期刊
NEUROIMAGE
卷 80, 期 -, 页码 475-488出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.05.013
关键词
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资金
- NIH [NS080655, MH097268, AG040060, EB008432, MH089722, HD050735, P41 EB015922, MH078143, MH083824, MH080912, HL113323, MH097940, R01 EB015611-01, U54MH091657-03]
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 MAL 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 manyfronts 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. (C) 2013 Elsevier Inc. All rights reserved.
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