A novel mouse model for pyridoxine-dependent epilepsy due to antiquitin deficiency
Bibliographic record
Abstract
Pyridoxine-dependent epilepsy (PDE) is a rare autosomal recessive disease caused by mutations in the ALDH7A1 gene leading to blockade of the lysine catabolism pathway. PDE is characterized by recurrent seizures that are resistant to conventional anticonvulsant treatment but are well-controlled by pyridoxine (PN). Most PDE patients also suffer from neurodevelopmental deficits despite adequate seizure control with PN. To investigate potential pathophysiological mechanisms associated with ALDH7A1 deficiency, we generated a transgenic mouse strain with constitutive genetic ablation of Aldh7a1. We undertook extensive biochemical characterization of Aldh7a1-KO mice consuming a low lysine/high PN diet. Results showed that KO mice accumulated high concentrations of upstream lysine metabolites including ∆1-piperideine-6-carboxylic acid (P6C), α-aminoadipic semialdehyde (α-AASA) and pipecolic acid both in brain and liver tissues, similar to the biochemical picture in ALDH7A1-deficient patients. We also observed preliminary evidence of a widely deranged amino acid profile and increased levels of methionine sulfoxide, an oxidative stress biomarker, in the brains of KO mice, suggesting that increased oxidative stress may be a novel pathobiochemical mechanism in ALDH7A1 deficiency. KO mice lacked epileptic seizures when fed a low lysine/high PN diet. Switching mice to a high lysine/low PN diet led to vigorous seizures and a quick death in KO mice. Treatment with PN controlled seizures and improved survival of high-lysine/low PN fed KO mice. This study expands the spectrum of biochemical abnormalities that may be associated with ALDH7A1 deficiency and provides a proof-of-concept for the utility of the model to study PDE pathophysiology and to test new therapeutics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".