Global Assessment of Mendelian Stroke Genetic Prevalence in 101 635 Individuals From 7 Ethnic Groups
Bibliographic record
Abstract
Background and Purpose— Mendelian stroke confers a high lifetime risk for mutation carriers; however, ethnicity-specific prevalence estimates have been difficult to establish. Methods— Eighteen genes responsible for Mendelian stroke were investigated using the Genome Aggregation Database. Genome Aggregation Database participants belonged to 1 of 7 populations: African/African-American, Latino/Admixed American, Ashkenazi Jewish, East Asian, Finnish European, non-Finnish European, and South Asian. Rare nonsynonymous variants from 101 635 participants free of neurological disease were examined for each ethnicity. Mutations were categorized according to 3 nested classes: pathogenic clinical variants, likely damaging variants based on in silico prediction, and all nonsynonymous variants. Results— ABCC6 , KRIT1 , CECR1 , COL3A1 , COL4A1 , COL4A2 , COLGALT1 , GLA , HTRA1 , NOTCH3 , RNF213 , and TREX1 harbored pathogenic clinical variants in Genome Aggregation Database. Across all 18 genes, total nonsynonymous carrier frequency was found to be high in 5 ethnicities (African/African-American, Latino/Admixed American, East Asian, non-Finnish European, and South Asian; 28.5%–37.5%) while lower total frequencies were estimated for in silico–predicted likely damaging variants (14.9%–19.7%) and pathogenic clinical variants (0.7%–2.8%). Overall, East Asian exhibited the highest total pathogenic clinical mutation carrier frequency (2.8%). ABCC6 pathogenic clinical variants were most prevalent among East Asian (0.8%). Pathogenic NOTCH3 variants, causal for cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, were most frequent among East Asian (1.1%) and South Asian (1.2%). East Asian also demonstrated the highest carrier rate for RNF213 (0.8%). Finnish European exhibited the greatest HTRA1 frequency (0.2%), while COL4A1 pathogenic variants were most prevalent in African/African-American (0.3%). Conclusions— Especially, among pathogenic clinical variants, Mendelian stroke genetic prevalence differed significantly between populations. These prevalence estimates may serve as guides for screening and risk profiling in patients worldwide, particularly for understudied non-European populations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".