Comparative Risks of Initial Aortic Events Associated With Genetic Thoracic Aortic Disease
Bibliographic record
Abstract
BACKGROUND: Pathogenic variants in 11 genes predispose individuals to heritable thoracic aortic disease (HTAD), but limited data are available to stratify the risk for aortic events associated with these genes. OBJECTIVES: This study sought to compare the risk of first aortic event, specifically thoracic aortic aneurysm surgery or an aortic dissection, among 7 HTAD genes and variant types within each gene. METHODS: A retrospective cohort of probands and relatives with rare variants in 7 genes for HTAD (n = 1,028) was assessed for the risk of first aortic events based on the gene altered, pathogenic variant type, sex, proband status, and location of recruitment. RESULTS: Significant differences in aortic event risk were identified among the smooth muscle contraction genes (ACTA2, MYLK, and PRKG1; P = 0.002) and among the genes for Loeys-Dietz syndrome, which encode proteins in the transforming growth factor (TGF)-β pathway (SMAD3, TGFB2, TGFBR1, and TGFBR2;P < 0.0001). Cumulative incidence of type A aortic dissection was higher than elective aneurysm surgery in patients with variants in ACTA2, MYLK, PRKG1, and SMAD3; in contrast, patients with TGFBR2 variants had lower cumulative incidence of type A aortic dissection than elective aneurysm surgery. Cumulative incidence of type B aortic dissection was higher for ACTA2, PRKG1, and TGFBR2 than other genes. After adjusting for proband status, sex, and recruitment location, specific variants in ACTA2 and TGFBR2 were associated with substantially higher risk of aortic event with childhood onset. CONCLUSIONS: Gene- and variant-specific data on aortic events in individuals with HTAD support personalized aortic surveillance and clinical management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".