A novel MT-CO2 variant causing cerebellar ataxia and neuropathy: The role of muscle biopsy in diagnosis and defining pathogenicity
Bibliographic record
Abstract
Pathogenic variants in mitochondrial DNA (mtDNA) are associated with significant clinical heterogeneity with neuromuscular involvement commonly reported. Non-syndromic presentations of mtDNA disease continue to pose a diagnostic challenge and with genomic testing still necessitating a muscle biopsy in many cases. Here we describe an adult patient who presented with progressive ataxia, neuropathy and exercise intolerance in whom the application of numerous Mendelian gene panels had failed to make a genetic diagnosis. Muscle biopsy revealed characteristic mitochondrial pathology (cytochrome c oxidase deficient, ragged-red fibers) prompting a thorough investigation of the mitochondrial genome. Two heteroplasmic MT-CO2 gene variants (NC_012920.1: m.7887G>A and m.8250G>A) were identified, necessitating single fiber segregation and familial studies - including the biopsy of the patient's clinically-unaffected mother - to demonstrate pathogenicity of the novel m.7887G>A p.(Gly101Asp) variant and establishing this as the cause of the mitochondrial biochemical defects and clinical presentation. In the era of high throughput whole exome and genome sequencing, muscle biopsy remains a key investigation in the diagnosis of patients with non-syndromic presentations of adult-onset mitochondrial disease and fully defining the pathogenicity of novel mtDNA variants.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".