A translocation t(6;7)(p11–p12;q22) associated with autism and mental retardation: localization and identification of candidate genes at the breakpoints
Bibliographic record
Abstract
OBJECTIVES: Our aim is to use information from cytogenetic anomalies to identify candidate genes for autism. METHODS: We have identified a male patient with mental retardation and autism who has a balanced translocation involving chromosomes 6 and 7, described as t(6;7)(p11-p12;q22). This translocation was inherited from an apparently normal father. RESULTS: Using fluorescence in situ hybridization, we have localized the breakpoints on both the chromosomes; and using bioinformatic genomic analysis, we have identified a number of potential candidate genes at these loci. These include the neural pentraxin 2 gene, NPTX2, and a novel gene encoding a transmembrane protein, TMEM130, which contains a polycystic kidney domain on 7q22. On 6p12 the breakpoint directly interrupts isoform 2 of the human homologue of the mouse dystonin gene. We also performed a 250 K single nucleotide polymorphism microarray analysis and comparative genomic hybridization using a bacterial artificial chromosome microarray to look for minor genomic deletions or duplications in the proband's DNA. The single nucleotide polymorphism microarray analysis identified a number of copy number variants, remote from the translocation breakpoints, containing potential candidate genes. CONCLUSION: It is conceivable that one or more of the copy number variant regions or either of the two breakpoint locations and the dystonin gene, in particular, may be a new locus for a form of mental retardation, which may also include autistic features.
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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) | 0.000 | 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".