Sarcopenia and its associated metabolic profile predict incident heart failure: a prospective cohort of 267,335 adults from the UK Biobank
Z I Y I Zhong, Y C Chen, Q X Xiang, H Y L Liu, M L Z Zhao, V P Pekovic, R S Sund, R S Sankaranarayanan, D J C Cuthbertson, M I IsanejadAbstract
Background
Sarcopenia is prevalent in heart failure (HF), but its role in incident HF and underlying metabolic mechanisms remains unclear.
Objectives
To examine whether clinical and metabolic features of sarcopenia are associated with HF risk.
Methods
We analysed UK Biobank participants without baseline HF. Associations between sarcopenia phenotypes and HF incidence were assessed using Cox regression. Nuclear magnetic resonance metabolomics was used to characterize sarcopenia-related profiles. Cox regression was applied to test metabolite–HF associations, and least absolute shrinkage and selection operator regression was further used to refine predictors. Incremental predictive value beyond clinical risk factors was evaluated using discrimination and reclassification metrics.
Results
During a median 15.3 years, 10,233 of 267,335 participants (mean age 56.5 ± 8.1 years; 44.6% men) developed HF. Confirmed sarcopenia (n=1,993) and low handgrip strength (HGS) (normalised to BMI) only (n=18,796) groups were associated with higher HF risk (HR 1.63, 95% CI 1.44–1.85; HR 1.76, 95% CI 1.66–1.85) compared with the reference group, with stronger effects in younger adults and women. Metabolomic profiling revealed sarcopenia-related alterations (higher glycoprotein acetyls, glucose–lactate, phenylalanine, tyrosine, 3-hydroxybutyrate; lower omega-3 fatty acids, docosahexaenoic acid, glycine, glutamine, histidine), which also predicted higher HF risk (Bonferroni-adjusted p < 0.05). Incorporating selected metabolites improved HF prediction (10-year net reclassification improvement 16–17%, integrated discrimination improvement 0.7–0.8%).
Conclusions
Sarcopenia, particularly reduced muscle strength, was a strong predictor for incident HF. Lipid-, amino acid-, and energy metabolism–related alterations modestly improved risk prediction, supporting their role as early biomarkers.For image description, please refer to the figure legend and surrounding text.