Clinical and electrophysiologic features of CMT2A with mutations in the mitofusin 2 gene
Bibliographic record
Abstract
BACKGROUND: Axonal neuropathy linked to the CMT2A locus was originally associated with a mutation in the KIF1B gene. However, mutations in this gene have not been described associated with any other CMT2A families. Recently, mutations in the MFN2 gene, encoding the mitochondrial GTPase mitofusin 2 (Mfn2), have been identified as causative of CMT2A in seven families. The authors report three additional CMT2A families associated with novel mutations in highly conserved regions of the Mfn2 GTPase domain. METHODS: The authors performed a standardized neuromuscular and nerve conduction examination, genotyped known CMT loci, and analyzed the MFN2 gene by direct sequencing in three pedigrees and 10 additional probands affected by axonal CMT. RESULTS: Sequencing of the MFN2 gene revealed a novel mutation in each family (c.818T>G, c.638T>C, and c.314C>T). The largest family demonstrated an age-independent variable expression such that approximately one quarter of individuals with the mutation presented with features mild enough as to remain occult even with electrophysiologic evaluation. CONCLUSION: These results confirm that the majority of cases of CMT linked to the CMT2A locus are due to MFN2 mutations. The phenotype is largely indistinguishable from KIF1B-related CMT and from CMT2E and CMT2F. At least in some families, as many as 25% of individuals with MFN2 mutations may be asymptomatic and have a normal electrophysiologic examination, although a detailed neuromuscular examination may suggest the trait. Given the frequency of MFN2 mutations among CMT2 probands (3/13, or 23%), genetic testing of CMT2 patients should begin with a screen of the MFN2 gene.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".