You are here

Article Text

Article menu

Download PDFPDF

Clinical and epidemiological research
Extended report
Relationship of serum markers of cartilage metabolism to imaging and clinical outcome measures of knee joint structure
  1. Patricia A Berry1,
  2. Rose A Maciewicz2,
  3. Anita E Wluka1,3,
  4. Mark D Downey-Jones2,
  5. Andrew Forbes1,
  6. Caroline J Hellawell2,
  7. Flavia M Cicuttini1
  1. 1Department of Epidemiology and Preventive Medicine, Monash University Medical School, Alfred Hospital, Prahran, Victoria, Australia
  2. 2Respiratory and Inflammation Research Area, AstraZeneca, Macclesfield, Cheshire, UK
  3. 3Baker Heart Research Institute, Melbourne, Victoria, Australia
  1. Correspondence to Professor Flavia M Cicuttini, Department of Epidemiology and Preventive Medicine, Monash University, Central and Eastern Clinical School, Alfred Hospital, Melbourne, VIC 3004, Australia; flavia.cicuttini{at}med.monash.edu.au

Abstract

Background Biomarkers of cartilage metabolism have prognostic potential.

Objective To examine whether serum cartilage biomarkers, cartilage oligomeric matrix protein (COMP), N-propeptide of type IIA procollagen (PIIANP), type II collagen breakdown product (collagen type-II cleavage (C2C)) predict cartilage volume loss and knee joint replacement.

Methods 117 subjects with knee osteoarthritis (OA) had MRI at baseline and 2 years. Cartilage biomarkers were measured at baseline. Change in knee cartilage volume over 2 years and knee joint replacement over 4 years was determined. The population was divided into subgroups with high or low cartilage biomarkers (based on biomarker levels greater than or equal to, or less than, the mean, respectively). The relationships between biomarkers and outcome measures were examined in the whole population, and separately in marker subgroups.

Results The relationship between cartilage biomarkers and cartilage volume loss was not linear across the whole population. In the low (regression coefficient B=–9.7, 95% CI –0.01 to 0.003, p=0.01), but not high (B=–0.46, 95% CI –8.9 to 8.0, p=0.92) COMP subgroup, COMP was significantly associated with a reduced rate of medial cartilage volume loss (p for difference between groups=0.05). Similarly, in the low (B=–8.2, 95% CI –12.9 to –3.5, p=0.001) but not high (B=2.6, 95% CI –3.3 to 8.5, p=0.38) PIIANP subgroup, PIIANP was associated with a significantly reduced rate of medial volume cartilage loss (p for difference=0.003). C2C was not significantly associated with rate of cartilage volume loss. PIIANP was associated with a reduced risk of joint replacement (odds ratio (OR)=0.28, 95% CI 0.10 to 0.93, p=0.04).

Conclusion Cartilage biomarkers may be used to identify subgroups among those with clinical knee OA in whom disease progresses at different rates. This may facilitate our understanding of the pathogenesis of disease and allow us to differentiate phenotypes of disease within a heterogeneous knee OA population.

https://doi.org/10.1136/ard.2009.124420

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Introduction

    Osteoarthritis (OA) is a major cause of pain and long-term disability, resulting in extensive use of healthcare resources. The societal and economic burden of this disease is only expected to increase owing to increased longevity and prevalence of obesity. Despite the significant burden of OA, the ability to predict structural change and identify those patients who will progress to the extent of requiring joint replacement is limited. Identifying better predictors of progression would allow more effective allocation of scarce healthcare resources, and reduce the overall burden of this disease.

    Loss of articular cartilage is a marker of the severity of OA.1 Biomarkers that reflect changes in cartilage metabolism may have prognostic potential. Since type II collagen is a major component of the cartilage matrix, there is increasing interest in biomarkers of type II collagen turnover.2,–,5 Such biomarkers include the N-propeptide of type IIA procollagen (PIIANP)6 which reflects synthesis of articular cartilage type IIA collagen, and collagen type-II cleavage (C2C), a product of type II collagen breakdown.7 Although it has been suggested that type II collagen synthesis and degradation is altered in OA,8,–,10 previous longitudinal studies examining the relationship between biomarkers of type II collagen turnover and disease progression have provided inconsistent results,2 3 or were unable to identify significant relationships.4 5 It may be that using a ratio of type II collagen synthesis to degradation is beneficial; indeed it has been shown to be more sensitive for investigating disease.2 4 11

