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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Abstract 49: Validation of Imaging-Derived Body Composition Subphenotypes Reflects Distinct Fat Distribution Patterns Associated with Different Degrees of Cardiovascular Disease Risk.
Circulation 153, 1 (2026)
Obesity affects more than one billion people and
drives cardiometabolic disease risk. While traditional definitions rely
on BMI, recent criteria promote direct measurement of excess adiposity,
such as magnetic resonance imaging (MRI).Using
MRI-derived adipose tissue (AT) data of visceral, subcutaneous, bone
marrow, cardiac, renal, hepatic, pancreatic, and skeletal muscle fat
with k-means clustering, we previously identified five distinct body
composition subphenotypes (I–V), each displaying unique cardiovascular
risk profiles.This study aimed to establish
the generalizability of these subphenotypes by replication in the German
National Cohort (NAKO) and validation of their association with
cardiovascular disease (CVD) risk.We
analyzed cross-sectional data from 29,352 individuals (44.2% female;
mean age 48±12 years; BMI 26.5±4.7 kg/m2) from the NAKO baseline
examination (2014–2019), who underwent comprehensive health assessments,
including interviews, questionnaires, biosample collection, and
whole-body MRI. Body composition subphenotypes were replicated using a
cluster validation framework. Associations with 10-year CVD risk,
estimated by the Framingham score, were evaluated using linear
regression.The five subphenotypes (I–V) were
successfully replicated. Cluster I (“lean”) was youngest, had the
lowest prevalence of hypertension, hypercholesterolemia, and diabetes,
and the lowest CVD risk. This cluster was the reference category in
further analyses. Cluster II (“average adiposity”) showed intermediate
risk factor levels and a 2-fold higher CVD risk (95% CI 1.9–2.0).
Cluster III (“bone and muscle adiposity”) included older participants
(56±9 years) and showed a 3.7-fold higher risk (3.6–3.8), consistent
with regular age-related changes. Cluster IV (“hepato-abdominal
adiposity”) had a similar age (50±10 years) as cluster II (48±10 years)
but adverse cardiometabolic features, elevated liver enzymes, and
3.4-fold higher risk (3.3–3.5). Cluster V (“general and pancreatic
adiposity”) had the highest burden of comorbidities, and a 5-fold higher
CVD risk (4.8–5.2). With an age (59±8 years) comparable to cluster III,
it represents an unhealthy ageing pattern.In
conclusion, MRI robustly identifies distinct body composition
subphenotypes that capture the interplay of AT depots, potentially
reflect aging pathways, and show differential CVD risk. Our results
highlight the potential of AT distribution for personalized risk
assessment and ageing trajectories.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Meeting abstract
Schlagwörter
Cluster (spacecraft) ; Disease ; Cohort ; Framingham Heart Study ; Generalizability Theory ; Framingham Risk Score ; Adipose Tissue ; Risk Factor ; Cohort Study
ISSN (print) / ISBN
0009-7322
e-ISSN
1524-4539
Zeitschrift
Circulation
Quellenangaben
Band: 153,
Heft: Suppl_1,
Seiten: 1
Verlag
Lippincott Williams & Wilkins
Verlagsort
Two Commerce Sq, 2001 Market St, Philadelphia, Pa 19103 Usa
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Epidemiology (EPI)