Causality between heart failure and epigenetic age: a bidirectional Mendelian randomization study

Area of Science:

• Cardiovascular Disease Epidemiology
• Genetics and Aging Research
• Biomarkers of Aging

Background:

• Heart failure (HF) is a common cardiovascular disease in older adults with a poor prognosis.
• Understanding the causal relationship between aging and HF is crucial for developing effective interventions.
• Epigenetic age serves as a biological marker of aging, distinct from chronological age.

Purpose of the Study:

• To investigate the causal relationship between epigenetic age and heart failure (HF) using a bidirectional Mendelian randomization (MR) approach.
• To assess whether genetically predicted epigenetic age influences the risk of developing HF.
• To determine if HF genetically influences epigenetic age.

Main Methods:

• A bidirectional Mendelian randomization (MR) analysis was performed using genome-wide association study data for epigenetic age clocks (GrimAge, HorvathAge, HannumAge, PhenoAge) and HF.
• The inverse-variance weighted (IVW) method was the primary analytical approach.
• Sensitivity analyses, including MR-Egger, weighted median, heterogeneity, leave-one-out, and pleiotropy analyses, were conducted to ensure robustness.

Main Results:

• The epigenetic PhenoAge clock showed a statistically significant causal effect, increasing the risk of heart failure (HF).
• The IVW analysis indicated an odds ratio (OR) of 1.015 (95% CI 1.002-1.028, P=0.028) for PhenoAge predicting HF.
• Other epigenetic age measures and the reverse causal analysis (HF on epigenetic age) did not yield statistically significant results.

Conclusions:

• This bidirectional MR study provides evidence for a causal link between genetically predicted epigenetic age and heart failure (HF) in individuals of European descent.
• The findings suggest that biological aging, as reflected by epigenetic age, is a contributing factor to HF development.
• Further investigation into epigenetic age across diverse populations and with additional HF genetic data is recommended.