PROJECT SUMMARY Epilepsy is a common neurological disorder that will affect 1 in 26 Americans during their lifetime. There is a range of severity, with developmental and epileptic encephalopathies (DEEs) being among the most severe and medically challenging. DEEs are a heterogenous group of disorders characterized by infant- onset seizures that respond poorly to available treatments, electroencephalographic (EEG) abnormalities, developmental delay/intellectual disability, and elevated mortality risk. DEEs are primarily due to monogenic variants that arise de novo in the affected child. Although each gene-based etiology is rare, collectively the incidence of DEEs is estimated at 1 in 2,000 live births, representing a significant public health burden. Poor response to available treatments is a defining feature of DEEs, representing a significant unmet need for effective therapies. DEEs share overlapping clinical characteristics despite multiple genetic etiologies, suggesting that disruption of final common pathways underlies these phenotypes. Identifying modifier genes that broadly influence epilepsy penetrance and expressivity may reveal these shared pathways. Our previous work showed that modifier genes often modulate function of multiple monogenic DEEs, and these same genes are also implicated as risk genes in common epilepsies with complex genetic basis. In the current study, we propose to identify modifier genes using a newly developed mouse model carrying the human DEE variant KCNB1-p.G379R that was identified as a pathogenic variant associated with developmental delay/intellectual disability, features of autism spectrum disorder, abnormalities in background EEG, and multiple seizure types that responded poorly to available treatments. We recently developed a Kcnb1G379R mouse model that recapitulates core aspects of the clinical phenotype, including spontaneous recurrent seizures, abnormalities in background EEG, and altered neurobehavior. Phenotype severity is dependent on strain background, suggesting a contribution of modifier genes. Based on these observations, we hypothesize that phenotype severity in the Kcnb1G379R DEE model is influenced by genetic modifiers. We will address our central hypothesis in three subaims. First, we will ascertain seizure and EEG phenotype severity in Kcnb1G379R mice on a diverse genetic panel using BxD recombinant inbred strains. Second, we will catalog differences in gene expression between Kcnb1G379R and WT mice on the C57BL/6J and [C57BL/6J]F1 strains. Third, we will integrate information from subaims 1A and 1B by perforning QTL mapping and candidate gene analysis to identify modifier loci and putative candiate genes that influence epilepsy severity. Advancing our understanding of the epilepsy gene network architecture for KCNB1- associated DEE will promote development of targeted therapeutic interventions and has the potential to benefit a broad population of individuals with DEE and other epilepsies.