MétaCan
Menu
← Back to cohort
Record W4390196952 · doi:10.1002/alz.081887

Domain‐specific cognitive decline associates with differential regional tau burden in the Alzheimer’s disease spectrum

2023· article· en· W4390196952 on OpenAlexaff
Frédéric St‐Onge, Alexa Pichet Binette, Marianne Chapleau, John C.S. Breitner, Sylvia Villeneuve

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill Genome CentreMcGill University
Fundersnot available
KeywordsCognitionDementiaPsychologyCognitive declineEpisodic memoryAlzheimer's diseaseEffects of sleep deprivation on cognitive performanceCognitive testAudiologyDiseaseNeuroscienceMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Patients presenting with distinct clinical variants of Alzheimer’s disease (AD) present differential patterns of tau pathology measured with positron emission tomography (PET). Yet, a single set of brain regions like a temporal meta‐ROI is often chosen to study the association between cognition and tau. Instead, we aimed to map the associations between regional tau and multiple cognitive domains, and to test whether using whole brain information yields stronger associations with cognition compared to a singular composite region. Method We included 372 amyloid‐positive ADNI participants that had at least one tau‐PET scan (163 cognitively unimpaired [CU], 132 with mild cognitive impairment [MCI], 77 with AD dementia). Composite cognitive scores for memory, executive functioning, visuospatial and language were used for cross‐sectional (closest score to tau‐PET) and longitudinal analyses. Individual rate of cognitive decline was computed using linear mixed effect models, leveraging all visits available for each participant. We did region‐wise analyses, relating tau in the 64 regions of the Desikan‐Killiany atlas plus the amygdalae with cognitive performance and rate of cognitive decline. We also derived a “spatial extent index” where we computed the number of abnormal tau regions and compared the performance of this index to detect cognitive impairment to what would have been found with a classical temporal meta‐ROI SUVR value. Result No regional association between tau and cognition survived FDR correction in CU participants. Cross‐sectionally and longitudinally, participants with MCI and with AD dementia, associations between tau and memory were predominant in the temporal lobe, associations with language were restricted mostly to the left hemisphere and associations with executive functioning spanned the entire cortex. (Fig 1) Comparing the sum of tau positive regions (spatial extent index) to tau SUVR in the temporal meta‐ROI, both measures were similarly associated with cognition, except for executive functioning at baseline where the spatial extent index was more strongly associated with cognition than the meta‐ROI. (Fig 2) Conclusion While temporal meta‐ROI tau SUVR may be sufficient to track non‐executive cognitive performance in individual with cognitive impairments, a whole brain measure may provide additional information regarding executive impairment occurring 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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.315
Teacher spread0.275 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAlzheimer s & Dementia→Same topicDementia and Cognitive Impairment Research→French-language works237,207→