Systemic and local autoantibody responses to extracellular matrix proteins define inflammatory phenotypes across arthropathies

Abstract

Objectives

Autoantibodies targeting extracellular matrix proteins are emerging as critical contributors to arthritis pathogenesis, yet their presence across different arthropathies remains incompletely characterized. This study investigated systemic and local expression of proteoglycan 4 (PRG4) and cartilage oligomeric matrix protein (COMP), alongside their corresponding autoantibodies, in healthy controls and patients with OA, RA or JIA.

Methods

Serum and SF samples were analysed by ELISA from control subjects, and OA, RA and JIA patients.

Results

Serum PRG4 levels were significantly decreased in RA compared with controls and OA, while JIA patients showed elevated levels. Serum COMP was significantly elevated in OA and JIA compared with controls and RA. In SF, OA showed decreased PRG4 compared with all other groups, while COMP levels were highest in OA and controls. Anti-PRG4 autoantibodies were significantly elevated in all disease groups compared with controls in serum, with RA and JIA also showing increased elevation in SF. Anti-COMP autoantibodies were significantly increased in RA and JIA serum and elevated in all disease groups in SF compared with controls. Notably, a positive correlation between PRG4 protein and anti-PRG4 antibodies was observed specifically in OA SF, suggesting local antigen-driven immune responses.

Conclusion

These findings demonstrate that autoantibodies against PRG4 and COMP are present across arthropathies with distinct patterns reflecting different pathogenic mechanisms. The detection of these autoantibodies provides mechanistic insights into disease progression and potential biomarkers for identifying differential pathway activation/inflammatory subgroups within arthropathies.

Rheumatology key messages.

• Autoantibodies against proteoglycan 4 (PRG4) and cartilage oligomeric matrix protein (COMP) are distinctively elevated and patterned across different arthropathies studied.

• Local SF antigen-driven immune responses to PRG4 differentiate osteoarthritis from other arthropathies mechanistically.

• Detecting extracellular matrix protein autoantibodies may guide identification of inflammatory subgroups and targeted arthritis therapies.

Introduction

OA, RA and JIA represent distinct yet overlapping joint disorders characterized by cartilage degeneration, synovial inflammation and progressive loss of joint function [1]. OA has traditionally been classified as a degenerative disease initiated by biomechanical stress and aging-associated changes in cartilage homeostasis. However, emerging evidence indicates that low-grade inflammation and immune dysregulation also contribute to OA progression [2]. In contrast, RA and JIA are autoimmune diseases driven by a breakdown in immune tolerance, leading to chronic synovitis, pannus formation and systemic immune activation [3, 4]. Despite their aetiological differences, all three conditions converge on dysregulated extracellular matrix (ECM) turnover, joint tissue remodelling and altered immune recognition of cartilage components.

Proteoglycan 4 (PRG4, also known as lubricin) and cartilage oligomeric matrix protein (COMP) are two ECM proteins essential for joint integrity. PRG4, secreted by synoviocytes and superficial zone chondrocytes, functions as a boundary lubricant and exerts anti-inflammatory and immunomodulatory effects, including suppression of Toll-like receptor (TLR) signalling and regulation of macrophage activity [5]. COMP, a pentameric glycoprotein of the thrombospondin family, binds collagens and other ECM proteins to maintain cartilage stability and load-bearing function [6]. During joint injury and disease, altered expression and proteolytic cleavage of both PRG4 and COMP result in their release into SF and circulation [7, 8], where they may act not only as biomarkers of cartilage turnover but also as potential autoantigens.

Autoantibody generation is a hallmark of RA and JIA and is increasingly recognized in subsets of OA [9]. The breakdown of central and peripheral tolerance leads to aberrant activation of autoreactive B cells, often facilitated by antigen-presenting cells that present cartilage-derived peptides in the context of inflammatory cytokine signalling [4, 10]. Post-translational modifications of joint proteins, such as citrullination, carbamylation or glycosylation, can enhance their immunogenicity by creating neo-epitopes recognized by autoreactive T and B cells. Once activated, certain B cells differentiate into plasma cells that secrete autoantibodies, which can form immune complexes, activate complement and drive Fc receptor–mediated inflammation [11].

