Microbial marker for echinococcosis as well as screening method and application of microbial marker

A technology of echinococcosis and screening method, which is applied in the field of disease diagnosis, can solve the problems of high false positive rate, lack of specificity, and inability to realize early diagnosis, and achieve the effect of good specificity and high prediction sensitivity

Active Publication Date: 2022-05-13
LANZHOU INST OF VETERINARY SCI CHINESE ACAD OF AGRI SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the diagnosis of echinococcosis is usually based on ultrasonography, combined with characteristic images of echinococcosis (CT, MRI) and epidemiological investigations, which lacks specificity; small cysts within 2 cm that lack characteristic imaging structures cannot be diagnosed. Diagnosis, leading to missed or misdiagnosed
Can only be identified after the formation of large hydatid cysts in the body, and early diagnosis cannot be achieved
And it is easy to be confused with hepatic cyst, hepatic hemangioma, etc., and it is highly dependent on the technical level and clinical experience of the operator
[0004] Immunological detection method is superior to ultrasonography in early diagnosis, but it often has cross-reaction with other tapeworms and trematodes, resulting in a high false positive rate
However, there is no report on a standard set of microbial markers for the detection of echinococcosis

Method used

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  • Microbial marker for echinococcosis as well as screening method and application of microbial marker
  • Microbial marker for echinococcosis as well as screening method and application of microbial marker
  • Microbial marker for echinococcosis as well as screening method and application of microbial marker

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] Collection of clinical stool samples and acquisition of fungal DNA data

[0055] (1) The stool samples of 63 patients with echinococcosis and 42 healthy controls were collected from the hospital, and DNA was extracted from the stool samples of patients with echinococcosis and healthy controls using a kit for extracting fecal fungal DNA, and then the ITS1 region Perform next-generation sequencing to obtain ITS1 sequencing data of intestinal flora;

[0056] (2) Search and match the Unite database (https: / / unite.ut.ee) with the BLAST method according to the ITS1 data to obtain the abundance value of each OTU. This match found 12472 OTU fungi;

Embodiment 2

[0058] Model algorithm selection and parameter optimization

[0059] The present invention obtains optimal random forest model (Random Forest) through a large amount of screening and matching, and specific method is as follows:

[0060] Use machine learning to pick model algorithms. Random forests utilize multiple decision tree classifiers whose output class is determined by the mode of the class output by individual trees. The cases of the sample data of the present invention have been clinically diagnosed and have classified labels, so they will be explored and selected in a supervised machine learning classification model. The fungal OTU abundance values ​​of all samples were used as input data, and the diagnostic results of samples were used as output classification labels. Algorithm construction with the following steps:

[0061] (1) All data obtained in Example 1 are randomly divided into 70% training set (n=73) and 30% test set (n=32);

[0062] (2) Build a machine l...

Embodiment 3

[0066] Fungal OTU selection and parameter optimization for specific species

[0067] (1) Calculate the importance (Mean DecreaseAccuracy) score of the training set variable features obtained by the random forest model (see figure 2 ), sort from high to low according to the score.

[0068] Using the rfcv and repeat functions in the randomForest software package, using ten-fold cross-validation (repeated 5 times), calculate the average error rate of gradually increasing the number of fungal variables (sorted according to the importance of variables) (see image 3 ), to find the number of fungal OTUs with the smallest error rate. The results showed that the error rate was the lowest when inputting the fungal abundance of 32 specific species as the characteristic variable.

[0069] (2) Input the OTU abundance values ​​of 32 specific species in the sample, construct a random forest model, and perform a grid search (grid) to optimize the mtry parameter using the ten-fold cross-va...

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Abstract

The invention provides an echinococcosis microbial marker as well as a screening method and application thereof, and belongs to the technical field of disease diagnosis. According to the method, ITS1 region sequencing is carried out on fungal components in faeces of healthy people and echinococcosis patients, the abundance of fungi is obtained, fungi of specific species are found through screening operation to serve as microbial markers, model optimization parameter adjustment is carried out through data with class labels, the accuracy and sensitivity of the model are improved, and the accuracy and sensitivity of the model are improved. Predicting the occurrence probability of the echinococcosis according to the output risk value, and indicating the balance state of the intestinal microorganisms at the same time. Experiments prove that the microbial marker for the echinococcosis can be effectively used for constructing an echinococcosis risk prediction model, the prediction sensitivity is high, the specificity is good, echinococcosis patients and healthy people can be effectively distinguished in multiple samples, the accuracy is 87.5% or above, and a foundation is laid for disease research.

Description

technical field [0001] The invention belongs to the technical field of disease diagnosis, and in particular relates to an echinococcosis microbial marker and a screening method and application thereof. Background technique [0002] Hydatid disease is a zoonotic parasitic disease caused by the infection of Echinococcus larvae that seriously affects human health and the development of animal husbandry. parasitic disease. Echinococcosis mainly includes Cysticechinococcosis (CE) caused by Echinococcus granulosus larvae and multilocular echinococcosis (CE) caused by Echinococcus granulosus larvae ( Alveolar echinococcosis, AE). [0003] Echinococcosis is asymptomatic in the early stage of infection, and symptoms usually appear after the formation of hydatid cysts. At present, the diagnosis of echinococcosis is usually based on ultrasonography, combined with characteristic images of echinococcosis (CT, MRI) and epidemiological investigations, which lacks specificity; small cyst...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B30/10G16B40/00G16B50/00C12Q1/6888
CPCG16B30/10G16B40/00G16B50/00C12Q1/6888Y02A90/10
Inventor 王帅才学鹏郭爱疆王玉桂刘仲藜邹扬
Owner LANZHOU INST OF VETERINARY SCI CHINESE ACAD OF AGRI SCI
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