WO2018124619A1 - Method for diagnosing bladder cancer via microbial metagenomic analysis - Google Patents

Abstract

The present invention relates to a method for diagnosing bladder cancer via microbial metagenomic analysis and, more particularly, to a method for diagnosing bladder cancer by performing metagenomic analysis of a microbe, such as a bacterium and an archaeon, by using a subject-derived sample, and analyzing an increase or decrease in the content of a specific microbe-derived extracellular vesicle. An extracellular vesicle secreted from a microbe, such as a bacterium, present in the environment can be absorbed into the body and directly affect the occurrence of cancer, and bladder cancer is difficult to diagnose early on before any symptom appears, which makes efficient treatment difficult. As such, through the metagenomic analysis of a microbe, such as a bacterium and an archaeon, using a human body-derived sample according to the present invention, the risk of the onset of bladder cancer can be predicted in advance, enabling early diagnosis and prediction of a bladder cancer risk group and delay of the time of the onset or prevention of the onset with proper care, and early diagnosis is still possible even after the onset, which can lower the incidence rate of bladder cancer and enhance the treatment effect.

Description

Bladder cancer diagnostic method through microbial metagenome analysis

The present invention relates to a method for diagnosing bladder cancer through a microbial metagenome analysis, and more specifically, the content of specific bacteria and archaea-derived extracellular vesicles by performing microbial metagenomic analysis of bacteria, archaea, etc. using a sample derived from a subject. The present invention relates to a method for diagnosing bladder cancer by analyzing the increase and decrease.

Bladder cancer (stomach carcinoma) is a malignant tumor of the bladder, which accounts for 90% of the transitional epithelial cell carcinoma derived from the transitional epithelial cell in direct contact with urine, and other squamous cell carcinoma, adenocarcinoma and sarcoma. Bladder cancers can be divided into superficial bladder cancers limited to the bladder mucosa or submucosa, invasive bladder cancers involving the muscle layer, and metastatic bladder cancers that have spread to other organs.

Smoking is the most dangerous factor of bladder cancer, and it is reported that smokers are twice as likely to get bladder cancer, and since the bladder is the last place to be discharged through the body, the carcinogen caused by smoking is the primary risk factor for bladder cancer. Known. In addition to smoking, occupationally exposed chemicals, etc., are also claimed to be risk factors. In terms of race, the incidence rate is more than twice that of the black and Hispanic race, and the incidence of men is four times higher than that of women. However, despite the development of modern medicine, there is no method of predicting bladder cancer by non-invasive method, and the existing diagnosis method is often found when solid cancer such as bladder cancer is advanced. To prevent this, it is an efficient way to anticipate the occurrence of bladder cancer and causative factors in advance, and to provide measures to prevent bladder cancer in high-risk groups.

On the other hand, the symbiosis of the human body reaches 100 trillion times 10 times more than human cells, the number of genes of the microorganism is known to be more than 100 times the number of human genes. A microbiota is a microbial community, including bacteria, archaea, and eukarya that exist in a given settlement. The intestinal microbiota plays an important role in human physiology. In addition, it is known to have a great effect on human health and disease through interaction with human cells. The symbiotic bacteria secrete nanometer-sized vesicles to exchange information about genes and proteins in other cells. The mucous membrane forms a physical protective film that particles larger than 200 nanometers (nm) in size can't pass through, so that the symbiotic bacteria cannot pass through the mucosa, but bacterial-derived vesicles are usually less than 100 nanometers in size. It freely speaks to the mucous membrane and is absorbed by our body.

Metagenomics, also called environmental genomics, is an analysis of metagenomic data obtained from samples taken from the environment. Recently, it has become possible to list the bacterial composition of the human microflora by a method based on 16s ribosomal RNA (16s rRNA) sequencing. Next generation sequencing of 16s rDNA sequencing gene of 16s ribosomal RNA is performed. , NGS) platform (Nature. 2007 Oct 18; 449 (7164): 804-810). However, in the development of bladder cancer, there has been no report on a method for identifying bladder cancer and diagnosing bladder cancer through metagenomic analysis present in bacterial-derived vesicles in human derivatives such as blood or urine.

In order to diagnose bladder cancer, the present inventors extracted a gene from bacteria and archaea-derived extracellular vesicles using blood and urine, a sample derived from a subject, and performed a metagenome analysis on the result, which may act as a causative factor of bladder cancer. Bacterial-derived extracellular vesicles were identified, which completed the present invention.

Accordingly, an object of the present invention is to provide a method for providing information for diagnosing bladder cancer through metagenomic analysis of bacteria and archaea-derived extracellular vesicles.

In addition, an object of the present invention is to provide a method for diagnosing bladder cancer and predicting the risk of developing bladder cancer through metagenomic analysis of the extracellular vesicles.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problem, another task that is not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the object of the present invention as described above, the present invention provides a method for providing information for diagnosing bladder cancer, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease in the content of the normal-derived sample and the bacteria and / or archaea-derived extracellular vesicles by sequencing the PCR product.

The present invention also provides a bladder cancer diagnostic method comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease in the content of the normal-derived sample and the bacteria and / or archaea-derived extracellular vesicles by sequencing the PCR product.

The present invention also provides a method for predicting the risk of developing bladder cancer, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease in the content of the normal-derived sample and the bacteria and / or archaea-derived extracellular vesicles by sequencing the PCR product.

In one embodiment of the invention, the subject sample may be blood or urine.

In another embodiment, at least one class selected from the group consisting of Rubrobacteria and Erysipelotrichi isolated from the subject blood sample in step (c). It may be to compare the increase or decrease in the content of bacterial-derived extracellular vesicles.

In another embodiment of the present invention, Rubrobacterales, Erysipelotrichales, Burkholderiales, Enterobacteria, isolated from the subject blood sample in step (c) It may be to compare the increase or decrease in the content of one or more order bacteria-derived extracellular vesicles selected from the group consisting of Enterobacteriales, Lactobacillales, Neisseriales, RF32.