    Cartilage oligomeric matrix protein (COMP) is an important component of the articular cartilage extracellular matrix, which may also be expressed in other joint tissues, including ligaments, tendons, menisci and synovium.12 13 Alterations in metabolism may affect cartilage integrity and stability.14,–,16 Although it has been suggested that elevated levels of COMP reflect synovitis,17 and the presence and severity of OA,18 19 previous longitudinal studies examining the relationship between COMP and OA progression have provided conflicting results.5 20,–,22

    Thus the aim of this study was to examine the relationship between biomarkers of cartilage metabolism and clinical outcome measures of joint structure. This study is particularly novel as very few studies have examined the relationship between cartilage biomarkers and cartilage volume loss assessed by MRI, as well as a joint replacement, a clinically important outcome.

    Patients and methods

    Study participants

    One hundred and thirty-two subjects aged >40 years with knee OA were recruited by advertising through local newspapers and the Victorian branch of the Arthritis Foundation of Australia and in collaboration with general practitioners, rheumatologists and orthopaedic surgeons as described.23 The study was approved by the ethics committee of the Alfred and Caulfield hospitals in Melbourne, Australia. All patients gave informed consent.

    All subjects fulfilled the American College of Rheumatology clinical and radiographic criteria for knee OA23, with pain at baseline in at least one pain dimension of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score >20% and osteophytes present within the knee. Subjects were excluded if any other form of arthritis was present, if there was any contraindication to MRI, if a total knee replacement was planned, or if they were unable to cooperate with study requirements.

    Data collection

    At baseline, weight was measured to the nearest 0.1 kg (shoes, socks and bulky clothing removed) using a single pair of electronic scales. Height was measured to the nearest 0.1 cm (shoes and socks removed) using a stadiometer. Body mass index (weight/height2 in kg/m2) was calculated. Knee pain (0–500), stiffness (0–200) and function (0–1700) were assessed with the WOMAC score at baseline, where zero represents no symptoms.24 A list of drugs was collected. Only one subject reported bisphosphonate treatment, and three had been receiving glucosamine for more than 6 months.

    MRI examination

    Each subject had an MRI performed on the symptomatic knee at baseline, and the mean±SD time for follow-up scan was 1.95±0.21 years later. Where both knees were symptomatic, the knee with least severe radiographic change was imaged to minimise loss to follow-up. Knees were imaged as previously described.25 26 (See online supplementary file 1 for further details.)

    Cartilage volume measurement

    Tibial cartilage volume was determined by image processing on an independent workstation using Osiris (University of Geneva), as previously described.23 The coefficients of variation (CV) for cartilage volume measures were 3.4% for medial tibial, and 2.0% for lateral tibial cartilage.25 (See supplementary file 2 for further details.)

    Bone area measurement

    Medial and lateral tibial plateau cross-sectional areas were directly measured from images using Osiris (University of Geneva) as described. The CVs for bone size measures were 2.3% for medial, 2.4% for lateral tibial plateau area.

    Measurement of biomarkers

    At the time of the first MRI, blood samples were obtained by direct venepuncture and centrifuged (1000 g at 4°C for 10 min) within 30 min of blood sampling. Serum was split into aliquots and frozen upright at −80°C.

    Sample handling

    All samples were thawed at 4°C, aliquoted, relabelled and refrozen. Before assaying, samples were defrosted at room temperature for 4 h; previously analyte stability had been assessed over 24 h and found to be acceptable at –80°C, 4°C and room temperature.

    Biomarker assays

    All ELISAs were run using duplicate wells for each sample, and the mean biomarker level was reported in each case.

    Cartilage formation was assessed by measurement of PIIANP (Synarc, Lyon, France). Cartilage degradation was assessed by measurement of serum levels of C2C (C2C ELISA, IBEX) and serum levels of intact or fragmented COMP (Wielisa Human COMP, Wieslab, Lund, Sweden) were assessed. The assays for COMP and C2C were run at Alderley Park, UK. The assay for PIIANP was run by the service provider Synarc.

