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Genome-Wide Association Study Meta-Analysis of Stroke in 22 000 Individuals of African Descent Identifies Novel Associations with Stroke

  • Keith L. Keene
  • , Hyacinth I. Hyacinth
  • , Joshua C. Bis
  • , Steven J. Kittner
  • , Braxton D. Mitchell
  • , Yu Ching Cheng
  • , Guillaume Pare
  • , Michael Chong
  • , Martin O'Donnell
  • , James F. Meschia
  • , Wei Min Chen
  • , Michèle M. Sale
  • , Stephen S. Rich
  • , Mike A. Nalls
  • , Alan B. Zonderman
  • , Michele K. Evans
  • , James G. Wilson
  • , Adolfo Correa
  • , Hugh S. Markus
  • , Matthew Traylor
  • Cathryn M. Lewis, Cara L. Carty, Alexander Reiner, Jeff Haessler, Carl D. Langefeld, Rebecca Gottesman, Thomas H. Mosley, Daniel Woo, Kristine Yaffe, Yong Mei Liu, William T. Longstreth, Bruce M. Psaty, Charles Kooperberg, Leslie A. Lange, Ralph Sacco, Tatjana Rundek, Jin Moo Lee, Carlos Cruchaga, Karen L. Furie, Donna K. Arnett, Oscar R. Benavente, Raji P. Grewal, Leema Reddy Peddareddygari, Martin Dichgans, Rainer Malik, Bradford B. Worrall, Myriam Fornage
  • East Carolina University
  • Emory University
  • University of Washington
  • University of Maryland, Baltimore
  • McMaster University
  • University of Galway
  • Mayo Clinic Rochester, MN
  • University of Virginia
  • National Institute on Aging
  • Data Tecnica International
  • National Institute on Aging
  • University of Mississippi
  • University of Cambridge
  • Queen Mary University of London
  • King's College London
  • Washington State University Spokane
  • Fred Hutchinson Cancer Research Center
  • Wake Forest University
  • Johns Hopkins University
  • University of California at San Francisco
  • Kaiser Permanente
  • University of Colorado Anschutz Medical Campus
  • University of Miami
  • Washington University St. Louis
  • Brown University
  • University of Kentucky
  • University of British Columbia
  • St. Francis Medical Center, Trenton
  • Ludwig Maximilian University of Munich
  • Munich Cluster for Systems Neurology (SyNergy)
  • University of Texas Health Science Center at Houston

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Background and Purpose: Stroke is a complex disease with multiple genetic and environmental risk factors. Blacks endure a nearly 2-fold greater risk of stroke and are 2× to 3× more likely to die from stroke than European Americans. Methods: The COMPASS (Consortium of Minority Population Genome-Wide Association Studies of Stroke) has conducted a genome-wide association meta-analysis of stroke in >22 000 individuals of African ancestry (3734 cases, 18 317 controls) from 13 cohorts. Results: In meta-analyses, we identified one single nucleotide polymorphism (rs55931441) near the HNF1A gene that reached genome-wide significance (P=4.62×10-8) and an additional 29 variants with suggestive evidence of association (P<1×10-6), representing 24 unique loci. For validation, a look-up analysis for a 100 kb region flanking the COMPASS single nucleotide polymorphism was performed in SiGN (Stroke Genetics Network) Europeans, SiGN Hispanics, and METASTROKE (Europeans). Using a stringent Bonferroni correction P value of 2.08×10-3 (0.05/24 unique loci), we were able to validate associations at the HNF1A locus in both SiGN (P=8.18×10-4) and METASTROKE (P=1.72×10-3) European populations. Overall, 16 of 24 loci showed evidence for validation across multiple populations. Previous studies have reported associations between variants in the HNF1A gene and lipids, C-reactive protein, and risk of coronary artery disease and stroke. Suggestive associations with variants in the SFXN4 and TMEM108 genes represent potential novel ischemic stroke loci. Conclusions: These findings represent the most thorough investigation of genetic determinants of stroke in individuals of African descent, to date.

Original languageEnglish
Pages (from-to)2454-2463
Number of pages10
JournalStroke
Volume51
Issue number8
DOIs
StatePublished - Aug 1 2020

Keywords

  • brain ischemia
  • coronary artery disease
  • genome-wide association study
  • meta-analysis
  • phenotype
  • risk factors

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