ROBO4 variants predispose individuals to bicuspid aortic valve and thoracic aortic aneurysm
Bibliographic record
Abstract
Bicuspid aortic valve (BAV) is a common congenital heart defect (population incidence, 1–2%)1–3 that frequently presents with ascending aortic aneurysm (AscAA)4. BAV/AscAA shows autosomal dominant inheritance with incomplete penetrance and male predominance. Causative gene mutations (for example, NOTCH1, SMAD6) are known for ≤1% of nonsyndromic BAV cases with and without AscAA5–8, impeding mechanistic insight and development of therapeutic strategies. Here, we report the identification of variants in ROBO4 (which encodes a factor known to contribute to endothelial performance) that segregate with disease in two families. Targeted sequencing of ROBO4 showed enrichment for rare variants in BAV/AscAA probands compared with controls. Targeted silencing of ROBO4 or mutant ROBO4 expression in endothelial cell lines results in impaired barrier function and a synthetic repertoire suggestive of endothelial-to-mesenchymal transition. This is consistent with BAV/AscAA-associated findings in patients and in animal models deficient for ROBO4. These data identify a novel endothelial etiology for this common human disease phenotype. Individuals with biscuspid aortic valve and ascending aortic aneurysm show enrichment of rare variants in ROBO4. Functional studies suggest that ROBO4 mutations disrupt endothelial cell performance and contribute to pathological remodeling of aortic tissues.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".