Disruption of <i><scp>YWHAE</scp></i> gene at 17p13.3 causes learning disabilities and brain abnormalities
Bibliographic record
Abstract
There is a broad phenotypic spectrum of patients with 17p13.3 deletions. One of the most prominent feature is lissencephaly caused by haploinsufficiency of the gene PAFAH1B1. The deletion of this gene and those distal to it, results in Miller-Dieker syndrome, however there have been many reports of patients with haploinsufficiency of the distal genes alone. The deletions of these genes including YWHAE CRK and TUSC5 have been studied extensively and YWHAE has been postulated to be the cause of neurological abnormalities. The patients with deletions of the Miller-Dieker syndrome distal region present with variable clinical features including brain abnormalities, growth retardation, developmental delay, facial dysmorphisms and seizures. While there have been many patients reported to have deletions involving the YWHAE gene along with other genes, here we present the first detailed clinical description of a patient with deletion of YWHAE alone, allowing a more accurate characterization of the pathogenicity of YWHAE haploinsufficiency. The patient reported here demonstrated brain abnormalities, learning disabilities, and seizures supporting the role of YWHAE in these features. We review the literature and use this case report to better characterize and further confirm the genotype-phenotype relationship of the genes within the critical region of Miller-Dieker 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".