Assessing the Effect of Combined Humanization of Apolipoprotein E, Amyloid and Tau on Cognition and Alzheimer’s Disease Pathology
Bibliographic record
Abstract
Abstract Background Apolipoprotein E (ApoE) exhibits isoform‐specific interactions with Alzheimer’s disease (AD)‐related pathology. In comparison with the more common ApoE3 isoform, ApoE4 promotes amyloid‐β (Aβ) deposition, enhances tau‐mediated neurodegeneration and inflammation. However, the lack of appropriate preclinical models has limited the ability to evaluate the potential synergistic effect of Aβ, tau and ApoE on cognition and disease progression. To overcome this, we developed new mouse models harbouring humanized variants of the ApoE genotypes (ApoE3 or ApoE4), hApp (AppNL or AppNL‐F) and hMAPT (tau) and evaluated whether the interaction among these AD‐related factors influence cognition, brain structure, and pathological load. Method An array of biochemical and imaging techniques including single‐nuclei (sn)RNA sequencing, magnetic resonance imaging (MRI), immunofluorescence microscopy, and Western blots were performed. Attentional demand was assessed, using the cross‐species Continuous Performance Task, an automated touchscreen test. Result Preliminary results indicate that AppNL‐F (ApoE3 or ApoE4), but not AppNL (ApoE3 or ApoE4) mice presented plaque pathology and insoluble Aβ. Moreover, increased levels of insoluble Aβ, plaque burden, plaque size and neuroinflammation were observed in the cortex of AppNL‐F ApoE4 mice in comparison to AppNL‐F ApoE3 at 9 and 12 months of age. At 16 months of age AppNL‐F ApoE3 and ApoE4 mice showed similar levels of insoluble Aβ. In vivo 9.4T MRI analyses indicated reduced grey matter volume in fronto‐cortical regions of AppNL‐F ApoE4 mice when compared to controls. snRNA sequencing also indicated a reduction of excitatory neurons in the cortex and upregulation of gliosis related genes and astrocytic populations at 9 months in AppNL‐F ApoE4 mice. Attentional deficits were observed on the CPT as early as 6 months of age in AppNL‐F ApoE4 mice that were maintained at 9 and 12 months of age. Conclusion Results from this project provide new insights into how amyloid, ApoE, and tau conspire to trigger and accelerate disease progression. We show that amyloid interacts with both ApoE3 and ApoE4 to drive degeneration, but in that the rate of this progression is faster in the ApoE4 background. Our findings also demonstrate that cognitive deficits are detectable much earlier than expected, in putative pre‐plaque stages of disease.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".