Imaging Genetics Center, Laboratory of NeuroImaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.
Neuroimage. 2013 Oct 15;80:475-88. doi: 10.1016/j.neuroimage.2013.05.013. Epub 2013 May 21.
Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods--such as genome-wide association studies (GWAS), linkage and candidate gene studies--that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity.
连接组遗传学试图发现遗传因素如何影响大脑连接。在这里,我们回顾了各种遗传分析方法,如全基因组关联研究(GWAS)、连锁和候选基因研究,这些方法已经成功地应用于成像数据,以确定基因组中与大脑相关特征的特定变体。强调遗传对大脑连接影响的研究。其中一些使用弥散磁共振成像(dMRI)分析大脑完整性和连接性,另一些则使用静息态功能磁共振成像(rs-fMRI)映射遗传对功能网络的影响。也进行了连接组全基因组扫描,我们回顾了处理基因组和网络数据极高维度所需的多元方法。我们还回顾了一些联盟的努力,如 ENIGMA,它提供了使用表型协调程序和荟萃分析检测稳健的常见遗传关联的能力。连接组遗传学的当前工作正在许多方面取得进展,并有望揭示疾病风险基因如何影响大脑。它已经发现了新的遗传位点,甚至整个影响大脑组织和连接的遗传网络。