Pharmacogenomic study of heart failure and candesartan response from the CHARM programme
Bibliographic record
Abstract
ABSTRACT Aims The Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity (CHARM) programme consisted of three parallel, randomised, double-blind clinical trials comparing candesartan with placebo in patients with heart failure (HF) categorised according to left ventricular ejection fraction and tolerability to an ACE inhibitor. We conducted a pharmacogenomic study of the CHARM studies to identify genetic predictors of heart failure progression and the efficacy and safety of treatment with candesartan. Methods We performed genome-wide association studies (GWAS) with the composite endpoint of cardiovascular death or hospitalisation for heart failure in 2727 patients from CHARM-Overall and stratified by CHARM study according to preserved and reduced ejection fraction. The safety endpoints were hyperkalaemia, renal dysfunction, hypotension, and change in systolic blood pressure. We also conducted a genome-wide gene-level collapsing analysis from whole-exome sequencing data with the composite cardiovascular endpoint. Results We found the genetic variant rs66886237 at 8p21.3 near the gene GFRA2 to be associated with the composite cardiovascular endpoint in 1029 HF patients with preserved ejection fraction from the CHARM-Preserved study [hazard ratio (HR): 1.91, 95% confidence interval (CI): 1.55-2.35; P=1.7×10 -9 ], but not in patients with reduced ejection fraction. None of the GWAS for candesartan safety or efficacy passed the significance threshold. Conclusions We have identified a candidate genetic variant potentially predictive of the progression of heart failure in patients with preserved ejection fraction. The findings require further replication and we cannot exclude the possibility that the results may be chance findings.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".