Identifying Translational Measures of Osteoarthritic Pain Between Preclinical Models and Patients

About This Grant

Project Summary Osteoarthritis (OA) is a chronic, progressive condition that affects over 32 million adults in the United States. Despite its widespread impact, preclinical research has struggled to develop effective treatments. A major obstacle is the knowledge and technology gap in OA research, where preclinical studies focus on understanding disease mechanisms, while clinical treatments primarily target pain relief. Although recent preclinical research has started to include pain assessments, these methods are still underdeveloped compared to those used in human patients. Historically, OA was thought to be caused by cartilage degradation due to wear and tear. However, it is now understood to be a more complex disease involving inflammatory and metabolic factors. Recent studies show that OA pain does not always correlate with joint damage, and pain severity is not necessarily linked to the degree of structural damage. This disconnect highlights the need for a unified approach that addresses both pain and disease progression. While clinicians focus on pain management, preclinical studies tend to emphasize cellular mechanisms and structural changes. Both perspectives are essential for developing comprehensive treatment strategies. To bridge this gap, researchers have begun incorporating pain as a key metric in preclinical studies, especially in animal models; however, measuring pain in animals is challenging. Human pain is commonly assessed through standardized questionnaires such as KOOS and WOMAC, while pain in animal models is inferred from behavioral changes, such as alterations in movement or weight-bearing. OA manifests in a variety of phenotypes in humans, making it difficult to replicate in animal models. The pain associated with OA is multifaceted, influenced by biological, psychological, and social factors. Current preclinical models utilize both stimulus-evoked and non-stimulus-evoked methods to assess pain in rodents. Non-stimulus- evoked methods, such as gait analysis and weight-bearing assessments, are gaining popularity due to their closer alignment with clinical pain experiences. Despite significant physiological differences between rodents and humans, such as differences in gait and anatomy, rodent models remain crucial for studying OA pain. However, to enhance the relevance of these models to human conditions, pain assessment techniques in rodents must be further developed. Therefore, the objective of this proposal is to identify and validate translatable pain metrics that can be used in both preclinical models and human patients. We propose to assess pain-like behaviors in rodents and humans using various methodologies, including gait analysis, quantitative sensory testing, and activity monitoring. By identifying reliable, translatable pain measures, we aim to improve the translational relevance of preclinical research and ultimately enhance clinical outcomes for OA patients.