Identification and Classification of Position-specific GABA<sub>A</sub> Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Understanding the effects of functionally unknown variants in epilepsy associated genes is crucial for elucidating disease pathophysiology and developing personalized therapeutics. With a multiscale framework, spanning from DNA sequence to protein function and neural behavior, we describe a novel approach for predicting and investigating pathogenic mutations, hypothesizing that epileptogenic mutations in the GABAA receptor subunit and nearby predicted mutations may produce similar effects on the CA1 pyramidal neuron model. By exploring the characteristic relationships between predicted pathogenic mutations and proximal epileptogenic mutations, the study aims to estimate the effects of predicted mutations based on the effects of epileptogenic mutations on hippocampal pyramidal neuron simulations. The methodology begins with the collection of GABAA receptor γ2 subunit genetic data, followed by data cleaning and formatting performed in R using a custom script. Next, ensemble predictors will be applied to identify and prioritize the pathogenic missense variants of the γ2 subunit. Mapping a specific pathogenic variant (predicted) to the subunit structural domains shared by epileptogenic mutations will be illustrated, accompanied by molecular modeling of their effects and consideration of evolutionary conservation. Then, variant-specific meta-analysis and parameter normalization will be performed, followed by correlation analysis to identify any significant relationships between predicted mutations and proximal epileptogenic mutations. Using a Python-based neural simulator, multi-compartmental conductance-based neuron model, reflecting the effect of wild-type and epileptogenic mutants will be described. Simulation of neural responses generated by epileptogenic GABAA receptor subtype will be considered for the rough estimation of the predicted pathogenic variants' effect on neural response. To our knowledge, this is the first protocol exploring a multiscale framework to estimate the effects of GABAA receptor variants on neuronal behavior, crucial for epilepsy research. This protocol can serve as a foundation for enhancing predictions of cellular phenotypes caused by potentially pathogenic variants of GABAA receptors associated with epilepsy.