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Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

机译:遗传连接矩阵的分层聚类揭示了基因动作对脑微观结构的网络拓扑:n = 531双语研究

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Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.
机译:遗传相关(R G )分析决定了两种措施之间的关联程度是由于常见的遗传影响。在分析来自531个健康的年轻成年双胞胎及其兄弟姐妹的4特斯拉扩散张量图像(DTI)中,我们推广了遗传相关的概念,以确定通过分数各向异性(FA)测量的白质完整性的常见遗传影响在大脑中,在大脑中的所有体素的FA值之间产生NXN遗传相关矩阵R G (x,y)。通过分层聚类,我们鉴定了具有相对均匀的遗传决定因素的脑区域,以提高识别因果单核苷酸多态性(SNP)的能力。我们应用了基因组 - 范围协会(GWA),以评估由集群遗传相关矩阵集群定义的群集的529,497个SNP和FA之间的关联。我们鉴定了一种基因网络,具有无规模的拓扑,影响白质完整性在多个脑区域上。

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