Stochastic dynamics in a time-delayed model for autoimmunity

Fatehi, Farzad, Kyrychko, Yuliya N and Blyuss, Konstantin B (2020) Stochastic dynamics in a time-delayed model for autoimmunity. Mathematical Biosciences, 322. a108323. ISSN 0025-5564

[img] PDF - Accepted Version
Restricted to SRO admin only until 23 February 2021.
Available under License Creative Commons Attribution-NonCommercial No Derivatives.

Download (4MB)

Abstract

In this paper we study interactions between stochasticity and time delays in the dynamics of immune response to viral infections, with particular interest in the onset and development of autoimmune response. Starting with a deterministic time-delayed model of immune response to infection, which includes cytokines and T cells with different activation thresholds, we derive an exact delayed chemical master equation for the probability density. We use system size expansion and linear noise approximation to explore how variance and coherence of stochastic oscillations depend on parameters, and to show that stochastic oscillations become more regular when regulatory T cells become more effective at clearing autoreactive T cells. Reformulating the model as an Itô stochastic delay differential equation, we perform numerical simulations to illustrate the dynamics of the model and associated probability distributions in different parameter regimes. The results suggest that even in cases where the deterministic model has stable steady states, in individual stochastic realisations, the model can exhibit sustained stochastic oscillations, whose variance increases as one gets closer to the deterministic stability boundary. Furthermore, in the regime of bi-stability, whereas deterministically the system would approach one of the steady states (or periodic solutions) depending on the initial conditions, due to the presence of stochasticity, it is now possible for the system to reach both of those dynamical states with certain probability. Biological significance of this result lies in highlighting the fact that since normally in a laboratory or clinical setting one would observe a single individual realisation of the course of the disease, even for all parameters characterising the immune system and the strength of infection being the same, there is a proportion of cases where a spontaneous recovery can be observed, and similarly, where a disease can develop in a situation that otherwise would result in a normal disease clearance.

Item Type: Article
Keywords: Autoimmunity, Immune response, Mathematical model, Stochasticity, Time delays
Schools and Departments: School of Mathematical and Physical Sciences > Mathematics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 30 Mar 2020 08:19
Last Modified: 30 Mar 2020 08:30
URI: http://sro.sussex.ac.uk/id/eprint/90601

View download statistics for this item

📧 Request an update