Two Loci Affect Angiotensin I–Converting Enzyme Activity in Baboons
Bibliographic record
Abstract
Serum LDL cholesterol (LDLC) concentrations and ACE activities are risk factors for the development of cardiovascular disease (CVD). However, the relationship between ACE and CVD susceptibility, and possible mechanisms of action, is controversial. With data on 622 pedigreed baboons, we used statistical genetic methods to determine the mode of inheritance of ACE activities and its relationship to LDLC on different diets. ACE activity was moderately heritable, and quantitative trait linkage analyses detected a quantitative trait locus (QTL) for ACE activity on the baboon homolog of human chromosome 17 (near the ACE structural locus, maximum multipoint lod=7.5, genomic P=0.000003). Bivariate analyses revealed that ACE activity was genetically correlated (rhoG) with LDLC response (LDLCRC) to a high-cholesterol diet (rhoG=0.30+/-0.13, P=0.01) but not to LDLC on a basal diet (rhoG=0.08+/-0.13). Bivariate genetic analyses indicated that a previously detected QTL for LDLCRC had significant (P=0.025) pleiotropic effects on ACE activity levels and accounted for the genetic correlation. Therefore, we have detected 2 putative loci that affect ACE activity in baboons, one of which also affects LDLC dietary response. The existence of at least 2 genes that affect ACE activity, one of which is diet-responsive, may help explain the lack of consistency among studies of the relationship between ACE and CVD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".