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dc.contributor.authorvan der Meer, Dennis
dc.contributor.authorShadrin, Alexey
dc.contributor.authorO'Connell, Kevin Sean
dc.contributor.authorBettella, Francesco
dc.contributor.authorDjurovic, Srdjan
dc.contributor.authorWolfers, Thomas
dc.contributor.authorAlnæs, Dag
dc.contributor.authorAgartz, Ingrid
dc.contributor.authorSmeland, Olav Bjerkehagen
dc.contributor.authorMelle, Ingrid
dc.contributor.authorSánchez, Jennifer Monereo
dc.contributor.authorLinden, David E.J.
dc.contributor.authorDale, Anders
dc.contributor.authorWestlye, Lars Tjelta
dc.contributor.authorAndreassen, Ole
dc.contributor.authorFrei, Oleksandr
dc.contributor.authorKaufmann, Tobias
dc.date.accessioned2022-09-12T09:24:39Z
dc.date.available2022-09-12T09:24:39Z
dc.date.created2022-05-20T14:42:40Z
dc.date.issued2022
dc.identifier.issn0006-3223
dc.identifier.urihttps://hdl.handle.net/11250/3017175
dc.description.abstractBackground Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. Methods We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. Results We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. Conclusions Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue–specific genetic variants and its use in polygenic risk frameworks.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleBoosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphologyen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2021 Society of Biological Psychiatryen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doi10.1016/j.biopsych.2021.12.007
dc.identifier.cristin2026012
dc.source.journalBiological Psychiatryen_US
dc.source.pagenumber291-298en_US
dc.identifier.citationBiological Psychiatry. 2022, 92 (4), 291-298.en_US
dc.source.volume92en_US
dc.source.issue4en_US


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal