Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation.

Pub Date : 2017-11-27 DOI:10.1515/sagmb-2016-0077
Elena Szefer, Donghuan Lu, Farouk Nathoo, Mirza Faisal Beg, Jinko Graham
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引用次数: 10

Abstract

Using publicly-available data from the Alzheimer's Disease Neuroimaging Initiative, we investigate the joint association between single-nucleotide polymorphisms (SNPs) in previously established linkage regions for Alzheimer's disease (AD) and rates of decline in brain structure. In an initial, discovery stage of analysis, we applied a weighted RV test to assess the association between 75,845 SNPs in the Alzgene linkage regions and rates of change in structural MRI measurements for 56 brain regions affected by AD, in 632 subjects. After confirming association, we selected refined lists of 1694 and 22 SNPs via a bootstrap-enhanced sparse canonical correlation analysis. In a final, validation stage, we confirmed association between the refined list of 1694 SNPs and the imaging phenotypes in an independent data set. Genes corresponding to priority SNPs having the highest contribution in the validation data have previously been implicated or hypothesized to be implicated in AD, including GCLC, IDE, and STAMBP1andFAS. Though the effect sizes of the 1694 SNPs in the priority set are likely small, further investigation within this set may advance understanding of the missing heritability in AD. Our analysis addresses challenges in current imaging-genetics studies such as biased sampling designs and high-dimensional data with low association signal.

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Alzgene连锁区域的单核苷酸多态性与大脑结构变化之间的多变量关联:发现、改进和验证。
利用来自阿尔茨海默病神经影像学倡议的公开数据,我们研究了先前建立的阿尔茨海默病(AD)连锁区域的单核苷酸多态性(snp)与大脑结构下降率之间的联合关联。在最初的发现分析阶段,我们应用加权RV检验来评估632名受试者中Alzgene连锁区域的75,845个snp与AD影响的56个大脑区域的结构MRI测量变化率之间的关系。在确认关联后,我们通过引导增强的稀疏典型相关分析选择了1694个和22个SNPs的精炼列表。在最后的验证阶段,我们在一个独立的数据集中确认了1694个SNPs的精炼列表与成像表型之间的关联。在验证数据中贡献最大的优先snp对应的基因先前被认为与AD有关或被假设与AD有关,包括GCLC、IDE和STAMBP1andFAS。尽管优先集中的1694个snp的效应量可能很小,但在该集中的进一步研究可能会促进对AD缺失遗传力的理解。我们的分析解决了当前成像遗传学研究中的挑战,如偏抽样设计和低关联信号的高维数据。
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