Deletion 17q12 Is a Recurrent Copy Number Variant that Confers High Risk of Autism and Schizophrenia
Bibliographic record
Abstract
Autism spectrum disorders (ASD) and schizophrenia are neurodevelopmental disorders for which recent evidence indicates an important etiologic role for rare copy number variants (CNVs) and suggests common genetic mechanisms. We performed cytogenomic array analysis in a discovery sample of patients with neurodevelopmental disorders referred for clinical testing. We detected a recurrent 1.4 Mb deletion at 17q12, which harbors HNF1B, the gene responsible for renal cysts and diabetes syndrome (RCAD), in 18/15,749 patients, including several with ASD, but 0/4,519 controls. We identified additional shared phenotypic features among nine patients available for clinical assessment, including macrocephaly, characteristic facial features, renal anomalies, and neurocognitive impairments. In a large follow-up sample, the same deletion was identified in 2/1,182 ASD/neurocognitive impairment and in 4/6,340 schizophrenia patients, but in 0/47,929 controls (corrected p = 7.37 × 10⁻⁵). These data demonstrate that deletion 17q12 is a recurrent, pathogenic CNV that confers a very high risk for ASD and schizophrenia and show that one or more of the 15 genes in the deleted interval is dosage sensitive and essential for normal brain development and function. In addition, the phenotypic features of patients with this CNV are consistent with a contiguous gene syndrome that extends beyond RCAD, which is caused by HNF1B mutations only.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.000 |
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".