Microdeletion in distal 17p13.1: A recognizable phenotype with microcephaly, distinctive facial features, and intellectual disability
Bibliographic record
Abstract
Array comparative genomic hybridization has led to the identification of new syndromes by identifying genomic imbalances not detectable by standard karyotyping methods and by allowing correlations with physical findings. Deletions in the 17p13.1 region have been reported in patients with dysmorphic features and developmental delay but a consistent phenotype has yet to emerge. This report describes two unrelated patients with a characteristic phenotype associated with overlapping de novo deletions in the distal region of 17p13.1 detected with array comparative genomic hybridization and confirmed by real-time PCR. These patients share remarkably similar clinical features including microcephaly, mild developmental delay, generalized joint laxity, and a body posture with knee and elbow flexion and hands held in midline. They have distinctive facial features which include long midface with retrognathia with overbite, and protruding ears. The deletions in both patients are the smallest ever reported in this region (approximately 252 and 219 kb). The overlapping region contains 18 genes. Various isolated deletions of the 17p13.1 region have been reported previously without delineation of a consistent phenotype. We propose that the described microdeletions in the distal portion of 17p13.1 represent a novel microdeletion syndrome.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".