title: Relationship of serum markers of cartilage metabolism to imaging and clinical outcome measures of knee joint structure.
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).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Epidemiology and Preventive Medicine, Monash University Medical School, Alfred Hospital, Prahran, Victoria, Australia.
authors.forename: Patricia A
authors.initials: PA
authors.lastname: Berry
authors.forename: Rose A
authors.initials: RA
authors.lastname: Maciewicz
authors.forename: Anita E
authors.initials: AE
authors.lastname: Wluka
authors.forename: Mark D
authors.initials: MD
authors.lastname: Downey-Jones
authors.forename: Andrew
authors.initials: A
authors.lastname: Forbes
authors.forename: Caroline J
authors.initials: CJ
authors.lastname: Hellawell
authors.forename: Flavia M
authors.initials: FM
authors.lastname: Cicuttini
mesh_terms: D000368:Aged; D019643:Arthroplasty, Replacement; D015415:Biomarkers / Q000097:blood; D002358:Cartilage, Articular / Q000378:metabolism* / Q000473:pathology; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007719:Knee Joint / Q000378:metabolism* / Q000473:pathology; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000175:diagnosis* / Q000473:pathology / Q000601:surgery; D011379:Prognosis
chemical_list: D015415:Biomarkers