A novel integrative multi-scale framework of inflammation and mechanical loading in knee osteoarthritis.

Obesity is a well-known prominent risk factor for knee osteoarthritis (OA). The onset and development of knee OA are affected by multifactorial interplays, involving the degeneration of articular cartilage. Emerging evidence shows the negative effects of obesity on cartilage degeneration across multi-scales. Specifically, obesity can stimulate inflammation and alter the biomechanical responses of the joint. However, the pathology of obesity-associated knee OA is still poorly understood. The aim of this study was to develop a multi-scale modelling framework to simulate and evaluate the mechanobiological roles of obesity in the degenerative process of cartilage. This framework integrated the inflammatory and biomechanical effects of obesity on cartilage degeneration in knee OA. A validated finite element model of a subject-specific knee joint was coupled with a mathematical model of adipokine-mediated OA inflammation. In the algorithm, excess stress resulted in mechanical damage that activated obesity-related inflammatory responses. The degeneration of cartilage was driven by both mechanical damage and body mass index (BMI). Parameter sensitivity analysis showed a good adaptivity of this framework to simulate cartilage degeneration. In addition, BMI and the stress threshold were sensitive to the degenerative process. Results indicate that a higher BMI level could not only increase the degeneration level but also lead to a larger degenerative volume of cartilage. Due to the elevated baseline of inflammation in the obese joint, the relative contributions of inflammation and mechanical damage might vary as cartilage degeneration progressed. This computational framework combines for the first time obesity-associated inflammation and mechanical loading in knee OA. It could be extended by specifying different degenerative pathways in cartilage degeneration. With further calibration, the framework has the potential to empower the identification of different phenotypes and endotypes of OA.