A mathematical model of the multiple sclerosis plaque. (7th March 2021)

• Record Type: Journal Article
• Authors: Moise, Nicolae; Friedman, Avner
• Is Part Of: Journal of theoretical biology. Volume 512(2021)
• Publication Date: 2021-03-07
• Subjects: Mathematical model -- Neurodegenerative diseases -- Autoimmune diseases -- Immunology; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2020.110532
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: The first model to include details of the geometry of the multiple sclerosis plaque. The model explains the role of pro/anti-inflammatory cells and cytokines in the plaque. The effects of commonly used and experimental drugs are simulated in the model. The model should be useful as a primary outcome measure of phase II trial. Abstract: Multiple sclerosis is an autoimmune disease that affects white matter in the central nervous system. It is one of the primary causes of neurological disability among young people. Its characteristic pathological lesion is called a plaque, a zone of inflammatory activity and tissue destruction that expands radially outward by destroying the myelin and oligodendrocytes of white matter. The present paper develops a mathematical model of the multiple sclerosis plaques. Although these plaques do not provide reliable information of the clinical disability in MS, they are nevertheless useful as a primary outcome measure of Phase II trials. The model consists of a system of partial differential equations in a simplified geometry of the lesion, consisting of three domains: perivascular space, demyelinated plaque, and white matter. The model describes the activity of various pro- and anti-inflammatory cells and cytokines in the plaque, and quantifies their effect on plaque growth. We show that volume growth of plaques are in qualitative agreement with reported clinical studies of several currently used drugs. We then use the model to explore treatments with combinations of such drugs, and with experimental drugs. We finally consider the benefits of early vs. delayed treatment.