Mathematical modelling of hair follicle cycles to test treatment for alopecia
2017
Florida State University, Tallahassee, USA
Alopecia areata (AA) is one of the most common autoimmune diseases and causes highly characteristic patterns of hair loss. A key feature of AA is that it disrupts the natural, constantly repeating cycle of hair follicles (HFs). Like so many other autoimmune diseases it shows a dynamic, chronic course of clinical disease relapses and remissions over the lifetime of patients. In the present study, the researchers aimed to overcome the limitations of in vitro models, which are very limited in time, and generate a computational and systems biology tool that could be if used for drug design purposes. The mathematical model incorporates HFs cycling and illustrates how the growth phase is interrupted by a dynamic interaction of autoreactive immune cells. The model illustrates different states and transitions from one state to another. The model allows the testing of how different processes, such as proliferation, apoptosis and input from stem cells, impact the growth of HFs in healthy versus AA individuals. In conclusion, the described model may help in evaluating the effectiveness of existing treatments and identifying new potential therapeutic targets.
Analysing the dynamics of a model for alopecia areata as an autoimmune disorder of hair follicle cycling
Atanaska Dobreva
Added on: 10-27-2021
[1] https://academic.oup.com/imammb/article/35/3/387/4071274[2] https://data.jrc.ec.europa.eu/dataset/700397b2-edd7-4ed6-86f7-fc1b164ed432
