Heterogeneous metabolomic aging across the same age and prediction of health outcome

Abstract

AbstractExisting metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, we leveraged metabolomic profiles of 239,291 UK Biobank participants for 10-year all-cause mortality prediction to generate and validate a new aging measure--MetaboAgeMort. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to conventional risk factors model improved the predictive ability of 10-year mortality. We identified 99 modifiable factors for MetaboAgeMort, where 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. Our study illuminates heterogeneous metabolomic aging across the same age, which provides avenues for developing anti-aging therapies and personalized interventions.