Diffuse angiopathy in Adams‐Oliver syndrome associated with truncating <i>DOCK6</i> mutations
Bibliographic record
Abstract
Adams-Oliver syndrome (AOS) is a rare malformation syndrome characterized by the presence of two anomalies: aplasia cutis congenita of the scalp and transverse terminal limb defects. Many affected individuals also have additional malformations, including a variety of intracranial anomalies such as periventricular calcification in keeping with cerebrovascular microbleeds, impaired neuronal migration, epilepsy, and microcephaly. Cardiac malformations can be present, as can vascular dysfunction in the forms of cutis marmorata telangiectasia congenita, pulmonary vein stenoses, and abnormal hepatic microvasculature. Elucidated genetic causes include four genes in different pathways, leading to a model of AOS as a multi-pathway disorder. We identified an infant with mild aplasia cutis congenita and terminal transverse limb defects, developmental delay and a severe, diffuse angiopathy with incomplete microvascularization. Whole-genome sequencing documented two rare truncating variants in DOCK6, a gene associated with a type of autosomal recessive AOS that recurrently features periventricular calcification and impaired neurodevelopment. We highlight an unexpectedly high frequency of likely deleterious mutations in this gene in the general population, relative to the rarity of the disease, and discuss possible explanations for this discrepancy.
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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 | 0.000 |
| 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".