Joint Shape Change as a Target for the Understanding, Diagnosis, Prevention, and Treatment of Osteoarthritis
Abstract
This project in the Topic Area of Arthritis addresses several fiscal year 2022 Peer Reviewed Medical Research Program Strategic Goals: * Foundational Studies: Mechanisms underlying the pathobiology of musculoskeletal disorders * Treatment: Testing novel intra-articular treatments for joint injuries; halt/slow disease progression * Prevention: Improved care at point of injury to prevent musculoskeletal disorder onset * Diagnosis: Develop novel tools/technologies for early and precision diagnosis of musculoskeletal disorders Osteoarthritis (OA) is a major unmet clinical need. Not only is OA the single most common cause of disability in older adults, but it also disproportionately impacts Veterans and Service Members. OA rates in the military are 26% higher than civilians in the 20-24 year age group and twice as high in those over 40. OA profoundly affects skeletal and systemic health. The painful arthritic degeneration of the joint drives opioid use and limits physical activity, which contributes to poor metabolic, cardiovascular, and mental health. Unfortunately, OA is irreversible and total joint replacement is often the only treatment option, even though implant lifespans of 15-20 years are insufficient for many, especially those with military service in whom OA strikes earlier and faster than in civilians. Disease-modifying OA drugs (DMOAD) do not exist, despite intense effort in academia and industry. One obstacle is the inability to diagnose individuals at high risk for OA during early stages of the disease when therapeutic interventions could prevent OA progression. In addition, convergent features of end-stage OA obscure the heterogeneous underlying disease processes, ranging from local joint injury to systemic consequences of aging. Given this heterogeneity, diagnostics or therapies that benefit one group of OA patients may have no effect or harm another. Deep learning analysis of MRI images can distinguish among several OA subtypes, including some related to the shape of the bone in the joint, that are detectable at early stages when therapeutic interventions could prove effective. However, the biological mechanisms corresponding to these subtypes remain unclear. The objective of this project is to improve diagnosis and treatment of OA by uncovering mechanisms responsible for clinically relevant changes in joint shape that are detectable by MRI in early-stage OA. The opportunity of this project lies in the unique convergence of interest on joint shape change as a pivotal determinant of OA. Four diverse lines of inquiry, each led by independent investigators on this project, arrive at this conclusion through unbiased analyses of human imaging and genetic data, and through careful laboratory and clinical observation. Pedoia identified joint shape change as a powerful predictor of OA while using deep learning algorithms to identify diagnostics of early-stage joint disease in clinical MRI scans. While searching for genetic biomarkers of OA, Evans uncovered genes associated with joint shape change as an important biomarker of disease. In the search for cellular and molecular mechanisms of OA, Alliston and Dang found that functional deficits in an unexpected bone cell type, osteocytes, caused cartilage degeneration that was accompanied by changes in joint shape. In clinical trials for the intra-articular treatment of OA, Rosen found that the compound TPX-100 reduced pain, OA progression, and joint shape change. The focus on joint shape is supported by recent studies on evolutionary and genetic mechanisms controlling joint shape and its role in OA. Thus, this proposal pursues the exciting and unexpected new intersection of four research programs on joint shape, which give rise to the proposed hypothesis and aims. Hypothesis: MRI and genetic markers of subchondral bone shape can identify pre-symptomatic individuals at high risk of OA, and agents targeting subchondral bone osteoc
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310875
Entities
People
- Tamara Alliston
Organizations
- United States Army
- University of California, San Francisco