APP overexpression in the absence of NPC1 exacerbates metabolism of amyloidogenic proteins of Alzheimer's disease
Bibliographic record
Abstract
Amyloid-β (Aβ) peptides originating from β-amyloid precursor protein (APP) are critical in Alzheimer's disease (AD). Cellular cholesterol levels/distribution can regulate production and clearance of Aβ peptides, albeit with contradictory outcomes. To better understand the relationship between cholesterol homeostasis and APP/Aβ metabolism, we have recently generated a bigenic ANPC mouse line overexpressing mutant human APP in the absence of Niemann-Pick type C-1 protein required for intracellular cholesterol transport. Using this unique bigenic ANPC mice and complementary stable N2a cells, we have examined the functional consequences of cellular cholesterol sequestration in the endosomal-lysosomal system, a major site of Aβ production, on APP/Aβ metabolism and its relation to neuronal viability. Levels of APP C-terminal fragments (α-CTF/β-CTF) and Aβ peptides, but not APP mRNA/protein or soluble APPα/APPβ, were increased in ANPC mouse brains and N2a-ANPC cells. These changes were accompanied by reduced clearance of peptides and an increased level/activity of γ-secretase, suggesting that accumulation of APP-CTFs is due to decreased turnover, whereas increased Aβ levels may result from a combination of increased production and decreased turnover. APP-CTFs and Aβ peptides were localized primarily in early-/late-endosomes and to some extent in lysosomes/autophagosomes. Cholesterol sequestration impaired endocytic-autophagic-lysosomal, but not proteasomal, clearance of APP-CTFs/Aβ peptides. Moreover, markers of oxidative stress were increased in vulnerable brain regions of ANPC mice and enhanced β-CTF/Aβ levels increased susceptibility of N2a-ANPC cells to H2O2-induced toxicity. Collectively, our results show that cellular cholesterol sequestration plays a key role in APP/Aβ metabolism and increasing neuronal vulnerability to oxidative stress in AD-related pathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".