Tissue and extracellular matrix remodeling of the subchondral bone during osteoarthritis of knee joints as revealed by spatial mass spectrometry imaging

Abstract

Osteoarthritis (OA) is a degenerative skeletal condition marked by the loss of articular cartilage and changes to subchondral bone homeostasis. Treatments for OA beyond full joint replacement are lacking primarily due to gaps in molecular knowledge of the biological drivers of disease. Mass Spectrometry Imaging (MSI) enables molecular spatial mapping of the proteomic landscape of tissues. Histologic sections of human tibial plateaus from knees of human OA patients and cadaveric controls were treated with collagenase III to target extracellular matrix (ECM) proteins prior to MS Imaging of bone and cartilage proteins. Spatial MS imaging of the knee identified distinct areas of joint damage to the subchondral bone underneath areas of lost cartilage. This damaged bone signature extended underneath remaining cartilage in OA joints, indicating subchondral bone remodeling could occur before full thickness cartilage loss in OA. Specific ECM peptide markers from OA-affected medial tibial plateaus were compared to their healthier lateral halves from the same patient, as well as to healthy, age-matched cadaveric knees. Overall, 31 peptide candidates from ECM proteins, including Collagen alpha-1(I), Collagen alpha-1(III), and surprisingly, Collagen alpha-1(VI) and Collagen alpha-3(VI), exhibited significantly elevated abundance in diseased tissues. Additionally, highly specific hydroxyproline-containing collagen peptides, mainly from collagen type I, dominated OA subchondral bone directly under regions of lost cartilage but not areas where cartilage remained intact. A separate analysis of synovial fluid from a second cohort of OA patients found similar regulation of collagens and ECM proteins via LC-MS/MS demonstrating that markers of subchondral bone remodeling discovered by MALDI-MS may be detectable as biomarkers in biofluid samples. The identification of specific protein markers for subchondral bone remodeling in OA advances our molecular understanding of disease progression in OA and provides potential new biomarkers for OA detection and disease grading.

References

[1] Fuchs J, Kuhnert R, Scheidt-Nave C. 12-month prevalence of osteoarthritis in Germany. J. Health Monit., 2017, 2: 51-56

[2] Resende VACet al.. Higher age, female gender, osteoarthritis and blood transfusion protect against periprosthetic joint infection in total hip or knee arthroplasties: a systematic review and meta-analysis. Knee Surg. Sports Traumatol. Arthrosc., 2021, 29: 8-43

[3] Schurman CAet al.. Molecular and cellular crosstalk between bone and brain: accessing bidirectional neural and musculoskeletal signaling during aging and disease. J. Bone Metab., 2023, 30: 1-29

[4] Heidari B. Knee osteoarthritis prevalence, risk factors, pathogenesis and features: Part I. Casp. J. Intern. Med., 2011, 2: 205-212

[5] Burr DB, Gallant MA. Bone remodelling in osteoarthritis. Nat. Rev. Rheumatol., 2012, 8: 665-673

[6] Goldring SR, Goldring MB. Changes in the osteochondral unit during osteoarthritis: structure, function and cartilage-bone crosstalk. Nat. Rev. Rheumatol., 2016, 12: 632-644

[7] Mazur CMet al.. Osteocyte dysfunction promotes osteoarthritis through MMP13-dependent suppression of subchondral bone homeostasis. Bone Res., 2019, 7: 34

[8] Hu Y, Chen X, Wang S, Jing Y, Su J. Subchondral bone microenvironment in osteoarthritis and pain. Bone Res., 2021, 9: 20

[9] Alliston T, Hernandez CJ, Findlay DM, Felson DT, Kennedy OD. Bone marrow lesions in osteoarthritis: What lies beneath. J. Orthop. Res., 2018, 36: 1818-1825

[10] Namiri NKet al.. Deep learning for large scale MRI-based morphological phenotyping of osteoarthritis. Sci. Rep., 2021, 11 10915

[11] Hayami Tet al.. The role of subchondral bone remodeling in osteoarthritis: reduction of cartilage degeneration and prevention of osteophyte formation by alendronate in the rat anterior cruciate ligament transection model. Arthritis Rheum., 2004, 50: 1193-1206

[12] Cabral WAet al.. Prolyl 3-hydroxylase 1 deficiency causes a recessive metabolic bone disorder resembling lethal/severe osteogenesis imperfecta. Nat. Genet., 2007, 39: 359-365

