Large Genomic Deletions in<i>AIP</i>in Pituitary Adenoma Predisposition
Bibliographic record
Abstract
CONTEXT: Germline mutations in AIP have been recently shown to cause pituitary adenoma predisposition (PAP). Subsequently, many intragenic germline mutations have been reported, both in familial and in sporadic settings. OBJECTIVE: Our objective was to evaluate the possible contribution of large genomic germline AIP deletions, an important mutation type in tumor predisposition syndromes, in PAP. DESIGN: Here, we applied the multiplex ligation-dependent probe amplification assay to examine whether large genomic AIP or MEN1 alterations account for a subset of PAP cases. PATIENTS: The study was performed on familial and sporadic pituitary adenoma cases of European origin, which had previously tested negative for germline AIP and MEN1 mutations by sequencing. RESULTS: Two of 21 pituitary adenoma families (9.5%) were found to harbor an AIP deletion. No copy number changes were detected among 67 sporadic pituitary adenoma patients. No MEN1 deletions were found. CONCLUSIONS: The present study shows that large genomic AIP deletions account for a subset of PAP. Therefore, in suspected PAP cases undergoing counseling and AIP genetic testing, multiplex ligation-dependent probe amplification could be considered if direct sequencing does not identify a mutation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".