Evidence map›Paper›PMID 32219555›Full record

ArticleJournal of neurology2020

Impaired connectivity within neuromodulatory networks in multiple sclerosis and clinical implications.

Antonio Carotenuto, Heather Wilson, Beniamino Giordano, Silvia P Caminiti, Zachary Chappell, Steven C R Williams, Alexander Hammers, Eli Silber, Peter Brex, Marios Politis

Open access · hybridAbstract read
In one paragraph

Article in Journal of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Trial
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  5. Article
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  7. Review
  8. Article
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  11. Depression and anxiety in multiple sclerosis. Review of a fatal combination.Journal of neural transmission (Vienna, Austria : 1996) · 2024
    Review
  12. Article
  13. Article
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  16. Article
  17. Review
  18. Relapsing and progressive MS: the sex-specific perspective.Therapeutic advances in neurological disorders · 2020
    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

10 authors at 5 institutions in 2 countries.

Antonio CarotenutoNeurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Heather WilsonNeurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Beniamino GiordanoNeurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Silvia P CaminitiNeurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Zachary ChappellNeurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Steven C R WilliamsInstitute of Psychiatry, Psychology and Neuroscience, Institute of Psychiatry, King's College London, London, UK.
Alexander HammersKing's College London and Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital, London, UK.
Eli SilberDepartment of Neurology, King's College Hospital NHS Foundation Trust, London, UK.
Peter BrexDepartment of Neurology, King's College Hospital NHS Foundation Trust, London, UK.
Marios PolitisNeurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. m.politis@exeter.ac.uk.
King's College London · GBKing's College Hospital NHS Foundation Trust · GBFederico II University Hospital · ITSt Thomas' Hospital · GBUniversity of Exeter · GB

Funding

Medical Research Council MR/N013042/1
6 · The paper itself

Abstract

There is mounting evidence regarding the role of impairment in neuromodulatory networks for neurodegenerative diseases, such as Parkinson's and Alzheimer's disease. However, the role of neuromodulatory networks in multiple sclerosis (MS) has not been assessed. We applied resting-state functional connectivity and graph theory to investigate the changes in the functional connectivity within neuromodulatory networks including the serotonergic, noradrenergic, cholinergic, and dopaminergic systems in MS. Twenty-nine MS patients and twenty-four age- and gender-matched healthy controls performed clinical and cognitive assessments including the expanded disability status score, symbol digit modalities test, and Hamilton Depression rating scale. We demonstrated a diffuse reorganization of network topography (P < 0.01) in serotonergic, cholinergic, noradrenergic, and dopaminergic networks in patients with MS. Serotonergic, noradrenergic, and cholinergic network functional connectivity derangement was associated with disease duration, EDSS, and depressive symptoms (P < 0.01). Derangements in serotonergic, noradrenergic, cholinergic, and dopaminergic network impairment were associated with cognitive abilities (P < 0.01). Our results indicate that functional connectivity changes within neuromodulatory networks might be a useful tool in predicting disability burden over time, and could serve as a surrogate endpoint to assess efficacy for symptomatic treatments.

Indexed as

ConnectomeAdultBrainCognitive DysfunctionDepressionFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMultiple Sclerosis, Relapsing-RemittingNerve NetSeverity of Illness IndexTime FactorsFunctional connectivityGraph theoryMultiple sclerosisNeurotransmitterResting-state fMRI

Identifiers

PMID32219555
PMCPMC7320961
OpenAlexW3013193510

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.