利用高角分辨率扩散成像(HARDI)定位遗传对脑纤维结构的影响

M. Chiang, M. Barysheva, Agatha D. Lee, S. Madsen, A. Klunder, A. Toga, K. Mcmahon, G. Zubicaray, M. Meredith, M. Wright, Anuj Srivastava, N. Balov, P. Thompson
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引用次数: 21

摘要

我们报告了遗传对大脑纤维复杂性影响的第一个3D地图。我们分析了来自90名年轻成年双胞胎的HARDI脑成像数据,使用信息理论测量,Jensen-Shannon散度(JSD),以衡量白质纤维取向分布函数(ODF)的区域复杂性。HARDI数据采用Karcher均值和ODF平方根进行流态配准;每个受试者的JSD地图是根据每个体素的邻域odf的空间相干性计算的。我们利用结构方程模型(SEM)评估了遗传对广义纤维各向异性(GFA)和复杂性(JSD)的影响。在每个体素上,估计数据变异的遗传和环境成分,并通过排列检验它们的拟合优度。颜色编码的地图显示,不同的大脑区域有不同的最佳模型。纤维复杂性主要受遗传控制,在各向异性越强的地区纤维复杂性越高。这些方法有望发现影响大脑纤维连接的因素。
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Mapping genetic influences on brain fiber architecture with high angular resolution diffusion imaging (HARDI)
We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpolation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color- coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.
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