Differences in Alzheimer’s Disease–Related Pathology Profiles Across Apolipoprotein Groups
Bibliographic record
Abstract
The apolipoprotein (APOE) ɛ4 allele is a risk factor for Alzheimer's disease (AD), whereas the ɛ2 allele is thought to be protective against AD. Few studies have examined the relationship between brain pathologies, atrophy, white matter hyperintensities (WMHs) and APOE status in those with the ɛ2ɛ4 genotype and results are inconsistent for those with an ɛ2 allele. Alzheimer's disease neuroimaging participants were divided into 1 of 4 APOE allele profiles (E4 = ɛ4ɛ4 or ɛ3ɛ4; E2 = ɛ2ɛ2 or ɛ2ɛ3; E3 = ɛ3ɛ3; or E24 = ɛ2ɛ4). Linear mixed models examined the relationship between APOE profiles and brain changes (i.e., regional WMHs, ventricle size, hippocampal and entorhinal cortex volume, amyloid level, and phosphorylated tau measures), while controlling for age, sex, education, and diagnostic status at baseline and over time. APOE ɛ4 was associated with increased pathology, whereas ɛ2 positivity is associated with reduced baseline and lower accumulation of pathologies and neurodegeneration. APOE ɛ2ɛ4 was similar to ɛ4 (increased neurodegeneration) but with a slower rate of change. The strong associations observed between APOE and pathology show the importance of how genetic factors influence structural brain changes. These findings suggest that ɛ2ɛ4 genotype is related to increased declines associated with the ɛ4 as opposed to the protective effects of the ɛ2. These findings have important implications for initiating treatments and interventions. Given that people with the ɛ2ɛ4 genotype can expect to have increased atrophy, they should be considered (alongside those with an ɛ4) in targeted interventions to reduce brain changes that occur with 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".