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dc.contributor.authorDoan, Nhat Trungen_US
dc.contributor.authorKaufmann, Tobiasen_US
dc.contributor.authorBettella, Francescoen_US
dc.contributor.authorJørgensen, Kjetil Nordbøen_US
dc.contributor.authorBrandt, Christine Lyckeen_US
dc.contributor.authorMoberget, Torgeiren_US
dc.contributor.authorAlnæs, Dagen_US
dc.contributor.authorDouaud, Gwenaëlleen_US
dc.contributor.authorDuff, Eugeneen_US
dc.contributor.authorDjurovic, Srdjanen_US
dc.contributor.authorMelle, Ingriden_US
dc.contributor.authorUeland, Torillen_US
dc.contributor.authorAgartz, Ingriden_US
dc.contributor.authorAndreassen, Ole Andreasen_US
dc.contributor.authorWestlye, Lars Tjeltaen_US
dc.PublishedDoan NT, Kaufmann T, Bettella F, Jørgensen Kn, Brandt CL, Moberget T, Alnæs D, et al. Distinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders. NeuroImage: Clinical. 2017;15:719-731eng
dc.description.abstractThe brain underpinnings of schizophrenia and bipolar disorders are multidimensional, reflecting complex pathological processes and causal pathways, requiring multivariate techniques to disentangle. Furthermore, little is known about the complementary clinical value of brain structural phenotypes when combined with data on cognitive performance and genetic risk. Using data-driven fusion of cortical thickness, surface area, and gray matter density maps (GMD), we found six biologically meaningful patterns showing strong group effects, including four statistically independent multimodal patterns reflecting co-occurring alterations in thickness and GMD in patients, over and above two other independent patterns of widespread thickness and area reduction. Case-control classification using cognitive scores alone revealed high accuracy, and adding imaging features or polygenic risk scores increased performance, suggesting their complementary predictive value with cognitive scores being the most sensitive features. Multivariate pattern analyses reveal distinct patterns of brain morphology in mental disorders, provide insights on the relative importance between brain structure, cognitive and polygenetic risk score in classification of patients, and demonstrate the importance of multivariate approaches in studying the pathophysiological substrate of these complex disorders.en_US
dc.rightsAttribution CC BY-NC-NDeng
dc.subjectMultimodal MRIeng
dc.subjectClinical predictioneng
dc.subjectBrain structureeng
dc.subjectBipolar disordereng
dc.subjectPolygenic riskeng
dc.titleDistinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disordersen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright 2017 The Authors
dc.source.journalNeuroImage: Clinical
dc.relation.projectHelse Sør-Øst RHF: 2014097
dc.relation.projectNorges forskningsråd: 249795

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