Method for evaluating healthy life and disease risk based on phenotypic age acceleration

By calculating the phenotype age acceleration value and combining survival analysis models to evaluate health lifespan and disease risk, the problem of inability to comprehensively quantify health lifespan and disease risk in the existing technology is solved, and scientific guidance for individualized health management and disease prevention is achieved.

CN120388745APending Publication Date: 2025-07-29THE SECOND AFFILIATED HOSPITAL TO NANCHANG UNIV
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Patent Information

Application Number
CN202510877569.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-27
Publication Date
2025-07-29

AI Technical Summary

Technical Problem

The existing technology is mainly concentrated on a single disease endpoint, ignoring the synergistic impact of the coexistence and development of multiple diseases, unable to comprehensively quantify healthy lifespan and disease risks, and unable to effectively guide the prevention strategies for aging-related diseases.

Method used

By obtaining baseline data from the target population, phenotype age accelerated values were calculated, and the association between aging degree and disease-free survival years and disease risk was evaluated through survival analysis models, and assessment results of health life span and disease risk were generated.

Benefits of technology

Provides reliable health lifespan and disease risk assessments, providing scientific basis for individualized health management and disease prevention, helping to extend healthy lifespan and improve quality of life.

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Abstract

The invention discloses a method for accelerated assessment of healthy life and disease risk based on phenotypic age, and the method comprises the following steps: S101, obtaining baseline data of a target population, the baseline data comprising actual age and multi-system clinical chemistry biomarker data; s102, calculating a phenotypic age according to the baseline data, and determining a phenotypic age acceleration value through regression analysis of the phenotypic age and an actual age; s103, performing aging degree layering on the target population according to the phenotypic age acceleration value; s104, evaluating the association between the aging degree layering and the disease-free survival years and the disease risk through a preset survival analysis model; and S105, outputting an evaluation result, wherein the evaluation result represents the health life difference and the disease risk change of the target population. The biological aging degree is reliably evaluated, and a scientific basis is provided for individualized health management and disease prevention.
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