Autoantibodies directed against ECM proteins contribute to pathology through several mechanisms. In RA, antibodies have been shown to enhance osteoclastogenesis, promote synovial inflammation and exacerbate cartilage destruction [12]. COMP autoantibodies, in particular, have been associated with erosive disease and increased joint damage in mice models [13]. While less studied, autoantibodies to PRG4 may have dual pathogenic effects: (i) by directly neutralizing PRG4’s lubricating and anti-inflammatory functions, thereby increasing cartilage wear and inflammatory signalling; and (ii) by forming immune complexes within the SF, perpetuating complement activation and leucocyte recruitment. In OA, where immune involvement has historically been underappreciated, the detection of autoantibodies against COMP and possibly PRG4 may indicate shared autoimmune mechanisms with RA and JIA, and help define subgroups of patients with more inflammatory phenotypes.

In this study, we investigate the local (SF) vs systemic (serum) expression of PRG4 and COMP, as well as the presence of circulating and synovial autoantibodies targeting these proteins, in control individuals and patients with OA, RA or JIA. By comparing expression profiles and immune responses across these distinct disease states, we aim to elucidate whether immune recognition of joint-derived ECM proteins represents a byproduct of tissue turnover or a mechanistic driver of pathology, and whether these autoantibodies can provide mechanistic insights into disease pathogenesis/progression and/or diagnostic or prognostic value as biomarkers of disease activity.

Patients and methods

Subjects and clinical evaluation

This study protocol was approved by the University of Calgary Human Research Ethics Board (REB15-005, REB15-0880, REB16-1262, REB-21987, REB15-0998). Participants provided written consent. All testing was carried out in accordance with the declaration of Helsinki. It is important to note that serum and SF were not necessarily collected from the same individuals within groups (Supplementary Table S1).

Control (serum n = 50, mean age 45.7 ± 3.7 years; SF = 20, mean age 53.2 ± 5.1 years): individuals showed no clinical signs of OA or RA (based on ACR criteria) and were questioned (and potentially excluded) regarding personal (intraarticular joint injury, inflammatory arthritis, autoimmune diseases) and family (inflammatory arthritis including any autoimmune diseases) histories. Participants (e.g. faculty, staff, students, volunteers) were recruited from the sports medicine program and human performance laboratory to provide serum. SF was collected from cadaveric knees (cartilage and synovial tissue was examined microscopically at the point of harvest) examined collected within 4 h after death received by the Southern Alberta Organ and Tissue Donation Program (SAOTDP). The SAOTDP obtains the medical history of every donor, including current medication, previous history of joint diseases and other comorbidities (e.g. cancer, diabetes, inflammatory diseases).

Knee OA (serum n = 50, mean age 60.4 ± 6 years; SF = 20, mean age 59.8 ± 8.3 years): inclusion criteria required a diagnosis of OA performed at the OA clinic (University of Calgary) based on clinical symptoms of 3 months or greater with radiographic (standing AP radiographs) evidence [Kellgren and Lawerence (K/l) grading: all radiographs were graded by a sports medicine physician and registered nurse first assistant: inter-reader reliability/kappa, κ = 0.84] of changes associated with OA in accordance with ACR criteria [14]. A K/l grade of 3 was required for inclusion into the knee OA cohort. A previous diagnosis of hip, hand or spine OA resulted in exclusion and a clinical assessment was undertaken to identify potential undiagnosed OA in these joints was undertaken at the time of recruitment.

RA (serum n = 50, mean age 47.2 ± 4.7; SF = 20, mean age 57.1 ± 8.2 years): inclusion criteria were an age of 40 years or older and a diagnosis based on the ACR criteria [15]. All RA patients were managed with various immune modulating drugs at the time of sample collection.

