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Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.

TitleMultiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.
Publication TypeJournal Article
Year of Publication2018
AuthorsMalik R, Chauhan G, Traylor M, et al.
Secondary AuthorsDichgans M
Corporate AuthorsAFGen Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology(CHARGE) Consortium, International Genomics of Blood Pressure(iGEN-BP) Consortium, INVENT Consortium, STARNET, BioBank Japan Cooperative Hospital Group, COMPASS Consortium, EPIC-CVD Consortium, EPIC-InterAct Consortium, International Stroke Genetics Consortium(ISGC), METASTROKE Consortium, Neurology Working Group of the CHARGE Consortium, NINDS Stroke Genetics Network(SiGN), UK Young Lacunar DNA Study, MEGASTROKE Consortium
JournalNat Genet
Volume50
Issue4
Pagination524-537
Date Published2018 04
ISSN1546-1718
KeywordsComputational Biology, Databases, Genetic, Epigenesis, Genetic, Female, Gene Regulatory Networks, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, INDEL Mutation, Linkage Disequilibrium, Male, Models, Genetic, Polymorphism, Single Nucleotide, Risk Factors, Stroke
Abstract

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.

DOI10.1038/s41588-018-0058-3
Alternate JournalNat Genet
PubMed ID29531354
PubMed Central IDPMC5968830
Grant ListR01 NS017950 / NS / NINDS NIH HHS / United States
K24 HL105780 / HL / NHLBI NIH HHS / United States
MR/P013880/1 / MRC_ / Medical Research Council / United Kingdom
R01 NS087541 / NS / NINDS NIH HHS / United States
Z99 AG999999 / ImNIH / Intramural NIH HHS / United States
MR/L003120/1 / MRC_ / Medical Research Council / United Kingdom
MC_UU_12015/1 / MRC_ / Medical Research Council / United Kingdom
P30 DK063491 / DK / NIDDK NIH HHS / United States
RG/16/4/32218 / BHF_ / British Heart Foundation / United Kingdom
MR/P02811X/1 / MRC_ / Medical Research Council / United Kingdom
R01 HL138423 / HL / NHLBI NIH HHS / United States
FS/14/55/30806 / BHF_ / British Heart Foundation / United Kingdom
UL1 TR001881 / TR / NCATS NIH HHS / United States
U01 AG049505 / AG / NIA NIH HHS / United States
RG/13/13/30194 / BHF_ / British Heart Foundation / United Kingdom
R01 AG054076 / AG / NIA NIH HHS / United States
R01 HL092577 / HL / NHLBI NIH HHS / United States
U01 HL130114 / HL / NHLBI NIH HHS / United States
S10 OD020069 / OD / NIH HHS / United States
P30 AG010129 / AG / NIA NIH HHS / United States
R01 HL088521 / HL / NHLBI NIH HHS / United States
U54 GM115428 / GM / NIGMS NIH HHS / United States
K23 HL114724 / HL / NHLBI NIH HHS / United States