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dc.contributor.authorChristoforou, Andreaen_US
dc.contributor.authorEspeseth, Thomasen_US
dc.contributor.authorDavis, G.en_US
dc.contributor.authorFernandes, Carla P.D.en_US
dc.contributor.authorGiddaluru, Sudheeren_US
dc.contributor.authorMattheisen, Manuelen_US
dc.contributor.authorTenesa, A.en_US
dc.contributor.authorHarris, Sarah E.en_US
dc.contributor.authorLiewald, David Cen_US
dc.contributor.authorPayton, Anthonyen_US
dc.contributor.authorOllier, Wen_US
dc.contributor.authorHoran, M.en_US
dc.contributor.authorPendleton, Neilen_US
dc.contributor.authorHaggarty, Paulen_US
dc.contributor.authorDjurovic, Srdjanen_US
dc.contributor.authorHerms, Stefanen_US
dc.contributor.authorHoffman, P.en_US
dc.contributor.authorCichon, Svenen_US
dc.contributor.authorStarr, John Men_US
dc.contributor.authorLundervold, Astrien_US
dc.contributor.authorReinvang, Ivaren_US
dc.contributor.authorSteen, Vidar Martinen_US
dc.contributor.authorDeary, Ian Jen_US
dc.contributor.authorLe Hellard, Stephanieen_US
dc.date.accessioned2015-03-27T13:11:25Z
dc.date.available2015-03-27T13:11:25Z
dc.date.issued2014-09eng
dc.identifier.issn1601-1848
dc.identifier.urihttps://hdl.handle.net/1956/9688
dc.description.abstractCognitive abilities vary among people. About 40–50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) – the ability to reason in novel situations – and general crystallized intelligence (gC) – the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF–gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.en_US
dc.language.isoengeng
dc.rightsAttribution-NonCommercial-NoDerivs CC BY-NC-NDeng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/eng
dc.subjectCrystallized intelligenceeng
dc.subjectFluid intelligenceeng
dc.subjectgene-based analysiseng
dc.subjectGWASeng
dc.subjectpathway analysiseng
dc.titleGWAS-based pathway analysis differentiates between fluid and crystallized intelligenceen_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2015-03-04T11:24:18Zen_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2014 The Authors
dc.identifier.doihttps://doi.org/10.1111/gbb.12152
dc.identifier.cristin1221083
dc.source.journalGenes, Brain and Behavior
dc.source.4013
dc.source.147
dc.source.pagenumber663-674


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