Multi-ancestry proteogenomic analysis identifies risk proteins for intracranial aneurysms
Bibliographic record
Abstract
Abstract Background Intracranial aneurysm (IA) and its complication, subarachnoid hemorrhage (SAH), cause morbidity and mortality, yet no preventative pharmacotherapies exist. Genome-wide association studies (GWAS) have identified risk loci for IA and SAH, but the causal proteins and pathways that connect genetic risk to aneurysm biology remain unclear. Methods We performed ancestry-stratified GWAS meta-analyses of IA and SAH in European and East Asian ancestries and linked these to circulating protein levels using proteome-wide Mendelian randomization (MR). We applied stringent instrument selection, sensitivity analyses, and colocalization, and implemented GWAS-by-subtraction to derive IA components not fully mediated by systolic blood pressure (SBP). We triangulated findings with UK Biobank observational associations, rare variant gene-burden testing in 426,295 exomes, and a French-Canadian familial IA cohort. Results Across 15,611 protein-outcome tests, 12 associations for nine proteins were significant in European ancestry. SLMAP, AMBP, ENTPD6, and PLEKHA1 were associated with increased IA risk, whereas SIRT2, JAG1, ADH4, and NAGLU were associated with decreased IA risk; ADAM23 was associated with increased SAH risk. Colocalization supported shared causal variants for ADH4, PLEKHA1, and SLMAP in IA. After removing SBP-mediated genetic effects, ADH4, JAG1, and PLEKHA1 remained associated with IA, suggesting effects not fully mediated by blood pressure. In UK Biobank, higher measured SLMAP, AMBP, and ENTPD6 levels showed concordant increases in cerebrovascular disease risk. Rare damaging JAG1 variants showed nominally higher odds of cerebrovascular disease, and a missense ENTPD6 variant was enriched in French-Canadian familial IA. Conclusions Integrating multi-ancestry genomics with large-scale proteomics implicates specific circulating proteins and pathways in IA and SAH risk. Convergent evidence prioritizes ADH4, a retinoid-pathway enzyme, and PLEKHA1, a phosphoinositide-binding adaptor in endothelial signaling, as non-SBP-mediated candidates for IA biology, with additional support for JAG1/Notch and SLMAP-related vascular pathways. These findings highlight mechanistic biomarkers and potential drug targets for aneurysm prevention that warrant experimental validation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| 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".