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dc.contributor.authorParker, Nadine
dc.contributor.authorCheng, Weiqiu
dc.contributor.authorHindley, Guy
dc.contributor.authorO'Connell, Kevin Sean
dc.contributor.authorKarthikeyan, Sandeep
dc.contributor.authorHolen, Børge
dc.contributor.authorShadrin, Alexey
dc.contributor.authorRahman, Zillur
dc.contributor.authorKaradag, Naz
dc.contributor.authorBahrami, Shahram
dc.contributor.authorLin, Aihua
dc.contributor.authorSteen, Nils Eiel
dc.contributor.authorUeland, Thor
dc.contributor.authorAukrust, Pål
dc.contributor.authorDjurovic, Srdjan
dc.contributor.authorDale, Anders
dc.contributor.authorSmeland, Olav Bjerkehagen
dc.contributor.authorFrei, Oleksandr
dc.contributor.authorAndreassen, Ole
dc.date.accessioned2024-01-17T12:23:27Z
dc.date.available2024-01-17T12:23:27Z
dc.date.created2023-09-06T08:43:32Z
dc.date.issued2024
dc.identifier.issn0006-3223
dc.identifier.urihttps://hdl.handle.net/11250/3112161
dc.description.abstractBackground For many brain disorders, a subset of patients jointly exhibit alterations in cortical brain structure and elevated levels of circulating immune markers. This may be driven in part by shared genetic architecture. Therefore, we investigated the phenotypic and genetic associations linking global cortical surface area and thickness with blood immune markers (i.e., white blood cell counts and plasma C-reactive protein levels). Methods Linear regression was used to assess phenotypic associations in 30,823 UK Biobank participants. Genome-wide and local genetic correlations were assessed using linkage disequilibrium score regression and local analysis of covariance annotation. The number of shared trait-influencing genetic variants was estimated using MiXeR. Shared genetic architecture was assessed using a conjunctional false discovery rate framework, and mapped genes were included in gene-set enrichment analyses. Results Cortical structure and blood immune markers exhibited predominantly inverse phenotypic associations. There were modest genome-wide genetic correlations, the strongest of which were for C-reactive protein levels (rg_surface_area = −0.13, false discovery rate–corrected p = 4.17 × 10−3; rg_thickness = −0.13, false discovery rate–corrected p = 4.00 × 10−2). Meanwhile, local genetic correlations showed a mosaic of positive and negative associations. White blood cells shared on average 46.24% and 38.64% of trait-influencing genetic variants with surface area and thickness, respectively. Additionally, surface area shared 55 unique loci with the blood immune markers while thickness shared 15. Overall, monocyte count exhibited the largest genetic overlap with cortical brain structure. A series of gene enrichment analyses implicated neuronal-, astrocytic-, and schizophrenia-associated genes. Conclusions The findings indicate shared genetic underpinnings for cortical brain structure and blood immune markers, with implications for neurodevelopment and understanding the etiology of brain-related disorders.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.titleGenetic Overlap Between Global Cortical Brain Structure, C-Reactive Protein, and White Blood Cell Countsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2023 Society of Biological Psychiatryen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doi10.1016/j.biopsych.2023.06.008
dc.identifier.cristin2172777
dc.source.journalBiological Psychiatryen_US
dc.source.pagenumber62-71en_US
dc.identifier.citationBiological Psychiatry. 2024, 95 (1), 62-71.en_US
dc.source.volume95en_US
dc.source.issue1en_US


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