A computational model for collective chondrocyte behaviour in osteoarthritis, in patient-specific biochemical micro-environments

Abstract

Osteoarthritis (OA) is a common condition characterised by the degradation of the articular cartilage that leads to stiff and painful joints. OA is related with the dysregulation of the cartilage chondrocyte’s activity, the latter becoming much more catabolic under OA conditions. Both mechanical and biochemical signals are involved in this dysregulation and need to be considered for the understanding of the condition and its treatment. On the one hand, cartilage tissue mechanics and multi-physics have been described through numerical finite element models (FEM) and simulations, pointing out clear relationships among cartilage composition, mechanical properties and OA. On the other hand, network-based modelling (NBM) has proven to be useful to simulate semi-quantitatively the biological activity of the chondrocyte, and there is abundant information about the transduction of mechanical signals by chondrocytes, at the molecular and cell scales. However, the knowledge gap between single-cell regulation and intercellular interactions in a representative tissue volume makes it difficult to readily interpolate tissue mechanics and chondrocyte mechano-transduction in OA, especially when the cell biochemical environment needs to be considered. Then, a method to merge both mechanic and biochemical signals is needed, where cell-cell interactions shall intervene. To address such a need, we hereby hypothesize that it is possible to simulate interacting network effects through agent-based modelling, to grasp relevant dynamics of cell and tissue regulation in OA. Whereas chemo- and mechano-regulation network models could be coupled at the cell and subcellular levels, the agents will simulate cell paracrine activity and the emergence of collective chondrocyte behaviour at the tissue level quantitatively, enabling to merge quantitative mechanics of FEM and semi-quantitative biochemistry from NBM. Both literature data and in vitro and ex vivo measurements will be used to calibrate and duly assess the different model components and the interactions thereof.