Epilepsy-associated genes: an update

Case report: A founder UGDH variant associated with developmental epileptic encephalopathy in Saudi Arabia

Congenital disorders of glycosylation (CDG) are a group of more than 100 rare genetic disorders characterized by impaired glycosylation of proteins and lipids. The clinical presentation of CDG varies tremendously, from single-organ to multi-organ involvement and from prenatal death to a normal adult phenotype. In this case study, we report a large consanguineous family with multiple children suffering from cerebral palsy, seizure, developmental and epileptic encephalopathy, and global developmental delay. Whole-exome sequencing (WES) analysis revealed a homozygous variant in the UDP-glucose dehydrogenase (UGDH) gene (c.950G>A; p.R317Q) which segregates with the familial phenotype with a plausible autosomal recessive mode of inheritance, indicating a potential disease-causing association. The UGDH gene encodes the UDP-glucose dehydrogenase, a key enzyme in the synthesis of specific extracellular matrix constituents (proteoglycans and glycolipids) involved in neural migration and connectivity during early brain development. Many pathogenic mutations of UGDH have been reported in recent literature works. However, the variant identified in this study has been observed only in the Saudi population (13 families) and not in any other ethnic background, suggesting that it may be an ancient founder mutation.

Pathogenicity Prediction of GABA A Receptor Missense Variants

Variants in the genes encoding the subunits of gamma-aminobutyric acid type A (GABA A ) receptors 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 for GABA A receptor variants. Here, we apply two state-of-the-art modeling tools, namely AlphaMissense, which uses an artificial intelligence-based approach based on AlphaFold structures, and Rhapsody, which integrates sequence evolution and known structure-based data, to predict the pathogenicity of saturating missense variants in genes that encode the major subunits of GABA A receptors in the central nervous system, including GABRA1 , GABRB2 , GABRB3 , and GABRG2 . Our results demonstrate that the predicted pathogenicity correlates well between AlphaMissense and Rhapsody although AlphaMissense tends to generate higher pathogenic probability. Furthermore, almost all annotated pathogenic variants in the ClinVar clinical 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 GABA A receptor missense variants provides a resource to the community as well as guidance for future experimental and clinical investigations.