JIA (serum n = 50, mean age 11.5 ± 2.9 years; SF = 20, mean age 11.4 ± 4.6 years): inclusion criteria were patients diagnosed with JIA based on the ILAR criteria (Oligoarticular Persistent/Extended; RF negative Polyarticular) [16] followed at the pediatric rheumatology clinic at the Alberta Children’s Hospital.

Sample collection

Serum samples were collected at rest by standard venipuncture with untreated vacuum tubes. Serum was immediately aliquoted and stored at −80ºC until required for analysis. All samples analysed were only thawed once (at the time of analysis).

SF (knee and hip OA cohorts) was aspirated from the knee joint by the attending orthopedic surgeon, rheumatologist or sports medicine physician. Control SF samples were obtained from the SAOTDP described above. SF samples were collected without the use of lavage. The samples centrifuged at 3000 g for 15 min at room temperature and stored at −80ºC. All samples analysed were only thawed once (at the time of analysis).

Quantification of PRG4 and COMP

Protein concentrations of PRG4 and COMP in serum (diluted 1:10) and SF (1:20 000) were determined by ELISA. Commercially available ELISA kits specific for human PRG4 (R&D Systems, Minneapolis, MN, USA; DY9829-05) and COMP (Abcam, Waltham, MA, USA; ab213764) were used according to the manufacturer’s protocols. Standards (the rhPRG4 from Lubris was used as the standard for the R&D kit in place of the included standard) and samples were assayed in duplicate. Protein concentrations were interpolated from standard curves generated for each plate. Negative controls for this assay were the exclusion of sample, and positive controls were the included standard.

Autoantibodies against PRG4 and COMP in serum and SF were analysed using the SimpleStep ELISA® Custom ELISA Kit (Abcam, Waltham, MA, USA). Recombinant human PRG4 (Lubris LLC, Weston, MA, USA) and COMP (R&D Systems, Minneapolis, MN, USA) proteins were conjugated to the capture peptide at a concentration of 1.0 mg/ml as recommended by the kit. These proteins were coated onto the assay plate, and patient samples were incubated following the recommended protocol. Bound autoantibodies were detected using an horseradish peroxidase–conjugated anti-human IgG detection antibody, and colorimetric signal was developed with 3,3′,5,5′-Tetramehtylbenzidine (TMB) substrate. Absorbance was measured at 450 nm using a microplate reader. As negative controls, SimpleStep peptide plates (without recombinant PRG4 or COMP) were used and no signal was detected.

To enable quantitative analysis and act as positive controls, monoclonal anti-PRG4 (Sigma, St. Lous, MO, MABT401) and anti-COMP (Abcam, Waltham, MA, USA; ab231977) antibodies used over a concentration range of 100 ng/ml to 100 µg/ml were used as positive controls and to determine detections ranges. Autoantibody concentrations were interpolated and expressed as arbitrary units (AU/ml). Intra-assay and inter-assay coefficients of variation were ∼8% and ∼13%, respectively, ensuring reproducibility across plates.

Statistical analysis

Group differences in protein levels and autoantibody titers were assessed using one-way analysis of variance, with a Tukey’s post-hoc test. Correlations between protein concentrations and autoantibody levels were evaluated using Pearson’s correlation coefficients. Statistical significance was defined as P < 0.05.

Results

Presence of PRG4 and COMP and their respective autoantibodies in serum

Serum from control, OA, RA and JIA (n = 50 each group) was collected and probed for PRG4 and COMP levels by ELISA (Fig. 1). For PRG4, the lowest concentration observed was 0.37 µg/ml (OA patient) and the highest recorded level was 1.86 µg/ml (RA patient). There was a significant decrease of PRG4 in the serum of RA patients compared with control and OA serum, while there was a significant increase in PRG4 in the serum of JIA patients compared with RA serum (Fig. 1A). In terms of serum concentrations of COMP, the lowest concentration observed was 0.02 µg/ml (control) and the highest recorded level was 6.76 µg/ml (OA patient). There were significant increases in OA patients compared with control and RA sera, while there was a significant decreased in control and RA COMP levels compared with JIA sera. There was no difference in COMP levels between OA and JIA patients (Fig. 1B).

