Biophysical and structural insights into the SCN4A E452K variant linked to myotonia and paramyotonia congenita
Bibliographic record
Abstract
Myotonia and paramyotonia congenita (PC) are rare neuromuscular disorders characterized by muscle stiffness that intensifies in cold environments. These disorders are associated with variants in the SCN4A gene, that encodes the alpha subunit of the voltage-gated sodium channel Nav1.4. We report here the case of a 36-year-old female who experiences diverse neurological symptoms, including myotonia, cold induced myotonia, resulting in muscle stiffness, and tightness. A whole exome sequencing revealed a missense variant in the SCN4A gene at position c.1354G > A, named p.E452K. We characterized the biophysical properties of this SCN4A variant by overexpressing the wild-type (WT) and mutant channels with the β1 regulatory subunit in HEK293 cells by transfection. Sodium currents were recorded at different temperatures and different extracellular potassium concentrations using the patch-clamp technique. Functional studies of the E452K variant revealed both loss and gain of function phenotypes at different temperatures, which were characterized by a decrease in current density and an increase in the window current. This was related to the shift of inactivation toward more depolarized voltages at both 22 °C and 10 °C and a slower slope factor of activation at 22 °C. A further gain-of-function effect was also observed, which was characterized by a faster onset and recovery from slow inactivation. MD simulation of the alpha subunit in a lipid bilayer suggested that the charge reversal destabilized a native salt bridge (E452-K249). We concluded that the observed enhanced functionality facilitates the activation process, leading to enhanced muscle excitability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".