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dc.date.accessioned2021-12-21T17:02:08Z
dc.date.available2021-12-21T17:02:08Z
dc.date.created2021-11-10T22:58:24Z
dc.date.issued2021
dc.identifier.citationShadrin, Alexey A. Kaufmann, Tobias van der Meer, Dennis Palmer, Clare E. Makowski, Carolina Loughnan, Robert Jernigan, Terry L. Seibert, Tyler M. Hagler, Donald J Smeland, Olav Bjerkehagen Motazedi, Ehsan Chu, Yunhan Lin, Aihua Cheng, Weiqiu Hindley, Guy Thompson, Wesley K. Fan, Chun Chieh Holland, Dominic Westlye, Lars Tjelta Frei, Oleksandr Andreassen, Ole Dale, Anders . Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology. NeuroImage. 2021, 244, 1-8
dc.identifier.urihttp://hdl.handle.net/10852/89757
dc.description.abstractBrain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleVertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology
dc.typeJournal article
dc.creator.authorShadrin, Alexey A.
dc.creator.authorKaufmann, Tobias
dc.creator.authorvan der Meer, Dennis
dc.creator.authorPalmer, Clare E.
dc.creator.authorMakowski, Carolina
dc.creator.authorLoughnan, Robert
dc.creator.authorJernigan, Terry L.
dc.creator.authorSeibert, Tyler M.
dc.creator.authorHagler, Donald J
dc.creator.authorSmeland, Olav Bjerkehagen
dc.creator.authorMotazedi, Ehsan
dc.creator.authorChu, Yunhan
dc.creator.authorLin, Aihua
dc.creator.authorCheng, Weiqiu
dc.creator.authorHindley, Guy
dc.creator.authorThompson, Wesley K.
dc.creator.authorFan, Chun Chieh
dc.creator.authorHolland, Dominic
dc.creator.authorWestlye, Lars Tjelta
dc.creator.authorFrei, Oleksandr
dc.creator.authorAndreassen, Ole
dc.creator.authorDale, Anders
cristin.unitcode185,53,10,70
cristin.unitnameNORMENT part UiO
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1953450
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=NeuroImage&rft.volume=244&rft.spage=1&rft.date=2021
dc.identifier.jtitleNeuroImage
dc.identifier.volume244
dc.identifier.doihttps://doi.org/10.1016/j.neuroimage.2021.118603
dc.identifier.urnURN:NBN:no-92356
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1053-8119
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/89757/1/Vertex-wise%2Bmultivariate%2Bgenome-wide%2Bassociation%2Bstudy%2Bidentifies%2B780%2Bunique%2Bgenetic%2Bloci%2Bassociated%2Bwith%2Bcortical%2Bmorphology.pdf
dc.type.versionPublishedVersion
cristin.articleid118603


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