Figure 1.

Levels of proteoglycan 4 (PRG4), cartilage oligomeric matrix protein (COMP) and their autoantibodies across arthropathies. Serum samples (n = 50 per group) from controls and patients with OA, RA or JIA were analysed by ELISA. PRG4 protein concentration showing significant decrease in RA compared with controls and OA, with elevated levels in JIA compared with RA (A). COMP concentration showing significant increases in OA and JIA compared with controls and RA (B). Anti-PRG4 autoantibody levels showing significant elevation in all disease groups compared with controls (C). Anti-COMP autoantibody levels showing significant increases in RA and JIA compared with controls and OA; note the apparent bimodal distribution of anti-COMP levels in the RA cohort (D). Protein concentrations are expressed in µg/ml (A, B); autoantibody levels are expressed in arbitrary relative units (RU) (C, D). Data represent mean ± s.d. Statistical comparisons were performed using one-way analysis of variance followed by multiple comparison correction. Significance threshold: P < 0.05

Antibodies for PRG4 and COMP were detected in the sera of all study participants. The lowest concentration observed for anti-PRG4 was 1.45 arbitrary relative units (RU) (OA) and the highest being 454.10 RU (OA). The control group presented with significantly lower anti-PRG4 antibodies vs all other groups, and there were no significant differences in anti-PRG4 between OA, RA or JIA (Fig. 1C). Anti-COMP antibodies were detected in the sera of every individual sample with the lowest concentration observed being 2.53 RU (JIA) and the highest being 501.40 RU (RA). RA and JIA patients had significantly increased anti-COMP levels respective to control and OA patients (Fig. 1D). There were no differences in anti-COMP between RA and JIA or control and OA (Fig. 1D). Interestingly, there appeared to be a bimodal distribution of anti-COMP levels in the RA with a clear low and high population (Fig. 1D).

Relationship between protein concentration and autoantibody levels in serum

To determine whether individuals with higher serum levels of PRG4 or COMP displayed higher levels of anti-PRG4 (Fig. 2) or anti-COMP (Fig. 3), respectively, Pearson correlation analysis was undertaken. There were no relationships observed in any cohort between PRG4 protein concentration and anti-PRG4 presence in the serum (Fig. 2). The same was observed for COMP vs anti-COMP levels (Fig. 3). We also examined whether there were any relationships between PRG4 (Supplementary Fig. S1), anti-PRG4 (Supplementary Fig. S2), COMP (Supplementary Fig. S3) or anti-COMP (Supplementary Fig. S4) with the age of the individuals within each cohort. No relationships between PRG4 or anti-PRG4 and age was observed in any cohort. In terms of serum COMP levels, there was a significant relationship between age and COMP concentration observed in the OA cohort with COMP levels increasing with age (R² = 0.1999) (Supplementary Fig. S3).

Figure 2.

Absence of correlation between serum proteoglycan 4 (PRG4) protein levels and anti-PRG4 autoantibodies across arthropathies. Pearson correlation analysis examining the relationship between serum PRG4 protein concentration and anti-PRG4 autoantibody levels. Each data point represents an individual subject. Correlation coefficient (R²) and P-values are displayed for each patient group. Controls (n = 50) (A), OA patients (n = 50) (B), RA patients (n = 50) (C), JIA patients (n = 50) (D). No significant correlations were observed in any cohort (P > 0.05 for all comparisons), suggesting that circulating anti-PRG4 antibody levels are independent of systemic PRG4 protein concentrations

Figure 3.

