Altered neurological and neurobehavioral phenotypes in a mouse model of the recurrent KCNB1-p.R306C voltage-sensor variant.
bioRxiv
; 2023 Mar 30.
Article
em En
| MEDLINE
| ID: mdl-37034689
ABSTRACT
Pathogenic variants in KCNB1 are associated with a neurodevelopmental disorder spectrum that includes global developmental delays, cognitive impairment, abnormal electroencephalogram (EEG) patterns, and epilepsy with variable age of onset and severity. Additionally, there are prominent behavioral disturbances, including hyperactivity, aggression, and features of autism spectrum disorder. The most frequently identified recurrent variant is KCNB1-p.R306C, a missense variant located within the S4 voltage-sensing transmembrane domain. Individuals with the R306C variant exhibit mild to severe developmental delays, behavioral disorders, and a diverse spectrum of seizures. Previous in vitro characterization of R306C described loss of voltage sensitivity and cooperativity of the sensor and inhibition of repetitive firing. Existing Kcnb1 mouse models include dominant negative missense variants, as well as knockout and frameshifts alleles. While all models recapitulate key features of KCNB1 encephalopathy, mice with dominant negative alleles were more severely affected. In contrast to existing loss-of-function and dominant-negative variants, KCNB1-p.R306C does not affect channel expression, but rather affects voltage-sensing. Thus, modeling R306C in mice provides a novel opportunity to explore impacts of a voltage-sensing mutation in Kcnb1. Using CRISPR/Cas9 genome editing, we generated the Kcnb1R306C mouse model and characterized the molecular and phenotypic effects. Heterozygous and homozygous R306C mice exhibited pronounced hyperactivity, altered susceptibility to flurothyl and kainic acid induced-seizures, and frequent, long runs of spike wave discharges on EEG. This novel model of channel dysfunction in Kcnb1 provides an additional, valuable tool to study KCNB1 encephalopathies. Furthermore, this allelic series of Kcnb1 mouse models will provide a unique platform to evaluate targeted therapies.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article