A Computational Model of Progressive Multifocal Leukoencephalopathy (Abstract)

Human Immunodeficiency Virus (HIV) and some treatments for autoimmune diseases such as Multiple Sclerosis (MS) and Crohn’s disease can result in a suppressed immune system. This opens up the possibility for further viral complications, including Progressive Multifocal Leukoencephalopathy (PML). Leukoencephalopathy quite literally means degeneration of the white matter of the brain, which is exactly what this disease entails. When the JC virus, which is dormant in at least half of the population, becomes active, it causes demyelination. This process involves damage to the myelin sheath, a fatty layer on nerve cells, therefore creating lesions that interfere with communication between neurons. Symptomatic expression of PML can vary, but most often presents as progressively worsening visual, cognitive, and motor deficits. Though this disease is relatively rare, affecting five in one hundred AIDS patients and four in one thousand MS patients who are on the medication natalizumab, its prevalence continues to increase with the use of drugs that modify immune response (Ferenczy et al., 2012). Furthermore, the lack of current treatment for PML has resulted in a mortality rate upwards of thirty percent, and it leaves survivors with lifelong impairment. Research on PML is imperative, which is why I hope to contribute to this effort by creating a computational model of PML and its cause, the JC virus.

I aim to study the mechanisms of the JC virus and how it results in PML on a molecular level, focusing on how the virus spreads and infects oligodendrocytes, the cells that form the myelin sheath to ensure that the nervous system is properly functioning. Using the JC viral mechanisms  as a point of origin, I will create a computer-based model of the molecular interactions occurring throughout the various stages of disease infection as detailed in the literature on the JC virus and PML. By comparing the mechanisms in healthy individuals, HIV-infected individuals, and immunosuppressed MS patients, I will be able to identify specific disease pathways, reactions, and dynamics. I will then rely on quantitative analysis of the molecular interactions, such as oscillations and kinetic rates, to create a complete and accurate model of the PML disease. Ideally, this working mathematical model will be capable of receiving inputs, including both disease and treatment factors, and measuring the effects immediately, which will demonstrate how changes to one aspect affect the other components. This has significant value when considering the testing of new therapeutic techniques, as it is time and cost effective and eliminates negative repercussions. The field of computational neuroscience holds extreme promise for advancing our understanding of disease pathogenesis and treatment in effective ways, which is why I look forward to making my own mathematical model.

 

References:

Ferenczy, M. W., Marshall, L. J., Nelson, C. D. S., Atwood, W. J., NAth, A., Khalili, K., & Major, E. O. (2012). Molecular biology, epidemiology, and pathogenesis of progressive multifocal leukoencephalopathy. Clinical Microbiology Reviews, 25(3), 471-506.

Speak Your Mind

*