Subphenotypes of body composition and their association with cardiometabolic risk – Magnetic resonance imaging in a population-based sample

Abstract

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.