    Biomarker quality assessment

    A quality assessment of the kits was completed before assessment of the samples to ensure robustness of the data. This was undertaken using serum from eight male/female healthy volunteers/donors aged 30–60 years and included an assessment of data drift across the plate, lower and upper limit of measurement, linearity of the response and spiking accuracy (recovery values fall within a range of 70–130%). All intra-and inter- assay CVs were within acceptable limits (<25%). The intra- and interassay CVs for each of the biomarkers were; COMP (5.4%, 5.1%), C2C (3.6%, 16.2%) and PIIANP (<10%),6 respectively.

    All kits met approval when healthy volunteer samples were analysed. All monitored participant's sample data points fell within the low to middle range of the standard curves and none of the samples approached the upper limit of measurement for any of the analytes. The lower limit of measurement was also recorded for each assay and data below this limit were set to the lower limit of measurement for the analysis.

    Ratios of biomarker of cartilage synthesis to cartilage degradation

    Ratios of biomarker of cartilage synthesis to cartilage degradation were obtained by dividing the biomarker of cartilage synthesis (PIIANP) by the biomarker of cartilage degradation (C2C) and the log ratios were used in the analysis.

    Statistical analyses

    Unpaired two-sample t tests were used to compare means in baseline characteristics between completers and those lost to follow up, the Mann–Whitney U test for comparison of medians and the χ2 test for comparison of proportions. The Kolmogorov–Smirnov statistic was used to test whether the data were normally distributed (a p value <0.05 was considered significantly different from a normal distribution). PIIANP displayed a skewed distribution; this information was log transformed, which resulted in the data approximating the normal distribution. The log transformed data was subsequently used.

    Annual percentage change in cartilage volume was computed as 100 × (initial volume − follow-up volume)/(initial volume × time between scans). The distribution of this outcome variable approximated the normal distribution.

    Linear and multiple linear regression models were used to examine the rate of cartilage volume loss and biomarker levels. In the results, a positive regression coefficient indicates that for every unit increase in biomarker, there was an associated increased rate of cartilage volume loss. A negative regression coefficient indicates that for every unit increase in biomarker, there was an associated reduction in the rate of cartilage volume loss.

    Logistic regression was used to examine the relationship between baseline cartilage biomarkers and risk of knee joint replacement over 4 years. A p value <0.05 (two-tailed) was regarded as statistically significant. All analyses were performed using the SPSS statistical package (standard version 14.0, SPSS, Chicago, Illinois, USA).

    Results

    Subject characteristics

    Of the original 132 participants, 117 (89%) completed follow-up. Differences in the baseline characteristics are shown in table 1. There were no significant differences between subjects with 4-year data in joint replacement (n=114) and those who were lost to follow-up (data not shown).

    View this table:
    Table 1

    Characteristics of the study population at baseline comparing those who completed the 2-year follow-up and those lost to follow-up

    The average annual rate of medial and lateral cartilage volume loss was 3.7±4.7% (mean±SD; 95% CI 2.7% to 4.8%) and 4.4±4.7% (mean±SD; 95% CI 3.4% to 5.5%) of initial cartilage. The difference in the rate of loss was not statistically significant (p=0.50).

    Cross-sectional relationship baseline cartilage biomarkers with baseline knee cartilage volume

    COMP and PIIANP were significantly associated with reduced medial cartilage volume after adjusting for potential confounders (table 2). C2C was associated with increased lateral cartilage volume. PIIANP:C2C was not significantly associated with cartilage volume (data not shown).

    View this table:
    Table 2

    Cross-sectional relationship between cartilage biomarkers and tibial cartilage volume at baseline in the total population

    Relationship between baseline cartilage biomarkers and change in knee cartilage volume over 2 years

    We initially examined the relationship between cartilage biomarkers and rate of cartilage volume loss in the whole population. This relationship was not linear with a change in gradient at approximately the mean for each of the biomarkers. As the data for these biomarkers were normally distributed and the mean and median values were similar, we used the mean to divide the populations into those with high biomarker levels (greater than or equal to the mean) and those with low biomarker levels (less than the mean).

    The relationship between baseline cartilage biomarkers and rate of cartilage volume loss in subgroups with high and low biomarker levels are presented in table 3. The independent samples z test was used to compare the rate of cartilage volume loss between high and low cartilage biomarker subgroups.