In another embodiment, Oxalobacteraceae isolated from the subject blood sample in step (c) (Oxalobacteraceae), Rikenellaaceae (Erysipelotrichaceae), Basil Bacillaceae, Rhizobiaceae, Fusobacteriaceae, Pseudomonadaceae, Comamonadaceae, Planococcaceae, Enterobacteriaceci Enterobacteriaceae, Lachnospiraceae, Corynebacteriaceae, Deinococcaceae, Porphyromonadaceae, Neisseriaceae, Enterero Extracellular vesicles derived from one or more family bacteria selected from the group consisting of Enterococcaceae, Lactobacillaceae, Tissierellaceae, and Peptocacaaceae Of It may be to compare the amount of increase or decrease.

In another embodiment of the present invention, Cupriavidus, Eubacterium, Blautia, Catenibacterium (Cupriavidus) isolated from the subject blood sample in step (c) Catenibacterium, Collinsella, Geobacillus, Roseburia, Coprococcus, Facalicaliterterium, Pseudomonas, Corynebacterium, Corynebacterium, Mucispirillum, Deinococcus, Wife Locus (Anaerococcus), Dorea, Enterococcus, Adlercreutzia, Parabacteroides, To compare the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Lactobacillus, rc4-4, Peptoniphilus, and Pinegoldia Can be.

In another embodiment, the cyanobacteria, Gemmatimonadetes, Planctomycetes, Acidobacteria isolated from the urine sample of the subject in step (c) It may be to compare the increase and decrease of the content of one or more phylum bacteria-derived extracellular vesicles selected from the group consisting of, and Euryarchaeota.

In another embodiment of the present invention, Chlooplast, Methanobacteria, Planctomycetia, Akidobacterium river, isolated from the subject urine sample in step (c). (Acidobacteriia), and Pedosphaerae (Pedosphaerae) can be compared to increase or decrease the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of.

In another embodiment, Stramenopiles, Streptophyta, Pseudomonadales, Turicibacterales isolated from the subject urine sample in step (c) Increase or decrease in the amount of extracellular vesicles derived from one or more order bacteria selected from the group consisting of Turicibacterales, Methanobacteriales, Gemmatales, Acidobacteriales, and Ellin329 It may be to compare the.

In another embodiment of the present invention, Flavobacteriaceae, Lactobacillaceae, Pseudomonadaceae, Luminosity isolated from the subject urine sample in the step (c) Ruminococcaceae, Comamonadaceae, Turicibacteraceae, Clostridiaceae, Gordoniaaceae, Rikennellaceae, Pres 1 selected from the group consisting of Prevotellaceae, Methanobacteriaceae, Barnesiellaceae, Peptostreptococcaceae, and Koribacteraceae. It may be to compare the increase or decrease in the content of extracellular vesicles derived from species or more family (bacteria).

In another embodiment of the present invention, Rhizobium, Proteus, Pseudomonas, Lactobacillus, Lactobacillus, Turicibacter isolated from the subject urine sample in step (c). ), Luminococcus, Klebsiella, Facalicaliterterium, Brevundimonas, Clostridium, Jeotgalicoccus, Megasphaera , At least one genus selected from the group consisting of Gordonia, Prevotella, Actinobacillus, Thermoanerobacterium, and Metanobrevibacter. ) May be compared to increase or decrease the content of bacterial-derived extracellular vesicles.

In another embodiment of the invention, the blood may be whole blood, serum, plasma, or blood monocytes.

Extracellular vesicles secreted by bacteria and archaea present in the environment can be absorbed directly into the body and directly affect cancer development, and since bladder cancer is difficult to diagnose early due to difficult early diagnosis, the human body according to the present invention Metagenome analysis of extracellular vesicles derived from bacteria using the derived samples predicts the risk of bladder cancer in advance, and diagnoses and predicts the risk group of bladder cancer early, so that it can be delayed or prevented by proper management. Early diagnosis can reduce the incidence of bladder cancer and increase the therapeutic effect. In addition, metagenome analysis in patients diagnosed with bladder cancer can be used to avoid the causative agent to improve the course of the cancer or prevent recurrence.

Figure 1a is a photograph of the distribution of bacteria and vesicles by time after the oral administration of enteric bacteria and bacterial derived vesicles (EV) to the mouse, Figure 1b is 12 hours after oral administration, blood And several organs were extracted to evaluate the distribution of bacteria and vesicles in the body.

Figure 2 shows the distribution of bacterial derived vesicles from bladder cancer patients and normal blood, and performing a metagenome analysis to show the distribution of bacterial derived vesicles (EVs) of significant diagnostic performance at the class level.

3 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order (neck) level after separating the bacteria-derived vesicles from bladder cancer patients and normal blood.

Figure 4 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating the bacteria-derived vesicles in bladder cancer patients and normal blood, and performing a metagenome analysis.

5 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separating the bacteria-derived vesicles from bladder cancer patients and normal blood.

6 is a result showing the distribution of bacteria-derived vesicles (EVs) of significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles in bladder cancer patients and normal urine.

7 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level by separating the bacteria-derived vesicles from bladder cancer patients and normal urine.

FIG. 8 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the neck level after separation of bacteria-derived vesicles from bladder cancer patients and normal urine.

9 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating the bacteria-derived vesicles from bladder cancer patients and normal urine.

10 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separating the bacteria-derived vesicles in bladder cancer patients and normal urine.

The present invention relates to a method for diagnosing bladder cancer through bacterial and archaea metagenomic analysis, and the present inventors extracted genes from bacterial and archaea-derived extracellular vesicles using a sample derived from a subject, and performed a metagenomic analysis on them. Bacterial-derived extracellular vesicles that could act as causative agents of bladder cancer were identified.

Thus, the present invention comprises the steps of (a) extracting DNA from the extracellular vesicles isolated from the subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(C) provides an information providing method for diagnosing bladder cancer comprising the step of comparing the increase and decrease of the content of bacteria and archaea-derived extracellular vesicles and the normal-derived sample through the sequencing of the PCR product.

As used herein, the term "diagnosis of bladder cancer" refers to determining whether bladder cancer is likely to develop, whether bladder cancer is relatively high, or whether bladder cancer has already occurred. The method of the present invention can be used to prevent or delay the onset of the disease through special and appropriate management as a patient at high risk of developing bladder cancer for any particular patient. In addition, the methods of the present invention can be used clinically to determine treatment by early diagnosis of bladder cancer and selection of the most appropriate treatment regimen.

