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Published on: April 23, 2021
Genetic architecture of white matter hyperintensities differs in hypertensive and nonhypertensive ischemic stroke
Poneh Adib-Samii1, William Devan2, Matthew Traylor2
1From 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., J.R.); Stroke Prevention Research Unit, Nuffield Department of Neuroscience, University of Oxford, Oxford, United Kingdom (P.M.R.); Division of Clinical Neurosciences, Neuroimaging Sciences, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (C.S.); Department of Cerebrovascular Diseases, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy (G.B.B.); Department of Neurology, Mayo Clinic, Jacksonville, FL (J.F.M.); Centre for Clinical Epidemiology and Biostatistics, Hunter Medical Research Institute and School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia (C.L.); Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University Munich, Munich, Germany (M.D.); and Munich Cluster for Systems Neurology (SyNergy), Center for Stroke and Dementia Research, Munich, Germany (M.D.). padibsam@sgul.ac.uk.
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 [HSNP]) 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 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). HSNP estimates were higher among hypertensive individuals (HSNP=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 (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 nonhypertensives. Future WMHV GWAS studies may gain power by accounting for this interaction.
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