    View this table:
    Table 3

    Relationship between baseline cartilage biomarkers and annual percentage cartilage volume loss in the medial and lateral compartments

    The relationship between COMP and cartilage volume loss was not linear across the whole population, but rather there appeared to be two subgroups. In the low (less than mean) COMP subgroup, for every unit increase in COMP, there was an associated reduced rate of medial cartilage volume loss. However, there was no significant association between COMP and loss of cartilage volume in the high (greater than or equal to the mean) COMP subgroup. The difference in rate of cartilage volume loss between high and low COMP subgroups was statistically significant (p=0.05) (figure 1A).

    Figure 1
    Figure 1

    Relationship between cartilage biomarkers, cartilage oligomeric matrix protein (COMP) (panel A), N-propeptide of type IIA procollagen (PIIANP) (panel B), collagen type-II cleavage (C2C) (panel C) and annual percentage rate of medial tibial cartilage volume loss in high (≥mean) and low (<mean) marker subgroups. The line drawn in each panel represents the multiple linear regression models.

    Similarly, the relationship between PIIANP and loss of cartilage volume was not linear across the whole population. In the low (less than the mean) PIIANP subgroup, for every unit increase in PIIANP, there was an associated reduced rate of medial cartilage volume loss. However, there was no significant association between PIIANP and loss of cartilage volume in the high (greater than or equal to the mean) PIIANP subgroup. The difference in rate of cartilage volume loss between high and low PIIANP subgroups was statistically significant (p=0.003) (figure 1B). There was only slight agreement between low COMP and low PIIANP subgroups, and this result was not statistically significant (κ value 0.08, p=0.34). There was no significant association between C2C and medial cartilage volume loss, and there was no significant difference in rate of loss between high and low C2C subgroups (p=0.18) (figure 1C). Similar results were obtained when the subject receiving bisphosphonate treatment, and the subjects receiving glucosamine were excluded from the analysis (data not shown).

    No significant associations were found between cartilage biomarkers and rate of cartilage volume loss in the lateral compartment, and in the rate of loss between cartilage biomarker subgroups (data not shown).

    Relationship between baseline cartilage biomarkers with risk of total knee joint replacement over 4 years

    Eighteen subjects underwent joint replacement over the study period. Using logistic regression there was a trend for baseline PIIANP to be associated with reduced risk of total knee joint replacement over 4 years in the whole population, which was significant after adjusting for potential confounders (table 4). Although the number of joint replacements over the study period was modest, this relationship seemed to be stronger in the low (p=0.02) than in the high (p=0.94) PIIANP subgroup (data not shown). When the ratio was considered, a similar association was obtained (data not shown). However, this relationship was attributable to the strong relationship between PIIANP and the ratio PIIANP:C2C (r=0.92, p<0.001).

    View this table:
    Table 4

    Relationship between baseline cartilage biomarkers at baseline and risk of knee joint replacement over 4 years in the whole population

    Discussion

    In this well-characterised population with knee OA, we found that the relationship between serum biomarkers COMP and PIIANP and cartilage volume loss was not linear across the population. In the low (less than the mean) but not high (greater than or equal to the mean) subgroups, COMP and PIIANP were associated with reduced medial cartilage volume loss. PIIANP was also associated with a significantly reduced risk of knee joint replacement. These results suggest that it is possible to use cartilage biomarkers to identify subgroups within an OA population who progress at different rates.

    Previous cross-sectional studies found that biomarkers are associated with the presence and severity of OA. COMP has been shown to be significantly higher in subjects with symptomatic, radiographic knee OA than in controls,18 19 27 increased in the early stages of disease,28 but decreased in advanced disease.17 29 Our cross-sectional data support these observations as increased COMP was associated with less medial cartilage volume, and is consistent with previous work showing that PIIANP levels are reduced in subjects with knee OA.2 6

    Previous longitudinal studies examining the relationship between COMP and progression of OA have provided conflicting results. Higher baseline COMP predicted increased progression over 5 years in 115 patients and over 3 years in 48 patients.20 21 These studies used heterogeneous summed outcomes to assess disease progression. In contrast, studies of 57 subjects with clinical knee OA22 and 38 subjects with chronic knee pain,30 did not identify any relationship between COMP and radiographic progression over 5 years, or early radiographic changes over 3 years, respectively.

