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体素全基因组关联研究(vGWAS)。

Voxelwise genome-wide association study (vGWAS).

机构信息

Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles School of Medicine, Neuroscience Research Building 225E, 635 Charles Young Drive, Los Angeles, CA 90095-1769, USA.

出版信息

Neuroimage. 2010 Nov 15;53(3):1160-74. doi: 10.1016/j.neuroimage.2010.02.032. Epub 2010 Feb 17.

Abstract

The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age+/-s.d.: 75.52+/-6.82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.

摘要

人脑结构具有高度遗传性,被认为受许多常见遗传变异的影响,其中许多变异目前尚不清楚。神经影像学和遗传学的最新进展使得能够同时收集高度详细的结构脑扫描和全基因组基因型信息。这一丰富的信息为发现影响大脑结构的基因提供了新的机会。在这里,我们探索了在包括阿尔茨海默病、轻度认知障碍和来自阿尔茨海默病神经影像学倡议 (ADNI) 的健康老年对照组在内的 740 名老年受试者(平均年龄+/-标准差:75.52+/-6.82 岁;438 名男性)的整个大脑的 31622 个体素的 448293 个单核苷酸多态性之间的关系。我们使用基于张量的形态测量学来测量相对于基于健康老年受试者的研究特定模板的个体间脑结构的个体差异。然后,我们在每个体素上进行全基因组关联,以确定感兴趣的遗传变异。通过仅在每个体素研究最相关的变异,我们开发了一种新的方法来解决与前所未有的大量数据相关的多重比较问题和计算负担。没有变体通过严格的显著标准,但确定了几个值得进一步探索的基因,包括 CSMD2 和 CADPS2。这些基因与大脑结构有很高的相关性。这是我们所知的第一个体素全基因组关联研究,提供了一种发现遗传对大脑结构影响的新方法。

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