A role for subchondral bone changes in the process of osteoarthritis; a micro-CT study of two canine models

BACKGROUND: This study evaluates changes in peri-articular bone in two canine models for osteoarthritis: the groove model and the anterior cruciate ligament transection (ACLT) model. METHODS: Evaluation was performed at 10 and 20 weeks post-surgery and in addition a 3-weeks time point was studied for the groove model. Cartilage was analysed, and architecture of the subchondral plate and trabecular bone of epiphyses was quantified using micro-CT. RESULTS: At 10 and 20 weeks cartilage histology and biochemistry demonstrated characteristic features of osteoarthritis in both models (very mild changes at 3 weeks). The groove model presented osteophytes only at 20 weeks, whereas the ACLT model showed osteophytes already at 10 weeks. Trabecular bone changes in the groove model were small and not consistent. This contrasts the ACLT model in which bone volume fraction was clearly reduced at 10 and 20 weeks (15-20%). However, changes in metaphyseal bone indicate unloading in the ACLT model, not in the groove model. For both models the subchondral plate thickness was strongly reduced (25-40%) and plate porosity was strongly increased (25-85%) at all time points studied. CONCLUSION: These findings show differential regulation of subchondral trabecular bone in the groove and ACLT model, with mild changes in the groove model and more severe changes in the ACLT model. In the ACLT model, part of these changes may be explained by unloading of the treated leg. In contrast, subchondral plate thinning and increased porosity were very consistent in both models, independent of loading conditions, indicating that this thinning is an early response in the osteoarthritis process

Intraarticular location predicts cartilage filling and subchondral bone changes in a chondral defect: A randomized, blind, long-term follow-up trial involving 82 rabbit knees

Open Access - This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the source is credited.Background and purpose: The natural history of, and predictive factors for outcome of cartilage restoration in chondral defects are poorly understood. We investigated the natural history of cartilage filling subchondral bone changes, comparing defects at two locations in the rabbit knee. Animals and methods: In New Zealand rabbits aged 22 weeks, a 4-mm pure chondral defect (ICRS grade 3b) was created in the patella of one knee and in the medial femoral condyle of the other. A stereo microscope was used to optimize the preparation of the defects. The animals were killed 12, 24, and 36 weeks after surgery. Defect filling and the density of subchondral mineralized tissue was estimated using Analysis Pro software on micrographed histological sections. Results: The mean filling of the patellar defects was more than twice that of the medial femoral condylar defects at 24 and 36 weeks of follow-up. There was a statistically significant increase in filling from 24 to 36 weeks after surgery at both locations. The density of subchondral mineralized tissue beneath the defects subsided with time in the patellas, in contrast to the density in the medial femoral condyles, which remained unchanged. Interpretation: The intraarticular location is a predictive factor for spontaneous filling and subchondral bone changes of chondral defects corresponding to ICRS grade 3b. Disregarding location, the spontaneous filling increased with long-term follow-up. This should be considered when evaluating aspects of cartilage restoration

Association of adiposity and mental health functioning across the lifespan:Findings from understanding society (The UK household longitudinal study)

Background: Evidence on the adiposity-mental health associations is mixed, with studies finding positive, negative or no associations, and less is known about how these associations may vary by age. Objective: To examine the association of adiposity -body mass index (BMI), waist circumference (WC) and percentage body fat (BF%)- with mental health functioning across the adult lifespan. Methods: Data from 11,257 participants (aged 18+) of Understanding Society: the UK Household Longitudinal Study (waves 2 and 3, 5/2010-7/2013) were employed. Regressions of mental health functioning, assessed by the Mental Component Summary (MCS-12) and the General Health Questionnaire (GHQ-12), on adiposity measures (continuous or dichotomous indicators) were estimated adjusted for covariates. Polynomial age-adiposity interactions were estimated. Results: Higher adiposity was associated with poorer mental health functioning. This emerged in the 30s, increased up to mid-40s (all central adiposity and obesity-BF% measures) or early 50s (all BMI measures) and then decreased with age. Underlying physical health generally accounted for these associations except for central adiposity, where associations remained statistically significant from the mid-30s to50s. Cardiovascular, followed by arthritis and endocrine, conditions played the greatest role in attenuating the associations under investigation. Conclusions: We found strong age-specific patterns in the adiposity-mental health functioning association that varied across adiposity measures. Underlying physical health had the dominant role in attenuating these associations. Policy makers and health professionals should target increased adiposity, mainly central adiposity, as it is a risk factor for poor mental health functioning in those aged between mid-30s to 50 years

