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Record W3112757916 · doi:10.1002/alz.044202

The effect of age on tau burden is dependent on amyloid status in late‐onset Alzheimer's disease

2020· article· en· W3112757916 on OpenAlexaff
Julie Ottoy, Min Su Kang, Mélissa Savard, Sulantha Mathotaarachchi, Tharick A. Pascoal, Mira Chamoun, Jean‐Paul Soucy, Serge Gauthier, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University Health CentreMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsNeuroinflammationInternal medicineMedicineAmyloid (mycology)PsychologyDiseaseOncologyPathology

Abstract

fetched live from OpenAlex

Abstract Background Growing evidence suggests that middle‐aged subjects with early‐onset AD show higher tau burden and more rapid tau accumulation compared to elderly. Here, we aim to investigate the effects of age, the greatest risk factor in AD, on amyloid, tau, and neuroinflammation in late‐onset AD. We hypothesized the independent effect of age on amyloid and neuroinflammation. However, the effect of age on tau would depend on amyloid load in AD. Method A total of 106 participants (66 A‐T‐, age 20‐86y; 40 A+T‐/A+T+, age 65‐84y) from the TRIAD cohort underwent static 40‐60min 18F‐AZD4694, 90‐110min 18F‐MK620, and 60‐90min 11C‐PBR28 SUVR, as well as MOCA and CDR‐SOB cognitive testing. All images were normalized to the ADNI template, and used cerebellar gray matter as the reference region. The effects of age on amyloid, tau, or neuroinflammation, as well as the interactive effect between age and AT status based on linear regression models. Last, the age‐dependent effect of amyloid, tau, or neuroinflammation on cognition is investigated. All models were corrected for sex, APOE, education, and remaining PET variables. Result We showed a positive main effect of age on amyloid (p<0.001) or neuroinflammation (p=0.05) while no interactive effect between age and AT status was observed. However, a significant interaction between age and AT status on tau in Braakstage1‐2 (p=0.01), Braakstage3‐4 (p=0.001), and Braakstage5‐6 (p=0.002) were observed (Figure1). In relation to cognition, younger subjects with higher tau load performed worse on cognitive testing as shown by a significant negative interaction between age and tau on MOCA. In contrast, age and amyloid showed a positive interactive effect on cognition. Conclusion Our study demonstrated that the age and amyloid or neuroinflammation have a positive association irrespective of the disease status. However, the effect of age on tau deposition depends on the amyloid load such that the presence of pathologic Ab leads to greater tau burden at younger age and worse cognition in late‐onset AD. This supports the framework where tau burden depends on amyloid load following the Ab cascade hypothesis.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.026
GPT teacher head0.306
Teacher spread0.280 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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