<i>RNF213</i> variation, a broader role in neurovascular disease in Caucasian and Japanese populations
Bibliographic record
Abstract
Abstract Moyamoya disease (MMD) is a chronic, occlusive cerebrovascular disease that predominantly affects East Asian populations. The major genetic mutation associated with MMD in Asian populations is the p.R4810K substitution in Ring Finger Protein 213 (RNF213). Interestingly, variants in the RNF213 gene have also been implicated in intracranial aneurysms (IA) in French-Canadian population, suggesting that variation in this gene may play a broader role in cerebrovascular phenotypes. In a recent genome-wide association study (GWAS) in a Caucasian population, variants rs6565653 and rs12601526 in the Solute Carrier Family 26 Member 11 ( SLC26A11 ) gene, which is less than 10kb away from RNF213 , showed a suggestive association with young onset ischemic stroke. We propose that the signal could be tagging an association with common variation in the RNF213 gene. We analyzed the linkage disequilibrium (LD) pattern in the SLC26A11-RNF213 gene region and we observed a high LD between variants in this region based on D’ values. We show that SLC26A11 rs6565653 variant tags RNF213 rs12944088, a missense variant that is more common among subjects with IA than in healthy individuals. Given the fact that rs6565653 tags several RNF213 variants, it is highly likely that some of these tagged variants modify the risk of suffering stroke. The LD analyses suggest that the SLC26A11 signal from the young onset ischemic stroke GWAS performed in a Caucasian population is also tagging variation at the RNF213 loci, supporting the hypothesis that RNF213 variation may result in a variety of neurovascular disorders including an increased risk and/or worse prognosis following ischemic stroke in Caucasian population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".