Identification of a novel mutation in pseudohypoparathyroidism type Ia in a Chinese family
Bibliographic record
Abstract
INTRODUCTION: Pseudohypoparathyroidism (PHP) indicates a group of rare disorders characterized by end-organ resistance to various hormones, primarily parathyroid hormone (PTH). One of its most common type is PHP-Ia, which is caused by maternally inherited inactivating mutations in GNAS. In this report, we present a Chinese girl with typical features of PHP-Ia and a novel mutation of the GNAS gene. PATIENT CONCERNS: A 9-year-old Chinese girl presented with recurrent epileptic seizure. DIAGNOSIS: Biochemical and imaging findings were consistent with PHP-Ia, including typical Albright hereditary osteodystrophy phenotype (short stature, round face, brachydactyly, and mild mental retardation), PTH resistance (hypocalcemia, hyperphosphatemia, elevated serum PTH, and multiple intracranial calcification) and thyroid stimulating hormone resistance (elevated serum thyroid stimulating hormone). INTERVENTIONS: The patient was given 1α-hydroxylated vitamin D (calcitriol, 0.5 ug/d), calcium carbonate and vitamin D3 tablets (1.5 g/d, including 600 mg calcium and 125 IU vitamin D3). DNA analysis of the GNAS gene was performed for the whole family. OUTCOMES: Investigation of the GNAS gene revealed a novel mutation c.313delG (p.Glu105Lysfs*7) in the patient, as well as her mother. So the diagnosis of PHP-Ia was confirmed. CONCLUSION: The study further expands the spectrum of known GNAS mutations associated with PHP and lay emphasis on the genetic analysis of GNAS gene for identifying genetic abnormalities as well as making diagnosis and differentiation of various subtypes of PHP.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".