Evidence map›Paper›PMID 42688976›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)

Clinically altered brain activity may not look like aged brain activity: Implications for brain-age modeling and biomarker strategies.

Lukas A W Gemein, Sinead Gaubert, Claire Paquet, Joseph Paillard, Sebastian C Holst, Thomas Tveitstøl, Ira R J H Haraldsen, Tony Kam-Thong, David J Hawellek, Jörg F Hipp and 1 more

Abstract read
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Article in Alzheimer's & dementia (New York, N. Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Lukas A W GemeinNeuroscience and Rare Diseases, Roche Innovation Center Basel, Roche Pharma Research and Early Development F. Hoffmann-La Roche Ltd. Basel Switzerland.
Sinead GaubertInserm UMRS 1144 Therapeutic Optimization in Neuropsychopharmacology, Fernand Widal Université Paris Cité Paris France.
Claire PaquetInserm UMRS 1144 Therapeutic Optimization in Neuropsychopharmacology, Fernand Widal Université Paris Cité Paris France.
Joseph PaillardNeuroscience and Rare Diseases, Roche Innovation Center Basel, Roche Pharma Research and Early Development F. Hoffmann-La Roche Ltd. Basel Switzerland.
Sebastian C HolstNeuroscience and Rare Diseases, Roche Innovation Center Basel, Roche Pharma Research and Early Development F. Hoffmann-La Roche Ltd. Basel Switzerland.
Thomas TveitstølDepartment of Neurology Oslo University Hospital Oslo Norway.
Ira R J H HaraldsenDepartment of Neurology Oslo University Hospital Oslo Norway.
Tony Kam-ThongComputational Sciences Center of Excellence F. Hoffmann La Roche Ltd. Basel Switzerland.
David J HawellekNeuroscience and Rare Diseases, Roche Innovation Center Basel, Roche Pharma Research and Early Development F. Hoffmann-La Roche Ltd. Basel Switzerland.
Jörg F HippNeuroscience and Rare Diseases, Roche Innovation Center Basel, Roche Pharma Research and Early Development F. Hoffmann-La Roche Ltd. Basel Switzerland.
Denis A EngemannNeuroscience and Rare Diseases, Roche Innovation Center Basel, Roche Pharma Research and Early Development F. Hoffmann-La Roche Ltd. Basel Switzerland.ORCID https://orcid.org/0000-0002-7223-1014

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBrain-age gap (BAG), the difference between predicted age and chronological age, is studied as a biomarker for the natural progression of neurodegeneration. The BAG captures brain atrophy as measured with structural magnetic resonance imaging (MRI). Electroencephalography (EEG) has also been explored for estimating the BAG (EEG-BAG). However, studies showed mixed results for the EEG-BAG including counterintuitive findings of younger predicted age in clinical populations, raising doubts about its utility as a clinical tool for mild cognitive impairment (MCI) and Alzheimer's disease (AD).

methodsThis study critically examined brain-age estimation from spectral EEG power as a common measure of brain activity in two of the largest public EEG datasets containing heterogeneous clinical cases alongside controls including MCI and AD. EEG recordings were analyzed from individuals with heterogeneous neurological conditions (

resultsWe found that age-prediction models trained on the reference population systematically underpredicted age in clinical conditions showing strong and systematic, age-related differences in EEG power compared to controls. Data exploration and simulations revealed how diverging age-related trends in specific EEG frequencies can account for a negative EEG-BAG. DISCUSSION: The utility of brain age as an interpretable biomarker relies on the observation from structural MRI that progressive neurodegeneration often broadly resembles aging. This assumption can be violated for functional assessments such as EEG spectral power related to different neurological and psychiatric conditions or medications. The sign of the BAG may therefore not be meaningfully interpreted as an individual aging metric, hence hampering its utility as an endpoint or biomarker in MCI and AD.

Indexed as

Alzheimer's diseasebiomarkerbrain‐age gapdementiaelectroencephalographymachine learningmagnetic resonance imagingmild cognitive impairment

Identifiers

PMID42688976
PMCPMC13536007

What Socratic holds

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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 Socratic graph.