Evidence map›Paper›PMID 34591698›Full record

ArticleMultiple sclerosis (Houndmills, Basingstoke, England)2022

Gray matter atrophy in relapsing-remitting multiple sclerosis is associated with white matter lesions in connecting fibers.

Matthias Bussas, Sophia Grahl, Viola Pongratz, Achim Berthele, Christiane Gasperi, Till Andlauer, Christian Gaser, Jan S Kirschke, Benedikt Wiestler, Claus Zimmer and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Multiple sclerosis (Houndmills, Basingstoke, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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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

12 authors at 3 institutions in 1 country.

Matthias BussasDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
Sophia GrahlDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
Viola PongratzDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
Achim BertheleDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.
Christiane GasperiDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.
Till AndlauerDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0002-2917-5889
Christian GaserDepartment of Psychiatry and Department of Neurology, Jena University Hospital, Jena, Germany.
Jan S KirschkeDepartment of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0002-7557-0003
Benedikt WiestlerDepartment of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0002-2963-7772
Claus ZimmerDepartment of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.
Bernhard HemmerDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.ORCID 0000-0001-5985-6784
Mark MühlauDepartment of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
Technical University of Munich · DEJena University Hospital · DEMunich Cluster for Systems Neurology · DE

Funding

Computational Imaging Biomarkers of Multiple SclerosisR01NS112161 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI VAN LEEMPUT, KOEN · 2019 to 2023
$1.5M
NINDS NIH HHS R01 NS112161
6 · The paper itself

Abstract

backgroundLesions of brain white matter (WM) and atrophy of brain gray matter (GM) are well-established surrogate parameters in multiple sclerosis (MS), but it is unclear how closely these parameters relate to each other.

objectiveTo assess across the whole cerebrum whether GM atrophy can be explained by lesions in connecting WM tracts.

methodsGM images of 600 patients with relapsing-remitting MS (women = 68%; median age = 33.0 years, median expanded disability status scale score = 1.5) were converted to atrophy maps by data from a healthy control cohort. An atlas of WM tracts from the Human Connectome Project and individual lesion maps were merged to identify potentially disconnected GM regions, leading to individual disconnectome maps. Across the whole cerebrum, GM atrophy and potentially disconnected GM were tested for association both cross-sectionally and longitudinally.

resultsWe found highly significant correlations between disconnection and atrophy across most of the cerebrum. Longitudinal analysis demonstrated a close temporal relation of WM lesion formation and GM atrophy in connecting fibers.

conclusionGM atrophy is associated with WM lesions in connecting fibers. Caution is warranted when interpreting group differences in GM atrophy exclusively as differences in early neurodegeneration independent of WM lesion formation.

Indexed as

Multiple SclerosisMultiple Sclerosis, Relapsing-RemittingWhite MatterAdultAtrophyBrainFemaleGray MatterHumansMagnetic Resonance ImagingatrophyBiomarkersmultiple sclerosisoutcome measurementrelapsing/remittingT2 lesions

Identifiers

PMID34591698
PMCPMC9024016
OpenAlexW3202482181

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.