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The link between liver fat and cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition
Univ Oslo, Norway; Univ Oslo, Norway; Maastricht Univ, Netherlands.
Univ Oslo, Norway; Univ Oslo, Norway.
Univ Oslo, Norway; Univ Oslo, Norway; Oslo Univ Hosp, Norway; Univ Oslo, Norway.
Univ Oslo, Norway; Univ Oslo, Norway.
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2022 (English)In: Communications Biology, E-ISSN 2399-3642, Vol. 5, no 1, article id 1271Article in journal (Refereed) Published
Abstract [en]

A GWAS study of European individuals uncovers genetic associations between whole-body MRI derived measures and cardiometabolic diseases and highlights the key role of liver fat in cardiometabolic health. 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.

Place, publisher, year, edition, pages
NATURE PORTFOLIO , 2022. Vol. 5, no 1, article id 1271
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Clinical Science
Identifiers
URN: urn:nbn:se:liu:diva-190333DOI: 10.1038/s42003-022-04237-4ISI: 000886136900005PubMedID: 36402844OAI: oai:DiVA.org:liu-190333DiVA, id: diva2:1716303
Note

Funding Agencies|Research Council of Norway [276082, 213837, 223273, 204966/F20, 229129, 249795/F20, 225989, 248778, 249795, 298646, 300767]; South-Eastern Norway Regional Health Authority [2013-123, 2014-097, 2015-073, 2016-064, 2017-004, 2017-112, 2019-101, 2020-060, 2022-080]; Stiftelsen Kristian Gerhard Jebsen [SKGJ-MED-021]; European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (ERC Starting Grant) [802998]; ERA-Net Cofund through the ERA PerMed project IMPLEMENT; National Institutes of Health [R01MH100351, R01GM104400]; European Unions Horizon 2020 Research and Innovation Program [847776]

Available from: 2022-12-05 Created: 2022-12-05 Last updated: 2023-09-29

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Dahlqvist Leinhard, Olof

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