Absence of correlation between serum cartilage oligomeric matrix protein (COMP) protein levels and anti-COMP autoantibodies across arthropathies. Pearson correlation analysis examining the relationship between serum COMP concentration and anti-COMP autoantibody levels. Each data point represents an individual subject. Correlation coefficient (R²) and P-values are displayed for each patient group. Controls (n = 50) (A), OA patients (n = 50) (B), RA patients (n = 50) (C), JIA patients (n = 50) (D). No significant correlations were observed in any cohort (P > 0.05 for all comparisons), indicating that circulating anti-COMP antibody levels are independent of systemic COMP protein concentrations

Presence of PRG4 and COMP and their respective autoantibodies in SF

SF from control, OA, RA and JIA (n = 20 each group) was collected (from a distinct cohort of patients vs the serum samples) and probed for PRG4 and COMP levels by ELISA (Fig. 1). For PRG4, the lowest concentration observed was 59.00 µg/ml (RA) and the highest recorded level was 711.00 µg/ml (control). There was a significant decrease of PRG4 in the SF of OA compared with control, RA and JIA patients, while there were no differences in PRG4 concentration between control, RA and JIA SF (Fig. 4A). In terms of SF concentrations of COMP, the lowest concentration observed was 9.91 µg/ml (JIA) and the highest recorded level was 52.50 µg/ml (OA). There was no difference between control and OA or RA and JIA COMP levels. RA and JIA COMP levels were decreased compared with control and JIA levels were decreased compared with OA. There was no difference in SF COMP levels between OA and RA (Fig. 4B).

Figure 4.

Localized expression of proteoglycan 4 (PRG4), cartilage oligomeric matrix protein (COMP) and their autoantibodies in SF. The SF samples (n = 20 per group) from controls and patients with OA, RA or JIA were analysed by ELISA. Note that SF and serum samples were obtained from distinct patient cohorts. PRG4 protein concentration showing significant decrease in OA compared with controls, RA and JIA, with no differences between controls, RA and JIA (A). COMP concentration showing elevated levels in controls and OA compared with RA and JIA (B). Anti-PRG4 autoantibody levels showing significant increases in RA and JIA compared with controls and OA; note the apparent bimodal distribution in RA and JIA groups (C). Anti-COMP autoantibody levels showing significant elevation in all disease groups (OA, RA, JIA) compared with controls (D). Protein concentrations are expressed in µg/ml (A, B); autoantibody levels are expressed in arbitrary relative units (RU) (C, D). Data represent mean ± s.d. Statistical comparisons were performed using one-way analysis of variance followed by multiple comparison correction. Significance threshold: P < 0.05

Antibodies directed against PRG4 and COMP were detected in the SF of all study participants with the lowest anti-PRG4 concentration observed being 19.00 RU (control/OA) and the highest being 187.00 RU (JIA). There were no differences between anti-PRG4 levels between control and OA, or RA and JIA, however, there was a significant increase in anti-PRG4 levels in the RA/JIA groups compared with the control/OA groups (Fig. 4C). Anti-COMP antibodies were detected in the serum of every individual SF sample with the lowest concentration observed being 16.01 RU (control) and the highest being 491.00 RU (JIA). There were no differences between OA, RA and JIA anti-COMP levels, but all were elevated compared with control levels (Fig. 4D). One interesting observation was the apparent bimodal distribution of anti-PRG4 levels in the RA and JIA groups (Fig. 4C).

Taken together, the heat map analysis of all proteins and antibodies in serum and SF across all patient groups provides an at-a-glance view of the heterogeneity in ECM protein abundance and autoantibody responses across arthropathies (Supplementary Fig. S5), underscoring that PRG4 and COMP are regulated differently in serum and SF and that the accompanying autoantibody signals likely reflect disease-specific immune and tissue-remodelling processes.

