Evaluation of non-synonymous NPPA single nucleotide polymorphisms in atrial fibrillation
Bibliographic record
Abstract
AIMS: Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is an important cause of morbidity and mortality. A genetic mutation in the NPPA gene, which encodes the atrial natriuretic peptide, has been identified as the putative causative factor in a family with an autosomal dominant pattern of inheritance for AF. Two common single nucleotide polymorphisms (SNPs) in NPPA, rs5063 and rs5065, result in amino acid changes of the primary peptide and have been previously implicated in conditions associated with AF, including stroke and hypertension. Recently, the rs5063 SNP has been reported to confer an increased risk of AF development in a Chinese population. We sought to examine the associations of both rs5063 and rs5065 with AF in two separate North American cohorts of European ancestry. METHODS AND RESULTS: Patients with early-onset AF, along with healthy controls, were recruited at the University of Ottawa Heart Institute (UOHI) and the Massachusetts General Hospital (MGH). Study participants were genotyped for rs5063 and rs5065 using a combination of restriction fragment length polymorphism analysis and DNA microarrays. The study genotyped a total of 620 AF cases and 2446 healthy controls. The UOHI arm of the study identified an odds ratio (OR) of 0.72 [95% confidence interval (CI): 0.42-1.24] for rs5063, whereas an OR of 1.33 (95% CI: 0.80-2.21) was observed in the MGH arm. The combined OR approximated unity (OR 0.99; 95% CI: 0.54-1.80). Analysis of rs5065 revealed an OR of 1.12 (95% CI: 0.84-1.48) in UOHI, 1.08 (95% CI 0.80-1.45) in MGH, and 1.10 (95% CI 0.90-1.35) when combined. CONCLUSION: Common non-synonymous genetic variants within NPPA in these two large North American cohorts of European ancestry are not associated with the development of AF.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".