Association Between Angiotensin-Converting Enzyme and Alzheimer Disease
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting enzyme has been reported to show altered activity in patients with neurologic diseases. An insertion-deletion polymorphism in ACE has recently been linked to heart disease, cerebrovascular disease, and AD. OBJECTIVE: To determine whether the angiotensin-converting enzyme (ACE) is associated with risk of Alzheimer disease (AD). METHODS: We investigated the ACE polymorphism as a potential risk factor for AD in 151 patients with AD and 206 ethnically matched controls from Russia and in 236 patients with AD and 169 controls from North America by means of allele association methods and logistic regression. RESULTS: None of the ACE genotypes was associated with increased susceptibility to AD in the total sample or in subsets stratified by apolipoprotein E gene (APOE) epsilon4 status. However, the D allele was more frequent among AD cases between ages 66 and 70 years compared with controls in both the Russian (P = .02) and North American (P = .001) datasets. In this age group, the effect of D (odds ratio, 11.2; 95% confidence interval, 2.9-44.0) appeared to be independent of and equal or greater in magnitude to the effect of APOE epsilon4 (odds ratio, 7.8; 95% confidence interval, 3.5-7.4). CONCLUSIONS: Our results suggest that APOE and ACE genotypes may be independent risk factors for late-onset AD, but the ACE association needs to be confirmed in independent samples in which the time and extent of vascular cofactors can be assessed.
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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 | 0.002 |
| 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) | 0.002 | 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".