Aβ inhibits SREBP-2 activation through Akt inhibition
Bibliographic record
Abstract
We previously demonstrated that oligomeric amyloid β 42 (oAβ 42 ) inhibits the mevalonate pathway impairing cholesterol synthesis and protein prenylation. Enzymes of the mevalonate pathway are regulated by the transcription factor SREBP-2. Here, we show that in several neuronal types challenged with oAβ 42 , SREBP-2 activation is reduced. Moreover, SREBP-2 activation is also decreased in the brain cortex of the Alzheimer's disease (AD) mouse model, TgCRND8, suggesting that SREBP-2 may be affected in vivo early in the disease. We demonstrate that oAβ 42 does not affect enzymatic cleavage of SREBP-2 per se, but may impair SREBP-2 transport from the endoplasmic reticulum (ER) to the Golgi. Trafficking of SREBP-2 from the ER to the Golgi requires protein kinase B (Akt) activation. oAβ 42 significantly reduces Akt phosphorylation and this decrease is responsible for the decline in SREBP-2 activation. Overexpression of constitutively active Akt prevents the effect of oAβ 42 on SREBP-2 and the downstream inhibition of cholesterol synthesis and protein prenylation. Our work provides a novel mechanistic link between Aβ and the mevalonate pathway, which will impact the views on issues related to cholesterol, isoprenoids, and statins in AD. We also identify SREBP-2 as an indirect target of Akt in neurons, which may play a role in the cross-talk between AD and diabetes.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".