Identification of Alzheimer’s disease–associated rare coding variants in the ECE2 gene
Bibliographic record
Abstract
Accumulation of amyloid β protein (Aβ) due to increased generation and/or impaired degradation plays an important role in Alzheimer's disease (AD) pathogenesis. In this report, we describe the identification of rare coding mutations in the endothelin-converting enzyme 2 (ECE2) gene in 1 late-onset AD family, and additional case-control cohort analysis indicates ECE2 variants associated with the risk of developing AD. The 2 mutations (R186C and F751S) located in the peptidase domain in the ECE2 protein were found to severely impair the enzymatic activity of ECE2 in Aβ degradation. We further evaluated the effect of the R186C mutation in mutant APP-knockin mice. Overexpression of wild-type ECE2 in the hippocampus reduced amyloid load and plaque formation, and improved learning and memory deficits in the AD model mice. However, the effect was abolished by the R186C mutation in ECE2. Taken together, the results demonstrated that ECE2 peptidase mutations contribute to AD pathogenesis by impairing Aβ degradation, and overexpression of ECE2 alleviates AD phenotypes. This study indicates that ECE2 is a risk gene for AD development and pharmacological activation of ECE2 could be a promising strategy for AD treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".