A novel SIGMAR1 missense mutation leads to distal hereditary motor neuropathy phenotype mimicking juvenile ALS: a case report of China
Bibliographic record
Abstract
We present the case of a 16-year-old East Asian Chinese girl with a novel mutation in the SIGMAR1 gene, initially diagnosed as juvenile amyotrophic lateral sclerosis (JALS). At the age of five, she began to exhibit gait abnormalities while walking, a condition that persisted for 4 years until muscle weakness and atrophy emerged, predominantly affecting her distal muscles symmetrically. Electromyography (EMG) initially revealed early abonormal motor conduction, and subsequent examinations indicated neurogenic damage accompanied by localized denervation potentials. Whole-exome sequencing identified compound heterozygous mutations in the SIGMAR1 gene. Throughout the course of her illness, the patient exhibited slow disease progression without cognitive impairment or scoliosis development. We ultimately revised the diagnosis to distal hereditary motor neuropathy (dHMN). This study reports the case of SIGMAR1 new locus mutation leading to dHMN in China, contributing to the expansion of the dHMN genetic database. In our patient, the initial EMG findings indicated issues with neurogenic conduction, followed by a slow progression of the disease. Subsequently, EMG results revealed axonal damage and denervation potentials. These clinical features can easily lead to confusion with JALS. This insight is valuable for improving diagnostic accuracy and understanding the clinical spectrum of dHMN related to SIGMAR1 mutations.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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; 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".