Physiological age prediction model based on urine proteins and metabolites and applications thereof
By constructing a physiological age prediction model based on urinary proteins and metabolites, the problem of non-invasively assessing an individual's aging status and health risks has been solved, enabling accurate physiological age prediction and early disease identification, and supporting self-health management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING HOSPITAL
- Filing Date
- 2025-01-09
- Publication Date
- 2026-07-10
AI Technical Summary
Current technologies lack stable, non-invasive aging clock models, making it impossible to effectively assess an individual's physiological age and health status, predict health risks, or enable self-health monitoring and early identification of age-related diseases.
By identifying urinary aging biomarkers through non-targeted metabolomics and proteomics, a physiological age prediction model based on urinary proteins and metabolites was constructed. Using indicators such as cartilage intermediate layer protein, collagen Alpha 1 chain, myristic acid, and 12-methyltridecanoic acid, combined with machine learning algorithms, a simplified comprehensive clock was constructed to achieve accurate prediction of physiological age.
It provides an accurate, convenient, and non-invasive method for assessing an individual's aging status and health risks, enabling early identification of age-related diseases, discovery of anti-aging targets, and support for self-health monitoring.
Smart Images
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