Genetic Architecture of White Matter Hyperintensities Differs in Hypertensive and Nonhypertensive Ischemic Stroke. Issue 2 (February 2015)

• Record Type: Journal Article
• Authors: Adib-Samii, Poneh; Devan, William; Traylor, Matthew; Lanfranconi, Silvia; Zhang, Cathy R.; Cloonan, Lisa; Falcone, Guido J.; Radmanesh, Farid; Fitzpatrick, Kaitlin; Kanakis, Allison; Rothwell, Peter M.; Sudlow, Cathie; Boncoraglio, Giorgio B.; Meschia, James F.; Levi, Chris; Dichgans, Martin; Bevan, Steve; Rosand, Jonathan; Rost, Natalia S.; Markus, Hugh S.
• Is Part Of: Stroke. Volume 46:Issue 2(2015)
• Publication Date: 2015-02
• Subjects: genetics -- hypertension -- leukoaraiosis -- stroke; Cerebrovascular disease -- Periodicals; Cerebral circulation -- Periodicals; 616.81
• DOI: 10.1161/STROKEAHA.114.006849
• Languages: English
• ISSNs: 0039-2499

Abstract

Abstract : Background and Purpose—: Epidemiological studies suggest that 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 nonhypertensive 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 (SNP heritability [ H SNP ]) and tested the hypothesis that WMH heritability differs between hypertensive and nonhypertensive individuals. 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 tool to estimate H SNP 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 ( H SNP =0.23; P =0.0026). H SNP estimates were higher among hypertensive individuals ( H SNP =0.45; P =7.99×10 −5 ); this increase was greater than expected by chance ( P =0.012). In contrast, estimates were lower, and nonsignificant, in nonhypertensive individuals ( H SNP =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 nonhypertensives. Future WMHV GWAS studies may gain power by accounting for this interaction. Abstract : Supplemental Digital Content is available in the text.