Domain‐specific cognitive decline associates with differential regional tau burden in the Alzheimer’s disease spectrum
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".