Abstract 15402: A Multi-ethnic Genome Wide Association Study of Aortic Stenosis in the Million Veteran Program Identifies Several Novel Loci
Bibliographic record
Abstract
Introduction: Valvular aortic stenosis (AS) is common with high morbidity and mortality in the absence of surgical intervention, but no current medical therapies are known to prevent or slow disease progression. Previous genetic studies have identified several genetic loci associated with prevalent AS, including LPA and PALMD , although most evidence is limited to populations of European ancestry. Methods: We performed a trans-ethnic genome-wide association study (GWAS) of prevalent AS in the Veterans Administration Million Veteran Program (MVP). Cases were identified by a combination of diagnostic billing and surgical codes and validated by association to the known LPA variant (rs10455872). GWAS was run separately for White, Black, and Hispanic individuals, controlling for age, sex, and six principal components, and combined using fixed effects meta-analysis. Results were limited to variants with a minor allele frequency greater than 1% in the trans-ancestry analysis. Lead independent genome wide significant loci were annotated by nearest gene. Results: 300,182 White, 80,744 Black, and 32,069 Hispanic participants were available for analysis. Of these, there were 12,385 (4.1%) White, 1,444 (1.8%) Black, and 611 (1.9%) Hispanic AS cases. Trans-ethnic analyses identified 10 independent genome wide significant (GWS, p≤5x10 -8 ) loci, replicating 6 known AS genetic loci ( ALPL, PALMD, TEX41, LPA, IL6, FADS1 ), and identifying 4 novel genetic loci ( CEP85L, CELSR2, NCK1, SLMAP ), of which 2 were present at nominal significance in Hispanic ( CELS2R ) or Black ( SLMAP ) individuals. Ethnicity-specific analyses additionally identified 9 novel GWS loci in White individuals, and 3 novel GWS loci in Hispanic individuals. Newly identified loci supported known biological pathways in AS including lipid/metabolic, inflammatory, and calcification, but also implicated new pathways such as those pertaining to QT interval ( SLC35F1 ) and the Brugada Syndrome ( SLMAP ). Conclusions: In this large trans-ethnic GWAS for AS we replicate previously identified genetic loci for AS, and identified several novel loci both in trans-ethnic and in ethnic-specific analyses. These loci implicate known and novel biological mechanisms for future prevention and treatment of AS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".