Genetic Architecture of White Matter Hyperintensities Differs in Hypertensive and Nonhypertensive Ischemic Stroke

Author:

Adib-Samii Poneh1,Devan William1,Traylor Matthew1,Lanfranconi Silvia1,Zhang Cathy R.1,Cloonan Lisa1,Falcone Guido J.1,Radmanesh Farid1,Fitzpatrick Kaitlin1,Kanakis Allison1,Rothwell Peter M.1,Sudlow Cathie1,Boncoraglio Giorgio B.1,Meschia James F.1,Levi Chris1,Dichgans Martin1,Bevan Steve1,Rosand Jonathan1,Rost Natalia S.1,Markus Hugh S.1

Affiliation:

1. From the Neuroscience Research Centre, Cardiovascular & Cell Sciences, St. George’s University of London, London, United Kingdom (P.A.-S., S.L.); Department of Neurology, Center for Human Genetic Research, Massachusetts General Hospital, Boston (W.D., C.R.Z., L.C., G.J.F., F.R., K.F., A.K., J.R., N.S.R.); Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom (M.T., S.B., H.S.M.); Program in Medical and Population Genetics, Broad Institute, Cambridge, MA (F.R.,...

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Neurology (clinical)

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2. Nonhypertensive White Matter Hyperintensities in Stroke: Risk Factors, Neuroimaging Characteristics, and Prognosis;Journal of the American Heart Association;2023-12-05

3. Overview-Research Progress of Leukoaraiosis;Journal of Behavioral and Brain Science;2022

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