Arginine:glycine amidinotransferase (AGAT) deficiency: Clinical features and long term outcomes in 16 patients diagnosed worldwide
Bibliographic record
Abstract
BACKGROUND: Arginine:glycine aminotransferase (AGAT) (GATM) deficiency is an autosomal recessive inborn error of creative synthesis. OBJECTIVE: We performed an international survey among physicians known to treat patients with AGAT deficiency, to assess clinical characteristics and long-term outcomes of this ultra-rare condition. RESULTS: 16 patients from 8 families of 8 different ethnic backgrounds were included. 1 patient was asymptomatic when diagnosed at age 3 weeks. 15 patients diagnosed between 16 months and 25 years of life had intellectual disability/developmental delay (IDD). 8 patients also had myopathy/proximal muscle weakness. Common biochemical denominators were low/undetectable guanidinoacetate (GAA) concentrations in urine and plasma, and low/undetectable cerebral creatine levels. 3 families had protein truncation/null mutations. The rest had missense and splice mutations. Treatment with creatine monohydrate (100-800 mg/kg/day) resulted in almost complete restoration of brain creatine levels and significant improvement of myopathy. The 2 patients treated since age 4 and 16 months had normal cognitive and behavioral development at age 10 and 11 years. Late treated patients had limited improvement of cognitive functions. CONCLUSION: AGAT deficiency is a treatable intellectual disability. Early diagnosis may prevent IDD and myopathy. Patients with unexplained IDD with and without myopathy should be assessed for AGAT deficiency by determination of urine/plasma GAA and cerebral creatine levels (via brain MRS), and by GATM gene sequencing.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".