Trajectories of amyloid beta accumulation – Unveiling the relationship with APOE genotype and cognitive decline
Bibliographic record
Abstract
Amyloid beta (Aβ) follows a sigmoidal time function with varying accumulation rates. We studied how the position on this function, reflected by different Aβ accumulation phases, influences APOE ɛ4's association with Aβ and cognitive decline in 503 participants without dementia using Aβ-PET imaging over 5.3-years. First, Aβ load and accumulation were analyzed irrespective of phases using linear mixed regression. Generally, ɛ4 carriers displayed a higher Aβ load. Moreover, Aβ normal (Aβ-) ɛ4 carriers demonstrated higher accumulation. Next, we categorized accumulation phases as "decrease", "stable", or "increase" based on trajectory shapes. After excluding the Aβ-/decrease participants from the initial regression, the difference in accumulation attributable to genotype among Aβ- individuals was no longer significant. Further analysis revealed that in increase phases, Aβ accumulation was higher among noncarriers, indicating a genotype-related timeline shift. Finally, cognitive decline was analyzed across phases and was already evident in the Aβ-/increase phase. Our results encourage early interventions for ɛ4 carriers and imply that monitoring accumulating Aβ- individuals might help identify those at risk for cognitive decline.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".