The term "metagenome" used in the present invention, also referred to as "metagenome", refers to the total of the genome including all viruses, bacteria, fungi, etc. in an isolated area such as soil, animal intestine, It is mainly used as a concept of genome explaining the identification of many microorganisms at once using sequencer to analyze microorganisms which are not cultured. In particular, metagenome does not refer to one species of genome or genome, but refers to a kind of mixed dielectric as the genome of all species of one environmental unit. This is a term from the point of view of defining a species in the course of the evolution of biology in terms of functional species as well as various species that interact with each other to create a complete species. Technically, rapid sequencing is used to analyze all DNA and RNA, regardless of species, to identify all species in one environment, and to identify interactions and metabolism. In the present invention, metagenome analysis was preferably performed using bacteria-derived extracellular vesicles isolated from blood and urine.

In the present invention, the subject sample may be blood or urine, and the blood may preferably be whole blood, serum, plasma, or blood monocytes, but is not limited thereto.

In an embodiment of the present invention, the metagenome analysis of the extracellular vesicles derived from bacteria and archaea was performed, and at the level of phylum, class, order, family, and genus, Each analysis identified bacterial vesicles that could actually cause bladder cancer.

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial metagenome at the river level for the vesicles present in the blood samples from the subject, the contents of the extracellular vesicles derived from Rubrobacteria and Erysipelotrichi bacteria are found in bladder cancer patients and normal people. There was a significant difference between them (see Example 4).

More specifically, in an embodiment of the present invention, bacterial metagenomes were analyzed at the neck level for vesicles present in a blood sample derived from a subject, and Rubrobacterales, Erysipelotrichales, Burkholderiales, Enterobacteriales, Lactobacillales, Neisseriales, and RF32 neck bacterial derived cells. There was a significant difference in the content of external vesicles between bladder cancer patients and normal individuals (see Example 4).

More specifically, in one embodiment of the present invention, the bacterial metagenome of the vesicles present in the blood samples from the subject at the level of analysis, Oxalobacteraceae, Rikenellaceae, Erysipelotrichaceae, Bacillaceae, Rhizobiaceae, Fusobacteriaceae, Pseudomonadaceae, Comamonadaceae, Planococcaceae, There were significant differences between Enterobacteriaceae, Lachnospiraceae, Corynebacteriaceae, Deinococcaceae, Porphyromonadaceae, Neisseriaceae, Enterococcaceae, Lactobacillaceae, Tissierellaceae, and Peptococcaceae and bacterial extracellular vesicles between normal and bladder cancer patients (see Example 4).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial metagenome at the genus level for the vesicles present in the blood samples from the subject, Cupriavidus, Eubacterium, Blautia, Catenibacterium, Collinsella, Geobacillus, Roseburia, Coprococcus, Faecalibacterium, Pseudomonas, Corynebacterium, Mucispirillum, Deinococcus, Anaerococcus, Dorea, Enterococcus, Adlercreutzia, Parabacteroides, Lactobacillus, rc4-4, Peptoniphilus, and Finegoldia were found to be significantly different between bladder cancer patients and normal individuals. See Example 4).

More specifically, in one embodiment of the present invention, the results of analyzing the bacterial metagenome at the gate level for the vesicles present in the urine sample derived from the subject, the content of extracellular vesicles derived from Cyanobacteria, Gemmatimonadetes, Planctomycetes, Acidobacteria, and Euryarchaeota door bacteria There was a significant difference between this bladder cancer patient and a normal person (see Example 5).

More specifically, in one embodiment of the present invention, the results of analysis of bacterial metagenome at the river level for vesicles present in the urine sample derived from the subject, the content of extracellular vesicles derived from Chloroplast, Methanobacteria, Planctomycetia, Acidobacteriia, and Pedosphaerae river bacteria There was a significant difference between this bladder cancer patient and a normal person (see Example 5).

More specifically, in an embodiment of the present invention, the bacterial metagenome was analyzed at the neck level for vesicles present in a urine sample derived from a subject, and Stramenopiles, Streptophyta, Pseudomonadales, Turicibacterales, Methanobacteriales, Gemmatales, Acidobacteriales, and Ellin329 throat bacteria The content of derived extracellular vesicles was significantly different between bladder cancer patients and normal subjects (see Example 5).

More specifically, in one embodiment of the present invention, the bacterial metagenomic analysis of the vesicles present in the urine sample from the subject at the level of Flavobacteriaceae, Lactobacillaceae, Pseudomonadaceae, Ruminococcaceae, Comamonadaceae, Turicibacteraceae, Clostridiaceae, Gordoniaceae, Rikenellaceae, The contents of prevotellaceae, Methanobacteriaceae, Barnesiellaceae, Peptostreptococcaceae, and Koribacteraceae and bacteria-derived extracellular vesicles were significantly different between bladder cancer patients and normal individuals (see Example 5).

More specifically, in one embodiment of the present invention, the bacterial metagenome of the vesicles present in the subject-derived urine sample at the genus level, Rhizobium, Proteus, Pseudomonas, Lactobacillus, Turicibacter, Ruminococcus, Klebsiella, Faecalibacterium, Brevundimonas The contents of extracellular vesicles derived from bacteria of the genus Clostridium, Jeotgalicoccus, Megasphaera, Gordonia, Prevotella, Actinobacillus, Thermoanaerobacterium, and Methanobrevibacter were significantly different between bladder cancer patients and normal individuals (see Example 5).

The present invention, through the results of the above Example, by identifying the bacteria-derived extracellular vesicles isolated from blood and urine by metagenomic analysis of bacteria-derived vesicles significantly changed in bladder cancer patients compared to normal people was identified , Metagenomic analysis confirmed that bladder cancer can be diagnosed by analyzing the increase and decrease of the contents of the bacteria-derived vesicles at each level.