    Results from studies using MRI defined outcomes are similarly inconclusive. One study5 demonstrated a detrimental effect of COMP on cartilage loss over 30 months in 137 subjects with symptomatic and clinical knee OA. Another study, showed no relationship between COMP and cartilage volume.31 The discrepancies in the results of these studies may be explained by different measures of cartilage integrity. Hunter et al5 used semiquantitative scoring of cartilage loss. It is also possible that previous studies may have been underpowered to detect a relationship.22 30

    Few studies have examined the relationship between PIIANP and progression of knee OA. A previous longitudinal study demonstrated that subjects with lower levels of PIIANP at baseline had higher risk of progression over 1 year as assessed by radiography.2 Another study which compared OA progressors, who had either a reduction in joint space width or knee joint replacement over a 5-year period, with non-progressors did not identify any significant differences in PIIANP between the two groups.3 The authors suggested that the study may have been underpowered, with few progressors. Sharif et al3 did show that among progressors, mean PIIANP levels increased significantly over the 5-year period. Taken together, these results suggest that PIIANP reflects cartilage repair, which is consistent with the results of our study demonstrating that PIIANP was associated with reduced cartilage volume loss and reduced risk of knee joint replacement.

    This study has shown that cartilage biomarkers may be used to identify different subgroups within an OA population and highlights that the relationship between these biomarkers and cartilage volume loss is non-linear across the whole population. In those with low (less than the mean) levels of COMP and PIIANP, we observed the expected relationships with reduced cartilage volume loss.32,–,34 However, in those with high (greater than or equal to the mean) levels of COMP and PIIANP we found no significant relationship with cartilage volume loss. We found that there was a statistically significant difference in the rate of cartilage volume loss between those in the high PIIANP and COMP and low PIIANP and COMP subgroups, respectively, supporting the notion that these subgroups are behaving differently. The non-linear relationship we observed may be explained by a ceiling effect, whereby these cartilage biomarkers contribute more at lower levels—and higher levels do not increase the effect. Ceiling effects have been documented previously in varied conditions.35,–,37

    Consistent with previous studies, we did not identify a significant relationship between C2C and OA progression.4 5 The isolated cross-sectional relationship between C2C and cartilage volume in the lateral compartment is interesting but further work will be required to clarify whether C2C has the potential to predict disease progression in an OA population. Previous studies have suggested that considering an imbalance between cartilage synthesis and degradation may be useful for predicting progression.2 4 5 11 In our study, the ratio was not useful, as the results were driven by the strong linear relationship between PIIANP and the ratio PIIANP:C2C.

    Our study has a number of potential limitations. We were unable to account for multiple joint involvement. Nevertheless, we were able to identify biologically plausible and consistent relationships between cartilage biomarkers and two independent outcome measures. The significant effects obtained in this study were mostly found in the medial rather than the lateral compartment, providing biological plausibility as higher axial loads pass through the medial compartment, which affects cartilage metabolism.38,–,40 We did not evaluate all known biomarkers of cartilage metabolism, and study of these may provide alternative hypotheses. We did not adjust for multiple testing as this study was viewed as hypothesis generating. Further work will be required to determine distinct cut-off points for progression, and larger studies may be required to examine a combination of biomarkers in further subgroups. Further studies will also be required to examine the relationship between change in cartilage biomarkers over time and the risk of knee joint replacement.

    In this study, COMP and PIIANP were associated with a reduced rate of cartilage volume loss in the low, but not high, marker subgroups, respectively. PIIANP was also associated with a reduced risk of knee joint replacement. The results of this study suggest that cartilage biomarkers may be used to identify subgroups within a knee OA population with different rates of progression of disease. This may facilitate our understanding of the pathogenesis of disease and highlights the heterogeneity of knee OA.

    Acknowledgments

    The authors would like to acknowledge the following people: at AstraZeneca who performed the biomarker assays (Jacqueline Caddy, Sharon Crosby, Joanne Wayne) and for supporting statistical analysis (Euan Macpherson); at DEPM, Judy Hankin who recruited study participants. The authors would especially like to thank the study participants who made this study possible.

