Trafficking Defect and Proteasomal Degradation Contribute to the Phenotype of a Novel KCNH2 Long QT Syndrome Mutation

The Kv11.1 (hERG) K+ channel plays a fundamental role in cardiac repolarization. Missense mutations in KCNH2, the gene encoding Kv11.1, cause long QT syndrome (LQTS) and frequently cause channel trafficking-deficiencies. This study characterized the properties of a novel KCNH2 mutation discovered in a LQT2 patient resuscitated from a ventricular fibrillation arrest. Proband genotyping was performed by SSCP and DNA sequencing. The electrophysiological and biochemical properties of the mutant channel were investigated after expression in HEK293 cells. The proband manifested a QTc of 554 ms prior to electrolyte normalization. Mutation analysis revealed an autosomal dominant frameshift mutation at proline 1086 (P1086fs+32X; 3256InsG). Co-immunoprecipitation demonstrated that wild-type Kv11.1 and mutant channels coassemble. Western blot showed that the mutation did not produce mature complex-glycosylated Kv11.1 channels and coexpression resulted in reduced channel maturation. Electrophysiological recordings revealed mutant channel peak currents to be similar to untransfected cells. Co-expression of channels in a 1∶1 ratio demonstrated dominant negative suppression of peak Kv11.1 currents. Immunocytochemistry confirmed that mutant channels were not present at the plasma membrane. Mutant channel trafficking rescue was attempted by incubation at reduced temperature or with the pharmacological agents E-4031. These treatments did not significantly increase peak mutant currents or induce the formation of mature complex-glycosylated channels. The proteasomal inhibitor lactacystin increased the protein levels of the mutant channels demonstrating proteasomal degradation, but failed to induce mutant Kv11.1 protein trafficking. Our study demonstrates a novel dominant-negative Kv11.1 mutation, which results in degraded non-functional channels leading to a LQT2 phenotype

Trafficking Defect and Proteasomal Degradation Contribute to the Phenotype of a Novel KCNH2 Long QT Syndrome Mutation

The Kv11.1 (hERG) K+ channel plays a fundamental role in cardiac repolarization. Missense mutations in KCNH2, the gene encoding Kv11.1, cause long QT syndrome (LQTS) and frequently cause channel trafficking-deficiencies. This study characterized the properties of a novel KCNH2 mutation discovered in a LQT2 patient resuscitated from a ventricular fibrillation arrest. Proband genotyping was performed by SSCP and DNA sequencing. The electrophysiological and biochemical properties of the mutant channel were investigated after expression in HEK293 cells. The proband manifested a QTc of 554 ms prior to electrolyte normalization. Mutation analysis revealed an autosomal dominant frameshift mutation at proline 1086 (P1086fs+32X; 3256InsG). Co-immunoprecipitation demonstrated that wild-type Kv11.1 and mutant channels coassemble. Western blot showed that the mutation did not produce mature complex-glycosylated Kv11.1 channels and coexpression resulted in reduced channel maturation. Electrophysiological recordings revealed mutant channel peak currents to be similar to untransfected cells. Co-expression of channels in a 1∶1 ratio demonstrated dominant negative suppression of peak Kv11.1 currents. Immunocytochemistry confirmed that mutant channels were not present at the plasma membrane. Mutant channel trafficking rescue was attempted by incubation at reduced temperature or with the pharmacological agents E-4031. These treatments did not significantly increase peak mutant currents or induce the formation of mature complex-glycosylated channels. The proteasomal inhibitor lactacystin increased the protein levels of the mutant channels demonstrating proteasomal degradation, but failed to induce mutant Kv11.1 protein trafficking. Our study demonstrates a novel dominant-negative Kv11.1 mutation, which results in degraded non-functional channels leading to a LQT2 phenotype

Trafficking-deficient hERG K+ channels linked to long QT syndrome are regulated by a microtubule-dependent quality control compartment in the ER

The human ether-a-go-go related gene (hERG) encodes the voltage-gated K+ channel that underlies the rapidly activating delayed-rectifier current in cardiac myocytes. hERG is synthesized in the endoplasmic reticulum (ER) as an “immature” N-linked glycoprotein and is terminally glycosylated in the Golgi apparatus. Most hERG missense mutations linked to long QT syndrome type 2 (LQT2) reduce the terminal glycosylation and functional expression. We tested the hypothesis that a distinct pre-Golgi compartment negatively regulates the trafficking of some LQT2 mutations to the Golgi apparatus. We found that treating cells in nocodazole, a microtubule depolymerizing agent, altered the subcellular localization, functional expression, and glycosylation of the LQT2 mutation G601S-hERG differently from wild-type hERG (WT-hERG). G601S-hERG quickly redistributed to peripheral compartments that partially colocalized with KDEL (Lys-Asp-Glu-Leu) chaperones but not calnexin, Sec31, or the ER golgi intermediate compartment (ERGIC). Treating cells in E-4031, a drug that increases the functional expression of G601S-hERG, prevented the accumulation of G601S-hERG to the peripheral compartments and increased G601S-hERG colocalization with the ERGIC. Coexpressing the temperature-sensitive mutant G protein from vesicular stomatitis virus, a mutant N-linked glycoprotein that is retained in the ER, showed it was not restricted to the same peripheral compartments as G601S-hERG at nonpermissive temperatures. We conclude that the trafficking of G601S-hERG is negatively regulated by a microtubule-dependent compartment within the ER. Identifying mechanisms that prevent the sorting or promote the release of LQT2 channels from this compartment may represent a novel therapeutic strategy for LQT2

Evaluation of Smoking Status Identification Using Electronic Health Records and Open-Text Information in a Large Mental Health Case Register

BACKGROUND:High smoking prevalence is a major public health concern for people with mental disorders. Improved monitoring could be facilitated through electronic health record (EHR) databases. We evaluated whether EHR information held in structured fields might be usefully supplemented by open-text information. The prevalence and correlates of EHR-derived current smoking in people with severe mental illness were also investigated. METHODS:All cases had been referred to a secondary mental health service between 2008-2011 and received a diagnosis of schizophreniform or bipolar disorder. The study focused on those aged over 15 years who had received active care from the mental health service for at least a year (N=1,555). The 'CRIS-IE-Smoking' application used General Architecture for Text Engineering (GATE) natural language processing software to extract smoking status information from open-text fields. A combination of CRIS-IE-Smoking with data from structured fields was evaluated for coverage and the prevalence and demographic correlates of current smoking were analysed. RESULTS:Proportions of patients with recorded smoking status increased from 11.6% to 64.0% through supplementing structured fields with CRIS-IE-Smoking data. The prevalence of current smoking was 59.6% in these 995 cases for whom this information was available. After adjustment, younger age (below 65 years), male sex, and non-cohabiting status were associated with current smoking status. CONCLUSIONS:A natural language processing application substantially improved routine EHR data on smoking status above structured fields alone and could thus be helpful in improving monitoring of this lifestyle behaviour. However, limited information on smoking status remained a challenge