Virginia Byers Kraus

Relapsing polychondritis (RP) is a rare and severe disease which may lead to destruction of elastic cartilages. Until now, no reliable biomarker of disease activity in RP has been available. This study was designed to measure serum levels of cartilage biomarkers during both active and inactive phases of the disease. Serum levels of cartilage oligomeric matrix protein (COMP), chondroitin sulfate 846 epitope (CS846) of proteoglycan aggrecan and collagen type II collagenase cleavage neoepitope (C2C) were measured retrospectively in 21 subjects with RP. The Wilcoxon matched-pairs signed-rank test was used for statistical comparisons of biomarker levels in active and inactive phases of RP. Only the serum level of COMP was significantly increased during disease flares. Steroids did not alter the serum cartilage-related biomarker levels. However, during the active phase, C2C levels were significantly higher in steroid treated patients compared with non-steroid treated patients. This study suggests that serum COMP level may be useful for monitoring disease activity of RP. Further prospective studies are required to confirm this result.

Osteoarthritis (OA) is a debilitating chronic multijoint disease of global proportions. OA presence and severity is usually documented by x-ray imaging but whole body imaging is impractical due to radiation exposure, time and cost. Systemic (serum or urine) biomarkers offer a potential alternative method of quantifying total body burden of disease but no OA-related biomarker has ever been stringently qualified to determine the feasibility of this approach. The goal of this study was to evaluate the ability of three OA-related biomarkers to predict various forms or subspecies of OA and total body burden of disease. Female participants (461) with clinical hand OA underwent radiography of hands, hips, knees and lumbar spine; x-rays were comprehensively scored for OA features of osteophyte and joint space narrowing. Three OA-related biomarkers, serum hyaluronan (sHA), cartilage oligomeric matrix protein (sCOMP), and urinary C-telopeptide of type II collagen (uCTX2), were measured by ELISA. sHA, sCOMP and uCTX2 correlated positively with total osteophyte burden in models accounting for demographics (age, weight, height): R² = 0.60, R² = 0.47, R² = 0.51 (all p−6); sCOMP correlated negatively with total joint space narrowing burden: R² = 0.69 (p−6). Biomarkers and demographics predicted 35–38% of variance in total burden of OA (total joint space narrowing or osteophyte). Joint size did not determine the contribution to the systemic biomarker concentration. Biomarker correlation with disease in the lumbar spine resembled that in the rest of the skeleton. We have suspected that the correlation of systemic biomarkers with disease has been hampered by the inability to fully phenotype the burden of OA in a patient. These results confirm the hypothesis, revealed upon adequate patient phenotyping, that systemic joint tissue concentrations of several biomarkers can be quantitative indicators of specific subspecies of OA and of total body burden of disease.

Objective The genetic contributions to the multifactorial disorder osteoarthritis (OA) have been increasingly recognized. The goal of the current study was to use OA‐related biomarkers of severity and disease burden as quantitative traits to identify genetic susceptibility loci for OA. Methods In a large multigenerational extended family (n = 350), we measured 5 OA‐related biomarkers: hyaluronan (HA), cartilage oligomeric matrix protein (COMP), N‐propeptide of type IIA collagen (PIIANP), C‐propeptide of type II procollagen (CPII), and type II collagen neoepitope (C2C). Single‐nucleotide polymorphism markers (n = 6,090) covering the whole genome were genotyped using the Illumina HumanLinkage‐12 BeadChip. Variance components analysis, as implemented in the Sequential Oligogenic Linkage Analysis Routines, was used to estimate heritabilities of the quantitative traits and to calculate 2‐point and multipoint logarithm of odds (LOD) scores using a polygenic model. Results After adjusting for age and sex, we found that 4 of the 5 biomarkers exhibited significant heritability (PIIANP 0.57, HA 0.49, COMP 0.43, C2C 0.30; P ≤ 0.01 for all). Fourteen of the 19 loci that had multipoint LOD scores of >1.5 were near to or overlapped with previously reported OA susceptibility loci. Four of these loci were identified by more than 1 biomarker. The maximum multipoint LOD scores for the heritable quantitative biomarker traits were 4.3 for PIIANP (chromosome 8p23.2), 3.2 for COMP (chromosome 8q11.1), 2.0 for HA (chromosome 6q16.3), and 2.0 for C2C (chromosome 5q31.2). Conclusion Herein, we report the first evidence of genetic susceptibility loci identified by OA‐related biomarkers in an extended family. Our results demonstrate that serum concentrations of PIIANP, HA, COMP, and C2C have substantial heritable components, and using these biomarkers, several genetic loci potentially contributing to the genetic diversity of OA were identified.

Background: Digital infrared thermal imaging is a means of measuring the heat radiated from the skin surface. Our goal was to develop and assess the reproducibility of serial infrared measurements of the knee and to assess the association of knee temperature by region of interest with radiographic severity of knee Osteoarthritis (rOA). Methods: A total of 30 women (15 Cases with symptomatic knee OA and 15 age-matched Controls without knee pain or knee OA) participated in this study. Infrared imaging was performed with a Meditherm Med2000™ Pro infrared camera. The reproducibility of infrared imaging of the knee was evaluated through determination of intraclass correlation coefficients (ICCs) for temperature measurements from two images performed 6 months apart in Controls whose knee status was not expected to change. The average cutaneous temperature for each of five knee regions of interest was extracted using WinTes software. Knee x-rays were scored for severity of rOA based on the global Kellgren-Lawrence grading scale. Results: The knee infrared thermal imaging procedure used here demonstrated long-term reproducibility with high ICCs (0.50–0.72 for the various regions of interest) in Controls. Cutaneous temperature of the patella (knee cap) yielded a significant correlation with severity of knee rOA (R = 0.594, P = 0.02). Conclusion: The skin temperature of the patellar region correlated with x-ray severity of knee OA. This method of infrared knee imaging is reliable and as an objective measure of a sign of inflammation, temperature, indicates an interrelationship of inflammation and structural knee rOA damage.

Objective: To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3‐year period.Methods: A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius.Results: Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52–0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79).Conclusion: We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.

Objective: The information content of knee bone scintigraphy was evaluated, including pattern, localisation and intensity of retention relative to radiographic features of knee osteoarthritis, knee alignment and knee symptoms. Methods: A total of 308 knees (159 subjects) with symptomatic and radiographic knee osteoarthritis of at least one knee was assessed by late-phase ^99mTechnetium methylene disphosphonate bone scintigraph, fixed-flexion knee radiograph, full limb radiograph for knee alignment and for self-reported knee symptom severity. Generalised linear models were used to control for within-subject correlation of knee data. Results: The compartmental localisation (medial vs lateral) and intensity of knee bone scan retention were associated with the pattern (varus vs valgus) (pConclusion: To the authors’ knowledge, this is the first study describing a relationship between knee malalignment, joint symptom severity and compartment-specific abnormalities by bone scintigraphy. This work demonstrates that bone scintigraphy is a sensitive and quantitative indicator of symptomatic knee osteoarthritis. Used selectively, bone scintigraphy is a dynamic imaging modality that holds great promise as a clinical trial screening tool and outcome measure.