EXAMPLE

Example  1. Analysis of absorption, distribution, and excretion of intestinal bacteria and bacterial-derived vesicles

In order to evaluate whether the intestinal bacteria and bacteria-derived vesicles are absorbed systemically through the gastrointestinal tract, experiments were performed as follows. Fluorescently labeled enterobacteriaceae and enteric bacteria-derived vesicles were administered to the gastrointestinal tract at doses of 50 μg, respectively, and the fluorescence was measured after 0, 5, 3, 6 and 12 hours. As a result of observing the entire image of the mouse, as shown in FIG. 1A, the bacteria (Bacteria) were not absorbed systemically, but in the case of bacteria-derived vesicles (EV), they were absorbed systemically 5 minutes after administration and administered. After 3 hours, the bladder was strongly observed, indicating that the vesicles were excreted by the urinary system. In addition, the vesicles were found to exist in the body until 12 hours of administration.

After the systemic absorption of enterobacteriaceae and enteric bacteria-derived vesicles systemically, in order to assess the invasion of various organs, the fluorescently labeled 50 μg of bacteria and bacteria-derived vesicles were administered in the same manner as above 12 hours. Blood, Heart, Lung, Liver, Kidney, Spleen, Adipose tissue, and Muscle were extracted from mice. As shown in FIG. 1B, the intestinal bacteria (Bacteria) were not absorbed into each organ, whereas the intestinal bacteria-derived extracellular vesicles (EV) were detected in the tissues, as shown in FIG. And distribution in liver, kidney, spleen, adipose tissue, and muscle.

Example 2. Vesicle Separation and DNA Extraction from Blood and Urine

To separate the vesicles from the blood and urine and extract the DNA, first put the blood or urine in a 10 ml tube and centrifuge (3,500 xg, 10min, 4 ° C) to settle the suspended solids to recover only the supernatant and then to the new 10 ml. Transferred to the tube. After removing the bacteria and foreign substances from the recovered supernatant using a 0.22 ㎛ filter, transfer to centripreigugal filters (50 kD) and centrifuged at 1500 xg, 4 ℃ for 15 minutes to discard the material smaller than 50 kD and 10 ml Concentrated until. Once again, remove the bacteria and foreign substances using a 0.22 ㎛ filter, discard the supernatant using ultra-fast centrifugation for 3 hours at 150,000 xg, 4 ℃ with a Type 90ti rotor and dissolve the agglomerated pellet in physiological saline (PBS) Vesicles were obtained.

According to the above method, 100 μl of the vesicles isolated from blood and urine were boiled at 100 ° C. to let the internal DNA come out of the lipid and then cooled on ice for 5 minutes. Next, in order to remove the remaining suspended matter, centrifugation at 10,000 x g, 4 ℃ for 30 minutes, and collected only the supernatant and quantified the DNA amount using Nanodrop. Thereafter, PCR was performed with the 16s rDNA primer shown in Table 1 to confirm whether the bacteria-derived DNA exists in the extracted DNA, and it was confirmed that the bacteria-derived gene exists in the extracted gene.

primer		order	SEQ ID NO:
16S rDNA	16S_V3_F	5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3 '	One
	16S_V4_R	5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3 '	2

Example 3 Metagenomic Analysis Using DNA Extracted from Blood and Urine

After the gene was extracted by the method of Example 2, PCR was performed using the 16S rDNA primer shown in Table 1 to amplify the gene and perform sequencing (Illumina MiSeq sequencer). Output the result as a Standard Flowgram Format (SFF) file, convert the SFF file into a sequence file (.fasta) and a nucleotide quality score file using GS FLX software (v2.9), check the credit rating of the lead, and window (20 bps) The part with the average base call accuracy of less than 99% (Phred score <20) was removed. After removing the low quality part, only the lead length was 300 bps or more (Sickle version 1.33), and the Operational Taxonomy Unit (OTU) performed UCLUST and USEARCH for clustering according to sequence similarity. Specifically, the clustering is based on 94% genus, 90% family, 85% order, 80% class, and 75% sequence similarity. OTU's door, river, neck, family and genus level classifications were performed, and bacteria with greater than 97% sequence similarity were analyzed using BLASTN and GreenGenes' 16S DNA sequence database (108,453 sequences) (QIIME).

Example  4. separated from blood Germ-derived  parcel Metagenome  Analysis-based Bladder Cancer Diagnosis Model

By the method of Example 3, the vesicles were isolated from the blood of 91 patients with bladder cancer and 176 normal people of age and sex matched with metagenome sequencing. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

As a result of analyzing the blood-derived vesicles in the blood at the class level, when the diagnostic model was developed with the Rubrobacteria and Erysipelotrichi bacterium biomarkers, the diagnostic performance of bladder cancer was significant (see Table 2 and FIG. 2). .

	Control		Bladder cancer		t-test		Training set			Test set
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity	AUC	sensitivity	specificity
c__Rubrobacteria	0.0009	0.0026	0.0000	0.0000	0.0001	0.05	0.65	0.90	0.27	0.52	0.84	0.09
c__Erysipelotrichi	0.0100	0.0162	0.0013	0.0013	0.0000	0.13	0.78	0.92	0.39	0.74	0.80	0.28

The analysis of blood-derived vesicles in the blood at the order level showed significant diagnostic performance for bladder cancer when developing diagnostic models with Rubrobacterales, Erysipelotrichales, Burkholderiales, Enterobacteriales, Lactobacillales, Neisseriales, and RF32 throat bacterial biomarkers. (See Table 3 and FIG. 3).

