Compound Heterozygous Mutations of SACS in a Korean Cohort Study of Charcot-Marie-Tooth Disease Concurrent Cerebellar Ataxia and Spasticity
Bibliographic record
Abstract
Mutations in the SACS gene are associated with autosomal recessive spastic ataxia of Charlevoix-Saguenay disease (ARSACS) or complex clinical phenotypes of Charcot-Marie-Tooth disease (CMT). This study aimed to identify SACS mutations in a Korean CMT cohort with cerebellar ataxia and spasticity. As a result, eight pathogenic SACS mutations in four families were identified as the underlying causes of these complex phenotypes. The prevalence of CMT families with SACS mutations was determined to be 0.3%. All the patients showed sensory, motor, and gait disturbances with increased deep tendon reflexes. Lower limb magnetic resonance imaging (MRI) was done in four patients, and all had fatty replacements. Of note, they all had similar fatty infiltrations between the proximal and distal lower limb muscles, different from the neuromuscular imaging feature in most CMT patients without SACS mutations who had distal dominant fatty involvement. Therefore, these findings were considered a characteristic feature in CMT patients with SACS mutations. Although further studies with more cases are needed, our results highlight lower extremity MRI findings in CMT patients with SACS mutations and broaden the clinical spectrum. We suggest screening for SACS in recessive CMT patients with complex phenotypes of ataxia and spasticity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".