Biochemical and molecular predictors for prognosis in nonketotic hyperglycinemia
Bibliographic record
Abstract
OBJECTIVE: Nonketotic hyperglycinemia is a neurometabolic disorder characterized by intellectual disability, seizures, and spasticity. Patients with attenuated nonketotic hyperglycinemia make variable developmental progress. Predictive factors have not been systematically assessed. METHODS: We reviewed 124 patients stratified by developmental outcome for biochemical and molecular predictive factors. Missense mutations were expressed to quantify residual activity using a new assay. RESULTS: Patients with severe nonketotic hyperglycinemia required multiple anticonvulsants, whereas patients with developmental quotient (DQ) > 30 did not require anticonvulsants. Brain malformations occurred mainly in patients with severe nonketotic hyperglycinemia (71%) but rarely in patients with attenuated nonketotic hyperglycinemia (7.5%). Neonatal presentation did not correlate with outcome, but age at onset ≥ 4 months was associated with attenuated nonketotic hyperglycinemia. Cerebrospinal fluid (CSF) glycine levels and CSF:plasma glycine ratio correlated inversely with DQ; CSF glycine > 230 μM indicated severe outcome and CSF:plasma glycine ratio ≤ 0.08 predicted attenuated outcome. The glycine index correlated strongly with outcome. Molecular analysis identified 99% of mutant alleles, including 96 novel mutations. Mutations near the active cleft of the P-protein maintained stable protein levels. Presence of 1 mutation with residual activity was necessary but not sufficient for attenuated outcome; 2 such mutations conferred best outcome. Divergent outcomes for the same genotype indicate a contribution of other genetic or nongenetic factors. INTERPRETATION: Accurate prediction of outcome is possible in most patients. A combination of 4 factors available neonatally predicted 78% of severe and 49% of attenuated patients, and a score based on mutation severity predicted outcome with 70% sensitivity and 97% specificity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".