Utilizing nutrition-related biomarkers to develop a nutrition-related aging clock for the chinese demographic.

Abstract

Introduction: This 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.

Methods: A 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).

Results: The 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.

Discussion: This 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.