Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites.

ABSTRACT: Chronological age is a major risk factor for numerous diseases. However, chronological age does not capture the complex biological aging process. The difference between chronological age and biologically driven aging could be more informative in reflecting health status. Here, we set out to develop a metabolomic age prediction model by applying ridge regression and bootstrapping with 826 metabolites (678 endogenous and 148 xenobiotics) measured by an untargeted platform in relatively healthy blood donors aged 18-75 years from the INTERVAL study (N = 11 977; 50.2% men). After bootstrapping internal validation, the metabolomic age prediction models demonstrated high performance with an adjusted R2 of 0.83 using all metabolites and 0.82 using only endogenous metabolites. The former was signif

SUBMITTER: Faquih TO 

PROVIDER: S-EPMC11809259 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature