A Global Metabolomic and Lipidomic Landscape of Human Plasma Across the Lifespan.

Understanding metabolic changes across the human lifespan is essential for addressing age-related health challenges. However, comprehensive metabolomic and lipidomic analyses, particularly in human plasma, remain underexplored. Herein, we performed untargeted metabolomics and lipidomics profiling of plasma collected from 136 individuals aged 0-84 years. This analysis reveals distinct metabolic signatures across life stages, with newborns displaying unique sphingosine (SPH) profiles, while aging was found to be characterized by elevated amino acid levels and lipid imbalances. Notably, we identified linear and nonlinear metabolic trajectories across the lifespan, highlighting critical transition points reflecting the key stages of metabolic reprogramming. By integrating these metabolic patterns, we developed an "aging clock" based on plasma metabolite profiling, thus providing a powerful tool to predict biological age. These findings offer new insights into the dynamic metabolic landscape of aging, paving the way for targeted interventions to improve healthspan and prevent age-related diseases.