Osteocyte-dependent mechanisms of bone cartilage crosstalk in osteoarthritis

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SUMMARY Cartilage and subchondral bone cooperate to support healthy joint function, and damage to either contributes to osteoarthritis and pain. Nonetheless, the mechanisms by which this cooperation between cartilage and bone occurs remain unclear. Preliminary and published data support the diagnostic and clinical importance of subchondral bone shape in osteoarthritis (OA) progression and pain. Bone shape features, identified by deep learning algorithms, are among the strongest predictive biomarkers for OA. However, a major gap in understanding remains identification of the cellar and molecular mechanisms controlling joint shape. Defining these mechanisms could reveal preventative or therapeutic strategies to protect joints from OA. This team described a new and causal role for osteocytes in OA, such that loss of subchondral bone osteocyte function causes cartilage degeneration and joint shape change. Therefore, with expertise in osteocyte biology, deep learning, and statistical genetics, this team takes an innovative, multi-dimensional approach to identify these mechanisms, as well as genetic and imaging biomarkers that can be used to diagnose early-stage OA when the disease can still be therapeutically modified. This project will test the hypothesis that MRI and genetic markers of joint shape can identify individuals at high risk of OA, and that agents targeting osteocytes can prevent joint shape changes to mitigate OA. Aim 1 will extract genetic factors associated with joint shape traits that predict OA progression and joint pain in the human Osteoarthritis Initiative (OAI) cohort. The function of these genetic factors, including a candidate osteocyte-derived factor that has therapeutic potential in clinical studies, will be examined in Aim 2. This project will impact the identification of genetic correlates to imaging traits that predict clinically relevant OA outcomes in early OA, suggest biological mechanisms driving joint shape change, and highlight these mechanisms as potential targets for OA diagnostics and therapies. Therefore, successful completion of this project could fill a major clinical gap by developing imaging and genetic biomarkers and therapies that can precisely identify and treat subgroups of people at high risk of OA due to joint shape change early enough to prevent severe joint disease.