Phenotypes and genotypes of mitochondrial aminoacyl‐tRNA synthetase deficiencies from a single neurometabolic clinic
Bibliographic record
Abstract
Abstract Mitochondrial aminoacyl‐tRNA synthetases play a major role in protein translation, synthesis, and oxidative phosphorylation. We reviewed all patients diagnosed with mitochondrial aminoacyl‐tRNA synthetase deficiencies diagnosed in a single neurometabolic clinic. We report five patients with mitochondrial aminoacyl‐tRNA synthetase deficiencies including DARS2, EARS2, PARS2, and RARS2 deficiencies. Siblings with DARS2 deficiency presented with global developmental delay within the first year of life. DARS2, EARS2, PARS2, and RARS2 deficiencies were identified by whole exome sequencing. We report coagulation factor abnormalities in PARS2 deficiency for the first time. We also report symmetric increased signal intensity in globus pallidi in FLAIR images in brain MRI in EARS2 deficiency for the first time. One patient with RARS2 deficiency had compound heterozygous variants in RARS2. One of those variants was an intronic variant. We confirmed the pathogenicity by mRNA studies. Mitochondrial aminoacyl‐tRNA synthetase deficiencies are diagnosed by molecular genetic investigations. Clinically available non‐invasive biochemical investigations are non‐specific for the diagnosis of mitochondrial aminoacyl‐tRNA synthetase deficiencies. A combination of brain MRI features and molecular genetic investigations should be undertaken to confirm the diagnosis of mitochondrial aminoacyl‐tRNA synthetase deficiencies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".