Accurate prediction of gain- and loss-of-function missense variants in GABA_A receptors

Missense variants in genes encoding GABA_A receptors are involved in the pathophysiology of common and rare epilepsies. Variant effects on channel biophysical function are associated with key clinical characteristics and treatment response. Predicting variant effects is therefore key to improving care for individuals with GABA_A receptor-related disorders.

We collected data from 505 affected individuals with 272 (likely) pathogenic GABA_A receptor missense variants (GABRA1, GABRB2, GABRB3, GABRG2). All variants were evaluated with in-vitro electrophysiology. Variants were annotated with features based on sequence, structure, and phenotype. Model performance was estimated using cross-validation and external validation on a further 197 individuals with 138 (likely) pathogenic variants.

Our models enable highly accurate prediction of missense variant effects in GABA_A (AU-ROC 0.862-0.946), outperforming state-of-the-art models (AU-ROC 0.495-0.756) and clinical decision-making. Model scores correlated with GABA sensitivity and were consistent with expert-based structure-function hypotheses, supporting plausibility. Predictions on population variants were similar to functionally neutral variants, while cases from ClinVar were similar to GOF/LOF variants. Our model may provide additional evidence for 5-25% of variants in ClinVar. Lastly, we show that we can predict likely clinical characteristics from variant information alone (median Lin similarity 0.754 IQR 0.161).

We demonstrate accurate missense variant effect prediction in GABA_A receptors with rigorous validation across a large dataset of functionally tested variants. These predictions may facilitate timely diagnosis and precision treatment of individuals with GABA_A receptor-related disorders, pending prospective clinical validation. A web interface, precomputed scores, and calibrated score thresholds for all possible variants are openly available.

Else Kröner-Fresenius-Stiftung; German Federal Ministry of Research, Technology and Space; German Research Foundation; Medical Faculty University of Tübingen; Lundbeck Foundation; Novo Nordisk Foundation.