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Record W4414888045 · doi:10.1093/brain/awaf374

Neuronal activity and amyloid-β promote tau seeding in the entorhinal cortex in Alzheimer’s disease

2025· article· en· W4414888045 on OpenAlexafffund
Christoffer G. Alexandersen, Danielle S. Bassett, Alain Goriely, Pavanjit Chaggar

Bibliographic record

VenueBrain · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchNational Institute on AgingNational Institutes of HealthNorthern California Institute for Research and EducationFoundation for the National Institutes of Health
KeywordsEntorhinal cortexNeuroimagingHippocampusAlzheimer's Disease Neuroimaging InitiativeDiseasePremovement neuronal activityTau proteinTemporal cortex

Abstract

fetched live from OpenAlex

The entorhinal cortex is the first region to develop tau pathology in Alzheimer's disease and primary age-related tauopathy, yet the reasons for this selective vulnerability remain unclear. We developed a computational model in which neuronal activity and amyloid-β (Aβ) modulate tau transport, hypothesizing that this mechanism explains entorhinal vulnerability to early tau pathology. The model combines structural connectivity with either neuronal activity (measured by FDG PET) or Aβ burden (measured by Aβ PET). We analysed Alzheimer's Disease Neuroimaging Initiative (ADNI) data comprising 527 FDG PET scans (mean age 71.8 years; 174 cognitively normal, 293 mild cognitive impairment, 60 Alzheimer's disease) and 1244 Aβ PET scans (mean age 72.4 years; 501 cognitively normal, 588 mild cognitive impairment, 155 Alzheimer's disease). From these, 253 FDG-tau and 453 Aβ-tau PET pairs were used in regression analyses. Key results were replicated in the Harvard Aging Brain Study (HABS; 300 FDG, 348 Aβ, 116 FDG-tau and 255 Aβ-tau pairs). Both FDG- and Aβ-based models consistently identified the entorhinal cortex as a primary tau seeding region in ADNI (FDG: z ≈ 4.6-4.9, P < 0.0066; Aβ: z ≈ 4.0-8.7, P ≤ 0.011) and in HABS (FDG: z = 5.7, P = 0.030; Aβ: z = 6.0, P = 0.0018). Simple linear regression showed modest associations between model-derived seeding and empirical entorhinal tau in ADNI (FDG: β = 6.7, P = 0.0039; Aβ: β = 11.3, P < 0.001), which remained significant after adjustment for age, sex, and APOE4 status (FDG: β = 7.1, P < 0.001; Aβ: β = 9.7, P < 0.001). Aβ-based associations replicated in HABS (β = 3.3, P < 0.001), while FDG-based correlations were not detectable in this predominantly cognitively normal cohort (β = -0.43, P = 0.80; power = 49%). These findings support a mechanistic role for neuronal activity and Aβ in initiating tau pathology, with the entorhinal cortex consistently emerging as highly vulnerable. Our computational model reliably identifies this region as the epicentre of pathology, supporting the idea that brain-wide patterns of neuronal activity and amyloid burden determine where tau pathology begins.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.030
GPT teacher head0.337
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2025
Admission routes2
Has abstractyes

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