Clinical significance of bone changes in osteoarthritis

Sections of Clinical Epidemiology Research and Training Unit, and Rheumatology, Department of Medicine, Boston University School of Medicine, 650 Albany Street, Suite X200, Clin Epi Unit, Boston, MA 02118, USA.
Therapeutic advances in musculoskeletal disease 08/2012; 4(4):259-67. DOI: 10.1177/1759720X12437354
Source: PubMed


Osteoarthritis (OA), the most common form of arthritis, is now understood to involve all joint tissues, with active anabolic and catabolic processes. Knee OA in particular is considered to be a largely mechanically-driven disease. As bone adapts to loads by remodeling to meet its mechanical demands, bone alterations likely play an important role in OA development. Subchondral bone changes in bone turnover, mineralization, and volume result in altered apparent and material density of bone that may adversely affect the joint's biomechanical environment. Subchondral bone alterations such as bone marrow lesions (BMLs) and subchondral bone attrition (SBA) both tend to occur more frequently in the more loaded knee compartments, and are associated with cartilage loss in the same region. Recently, MRI-based 3D bone shape has been shown to track concurrently with and predict OA onset.The contributions of structural abnormalities to the clinical manifestations of knee OA are becoming better understood as well. While a structure-symptom discordance in knee OA is thought to exist, such observations do not take into account all potential factors that can contribute to between-person differences in the pain experience. Using novel methodology, pain fluctuation has been associated with changes in BMLs, synovitis and effusion. SBA has also been associated with knee pain, but the relationship of osteophytes to pain has been conflicting.Understanding the pathophysiologic sequences and consequences of OA pathology will guide rational therapeutic targeting. Importantly, rational treatment targets require understanding what structures contribute to pain as pain is the reason patients seek medical care.

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    • "One possible objective measure could come from radiographic analyses. Numerous studies however have reported that radiographic measures which are the recommended validated technique to assess OA structural anomalies, correlate poorly at the individual level with patient symptoms [6] [7] [8]. Such measures are also made in static conditions during which the principle deficits related to movement may not appear. "
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    ABSTRACT: The clinical evaluation of patients in hip osteoarthritis is often done using patient questionnaires. While this provides important information it is also necessary to continue developing objective measures. In this investigation we further the studies concerning the use of 3D gait analysis to attain this goal. The gait analysis was associated with machine learning methods in order to provide a direct measure of patient control gait discrimination. The applied machine learning method was the support vector machine (SVM). Applying the SVM on all the measured kinematic trajectories, we were able to classify individual patient and control gait cycles with a mean success rate of 88%. With the use of an ROC curve to establish the threshold number of cycles necessary for a subject to be identified as a patient, this translated to a capacity of higher than 90% for discriminating patient and control subjects. We then went on to determine the importance of each trajectory. By ranking the capacity of each trajectory for this discrimination, we provided a guide on their order of importance in evaluating patient severity. In order to be clinically relevant, any measure of patient deficit must be compared with clinically validated scores of functional disability. In the case of hip osteoarthritis (OA), the WOMAC scores are currently one of the most widely accepted clinical scores for quantifying OA severity. The kinematic trajectories that provided the best patient-control discrimination with the SVM were found to correlate well but imperfectly with the WOMAC scores, hence indicating the presence of complementary information in the two.
    Computers in Biology and Medicine 12/2014; 55. DOI:10.1016/j.compbiomed.2014.09.012 · 1.24 Impact Factor
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    ABSTRACT: Previous reports indicate a potential role for calcitonin in the treatment of osteoarthritis (OA). To evaluate this potential therapeutic role, we investigated the effect of calcitonin pretreatment on the activation of mitogen-activated protein kinase (MAPK) signaling and the expression of MMP-13 in IL-1β-induced chondrocytes, and further assessed its protective effect in a rat model of anterior cruciate ligament transection (ACLT), using sham-operated and saline-treated controls. Using western blotting in vitro, we found that calcitonin pretreatment inhibited the IL-1β-induced phosphorylation of p38 and ERK1/2 and reduced the expression of MMP-13 protein. For the in vivo experiment, 30 male rats were randomly divided into three groups of 10, subjected to bilateral ACLT or sham surgery, and then treated for 12 weeks with subcutaneous injections of calcitonin or normal saline. Histological observations showed that calcitonin treatment reduced the severity of the cartilage lesions stemming from the ACLT surgery and provided a lower Mankin score as compared with that determined for rats in the saline-treated ACLT group. Immunohistochemical staining revealed that calcitonin treatment increased type II collagen expression, and decreased MMP-3 and ADAMTS-4 expression as compared with the saline-treated group. Subchondral bone analysis indicated that calcitonin treatment inhibited the reduction in bone mineral density (BMD) observed in the saline-treated ACLT group and reduced the ACLT-induced destruction to the subchondral trabecular microstructure. Our data demonstrate that calcitonin induces its protective effects by reducing the chondrocyte response to inflammatory stimuli, cartilage extracellular matrix degradation and subchondral trabecular microstructure damages brought on by OA.
    Connective tissue research 01/2013; 54(2). DOI:10.3109/03008207.2012.760549 · 1.61 Impact Factor
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