Novel pathogenic <i>SMAD2</i> variants in five families with arterial aneurysm and dissection: further delineation of the phenotype
Bibliographic record
Abstract
Background Missense variants in SMAD2, encoding a key transcriptional regulator of transforming growth factor beta signalling, were recently reported to cause arterial aneurysmal disease. Objectives The aims of the study were to identify the genetic disease cause in families with aortic/arterial aneurysmal disease and to further define SMAD2 genotype–phenotype correlations. Methods and results Using gene panel sequencing, we identified a SMAD2 nonsense variant and four SMAD2 missense variants, all affecting highly conserved amino acids in the MH2 domain. The premature stop codon (c.612dup; p.(Asn205*)) was identified in a marfanoid patient with aortic root dilatation and in his affected father. A p.(Asn318Lys) missense variant was found in a Marfan syndrome (MFS)-like case who presented with aortic root aneurysm and in her affected daughter with marfanoid features and mild aortic dilatation. In a man clinically diagnosed with Loeys-Dietz syndrome (LDS) that presents with aortic root dilatation and marked tortuosity of the neck vessels, another missense variant, p.(Ser397Tyr), was identified. This variant was also found in his affected daughter with hypertelorism and arterial tortuosity, as well as his affected mother. The third missense variant, p.(Asn361Thr), was discovered in a man presenting with coronary artery dissection. Variant genotyping in three unaffected family members confirmed its absence. The last missense variant, p.(Ser467Leu), was identified in a man with significant cardiovascular and connective tissue involvement. Conclusion Taken together, our data suggest that heterozygous loss-of-function SMAD2 variants can cause a wide spectrum of autosomal dominant aortic and arterial aneurysmal disease, combined with connective tissue findings reminiscent of MFS and LDS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".