[13] Saito M, Marumo K. Effects of collagen crosslinking on bone material properties in health and disease. Calcif. Tissue Int., 2015, 97: 242-261

[14] Acevedo Cet al.. Contributions of material properties and structure to increased bone fragility for a given bone mass in the UCD-T2DM rat model of type 2 diabetes. J. Bone Miner. Res., 2018, 33: 1066-1075

[15] Schurman CAet al.. Aging impairs the osteocytic regulation of collagen integrity and bone quality. Bone Res., 2024, 12: 13

[16] Franck Jet al.. MALDI imaging mass spectrometry: state of the art technology in clinical proteomics. Mol. Cell Proteom., 2009, 8: 2023-2033

[17] Walch A, Rauser S, Deininger SO, Hofler H. MALDI imaging mass spectrometry for direct tissue analysis: a new frontier for molecular histology. Histochem Cell Biol., 2008, 130: 421-434

[18] Michno W, Wehrli PM, Blennow K, Zetterberg H, Hanrieder J. Molecular imaging mass spectrometry for probing protein dynamics in neurodegenerative disease pathology. J. Neurochem, 2019, 151: 488-506

[19] Hanrieder, J., Ljungdahl, A. & Andersson, M. MALDI imaging mass spectrometry of neuropeptides in Parkinson’s disease. J. Vis. Exp. (2012).

[20] Angel PMet al.. Extracellular matrix imaging of breast tissue pathologies by MALDI-imaging mass spectrometry. Proteom. Clin. Appl., 2019, 13 e1700152

[21] Angel PMet al.. Zonal regulation of collagen-type proteins and posttranslational modifications in prostatic benign and cancer tissues by imaging mass spectrometry. Prostate, 2020, 80: 1071-1086

[22] Heijs Bet al.. Molecular signatures of tumor progression in myxoid liposarcoma identified by N-glycan mass spectrometry imaging. Lab Invest., 2020, 100: 1252-1261

[23] Angel PM, Mehta A, Norris-Caneda K, Drake RR. MALDI imaging mass spectrometry of N-glycans and tryptic peptides from the same formalin-fixed, paraffin-embedded tissue section. Methods Mol. Biol., 2018, 1788: 225-241

[24] Tuck M, Grelard F, Blanc L, Desbenoit N. MALDI-MSI towards multimodal imaging: challenges and perspectives. Front. Chem., 2022, 10: 904688

[25] Ogrinc Net al.. Robot-assisted SpiderMass for in vivo real-time topography mass spectrometry imaging. Anal. Chem., 2021, 93: 14383-14391

[26] Eveque-Mourroux MR, Rocha B, Barre FPY, Heeren RMA, Cillero-Pastor B. Spatially resolved proteomics in osteoarthritis: State of the art and new perspectives. J. Proteom., 2020, 215: 103637

[27] Aichler M, Walch A. MALDI imaging mass spectrometry: current frontiers and perspectives in pathology research and practice. Lab Invest., 2015, 95: 422-431

[28] Kriegsmann Met al.. MALDI MS imaging as a powerful tool for investigating synovial tissue. Scand. J. Rheumatol., 2012, 41: 305-309

[29] Cillero-Pastor B, Eijkel GB, Blanco FJ, Heeren RMA. Protein classification and distribution in osteoarthritic human synovial tissue by matrix-assisted laser desorption ionization mass spectrometry imaging. Anal. Bioanal. Chem., 2015, 407: 2213-2222

[30] Lee, Y. R. et al. Mass spectrometry imaging as a potential tool to investigate human osteoarthritis at the tissue level. Int. J. Mol. Sci.21, 6414 (2020).

[31] Rocha Bet al.. Identification of a distinct lipidomic profile in the osteoarthritic synovial membrane by mass spectrometry imaging. Osteoarthr. Cartil., 2021, 29: 750-761

[32] Eveque-Mourroux MRet al.. Spatially resolved endogenous improved metabolite detection in human osteoarthritis cartilage by matrix assisted laser desorption ionization mass spectrometry imaging. Analyst, 2019, 144: 5953-5958

[33] Haartmans MJJet al.. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) reveals potential lipid markers between infrapatellar fat pad biopsies of osteoarthritis and cartilage defect patients. Anal. Bioanal. Chem., 2023, 415: 5997-6007

[34] Schaepe Ket al.. Imaging of lipids in native human bone sections using tof-secondary ion mass spectrometry, atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization orbitrap mass spectrometry, and orbitrap-secondary ion mass spectrometry. Anal. Chem., 2018, 90: 8856-8864

