FHF1 (FGF12) epileptic encephalopathy
Bibliographic record
Abstract
Voltage-gated sodium channels (Navs) are mainstays of neuronal function, and mutations in the genes encoding CNS Navs (Nav1.1 [ SCN1A ], Nav1.2 [ SCN2A ], Nav1.3 [ SCN3A ], and Nav1.6 [ SCN8A ]) are causes of some of the most common and severe genetic epilepsies and epileptic encephalopathies (EE).1 Fibroblast-growth-factor homologous factors (FHFs) compose a family of 4 proteins that interact with the C-terminal tails of Navs to modulate the channels' fast, and long-term, inactivations.2 FHF2 mutation is a rare cause of generalized epilepsy with febrile seizures plus (GEFS+).3 Recently, a de novo FHF1 mutation (p.R52H) was reported in early-onset EE in 2 siblings.4 We report 3 patients from unrelated families with the same FHF1 p.R52H mutation. The 5 cases together frame the FHF1 R52H EE from infancy to adulthood. As discussed below, this gain-of-function disease may be amenable to personalized therapy. Acknowledgment: The study has UK Research Ethics Committee's approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12 granted by the Republic of Ireland REC). The research team acknowledges the support of the National Institute for Health Research through the Comprehensive Clinical Research Network, the Health Innovation Challenge Fund (grant HICF-1009-003), and the Wellcome Trust Sanger Institute (grant WT098051). BAM holds the University of Toronto Michael Bahen Chair in Epilepsy Research. The authors thank the Next Generation Sequencing/bioinformatics teams at McGill University, the Genome Quebec Innovation Center, the Réseau de Médecine Génétique Appliquée, and Drs. Ledia Brunga (DNA sample management); Dipayan Mitra (MRI); Ms. Gail Charlton (EEG); and Ms. Sylvia Dobrzeniecka (sequencing) for their efforts.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".