Document Type
Article
Publication Date
1-26-2024
Manuscript Version
vor
Abstract
Variants in the genes encoding gamma-aminobutyric acid type A (GABAA) receptor subunits are associated with epilepsy. To date, over 1000 clinical variants have been identified in these genes. However, the majority of these variants lack functional studies and their clinical significance is uncertain although accumulating evidence indicates that proteostasis deficiency is the major disease-causing mechanism. Here, we apply two state-of-the-art modeling tools, namely AlphaMissense and Rhapsody to predict the pathogenicity of saturating missense variants in genes that encode the major subunits of GABAA receptors in the central nervous system, including GABRA1, GABRB2, GABRB3, and GABRG2. We demonstrate that the predicted pathogenicity correlates well between AlphaMissense and Rhapsody. In addition, AlphaMissense pathogenicity score correlates modestly with plasma membrane expression, peak current amplitude, and GABA potency of the variants that have available experimental data. Furthermore, almost all annotated pathogenic variants in the ClinVar database are successfully identified from the prediction, whereas uncertain variants from ClinVar partially due to the lack of experimental data are differentiated into different pathogenicity groups. The pathogenicity prediction of GABAA receptor missense variants provides a resource to the community as well as guidance for future experimental and clinical investigations.
Keywords
epilepsy, GABA receptors A, ion channels, pathogenicity, proteostasis
Publication Title
Israel Journal of Chemistry
Grant
R01NS105789
Rights
© 2024 The Authors. Israel Journal of Chemistry published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Y.-J. Wang, G. H. Vu, T.-W. Mu, Isr. J. Chem. 2024, 64, e202300161. https://doi.org/10.1002/ijch.202300161