[35] Seeley EHet al.. Co-registration of multi-modality imaging allows for comprehensive analysis of tumor-induced bone disease. Bone, 2014, 61: 208-216

[36] Fujino Y, Minamizaki T, Yoshioka H, Okada M, Yoshiko Y. Imaging and mapping of mouse bone using MALDI-imaging mass spectrometry. Bone Rep., 2016, 5: 280-285

[37] Svirkova A, Turyanskaya A, Perneczky L, Streli C, Marchetti-Deschmann M. Multimodal imaging of undecalcified tissue sections by MALDI MS and muXRF. Analyst, 2018, 143: 2587-2595

[38] Vandenbosch Met al.. Sample preparation of bone tissue for MALDI-MSI for forensic and (pre)clinical applications. Anal. Bioanal. Chem., 2021, 413: 2683-2694

[39] Lee YRet al.. High-resolution N-Glycan MALDI mass spectrometry imaging of subchondral bone tissue microarrays in patients with knee osteoarthritis. Anal. Chem., 2023, 95: 12640-12647

[40] Briggs MTet al.. MALDI mass spectrometry imaging of N-glycans on tibial cartilage and subchondral bone proteins in knee osteoarthritis. Proteomics, 2016, 16: 1736-1741

[41] Cillero-Pastor B, Eijkel GB, Kiss A, Blanco FJ, Heeren RM. Matrix-assisted laser desorption ionization-imaging mass spectrometry: a new methodology to study human osteoarthritic cartilage. Arthritis Rheum., 2013, 65: 710-720

[42] Rocha B, Cillero-Pastor B, Blanco FJ, Ruiz-Romero C. MALDI mass spectrometry imaging in rheumatic diseases. Biochim. Biophys. Acta Proteins Proteom., 2017, 1865: 784-794

[43] Angel PMet al.. Extracellular matrix alterations in low-grade lung adenocarcinoma compared with normal lung tissue by imaging mass spectrometry. J. Mass Spectrom., 2020, 55 e4450

[44] Clift CLet al.. Evaluation of therapeutic collagen-based biomaterials in the infarcted mouse heart by extracellular matrix targeted MALDI imaging mass spectrometry. J. Am. Soc. Mass Spectrom., 2021, 32: 2746-2754

[45] Schurman, C. A. et al. Multiplexed targeted spatial mass spectrometry imaging assays to monitor lipids and NAD+ metabolites in CD38 knockout mice exhibiting improved metabolism. bioRxivhttps://doi.org/10.1101/2025.05.25.655991 (2025).

[46] Clift CL, Drake RR, Mehta A, Angel PM. Multiplexed imaging mass spectrometry of the extracellular matrix using serial enzyme digests from formalin-fixed paraffin-embedded tissue sections. Anal. Bioanal. Chem., 2021, 413: 2709-2719

[47] Clift CL, Mehta A, Drake RR, Angel PM. Multiplexed imaging mass spectrometry of histological staining, N-Glycan and extracellular matrix from one tissue section: a tool for fibrosis research. Methods Mol. Biol., 2021, 2350: 313-329

[48] Angel PMet al.. Advances in MALDI imaging mass spectrometry of proteins in cardiac tissue, including the heart valve. Biochim. Biophys. Acta Proteins Proteom., 2017, 1865: 927-935

[49] Oegema TRJr, Carpenter RJ, Hofmeister F, Thompson RCJr. The interaction of the zone of calcified cartilage and subchondral bone in osteoarthritis. Microsc. Res. Tech., 1997, 37: 324-332

[50] Sandhu A, Rockel JS, Lively S, Kapoor M. Emerging molecular biomarkers in osteoarthritis pathology. Ther. Adv. Musculoskelet. Dis., 2023, 15: 1759720X231177116

[51] Cook NR. Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. Clin. Chem., 2008, 54: 17-23

[52] Hoo ZH, Candlish J, Teare D. What is an ROC curve?. Emerg. Med. J., 2017, 34: 357-359

[53] Greene MA, Loeser RF. Aging-related inflammation in osteoarthritis. Osteoarthr. Cartil., 2015, 23: 1966-1971

[54] Angelini Fet al.. Osteoarthritis endotype discovery via clustering of biochemical marker data. Ann. Rheum. Dis., 2022, 81: 666-675

[55] Li Y, Wei X, Zhou J, Wei L. The age-related changes in cartilage and osteoarthritis. Biomed. Res. Int., 2013, 2013: 916530

[56] Werdyani Set al.. Endotypes of primary osteoarthritis identified by plasma metabolomics analysis. Rheumatol. (Oxf.), 2021, 60: 2735-2744

[57] Kühn, K. in Structure and Function of Collagen Types (eds Richard Mayne & Robert E. Burgeson) 1-42 (Academic Press, 1987).

