Objective:For 3,670 stroke patients from the United Kingdom, United States, Australia, Belgium, and Italy, we performed a genome-wide meta-analysis of white matter hyperintensity volumes (WMHV) on data imputed to the 1000 Genomes reference dataset to provide insights into disease mechanisms.Methods:We first sought to identify genetic associations with white matter hyperintensities in a stroke population, and then examined whether genetic loci previously linked to WMHV in community populations are also associated in stroke patients. Having established that genetic associations are shared between the 2 populations, we performed a meta-analysis testing which associations with WMHV in stroke-free populations are associated overall when combined with stroke populations.Results:There were no associations at genome-wide significance with WMHV in stroke patients. All previously reported genome-wide significant associations with WMHV in community populations shared direction of effect in stroke patients. In a meta-analysis of the genome-wide significant and suggestive loci (p < 5 × 10−6) from community populations (15 single nucleotide polymorphisms in total) and from stroke patients, 6 independent loci were associated with WMHV in both populations. Four of these are novel associations at the genome-wide level (rs72934505 [NBEAL1], p = 2.2 × 10−8; rs941898 [EVL], p = 4.0 × 10−8; rs962888 [C1QL1], p = 1.1 × 10−8; rs9515201 [COL4A2], p = 6.9 × 10−9).Conclusions:Genetic associations with WMHV are shared in otherwise healthy individuals and patients with stroke, indicating common genetic susceptibility in cerebral small vessel disease.

Our results indicate an association between common variation in the COL4A2 gene and symptomatic small vessel disease, particularly deep intracerebral hemorrhage. These findings merit replication studies, including in ethnic groups of non-European ancestry.

Background and Purpose Epidemiological studies suggest white matter hyperintensities (WMH) are extremely heritable but the underlying genetic variants are largely unknown. Pathophysiological heterogeneity is known to reduce the power of genome-wide association studies (GWAS). Hypertensive and non-hypertensive individuals with WMH might have different underlying pathologies. We used GWAS data to calculate the variance in WMH volume (WMHV) explained by common single nucleotide polymorphisms (SNPs) as a measure of heritability (HSNP), and tested the hypothesis that WMH heritability differs between hypertensive and non-hypertensives. Methods WMHV was measured on MRI in the stroke-free cerebral hemisphere of 2336 ischemic stroke cases with GWAS data. After adjustment for age and intracranial volume, we determined which cardiovascular risk factors were independent predictors of WMHV. Using the genome-wide complex trait analysis (GCTA) tool to estimate HSNP for WMHV overall, and within subgroups stratified by risk factors found to be significant in multivariate analyses. Results A significant proportion of the variance of WMHV was attributable to common SNPs after adjustment for significant risk factors (HSNP=0.23,p=0.0026). When stratified by hypertension, SNP heritability estimates were higher amongst hypertensive individuals; (HSNP=0.45, p=7.99e-5); this increase was greater than expected by chance (p=0.012). In contrast estimates were lower, and non-significant, in non-hypertensives (HSNP=0.13, p=0.13). Conclusions A quarter of variance is attributable to common SNPs but this estimate was greater in hypertensive individuals. These findings suggest that the genetic architecture of WMH in ischemic stroke differs between hypertensives and non-hypertensives. Future WMHV GWAS studies may gain power by accounting for this interaction.