    References

    1. ↵
      1. Cicuttini FM,
      2. Wluka AE,
      3. Forbes A,
      4. et al
      . Comparison of tibial cartilage volume and radiologic grade of the tibiofemoral joint. Arthritis Rheum 2003;48:682–8.
      OpenUrlCrossRefPubMedWeb of Science
    2. ↵
      1. Garnero P,
      2. Ayral X,
      3. Rousseau JC,
      4. et al
      . Uncoupling of type II collagen synthesis and degradation predicts progression of joint damage in patients with knee osteoarthritis. Arthritis Rheum 2002;46:2613–24.
      OpenUrlCrossRefPubMedWeb of Science
    3. ↵
      1. Sharif M,
      2. Kirwan J,
      3. Charni N,
      4. et al
      . A 5-yr longitudinal study of type IIA collagen synthesis and total type II collagen degradation in patients with knee osteoarthritis–association with disease progression. Rheumatology (Oxford) 2007;46:938–43.
      OpenUrlAbstract/FREE Full Text
    4. ↵
      1. Cahue S,
      2. Sharma L,
      3. Dunlop D,
      4. et al
      . The ratio of type II collagen breakdown to synthesis and its relationship with the progression of knee osteoarthritis. Osteoarthr Cartil 2007;15:819–23.
      OpenUrlCrossRefPubMedWeb of Science
    5. ↵
      1. Hunter DJ,
      2. Li J,
      3. LaValley M,
      4. et al
      . Cartilage markers and their association with cartilage loss on magnetic resonance imaging in knee osteoarthritis: the Boston Osteoarthritis Knee Study. Arthritis Res Ther 2007;9:R108.
      OpenUrlCrossRefPubMed
    6. ↵
      1. Rousseau JC,
      2. Zhu Y,
      3. Miossec P,
      4. et al
      . Serum levels of type IIA procollagen amino terminal propeptide (PIIANP) are decreased in patients with knee osteoarthritis and rheumatoid arthritis. Osteoarthr Cartil 2004;12:440–7.
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Poole AR,
      2. Ionescu M,
      3. Fitzcharles MA,
      4. et al
      . The assessment of cartilage degradation in vivo: development of an immunoassay for the measurement in body fluids of type II collagen cleaved by collagenases. J Immunol Methods 2004;294:145–53.
      OpenUrlCrossRefPubMedWeb of Science
    8. ↵
      1. Nelson F,
      2. Dahlberg L,
      3. Laverty S,
      4. et al
      . Evidence for altered synthesis of type II collagen in patients with osteoarthritis. J Clin Invest 1998;102:2115–25.
      OpenUrlCrossRefPubMedWeb of Science
    9. ↵
      1. Hollander AP,
      2. Heathfield TF,
      3. Webber C,
      4. et al
      . Increased damage to type II collagen in osteoarthritic articular cartilage detected by a new immunoassay. J Clin Invest 1994;93:1722–32.
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      1. Hollander AP,
      2. Pidoux I,
      3. Reiner A,
      4. et al
      . Damage to type II collagen in aging and osteoarthritis starts at the articular surface, originates around chondrocytes, and extends into the cartilage with progressive degeneration. J Clin Invest 1995;96:2859–69.
      OpenUrlCrossRefPubMedWeb of Science
    11. ↵
      1. Davis CR,
      2. Karl J,
      3. Granell R,
      4. et al
      . Can biochemical markers serve as surrogates for imaging in knee osteoarthritis? Arthritis Rheum 2007;56:4038–47.
      OpenUrlCrossRefPubMedWeb of Science
    12. ↵
      1. Neidhart M,
      2. Hauser N,
      3. Paulsson M,
      4. et al
      . Small fragments of cartilage oligomeric matrix protein in synovial fluid and serum as markers for cartilage degradation. Br J Rheumatol 1997;36:1151–60.
      OpenUrlAbstract/FREE Full Text
    13. ↵
      1. Müller G,
      2. Michel A,
      3. Altenburg E
      . COMP (cartilage oligomeric matrix protein) is synthesized in ligament, tendon, meniscus, and articular cartilage. Connect Tissue Res 1998;39:233–44.
      OpenUrlCrossRefPubMedWeb of Science
    14. ↵
      1. Rosenberg K,
      2. Olsson H,
      3. Mörgelin M,
      4. et al
