudil treatment, in both stretched and unstretched conditions. C, Immunofluorescence staining for SMAα and DAPI in paired, unstretched and stretched LF fascicles, with quantification of n = 12 triply paired fascicles. Images and graph in c have been reproduced from main manuscript Figs. 4g and 5f, respectively, for efficient comparison to results in b,i-v. Quantitative data are shown as mean ± sem.

Source data

Extended Data Fig. 10 LF fascicle Young’s modulus significantly decreases after 24 hour incubation with Ripasudil, and decreases significantly more than when incubated with DMSO.

A, Timeline describing experimental protocol for LF collection from the operating room through beginning incubation with DMSO or ripasudil, referred to in graphs as ‘0 h’, and competition of the incubation period, referred to in graphs as ‘24 h’. B,C, Schematics demonstrating the hypothesized components resisting tension and thus contributing to LF fascicle bulk modulus - ECM fibers and cellular cytoskeletal tension, the latter of which would be disrupted with Ripasudil treatment. D, In 6 sets of quadruply-paired fascicles from 5 patients, the Young’s modulus of fascicles treated with Ripasudil decreased significantly (p = 0.0012) while the Young’s modulus of fascicles treated with DMSO decreased non-significantly (p = 0.0523). E, Fascicles treated with Ripasudil had a significantly greater negative change in modulus (YMend - YMstart) than fascicles treated with DMSO (p = 0.0467). Tests are paired, one-tailed t-tests.

Source data

Supplementary information

Supplementary Information

Supplementary figures and tables.

Reporting Summary

Peer Review File

Data

Source data for the supplementary figures.

Data

Uncropped western blots for Supplementary Fig. 4.

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hadzipasic, M., Sten, M.S., Massaad, E. et al. ROCK-dependent mechanotransduction of macroscale forces drives fibrosis in degenerative spinal disease. Nat. Biomed. Eng (2025). https://doi.org/10.1038/s41551-025-01396-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41551-025-01396-7

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer