Genomic architecture of human neuroanatomical diversity

Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for <5% of the variance. Here, b...

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Main Authors: Toro, Roberto (Author) , Banaschewski, Tobias (Author) , Flor, Herta (Author) , Mann, Karl (Author) , Rietschel, Marcella (Author)
Format: Article (Journal)
Language:English
Published: 16 September 2014
In: Molecular psychiatry
Year: 2014, Volume: 20, Issue: 8, Pages: 1011-1016
ISSN:1476-5578
DOI:10.1038/mp.2014.99
Online Access:Verlag, Volltext: http://dx.doi.org/10.1038/mp.2014.99
Verlag, Volltext: https://www.nature.com/articles/mp201499
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Author Notes:R. Toro, J.-B. Poline, G. Huguet, E. Loth, V. Frouin, T. Banaschewski, G.J. Barker, A. Bokde, C. Büchel, F.M. Carvalho, P. Conrod, M. Fauth-Bühler, H. Flor, J. Gallinat, H. Garavan, P. Gowland, A. Heinz, B. Ittermann, C. Lawrence, H. Lemaître, K. Mann, F. Nees, T. Paus, Z. Pausova, M. Rietschel, T. Robbins, M.N. Smolka, A. Ströhle, G. Schumann, T. Bourgeron and the IMAGEN consortium (www.imagen-europe.com)
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Summary:Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for <5% of the variance. Here, based on our analyses of neuroimaging and whole-genome genotyping data from 1765 subjects, we show that up to 54% of this heritability is captured by large numbers of single-nucleotide polymorphisms of small-effect spread throughout the genome, especially within genes and close regulatory regions. The genetic bases of neuroanatomical diversity appear to be relatively independent of those of body size (height), but shared with those of verbal intelligence scores. The study of this genomic architecture should help us better understand brain evolution and disease.
Item Description:Gesehen am 20.02.2018
Physical Description:Online Resource
ISSN:1476-5578
DOI:10.1038/mp.2014.99