Subphenotypes of body composition and their association with cardiometabolic risk - Magnetic resonance imaging in a
Elena Grune1, Johanna Nattenmüller2, Lena S Kiefer3
1Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany; Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
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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