Stroke is among the understudied disorders despite its high burden to morbidity and mortality in the US. Ischemic stroke, which is due to cerebral vessel occlusion, accounts for 80% of cases. Ischemic stroke is a complex, multi-factorial disease, with heterogeneity by age, sex, and stroke subtype. A substantial proportion of stroke risk remains unexplained. The relatively low yield of stroke genetic studies to date may reflect the heterogeneous causes and clinical presentations of the various subtypes. Many of the studies participating in stroke GWAS have included have had little or no data available on stroke-specific risk factors or other CVD outcomes, which are key to understanding causal mechanisms and potential gene?environment interactions. Next generation sequencing (NGS) and multi-omics integrative biology research offer new opportunities in the way we research and understand stroke. Whole genome sequence (WGS) data, including both coding and functional non-coding variants, are required to identify the full spectrum of contributions of uncommon variants to stroke risk. Deep WGS data are currently being generated in over 11,000 WHI participants through the NHLBI TOPMed project, including over 4,000 ischemic stroke cases. Here we propose to apply innovative statistical approaches to perform a well-powered analysis to discover, replicate, and functionally characterize new loci (particularly rare or low frequency coding and non-coding regulatory variants) for ischemic stroke (and its subtypes) using WGS and imputation. Discovery will be performed in ~4,000 incident ischemic stroke cases and over 5,000 controls from WHI with WGS through TOPMed. Single variant and gene-based tests will be performed, prioritizing ~100 genomic regions based on prior GWAS and current epigenomic and proteomic analyses. Replication will be performed through state-of-the art WGS-based exome and GWAS imputation in up to ~77,000 additional ischemic stroke cases (and controls) obtained through UKBiobank, Million Veteran Program, and the SiGN and METASTROKE stroke genomics consortia. To assess the biologic mechanism of stroke-associated genetic loci, we will further test any newly identified stroke loci for association with: (1) a rich set of CVD risk factors and ~40 plasma biomarkers related to atherosclerosis, thrombosis, inflammation, and hormones available in WHI; (2) a new, commercial panel of 184 emerging biomarkers related to neurovascular disease and CVD in 2000 WHI TOPMed samples selected on the basis of genotype. Using casual inference methodology, we will perform mediation analyses to determine mechanistic relationships between genotype, intermediate biomarker phenotype, and stroke outcome.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Neurological, Aging and Musculoskeletal Epidemiology (NAME)
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Ludlam, Shari
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Fred Hutchinson Cancer Research Center
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United States
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