Dynamics and heterogeneity of brain damage in multiple sclerosis

Kotelnikova, Ekaterina; Kiani, Narsis A.; Abad Adan, Elena; Martínez Lapiscina, Elena H.; Andorrà, Magí; Zubizarreta, Irati; Pulido Valdeolivas, Irene; Pertsovskaya, Inna; Alexopoulos, Leonidas G.; Olsson, Tomas; Martin, Roland; Paul, Friedemann; Tegnér, Jesper; García Ojalvo, Jordi; Villoslada, Pablo

doi:http://dx.doi.org/10.1371/journal.pcbi.1005757

Dynamics and heterogeneity of brain damage in multiple sclerosis

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Kotelnikova E, Kiani NA, Abad E, Martinez-Lapiscina EH, Andorra M, Zubizarreta I et al. Dynamics and heterogeneity of brain damage in multiple sclerosis. PLoS Comput Biol. 2017 Oct 26;13(10):e1005757. DOI: 10.1371/journal.pcbi.1005757

Abstract

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.