The role of idiotypic interactions in the adaptive immune system: a belief-propagation approach

TL;DR

This paper employs belief-propagation to analyze how idiotypic interactions among B clones influence immune system stability, resilience, and clone size distribution, providing analytical insights into activation thresholds and cross-talk effects.

Contribution

It introduces a belief-propagation based model to analytically study the impact of idiotypic interactions on immune system dynamics and clone size distribution.

Findings

B-B interactions enhance system resilience to noise

Increased idiotypic interactions raise activation noise thresholds

The model predicts clone size distributions measurable experimentally

Abstract

In this work we use belief-propagation techniques to study the equilibrium behaviour of a minimal model for the immune system comprising interacting T and B clones. We investigate the effect of the so-called idiotypic interactions among complementary B clones on the system's activation. Our result shows that B-B interactions increase the system's resilience to noise, making clonal activation more stable, while increasing the cross-talk between different clones. We derive analytically the noise level at which a B clone gets activated, in the absence of cross-talk, and find that this increases with the strength of idiotypic interactions and with the number of T cells signalling the B clone. We also derive, analytically and numerically, via population dynamics, the critical line where clonal cross-talk arises. Our approach allows us to derive the B clone size distribution, which can be experimentally measured and gives important information about the adaptive immune system response to antigens and vaccination.