Apolipoprotein E (ApoE) 4 exacerbates pattern separation deficits and amyloid pathology in a combined humanized knock‐in Apolipoprotein E, Amyloid, and Tau model of Alzheimer's Disease
Bibliographic record
Abstract
Abstract Background Cognitive deficits in Alzheimer's Disease (AD) are attributed to neuronal network disruptions associated with amyloid β and hyperphosphorylated tau aggregates. Pattern separation, the ability to store and differentiate between similar experiences, is linked to hippocampal function. Pattern separation shows increasing impairment with AD progression. Apolipoprotein E (ApoE) 4 is a significant genetic risk factor for AD, associated with earlier onset, more severe pathology, and cognitive deficits. It is unclear how ApoE4 may interact with AD pathology to affect hippocampal function and pattern separation. This study uses humanized mouse models combining ApoE (3 or 4), App (App, App NL , App NL‐F ), and MAPT (tau) to evaluate the interaction of these factors on pattern separation and amyloid pathology. Method Pattern separation was assessed using the automated touchscreen location discrimination (LD) task at ages 6, 9, 12, and 16 months in both male and female mice. Hippocampal amyloid pathology was quantified at the same timepoints using biochemical and immunofluorescence. Results Whereas AppApoE3 and ApoE4 mice presented no difference in LD performance at 6 months of age, App NL ApoE4 and App NL‐F ApoE4 mice demonstrated poorer performance than their ApoE3 counterparts at all ages. When comparing App NL and App NL‐F groups, App NL‐F ApoE4 mice exhibited the poorest performance in comparison to the other groups at all ages. App mice showed no signs of amyloid pathology. App NL ApoE3 and App NL ApoE4 mice showed no significant difference in insoluble Aβ 42 , and no plaques were detected. In contrast, App NL‐F ApoE4 mice displayed increased Aβ 42 concentrations compared to App NL‐F ApoE3, and also presented increased plaque pathology up to 16 months of age. Conclusion These results suggest even minor changes in amyloid processing (in App NL mice) seem to synergize with ApoE4 as a driving mechanism of pattern separation deficits, detectable as early as 6 months old. This effect seems to be independent of insoluble amyloid accumulation, which was significantly increased in the hippocampus only after 9 months. Ongoing work examines whether soluble amyloid oligomers and ApoE4's direct impact on neurogenesis contribute to the pattern separation deficits. Nonetheless, we observed a reproducible deficit in LD performance in these mice compatible with early pattern separation deficits.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".