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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.

Original publication

DOI

10.1016/j.neuroimage.2013.05.013

Type

Journal article

Journal

NeuroImage

Publication Date

10/2013

Volume

80

Pages

475 - 488

Addresses

Imaging Genetics Center, Laboratory of NeuroImaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA. thompson@loni.ucla.edu

Keywords

Brain, Nerve Net, Humans, Genome, Human, Models, Genetic, Models, Neurological, Models, Anatomic, Metabolome, Connectome