Annals of Neurology · 2019 · 69 citations · 32 references
Natural SciencesNeurobiologyNeuroscienceElectrophysiologyIon Channel BiophysicsMolecular NeuroscienceChannelopathiesIon Channel DisordersIon Channel DisruptionIon Channel ExpressionIon Channel PhysiologyIon ChannelsIon Channel Voltage DependenceMolecular Gating MechanismsPotassium Channel GenesPotassium Channel PhysiologyPotassium ChannelopathiesVoltage-gated Ion Channel DisordersVoltage-gated Potassium Channel DisordersVoltage-gated Potassium Channels
Objective Pathogenic variants in KCNB1 , encoding the voltage‐gated potassium channel K V 2.1, are associated with developmental and epileptic encephalopathy (DEE). Previous functional studies on a limited number of KCNB1 variants indicated a range of molecular mechanisms by which variants affect channel function, including loss of voltage sensitivity, loss of ion selectivity, and reduced cell‐surface expression. Methods We evaluated a series of 17 KCNB1 variants associated with DEE or other neurodevelopmental disorders (NDDs) to rapidly ascertain channel dysfunction using high‐throughput functional assays. Specifically, we investigated the biophysical properties and cell‐surface expression of variant K V 2.1 channels expressed in heterologous cells using high‐throughput automated electrophysiology and immunocytochemistry–flow cytometry. Results Pathogenic variants exhibited diverse functional defects, including altered current density and shifts in the voltage dependence of activation and/or inactivation, as homotetramers or when coexpressed with wild‐type K V 2.1. Quantification of protein expression also identified variants with reduced total K V 2.1 expression or deficient cell‐surface expression. Interpretation Our study establishes a platform for rapid screening of K V 2.1 functional defects caused by KCNB1 variants associated with DEE and other NDDs. This will aid in establishing KCNB1 variant pathogenicity and the mechanism of dysfunction, which will enable targeted strategies for therapeutic intervention based on molecular phenotype. ANN NEUROL 2019;86:899–912
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