<i>COL4A2</i> is associated with lacunar ischemic stroke and deep ICH
Bibliographic record
Abstract
Objective: To determine whether common variants in familial cerebral small vessel disease (SVD) genes confer risk of sporadic cerebral SVD. Methods: We meta-analyzed genotype data from individuals of European ancestry to determine associations of common single nucleotide polymorphisms (SNPs) in 6 familial cerebral SVD genes (COL4A1, COL4A2, NOTCH3, HTRA1, TREX1, and CECR1) with intracerebral hemorrhage (ICH) (deep, lobar, all; 1,878 cases, 2,830 controls) and ischemic stroke (IS) (lacunar, cardioembolic, large vessel disease, all; 19,569 cases, 37,853 controls). We applied data quality filters and set statistical significance thresholds accounting for linkage disequilibrium and multiple testing. Results: A locus in COL4A2 was associated (significance threshold p < 3.5 × 10−4) with both lacunar IS (lead SNP rs9515201: odds ratio [OR] 1.17, 95% confidence interval [CI] 1.11–1.24, p = 6.62 × 10−8) and deep ICH (lead SNP rs4771674: OR 1.28, 95% CI 1.13–1.44, p = 5.76 × 10−5). A SNP in HTRA1 was associated (significance threshold p < 5.5 × 10−4) with lacunar IS (rs79043147: OR 1.23, 95% CI 1.10–1.37, p = 1.90 × 10−4) and less robustly with deep ICH. There was no clear evidence for association of common variants in either COL4A2 or HTRA1 with non-SVD strokes or in any of the other genes with any stroke phenotype. Conclusions: These results provide evidence of shared genetic determinants and suggest common pathophysiologic mechanisms of distinct ischemic and hemorrhagic cerebral SVD stroke phenotypes, offering new insights into the causal mechanisms of cerebral SVD.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".