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
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., 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.).
Stroke. 2015 Feb;46(2):348-53. doi: 10.1161/STROKEAHA.114.006849. Epub 2014 Dec 30.
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.
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.
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).
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.
流行病学研究表明，脑白质高信号（WMH）具有高度遗传性，但其潜在的基因变异大多未知。已知病理生理异质性会降低全基因组关联研究（GWAS）的效能。患有WMH的高血压个体和非高血压个体可能存在不同的潜在病理状况。我们利用GWAS数据计算常见单核苷酸多态性（SNP）所解释的WMH体积（WMHV）方差，以此作为遗传性的一种度量（SNP遗传性[HSNP]），并检验了WMH遗传性在高血压个体和非高血压个体之间存在差异这一假设。
在2336例有GWAS数据的缺血性卒中病例的无卒中大脑半球上，通过MRI测量WMHV。在调整年龄和颅内体积后，我们确定哪些心血管危险因素是WMHV的独立预测因素。使用全基因组复杂性状分析工具来估计总体WMHV以及在多变量分析中发现的显著危险因素分层的亚组内的HSNP。
在调整显著危险因素后，WMHV的很大一部分方差可归因于常见SNP（HSNP = 0.23；P = 0.0026）。高血压个体中的HSNP估计值更高（HSNP = 0.45；P = 7.99×10⁻⁵）；这种增加大于偶然预期（P = 0.012）。相比之下，非高血压个体中的估计值较低且无统计学意义（HSNP = 0.13；P = 0.13）。
四分之一的方差可归因于常见SNP，但这一估计在高血压个体中更大。这些发现表明，缺血性卒中中WMH的遗传结构在高血压患者和非高血压患者之间存在差异。未来的WMHV GWAS研究可能通过考虑这种相互作用而提高效能。
