Investigating Divergent Disease Severity in Human Neuronal Models of KCNQ2-Related Developmental and Epilepsy Disorders

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Mutations in KCNQ2 encoding voltage-gated K+ (KV7.2) channel are associated with monogenic early-onset childhood epilepsies with overlapping characteristics but divergent clinical severity. The clinical spectrum of KCNQ2-related epilepsy disorders ranges from autosomal-dominant Benign Familial Neonatal Seizures (BFNS) to sporadic cases of severe Developmental and Epileptic Encephalopathy (DEE). Mutations in KCNQ2 account for approximately 5% of all mutations identified in genetic epilepsy and 10% of those associated with early-onset epilepsy. The mechanisms that drive the differential severity between BFNS and DEE cases are poorly understood. Currently 30% of all epilepsy patients are completely refractory to any existing anti-epileptic treatments and there are no treatments for the lifelong developmental and physical disabilities associated with DEE. Thus, addressing this overarching question can facilitate development of novel and targeted therapeutic strategies. Studies using heterologous expression systems and mouse models have provided many advances in our understanding of KCNQ2-related epilepsies, but fail to account for some of the sources of phenotypic variation associated with cellular and network-level development of the human brain. As a result of these limitations there is a fundamental need to develop more human-relevant model systems for epilepsy. Recent advances in the generation of human patient-specific induced pluripotent stem cells (hiPSCs) have allowed patient somatic cells to be reprogrammed to pluripotency and differentiated into neurons. Thus, the present proposal seeks to take advantage of these technologies to address how stable mutations in KCNQ2 affect: 1) intrinsic and network excitability in specific human neuronal subtypes and 2) electrophysiological maturation and plasticity of complex neuronal networks to determine whether these properties are altered in a disease-severity specific manner. Here, we will use an established patient-specific iPSC-based platform to determine how BFNS and DEE variants differentially impact human neurons using patch-clamp electrophysiology and multi-electrode array (MEA) techniques.