High Soluble Amyloid-β42 Predicts Normal Cognition in Amyloid-Positive Individuals with Alzheimer’s Disease-Causing Mutations
Bibliographic record
Abstract
BACKGROUND: In amyloid-positive individuals at risk for Alzheimer's disease (AD), high soluble 42-amino acid amyloid-β (Aβ42) levels are associated with normal cognition. It is unknown if this relationship applies longitudinally in a genetic cohort. OBJECTIVE: To test the hypothesis that high Aβ42 preserves normal cognition in amyloid-positive individuals with Alzheimer's disease (AD)-causing mutations (APP, PSEN1, or PSEN2) to a greater extent than lower levels of brain amyloid, cerebrospinal fluid (CSF) phosphorylated tau (p-tau), or total tau (t-tau). METHODS: Cognitive progression was defined as any increase in Clinical Dementia Rating (CDR = 0, normal cognition; 0.5, very mild dementia; 1, mild dementia) over 3 years. Amyloid-positivity was defined as a standard uptake value ratio (SUVR) ≥1.42 by Pittsburgh compound-B positron emission tomography (PiB-PET). We used modified Poisson regression models to estimate relative risk (RR), adjusted for age at onset, sex, education, APOE4 status, and duration of follow-up. The results were confirmed with multiple sensitivity analyses, including Cox regression. RESULTS: Of 232 mutation carriers, 108 were PiB-PET-positive at baseline, with 43 (39.8%) meeting criteria for progression after 3.3±2.0 years. Soluble Aβ42 levels were higher among CDR non-progressors than CDR progressors. Higher Aβ42 predicted a lower risk of progression (adjusted RR, 0.36; 95% confidence interval [CI], 0.19-0.67; p = 0.002) better than lower SUVR (RR, 0.81; 95% CI, 0.68-0.96; p = 0.018). CSF Aβ42 levels predicting lower risk of progression increased with higher SUVR levels. CONCLUSION: High CSF Aβ42 levels predict normal cognition in amyloid-positive individuals with AD-causing genetic mutations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".