Evidence map›Paper›PMID 40153923›Full record

ArticleEBioMedicine2025

Exploring the neuromagnetic signatures of cognitive decline from mild cognitive impairment to Alzheimer's disease dementia.

Sinead Gaubert, Pilar Garces, Jörg Hipp, Ricardo Bruña, Maria Eugenia Lopéz, Fernando Maestu, Delshad Vaghari, Richard Henson, Claire Paquet, Denis-Alexander Engemann

Abstract read
In one paragraph

Article in EBioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

10 authors.

Sinead GaubertUniversité Paris Cité, Inserm UMRS 1144 Therapeutic Optimization in Neuropsychopharmacology, Paris, France; Cognitive Neurology Center, GHU.Nord APHP Hôpital Lariboisière Fernand Widal, Paris, France. Electronic address: sinead.gaubert@aphp.fr.
Pilar GarcesRoche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Jörg HippRoche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Ricardo BruñaCenter for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28223, Madrid, Spain; Department of Radiology, Rehabilitation and Physiotherapy, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain.
Maria Eugenia LopézCenter for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28223, Madrid, Spain; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.
Fernando MaestuCenter for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28223, Madrid, Spain; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.
Delshad VaghariDepartment of Psychology, University of Cambridge, UK.
Richard HensonMRC Cognition and Brain Sciences Unit, University of Cambridge, CB2 7EF, UK; Department of Psychiatry, University of Cambridge, UK.
Claire PaquetUniversité Paris Cité, Inserm UMRS 1144 Therapeutic Optimization in Neuropsychopharmacology, Paris, France; Cognitive Neurology Center, GHU.Nord APHP Hôpital Lariboisière Fernand Widal, Paris, France.
Denis-Alexander EngemannRoche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland. Electronic address: denis.engemann@roche.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeveloping non-invasive and affordable biomarkers to detect Alzheimer's disease (AD) at a prodromal stage is essential, particularly in the context of new disease-modifying therapies. Mild cognitive impairment (MCI) is a critical stage preceding dementia, but not all patients with MCI will progress to AD. This study explores the potential of magnetoencephalography (MEG) to predict cognitive decline from MCI to AD dementia.

methodsWe analysed resting-state MEG data from the BioFIND dataset including 117 patients with MCI among whom 64 developed AD dementia (AD progression), while 53 remained cognitively stable (stable MCI), using spectral analysis. Logistic regression models estimated the additive explanation of selected clinical, MEG, and MRI variables for AD progression risk. We then built a high-dimensional classification model to combine all modalities and variables of interest.

findingsMEG 16-38Hz spectral power, particularly over parieto-occipital magnetometers, was significantly reduced in the AD progression group. In logistic regression models, decreased MEG 16-38Hz spectral power and reduced hippocampal volume/total grey matter ratio on MRI were independently linked to higher AD progression risk. The data-driven classification model confirmed, among other factors, the complementary information of MEG covariance (AUC = 0.74, SD = 0.13) and MRI cortical volumes (AUC = 0.77, SD = 0.14) to predict AD progression. Combining all inputs led to markedly improved classification scores (AUC = 0.81, SD = 0.12).

interpretationThese findings highlight the potential of spectral power and covariance as robust non-invasive electrophysiological biomarkers to predict AD progression, complementing other diagnostic measures, including cognitive scores and MRI.

fundingThis work was supported by: Fondation pour la Recherche Médicale (grant FDM202106013579).

Indexed as

Alzheimer DiseaseCognitive DysfunctionMagnetoencephalographyAgedAged, 80 and overBiomarkersDisease ProgressionFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedBiomarkersAlzheimer's disease (AD)Brain rhythmsDisease progressionMagnetoencephalography (MEG)Mild cognitive impairment (MCI)Spectral power

Identifiers

PMID40153923
PMCPMC11995804

What OpenQuestion holds

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LicenceCC BY
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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.