Evidence map›Paper›PMID 41042072›Full record

ArticleHuman brain mapping2025

Divergent Brain Network Activity in Asymptomatic C9orf72 and SOD1 Variant Carriers Compared With Established Amyotrophic Lateral Sclerosis.

Michael Trubshaw, Chetan Gohil, Evan Edmond, Malcolm Proudfoot, Katie Yoganathan, Joanne Wuu, Alicia Northall, Oliver Kohl, Charlotte J Stagg, Anna C Nobre and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Human brain mapping, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Review
  4. 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.

Michael TrubshawOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.ORCID 0000-0002-4848-6156
Chetan GohilOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.ORCID 0000-0002-0888-1207
Evan EdmondOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Malcolm ProudfootNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0002-0774-4366
Katie YoganathanOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Joanne WuuDepartment of Neurology, University of Miami, Florida, USA.
Alicia NorthallOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Oliver KohlOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Charlotte J StaggOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Anna C NobreOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Kevin TalbotNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Alexander G ThompsonNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Michael BenatarDepartment of Neurology, University of Miami, Florida, USA.
Mark WoolrichOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Martin R TurnerOxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Funding

Pre-Symptomatic Familial ALS (Pre-fALS) Study - Prelude to a Treatment Trial; Administrative SupplementR01NS105479 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI BENATAR, MICHAEL, WUU, JOANNE · 2018 to 2022
$3.0M
ALS Association 2015Motor Neurone Disease Association MR/K01014X/1Muscular Dystrophy Association 172123Muscular Dystrophy Association 4365National Institute of Health Research Oxford Cognitive Health Clinical Research FacilityNational Institute of Health Research Oxford Health Biomedical Research Centre NIHR203316NIH HHS R01 NS105479NINDS NIH HHS R01 NS105479Wellcome Centre for Integrative Neuroimaging 203139/Z/16/ZWellcome Trust
6 · The paper itself

Abstract

Understanding the presymptomatic biology in those at high risk of developing amyotrophic lateral sclerosis (ALS) is essential for the development of preventative therapeutic interventions. Approximately 10% of ALS is associated with a C9orf72 expansion or pathogenic variants in SOD1. Magnetoencephalography (MEG), combined with machine learning algorithms, can model brain network dynamics in such at-risk populations to develop pathogenic biomarkers. Individuals with symptomatic ALS (symALS, n = 61), asymptomatic C9orf72 carriers (aC9, n = 16), or pathological SOD1 carriers (aSOD, n = 12), and healthy controls (n = 84) underwent resting-state MEG recordings. Extracted metrics included regional oscillatory power, connectivity, and spectral shape. 'DyNeMo' was trained to identify six functional dynamic brain networks. Metrics were compared between groups. A classifier was trained to distinguish asymptomatic gene carriers from controls. Compared to controls, beta frequency power was decreased in both symALS and aC9 groups. The aC9 group showed a marked slowing of frontal oscillatory activity, while the aSOD group showed a marked acceleration. Dynamic network coactivation was dramatically disrupted in aC9, more than in both symALS and aSOD. The classifier accurately distinguished genetically at-risk groups from controls (receiver-operator-characteristic area-under-curve 0.89). The cerebral network dynamics of aC9 are markedly different from both aSOD and symALS, supporting the concept of profoundly different upstream pathways in SOD1 ALS, sparing wider cortical pathology when compared to C9orf72 ALS. aC9 changes may reflect chronic adaptive changes relating to neurodevelopmental factors or underpin aspects of system vulnerability that define penetrance variability. MEG metrics might provide important biomarkers of prevention therapy efficacy and phenoconversion in at-risk populations.

Indexed as

Amyotrophic Lateral SclerosisC9orf72 ProteinConnectomeNerve NetSuperoxide Dismutase-1AdultAgedFemaleHeterozygoteHumansMagnetoencephalographyMaleMiddle AgedC9orf72 ProteinC9orf72 protein, humanSOD1 protein, humanSuperoxide Dismutase-1amyotrophic lateral sclerosisbiomarkerC9orf72geneticmachine learningmagnetoencephalographymotor neuron diseasenetworkspresymptomaticSOD1

Identifiers

PMID41042072
PMCPMC12492477

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.