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GWAS Study

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 D, Gurholt TP, Sønderby IE et al.

36402844 PubMed ID
GWAS Study Type
33532 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

VD
van der Meer D
GT
Gurholt TP
SI
Sønderby IE
SA
Shadrin AA
HG
Hindley G
RZ
Rahman Z
DL
de Lange AG
FO
Frei O
LO
Leinhard OD
LJ
Linge J
SR
Simon R
BD
Beck D
WL
Westlye LT
HS
Halvorsen S
DA
Dale AM
KT
Karlsen TH
KT
Kaufmann T
AO
Andreassen OA
Chapter II

Abstract

Summary of the research findings

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.

33,532 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

33532
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
U.K.
Recruitment Country
Chapter IV

Analysis

Comprehensive review of health and genetic findings

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