Autoimmune diseases initiated by pathogen infection: Mathematical modeling

Akane Hara*, Yoh Iwasa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Many incurable diseases in humans are related to autoimmunity and are initially induced by a viral infection. Presumably, the virus has antigens with epitopes similar to those found in components of the host's body, thus allowing it to evade immune surveillance. Viral infection activates the immune system, which results in viral clearance. After infection, the enhanced immune system may begin to attack the host's cells, tissues, and organs. In this study, we developed a simple mathematical model in which we identify the conditions needed to trigger an autoimmune response. This model considers the dynamics of T helper (Th) cells, viruses, self-antigens, and memory T cells. Viral infection results in a temporal increase in viral abundance, which is suppressed by an increase in the number of Th cells. For the virus to be eliminated from the body, the level of Th cells must be maintained above a certain threshold to prevent viral replication, even in the absence of virus in the body. This role is realized by memory T cells produced during temporal viral infections. Thus, we investigated the conditions needed for the immune response to be enhanced after viral infection and concluded that cross-immunity must be weak for negative selection and T-cell activation but strong for antigen-suppressing reactions. We also discuss alternative models of cross-immunity and possible extensions of the model.

Original languageEnglish
Article number110296
JournalJournal of Theoretical Biology
Volume498
DOIs
StatePublished - 2020/08/07

Keywords

  • Autoimmunity
  • Immune memory
  • Molecular mimicry

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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