[58] Krane SM. The importance of proline residues in the structure, stability and susceptibility to proteolytic degradation of collagens. Amino Acids, 2008, 35: 703-710

[59] Slattery C, Kweon CY. Classifications in Brief: outerbridge classification of chondral lesions. Clin. Orthop. Relat. Res., 2018, 476: 2101-2104

[60] Bailey KNet al.. Mechanosensitive control of articular cartilage and subchondral bone homeostasis in mice requires osteocytic transforming growth factor beta signaling. Arthritis Rheumatol., 2021, 73: 414-425

[61] Hu, Q. & Ecker, M. Overview of MMP-13 as a promising target for the treatment of osteoarthritis. Int. J. Mol. Sci.22, 1742 (2021).

[62] Bellis SL. Advantages of RGD peptides for directing cell association with biomaterials. Biomaterials, 2011, 32: 4205-4210

[63] Sweeney SMet al.. Candidate cell and matrix interaction domains on the collagen fibril, the predominant protein of vertebrates. J. Biol. Chem., 2008, 283: 21187-21197

[64] San Antonio, J. D., Jacenko, O., Fertala, A. & Orgel, J. Collagen Structure-Function Mapping Informs Applications for Regenerative Medicine. Bioengineering (Basel)8, 3 (2020).

[65] Bachmann MF, Oxenius A. Interleukin 2: from immunostimulation to immunoregulation and back again. EMBO Rep., 2007, 8: 1142-1148

[66] Sondag, C. M. & Combs, C. K. Adhesion of monocytes to type I collagen stimulates an APP-dependent proinflammatory signaling response and release of Aβ1-40. J. Neuroinflamm.7, 22 (2010).

[67] George A, Hao J. Role of phosphophoryn in dentin mineralization. Cells Tissues Organs, 2005, 181: 232-240

[68] Rappu P, Salo AM, Myllyharju J, Heino J. Role of prolyl hydroxylation in the molecular interactions of collagens. Essays Biochem., 2019, 63: 325-335

[69] Garnero P. The contribution of collagen crosslinks to bone strength. Bonekey Rep., 2012, 1: 182

[70] Grzesik WJet al.. Age-related changes in human bone proteoglycan structure. Impact of osteogenesis imperfecta. J. Biol. Chem., 2002, 277: 43638-43647

[71] Chang SHet al.. Excessive mechanical loading promotes osteoarthritis through the gremlin-1-NF-kappaB pathway. Nat. Commun., 2019, 10 1442

[72] Hosseininia Set al.. Evidence for enhanced collagen type III deposition focally in the territorial matrix of osteoarthritic hip articular cartilage. Osteoarthr. Cartil., 2016, 24: 1029-1035

[73] Volk SWet al.. Type III collagen regulates osteoblastogenesis and the quantity of trabecular bone. Calcif. Tissue Int., 2014, 94: 621-631

[74] Chiba K, Ito M, Osaki M, Uetani M, Shindo H. In vivo structural analysis of subchondral trabecular bone in osteoarthritis of the hip using multi-detector row CT. Osteoarthr. Cartil., 2011, 19: 180-185

[75] Di Martino, A. et al. Collagen VI in the musculoskeletal system. Int. J. Mol. Sci.24, 5095 (2023).

[76] Keene DR, Sakai LY, Burgeson RE. Human bone contains type III collagen, type VI collagen, and fibrillin: type III collagen is present on specific fibers that may mediate attachment of tendons, ligaments, and periosteum to calcified bone cortex. J. Histochem. Cytochem, 1991, 39: 59-69

[77] Williams L, Layton T, Yang N, Feldmann M, Nanchahal J. Collagen VI as a driver and disease biomarker in human fibrosis. FEBS J., 2022, 289: 3603-3629

[78] Komori, T. et al. Type VI Collagen regulates endochondral ossification in the temporomandibular Joint. JBMR Plus6, e10617 (2022).

