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多部位弥散图像的遗传分析和体素遗传分析:ENIGMA-DTI 工作组的初步研究。

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.

机构信息

Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.

Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.

出版信息

Neuroimage. 2013 Nov 1;81:455-469. doi: 10.1016/j.neuroimage.2013.04.061. Epub 2013 Apr 28.

Abstract

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

摘要

ENIGMA(通过荟萃分析增强神经影像学遗传学)联盟成立的目的是分析来自世界各地多个地点的大脑测量值和基因型,以提高检测影响大脑的遗传变异的能力。弥散张量成像(DTI)可提供对大脑发育和退化敏感的定量测量值,一些常见的遗传变异可能与白质完整性或连接性有关。DTI 测量值,如水分子扩散的各向异性分数(FA),可能有助于识别影响大脑微观结构的遗传变异。然而,全基因组关联研究(GWAS)需要大量人群才能获得足够的能力来检测和复制显著的影响,这促使了多地点联盟的努力。作为 ENIGMA-DTI 工作组的一部分,我们分析了来自北美的多个成像地点、澳大利亚和欧洲的高分辨率 FA 图像,以解决在多个地点收集成像数据的协调问题。我们使用来自四个地点的 400 张健康成年人的高分辨率 FA 图像来创建模板和相应的骨架 FA 图像作为公共参考空间。利用不同种族的双胞胎和家系样本,我们使用共同的模板来评估基于束的 FA 测量值的遗传性。我们表明,我们的模板通过荟萃分析组合结果以及通过探索性 mega 分析统一数据,是整合多个数据集的可靠方法。我们的结果可能有助于确定 FA 图谱中受加性遗传因素一致影响的区域,以便为未来的遗传发现研究提供优先考虑。协议和模板可在(http://enigma.loni.ucla.edu/ongoing/dti-working-group/)上获得。

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