Computer Simulation Suggests Multiple Sclerosis is a Single Disease

Summary: Using a mathematical model based on experimental data from multiple sclerosis patients, researchers performed computer simulations of the different known biological processes associated with the disease. They discovered the symptoms and disease course are produced by the same underlying mechanism that damages the nerve cells over time.

Source: PLOS.

New research supports the idea that multiple sclerosis (MS), which has widely varying symptoms and progression in different patients, is nonetheless a single disease with common underlying mechanisms. The findings are published in PLOS Computational Biology.

MS is an autoimmune disease in which the immune system disrupts the function of nerve cells in the spinal cord and brain. This can cause a variety of problems, including blurred vision, memory problems, paralysis, and more. Symptoms and patterns of disease progression over time can vary between patients, leading to suggestions that MS may actually consist of two or more different diseases.

Ekaterina Kotelnikova of the IDIBAPS – University of Barcelona, Spain, and colleagues hypothesized that MS is a single disease with multiple results in patients, all driven by the same underlying biological mechanism: immune system attack of the protective fibers shielding nerve cells and loss of the axons used by nerve cells to communicate with each other.

To explore this hypothesis, the researchers developed a mathematical model of MS based on experimental data from 66 patients who had been followed for up to 20 years. Using the model, they were able to perform computational simulations of the different known biological processes involved in the disease.

To test the validity of the model, the scientists ran simulations using data from a second group of 120 MS patients. They found that, by changing the intensity of the underlying biological processes involved in MS at distinct times, they were able to successfully reproduce the variability of disease courses seen in these patients.

These results support the hypothesis that that all the symptoms and disease courses observed in MS patients are produced by the same underlying mechanisms that damage nerve cells over time. This implies that, even though it may follow different patterns, MS will worsen over time for all patients.

Image shows a brain slice.
The diverse phenotype of Multiple Sclerosis is the consequence of the dynamic damage to the brain. Chronic autoimmune inflammatory damage to the brain produces waves of demyelination (blue line in the graph) and cumulative axonal loss (green line in the graph) in different intensities along time leading to all MS phenotypes. NeuroscienceNews.com image is credited to Dr Santiago Ortiz-Perez, from the Institute of Ophthalmology and Center of Neuroimmunology, IDIBAPS – Hospital Clinic, University of Barcelona.

“This concept has significant therapeutic implications and will drive the development of new therapies because it implies that MS will produce significant disability if suffered for enough time in all patients,” says co-author Dr. Pablo Villoslada, Head of the IDIBAPS research group in Pathogenesis and new treatments in multiple sclerosis and coordinator of the study. “Indeed, preventing relapses, although very important, will be not enough to achieve good control of the disease.”

About this neuroscience research article

Funding: Funding support: The European Union Seventh Framework Program (HEALTH-F4-2012-305397): “CombiMS”, grant agreement No 30539; the Horizon 2020 program ERACOSYSMED: Sys4MS grant, and the Spanish Ministry of Economy and Competitiveness and FEDER (project FIS2015-66503-C3-1-P), and the Swedish Research Council (3R). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

Source: Pablo Villoslada – PLOS
Publisher: Organized by NeuroscienceNews.com.
Image Source: NeuroscienceNews.com image is credited to Dr Santiago Ortiz-Perez, from the Institute of Ophthalmology and Center of Neuroimmunology, IDIBAPS – Hospital Clinic, University of Barcelona.
Original Research: Full open access research for “Dynamics and heterogeneity of brain damage in multiple sclerosis” by Ekaterina Kotelnikova, Narsis A. Kiani, Elena Abad, Elena H. Martinez-Lapiscina, Magi Andorra, Irati Zubizarreta, Irene Pulido-Valdeolivas, Inna Pertsovskaya, Leonidas G. Alexopoulos, Tomas Olsson, Roland Martin, Friedemann Paul, Jesper Tegnér, Jordi Garcia-Ojalvo, Pablo Villoslada in PLOS Computational Biology. Published online October 26 2017 doi:10.1371/journal.pcbi.1005757

Cite This NeuroscienceNews.com Article

[cbtabs][cbtab title=”MLA”]PLOS “Computer Simulation Suggests Multiple Sclerosis is a Single Disease.” NeuroscienceNews. NeuroscienceNews, 28 October 2017.
<https://neurosciencenews.com/multiple-sclerosis-computer-simulation-7828/>.[/cbtab][cbtab title=”APA”]PLOS (2017, October 28). Computer Simulation Suggests Multiple Sclerosis is a Single Disease. NeuroscienceNews. Retrieved October 28, 2017 from https://neurosciencenews.com/multiple-sclerosis-computer-simulation-7828/[/cbtab][cbtab title=”Chicago”]PLOS “Computer Simulation Suggests Multiple Sclerosis is a Single Disease.” https://neurosciencenews.com/multiple-sclerosis-computer-simulation-7828/ (accessed October 28, 2017).[/cbtab][/cbtabs]


Abstract

Dynamics and heterogeneity of brain damage in multiple sclerosis

Multiple Sclerosis (MS) is an autoimmune disease driving inflammatory and degenerative processes that damage the central nervous system (CNS). However, it is not well understood how these events interact and evolve to evoke such a highly dynamic and heterogeneous disease. We established a hypothesis whereby the variability in the course of MS is driven by the very same pathogenic mechanisms responsible for the disease, the autoimmune attack on the CNS that leads to chronic inflammation, neuroaxonal degeneration and remyelination. We propose that each of these processes acts more or less severely and at different times in each of the clinical subgroups. To test this hypothesis, we developed a mathematical model that was constrained by experimental data (the expanded disability status scale [EDSS] time series) obtained from a retrospective longitudinal cohort of 66 MS patients with a long-term follow-up (up to 20 years). Moreover, we validated this model in a second prospective cohort of 120 MS patients with a three-year follow-up, for which EDSS data and brain volume time series were available. The clinical heterogeneity in the datasets was reduced by grouping the EDSS time series using an unsupervised clustering analysis. We found that by adjusting certain parameters, albeit within their biological range, the mathematical model reproduced the different disease courses, supporting the dynamic CNS damage hypothesis to explain MS heterogeneity. Our analysis suggests that the irreversible axon degeneration produced in the early stages of progressive MS is mainly due to the higher rate of myelinated axon degeneration, coupled to the lower capacity for remyelination. However, and in agreement with recent pathological studies, degeneration of chronically demyelinated axons is not a key feature that distinguishes this phenotype. Moreover, the model reveals that lower rates of axon degeneration and more rapid remyelination make relapsing MS more resilient than the progressive subtype. Therefore, our results support the hypothesis of a common pathogenesis for the different MS subtypes, even in the presence of genetic and environmental heterogeneity. Hence, MS can be considered as a single disease in which specific dynamics can provoke a variety of clinical outcomes in different patient groups. These results have important implications for the design of therapeutic interventions for MS at different stages of the disease.

“Dynamics and heterogeneity of brain damage in multiple sclerosis” by Ekaterina Kotelnikova, Narsis A. Kiani, Elena Abad, Elena H. Martinez-Lapiscina, Magi Andorra, Irati Zubizarreta, Irene Pulido-Valdeolivas, Inna Pertsovskaya, Leonidas G. Alexopoulos, Tomas Olsson, Roland Martin, Friedemann Paul, Jesper Tegnér, Jordi Garcia-Ojalvo, Pablo Villoslada in PLOS Computational Biology. Published online October 26 2017 doi:10.1371/journal.pcbi.1005757

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