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Subphenotypes of body composition and their association with cardiometabolic risk - Magnetic resonance imaging in a population-based sample.
Metabolism 164:156130 (2025)
BACKGROUND: For characterizing health states, fat distribution is more informative than overall body size. We used population-based whole-body magnetic resonance imaging (MRI) to identify distinct body composition subphenotypes and characterize associations with cardiovascular disease (CVD) risk. METHODS: Bone marrow, visceral, subcutaneous, cardiac, renal, hepatic, skeletal muscle and pancreatic adipose tissue were measured by MRI in n = 299 individuals from the population-based KORA cohort. Body composition subphenotypes were identified by data-driven k-means clustering. CVD risk was calculated by established scores. RESULTS: We identified five body composition subphenotypes, which differed substantially in CVD risk factor distribution and CVD risk. Compared to reference subphenotype I with favorable risk profile, two high-risk phenotypes, III&V, had a 3.8-fold increased CVD risk. High-risk subphenotype III had increased bone marrow and skeletal muscle fat (26.3 % vs 11.4 % in subphenotype I), indicating ageing effects, whereas subphenotype V showed overall high fat contents, and particularly elevated pancreatic fat (25.0 % vs 3.7 % in subphenotype I), indicating metabolic impairment. Subphenotype II had a 2.7-fold increased CVD risk, and an unfavorable fat distribution, probably smoking-related, while BMI was only slightly elevated. Subphenotype IV had a 2.8-fold increased CVD risk with comparably young individuals, who showed high blood pressure and hepatic fat (17.7 % vs 3.0 % in subphenotype I). CONCLUSIONS: Whole-body MRI can identify distinct body composition subphenotypes associated with different degrees of cardiometabolic risk. Body composition profiling may enable a more comprehensive risk assessment than individual fat compartments, with potential benefits for individualized prevention.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Adipose Tissue ; Body Composition ; Cardiometabolic Risk ; Clustering ; Magnetic Resonance Imaging ; Obesity ; Population-based; Subcutaneous Adipose-tissue; Fatty Liver-disease; Ectopic Fat; Pancreas; Kora
ISSN (print) / ISBN
0026-0495
e-ISSN
1532-8600
Quellenangaben
Volume: 164,
Article Number: 156130
Publisher
Elsevier
Publishing Place
1600 John F Kennedy Boulevard, Ste 1800, Philadelphia, Pa 19103-2899 Usa
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Epidemiology II (EPI2)
Institute of Diabetes Research and Metabolic Diseases (IDM)
Institute of Diabetes Research and Metabolic Diseases (IDM)
Grants
German Federal Ministry of Education and Research (BMBF)
state of Bavaria
University Hospital of Augsburg
Munich Center of Health Sciences (MC-Health)
German Research Foundation
Centre for Diabetes Research (DZD e. V., Neuherberg, Germany)
Siemens Healthcare
state of Bavaria
University Hospital of Augsburg
Munich Center of Health Sciences (MC-Health)
German Research Foundation
Centre for Diabetes Research (DZD e. V., Neuherberg, Germany)
Siemens Healthcare