      . Cartilage oligomeric matrix protein shows high affinity zinc-dependent interaction with triple helical collagen. J Biol Chem 1998;273:20397–403.
      OpenUrlAbstract/FREE Full Text
    15. ↵
      1. Thur J,
      2. Rosenberg K,
      3. Nitsche DP,
      4. et al
      . Mutations in cartilage oligomeric matrix protein causing pseudoachondroplasia and multiple epiphyseal dysplasia affect binding of calcium and collagen I, II, and IX. J Biol Chem 2001;276:6083–92.
      OpenUrlAbstract/FREE Full Text
    16. ↵
      1. Song HR,
      2. Lee KS,
      3. Li QW,
      4. et al
      . Identification of cartilage oligomeric matrix protein (COMP) gene mutations in patients with pseudoachondroplasia and multiple epiphyseal dysplasia. J Hum Genet 2003;48:222–5.
      OpenUrlCrossRefPubMedWeb of Science
    17. ↵
      1. Lohmander LS,
      2. Saxne T,
      3. Heinegård DK
      . Release of cartilage oligomeric matrix protein (COMP) into joint fluid after knee injury and in osteoarthritis. Ann Rheum Dis 1994;53:8–13.
      OpenUrlAbstract/FREE Full Text
    18. ↵
      1. Clark AG,
      2. Jordan JM,
      3. Vilim V,
      4. et al
      . Serum cartilage oligomeric matrix protein reflects osteoarthritis presence and severity: the Johnston County Osteoarthritis Project. Arthritis Rheum 1999;42:2356–64.
      OpenUrlCrossRefPubMedWeb of Science
    19. ↵
      1. Garnero P,
      2. Piperno M,
      3. Gineyts E,
      4. et al
      . Cross sectional evaluation of biochemical markers of bone, cartilage, and synovial tissue metabolism in patients with knee osteoarthritis: relations with disease activity and joint damage. Ann Rheum Dis 2001;60:619–26.
      OpenUrlAbstract/FREE Full Text
    20. ↵
      1. Sharif M,
      2. Kirwan JR,
      3. Elson CJ,
      4. et al
      . Suggestion of nonlinear or phasic progression of knee osteoarthritis based on measurements of serum cartilage oligomeric matrix protein levels over five years. Arthritis Rheum 2004;50:2479–88.
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      1. Vilim V,
      2. Olejarova M,
      3. Machacek S,
      4. et al
      . Serum levels of cartilage oligomeric matrix protein correlate with radiographic progression of knee osteoarthritis. Osteoarthritis Cartilage 2002;10:707–13.
      OpenUrlCrossRefPubMedWeb of Science
    22. ↵
      1. Sharif M,
      2. Saxne T,
      3. Shepstone L,
      4. et al
      . Relationship between serum cartilage oligomeric matrix protein levels and disease progression in osteoarthritis of the knee joint. Br J Rheumatol 1995;34:306–10.
      OpenUrlAbstract/FREE Full Text
    23. ↵
      1. Wluka AE,
      2. Stuckey S,
      3. Snaddon J,
      4. et al
      . The determinants of change in tibial cartilage volume in osteoarthritic knees. Arthritis Rheum 2002;46:2065–72.
      OpenUrlCrossRefPubMedWeb of Science
    24. ↵
      1. Bellamy N,
      2. Boers M,
      3. Felson D,
      4. et al
      . Health status instruments/utilities. J Rheumatol 1995;22:1203–7.
      OpenUrlPubMedWeb of Science
    25. ↵
      1. Wluka AE,
      2. Davis SR,
      3. Bailey M,
      4. et al
      . Users of oestrogen replacement therapy have more knee cartilage than non-users. Ann Rheum Dis 2001;60:332–6.
      OpenUrlAbstract/FREE Full Text
    26. ↵
      1. Wluka AE,
      2. Wolfe F,
      3. Stuckey SL,
      4. et al
      . How does tibial cartilage volume relate to symptoms in subjects with knee osteoarthritis? ARD 2003;63:264–8.
      OpenUrl
    27. ↵
      1. Fernandes FA,
      2. Pucinelli ML,
      3. da Silva NP,
      4. et al
      . Serum cartilage oligomeric matrix protein (COMP) levels in knee osteoarthritis in a Brazilian population: clinical and radiological correlation. Scand J Rheumatol 2007;36:211–15.
      OpenUrlCrossRefPubMedWeb of Science
    28. ↵
      1. Kelman A,
      2. Lui L,
      3. Yao W,
      4. et al
