Distinct Functional Alterations and Therapeutic Options of Two Pathological De Novo Variants of the T292 Residue of GABRA1 Identified in Children with Epileptic Encephalopathy and Neurodevelopmental Disorders
Bibliographic record
Abstract
Mutations of GABAAR have reportedly led to epileptic encephalopathy and neurodevelopmental disorders. We have identified a novel de novo T292S missense variant of GABRA1 from a pediatric patient with grievous global developmental delay but without obvious epileptic activity. This mutation coincidentally occurs at the same residue as that of a previously reported GABRA1 variant T292I identified from a pediatric patient with severe epilepsy. The distinct phenotypes of these two patients prompted us to compare the impacts of the two mutants on the receptor function and to search for suitable therapeutics. In this study, we used biochemical techniques and patch-clamp recordings in HEK293 cells overexpressing either wild-type or mutated rat recombinant GABAARs. We found that the α1T292S variant significantly increased GABA-evoked whole-cell currents, shifting the dose–response curve to the left without altering the maximal response. In contrast, the α1T292I variant significantly reduced GABA-evoked currents, shifting the dose–response curve to the right with a severely diminished maximum response. Single-channel recordings further revealed that the α1T292S variant increased, while the α1T292I variant decreased the GABAAR single-channel open time and open probability. Importantly, we found that the T292S mutation-induced increase in GABAAR function could be fully normalized by the negative GABAAR modulator thiocolchicoside, whereas the T292I mutation-induced impairment of GABAAR function was largely rescued with a combination of the GABAAR positive modulators diazepam and verapamil. Our study demonstrated that α1T292 is a critical residue for controlling GABAAR channel gating, and mutations at this residue may produce opposite impacts on the function of the receptors. Thus, the present work highlights the importance of functionally characterizing each individual GABAAR mutation for ensuring precision medicine.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".