Abstract
A major contribution to the onset and development of autoimmune disease is known to come from infections. An important practical problem is identifying the precise mechanism by which the breakdown of immune tolerance as a result of immune response to infection leads to autoimmunity. In this paper, we develop a mathematical model of immune response to a viral infection, which includes T cells with different activation thresholds, regulatory T cells (Tregs), and a cytokine mediating immune dynamics. Particular emphasis is made on the role of time delays associated with the processes of infection and mounting the immune response. Stability analysis of various steady states of the model allows us to identify parameter regions associated with different types of immune behaviour, such as, normal clearance of infection, chronic infection, and autoimmune dynamics. Numerical simulations are used to illustrate different dynamical regimes, and to identify basins of attraction of different dynamical states. An important result of the analysis is that not only the parameters of the system, but also the initial level of infection and the initial state of the immune system determine the progress and outcome of the dynamics.
Highlights
An immune system can only be viewed as effective when it can robustly identify and destroy pathogen-infected cells, while distinguishing such cells from healthy cells
We have developed and analysed a time-delayed model of immune response to a viral infection, which accounts for T cells with different activation thresholds, a cytokine mediating T cell proliferation, as well as regulatory T cells
To achieve better biological realism of the model, we have explicitly included time delays associated with the eclipse phase of the virus life cycle, stimulation/proliferation of T cells by IL-2, and suppression of IL-2 by regulatory T cells
Summary
An immune system can only be viewed as effective when it can robustly identify and destroy pathogen-infected cells, while distinguishing such cells from healthy cells. Among various parts of the immune system involved in coordinating an effective immune response, a significant role is known to be played by the T cells, with experimental evidence suggesting that regulatory T cells are vitally important for controlling autoimmunity [29,30,31,32] To account for this fact in mathematical models, Alexander and Wahl [23] and Burroughs et al [26,27]. Blyuss and Nicholson [43,44] have proposed a mathematical model of autoimmunity resulting from immune response to a viral infection through a mechanism of molecular mimicry This model explicitly includes the virus population and two types of T cells with different activation thresholds, and it accounts for a biologically realistic scenario where infection and autoimmune response can occur in different organs of the host.
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