Publication

Stroke genetics informs drug discovery and risk prediction across ancestries

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Last modified
  • 06/25/2025
Type of Material
Authors
    Peter Wilson, Emory UniversityYan Sun, Emory UniversityHyacinth Hyacinth, Emory University
Language
  • English
Date
  • 2022-09-30
Publisher
  • Nature Research
Publication Version
Copyright Statement
  • © The Author(s) 2022, corrected publication 2022
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 611
Issue
  • 7934
Start Page
  • 115
End Page
  • 123
Supplemental Material (URL)
Abstract
  • Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. 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 analysis3, 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 approach4, 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 ancestry5. 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.
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Research Categories
  • Health Sciences, Pathology
  • Biology, Biostatistics
  • Mathematics

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