Method for screening intestinal microorganism markers of chronic diseases and constructing early screening model

By screening and constructing a random forest model based on gut microbiota biomarkers, the problems of non-invasiveness, sensitivity, and parallel analysis of multiple diseases in early screening of chronic diseases were solved, achieving efficient and accurate screening and risk assessment for 11 chronic diseases.

CN122157760APending Publication Date: 2026-06-05TONGJI UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TONGJI UNIV
Filing Date
2026-03-02
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing chronic disease screening methods are not sufficiently non-invasive, sensitive, or capable of parallel analysis of multiple diseases, making it difficult to identify chronic diseases at an early stage. In particular, the need for co-screening of multiple chronic diseases has not been met.

Method used

By acquiring relative abundance data of gut microbiome metagenomics and clinical information, nested cross-validation and sequence feature selection methods were used to screen for specific gut microbiome biomarkers for health and chronic diseases. A random forest model was constructed for early screening, and the abundance of specific microbiome biomarkers was detected using fecal samples.

Benefits of technology

It enables early screening and risk assessment of 11 common chronic diseases, with high coverage and accuracy. It is non-invasive, convenient, and low-cost, and is suitable for health checkups, personalized medicine, and chronic disease follow-up monitoring.

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Abstract

The application discloses a health and chronic disease intestinal microorganism marker screening method, comprising the following steps: 1) obtaining sample intestinal microorganism metagenome relative abundance data and clinical information; 2) screening samples covering health and chronic disease phenotypes; 3) normalizing the intestinal microorganism metagenome relative abundance data of each sample; 4) in the training set, using nested cross-validation and sequence feature selection methods, screening phenotype-specific intestinal microorganism markers for health and each type of chronic disease phenotype respectively. The application also discloses a method for constructing a chronic disease early screening model based on the combination of the microorganism markers screened by the above method. The application realizes early precise screening and risk assessment of 11 common chronic diseases by screening intestinal microorganism markers and establishing a chronic disease early screening model, and can be used for distinguishing between healthy people and chronic disease risk people, and accurately identifying high-risk individuals of various chronic diseases.
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