Stroke genetics informs drug discovery and risk prediction across ancestries
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- Meta-epidemiology (narrow), Research integrity
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.981
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.301 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Abstract Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry 1,2 . Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated ( P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis 3 , and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN ) and variants (such as at GRK5 and NOS3 ). Using a three-pronged approach 4 , we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry 5 . Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Nature
- Topic
- Genetic Associations and Epidemiology
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- McGill Genome CentreImpactMcGill UniversityPopulation Health Research InstituteMcMaster UniversityUniversity of TorontoUniversity Health NetworkUniversity of British ColumbiaOntario Brain InstituteThrombosis and Atherosclerosis Research Institute
- Funders
- Faculty of Medicine and Health, University of SydneyNational Heart, Lung, and Blood InstituteErasmus Universitair Medisch Centrum RotterdamCenter for Clinical and Translational Science, Ohio State UniversityOhio State UniversityUniversity of TokyoAgence Nationale de la RechercheUniversiteit MaastrichtUniversiteit van AmsterdamMedical Research CouncilLeids Universitair Medisch CentrumUniversiteit LeidenStatens Serum InstitutUniversity of BristolInstitut National de la Santé et de la Recherche MédicaleInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementNational Human Genome Research InstituteAmsterdam University Medical CentersU.S. National Library of MedicineNational Institute of Neurological Disorders and StrokeBritish Heart FoundationWellcome TrustNational Institute of Diabetes and Digestive and Kidney DiseasesNorges Teknisk-Naturvitenskapelige UniversitetUniversity of WashingtonLundbeckfondenMassachusetts General HospitalUniversity of MinnesotaNational Institute on AgingNational Institute for Health and Care ResearchUniversitair Medisch Centrum GroningenMcKnight FoundationMaastricht Universitair Medisch CentrumUniversity of California, San DiegoU.S. Department of Veterans Affairs
- Keywords
- Genome-wide association studyStroke (engine)Genetic associationGeneticsBiologyMedicineBioinformaticsGeneSingle-nucleotide polymorphismGenotype
- Has abstract in OpenAlex
- yes