Objective To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. Methods This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein–protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network. Results Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores. Conclusion Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response.

In hand OA the quantitative JSW measurement is a valid method to measure joint space and shows a good relation with clinical features.

ObjectiveOsteoarthritis (OA) has a strong genetic component but the success of previous genome-wide association studies (GWAS) has been restricted due to insufficient sample sizes and phenotype heterogeneity. Our aim was to examine the effect of clinically relevant endophenotyping according to site of maximal joint space narrowing (maxJSN) and bone remodelling response on GWAS signal detection in hip OA.MethodsA stratified GWAS meta-analysis was conducted in 2118 radiographically defined hip OA cases and 6500 population-based controls. Signals were followed up by analysing differential expression of proximal genes for bone remodelling endophenotypes in 33 pairs of macroscopically intact and OA-affected cartilage.ResultsWe report suggestive evidence (p<5×10−6) of association at 6 variants with OA endophenotypes that would have been missed by using presence of hip OA as the disease end point. For example, in the analysis of hip OA cases with superior maxJSN versus cases with non-superior maxJSN we detected association with a variant in the LRCH1 gene (rs754106, p=1.49×10−7, OR (95% CIs) 0.70 (0.61 to 0.80)). In the comparison of hypertrophic with non-hypertrophic OA the most significant variant was located between STT3B and GADL1 (rs6766414, p=3.13×10−6, OR (95% CIs) 1.45 (1.24 to 1.69)). Both of these associations were fully attenuated in non-stratified analyses of all hip OA cases versus population controls (p>0.05). STT3B was significantly upregulated in OA-affected versus intact cartilage, particularly in the analysis of hypertrophic and normotrophic compared with atrophic bone remodelling pattern (p=4.2×10−4).ConclusionsOur findings demonstrate that stratification of OA cases into more homogeneous endophenotypes can identify genes of potential functional importance otherwise obscured by disease heterogeneity.

ObjectiveTo validate a newly developed quantification method that automatically detects and quantifies the joint space width (JSW) in hand radiographs. Repeatability, accuracy and sensitivity to changes in JSW were determined. The influence of joint location and joint shape on the measurements was tested.MethodsA mechanical micrometer set-up was developed to define and adjust the true JSW in an acrylic phantom joint and in human cadaver-derived phalangeal joints. Radiographic measurements of the JSW were compared to the true JSW. Repeatability, systematic error (accuracy) and sensitivity (defined as the smallest detectable difference (SDD)) were determined. The influence of joint position on the JSW measurement was assessed by varying the location of the acrylic phantom on the X-ray detector with respect to the X-ray beam and the influence of joint shape was determined by using morphologically different human cadaver joints.ResultsThe mean systematic error was 0.052 mm in the phantom joint and 0.210 mm in the cadaver experiment. In the phantom experiments, the repeatability was high (SDD = 0.028 mm), but differed slightly between joint locations (p = 0.046), and a change in JSW of 0.037 mm could be detected. Dependent of the joint shape in the cadaver hand, a change in JSW between 0.018 and 0.047 mm could be detected.ConclusionsThe automatic quantification method is sensitive to small changes in JSW. Considering the published data of JSW decline in the normal and osteoarthritic population, the first signs of OA progression with this method can be detected within 1 or 2 years.

Localized knee OA developed from risk factors identified from the findings of MR imaging performed a decade ago in patients with subacute knee symptoms and did not depend on the surgical treatment of those findings.