[79] Quarto R, Dozin B, Bonaldo P, Cancedda R, Colombatti A. Type VI collagen expression is upregulated in the early events of chondrocyte differentiation. Development, 1993, 117: 245-251

[80] Zelenski NAet al.. Type VI collagen regulates pericellular matrix properties, chondrocyte swelling, and mechanotransduction in mouse articular cartilage. Arthritis Rheumatol., 2015, 67: 1286-1294

[81] Pullig O, Weseloh G, Swoboda B. Expression of type VI collagen in normal and osteoarthritic human cartilage. Osteoarthr. Cartil., 1999, 7: 191-202

[82] Williams SN, W M., Bercovitz A. Hospitalization for total knee replacement among inpatients aged 45 and over: United States, 2000–2010. (2015)

[83] Rujchanarong, D. et al. Defining the tumor microenvironment by integration of immunohistochemistry and extracellular matrix targeted Imaging Mass Spectrometry. Cancers13, 4419 (2021).

[84] Angel PMet al.. Mapping extracellular matrix proteins in formalin-fixed, paraffin-embedded tissues by MALDI imaging mass spectrometry. J. Proteome Res., 2018, 17: 635-646

[85] Taylor Het al.. Spatial localization of collagen hydroxylated proline site variation as an ancestral trait in the breast cancer microenvironment. Matrix Biol., 2025, 136: 71-86

[86] Eckhard U, Huesgen PF, Brandstetter H, Overall CM. Proteomic protease specificity profiling of clostridial collagenases reveals their intrinsic nature as dedicated degraders of collagen. J. Proteom., 2014, 100: 102-114

[87] Eckhard U, Schonauer E, Nuss D, Brandstetter H. Structure of collagenase G reveals a chew-and-digest mechanism of bacterial collagenolysis. Nat. Struct. Mol. Biol., 2011, 18: 1109-1114

[88] Sauve, A. C. & Speed, T. P. Normalization, baseline correction and alignment of high-throughput mass spectrometry data. Proc. Gensips 1–4. John Hopkins University, Baltimore, MD, May 26–27 (2004).

[89] Deininger SOet al.. Normalization in MALDI-TOF imaging datasets of proteins: practical considerations. Anal. Bioanal. Chem., 2011, 401: 167-181

[90] Trede Det al.. Exploring three-dimensional matrix-assisted laser desorption/ionization imaging mass spectrometry data: three-dimensional spatial segmentation of mouse kidney. Anal. Chem., 2012, 84: 6079-6087

[91] Zou KH, O’Malley AJ, Mauri L. Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models. Circulation, 2007, 115: 654-657

[92] Klein Oet al.. MALDI imaging mass spectrometry: discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures. Proteomics, 2014, 14: 2249-2260

[93] Xia J, Psychogios N, Young N, Wishart DS. MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res., 2009, 37: W652-W660

[94] Meier Fet al.. Online parallel accumulation-serial fragmentation (PASEF) with a novel trapped ion mobility mass spectrometer. Mol. Cell Proteom., 2018, 17: 2534-2545

[95] Tsou CCet al.. DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics. Nat. Methods, 2015, 12: 258-264

[96] MacLean BXet al.. Using skyline to analyze data-containing liquid chromatography, ion mobility spectrometry, and mass spectrometry dimensions. J. Am. Soc. Mass Spectrom., 2018, 29: 2182-2188

[97] Tyanova S, Temu T, Cox J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc., 2016, 11: 2301-2319

[98] Gillet LCet al.. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell Proteom., 2012, 11: O111 016717

[99] Collins BCet al.. Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry. Nat. Commun., 2017, 8 291

[100] Burger T. Gentle introduction to the statistical foundations of false discovery rate in quantitative proteomics. J. Proteome Res., 2018, 17: 12-22

Funding

U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)(P01 AG066591)

U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)(R21 AR084303)

U.S. Department of Health & Human Services | NIH | NIH Office of the Director (OD)(S10 OD038264)

U.S. Department of Health & Human Services | NIH | National Institute of Dental and Craniofacial Research (NIDCR)(R01 DE019284)

U.S. Department of Defense (United States Department of Defense)(DOD PRORP W81XWH1810155)

U.S. Department of Health & Human Services | NIH | NCI | Division of Cancer Epidemiology and Genetics, National Cancer Institute (National Cancer Institute Division of Cancer Epidemiology and Genetics)(R21 CA240148)

U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)(S10 OD030212)

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