	Control		Bladder cancer		t-test		Training set			Test set
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity	AUC	sensitivity	specificity
o__Rubrobacterales	0.0009	0.0026	0.0000	0.0000	0.0001	0.05	0.65	0.90	0.27	0.52	0.84	0.09
o__Erysipelotrichales	0.0100	0.0162	0.0013	0.0013	0.0000	0.13	0.78	0.92	0.39	0.74	0.80	0.28
o__Burkholderiales	0.0304	0.0333	0.0066	0.0066	0.0000	0.22	0.81	0.79	0.56	0.84	0.86	0.66
o__Enterobacteriales	0.0924	0.0763	0.0377	0.0377	0.0000	0.41	0.76	0.83	0.44	0.76	0.76	0.59
o__Lactobacillales	0.0892	0.0469	0.1895	0.1895	0.0000	2.12	0.71	0.97	0.42	0.65	1.00	0.19
o__Neisseriales	0.0150	0.0439	0.0446	0.0446	0.0000	2.97	0.75	0.96	0.07	0.79	0.98	0.13
o__RF32	0.0002	0.0009	0.0026	0.0026	0.0007	11.82	0.72	0.97	0.22	0.69	0.98	0.31

Analysis of bacteria-derived vesicles in the blood at the family level revealed that Oxalobacteraceae, Rikenellaceae, Erysipelotrichaceae, Bacillaceae, Rhizobiaceae, Fusobacteriaceae, Pseudomonadaceae, Comamonadaceae, Planococcaceae, Enterobacteriaceae, Lachnospiraceae, Corynebacteriaceae, Deinorimonaaceae, Nepoccocaceae, When diagnostic models were developed with Tissierellaceae, Peptococcaceae and bacterial biomarkers, the diagnostic performance for bladder cancer was significant (see Table 4 and FIG. 4).

	Control		Bladder cancer		t-test		Training set			Test set
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity	AUC	sensitivity	specificity
f__Oxalobacteraceae	0.0134	0.0231	0.0009	0.0009	0.0000	0.06	0.80	0.74	0.68	0.85	0.86	0.50
f__Rikenellaceae	0.0025	0.0058	0.0002	0.0002	0.0000	0.09	0.70	0.99	0.02	0.63	1.00	0.00
f__Erysipelotrichaceae	0.0100	0.0162	0.0013	0.0013	0.0000	0.13	0.78	0.92	0.39	0.74	0.80	0.28
f__Bacillaceae	0.0077	0.0134	0.0015	0.0015	0.0000	0.19	0.76	0.94	0.24	0.69	0.92	0.06
f__Rhizobiaceae	0.0057	0.0099	0.0011	0.0011	0.0000	0.19	0.73	0.98	0.03	0.74	1.00	0.03
f__Fusobacteriaceae	0.0025	0.0045	0.0005	0.0005	0.0000	0.21	0.70	0.98	0.03	0.59	1.00	0.00
f__Pseudomonadaceae	0.0804	0.0860	0.0214	0.0214	0.0000	0.27	0.81	0.81	0.49	0.77	0.84	0.50
f__Comamonadaceae	0.0129	0.0253	0.0048	0.0048	0.0001	0.38	0.65	0.96	0.14	0.55	0.90	0.00
f__Planococcaceae	0.0047	0.0117	0.0019	0.0019	0.0032	0.41	0.64	0.99	0.00	0.59	1.00	0.00
f__Enterobacteriaceae	0.0924	0.0763	0.0377	0.0377	0.0000	0.41	0.76	0.83	0.44	0.76	0.76	0.59
f__Lachnospiraceae	0.0584	0.0641	0.0288	0.0288	0.0000	0.49	0.68	0.94	0.17	0.62	0.88	0.06
f__Corynebacteriaceae	0.0310	0.0396	0.0655	0.0655	0.0000	2.11	0.68	0.94	0.22	0.74	0.94	0.19
f__Deinococcaceae	0.0014	0.0042	0.0036	0.0036	0.0033	2.51	0.61	0.98	0.03	0.60	1.00	0.03
f__Porphyromonadaceae	0.0060	0.0064	0.0160	0.0160	0.0001	2.68	0.62	0.98	0.20	0.67	1.00	0.25
f__Neisseriaceae	0.0150	0.0439	0.0446	0.0446	0.0000	2.97	0.75	0.96	0.07	0.79	0.98	0.13
f__Enterococcaceae	0.0065	0.0097	0.0207	0.0207	0.0000	3.17	0.67	0.98	0.34	0.44	0.96	0.16
f__Lactobacillaceae	0.0349	0.0331	0.1276	0.1276	0.0000	3.66	0.77	0.99	0.37	0.77	0.98	0.38
f __ [Tissierellaceae]	0.0068	0.0137	0.0254	0.0254	0.0000	3.76	0.76	0.98	0.34	0.78	0.92	0.41
f__Peptococcaceae	0.0011	0.0043	0.0052	0.0052	0.0000	4.95	0.80	0.96	0.27	0.72	0.98	0.31

Analysis of bacteria-derived vesicles in the blood at genus level revealed Cupriavidus, Eubacterium, Blautia, Catenibacterium, Collinsella, Geobacillus, Roseburia, Coprococcus, Faecalibacterium, Pseudomonas, Corynebacterium, Mucispirillum, Deinococcus, Anaerococcuszi, Dorea, Enterler, Enter When diagnostic models were developed with bacterial biomarkers of the genus Parabacteroides, Lactobacillus, rc4-4, Peptoniphilus, and Finegoldia, the diagnostic performance for bladder cancer was significant (see Table 5 and FIG. 5).