      . Association of higher levels of serum cartilage oligomeric matrix protein and N-telopeptide crosslinks with the development of radiographic hip osteoarthritis in elderly women. Arthritis Rheum 2006;54:236–43.
      OpenUrlCrossRefPubMedWeb of Science
    29. ↵
      1. Saxne T,
      2. Heinegård D
      . Cartilage oligomeric matrix protein: a novel marker of cartilage turnover detectable in synovial fluid and blood. Br J Rheumatol 1992;31:583–91.
      OpenUrlAbstract/FREE Full Text
    30. ↵
      1. Petersson IF,
      2. Boegård T,
      3. Svensson B,
      4. et al
      . Changes in cartilage and bone metabolism identified by serum markers in early osteoarthritis of the knee joint. Br J Rheumatol 1998;37:46–50.
      OpenUrlAbstract/FREE Full Text
    31. ↵
      1. Bruyere O,
      2. Collette J,
      3. Kothari M,
      4. et al
      . Osteoarthritis, magnetic resonance imaging, and biochemical markers: a one year prospective study. Ann Rheum Dis 2006;65:1050–4.
      OpenUrlAbstract/FREE Full Text
    32. ↵
      1. Salminen H,
      2. Perälä M,
      3. Lorenzo P,
      4. et al
      . Up-regulation of cartilage oligomeric matrix protein at the onset of articular cartilage degeneration in a transgenic mouse model of osteoarthritis. Arthritis Rheum 2000;43:1742–8.
      OpenUrlCrossRefPubMedWeb of Science
    33. ↵
      1. Koelling S,
      2. Clauditz TS,
      3. Kaste M,
      4. et al
      . Cartilage oligomeric matrix protein is involved in human limb development and in the pathogenesis of osteoarthritis. Arthritis Res Ther 2006;8:R56.
      OpenUrlCrossRefPubMed
    34. ↵
      1. Aigner T,
      2. Zhu Y,
      3. Chansky HH,
      4. et al
      . Reexpression of type IIA procollagen by adult articular chondrocytes in osteoarthritic cartilage. Arthritis Rheum 1999;42:1443–50.
      OpenUrlCrossRefPubMedWeb of Science
    35. ↵
      1. Anderson D,
      2. Phillips BJ,
      3. Yu TW,
      4. et al
      . The effects of vitamin C supplementation on biomarkers of oxygen radical generated damage in human volunteers with “low” or “high” cholesterol levels. Environ Mol Mutagen 1997;30:161–74.
      OpenUrlCrossRefPubMedWeb of Science
    36. ↵
      1. Akhter M,
      2. Iwasaki M,
      3. Yamaji T,
      4. et al
      . Dietary isoflavone and the risk of colorectal adenoma: a case-control study in Japan. Br J Cancer 2009;100:1812–16.
      OpenUrlCrossRefPubMedWeb of Science
    37. ↵
      1. Lim E,
      2. Cornelissen J,
      3. Routledge T,
      4. et al
      . Biological efficacy of low versus medium dose aspirin after coronary surgery: results from a randomized trial (NCT00262275). BMC Med 2006;4:12.
      OpenUrlCrossRefPubMed
    38. ↵
      1. Rubin CT,
      2. Lanyon LE
      . Regulation of bone mass by mechanical strain magnitude. Calcif Tissue Int 1985;37:411–17.
      OpenUrlCrossRefPubMedWeb of Science
    39. ↵
      1. Mechanic GL,
      2. Young DR,
      3. Banes AJ,
      4. et al
      . Nonmineralized and mineralized bone collagen in bone of immobilized monkeys. Calcif Tissue Int 1986;39:63–8.
      OpenUrlPubMedWeb of Science
    40. ↵
      1. Pead MJ,
      2. Skerry TM,
      3. Lanyon LE
      . Direct transformation from quiescence to bone formation in the adult periosteum following a single brief period of bone loading. J Bone Miner Res 1988;3:647–56.
      OpenUrlPubMedWeb of Science

    Footnotes

    • Funding This work was supported by NHMRC project grant 980914. PAB is the recipient of an Australian postgraduate association scholarship. AEW is the recipient of an NHMRC career development award (545876).

    • Competing interests None.

    • Patient consent Obtained.

    • Ethics approval This study was conducted with the approval of the Alfred and Caulfield Hospitals in Melbourne, Australia.

    • Provenance and peer review Not commissioned; externally peer reviewed.