Screening for SCA27B in a cohort of Brazilian patients with unsolved ataxias
Bibliographic record
Abstract
Spinocerebellar Ataxia 27B (SCA27B) is a recently described autosomal dominant neurodegenerative disease, prevalent in Europe and North America, but not yet properly investigated in Latin America. It is caused by a heterozygous trinucleotide repeat expansion (GAA) >300 in FGF14 gene. Since it is an expansion disorder, diagnosis requires specific molecular techniques. In this scenario, the aim of this study is to screen a large cohort of adults with unsolved ataxias for SCA27B. To date, 108 patients with ataxia were recruited, including patients negative for SCA1,2,3,6,7 and 8. DNA was extracted from peripheral blood and analyzed using different PCR techniques. Initially, long-range PCR (LR-PCR) was used to exclude patients with two alleles within the normal repeat range, 90 patients were negative for FGF14 expansion and eighteen patients showing only one allele in normal size range. Repeat-primed PCR was carried out to identify the expansion and in five out of the 18 analyzed patients the expansion pattern was detected (4.6%). The phenotype was a late-onset slowly progressive ataxia in all cases, with paroxysmal symptoms in 3/5 and pyramidal signs in 1/5. None of them had sensory manifestations. The mean age at onset was 55 years. Our results are consistent with previous publications, which showed that SCA27B ataxia presents initial symptoms at an advanced age and has slow progression. The prevalence of SCA27B we found (4.6%) was much smaller than in French Canadian (61%) and European (18%) cohorts. In conclusion, LR-PCR followed by RP-PCR is a reliable and fast approach to diagnose SCA27B. The phenotype of Brazilian patients with SCA27B is similar to previous reports, however considering that most of the patients included in this study have unsolved ataxia, often with distinct clinical manifestation, the frequency is much smaller. Further studies are needed to understand the genetic epidemiology of this new disease beyond Europe and North America.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".