Novel α1 and γ2 GABA<sub>A</sub> receptor subunit mutations in families with idiopathic generalized epilepsy
Bibliographic record
Abstract
Epilepsy is a heterogeneous neurological disease affecting approximately 50 million people worldwide. Genetic factors play an important role in both the onset and severity of the condition, with mutations in several ion-channel genes being implicated, including those encoding the GABA(A) receptor. Here, we evaluated the frequency of additional mutations in the GABA(A) receptor by direct sequencing of the complete open reading frame of the GABRA1 and GABRG2 genes from a cohort of French Canadian families with idiopathic generalized epilepsy (IGE). Using this approach, we have identified three novel mutations that were absent in over 400 control chromosomes. In GABRA1, two mutations were found, with the first being a 25-bp insertion that was associated with intron retention (i.e. K353delins18X) and the second corresponding to a single point mutation that replaced the aspartate 219 residue with an asparagine (i.e. D219N). Electrophysiological analysis revealed that K353delins18X and D219N altered GABA(A) receptor function by reducing the total surface expression of mature protein and/or by curtailing neurotransmitter effectiveness. Both defects would be expected to have a detrimental effect on inhibitory control of neuronal circuits. In contrast, the single point mutation identified in the GABRG2 gene, namely P83S, was indistinguishable from the wildtype subunit in terms of surface expression and functionality. This finding was all the more intriguing as the mutation exhibited a high degree of penetrance in three generations of one French Canadian family. Further experimentation will be required to understand how this mutation contributes to the occurrence of IGE in these individuals.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".