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dc.date.accessioned2022-12-13T16:29:10Z
dc.date.available2022-12-13T16:29:10Z
dc.date.created2022-12-07T12:38:47Z
dc.date.issued2022
dc.identifier.citationvan der Meer, Dennis Gurholt, Tiril Pedersen Sønderby, Ida Elken Shadrin, Alexey Hindley, Guy Frederick Lanyon Rahman, Zillur de Lange, Ann-Marie Glasø Frei, Oleksandr Leinhard, Olof D. Linge, Jennifer Simon, Rozalyn Beck, Dani Westlye, Lars Tjelta Halvorsen, Sigrun Dale, Anders M Karlsen, Tom Hemming Kaufmann, Tobias Andreassen, Ole . The link between liver fat and cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition. Communications Biology. 2022, 5(1)
dc.identifier.urihttp://hdl.handle.net/10852/98170
dc.description.abstractAbstract Obesity and associated morbidities, metabolic associated fatty liver disease (MAFLD) included, constitute some of the largest public health threats worldwide. Body composition and related risk factors are known to be heritable and identification of their genetic determinants may aid in the development of better prevention and treatment strategies. Recently, large-scale whole-body MRI data has become available, providing more specific measures of body composition than anthropometrics such as body mass index. Here, we aimed to elucidate the genetic architecture of body composition, by conducting genome-wide association studies (GWAS) of these MRI-derived measures. We ran both univariate and multivariate GWAS on fourteen MRI-derived measurements of adipose and muscle tissue distribution, derived from scans from 33,588 White European UK Biobank participants (mean age of 64.5 years, 51.4% female). Through multivariate analysis, we discovered 100 loci with distributed effects across the body composition measures and 241 significant genes primarily involved in immune system functioning. Liver fat stood out, with a highly discoverable and oligogenic architecture and the strongest genetic associations. Comparison with 21 common cardiometabolic traits revealed both shared and specific genetic influences, with higher mean heritability for the MRI measures (h 2  = .25 vs. .13, p  = 1.8x10 −7 ). We found substantial genetic correlations between the body composition measures and a range of cardiometabolic diseases, with the strongest correlation between liver fat and type 2 diabetes (r g  = .49, p  = 2.7x10 −22 ). These findings show that MRI-derived body composition measures complement conventional body anthropometrics and other biomarkers of cardiometabolic health, highlighting the central role of liver fat, and improving our knowledge of the genetic architecture of body composition and related diseases.
dc.languageEN
dc.publisherNature Portfolio
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleThe link between liver fat and cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition
dc.title.alternativeENEngelskEnglishThe link between liver fat and cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition
dc.typeJournal article
dc.creator.authorvan der Meer, Dennis
dc.creator.authorGurholt, Tiril Pedersen
dc.creator.authorSønderby, Ida Elken
dc.creator.authorShadrin, Alexey
dc.creator.authorHindley, Guy Frederick Lanyon
dc.creator.authorRahman, Zillur
dc.creator.authorde Lange, Ann-Marie Glasø
dc.creator.authorFrei, Oleksandr
dc.creator.authorLeinhard, Olof D.
dc.creator.authorLinge, Jennifer
dc.creator.authorSimon, Rozalyn
dc.creator.authorBeck, Dani
dc.creator.authorWestlye, Lars Tjelta
dc.creator.authorHalvorsen, Sigrun
dc.creator.authorDale, Anders M
dc.creator.authorKarlsen, Tom Hemming
dc.creator.authorKaufmann, Tobias
dc.creator.authorAndreassen, Ole
cristin.unitcode185,53,10,70
cristin.unitnameNORMENT part UiO
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin2090051
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Communications Biology&rft.volume=5&rft.spage=&rft.date=2022
dc.identifier.jtitleCommunications Biology
dc.identifier.volume5
dc.identifier.issue1
dc.identifier.pagecount0
dc.identifier.doihttps://doi.org/10.1038/s42003-022-04237-4
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2399-3642
dc.type.versionPublishedVersion
cristin.articleid1271
dc.relation.projectSIGMA2/NS9666S
dc.relation.projectNIHE/R01GM104400
dc.relation.projectNFR/223273
dc.relation.projectNFR/213837
dc.relation.projectNFR/225989
dc.relation.projectEC/HEU/847776
dc.relation.projectNIHE/R01MH100351
dc.relation.projectHSØ/2017-004
dc.relation.projectNFR/204966
dc.relation.projectNFR/276082
dc.relation.projectSKGJ/SKGJ-MED-021
dc.relation.projectHSØ/2022-080
dc.relation.projectNFR/229129
dc.relation.projectNFR/298646
dc.relation.projectNFR/300767
dc.relation.projectNFR/248778
dc.relation.projectERC/802998
dc.relation.projectNFR/249795
dc.relation.projectHSØ/2015-073
dc.relation.projectHSØ/2020-060
dc.relation.projectHSØ/2017-112
dc.relation.projectHSØ/2016-064
dc.relation.projectHSØ/2013-123
dc.relation.projectHSØ/2019-101
dc.relation.projectHSØ/2014-097


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