Is ApoE ɛ 4 a good biomarker for amyloid pathology in late onset Alzheimer’s disease?
Bibliographic record
Abstract
Amyloid plaques are pathological hallmarks of Alzheimer's Disease (AD) and biomarkers such as cerebrospinal fluid (CSF) β-amyloid 1-42 (Aβ1-42) and amyloid positron emission tomographic (PET) imaging are important in diagnosing amyloid pathology in vivo. ɛ4 allele of the Apolipoprotein E gene (ApoE ɛ 4), which is a major genetic risk factor for late onset AD, is an important genetic biomarker for AD pathophysiology. It has been shown that ApoE ɛ 4 is involved in Aβ deposition and formation of amyloid plaques. Studies have suggested the utility of peripheral blood ApoE ɛ 4 in AD diagnosis and risk assessment. However it is still a matter of debate whether ApoE ɛ 4 status would improve prediction of amyloid pathology and represent a cost-effective alternative to amyloid PET or CSF Aβ in resource-limited settings in late onset AD. Recent research suggest that the mean prevalence of PET amyloid-positivity is 95% in ApoE ɛ 4-positive AD patients. This short review aims to provide an updated information on the relationship between ApoE ɛ 4 and amyloid biomarkers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".