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WO2018111028A1 - Procédé de diagnostic d'une maladie cardiaque par analyse de métagénome bactérien - Google Patents

Procédé de diagnostic d'une maladie cardiaque par analyse de métagénome bactérien Download PDF

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WO2018111028A1
WO2018111028A1 PCT/KR2017/014815 KR2017014815W WO2018111028A1 WO 2018111028 A1 WO2018111028 A1 WO 2018111028A1 KR 2017014815 W KR2017014815 W KR 2017014815W WO 2018111028 A1 WO2018111028 A1 WO 2018111028A1
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extracellular vesicles
bacteria
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김윤근
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MD Healthcare Inc
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MD Healthcare Inc
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Priority claimed from KR1020170172461A external-priority patent/KR101940423B1/ko
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Priority to EP17880997.6A priority Critical patent/EP3567118B1/fr
Priority to JP2019531913A priority patent/JP6830693B2/ja
Priority to US16/469,193 priority patent/US20200071748A1/en
Priority to CN201780077972.2A priority patent/CN110392741B/zh
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
    • C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria

Definitions

  • the present invention relates to a method for diagnosing heart disease through bacterial metagenome analysis, and more particularly, by analyzing bacterial metagenomic analysis using a sample derived from a subject, analyzing the increase or decrease in the content of specific bacterial-derived extracellular vesicles.
  • the present invention relates to a method for diagnosing a risk factor.
  • Heart disease is a disease occurring in the heart.
  • the main diseases include ischemic heart disease, coronary artery disease, angina pectoris, myocardial infarction, and arrhythmia.
  • Coronary artery disease (coronary artery disease) is a group of diseases including diseases such as angina (angina) and myocardial infarction, also known as ischemic heart disease (ischemic heart disease).
  • Myocardial infarction is a disease in which cardiac muscle infarction occurs due to blood clots due to thrombosis in the coronary arteries.
  • Risk factors for coronary artery disease include hypertension, smoking, diabetes, lack of exercise, obesity, hyperlipidemia, and excessive drinking. It has been reported that the disease is prevented when taking foods high in fruits and vegetables, and that the risk of developing it is increased when taking foods high in trans fat.
  • Dilated cardiomyopathy is a disease in which the heart expands and does not contract well, and is known to be the most common cause of non-coronary artery disease and cardiomyopathy. Toxins, metabolic disorders, and infectious agents have been suggested as causative agents, but there are no known causal factors.
  • Angina is a disease caused by the narrowing of blood vessels called coronary arteries that supply blood to the heart, which does not meet the required amount of blood. If the coronary vessels are narrowed, the blood supply will not be sufficient if necessary, causing symptoms of chest pain. If the angina is left, it can progress to acute myocardial infarction and cause sudden death.
  • Angina can be divided into stable angina, unstable angina and heteroangular angina. Of these three, stable angina and unstable angina are mostly caused by atherosclerotic plaques, while variant angina is called heterozygous angina, meaning that the cause of the disease is different.
  • heteroangular angina is a disease caused by convulsions due to convulsions but normal diameter. Angina is constricted by convulsions, and blood flow is reduced or blocked, causing chest pain. These symptoms usually occur at dawn the next day in the case of drinking or stress.
  • Atrial fibrillation is a symptom that causes a fast, irregular heart rate as the atria constantly scramble.
  • the atria run more than 300-400 times per minute, but most of the stimulation is blocked by AV nodes, and the stimulus to the ventricles is approximately 75-175 per minute.
  • the causes include underlying heart problems, such as coronary artery disease, myocardial infarction, hypertension and mitral valve, as well as pericarditis, pulmonary embolism, hyperthyroidism or hypothyroidism, sepsis, diabetes, hyperextension and pheochromocytoma. (pheochromocytoma).
  • 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.
  • 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 the metagenomic data obtained from samples taken from the environment. In 1998, metagenomics was collectively referred to as the total genome of all microbial communities in the natural environment in which microbes exist. First used by Jo bottlesman (Handelsman et al., 1998 Chem. Biol. 5, R245-249). Recently, a method based on 16s ribosomal RNA (16s rRNA) sequences has been possible to list the bacterial composition of the human microflora, and 16s ribosomal RNA is sequenced using the 454FLX titanium platform.
  • heart disease meta-genomic analysis, which is present in vesicles derived from bacteria in human derivatives such as blood or urine, identifies the causative factors of heart disease, especially myocardial infarction, cardiomyopathy, dysplastic angina and atrial fibrillation. There is no report on how to diagnose the disease.
