Multi-ancestry meta-analysis identifies 5 novel loci for ischemic stroke and reveals heterogeneity of effects between sexes and ancestries

Ida Surakka; Kuan-Han Wu; Whitney Hornsby; Brooke N Wolford; Fred Shen; Wei Zhou; Jennifer E Huffman; Anita Pandit; Yao Hu; Ben Brumpton; Anne Heidi Skogholt; Maiken E Gabrielsen; Robin G Walters; TOPMed Stroke Working Group; Million Veteran Program (MVP); Kristian Hveem; Charles Kooperberg; Sebastian Zöllner; Peter W F Wilson; Nadia R Sutton; Mark J Daly; Benjamin M Neale; Cristen J Willer; Global Biobank Meta-analysis Initiative (GBMI)

doi:10.1016/j.xgen.2023.100345

Multi-ancestry meta-analysis identifies 5 novel loci for ischemic stroke and reveals heterogeneity of effects between sexes and ancestries

Cell Genom. 2023 Jun 19;3(8):100345. doi: 10.1016/j.xgen.2023.100345. eCollection 2023 Aug 9.

Authors

Ida Surakka¹, Kuan-Han Wu², Whitney Hornsby¹, Brooke N Wolford^{2

3}, Fred Shen¹, Wei Zhou^{4

5}, Jennifer E Huffman⁶, Anita Pandit³, Yao Hu⁷, Ben Brumpton^{8

9

10}, Anne Heidi Skogholt⁸, Maiken E Gabrielsen⁸, Robin G Walters^{11

12}; TOPMed Stroke Working Group; Million Veteran Program (MVP); Kristian Hveem^{8

10}, Charles Kooperberg⁷, Sebastian Zöllner³, Peter W F Wilson^{13

14}, Nadia R Sutton¹, Mark J Daly^{4

5

15

16}, Benjamin M Neale^{4

5

16}, Cristen J Willer^{1

2

9

17}; Global Biobank Meta-analysis Initiative (GBMI)

Affiliations

¹ Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
² Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
³ Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
⁴ Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁵ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.
⁷ Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
⁸ K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
⁹ Clinic of Medicine, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway.
¹⁰ HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway.
¹¹ Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
¹² Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
¹³ Atlanta VA Health Care System, Decatur, GA, USA.
¹⁴ Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA.
¹⁵ Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
¹⁶ Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
¹⁷ Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.

Abstract

Stroke is the second leading cause of death and disability worldwide. Stroke prevalence varies by sex and ancestry, possibly due to genetic heterogeneity between subgroups. We performed a genome-wide meta-analysis of 16 biobanks across multiple ancestries to study the genetics of ischemic stroke (60,176 cases, 1,310,725 controls) as part of the Global Biobank Meta-analysis Initiative (GBMI) and further combined the results with previously published MegaStroke. Five novel loci for ischemic stroke (LAMC1, CALCRL, PLSCR1, CDKN1A, and SWAP70) were identified after replication in four additional datasets. One previously reported locus showed significant ancestry heterogeneity (ABO), and one showed significant sex heterogeneity (ALDH2). The ALDH2 association was male specific (males p = 1.67e-24, females p = 0.126) and was additionally observed only in the East Asian ancestry (male) samples. These findings emphasize the need for more diverse datasets with large sample sizes to further understand the genetic predisposition of stroke in different ancestry and sex groups.

Keywords: GBMI; GWAS; heterogeneity; ischemic stroke; meta-analysis.