Matchmaking facilitates the diagnosis of an autosomal-recessive mitochondrial disease caused by biallelic mutation of the tRNA isopentenyltransferase (<i>TRIT1</i>) gene
Bibliographic record
Abstract
Deleterious variants in the same gene present in two or more families with overlapping clinical features provide convincing evidence of a disease-gene association; this can be a challenge in the study of ultrarare diseases. To facilitate the identification of additional families, several groups have created "matching" platforms. We describe four individuals from three unrelated families "matched" by GeneMatcher and MatchMakerExchange. Individuals had microcephaly, developmental delay, epilepsy, and recessive mutations in TRIT1. A single homozygous mutation in TRIT1 associated with similar features had previously been reported in one family. The identification of these individuals provides additional evidence to support TRIT1 as the disease-causing gene and interprets the variants as "pathogenic." TRIT1 functions to modify mitochondrial tRNAs and is necessary for protein translation. We show that dysfunctional TRIT1 results in decreased levels of select mitochondrial proteins. Our findings confirm the TRIT1 disease association and advance the phenotypic and molecular understanding of this disorder.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".