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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.
van der Meer, Dennis; Gurholt, Tiril P; Sønderby, Ida E; Shadrin, Alexey A; Hindley, Guy; Rahman, Zillur; de Lange, Ann-Marie G; Frei, Oleksandr; Leinhard, Olof D; Linge, Jennifer; Simon, Rozalyn; Beck, Dani; Westlye, Lars T; Halvorsen, Sigrun; Dale, Anders M; Karlsen, Tom H; Kaufmann, Tobias; Andreassen, Ole A.
Afiliación
  • van der Meer D; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway. d.v.d.meer@medisin.uio.no.
  • Gurholt TP; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands. d.v.d.meer@medisin.uio.no.
  • Sønderby IE; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Shadrin AA; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Hindley G; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.
  • Rahman Z; K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway.
  • de Lange AG; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Frei O; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Leinhard OD; Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK.
  • Linge J; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Simon R; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Beck D; LREN, Centre for Research in Neurosciences, Dept. of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
  • Westlye LT; Dept. of Psychiatry, University of Oxford, Oxford, UK.
  • Halvorsen S; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Dale AM; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway.
  • Karlsen TH; AMRA Medical, Linköping, Sweden.
  • Kaufmann T; Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
  • Andreassen OA; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Commun Biol ; 5(1): 1271, 2022 11 19.
Article en En | MEDLINE | ID: mdl-36402844
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 (h2 = .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 (rg = .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.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Diabetes Mellitus Tipo 2 Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Commun Biol Año: 2022 Tipo del documento: Article
Texto completo
Imprimir
XML
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Buscar en Google

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Diabetes Mellitus Tipo 2 Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Commun Biol Año: 2022 Tipo del documento: Article