Distinct relationships of compartment-specific fat distribution profiles with cardiovascular ageing and future cardiovascular events.
Authors
Affiliations (5)
Affiliations (5)
- Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, National Institute for Health Research Barts Biomedical Research Centre, Queen Mary University of London, London, UK.
- Division of Cardiovascular Sciences, British Heart Foundation Leicester Centre of Research Excellence, University of Leicester, Leicester, UK.
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.
- Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, National Institute for Health Research Barts Biomedical Research Centre, Queen Mary University of London, London, UK [email protected].
Abstract
Obesity is a major contributor to cardiovascular disease (CVD). Different fat depots may have distinct effects on cardiac ageing and cardiovascular risk. We examined associations of imaging-defined obesity phenotypes with biological heart ageing and incident CVD and evaluated whether they provide additional information beyond anthropometric measures. This study included UK Biobank participants without CVD, with cardiac and abdominal MRI and linked health records. Biological heart age was estimated using machine learning from 56 cardiac MRI phenotypes. Abdominal visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT) and pericardial adipose tissue (PAT) were clustered via K-means to identify distinct adiposity phenotypes. Mediation analysis quantified the contribution of individual fat compartments to incident CVD through biological heart ageing. Findings were compared with anthropometric measures. Analyses were sex-stratified. The analysis included 34 496 participants (55%, n=18 978 females) with an average age of 63.5 years. Median body mass index (BMI) was 25.7 kg/m<sup>2</sup>, with 58.4% classed as overweight or obese. Imaging-defined adiposity clustering identified a high-risk phenotype (comprising higher VAT, ASAT and PAT levels) associated with greater heart ageing and a lower-risk phenotype linked with reduced ageing. Imaging-defined adiposity clusters outperformed BMI categories in their association with biological heart age. In mediation analyses, VAT explained 14% of its association with incident CVD through accelerated heart ageing, the strongest mediation effect across all fat depots. PAT showed similar mediation (10.7%), but this fell to <1% after adjustment for VAT. Associations were more pronounced among males. Among the adiposity compartments studied, VAT showed the strongest relationships with cardiovascular ageing and incident CVD. While PAT showed initial associations, these were not independent of VAT. Imaging-defined adiposity phenotypes can allow more precise definition of cardiovascular risk and may enhance mechanistic understanding of obesity-related CVD, including sex-specific susceptibilities.