Nalls, Michael A.

BACKGROUND: Recent genome-wide association studies (GWAS) have identified a number of novel SNPs associated with blood pressure and hypertension-related traits although studies were very large (approaching 80K participants) and effect sizes were modest with per allele effect sizes as small variants as a single millimeter of mercury difference in blood pressure. However, because hypertension is the most potent modifiable risk factor for ischemic stroke, lowering blood pressure by a few mm Hg can translate into measurable decrease in stroke risk. METHODS: We investigated 22 hypertension (HTN) associated SNPs in a case-control analysis of ischemic stroke in multiple stroke studies including the Siblings With Ischemic Stroke Study (SWISS), the Ischemic Stroke Genetics Study (ISGS), the Bio-Repository of DNA in Stroke (BRAINS), the Vitamin Intervention for Stroke Prevention (VISP) trial, and the Women's Health Initiative (WHI). SWISS/ISGS/BRAINS were analyzed together and included subtype information. Genotyping was funded through the individual studies, the Genomics and Randomized Trials Network (GARNET) consortium, and the SHARe (SNP Health Association Resource). All studies had both raw and imputed GWAS data. Analyses included the following phenotypes: all ischemic stroke, stroke subtypes, and age-at-stroke-onset and were stratified by race. Analyses were minimally adjusted for age, sex and principal components 1 & 2. Alpha was set at 0.05. RESULTS: Eleven of the SNPs from the HTN GWAS were associated with ischemic stroke in European ancestry from one or more of the study populations. Two SNPs on chromosome 12 and one on chromosome 21 were associated in multiple European ancestry cohorts. No SNP was associated in all studies. A SNP previously associated with HTN in African ancestry populations was associated with stroke in African-Americans. Analysis of subtypes found associations with small vessel disease and cardioembolic stroke but not large artery disease. The case-only age-at-stroke-onset analysis also found associations for the two SNPs on chromosome 12. CONCLUSION: These data suggest that candidate SNPs from a HTN GWAS may be associated with ischemic stroke and warrant further investigation. Racial differences were observed. Replication in populations from the other SiGN (Stroke Genetics Network), GENEVA (Gene Environment Association Studies) consortium, and the ISGC (International Stroke Genetics Consortium) studies are underway.

Background and Purpose: Family-based methods for estimating heritability cannot discriminate between shared genetic and shared environmental exposures. Recently, methods have been developed for estimating heritability in population samples using genome-wide SNPs. We used the approach developed by Visscher and colleagues to estimate the heritability of ischemic stroke in Caucasian subjects. In addition to evaluating the overall heritability of ischemic stroke, we assessed whether stroke heritability varies by age, gender, and stroke subtype. Methods: Using publicly available software (GCTA and PLINK), we estimated ischemic stroke heritability stratified by age and gender using genome-wide association (GWA) data from three Caucasian ischemic stroke studies: Ischemic Stroke Genetics Study (ISGS), Bio-Repository of DNA in Stroke (BRAINS), and Genetics of Early-Onset Stroke (GEOS). Weighted means of site-specific heritability point estimates were combined according to a standard fixed effects model. Results: Conclusions: A SNP-based approach may be useful in discerning differences in ischemic stroke heritability between different cohorts and subtypes. Overall, our analysis estimated ischemic stroke heritability to be 31% (SE = 7%), with a suggestion of higher heritability for younger cases. Small vessel stroke showed the highest heritability (58 ± 19%), with cardioembolic showing the lowest heritability (16 ± 14%). It should be emphasized that heritability estimates are population-specific and that the method used only reflects the heritability captured by common SNP variants measured in GWA studies, and not phenotypic variability explained by rare variants.