Moyamoya Disease-Associated <i>RNF213</i> Alleles Encode Dominant Negative Alleles That Globally Impair Ubiquitylation
Bibliographic record
Abstract
Abstract Single nucleotide polymorphisms (SNPs) in RNF213 , which encodes a 591kDa protein with AAA+ ATPase and RING E3 domains, are associated with a rare, autosomal dominant cerebrovascular disorder, Moyamoya disease (MMD). MMD-associated SNPs primarily localize to the C-terminal region of RNF213, and some affect conserved residues in the RING domain. Although the autosomal dominant inheritance of MMD could most easily be explained by RNF213 gain-of-function, the type of ubiquitylation catalyzed by RNF213 and the effects of MMD-associated SNPs on its E3-ligase activity have remained unclear. We found that the RING domain of RNF213 uses the E2-conjugating enzyme UBE2D2 to catalyze predominantly K6-dependent poly-ubiquitination events comprising a mixture of typical and atypical ubiquitin linkages. MMD-associated SNPs encode proteins with decreased E3-ligase activity and the most frequent MMD allele, RNF213 R4810K , is a dominant negative mutant that decreases ubiquitylation globally. By contrast, MMD-associated RNF213 SNPs do not affect ATPase activity. We propose that decreased RNF213 E3-ligase activity is central to MMD pathogenesis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.006 | 0.002 |
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".