Genetic Contributions to Early and Late Onset Ischemic Stroke
Bibliographic record
Abstract
Abstract Objective To determine the contribution of common genetic variants to risk of early onset ischemic stroke (IS). Methods We performed a meta-analysis of genome-wide association studies of early onset IS, ages 18-59, using individual level data or summary statistics in 16,927 cases and 576,353 non-stroke controls from 48 different studies across North America, Europe, and Asia. We further compared effect sizes at our most genome-wide significant loci between early and late onset IS and compared polygenic risk scores for venous thromboembolism between early versus later onset IS. Results We observed an association between early onset IS and ABO , a known stroke locus. The effect size of the peak ABO SNP, rs8176685, was significantly larger in early compared to late onset IS (OR 1.17 (95% C.I.: 1.11-1.22) vs 1.05 (0.99-1.12); p for interaction = 0.008). Analysis of genetically determined ABO blood groups revealed that early onset IS cases were more likely to have blood group A and less likely to have blood group O compared to both non-stroke controls and to late onset IS cases. Using polygenic risk scores, we observed that greater genetic risk for venous thromboembolism, another prothrombotic condition, was more strongly associated with early, compared to late, onset IS (p=0.008). Conclusion The ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with early onset IS, compared with late onset IS, supporting a stronger role of prothrombotic factors in early onset IS.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".