Channelopathies Are a Frequent Cause of Genetic Ataxias Associated with Cerebellar Atrophy
Bibliographic record
Abstract
BACKGROUND: Cerebellar atrophy is a nonspecific imaging finding observed in a number of neurological disorders. Genetic ataxias associated with cerebellar atrophy are a heterogeneous group of conditions, rendering the approach to diagnosis challenging. OBJECTIVES: To define the spectrum of genetic ataxias associated with cerebellar atrophy in a Canadian cohort and the diagnostic yield of exome sequencing for this group of conditions. METHODS: A total of 92 participants from 66 families with cerebellar atrophy were recruited for this multicenter prospective cohort study. Exome sequencing was performed for all participants between 2011 and 2017 as part of 1 of 2 national research programs, Finding of Rare Genetic Disease Genes or Enhanced Care for Rare Genetic Diseases in Canada. RESULTS: A genetic diagnosis was established in 53% of families (35/66). Pathogenic variants were found in 21 known genes, providing a diagnosis for 31/35 families (89%), and in 4 novel genes, accounting for 4/35 families (11%). Of the families, 31/66 (47%) remained without a genetic diagnosis. The most common diagnoses were channelopathies, which were established in 9/35 families (26%). Additional clinical findings provided useful clues to specific diagnoses. CONCLUSIONS: We report on the high frequency of channelopathies as a cause of genetic ataxias associated with cerebellar atrophy and the utility of exome sequencing for this group of conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".