tRNA methyltransferase 10 homologue A (<i>TRMT10A</i>) mutation in a Chinese patient with diabetes, insulin resistance, intellectual deficiency and microcephaly
Bibliographic record
Abstract
Introduction Loss-of-function mutations in tRNA methyltransferase 10 homologue A (TRMT10A), a tRNA methyltransferase, have recently been described as a monogenic cause of early-onset diabetes with microcephaly, epilepsy and intellectual disability. Research design and methods We report a Chinese young patient who was diagnosed with diabetes mellitus as a result of a TRMT10A mutation. Results A homozygous mutation c.496–1G>A in TRMT10A was identified using targeted next-generation sequencing and confirmed by PCR/Sanger sequencing. In addition to being diagnosed with diabetes, the patient also has microcephaly and intellectual deficiency. The diabetes was due to marked insulin resistance and responded very well to metformin treatment. Conclusion Our case is the first report in the Asian population. It adds to current knowledge of TRMT10A related with young-onset non-insulin-dependent diabetes and confirms the a single previous report of insulin resistance in this syndrome. Genomic testing should be considered in children with non-insulin-dependent diabetes with intellectual disability and microcephaly. A clear genetic diagnosis is helpful for early detection and treatment addressing insulin resistance.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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".