Mapping genetic influences on ventricular structure in twins.
Mapping genetic influences on ventricular structure in twins.
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DOI：
10.1016/j.neuroimage.2008.10.036
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发表时间：
2009-02-15
期刊：
影响因子：
5.7
通讯作者：
Thompson PM
中科院分区：
文献类型：
--
作者：
Chou YY;Leporé N;Chiang MC;Avedissian C;Barysheva M;McMahon KL;de Zubicaray GI;Meredith M;Wright MJ;Toga AW;Thompson PM
尽管在测量人类大脑的解剖学和功能变异方面取得了重大进展，但对这些变异的遗传和环境原因知之甚少。在这里，我们开发了一个自动化系统，在大型脑MRI数据库中可视化遗传和环境对脑结构的影响。我们应用我们的多模板分割方法，称为“多图谱流体图像对齐”，以流体传播手动标记的参数化表面网格，标记侧脑室，在3D体积MRI扫描的76个相同的（同卵，MZ）双胞胎（38对;平均年龄=24.6（SD=1.7））;和56同性兄弟（异卵，DZ）双胞胎（28对;平均年龄=23.0（SD=1.8）），作为最终将研究超过1000名受试者的5年研究的一部分进行扫描。在受试者内对网格表面进行平均，以最大限度地减少分割误差。我们在30，000个表面点中的每个点上拟合定量遗传模型，以测量形状方差的比例，这些形状方差可归因于（1）受试者之间的遗传差异，（2）每个个体独特的环境影响，以及（3）共享的环境影响。基于表面的统计地图，来自路径分析，揭示了遗传模式，及其意义，在3D。最佳拟合数据的“ACE”模型的通径系数表明遗传因素（A=7.3%）、共同环境（C=38.9%）和独特环境（E=53.8%）对侧脑室容积有显著贡献。较早成熟的枕角区域也可能比较晚成熟的额叶区域受到更多的遗传影响。地图可视化空间变化的环境与遗传影响的档案。该方法显示了在大型图像数据库中自动测量基因-环境效应的前景。
Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed “Multi-Atlas Fluid Image Alignment” to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age=24.6 (SD=1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age=23.0 (SD=1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the ‘ACE’ model that best fitted the data indicated significant contributions from genetic factors (A=7.3%), common environment (C=38.9%) and unique environment (E=53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.
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DOI：
10.1073/pnas.0402680101
发表时间：
2004-05-25
影响因子：
11.1
作者：
Gogtay, N;Giedd, JN;Thompson, PM
通讯作者：
Thompson, PM
影响因子：
1.3
作者：
COLLINS, DL;NEELIN, P;EVANS, AC
通讯作者：
EVANS, AC
影响因子：
3.7
作者：
Bearden, Carrie E.;van Erp, Theo G. M.;Thompson, Paul M.
通讯作者：
Thompson, Paul M.
影响因子：
--
作者：
Cannon, TD;Hennah, W;Peltonen, L
通讯作者：
Peltonen, L
DOI：
10.1073/pnas.052494999
发表时间：
2002-03-05
影响因子：
11.1
作者：
Geschwind, DH;Miller, BL;Carmelli, D
通讯作者：
Carmelli, D