Application of ratio of positive effects to negative effects in human microbial interaction network in assessment of human health and disease diagnosis

Abstract

The invention relates to the fields of computational biology and medical health, and mainly aims at personalized precise diagnosis and health assessment of diseases called "microbial flora-related diseases", such as the disease of the digestive tract, bacterial vaginosis and periodontitis. An assessment method based on the microbial interaction network analysis of the human microbial flora is disclosed and validated. Specifically, the above diagnostic or assessment purpose is realized by detecting and monitoring the ratio of positive effects to negative effects in a human microbial interactionnetwork. By analyzing the microbial flora data of the human body including intestines, vagina, lungs, mouth and various parts of the skin, the inventor found that the ratio of positive effects to negative effects in the microbial interaction network of patients and that in the microbial interaction network of healthy people (ie, P / N ratio) are significantly different. Therefore, an effective detection index and implementation technology can be provided for personalized precise diagnosis of "microbial flora-related diseases", and at the same time, reliable reference indicators and technical support can be provided for assessing the disease risk of healthy people.

Description

technical field [0001] The invention relates to the fields of computational biology and medical health, in particular to the application of the positive-negative relationship ratio in human-microbial interaction network in human health assessment and disease diagnosis. Background technique [0002] There are a large number of microorganisms in various parts of the human body. Except for a few pathogenic bacteria, the vast majority of microorganisms coexist with their hosts and influence each other. Since the Human Microbiome Project (HMP) was launched in 2008, a large number of studies have shown that the human microbiome is closely related to human health and diseases, especially obesity, colon cancer, dermatitis Diseases such as bacterial vaginosis, periodontitis, and bacterial vaginosis are more closely related to human microbial flora, and these diseases are called "microbial-related diseases". The etiology of most of these diseases is relatively complex, the developmen...

AI Technical Summary

Problems solved by technology

Most of the existing studies look for the difference between disease and healthy human microflora from the perspective of species diversity. However, many microbial-related diseases do not affect the biodiversity of the patient's microbiome. Therefore, the diversity index between patients and healthy individuals, Significance such as species abundance and diversity index often have no difference

In addition, the ecological methods based on diversity focus on the number of species, that is, the abundance itself, ignoring the interaction between species in the flora, and the interaction between species is more sensitive to changes in the host's internal environment. Therefore, traditional diversity indicators cannot be widely used in the diagnosis of various diseases and the assessment of human health status

[0004] Network analysis has already appeared in many fields of computational biology and bioinformatics, including genomics, proteomics, metabolomics, etc., but it has not been widely used in the study of microbial flora.

Images