Genetic Variants in the SCN9A Gene are Detected in a Minority of Erythromelalgia Patients
Bibliographic record
Abstract
Gain-of-function variants in the voltage-gated sodium channel Nav1.7, encoded by the SCN9A gene, have previously been identified in patients with erythromelalgia, a clinical diagnosis defined by intermittent attacks of painful, hot, swollen, and red skin, predominantly involving the hands and feet. Symptoms are induced or aggravated by warming and relieved by cooling. In primary erythromelalgia there is no known underlying disease. This study investigated the frequency of SCN9A variants in a cohort of primary erythromelalgia patients collected at a single centre, and examined the clinical signs and symptoms associated with identified variants. One hundred patients with possible erythromelalgia were collected prospectively and evaluated by clinical examination. Thirty-five patients fulfilling the clinical criteria of primary erythromelalgia were screened for variants in SCN9A. Five were found to carry likely causal variants, including a variant found in 2 related individuals and a variant not previously described in patients with erythromelalgia. The clinical findings differed significantly between the patients. Overall, in this cohort only 4/34 (11.7%) of unrelated patients had erythromelalgia likely caused by gain-of-function variants in SCN9A. Variants in SCN9A are therefore likely to cause or contribute to primary erythromelalgia in only a small proportion of patients.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".