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Record W4414449579 · doi:10.1093/brain/awaf351

The presymptomatic and early manifestations of semantic dementia

2025· article· en· W4414449579 on OpenAlexfundno aff
David J. Whiteside, Matthew A Rouse, P Simon Jones, Ian Coyle‐Gilchrist, Alexander G. Murley, Katherine Stockton, Laura E. Hughes, Richard A. I. Bethlehem, Varun Warrier, Matthew A. Lambon Ralph, Timothy Rittman, James B. Rowe

Bibliographic record

VenueBrain · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsnot available
FundersNational Institute for Health Research Applied Research Collaboration East of EnglandNational Institute on AgingCambridge Centre for Parkinson-PlusAssociation of British NeurologistsMedical Research CouncilMedical Research Council CanadaAlzheimer’s Research UKDepartment of Health and Social CareWellcome TrustNIHR Cambridge Biomedical Research CentreAlzheimer's Disease Neuroimaging InitiativeMassachusetts General HospitalNational Institute for Health and Care ResearchPatrick Berthoud Charitable TrustUniversity of WashingtonUniversity of California, San Francisco
KeywordsFrontotemporal dementiaPrimary progressive aphasiaSemantic dementiaFrontotemporal lobar degenerationAtrophyNeuroimagingNeuropathologyCohortDementia

Abstract

fetched live from OpenAlex

People with semantic dementia (SD) or semantic variant primary progressive aphasia typically present with marked atrophy of the anterior temporal lobe, and thereafter progress more slowly than other forms of frontotemporal dementia. This suggests a prolonged prodromal phase with accumulation of neuropathology and minimal symptoms, about which little is known. To study early and presymptomatic SD, we first examine a well-characterized cohort of people with SD recruited from the Cambridge Centre for Frontotemporal Dementia. Five people with early SD had coincidental MRI prior to the onset of symptoms or were healthy volunteers in research with anterior temporal lobe atrophy as an incidental finding. We model longitudinal imaging changes in left- and right-lateralized SD to predict atrophy at symptom onset. We then assess 61 203 participants with structural brain MRI in the UK Biobank to find individuals with imaging changes in keeping with SD but with no neurodegenerative diagnosis. To identify these individuals in the UK Biobank, we design an ensemble-based classifier, differentiating baseline structural MRI in SD from healthy controls and patients with other neurodegenerative diseases, including other causes of frontotemporal lobar degeneration. We train the classifier on a Cambridge-based cohort (SD n = 47, other neurodegenerative diseases n = 498, healthy controls n = 88) and test it on a combined cohort from the Neuroimaging in Frontotemporal Dementia study and the Alzheimer's Disease Neuroimaging Initiative (SD n = 42, other neurodegenerative disease n = 449, healthy controls n = 127). From our case series, we find people with marked atrophy 3 to 5 years before recognition of symptom onset in left- or right-predominant SD. We present right-lateralized cases with subtle multimodal semantic impairment, found concurrently with only mild behavioural disturbance. We show that imaging measures can reliably and accurately differentiate clinical SD from other neurodegenerative diseases (recall: 0.88, precision: 0.95, F1 score: 0.91). We find individuals with no neurodegenerative diagnosis in the UK Biobank with striking left-lateralized (prevalence ages 45-85, 4.8/100 000) or right-lateralized (5.9/100 000) anterior temporal lobe atrophy, with deficits on cognitive testing suggestive of semantic impairment. These individuals show progressive involvement of other cognitive domains in longitudinal follow-up. Together, our findings suggest that (i) there is a burden of incipient early anterior temporal lobe atrophy in older populations, with comparable prevalence of left- and right-sided cases from this prospective unbiased approach to identification; (ii) substantial atrophy is required for manifest symptoms, particularly in right-lateralized cases; and (iii) semantic deficits across multiple domains can be detected in the early symptomatic phase.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.103

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.279
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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