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本文引用的文献

1
White matter microstructural abnormalities in bipolar disorder: A whole brain diffusion tensor imaging study.双相障碍的脑白质微观结构异常:全脑弥散张量成像研究。
Neuroimage Clin. 2013 Apr 5;2:558-68. doi: 10.1016/j.nicl.2013.03.016. eCollection 2013.
2
OpenMx: An Open Source Extended Structural Equation Modeling Framework.OpenMx:一个开源的扩展结构方程建模框架。
Psychometrika. 2011 Apr 1;76(2):306-317. doi: 10.1007/s11336-010-9200-6.
3
Disrupted brain networks in the aging HIV+ population.衰老 HIV+人群的大脑网络紊乱。
Brain Connect. 2012;2(6):335-44. doi: 10.1089/brain.2012.0105-Rev.
4
White matter integrity as an intermediate phenotype: exploratory genome-wide association analysis in individuals at high risk of bipolar disorder.作为一种中间表型的脑白质完整性:在双相情感障碍高危个体中的全基因组关联分析探索。
Psychiatry Res. 2013 Apr 30;206(2-3):223-31. doi: 10.1016/j.psychres.2012.11.002. Epub 2012 Dec 4.
5
Testing the hypothesis of accelerated cerebral white matter aging in schizophrenia and major depression.检测精神分裂症和重度抑郁症患者大脑白质加速老化的假说。
Biol Psychiatry. 2013 Mar 1;73(5):482-91. doi: 10.1016/j.biopsych.2012.10.002. Epub 2012 Nov 28.
6
Anatomical MRI and DTI in the diagnosis of Alzheimer's disease: a European multicenter study.基于 MRI 和 DTI 的解剖学研究对阿尔茨海默病的诊断价值:一项欧洲多中心研究。
J Alzheimers Dis. 2012;31 Suppl 3:S33-47. doi: 10.3233/JAD-2012-112118.
7
DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME.影响人类大脑连接性的基因发现:连接组的全基因组分析
Proc IEEE Int Symp Biomed Imaging. 2012:542-545. doi: 10.1109/ISBI.2012.6235605.
8
DIFFUSION IMAGING PROTOCOL EFFECTS ON GENETIC ASSOCIATIONS.扩散成像协议对基因关联的影响。
Proc IEEE Int Symp Biomed Imaging. 2012:944-947. doi: 10.1109/ISBI.2012.6235712.
9
The TWIN-E project in emotional wellbeing: study protocol and preliminary heritability results across four MRI and DTI measures.情感健康方面的TWIN-E项目:研究方案及四项磁共振成像和弥散张量成像测量的初步遗传力结果
Twin Res Hum Genet. 2012 Jun;15(3):419-41. doi: 10.1017/thg.2012.12.
10
Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies.遗传和环境对神经影像学表型的影响:双生子影像学研究的荟萃分析视角
Twin Res Hum Genet. 2012 Jun;15(3):351-71. doi: 10.1017/thg.2012.11.

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.

DOI:10.1016/j.neuroimage.2013.04.061
PMID:23629049
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3729717/
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。