Novel Genetic Variants Expand the Functional, Molecular, and Pathological Diversity of KCNA1 Channelopathy.

The KCNA1 gene encodes Kv1.1 voltage-gated potassium channel α subunits, which are crucial for maintaining healthy neuronal firing and preventing hyperexcitability. Mutations in the KCNA1 gene can cause several neurological diseases and symptoms, such as episodic ataxia type 1 (EA1) and epilepsy, which may occur alone or in combination, making it challenging to establish simple genotype-phenotype correlations. Previous analyses of human KCNA1 variants have shown that epilepsy-linked mutations tend to cluster in regions critical for the channel's pore, whereas EA1-associated mutations are evenly distributed across the length of the protein. In this review, we examine 17 recently discovered pathogenic or likely pathogenic KCNA1 variants to gain new insights into the molecular genetic basis of KCNA1 channelopathy. We provide the first systematic breakdown of disease rates for KCNA1 variants in different protein domains, uncovering potential location biases that influence genotype-phenotype correlations. Our examination of the new mutations strengthens the proposed link between the pore region and epilepsy and reveals new connections between epilepsy-related variants, genetic modifiers, and respiratory dysfunction. Additionally, the new variants include the first two gain-of-function mutations ever discovered for KCNA1, the first frameshift mutation, and the first mutations located in the cytoplasmic N-terminal domain, broadening the functional and molecular scope of KCNA1 channelopathy. Moreover, the recently identified variants highlight emerging links between KCNA1 and musculoskeletal abnormalities and nystagmus, conditions not typically associated with KCNA1. These findings improve our understanding of KCNA1 channelopathy and promise to enhance personalized diagnosis and treatment for individuals with KCNA1-linked disorders.

Microelectrode Array Recording of Sinoatrial Node Firing Rate to Identify Intrinsic Cardiac Pacemaking Defects in Mice.

The sinoatrial node (SAN), located in the right atrium, contains the pacemaker cells of the heart, and dysfunction of this region can cause tachycardia or bradycardia. Reliable identification of cardiac pacemaking defects requires the measurement of intrinsic heart rates by largely preventing the influence of the autonomic nervous system, which can mask rate deficits. Traditional methods to analyze intrinsic cardiac pacemaker function include drug-induced autonomic blockade to measure in vivo heart rates, isolated heart recordings to measure intrinsic heart rates, and sinoatrial strip or single-cell patch-clamp recordings of sinoatrial pacemaker cells to measure spontaneous action potential firing rates. However, these more traditional techniques can be technically challenging and difficult to perform. Here, we present a new methodology to measure intrinsic cardiac firing rate by performing microelectrode array (MEA) recordings of whole-mount sinoatrial node preparations from mice. MEAs are composed of multiple microelectrodes arranged in a grid-like pattern for recording in vitro extracellular field potentials. The method described herein has the combined advantage of being relatively faster, simpler, and more precise than previous approaches for recording intrinsic heart rates, while also allowing easy pharmacological interrogation.

Clinical Spectrum of KCNA1 Mutations: New Insights into Episodic Ataxia and Epilepsy Comorbidity.

Mutations in the KCNA1 gene, which encodes voltage-gated Kv1.1 potassium channel α-subunits, cause a variety of human diseases, complicating simple genotype-phenotype correlations in patients. KCNA1 mutations are primarily associated with a rare neurological movement disorder known as episodic ataxia type 1 (EA1). However, some patients have EA1 in combination with epilepsy, whereas others have epilepsy alone. KCNA1 mutations can also cause hypomagnesemia and paroxysmal dyskinesia in rare cases. Why KCNA1 variants are associated with such phenotypic heterogeneity in patients is not yet understood. In this review, literature databases (PubMed) and public genetic archives (dbSNP and ClinVar) were mined for known pathogenic or likely pathogenic mutations in KCNA1 to examine whether patterns exist between mutation type and disease manifestation. Analyses of the 47 deleterious KCNA1 mutations that were identified revealed that epilepsy or seizure-related variants tend to cluster in the S1/S2 transmembrane domains and in the pore region of Kv1.1, whereas EA1-associated variants occur along the whole length of the protein. In addition, insights from animal models of KCNA1 channelopathy were considered, as well as the possible influence of genetic modifiers on disease expressivity and severity. Elucidation of the complex relationship between KCNA1 variants and disease will enable better diagnostic risk assessment and more personalized therapeutic strategies for KCNA1 channelopathy.