	Control		Bladder cancer		t-test		Training set			Test set
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity	AUC	sensitivity	specificity
g__Cupriavidus	0.008	0.020	0.000	0.000	0.000	0.02	0.76	0.98	0.12	0.87	0.96	0.25
g __ [Eubacterium]	0.002	0.004	0.000	0.000	0.000	0.03	0.77	0.91	0.25	0.70	0.88	0.06
g__Blautia	0.013	0.021	0.001	0.001	0.000	0.04	0.82	0.71	0.71	0.77	0.73	0.69
g__Catenibacterium	0.006	0.014	0.000	0.000	0.000	0.04	0.77	0.91	0.25	0.67	0.82	0.19
g__Collinsella	0.006	0.012	0.000	0.000	0.000	0.07	0.80	0.82	0.54	0.68	0.71	0.47
g__Geobacillus	0.003	0.008	0.000	0.000	0.000	0.11	0.65	0.94	0.22	0.50	0.86	0.06
g__Roseburia	0.002	0.003	0.000	0.000	0.000	0.17	0.68	0.92	0.24	0.60	0.80	0.06
g__Coprococcus	0.007	0.008	0.001	0.001	0.000	0.20	0.80	0.79	0.53	0.67	0.76	0.38
g__Faecalibacterium	0.021	0.024	0.005	0.005	0.000	0.23	0.74	0.97	0.24	0.77	0.86	0.19
g__Pseudomonas	0.076	0.083	0.019	0.019	0.000	0.26	0.81	0.83	0.54	0.78	0.84	0.50
g__Corynebacterium	0.031	0.040	0.066	0.066	0.000	2.11	0.68	0.94	0.22	0.74	0.94	0.19
g__Mucispirillum	0.002	0.006	0.004	0.004	0.021	2.43	0.65	0.98	0.03	0.52	1.00	0.03
g__Deinococcus	0.001	0.004	0.004	0.004	0.003	2.52	0.61	0.98	0.03	0.60	1.00	0.03
g__Anaerococcus	0.003	0.009	0.009	0.009	0.001	2.59	0.68	0.98	0.12	0.64	0.94	0.16
g__Dorea	0.003	0.004	0.008	0.008	0.002	2.66	0.67	0.94	0.25	0.57	0.88	0.22
g__Enterococcus	0.006	0.009	0.018	0.018	0.000	3.01	0.67	0.98	0.36	0.44	0.96	0.16
g__Adlercreutzia	0.002	0.004	0.006	0.006	0.000	3.07	0.67	0.94	0.10	0.68	1.00	0.13
g__Parabacteroides	0.004	0.006	0.016	0.016	0.000	3.55	0.68	0.95	0.27	0.69	0.96	0.31
g__Lactobacillus	0.034	0.033	0.127	0.127	0.000	3.70	0.77	0.99	0.37	0.77	0.98	0.38
g__rc4-4	0.001	0.004	0.005	0.005	0.000	5.30	0.80	0.96	0.27	0.73	0.98	0.31
g__Peptoniphilus	0.001	0.004	0.006	0.006	0.000	5.33	0.73	0.97	0.25	0.70	0.90	0.28
g__Finegoldia	0.002	0.008	0.010	0.010	0.000	5.70	0.75	0.98	0.32	0.76	0.98	0.28

Example  5. separated from urine Germ-derived  parcel Metagenome  Analysis-based Bladder Cancer Diagnosis Model

By the method of Example 3, vesicles were isolated from urine of 42 patients with bladder cancer and 107 normal subjects matched with age and sex, followed by metagenome sequencing. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

Analysis of bacteria-derived vesicles in the urine at the phylum level showed significant diagnostic performance for bladder cancer when diagnostic models were developed with Cyanobacteria, Gemmatimonadetes, Planctomycetes, Acidobacteria, and Euryarchaeota phytobacterial biomarkers. 6 and FIG. 6).

	Control		Bladder cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
p__Cyanobacteria	0.0240	0.0331	0.0047	0.0053	0.0000	0.19	0.77	0.92	0.29
p__Gemmatimonadetes	0.0003	0.0010	0.0013	0.0017	0.0008	4.35	0.68	0.95	0.26
p__Planctomycetes	0.0003	0.0012	0.0014	0.0022	0.0027	4.80	0.70	0.96	0.19
p__Acidobacteria	0.0008	0.0022	0.0047	0.0077	0.0024	6.17	0.70	0.97	0.31
p__Euryarchaeota	0.0004	0.0011	0.0028	0.0030	0.0000	6.91	0.74	0.95	0.43

Analysis of bacterial vesicles in urine at the class level showed significant diagnostic performance for bladder cancer when developing diagnostic models with Chloroplast, Methanobacteria, Planctomycetia, Acidobacteriia, and Pedosphaerae river bacterial biomarkers. 7 and FIG. 7).

	Control		Bladder cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
c__Chloroplast	0.0236	0.0329	0.0041	0.0050	0.0000	0.17	0.78	0.92	0.33
c__Methanobacteria	0.0004	0.0011	0.0028	0.0030	0.0000	6.98	0.73	0.95	0.43
c__Planctomycetia	0.0001	0.0005	0.0012	0.0021	0.0033	9.39	0.73	0.96	0.24
c__Acidobacteriia	0.0001	0.0004	0.0016	0.0029	0.0014	22.66	0.69	0.99	0.29
c __ [Pedosphaerae]	0.0000	0.0000	0.0008	0.0020	0.0001		0.63	1.00	0.24

Analysis of urine-derived vesicles at the order level showed diagnostic performance for bladder cancer when the diagnostic model was developed with Stramenopiles, Streptophyta, Pseudomonadales, Turicibacterales, Methanobacteriales, Gemmatales, Acidobacteriales, and Ellin329 wood bacterial biomarkers. This was significant (see Table 8 and FIG. 8).

	Control		Bladder cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
o__Stramenopiles	0.0047	0.0074	0.0000	0.0000	0.0001	0.00	0.87	0.87	0.57
o__Streptophyta	0.0189	0.0321	0.0041	0.0050	0.0000	0.22	0.70	0.98	0.05
o__Pseudomonadales	0.1456	0.1521	0.0641	0.0372	0.0000	0.44	0.70	0.97	0.10
o__Turicibacterales	0.0014	0.0022	0.0037	0.0040	0.0010	2.66	0.70	0.92	0.19
o__Methanobacteriales	0.0004	0.0011	0.0028	0.0030	0.0000	6.98	0.73	0.95	0.43
o__Gemmatales	0.0000	0.0003	0.0010	0.0021	0.0066	19.91	0.71	0.97	0.24
o__Acidobacteriales	0.0001	0.0004	0.0016	0.0029	0.0014	22.66	0.69	0.99	0.29
o__Ellin329	0.0000	0.0000	0.0006	0.0013	0.0096	126.84	0.65	0.99	0.26

Family-level analysis of bacterial vesicles in urine revealed diagnostic performance for bladder cancer when the diagnostic model was developed with Stramenopiles, Streptophyta, Pseudomonadales, Turicibacterales, Methanobacteriales, Gemmatales, Acidobacteriales, and Ellin329 and bacterial biomarkers. This was significant (see Table 9 and FIG. 9).

