The role of rare genetic variants in aortic valve stenosis
Bibliographic record
Abstract
Calcific aortic valve stenosis (CAVS) is a severe and common cardiovascular disease, affecting 2 to 5% of individuals aged 65 and up.There is currently no pharmaceutical treatment for CAVS, making valve replacement the only option.A partial explanation for this is that our understanding of the genetic basis of CAVS is limited.The role of rare genetic variants in CAVS has not been investigated, despite the fact that rare variants typically have stronger effect sizes than common variants and are known to play a role in other cardiovascular diseases.The research presented in this thesis assesses the role of rare variants in CAVS.Targeted and exome-wide analyses of rare variant associations with CAVS were conducted in multiple cohorts of European and Quebecois ancestry.An investigation was also conducted into the association with CAVS of clonal hematopoiesis of indeterminate potential (CHIP), an emerging risk factor for multiple cardiovascular diseases caused by rare/low-frequency somatic mutations in progenitor blood cells.Exome-wide significant associations with CAVS were identified for 53 variants, 48 of which are rare (minor allele frequency < 0.01).In single-variant and targeted analyses, genes containing rare variants that associated with CAVS included SMC2, where common variants were previously associated with CAVS, and PCSK6, associated with lipoprotein metabolism, as well as several genes involved in congenital cardiovascular disease, diverse calcium-related phenotypes, and thrombotic pathways.Multiple lipid-related pathways identified by pathway enrichment analysis are consistent with previous common variation studies, and also suggest that rare variants affect the same etiological pathways.CHIP analyses replicated known associations with heart failure and atherosclerotic cardiovascular disease, but did not identify significant associations with CAVS after correction for multiple testing.Several CHIP genetic risk scores were constructed from publicly available data, but were also not significantly associated with CAVS.The identification of novel rare variants in several genes is supported by previous work, including GWAS, and confirms that the genetic architecture of CAVS includes both common and rare variants and furthers our understanding of its etiology.The results presented here highlight the breadth of calcium pathways likely involved in CAVS and suggest that the role of
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".