Associations of Accelerated DNA Methylation Aging Algorithms with Chronic Liver Disease and All-Cause Mortality
Background: Chronic liver disease (CLD) represents a substantial global health challenge, with significant morbidity and mortality worldwide. Biological aging may be involved in CLD-related outcomes, but the associations of diverse DNA methylation (DNAm) aging algorithms with CLD phenotypes and long-term mortality remain incompletely characterized. Methods: Using a US nationally representative cohort, we analyzed 12 DNAm aging algorithms in 2522 adults aged ≥50. CLD was classified into viral, alcohol-related, metabolic syndrome (MetS)-related liver disease, or uncharacterized groups. Advanced fibrosis was defined by AST-to-platelet ratio index ≥0.7. Associations of algorithms with CLD and all-cause mortality (followed through 2019) were assessed using multivariable-adjusted regression and logistic regression models and Cox models, accounting for complex sampling. Results: Among participants with CLD, DNAm aging algorithms showed only nominal associations with APRI-defined advanced fibrosis. GrimAgeMortAcc, GrimAge2MortAcc, HannumAgeAcc, PhenoAgeAcc, DunedinPoAm, and HorvathTelo were significantly associated with all-cause mortality. GrimAge-based measures and PhenoAgeAcc showed the strongest associations with all-cause mortality across CLD-related phenotypes (HRs ranged from 1.31 to 1.82). HorvathTelo was inversely associated with mortality risk (HR = 0.71, 95% CI: 0.62–0.82). Conclusions: DNAm aging algorithms, particularly GrimAge-based measures, are strongly associated with long-term all-cause mortality among individuals with CLD-related phenotypes. Although associations with fibrosis-related outcomes varied according to fibrosis definitions, DNAm aging algorithms may provide additional biological information for mortality risk stratification among individuals with CLD-related phenotypes.