AUTHOR=Ma Ya-Qing , Dang Ya-Min , Zeng Lv-Tao , Gao Xin , Li Si-Jia , Zhang Li-Qun , Li Jin , Zhou Xiao-Yang , Ren Shan-Shan , Liu Hong-Lei , Qi Ruo-Mei , Pang Jing , Cui Ju , Zhang Tie-Mei , Cai Jian-Ping TITLE=Utilizing nutrition-related biomarkers to develop a nutrition-related aging clock for the chinese demographic JOURNAL=Frontiers in Nutrition VOLUME=Volume 12 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1563220 DOI=10.3389/fnut.2025.1563220 ISSN=2296-861X ABSTRACT=IntroductionThis study aims to investigate the relationship between nutrition-related biomarkers, body composition, and oxidative stress indicators in the human aging process, so as to provide new insights for understanding individual aging differences and developing targeted intervention strategies.MethodsA total of 100 healthy participants aged 26–85 years were enrolled. Plasma concentrations of 9 amino acids and 13 vitamins were quantitatively analyzed, along with urinary oxidative stress markers 8-oxoGuo and 8-oxodGuo. Body composition was assessed using bioelectrical impedance analysis (BIA). A nutrition-based aging clock model was constructed using the Light Gradient Boosting Machine algorithm, with model performance evaluated by mean absolute error (MAE) and coefficient of determination (R2).ResultsThe younger group showed significantly lower levels of oxidative stress markers compared to the older group. Multiple amino acids and vitamins exhibited age-dependent changes in plasma concentrations. The developed aging clock model demonstrated high predictive accuracy, with an MAE of 2.5877 and R2 of 0.8807. Correlation analyses further indicated associations between model-predicted biological age and physiological changes reflected in biochemical and physical examination indicators.DiscussionThis study establishes a significant link between nutrition-related biomarkers, oxidative stress, body composition, and aging. The proposed model serves as a reliable tool for predicting biological age and offers a scientific basis for future research on aging mechanisms and personalized interventions.