S-GMAS:脑皮质下形状介质的全基因组中介分析

IF 3.3 2区 医学 Q1 NEUROIMAGING
Shengxian Ding, Rongjie Liu, Anuj Srivastava, Richard S. Nowakowski, Li Shen, Paul M. Thompson, Heping Zhang, Chao Huang
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引用次数: 0

摘要

中介分析在神经科学中被广泛应用于研究脑图像表型在从遗传暴露到临床结果的神经通路中的作用。然而,由于以下几个挑战,使用全基因组暴露和大脑皮层下形状介质进行中介分析仍然很困难:(i)大规模遗传暴露,即数百万单核苷酸多态性(snp);(ii)形状介质的非线性Hilbert空间;(三)直接效应和间接效应的统计推断。为了解决这些挑战,本文提出了一个包含大脑皮层下形状介质的全基因组中介分析框架。首先,为了解决遗传暴露的高维性所带来的问题,我们进行了快速全基因组关联分析,以发现对临床结果有显著遗传影响的潜在遗传变异。其次,从大脑皮层下形状中提取平方根速度函数表示,这些形状属于无约束的线性希尔伯特子空间。第三,为了通过形状介质确定从检测到的snp到临床结果隐含的潜在因果通路,我们使用了由形状-标量模型和标量-形状模型组成的形状中介分析框架。此外,采用自举重采样方法研究了全球和空间显著的中介效应。最后,我们的框架应用于来自阿尔茨海默病神经成像倡议的胼胝体形状数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators

S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators

Mediation analysis is widely utilized in neuroscience to investigate the role of brain image phenotypes in the neurological pathways from genetic exposures to clinical outcomes. However, it is still difficult to conduct mediation analyses with whole genome-wide exposures and brain subcortical shape mediators due to several challenges including (i) large-scale genetic exposures, that is, millions of single-nucleotide polymorphisms (SNPs); (ii) nonlinear Hilbert space for shape mediators; and (iii) statistical inference on the direct and indirect effects. To tackle these challenges, this paper proposes a genome-wide mediation analysis framework with brain subcortical shape mediators. First, to address the issue caused by the high dimensionality in genetic exposures, a fast genome-wide association analysis is conducted to discover potential genetic variants with significant genetic effects on the clinical outcome. Second, the square-root velocity function representations are extracted from the brain subcortical shapes, which fall in an unconstrained linear Hilbert subspace. Third, to identify the underlying causal pathways from the detected SNPs to the clinical outcome implicitly through the shape mediators, we utilize a shape mediation analysis framework consisting of a shape-on-scalar model and a scalar-on-shape model. Furthermore, the bootstrap resampling approach is adopted to investigate both global and spatial significant mediation effects. Finally, our framework is applied to the corpus callosum shape data from the Alzheimer's Disease Neuroimaging Initiative.

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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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