Diversity of ARSACS Mutations in French-Canadians
Bibliographic record
Abstract
BACKGROUND: The growing number of spastic ataxia of Charlevoix-Saguenay (SACS) gene mutations reported worldwide has broadened the clinical phenotype of autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS). The identification of Quebec ARSACS cases without two known SACS mutation led to the development of a multi-modal genomic strategy to uncover mutations in this large gene and explore phenotype variability. METHODS: Search for SACS mutations by combining various methods on 20 cases with a classical French-Canadian ARSACS phenotype without two mutations and a group of 104 sporadic or recessive spastic ataxia cases of unknown cause. Western blot on lymphoblast protein from cases with different genotypes was probed to establish if they still expressed sacsin. RESULTS: A total of 12 mutations, including 7 novels, were uncovered in Quebec ARSACS cases. The screening of 104 spastic ataxia cases of unknown cause for 98 SACS mutations did not uncover carriers of two mutations. Compounds heterozygotes for one missense SACS mutation were found to minimally express sacsin. CONCLUSIONS: The large number of SACS mutations present even in Quebec suggests that the size of the gene alone may explain the great genotypic diversity. This study does not support an expanding ARSACS phenotype in the French-Canadian population. Most mutations lead to loss of function, though phenotypic variability in other populations may reflect partial loss of function with preservation of some sacsin expression. Our results also highlight the challenge of SACS mutation screening and the necessity to develop new generation sequencing methods to ensure low cost complete gene sequencing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".