Description

The proposed research builds on the most robust, statistically significant and replicated association identified to determine the mechanism by which it may relate to intracerebral hemorrhage (ICH) risk. Given that ICH is an extreme phenotype on a spectrum of manifestations of cerebral small vessel disease, the findings that emerge from our proposed studies offer the promise of broad impact for research and treatment in a wide variety of cerebrovascular disorders.

In the genetic epidemiology of hemorrhagic stroke, we propose to perform an in-depth fine-mapping of the entire 1q22 genomic region (~250kb) to investigate whether genetic variants influence gene expression that correlates with ICH status or changes in expression over time in ICH cases. As existing samples were not processed for gene expression analysis, we will recruit 500 non-lobar ICH cases (~150 black, ~350 white) and 1000 controls (300 black, 700 white) to correlate sequence variation with gene expression levels in the same samples. Identified associations will be replicated in 6,000 cases of ICH and 9,361 individuals in the CHARGE consortium with MRI white matter hyperintensity volume measurements and 5,000 controls. The current proposal takes the next logical step by pursuing the most promising findings of our Genome-Wide Association Study (GWAS) to complete the following aims:

Specific Aim #1: Perform deep DNA sequencing of Chr 1q22 among non-Hispanic white and black ICH cases and controls to identify all genomic variation within these regions and test the following:

Hypothesis #1a: Variants strongly associated with ICH risk at 1q22 are either directly causal or in linkage disequilibrium to causal variants that influence ICH risk, and sequencing of these regions will reveal both common and rare variants that exert this causal influence.

Hypothesis #1b: Variants strongly associated with ICH risk at 1q22 will be associated with risk of, or severity of, leukoaraiosis.

Specific Aim #2: Prospectively collect DNA, RNA, and serum on ICH cases and geographic region site-specific controls both at the time of ICH and in the convalescent period. We will perform RNA expression profiling between cases and controls and over time in cases. We will compute expression quantitative trait locus (eQTL) analysis with Single Nucleotide Polymorphisms (SNPs) arising from Aim 1. We will also determine whether alternatively spliced transcripts differ between cases and controls.

Hypothesis #2a: Variation in gene expression or alternatively spliced transcripts affects risk of ICH.

Hypothesis #2b: Variations identified by DNA sequencing will affect gene expression and/or alternatively spliced transcripts that affect risk of ICH.