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Record W7117139152 · doi:10.1002/alz70856_098216

Vascular risk factors modulate the association between amyloid and tau PET in cognitively normal patients

2025· article· en· W7117139152 on OpenAlexaff
Valentin Ourry, Ting Qiu, Daniel C. Bowie, John C.S. Breitner, Josée Poirier, Sylvia Villeneuve

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsAmyloid (mycology)Association (psychology)Hyperlipidemiaβ amyloidAmyloid β

Abstract

fetched live from OpenAlex

BACKGROUND: Vascular risk factors have been associated with increased risk of Alzheimer's disease (AD) dementia. Previous studies showed mixed and complex interactions between vascular pathology and AD. In a longitudinal study of cognitively normal participants, we evaluated whether individual vascular risk factors are associated with amyloid and/or tau burden. We also investigated whether these factors and their treatments influence the association between amyloid and tau pathology. METHODS: We performed [18F]-NAV4694 and [18F]-AV1451 positron emission tomography on 241 older adults (age 68.3 ± 5.1 years, 69.3% female) from the PREVENT-AD cohort. All participants had been cognitively unimpaired at baseline. Longitudinal scans were available for 115 persons (4.4 ± 0.6 years follow-up). We examined the association between individual vascular factors (ApoE status, BMI, cholesterol, blood pressure) and global Aβ and/or temporal META-ROI tau burden, as well as their annual change. We then examined two-way interactions between global Aβ and these vascular factors (using clinical-categorical measures) or treatments as predictors of tau burden. Finally, we explored three-way interactions that included both vascular factors and medical treatments. All analyses were adjusted for age, sex, and education. RESULTS: Among the individual vascular risk factors, only ApoE4 status was significantly associated with amyloid burden (p < 0.001) and its annual change (p = 0.002). ApoE4 status also predicted tau burden (p < 0.001), but its association with annual change in tau was at a trend level (p = 0.088; not shown). At abnormal levels of HDL cholesterol, and diastolic blood pressure, there was a stronger increase in temporal Meta-ROI tau-PET at any given level of amyloid PET (Figure 1). Furthermore, stronger amyloid-related increase in tau was observed in patients untreated for hypertension but not treated patients (Figure 2). Three-way interactions showed that HDL cholesterol and diastolic blood pressure were modulatory factors only in the hypertension untreated patients, suggesting that hypertension treatment alleviates the influence of vascular risk factors on tau pathology (Figure 3). CONCLUSIONS: Hyperlipidemia and hypertension, if untreated, are associated with accelerated amyloid related increase in tau pathology in AD.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.014
GPT teacher head0.276
Teacher spread0.262 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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