	Control		Bladder cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
f__Flavobacteriaceae	0.0028	0.0038	0.0004	0.0009	0.0000	0.15	0.72	1.00	0.02
f__Lactobacillaceae	0.0507	0.0497	0.0216	0.0115	0.0000	0.43	0.68	0.95	0.07
f__Pseudomonadaceae	0.0765	0.0775	0.0348	0.0237	0.0000	0.45	0.74	0.92	0.12
f__Ruminococcaceae	0.0567	0.0706	0.1340	0.0720	0.0000	2.36	0.84	0.92	0.33
f__Comamonadaceae	0.0054	0.0095	0.0135	0.0100	0.0000	2.48	0.80	0.94	0.24
f__Turicibacteraceae	0.0014	0.0022	0.0037	0.0040	0.0010	2.66	0.70	0.92	0.19
f__Clostridiaceae	0.0077	0.0105	0.0208	0.0180	0.0001	2.69	0.77	0.87	0.31
f__Gordoniaceae	0.0001	0.0005	0.0008	0.0013	0.0020	5.73	0.69	0.96	0.24
f__Rikenellaceae	0.0011	0.0029	0.0064	0.0064	0.0000	5.87	0.84	0.95	0.48
f__Prevotellaceae	0.0102	0.0121	0.0609	0.0785	0.0002	5.95	0.93	0.94	0.74
f__Methanobacteriaceae	0.0004	0.0011	0.0028	0.0030	0.0000	6.98	0.73	0.95	0.43
f __ [Barnesiellaceae]	0.0002	0.0008	0.0018	0.0038	0.0096	9.42	0.71	0.97	0.36
f__Peptostreptococcaceae	0.0010	0.0020	0.0097	0.0085	0.0000	9.64	0.87	0.95	0.62
f__Koribacteraceae	0.0001	0.0004	0.0015	0.0026	0.0009	21.66	0.69	0.99	0.29

Analysis of bacteria-derived vesicles in the urine at genus level revealed Rhizobium, Proteus, Pseudomonas, Lactobacillus, Turicibacter, Ruminococcus, Klebsiella, Faecalibacterium, Brevundimonas, Clostridium, Jeotgalicoccus, Megasphaera, Gordonia, Prebacterus, Methanol, and Actobacillus When developing a diagnostic model with a genus bacterial biomarker, the diagnostic performance for bladder cancer was significant (see Table 10 and Figure 10).

	Control		Bladder cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
g__Rhizobium	0.0044	0.0068	0.0001	0.0003	0.0000	0.01	0.87	0.89	0.57
g__Proteus	0.0197	0.0287	0.0015	0.0027	0.0000	0.07	0.81	0.91	0.45
g__Pseudomonas	0.0736	0.0770	0.0267	0.0203	0.0000	0.36	0.79	0.87	0.31
g__Lactobacillus	0.0503	0.0497	0.0208	0.0114	0.0000	0.41	0.69	0.94	0.12
g__Turicibacter	0.0014	0.0022	0.0037	0.0040	0.0010	2.66	0.70	0.92	0.19
g__Ruminococcus	0.0071	0.0134	0.0188	0.0173	0.0002	2.67	0.77	0.95	0.24
g__Klebsiella	0.0015	0.0038	0.0040	0.0038	0.0005	2.67	0.76	0.93	0.17
g__Faecalibacterium	0.0181	0.0330	0.0488	0.0354	0.0000	2.70	0.80	0.92	0.24
g__Brevundimonas	0.0004	0.0010	0.0010	0.0014	0.0073	2.85	0.68	0.95	0.12
g__Clostridium	0.0016	0.0049	0.0073	0.0130	0.0088	4.62	0.72	0.97	0.14
g__Jeotgalicoccus	0.0011	0.0023	0.0055	0.0078	0.0008	5.06	0.71	0.94	0.31
g__Megasphaera	0.0003	0.0011	0.0013	0.0028	0.0251	5.15	0.63	0.99	0.14
g__Gordonia	0.0001	0.0005	0.0008	0.0013	0.0020	5.73	0.69	0.96	0.24
g__Prevotella	0.0102	0.0121	0.0609	0.0785	0.0002	5.95	0.93	0.94	0.74
g__Actinobacillus	0.0002	0.0006	0.0010	0.0018	0.0037	6.64	0.66	0.97	0.21
g__Thermoanaerobacterium	0.0002	0.0013	0.0013	0.0050	0.1583	6.91	0.61	0.98	0.05
g__Methanobrevibacter	0.0002	0.0007	0.0018	0.0025	0.0003	9.15	0.74	0.97	0.26

The description of the present invention set forth above is for illustrative purposes, and one of ordinary skill in the art may understand that the present invention may be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. There will be. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

By predicting the risk of bladder cancer in advance through metagenomic analysis of bacterial-derived extracellular parcel vesicles using a human-derived sample according to the present invention, early diagnosis and prediction of risk groups of bladder cancer can be delayed or prevented. It can be diagnosed early after the onset, which can lower the incidence of bladder cancer and increase the therapeutic effect. In addition, metagenome analysis in patients diagnosed with bladder cancer can be used to avoid the causative agent to improve the course of the cancer or prevent recurrence.

Claims (16)

1. (a) extracting DNA from extracellular vesicles isolated from a subject sample;

   (b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

   (c) comparing the increase and decrease of the content of the normal-derived sample and the bacterial-derived extracellular vesicles through the sequencing of the PCR product, information providing method for bladder cancer diagnosis.
2. The method of claim 1,

   At least one door selected from the group consisting of cyanobacteria, Gemmatimonadetes, Planctomycetes, Acidobacteria, and Euryarchaeota in step (c). (phylum) Information providing method, characterized in that comparing the increase and decrease of the content of the bacteria-derived extracellular vesicles.
3. The method of claim 1,

   In the step (c) Rubrobacteria, Erysipelotrichi, Chryoplast, Methanobacteria, Planctomycetia, Akidobacterium steel ( Acidobacteriia), and Pedosphaerae (Pedosphaerae), characterized in that comparing the increase and decrease of the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of.
4. The method of claim 1,

