<i>De novo</i> variants of <i>NALCN</i> differentially impact both the phenotypic spectrum of patients and the biophysical properties of the NALCN current
Bibliographic record
Abstract
Abstract The Na + leak channel NALCN regulates the resting membrane potential and consequently cell excitability of several cell types, including neurons. Studies of animal models demonstrated that NALCN is involved in fundamental physiological functions such as respiratory rhythm, circadian rhythm, sleep, locomotor behavior and pain perception. Pathogenic variants of NALCN have been associated with ultra-rare developmental disorders characterized by a wide range of symptoms with variable severity. We and others previously showed that pathogenic variants of NALCN can be categorized in 2 groups. The first group corresponds to inherited biallelic loss-of-function variants with patients suffering from the IHPRF1 syndrome (OMIM #615419). The second one corresponds to de novo gain-of-function variants that cause the CLIFAHDD syndrome (OMIM #616266). In this study, we provide a standardized phenotypic description of a large group of 35 individuals with de novo pathogenic variants of NALCN . In addition, we performed functional studies of several of these variants using the patch clamp technique in a recombinant system. We highlight a large heterogeneity in terms of both expressed symptoms and their severity. By contrast with previous reports only showing a pure gain-of-function effect of de novo pathogenic variants, we found that de novo variants of NALCN differentially impact the biophysical properties of the NALCN current and likely influence cell excitability. To conclude, de novo variants of NALCN differentially impact the biophysical properties of the NALCN current. We hypothesize that this may at least partly explain the phenotypic diversity observed in patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".