Relationship between protein concentration and autoantibody levels in SF

To determine whether individuals with higher SF levels of PRG4 or COMP displayed higher levels of anti-PRG4 (Fig. 5) or anti-COMP (Fig. 6), respectively, Pearson correlation analysis was undertaken. There was a significant relationship between PRG4 and anti-PRG4 levels in the OA cohort (R² = 0.2395) (Fig. 5) with no other significant relationships identified in the other cohorts. There were no relationships observed in any cohort between COMP protein concentration and anti-COMP levels in SF (Fig. 6). We also examined if there were any relationships between PRG4 (Supplementary Fig. S6), COMP (Supplementary Fig. S7), anti-PRG4 (Supplementary Fig. S8) or anti-COMP (Supplementary Fig. S9) with the age of the individuals within each cohort. No relationships between PRG4 (Supplementary Fig. S6) or anti-PRG4 (Supplementary Fig. S8) and age was observed in any cohort. When we examined the relationship between age and COMP or anti-COMP levels, we observed a significant relationship between age and anti-COMP concentration observed in the RA cohort with COMP levels increasing with age (R² = 0.2256) (Supplementary Fig. S9).

Figure 5.

Antigen-driven correlation between proteoglycan 4 (PRG4) protein and anti-PRG4 autoantibodies in osteoarthritic SF. Pearson correlation analysis examining the relationship between SF PRG4 protein concentration and anti-PRG4 autoantibody levels. Each data point represents an individual subject. Correlation coefficient (R²) and P-values are displayed for each patient group. Controls (n = 20) (A), OA patients (n = 20) (B), RA patients (n = 20) (C), JIA patients (n = 20) (D). A significant positive correlation was observed exclusively in the OA cohort (R²=0.2395, P < 0.05), suggesting local antigen-driven immune responses within the OA joint compartment. No significant correlations were detected in controls, RA or JIA groups

Figure 6.

Absence of correlation between SF cartilage oligomeric matrix protein (COMP) protein levels and anti-COMP autoantibodies across arthropathies. Pearson correlation analysis examining the relationship between SF COMP concentration and anti-COMP autoantibody levels. Each data point represents an individual subject. Correlation coefficient (R²) and P-values are displayed for each patient group. Controls (n = 20) (A), OA patients (n = 20) (B), RA patients (n = 20) (C), JIA patients (n = 20) (D). No significant correlations were observed in any cohort (P > 0.05 for all comparisons), indicating that SF anti-COMP antibody levels are independent of local COMP protein concentrations

ROC analysis of PRG4 and COMP as putative discriminators of arthropathy subtypes

Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of PRG4 and COMP protein levels, as well as their corresponding autoantibodies, to distinguish control samples from OA, RA and JIA in both serum and SF (Supplementary Figs S10–S13).

In serum, PRG4 displayed poor to modest discrimination across comparisons (Supplementary Fig. S10), with area under the curve (AUC) values of 0.53 for control vs OA, 0.65 for control vs RA, and 0.65 for control vs JIA, indicating limited diagnostic utility for systemic PRG4 alone. Serum COMP performed better, particularly for control vs JIA (AUC = 0.84), while discrimination for control vs OA (AUC = 0.67) and control vs RA (AUC = 0.63) was more modest.

In SF (Supplementary Fig. S12), PRG4 showed moderate discriminatory performance for control vs OA (AUC = 0.82) and control vs JIA (AUC = 0.64), but only weak performance for control vs RA (AUC = 0.57), indicating that local PRG4 levels are more informative for OA and JIA than for RA. COMP in SF showed limited-to-moderate discrimination for control vs OA (AUC = 0.59) and control vs RA (AUC = 0.74), while performance was strongest for control vs JIA (AUC = 0.85), suggesting that synovial COMP is most useful for identifying paediatric inflammatory disease.

Autoantibody-based ROC analysis showed stronger overall performance than protein measures. In serum (Supplementary Fig. S11), anti-PRG4 demonstrated good discrimination for control vs OA (AUC = 0.77), control vs RA (AUC = 0.73) and control vs JIA (AUC = 0.68), whereas anti-COMP showed comparable or improved performance, especially for control vs RA (AUC = 0.87) and control vs JIA (AUC = 0.88). In SF (Supplementary Fig. S13), anti-PRG4 differentiated controls from OA with an AUC of 0.75 and showed excellent discrimination for control vs RA (AUC = 0.96) and control vs JIA (AUC = 0.90), while anti-COMP showed high performance across all comparisons, including control vs OA (AUC = 0.89), control vs RA (AUC = 0.96) and control vs JIA (AUC = 0.97). Collectively, these ROC analyses indicate that autoantibodies to PRG4 and COMP, particularly in SF, have stronger potential as discriminatory biomarkers than the corresponding proteins alone and may better capture disease-associated immune activity.