   Rubrobacterales, Erysipelotrichales, Burkholderiales, Enterobacteriales, Lactobacillales, Lactobacillales in the step (c) (Neisseriales), RF32, Stramenopiles, Streptophyta, Pseudomonadales, Turicibacterales, Methanobacteriales, Gemmatales ), Comparing the increase or decrease of the content of one or more order bacteria-derived extracellular vesicles selected from the group consisting of Acidobacteriales, and Ellin329.
5. The method of claim 1,

   Oxalobacteraceae, Rikennellaceae, Erysipelotrichaceae, Bacillaceae, Rhizobiaceae, and Fusobacteria in step (c). Fusobacteriaceae, Pseudomonadaceae, Comamonadaceae, Planococcaceae, Enterobacteriaceae, Lachnospiraceae, Corynebacteria Corynebacteriaceae, Deinococcaceae, Porphyromonadaceae, Neisseriaceae, Enterococcaceae, Lactobacillaceae, Tissi Tissierellaceae, Peptococcaceae, Flavobacteriaceae, Lactobacillaceae, Pseudomonadaceae, Luminococcaceae, Coma Mona City (Coma monadaceae, Turicibacteraceae, Clostridiaceae, Gordoniaaceae, Rikennellaceae, Prevotellaceae, Metanobacterial Of one or more family bacterial-derived extracellular vesicles selected from the group consisting of Methanobacteriaceae, Barnesiellaceae, Peptostreptococcaceae, and Koribacteraceae. Information providing method, characterized in that comparing the increase and decrease.
6. The method of claim 1,

   Cupriavidus, Eubacterium, Blautia, Catenibacterium, Collinsella, Geobacillus, Roseview in step (c) Roseburia, Coprococcus, Facalcalibacterium, Pseudomonas, Corynebacterium, Mucispirillum, Deinococcus, Wife Anaerococcus, Dorea, Enterococcus, Adlercreutzia, Parabaceroides, Lactobacillus, rc4-4, Pepttoniphilus , Finegoldia, Rhizobium, Proteus, Pseudomonas, Lactobacillus, Turicibacter, Rumicoccus, Klebsiella, Klebsiella Facalicaliterium, Brevundimonas ( Brebundimonas, Clostridium, Jeotgalicoccus, Megasphaera, Gordonia, Prevotella, Actinobacillus, Thermoaerobacte An information providing method, characterized by comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of (Thermoanaerobacterium) and Metanobrevibacter.
7. The method of claim 1,

   The subject sample is blood or urine, characterized in that the information providing method.
8. The method of claim 7, wherein

   The blood is characterized in that the whole blood, serum, plasma, or blood monocytes, information providing method.
9. (a) extracting DNA from extracellular vesicles isolated from a subject sample;

   (b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

   (c) comparing the increase and decrease of the content of the normal-derived sample and the bacterial-derived extracellular vesicles through the sequencing of the PCR product, bladder cancer diagnostic method.
10. The method of claim 9,

    At least one door selected from the group consisting of cyanobacteria, Gemmatimonadetes, Planctomycetes, Acidobacteria, and Euryarchaeota in step (c). (phylum) A diagnostic method, characterized by comparing the increase and decrease of the content of bacteria-derived extracellular vesicles.
11. The method of claim 9,

    In the step (c) Rubrobacteria, Erysipelotrichi, Chryoplast, Methanobacteria, Planctomycetia, Akidobacterium steel ( Acidobacteriia), and Pedosphaerae (Pedosphaerae), characterized in that the comparison of the increase or decrease in the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of.
12. The method of claim 9,

    Rubrobacterales, Erysipelotrichales, Burkholderiales, Enterobacteriales, Lactobacillales, Lactobacillales in the step (c) (Neisseriales), RF32, Stramenopiles, Streptophyta, Pseudomonadales, Turicibacterales, Methanobacteriales, Gemmatales ), Aquidobacteriales (Acidobacteriales), and Ellin329, diagnostic method, characterized in that the increase and decrease of the content of the extracellular vesicles derived from one or more order bacteria (order) bacteria selected from the group consisting of.
13. The method of claim 9,

    Oxalobacteraceae, Rikennellaceae, Erysipelotrichaceae, Bacillaceae, Rhizobiaceae, and Fusobacteria in step (c). Fusobacteriaceae, Pseudomonadaceae, Comamonadaceae, Planococcaceae, Enterobacteriaceae, Lachnospiraceae, Corynebacteria Corynebacteriaceae, Deinococcaceae, Porphyromonadaceae, Neisseriaceae, Enterococcaceae, Lactobacillaceae, Tissi Tissierellaceae, Peptococcaceae, Flavobacteriaceae, Lactobacillaceae, Pseudomonadaceae, Luminococcaceae, Coma Mona City (Coma monadaceae, Turicibacteraceae, Clostridiaceae, Gordoniaaceae, Rikennellaceae, Prevotellaceae, Metanobacterial Of one or more family bacterial-derived extracellular vesicles selected from the group consisting of Methanobacteriaceae, Barnesiellaceae, Peptostreptococcaceae, and Koribacteraceae. A diagnostic method, characterized by comparing the increase and decrease in content.
14. The method of claim 9,

    Cupriavidus, Eubacterium, Blautia, Catenibacterium, Collinsella, Geobacillus, Roseview in step (c) Roseburia, Coprococcus, Facalcalibacterium, Pseudomonas, Corynebacterium, Mucispirillum, Deinococcus, Wife Anaerococcus, Dorea, Enterococcus, Adlercreutzia, Parabaceroides, Lactobacillus, rc4-4, Pepttoniphilus , Finegoldia, Rhizobium, Proteus, Pseudomonas, Lactobacillus, Turicibacter, Rumicoccus, Klebsiella, Klebsiella Facalicaliterium, Brebundi Nass (Brevundimonas), Clostridium, Yatgalicoccus, Megasphaera, Gordonia, Prevotella, Actinobacillus, Thermo-Aerobacte A diagnostic method, characterized by comparing the increase and decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of (Thermoanaerobacterium) and Metanobrevibacter.
15. The method of claim 9,

    The subject sample is a diagnostic method, characterized in that the blood or urine.
16. The method of claim 15,

    Wherein said blood is whole blood, serum, plasma, or blood monocytes.

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