Epigenetic scores and aging clocks capture mortality risk in heart failure
P Meyre, M C Chong, P J Joseph, D L Leong, T M McCready, A G Grinvalds, S Y Yusuf, G P PareAbstract
Background
Current prognostic tools for heart failure (HF) rely mainly on clinical parameters and often fail to reflect the biological heterogeneity underlying patient outcomes. DNA methylation (DNAm)-based aging clocks and trait-specific epigenetic scores capture biological age and cumulative lifestyle and environmental exposures, potentially identifying high-risk patients not detected by clinical risk tools.
Purpose
To determine whether DNAm-based aging clocks and trait-specific epigenetic scores improve mortality risk prediction beyond clinical assessment in a multinational HF population.
Methods
We analyzed patients with established HF from the Global Congestive Heart Failure (G-CHF) study with available baseline whole-blood DNAm data. Eleven trait-specific DNAm scores (e.g., Smoking, Alcohol, CRP, BMI, diet) and five epigenetic aging clocks (GrimAge, HannumAge, PhenoAge, PaceOfAging, HorvathAge) were derived using published epigenome-wide association study weights. Mortality associations were assessed using multivariable Cox regression adjusted for age, sex, ancestry, and the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score. Patients were stratified according to number of DNAm score and aging clock extremes (≥1.5 standard deviation [SD]). LASSO regression was used to identify the most predictive DNAm scores and clocks, which were combined into a composite Epigenetic model. Model performance for mortality prediction was compared between the MAGGIC and the Epigenetic model using Harrell’s C-index.
Results
A total of 2,594 HF patients (mean±SD age, 63±14; 34% female) were included. During a median follow-up of 3 years, 565 (22%) patients died from any cause. In multivariable Cox models, several DNAm scores (CRP, Frailty, Mortality) and aging clocks (GrimAge, PhenoAge, PaceOfAging) were independently associated with mortality (Figure 1a). Having 3, 4 and ≥5 extreme DNAm scores/aging clocks conferred a 1.57-fold, 2.16-fold and 2.70-fold (P=2.96×10-3, P=4.36×10-5 and P=4.65×10-7) increased risk of death, respectively (Figure 1b). Using a LASSO-derived Epigenetic composite (including CRP, GrimAge, Mortality, PhenoAge, AHEI [Alternative healthy eating index]), patients with high Epigenetic but low MAGGIC had a 3.10-fold (95% CI 2.19-4.39) higher risk of death versus those with low Epigenetic and low MAGGIC (Figure 2a). The Epigenetic model improved mortality prediction beyond the MAGGIC score, particularly in patients from low-income countries (C-index 0.65 vs. 0.58, P=0.0115; Figure 2b).
Conclusions
A cumulative epigenetic signature stratifies mortality risk in HF and outperforms clinical risk assessment. DNAm-based profiling may enable more precise identification of high-risk patients beyond conventional scores.Figure1Figure2