Inhibition of BACE1 affected both its Aβ producing and degrading activities and increased Aβ42 and Aβ40 levels at high-level BACE1 expression
Bibliographic record
Abstract
The beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) is the predominant β-secretase, cleaving the amyloid precursor protein (APP) via the amyloidogenic pathway. In addition, BACE1 as an amyloid degrading enzyme (ADE), cleaves Aβ to produce the C-terminally truncated non-toxic Aβ fragment Aβ34 which is an indicator of amyloid clearance. Here, we analyzed the effects of BACE1 inhibitors on its opposing enzymatic functions, i.e., amyloidogenic (Aβ producing) and amyloidolytic (Aβ degrading) activities, using cell culture models with varying BACE1/APP ratios. Under high-level BACE1 expression, low-dose inhibition unexpectedly yielded a two-fold increase in Aβ42 and Aβ40 levels. The concomitant decrease in Aβ34 and secreted APPβ levels suggested that the elevated Aβ42 and Aβ40 levels were due to the attenuated Aβ degrading activity of BACE1. Notably, the amyloidolytic activity of BACE1 was impeded at lower BACE1 inhibitor concentrations compared to its amyloidogenic activity, thereby suggesting that the Aβ degrading activity of BACE1 was more sensitive to inhibition than its Aβ producing activity. Under endogenous BACE1 and APP levels, "low-dose" BACE1 inhibition affected both the Aβ producing and degrading activities of BACE1, i.e., significantly increased Aβ42/Aβ40 ratio and decreased Aβ34 levels, respectively. Further, we incubated recombinant BACE1 with synthetic Aβ peptides and found that BACE1 has a higher affinity for Aβ substrates over APP. In summary, our results suggest that stimulating BACE1's ADE activity and halting Aβ production without decreasing Aβ clearance could still be a promising therapeutic approach with new, yet to be developed, BACE1 modulators.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".