Site-specific analysis of gene expression in early osteoarthritis using the Pond-Nuki model in dogs

BACKGROUND: Osteoarthritis (OA) is a progressive and debilitating disease that often develops from a focal lesion and may take years to clinically manifest to a complete loss of joint structure and function. Currently, there is not a cure for OA, but early diagnosis and initiation of treatment may dramatically improve the prognosis and quality of life for affected individuals. This study was designed to determine the feasibility of analyzing changes in gene expression of articular cartilage using the Pond-Nuki model two weeks after ACL-transection in dogs, and to characterize the changes observed at this time point. METHODS: The ACL of four dogs was completely transected arthroscopically, and the contralateral limb was used as the non-operated control. After two weeks the dogs were euthanatized and tissues harvested from the tibial plateau and femoral condyles of both limbs. Two dogs were used for histologic analysis and Mankin scoring. From the other two dogs the surface of the femoral condyle and tibial plateau were divided into four regions each, and tissues were harvested from each region for biochemical (GAG and HP) and gene expression analysis. Significant changes in gene expression were determined using REST-XL, and Mann-Whitney rank sum test was used to analyze biochemical data. Significance was set at (p < 0.05). RESULTS: Significant differences were not observed between ACL-X and control limbs for Mankin scores or GAG and HP tissue content. Further, damage to the tissue was not observed grossly by India ink staining. However, significant changes in gene expression were observed between ACL-X and control tissues from each region analyzed, and indicate that a unique regional gene expression profile for impending ACL-X induced joint pathology may be identified in future studies. CONCLUSION: The data obtained from this study lend credence to the research approach and model for the characterization of OA, and the identification and validation of future diagnostic modalities. Further, the changes observed in this study may reflect the earliest changes in AC reported during the development of OA, and may signify pathologic changes within a stage of disease that is potentially reversible

Proteomics to predict the response to tumour necrosis factor-α inhibitors in rheumatoid arthritis using a supervised cluster-analysis based protein score

<p><b>Objective</b>: In rheumatoid arthritis (RA), it is of major importance to identify non-responders to tumour necrosis factor-α inhibitors (TNFi) before starting treatment, to prevent a delay in effective treatment. We developed a protein score for the response to TNFi treatment in RA and investigated its predictive value.</p> <p><b>Method</b>: In RA patients eligible for biological treatment included in the BiOCURA registry, 53 inflammatory proteins were measured using xMAP® technology. A supervised cluster analysis method, partial least squares (PLS), was used to select the best combination of proteins. Using logistic regression, a predictive model containing readily available clinical parameters was developed and the potential of this model with and without the protein score to predict European League Against Rheumatism (EULAR) response was assessed using the area under the receiving operating characteristics curve (AUC-ROC) and the net reclassification index (NRI).</p> <p><b>Results</b>: For the development step (n = 65 patient), PLS revealed 12 important proteins: CCL3 (macrophage inflammatory protein, MIP1a), CCL17 (thymus and activation-regulated chemokine), CCL19 (MIP3b), CCL22 (macrophage-derived chemokine), interleukin-4 (IL-4), IL-6, IL-7, IL-15, soluble cluster of differentiation 14 (sCD14), sCD74 (macrophage migration inhibitory factor), soluble IL-1 receptor I, and soluble tumour necrosis factor receptor II. The protein score scarcely improved the AUC-ROC (0.72 to 0.77) and the ability to improve classification and reclassification (NRI = 0.05). In validation (n = 185), the model including protein score did not improve the AUC-ROC (0.71 to 0.67) or the reclassification (NRI = −0.11).</p> <p><b>Conclusion</b>: No proteomic predictors were identified that were more suitable than clinical parameters in distinguishing TNFi non-responders from responders before the start of treatment. As the results of previous studies and this study are disparate, we currently have no proteomic predictors for the response to TNFi.</p