APOEε4 associates with microglial activation independently of Aβ plaques and tau tangles.
Bibliographic record
Abstract
Animal studies suggest that the apolipoprotein E ε4 (APOEε4) allele is a culprit of early microglial activation in Alzheimer's disease (AD). Here, we tested the association between APOEε4 status and microglial activation in living individuals across the aging and AD spectrum. We studied 118 individuals with positron emission tomography for amyloid-β (Aβ; [18F]AZD4694), tau ([18F]MK6240), and microglial activation ([11C]PBR28). We found that APOEε4 carriers presented increased microglial activation relative to noncarriers in early Braak stage regions within the medial temporal cortex accounting for Aβ and tau deposition. Furthermore, microglial activation mediated the Aβ-independent effects of APOEε4 on tau accumulation, which was further associated with neurodegeneration and clinical impairment. The physiological distribution of APOE mRNA expression predicted the patterns of APOEε4-related microglial activation in our population, suggesting that APOE gene expression may regulate the local vulnerability to neuroinflammation. Our results support that the APOEε4 genotype exerts Aβ-independent effects on AD pathogenesis by activating microglia in brain regions associated with early tau deposition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".