NOTCH1 genetic variants in patients with tricuspid calcific aortic valve stenosis.
Bibliographic record
Abstract
BACKGROUND AND AIM OF THE STUDY: Calcific aortic valve stenosis (AS) affects 2-5% of the population aged > 65 years. Functional DNA variants at the NOTCH1 locus result in bicuspid aortic valve (BAV) and severe valve calcification. The contribution of these variants to AS in the population with tricuspid aortic valve (TAV) remains to be determined. METHODS: Fourteen genetic variants surrounding the NOTCH1 gene were genotyped, including rare mutations previously reported, and common polymorphisms. The study involved 457 French Canadian patients with severe tricuspid AS. Genotyping was carried out using the Illumina BeadXpress platform. Allele frequencies of common single nucleotide polymorphisms (SNPs) for patients with AS were compared to a shared control group of European ancestry (n = 3,294). In total, 88 ancestry-informative markers were used to correct for population stratification. RESULTS: The mutation R1107X, previously associated with AS and BAV, was identified in a relatively young patient (aged 58 years). The mutations R1279H and V2285I were detected in 18 and 14 heterozygotes, respectively. A common polymorphism (rs13290979) located in intron 2 was significantly associated with AS (p = 0.003), which remained significant after correction for multiple testing. However, this association was no longer significant after accounting for population stratification (p = 0.088). CONCLUSION: In this study, rare functional variants were found in the NOTCH1 gene in a French Canadian population of patients with severe tricuspid AS. This also suggests, for the first time, the presence of a common polymorphism in this gene conferring susceptibility to AS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".