Discussion

The findings from this study provide novel insights into the expression of the ECM proteins PRG4 and COMP, their systemic and SF concentrations, and the presence of corresponding autoantibodies across different arthropathies. The observed patterns of both protein expression and autoantibody generation reveal potentially important mechanistic and clinical implications that extend our understanding of joint pathophysiology.

PRG4 expression and function in joint disease

The significant decrease in serum PRG4 levels observed in RA patients compared with controls and OA patients aligns with emerging evidence that PRG4 deficiency contributes to inflammatory joint pathology [7, 17]. This finding is particularly significant given PRG4’s multifaceted role in joint homeostasis, extending beyond boundary lubrication to include anti-inflammatory functions through interaction with TLRs. Studies have demonstrated that PRG4 binds TLR2 and TLR4, inhibiting their activation by inflammatory agonists and reducing nuclear factor kappa B signalling in synoviocytes [18, 19]. The reduced serum PRG4 in RA may therefore contribute to sustained inflammation by compromising this endogenous anti-inflammatory mechanism [5, 20]. The elevated PRG4 levels in JIA patients represent an intriguing finding that may reflect the unique pathophysiology of pediatric arthritis. Unlike adult RA, where chronic inflammation may deplete PRG4 reserves, the developing musculoskeletal system in JIA patients may mount a more robust compensatory response to preserve joint function. This observation is supported by evidence suggesting that PRG4 expression can be upregulated in response to mechanical stress and inflammatory signals through TGF-β signalling pathways [21, 22].

COMP as a biomarker of cartilage turnover

The significantly elevated COMP levels in both OA and JIA serum samples confirm previous studies of COMP’s established role as a biomarker of cartilage degradation [8, 23, 24]. COMP is released from cartilage during matrix turnover and has been consistently associated with disease severity and progression in arthritis [6, 8, 24, 25]. The bimodal distribution of COMP levels observed in RA patients suggests potential disease heterogeneity, with distinct subgroups potentially representing different pathogenic mechanisms or disease stages. Recent proteomic analyses have validated the diagnostic potential of COMP, with ROC curve analysis demonstrating area under the curve values of 96%, 87.2% and 85.2% for distinguishing OA grades 2, 3 and 4 from RA, respectively [26]. These findings support the utility of COMP as a biomarker of cartilage destruction and also for differential diagnosis between arthropathies.

Autoantibody generation and immune tolerance breakdown

The presence of anti-PRG4 and anti-COMP autoantibodies across all study groups, including healthy controls, reflects the natural occurrence of ‘low-level’ autoantibodies against self-antigens [27]. However, the significantly elevated levels in disease states, particularly the increased anti-PRG4 antibodies in OA, RA and JIA compared with controls, suggests that immune tolerance breakdown against ECM proteins is a common feature across arthropathies. The pathogenic potential of anti-COMP antibodies has been demonstrated in experimental models, where monoclonal anti-COMP antibodies can induce arthritis in naïve mice through immune complex formation and complement activation [13]. The crystal structure of pathogenic anti-COMP antibodies has revealed that these antibodies recognize specific epitopes on COMP, and importantly, these epitopes can undergo citrullination—a post-translational modification that enhances immunogenicity in RA [28]. This finding provides a mechanistic link between COMP autoantibodies and the well-established role of ACPA in RA pathogenesis.

