Investigating improved diagnosis and treatment of epilepsy-associated genetic variations

Abstract

Recent advances in sequence technology have enabled the rapid identification of genetic variants in childhood epilepsies. Translating this into improved clinical outcomes requires two further scientific developments. First, the ability to accurately and rapidly assign pathogenicity to variants identified with next generation sequencing and secondly, the development of new, precision medicine treatments that targeted the impairment caused by the genetic variant. This thesis critically assesses the potential of two emerging technologies to improve clinical outcomes at genetic variants in epilepsy-associated γ-aminobutyric acid type A (GABAA) receptor variants. Chapter 3 utilizes a modified Bayesian method and tightly defined control datasets to assess three different in silico prediction tools, AlphaMissense, SIFT, and Polyphen-2, and the potential of artificial intelligence (AI) to replace the current ACMG methodology of assigning variant pathogenicity. Chapter 4 assesses the potential of a repurposed drug 4-phenylbutyrate (4-PBA) to increase the surface expression of extrasynaptic GABAA receptors and thus restore tonic currents at individuals with GABAA receptor-associated epilepsies. This analysis shows that the AI program AlphaMissense is an incremental improvement in assigning pathogenicity to GABAA receptor genetic variants rather than a paradigm shift. Results from the Bayesian method imply that the current ACMG criteria is superior at assigning pathogenicity. While 4-PBA is a theoretically promising therapeutic for GABAA receptor epilepsies, we were unable to provide evidence either for or against its development as a therapeutic. While these exciting technologies and novel treatments hold much promise, rigorous empirical analysis will be essential for realizing the promise of these novel methodologies and treatments.

Date of Thesis submission	2025
Original language	English
Awarding Institution	Western Sydney University
Sponsors	Australian Government Research Training Program Scholarship
Supervisor	Sam Merlin (Supervisor) & Nathan Absalom (Supervisor)