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.

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Publication Details

Journal
Aging Cell
Published
2025-12-06
DOI
https://doi.org/10.1111/acel.70316
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Tingting Liang, Fang Ni, Beibei Huang, Rui Zhao et al.
Aging Cell
Metabolomics and Mass Spectrometry Studies
article

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

Tingting Liang, Fang Ni, Beibei Huang, Rui Zhao, Xiaobi Huang, Mingming Zhu, Xinru Liu
article en

Abstract

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.

Aging CellVol. 25(1)
University of Science and Technology of China (CN), Anhui Medical University (CN), Anhui Provincial Children's Hospital (CN)
Openalex Percentile: Top 65%
Metabolomics and Mass Spectrometry Studies
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