Computational Modelling of Immune Interaction and Epidermal Homeostasis in Psoriasis

Psoriasis is an incurable chronic inflammatory skin disease characterised by immune cytokine-stimulated epidermal hyperproliferation. This results in the skin becoming red with scaly plaques that can appear anywhere on the body, decreasing the quality of life for patients. Previous modelling studies of psoriasis have been limited to 2D models and lacked cell-cell interactions. We have developed a 3D agent-based model of epidermal cell dynamics to gain insights into how immune cytokine stimuli induces hyperproliferation in psoriasis to better understand disease formation and structural changes. Three main keratinocytes, stem, transit-amplifying (TA), differentiated and T cells, are modelled with proliferation and division governed by various nutrients and immune cytokines. Each cell has a set of attributes (growth rate, division probability, position, etc) whose values are governed by processes such as monod-based cellular growth model, probability-based division based on calcium and cytokine concentration and various forces to form the epidermal layers. The model has 2 steady states, healthy (non-lesional) and psoriatic (lesional) skin. Transition from healthy to psoriatic state is triggered by a temporary cytokine stimulus which causes hyperproliferation to occur, a hallmark of psoriasis. This results in the deepening of rete ridges and thickening of the epidermal structure. Model outputs has been validated against population ratios of stem, TA, differentiated, and T cells, cell cycle and turnover times in vivo. The model simulates the structural properties of epidermis, including layer stratification, formation of wave-like rete ridges, change in epidermal height and length of rete ridges from healthy to psoriasis. This has provided some insights on the complex spatio-temporal changes when transitioning between the 2 steady states and how a shot of temporary cytokine stimulus can induce different severity of psoriasis and alters proliferation between healthy and psoriatic skin in line with known literature. This provides the basis to study different cytokine simulation variations of psoriasis development and tracking of cell proliferation in the lab. It also provides a baseline to model the effects of psoriasis treatments such as narrowband-ultraviolet B (NB-UVB) or biologics and predict potential treatment outcomes for patients.