A mathematical model for inflammation and demyelination in multiple sclerosis

Multiple sclerosis (MS) is an incurable, life-long disease caused by the demyelination of neurons in the brain and spine. MS is often characterized by relapses in inflammation and demyelination, followed by periods of remission. Symptoms can be highly debilitating, and there are still many open questions about the origin and progression of the disease. Mathematical modelling is well placed to capture the dynamics of MS and provide insight into disease aetiology. In this work, we present a minimal model for MS disease onset and progression driven by inflammation and demyelination. The model dynamics are capable of describing a typical evolution of the illness, with changes from a healthy state to a diseased scenario captured by certain ranges of parameter values. Our model also describes the non-uniform oscillatory nature of the disease, born from a Hopf bifurcation owing to the strength of the inflammatory response. In particular, using experimental data for contrast-enhancing lesions obtained from MS patients, we can reproduce some of the typical relapsing-remitting behaviours of this disease. We hope that the model presented here can serve as a baseline for more complex approaches and as a tool for predicting possible evolutions of the disease.

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Publication Details

Journal
Journal of The Royal Society Interface
Published
2026-07-22
DOI
https://doi.org/10.1098/rsif.2026.0364
Citations
1
Primary Topic
Multiple Sclerosis Research Studies
Type
article
Field-Weighted Citation Impact
8.22
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article

A mathematical model for inflammation and demyelination in multiple sclerosis

Federico Frascoli, Adrianne L. Jenner, Georgia R. Weatherley
1 citations
Journal of The Royal Society Interface
Multiple Sclerosis Research Studies
8.22
article

A mathematical model for inflammation and demyelination in multiple sclerosis

Federico Frascoli, Adrianne L. Jenner, Georgia R. Weatherley
article en
1 citations

Abstract

Multiple sclerosis (MS) is an incurable, life-long disease caused by the demyelination of neurons in the brain and spine. MS is often characterized by relapses in inflammation and demyelination, followed by periods of remission. Symptoms can be highly debilitating, and there are still many open questions about the origin and progression of the disease. Mathematical modelling is well placed to capture the dynamics of MS and provide insight into disease aetiology. In this work, we present a minimal model for MS disease onset and progression driven by inflammation and demyelination. The model dynamics are capable of describing a typical evolution of the illness, with changes from a healthy state to a diseased scenario captured by certain ranges of parameter values. Our model also describes the non-uniform oscillatory nature of the disease, born from a Hopf bifurcation owing to the strength of the inflammatory response. In particular, using experimental data for contrast-enhancing lesions obtained from MS patients, we can reproduce some of the typical relapsing-remitting behaviours of this disease. We hope that the model presented here can serve as a baseline for more complex approaches and as a tool for predicting possible evolutions of the disease.

Journal of The Royal Society InterfaceVol. 23(240)
Queensland University of Technology (AU), Swinburne University of Technology (AU)
Openalex Percentile: Top 8%
Multiple Sclerosis Research Studies
8.22
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