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

A technology of interactive network and positive and negative effects, applied in the field of computational biology and medical health, can solve the problems that the diversity index cannot be widely used in various diseases, and the research on microbial flora has not been widely used, so as to improve the accuracy of detection The effect of degree and sensitivity

Active Publication Date: 2018-06-01
KUNMING INST OF ZOOLOGY CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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.

Method used

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

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0019] Example 1: Comparing the positive and negative relationship ratios in the intestinal flora interaction network of HIV-positive patients and negative controls

[0020] The calculation process of the present invention is as accompanying drawing figure 1 shown

[0021] Data Sources:

[0022] In 2013, McHardy et al. published data on the intestinal microbiota of HIV-positive and negative individuals. The samples were collected from the intestinal mucosa of 20 HIV patients who had not received antiretroviral treatment and 20 healthy individuals. After the DNA is extracted from the sample, the 16S rDNA fragment is amplified using a general-purpose method. After sequencing using the Illumina HiSeq 2000 sequencing platform, an OTU table clustered on the basis of 97% similarity was obtained through bioinformatics analysis, where each OTU represents a species, and the sequencing content of the OTU in each sample represents the OTU in the Species abundance within this sample. ...

Embodiment 2

[0028] Example 2: Comparing the ratio of positive and negative relationships in the oral flora interaction network of smokers and non-smokers

[0029] The calculation process of the present invention is as accompanying drawing figure 1 shown

[0030] Data Sources:

[0031] Lazarevic et al published oral saliva microbial flora data of smokers and non-smokers in 2010, and collected oral saliva samples of two non-smoking individuals and three smoking individuals at three time points within 29 days. After DNA extraction, the 16S rDNA fragment was amplified with universal primers, the sequence was sequenced by the Genome Sequencer FLX system, and then the OTU table clustered on the basis of 97% similarity was obtained through bioinformatics analysis, in which each OTU represented Represents a species, and the sequencing content of the OTU in each sample represents the species abundance of the OTU in the sample.

[0032] Construction of oral flora interaction network:

[0033] B...

Embodiment 3

[0038] Example 3: Comparing the ratio of positive and negative edges in the skin flora interaction network of atopic dermatitis patients and healthy people

[0039] The calculation process of the present invention is as accompanying drawing figure 1 shown

[0040] Data Sources:

[0041] The skin microflora data of patients with atopic dermatitis (AD) and healthy people published by Kong et al. in 2012, samples were collected from 12 AD patients aged 2-15 years and 11 healthy people of skin samples. After the DNA was extracted from the sample, the 16S rDNA fragment was amplified by general purpose. After sequencing, the OTU table clustered on the basis of 97% similarity was obtained through bioinformatics analysis. Each OTU represented a species, and each The sequence content of the OTU in a sample represents the species abundance of the OTU in the sample.

[0042] Construction of skin flora interaction network:

[0043] Based on the species abundance expressed by OTU, the...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00
CPCA61B5/00
Inventor 马占山
Owner KUNMING INST OF ZOOLOGY CHINESE ACAD OF SCI
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