TRAPPing a neurological disorder: from yeast to humans
Bibliographic record
Abstract
The modular complex TRAPP acts as an activator of a subgroup of Ypt/RAB GTPases. The substrate GTPases and TRAPP are conserved from yeast to human cells, required for secretion and macroautophagy/autophagy and implicated in human disease. All TRAPP complexes contain four core subunits essential for cell viability, and until recently there were no human diseases associated with any core TRAPP subunit. Recently, we reported a neurological disorder associated with a pathogenic variant of the core TRAPP subunit TRAPPC4. This variant results in lower levels of full-length TRAPPC4 protein and the TRAPP complex. A conditional mutation of the yeast homolog of TRAPPC4, Trs23, also results in a lower level of the protein and the TRAPP complex. Phenotypic analysis of the yeast mutant cells reveals a minor defect in secretion and a major defect in autophagy. Similarly, primary fibroblasts derived from human patients also exhibit minor and severe defects in secretion and autophagy, respectively. We propose that the autophagy defect caused by the pathogenic-TRAPPC4 variant results in the severe neurological disorder. Moreover, we hypothesize that low levels of the core TRAPP complex are more detrimental to autophagy than to secretion, and that the long-term autophagy defect is especially harmful to neuronal cells.Abbreviations: ER: endoplasmic reticulum; PM: plasma membrane; TRAPP: transport protein particle; Ypt: yeast protein transport
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".