FGF14 (GAA∙TTC) repeat expansion-related ataxia SCA27B is common in Northern Finland
Bibliographic record
Abstract
Introduction An intronic repeat expansion (GAA∙TTC) exp in the FGF14 gene ( FGF14 (GAA∙TTC) exp ) has recently been found to cause dominantly inherited ataxia SCA27B. The core phenotype consists of late-onset and slowly progressing ataxia with down-beat nystagmus and episodic features. Disease penetrance depends on the number of repeat units and ≥ 300 is widely used pathogenic threshold for complete penetrance. The Finnish population is genetically unique and SCA27B has not previously been reported in Finland. Methods We investigated FGF14 (GAA∙TTC) exp in a cohort of 96 Finnish patients with suspected hereditary ataxia or ataxia of unknown etiology, of whom 62 patients had no previous genetic diagnosis. We also assessed FGF14 (GAA∙TTC) exp in 561 controls in order to estimate its population prevalence in North Ostrobothnia. Results We found five patients with FGF14 (GAA∙TTC) ≥250 giving a frequency of 5.2 % in the ataxia cohort. One patient had a rare biallelic genotype. Four patients had the classical SCA27B phenotype with no atypical features. Two of the patients had a previous genetic diagnosis and digenic contribution could not be excluded. Moreover, we found one patient with suspected FGF14 disease and with (GAA∙TTC) 248 , but the segregation analysis remained inconclusive. The (GAA∙TTC) ≥250 frequency was 2.7 % in the general population. Population prevalence was 1.7 per 100 000 in North Ostrobothnia. The frequency of alleles harboring 200‒249 repeats was 2.2 % in patients and 1.5 % in controls. Conclusion Our results suggest that screening of FGF14 expansion should be carried out in Finnish patients with suspected hereditary ataxia or ataxia of unknown etiology.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".