SF dynamics and local immune responses

The distinct patterns observed in SF compared with serum highlight the importance of local joint microenvironment in ECM protein metabolism and immune responses, with the caveat that serum and SF samples were obtained from distinct cohorts of patients. The positive correlation between PRG4 protein levels and anti-PRG4 antibodies specifically in OA SF suggests that local antigen exposure may drive antibody production within the joint compartment in some but not all arthropathies. This finding is consistent with evidence that immune complexes that contain joint proteins can be isolated from arthritic tissues and that these complexes contribute to local inflammation [29]. The decreased PRG4 levels in OA SF compared with other groups may reflect increased proteolytic degradation in the OA joint environment. Our recent studies have identified mast cell tryptase β and Cathepsin G as proteases that cleaves PRG4 in osteoarthritic joints, reducing its lubricating function and promoting inflammatory signalling through enhanced TLR activation [7, 30]. This mechanism provides a potential explanation for the progressive loss of joint function in OA despite attempts at tissue repair.

Clinical and therapeutic implications

The detection of autoantibodies against PRG4 and COMP across different arthropathies suggests shared autoimmune mechanisms that may contribute to disease progression. In OA, traditionally viewed as primarily a non-inflammatory degenerative condition, the presence of these autoantibodies indicates immune system involvement that could define inflammatory OA phenotypes requiring different therapeutic approaches. The therapeutic potential of targeting these pathways is supported by preclinical studies demonstrating that recombinant PRG4 administration can mitigate cartilage degeneration and reduce inflammation in experimental arthritis models [31, 32]. Similarly, understanding the epitope specificity of pathogenic anti-PRG4 and anti-COMP antibodies could inform the development of targeted immunotherapies to neutralize these antibodies or prevent their formation.

Future directions and limitations

While this study provides valuable insights into ECM protein autoimmunity in joint disease, several limitations should be acknowledged. The lack of correlation between protein levels and autoantibody titres in most cohorts suggests complex relationships between antigen exposure, immune tolerance and antibody production that require further investigation. Additionally, the study did not examine the functional consequences of these autoantibodies on protein function or their relationship with clinical outcomes. Future research should focus on determining whether these autoantibodies contribute to disease pathogenesis or represent epiphenomena of tissue damage. Longitudinal studies examining the temporal relationship between autoantibody development and disease progression would be particularly informative. Furthermore, investigating the potential for these biomarkers to predict therapeutic responses or identify patients who might benefit from specific interventions represents an important clinical application. It is also important to recognize that we did not include age-matched serum and SF healthy/control samples for the JIA cohort as obtaining these samples—particularly SF from healthy children—is ethically and logistically challenging. It is also possible that proteolytic fragmentation of PRG4 may artifactually increase its ELISA-measured concentration because of the highly repetitive central mucin domain, however prior work examining PRG4 in SF shows similar levels to what we have reported here [33].

Overall, the identification of PRG4 and COMP autoantibodies across different arthropathies expands our understanding of the immune components underlying joint disease and provides new avenues for both biomarker development and therapeutic intervention in the management of arthritis.

Supplementary material

Supplementary material is available at Rheumatology online.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request due to their containing information that could compromise the privacy of research participants.

Contribution statement

R.J.K. conceived, designed and oversaw experiments with scientific assistance from M.M., S.A., T.A.S., G.D.J. and M.J.F. R.J.K., M.M. and S.A. performed all experiments. R.J.K. analysed data and wrote the manuscript. D.N.V., H.S. and M.J.F. assisted with data collection. All authors were involved in critical review of the manuscript, and all authors have approved the final version for submission.

Funding

This work was supported by grants from Natural Sciences and Engineering Research Council (NSERC) of Canada RGPIN-2014–04586; Canada Foundation for Innovation; the Calgary Foundation, Grace Glaum Professorship and M.M. was supported by a Canadian Institutes for Health Research Grant [Prevention of Early Knee OA (PrE-OA Knee)]. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Disclosure statement: T.A.S. and G.D.J. authored patents on rhPRG4, and are paid consultants for Lubris LLC, MA, USA, and hold equity in Lubris LLC, MA, USA. M.J.F. is the founder and director of Mitogen Diagnostics Corp. and is a consultant to Werfen (San Diego, CA, USA) and ThermoFisher (Freiburg, Germany).