Imaging-derived Sarcopenic Obesity Index predicts heart failure risk and mortality in large cohort
Background
The prognostic value of obesity in cardiovascular disease is complex, with traditional measures like BMI showing inconsistent associations with outcomes, particularly in heart failure. Sarcopenic obesity, characterized by excess fat and low muscle mass, offers a more nuanced risk assessment. However, its routine quantification in clinical practice remains challenging. This study aimed to develop a translatable method for assessing sarcopenic obesity from cardiovascular imaging to clarify its clinical relevance and underlying biological mechanisms.
Study Design
Researchers developed a deep learning pipeline to quantify pectoralis major muscle mass from 55,768 cardiovascular magnetic resonance (CMR) examinations. This muscle mass data was combined with body weight to create a novel sarcopenic obesity index. The index's associations with cardiac remodeling phenotypes and adverse cardiovascular and mortality outcomes were assessed using multivariable models. Additionally, genome-wide association analysis (GWAS), colocalization, and polygenic risk score evaluation were performed for the index. Transcriptomic profiling of skeletal muscle across 7 pathophysiological states was conducted to assess differential gene expression.
Results
A higher sarcopenic obesity index was significantly associated with adverse cardiac remodeling. The index also predicted an increased risk of incident heart failure (HR: 1.31; 95% CI: 1.16-1.49), cardiovascular death (HR: 1.51; 95% CI: 1.25-1.81), and all-cause mortality (HR: 1.37; 95% CI: 1.26-1.49).
Key Findings
- A higher sarcopenic obesity index was associated with adverse cardiac remodeling.
- Increased sarcopenic obesity index raised incident heart failure risk by 31% (HR: 1.31).
- Cardiovascular death risk increased by 51% (HR: 1.51) with a higher index.
- All-cause mortality risk increased by 37% (HR: 1.37) with a higher index.
- Genome-wide association analysis identified 16 loci for sarcopenic obesity, including genes linked to heart failure.
Why It Matters
This study introduces a translatable, imaging-derived method for identifying sarcopenic obesity, offering a powerful tool for risk stratification in cardiovascular disease. By accurately identifying individuals at higher risk of heart failure and mortality, clinicians could implement earlier, targeted interventions. The genetic insights, particularly the identification of ACVR2B modulation during muscle atrophy, highlight potential therapeutic targets. This could inform future strategies involving compounds like bimagrumab (an ACVR2B inhibitor) and semaglutide, which are being explored to enhance fat loss while preserving lean muscle mass, offering a pathway to mitigate sarcopenic obesity's adverse effects.
sarcopenic-obesity
cardiovascular-disease
heart-failure
mortality
deep-learning
imaging