Exome Sequencing Identifies <i>SMAD3</i> Mutations as a Cause of Familial Thoracic Aortic Aneurysm and Dissection With Intracranial and Other Arterial Aneurysms
Bibliographic record
Abstract
RATIONALE: Thoracic aortic aneurysms leading to acute aortic dissections (TAAD) can be inherited in families in an autosomal dominant manner. As part of the spectrum of clinical heterogeneity of familial TAAD, we recently described families with multiple members that had TAAD and intracranial aneurysms or TAAD and intracranial and abdominal aortic aneurysms inherited in an autosomal dominant manner. OBJECTIVE: To identify the causative mutation in a large family with autosomal dominant inheritance of TAAD with intracranial and abdominal aortic aneurysms by performing exome sequencing of 2 distantly related individuals with TAAD and identifying shared rare variants. METHODS AND RESULTS: A novel frame shift mutation, p. N218fs (c.652delA), was identified in the SMAD3 gene and segregated with the vascular diseases in this family with a logarithm of odds score of 2.52. Sequencing of 181 probands with familial TAAD identified 3 additional SMAD3 mutations in 4 families, p.R279K (c.836G>A), p.E239K (c.715G>A), and p.A112V (c.235C>T), resulting in a combined logarithm of odds score of 5.21. These 4 mutations were notably absent in 2300 control exomes. SMAD3 mutations were recently described in patients with aneurysms osteoarthritis syndrome and some of the features of this syndrome were identified in individuals in our cohort, but these features were notably absent in many SMAD3 mutation carriers. CONCLUSIONS: SMAD3 mutations are responsible for 2% of familial TAAD. Mutations are found in families with TAAD alone, along with families with TAAD, intracranial aneurysms, abdominal aortic and bilateral iliac aneurysms segregating in an autosomal dominant manner.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".