Trafficking Defect and Proteasomal Degradation Contribute to the Phenotype of a Novel KCNH2 Long QT Syndrome Mutation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".