Intracerebral hemorrhage (ICH) is the most deadly form of stroke, and those that survive carry a high burden of long-term disability. ICH is an acute manifestation of progressive small vessel disease (CSVD), a condition that collectively causes ICH and small vessel (SV) ischemic stroke, cognitive decline, late-life depression, and gait deterioration. Because we have found shared epidemiologic and genetic risk factors among ICH and other CSVD manifestations, understanding the biological foundations of ICH offers the opportunity to develop effective treatment and prevention strategies across CSVD. Through prior genome-wide association studies (GWAS), we have identified three promising gene-rich loci, 1q22, 13q34, and 16q24, carrying associations with both ICH and SV stroke. These loci are united by a common theme in which associated variants are located in regions enriched for non-coding regulatory roles, rather than protein-coding function. Identification of causal functional variants and their regulatory mechanisms must occur before this knowledge can be applied to improve stroke care. Our proposal is motivated by (A) well-powered GWAS of ICH and small vessel stroke as well as preliminary targeted sequencing data suggesting a prominent regulatory role for ICH-associated variants at these loci, (B) the availability of whole genome sequencing (WGS) data on large populations with ICH and ischemic stroke for well- powered association testing at these loci, and (C) accumulated expertise in translational genomic approaches that can link genetic variants to functional biological effects, bridging the gap between disease association results and biological consequence. This proposal serves our central hypothesis that exploring the functional impact of genetic associations in ICH will yield biological insights that will identify novel treatment targets and advance the search for therapeutic strategies with bedside applications. Our proposal, entitled ?Sequencing Annotation and Functional Analysis of Risk in ICH?, or SAFARI-ICH, will leverage NIH-supported WGS efforts from NHLBI TOPMed and the NHGRI Centers for Common Disease Genomics to comprehensively determine 1) which particular sequence and structural variants at 1q22, 13q34, and 16q24 predispose to CSVD, 2) which of these associated variants, using annotation and cross-phenotype analyses, are most likely to reflect causal biology, and 3) what effect these putative causal variants have on gene transcription at these and other loci using relevant cellular models. Our approach leverages NIH investment in WGS at no cost to this proposal, allowing resources to be devoted to identifying the causal variants and their functional ramifications in ICH and SV stroke. Because our approach is designed to characterize variants with an impact on gene regulation at the cellular level, this proposal offers a unique opportunity to deliver insight into ICH pathobiology and highlight potential targets for future treatment of ICH and other adverse and highly prevalent CSVD manifestations.
This proposal will use genome sequencing data to identify disease-causing genetic variants at 1q22, 13q34, and 16q24 loci, previously identified and replicated in genome-wide association studies of intracerebral hemorrhage and small vessel ischemic stroke. Once putative causal variants have been identified, we will perform functional cellular assays to clarify how these variants cause biological changes leading to stroke. Results from this proposal will advance strategies to use pathways highlighted by genetic studies as treatment targets to reduce the risk of intracerebral hemorrhage and related diseases.
| Marini, Sandro; Devan, William J; Radmanesh, Farid et al. (2018) 17p12 Influences Hematoma Volume and Outcome in Spontaneous Intracerebral Hemorrhage. Stroke 49:1618-1625 |
| Murphy, Meredith P; Kuramatsu, Joji B; Leasure, Audrey et al. (2018) Cardioembolic Stroke Risk and Recovery After Anticoagulation-Related Intracerebral Hemorrhage. Stroke 49:2652-2658 |
| Marini, Sandro; Lena, Umme K; Crawford, Katherine M et al. (2018) Comparison of Genetic and Self-Identified Ancestry in Modeling Intracerebral Hemorrhage Risk. Front Neurol 9:514 |
