Open Access Research article

Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in Multiple Sclerosis

Nieves Vélez de Mendizábal12, Jorge Carneiro3, Ricard V Solé4, Joaquín Goñi1, Jean Bragard1, Ivan Martinez-Forero1, Sara Martinez-Pasamar5, Jorge Sepulcre1, Javier Torrealdea2, Francesca Bagnato6, Jordi Garcia-Ojalvo7 and Pablo Villoslada5*

Author Affiliations

1 Division of Neurosciences, CIMA - University of Navarra. Avenida Pio XII 55, 31008 Pamplona, Spain

2 Computer Science and Artificial Intelligence Department, University of the Basque Country, Paseo de Manuel Lardizábal, 1, 20018 San Sebastian, Spain

3 Theoretical Immunology Group, Instituto Gulbenkian de Ciencia, Rua da Quinta Grande 6, 2780-156 Oeiras, Portugal

4 Complex Systems Lab, Universitat Pompeu Fabra, Carrer del Dr. Aiguader, 88, 08003 Barcelona, Spain

5 Center for Neuroimmunology, Department of Neurosciences. Institute of Biomedical Research August Pi Sunyer (IDIBAPS) - Hospital Clinic of Barcelona. Villarroel 170, 08036 Barcelona, Spain

6 Neuroimmunology Branch, National Institute of Neurological Diseases and Stroke. 9000 Rockville Pike, Bethesda, MD. USA

7 Departament de Física i Enginyeria Nuclear, Universitat Politecnica de Catalunya, Rambla Sant Nebridi s/n, 08222 Terrasa, Spain

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BMC Systems Biology 2011, 5:114  doi:10.1186/1752-0509-5-114

Published: 15 July 2011



The relapsing-remitting dynamics is a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). Although current understanding of both cellular and molecular mechanisms involved in the pathogenesis of autoimmune diseases is significant, how their activity generates this prototypical dynamics is not understood yet. In order to gain insight about the mechanisms that drive these relapsing-remitting dynamics, we developed a computational model using such biological knowledge. We hypothesized that the relapsing dynamics in autoimmunity can arise through the failure in the mechanisms controlling cross-regulation between regulatory and effector T cells with the interplay of stochastic events (e.g. failure in central tolerance, activation by pathogens) that are able to trigger the immune system.


The model represents five concepts: central tolerance (T-cell generation by the thymus), T-cell activation, T-cell memory, cross-regulation (negative feedback) between regulatory and effector T-cells and tissue damage. We enriched the model with reversible and irreversible tissue damage, which aims to provide a comprehensible link between autoimmune activity and clinical relapses and active lesions in the magnetic resonances studies in patients with Multiple Sclerosis. Our analysis shows that the weakness in this negative feedback between effector and regulatory T-cells, allows the immune system to generate the characteristic relapsing-remitting dynamics of autoimmune diseases, without the need of additional environmental triggers. The simulations show that the timing at which relapses appear is highly unpredictable. We also introduced targeted perturbations into the model that mimicked immunotherapies that modulate effector and regulatory populations. The effects of such therapies happened to be highly dependent on the timing and/or dose, and on the underlying dynamic of the immune system.


The relapsing dynamic in MS derives from the emergent properties of the immune system operating in a pathological state, a fact that has implications for predicting disease course and developing new therapies for MS.