Aminoacyl-tRNA synthetases in human health and disease
Bibliographic record
Abstract
The Aminoacyl-tRNA Synthetases (aaRSs) are an evolutionarily ancient family of enzymes that catalyze the esterification reaction linking a transfer RNA (tRNA) with its cognate amino acid matching the anticodon triplet of the tRNA. Proper functioning of the aaRSs to create aminoacylated (or "charged") tRNAs is required for efficient and accurate protein synthesis. Beyond their basic canonical function in protein biosynthesis, aaRSs have a surprisingly diverse array of non-canonical functions that are actively being defined. The human genome contains 37 genes that encode unique aaRS proteins. To date, 56 human genetic diseases caused by damaging variants in aaRS genes have been described: 46 are autosomal recessive biallelic disorders and 10 are autosomal dominant monoallelic disorders. Our appreciation of human diseases caused by damaging genetic variants in the aaRSs has been greatly accelerated by the advent of next-generation sequencing, with 89% of these gene discoveries made since 2010. In addition to these genetic disorders of the aaRSs, anti-synthetase syndrome (ASSD) is a rare autoimmune inflammatory myopathy that involves the production of autoantibodies that disrupt aaRS proteins. This review provides an overview of the basic biology of aaRS proteins and describes the rapidly growing list of human diseases known to be caused by genetic variants or autoimmune targeting that affect both the canonical and non-canonical functions of these essential proteins.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".