Spectrum of mutations in<i>mut</i>methylmalonic acidemia and identification of a common Hispanic mutation and haplotype
Bibliographic record
Abstract
Cobalamin nonresponsive methylmalonic acidemia (MMA, mut complementation class) results from mutations in the nuclear gene MUT, which codes for the mitochondrial enzyme methylmalonyl CoA mutase (MCM). To better elucidate the spectrum of mutations that cause MMA, the MUT gene was sequenced in 160 patients with mut MMA. Sequence analysis identified mutations in 96% of disease alleles. Mutations were found in all coding exons, but predominantly in exons 2, 3, 6, and 11. A total of 116 different mutations, 68 of which were novel, were identified. Of the 116 different mutations, 53% were missense mutations, 22% were deletions, duplications or insertions, 16% were nonsense mutations, and 9% were splice-site mutations. Sixty-one of the mutations have only been identified in one family. A novel mutation in exon 2, c.322C>T (p.R108C), was identified in 16 of 27 Hispanic patients. SNP genotyping data demonstrated that Hispanic patients with this mutation share a common haplotype. Three other mutations were seen exclusively in Hispanic patients: c.280G>A (p.G94R), c.1022dupA, and c.970G>A (p.A324T). Seven mutations were seen almost exclusively in black patients, including the previously reported c.2150G>T (p.G717V) mutation, which was identified in 12 of 29 black patients. Two mutations were seen only in Asian patients. Some frequently identified mutations were not population-specific and were identified in patients of various ethnic backgrounds. Some of these mutations were found in mutation clusters in exons 2, 3, 6, and 11, suggesting a recurrent mutation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".