RFC1 repeat expansions in downbeat nystagmus syndromes: frequency and phenotypic profile
Bibliographic record
Abstract
OBJECTIVES: The cause of downbeat nystagmus (DBN) remains unknown in a substantial number of patients ("idiopathic"), although intronic GAA expansions in FGF14 have recently been shown to account for almost 50% of yet idiopathic cases. Here, we hypothesized that biallelic RFC1 expansions may also represent a recurrent cause of DBN syndrome. METHODS: We genotyped the RFC1 repeat and performed in-depth phenotyping in 203 patients with DBN, including 65 patients with idiopathic DBN, 102 patients carrying an FGF14 GAA expansion, and 36 patients with presumed secondary DBN. RESULTS: Biallelic RFC1 AAGGG expansions were identified in 15/65 patients with idiopathic DBN (23%). None of the 102 GAA-FGF14-positive patients, but 2/36 (6%) of patients with presumed secondary DBN carried biallelic RFC1 expansions. The DBN syndrome in RFC1-positive patients was characterized by additional cerebellar impairment in 100% (15/15), bilateral vestibulopathy (BVP) in 100% (15/15), and polyneuropathy in 80% (12/15) of cases. Compared to GAA-FGF14-positive and genetically unexplained patients, RFC1-positive patients had significantly more frequent neuropathic features on examination and BVP. Furthermore, vestibular function, as measured by the video head impulse test, was significantly more impaired in RFC1-positive patients. DISCUSSION: Biallelic RFC1 expansions are a common monogenic cause of DBN syndrome.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 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".