CACNA1A Mutation in a EA-2 Patient Responsive to Acetazolamide and Valproic Acid
Bibliographic record
Abstract
BACKGROUND: Episodic ataxia type-2 (EA-2) is an autosomal dominant neurological disorder that has been shown to result from mutations in the CACNA1A gene encoding the P/Q-type calcium channel. Affected individuals experience episodes of cerebellar ataxia usually associated with migraine symptoms, interictal nystagmus, mild residual and in some cases a progressive cerebellar incoordination and respond to acetazolamide treatment. We identified a patient with a positive family history for episodic ataxia, who was originally diagnosed with epilepsy and treated with valproic acid. Subsequent examination revealed that the symptoms were consistent with a diagnosis of EA-2. The patient responded positively to a combination of acetazolamide and valproic acid. Molecular genetic analysis of the CACNA1A gene was performed in order to confirm a diagnosis of EA-2. METHODS: The CACNA1A gene was evaluated for mutations using single strand conformational polymorphism analysis and direct DNA sequencing. Allele specific oligo hybridization was used to confirm that the mutation was segregating with only affected family members and was not present in the control group. RESULTS: In this study we identified a new missense mutation in exon 12 of the CACNA1A gene from a patient with EA-2 whose symptoms could be controlled with a combination of acetazolamide and valproic acid. This G to A transition changes a highly conserved glutamic acid residue to a lysine residue in domain II S2 of the P/Q-type calcium channel alpha1A subunit. CONCLUSIONS: The use of valproic acid in treating patients with EA-2 is not well documented. Here we describe a patient with a novel mutation in the CACNA1A gene who responded positively to a combination of acetazolamide and valproic acid.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| 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".