Global genetic variations predict brain response to faces.
| Autor: | Erin W Dickie, Amir Tahmasebi, Leon French, Natasa Kovacevic, Tobias Banaschewski, Gareth J Barker, Arun Bokde, Christian Büchel, Patricia Conrod, Herta Flor, Hugh Garavan, Juergen Gallinat, Penny Gowland, Andreas Heinz, Bernd Ittermann, Claire Lawrence, Karl Mann, Jean-Luc Martinot, Frauke Nees, Thomas Nichols, Mark Lathrop, Eva Loth, Zdenka Pausova, Marcela Rietschel, Michal N Smolka, Andreas Ströhle, Roberto Toro, Gunter Schumann, Tomáš Paus, IMAGEN consortium |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | PLoS Genetics, Vol 10, Iss 8, p e1004523 (2014) |
| Druh dokumentu: | article |
| ISSN: | 1553-7390 1553-7404 |
| DOI: | 10.1371/journal.pgen.1004523 |
| Popis: | Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼ 500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40-50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R(2) = 0.38, p |
| Databáze: | Directory of Open Access Journals |
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