Genetic variants associated with angiotensin-converting enzyme inhibitor-associated angioedema
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to identify genetic variants associated with angiotensin-converting enzyme (ACE) inhibitor-associated angioedema. PARTICIPANTS AND METHODS: We carried out a genome-wide association study in 175 individuals with ACE inhibitor-associated angioedema and 489 ACE inhibitor-exposed controls from Nashville (Tennessee) and Marshfield (Wisconsin). We tested for replication in 19 cases and 57 controls who participated in Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial (ONTARGET). RESULTS: There were no genome-wide significant associations of any single-nucleotide polymorphism (SNP) with angioedema. Sixteen SNPs in African Americans and 41 SNPs in European Americans were associated moderately with angioedema (P<10) and evaluated for association in ONTARGET. The T allele of rs500766 in PRKCQ was associated with a reduced risk, whereas the G allele of rs2724635 in ETV6 was associated with an increased risk of ACE inhibitor-associated angioedema in the Nashville/Marshfield sample and ONTARGET. In a candidate gene analysis, rs989692 in the gene encoding neprilysin (MME), an enzyme that degrades bradykinin and substance P, was significantly associated with angioedema in ONTARGET and Nashville/Marshfield African Americans. CONCLUSION: Unlike other serious adverse drug effects, ACE inhibitor-associated angioedema is not associated with a variant with a large effect size. Variants in MME and genes involved in immune regulation may be associated with ACE inhibitor-associated angioedema.
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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 | 0.000 | 0.001 |
| 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".