Osteocyte-dependent mechanisms of bone cartilage crosstalk in osteoarthritis

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.

Grant Number: 1R21AR083065-01
NIH Institute/Center: NIH
Principal Investigator: Ayse Serra Akbas Kaya