Understanding the Roles of Synovitis, Knee-Adjacent Obesity and Sarcopenia in Pain Phenotypes and Structural Progression of Knee Osteoarthritis - An Analysis of the Entire Osteoarthritis Initiative - Project Summary Osteoarthritis (OA) is a highly prevalent joint disease affecting over 500 million individuals globally, of whom more than 260 million have knee OA. Obesity, inflammation, and sarcopenia are established modifiable risk factors for OA, and OA and other obesity-related diseases place an enormous physical and financial burden on the US healthcare system. Given our aging population and an associated increase in obesity, these numbers are expected to increase, leading to even higher rates of disability and healthcare costs. Obesity has become a US “epidemic,” and projections have suggested that 86.3% of adults in the United States will be overweight or obese by 2030. Our recent work has suggested a complex interrelationship between the modifiable risk factors obesity, sarcopenia, and inflammation, with weight loss increasing sarcopenia and increased inflammation being associated with obesity. There is also a knowledge gap on how these risk factors impact pain and structural outcomes, which is crucial for managing OA and influencing quality of life and mobility. Moreover, there is limited knowledge of how concurrent factors such as weight change, co-morbidities, mental health, lifestyle (such as diet), and physical activity mediate the progression of osteoarthritis. The innovation of this proposal is centered on three key features: (i) modifiable risk factors that can be measured fully automatically on MRI studies with machine learning algorithms, (ii) impact of mediators on OA outcomes including novel pain phenotype and structural outcomes, and (iii) the development of clinically applicable machine learning models to predict pain and structural outcomes. Three Specific Aims are proposed: In Specific Aim 1, we will investigate the associations of modifiable risk factors synovitis, knee-adjacent obesity, and muscle volume and fat infiltration with novel pain phenotypes and knee structural disease severity at baseline. In Specific Aim 2, we will analyze how longitudinal changes in synovitis, knee-adjacent obesity, and muscle impact outcomes of knee pain and structural changes. We will also conduct a mediation/pathway analysis to determine how this relationship is affected by weight change, co- morbidities, lifestyle factors, and physical activity. We believe that these mechanisms/mediators being investigated are related to pain phenotypes and structural outcomes and that they may provide avenues to prevent the progression of OA. In Specific Aim 3, we will develop a clinically applicable prediction model using machine learning to determine which combination of modifiable biomarkers, demographic, and clinical features best predicts pain and structural outcomes in individuals with risk factors for or mild to moderate OA. The overall goal of this proposal is that by determining biological mechanisms and pathways responsible for OA-related outcomes such as pain (specific pain phenotypes and overall pain) and structural outcomes (based on radiographs and MRI findings) we will be able to identify potential treatment targets that prevent incidence and progression of knee OA.
