Compartment-specific Fat Distribution Profiles have Distinct Relationships with Cardiovascular Ageing and Future Cardiovascular Events

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Abstract

Obesity is a global public health priority and a major risk factor for cardiovascular disease (CVD). Emerging evidence indicates variation in pathologic consequences of obesity deposition across different body compartments. Biological heart age may be estimated from imaging measures of cardiac structure and function and captures risk beyond traditional measures. Using cardiac and abdominal magnetic resonance imaging (MRI) from 34,496 UK Biobank participants and linked health record data, we investigated how compartment-specific obesity phenotypes relate to cardiac ageing and incident CVD risk. Biological heart age was estimated using machine learning from 56 cardiac MRI phenotypes. K-means clustering of abdominal visceral (VAT), abdominal subcutaneous (ASAT), and pericardial (PAT) adiposity identified a high-risk cluster (characterised by greater adiposity across all three depots) associated with accelerated cardiac ageing - and a lower-risk cluster linked to decelerated ageing. These clusters provided more precise stratification of cardiovascular ageing trajectories than established body mass index categories. Mediation analysis showed that VAT and PAT explained 13.7% and 11.9% of obesity-associated CVD risk, respectively, whereas ASAT contributed minimally, with effects more pronounced in males. Thus, cardiovascular risk appears to be driven primarily by visceral and pericardial rather than subcutaneous fat. Our findings reveal a distinct risk profile of compartment-specific fat distributions and show the importance of pericardial and visceral fat as drivers of greater cardiovascular ageing. Advanced image-defined adiposity profiling may enhance CVD risk prediction beyond anthropometric measures and enhance mechanistic understanding.

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