Combined pituitary hormone deficiency in Australian children: clinical and genetic correlates
Bibliographic record
Abstract
OBJECTIVE: Mutations in the gene for the POU domain transcription factor POU1F1 (human Pit-1) have been reported in patients with GH, TSH and PRL deficiencies. PROP1 (Prophet of Pit-1) gene mutations also cause gonadotrophin deficiencies and in some cases partial ACTH deficiency. This study analyses the POU1F1 and PROP1 genes in a cohort of Australian children with combined pituitary hormone deficiency (CPHD) and correlates results with patient phenotype. PATIENTS AND DESIGN: Genomic analysis was carried out on 33 patients with CPHD referred from centres around Australia. Clinical data were collected from medical records and referring physicans. RESULTS: POU1F1 mutations were identified in two of four patients with a suggestive phenotype. In a female patient, novel compound heterozygous POU1F1 mutations were identified: Arg143Leu in exon 3 and Leu194Gln in exon 4. This patient presented with failure to thrive at 6 weeks of age and has deficiencies of TSH and GH. A previously described heterozygous Arg271Trp mutation in exon 6 of the POU1F1 gene was identified in a female infant who presented with growth failure and was diagnosed with TSH then GH deficiencies. No PROP1 mutations were identified; however, we describe a number of previously unreported PROP1 polymorphisms. No patients presenting with deficiencies of all anterior pituitary hormones early in life had POU1F1 or PROP1 gene mutations. CONCLUSIONS: In 33 Australian children with CPHD we have identified POU1F1 mutations in two patients and no PROP1 mutations. We speculate that in the majority of children other genes must be responsible for the CPHD phenotype.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".