Evidence map›Paper›PMID 29073203›Full record

ArticlePLoS computational biology2017

Dynamics and heterogeneity of brain damage in multiple sclerosis.

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 and 5 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 50 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Multiscale networks in multiple sclerosis.PLoS computational biology · 2024
    Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. CombiningFrontiers in neuroscience · 2022
    Article
  15. Observational
  16. Review
  17. Article
  18. Androgen Therapy in Neurodegenerative Diseases.Journal of the Endocrine Society · 2020
    Review
  19. The immune signatures of multiple sclerosis: Lessons from twin studies.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 7 institutions in 6 countries.

Ekaterina KotelnikovaCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.ORCID http://orcid.org/0000-0002-8026-078X
Narsis A KianiUnit of Computational Medicine, Department of Medicine & Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.
Elena AbadCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.
Elena H Martinez-LapiscinaCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.
Magi AndorraCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.
Irati ZubizarretaCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.ORCID http://orcid.org/0000-0001-7637-7830
Irene Pulido-ValdeolivasCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.ORCID http://orcid.org/0000-0003-0188-2458
Inna PertsovskayaCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.ORCID http://orcid.org/0000-0002-4873-8659
Leonidas G AlexopoulosNational Technical University of Athens, Athens, Greece.ORCID http://orcid.org/0000-0003-0425-166X
Tomas OlssonUnit of Neuroimmunology, Karolinska Institute, Stockholm, Sweden.
Roland MartinNeuroimmunology and MS Research, Neurology Clinic, University Hospital, University Zurich, Zurich, Switzerland.
Friedemann PaulNeuroCure Clinical Research Center, and the Experimental and Clinical Research Center, Charité Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine Berlin, Berlin, Germany.
Jesper TegnérUnit of Computational Medicine, Department of Medicine & Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.
Jordi Garcia-OjalvoUniversitat Pompeu Fabra, Barcelona, Spain.ORCID http://orcid.org/0000-0002-3716-7520
Pablo VillosladaCenter for Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.ORCID http://orcid.org/0000-0002-8735-6119
Consorci Institut D'Investigacions Biomediques August Pi I Sunyer · ESScience for Life Laboratory · SEUniversitat Pompeu Fabra · ESKarolinska Institutet · SEMax Delbrück Center · DENational Technical University of Athens · GRUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BrainMultiple SclerosisComputational BiologyDatabases, FactualHumansImage Processing, Computer-AssistedInflammationMagnetic Resonance ImagingProspective Studies

Identifiers

PMID29073203
PMCPMC5657613
OpenAlexW2765502040

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.