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dc.date.accessioned2022-10-28T15:38:09Z
dc.date.available2022-10-28T15:38:09Z
dc.date.created2022-10-10T14:29:24Z
dc.date.issued2022
dc.identifier.citationFan, Chun Chieh Loughnan, Robert Makowski, Carolina Pecheva, Diliana Chen, Chi-Hua Hagler, Donald J. Thompson, Wesley Kurt Parker, Nadine van der Meer, Dennis Frei, Oleksandr Andreassen, Ole Dale, Anders . Multivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain. Nature Communications. 2022, 13(1)
dc.identifier.urihttp://hdl.handle.net/10852/97399
dc.description.abstractAbstract The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discover 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% are validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development are found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.
dc.languageEN
dc.publisherNature Portfolio
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleMultivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain
dc.title.alternativeENEngelskEnglishMultivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain
dc.typeJournal article
dc.creator.authorFan, Chun Chieh
dc.creator.authorLoughnan, Robert
dc.creator.authorMakowski, Carolina
dc.creator.authorPecheva, Diliana
dc.creator.authorChen, Chi-Hua
dc.creator.authorHagler, Donald J.
dc.creator.authorThompson, Wesley Kurt
dc.creator.authorParker, Nadine
dc.creator.authorvan der Meer, Dennis
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.cristin2060125
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Nature Communications&rft.volume=13&rft.spage=&rft.date=2022
dc.identifier.jtitleNature Communications
dc.identifier.volume13
dc.identifier.issue1
dc.identifier.pagecount0
dc.identifier.doihttps://doi.org/10.1038/s41467-022-30110-3
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2041-1723
dc.type.versionPublishedVersion
cristin.articleid2423


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