  • the present inventors In order to diagnose heart diseases such as myocardial infarction, cardiomyopathy, heteroangular angina, and atrial fibrillation, the present inventors extracted a gene from bacterial vesicles using serum, a sample derived from a subject, and performed a metagenome analysis. Identified bacterial extracellular vesicles that can act as a causative agent of heart disease, the present invention was completed based on this.
  • an object of the present invention is to provide a method for providing information for diagnosing heart disease through metagenome analysis of bacterial extracellular vesicles.
  • the present invention provides a method for providing information for diagnosing heart disease, comprising the following steps:
  • the present invention provides a method for diagnosing heart disease, comprising the following steps:
  • the present invention also provides a method for predicting the risk of developing heart disease, comprising the following steps:
  • the subject sample is blood
  • step (c) Acidobacteria, Firmicutes, Crenarchaeota, Planctomycetes, Chloroflexi, Euryarchaeota, WS3, Nitrospirae, WPS-2, AD3, Verrucomicrobia, Acidobacteria, Gemmatimonadetes, Planctomycetes, Verrucomicrobia, Acidobacteria, Planctomycetes, Gemmalorofade, Ecobacteria Extracellular vesicles derived from one or more phylum bacteria selected from the group consisting of TM7, Chloroflexi, Acidobacteria, and Cyanobacteria,
  • Acidobacteriia DA052, Methanomicrobia, Thaumarchaeota, Clostridia, Coriobacteriia, Betaproteobacteria, Ktedonobacteria, Planctomycetia, Solibacteres, Erysipelotrichi, Verrucomicrobiae, TM7-3, Bacteroidia, Phycisphaerae, MCle, Nitrospira, Microspeci TM1, Deltaproteobacteria, Anaerolineae, Thermoplasmata, Chthonomonadetes, Acidobacteria-6, Verrucomicrobiae, Fusobacteriia, Acidobacteriia, Planctomycetia, DA052, Deltaproteobacteria, Acidimicrobiia, Verrucomicrobiae, Acidobacteriia, Fimbriimonadia, Erytediperotrichio, Fla.
  • Lactobacillales Acidobacteriales, Enterobacteriales, Xanthomonadales, Clostridiales, Coriobacteriales, Ellin6513, Burkholderiales, Erysipelotrichales, Solibacterales, Verrucomicrobiales, Rhodospirillales, Gemmatales, Thermogemmatisporales, Saprospirales, Acidimicrobiales, Pedosphaerales, Bifidobacteriales, Chthoniobacterales, Solirubrobacterales, Syntrophobacterales, Bacteroidales, Nitrospirales, Ktedonobacterales, WD2101, iii1-15, Ellin329, Thiotrichales, Myxococcales, Stramenopiles, Vibrionales, Pseudomonadales, Bacillales, Acidobacteriales, Sphingomonadales, Verrucomicrobiales, Turicibacterales, Acidimicrobiales, Ellin6513,
  • Koribacteraceae Comamonadaceae, Enterobacteriaceae, Streptococcaceae, Coriobacteriaceae, Lachnospiraceae, Prevotellaceae, Ruminococcaceae, Xanthomonadaceae, Propionibacteriaceae, Hyphomicrobiaceae, Verrucomicrobiaceae, Solibacteraceae, Acidobacteriaceae, Erysipelotrichaceae, Ktedonobacteraceae, Thermogemmatisporaceae, Moraxellaceae, Veillonellaceae, Burkholderiaceae, Rhodospirillaceae, Bifidobacteriaceae, Gemmataceae, Streptomycetaceae, Chitinophagaceae, Brucellaceae, Rhizobiaceae, Chthoniobacteraceae, Sinobacteraceae, Conexibacteraceae, Oxalobacteraceae, Isospha
  • the heart disease may be myocardial infarction, cardiomyopathy, heteroangular angina, or atrial fibrillation.
  • At least one phylum selected from the group consisting of Acidobacteria, Firmicutes, Crenarchaeota, Planctomycetes, Chloroflexi, Euryarchaeota, WS3, Nitrospirae, WPS-2, and AD3 in step (c) It may be to diagnose myocardial infarction by comparing the increase or decrease of the bacterial-derived extracellular vesicles.
  • Acidobacteriia DA052, Methanomicrobia, Thaumarchaeota, Clostridia, Coriobacteriia, Betaproteobacteria, Ktedonobacteria, Planctomycetia, Solibacteres, Erysipelotrichi, Verrucomicrobiae, TM7-3, Bacterphaeraspira, Phyci Of one or more class bacterial-derived extracellular vesicles selected from the group consisting of, Pedosphaerae, Thermoleophilia, Saprospirae, PRR-12, Spartobacteria, Acidimicrobiia, TM1, Deltaproteobacteria, Anaerolineae, Thermoplasmata, Chthonomonadetes, and Acidobacteria-6
  • the diagnosis may be to compare myocardial infarction.
  • Lactobacillales Acidobacteriales, Enterobacteriales, Xanthomonadales, Clostridiales, Coriobacteriales, Ellin6513, Burkholderiales, Erysipelotrichales, Solibacterales, Verrucomicrobiales, Rhodospirillales, Gemmatales, Thermo Saliverobiales, Content of one or more extracellular vesicles derived from one or more order bacteria derived from the group consisting of Chthoniobacterales, Solirubrobacterales, Syntrophobacterales, Bacteroidales, Nitrospirales, Ktedonobacterales, WD2101, iii1-15, Ellin329, Thiotrichales, Myxococcales, Stramenopiles, and Vibrionales
  • the diagnosis may be to compare myocardial infarction.
  • step (c) Koribacteraceae, Comamonadaceae, Enterobacteriaceae, Streptococcaceae, Coriobacteriaceae, Lachnospiraceae, Prevotellaceae, Ruminococcaceae, Xanthomonadaceae, Propionibacteriaceae, Hyphomicrobiaceae, Verrucomicrobiaceae, Solibacteraceaeaceae, Eotedceaceae , Veillonellaceae, Burkholderiaceae, Rhodospirillaceae, Bifidobacteriaceae, Gemmataceae, Streptomycetaceae, Chitinophagaceae, Brucellaceae, Rhizobiaceae, Chthoniobacteraceae, Sinobacteraceae, Conexibacteraceae, Oxalobacteraceae, Isosphaeraceae, Ellin515, Pisciaceae family selected from the family of species
  • the cardiomyopathy is compared in step (c) by comparing the increase or decrease of the content of one or more phylum bacteria-derived extracellular vesicles selected from the group consisting of Verrucomicrobia, Acidobacteria, Gemmatimonadetes, and Planctomycetes. It may be to diagnose.
  • the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of Verrucomicrobiae, Fusobacteriia, Acidobacteriia, Planctomycetia, DA052, Deltaproteobacteria, and Acidimicrobiia in step (c) may be to compare the diagnosis of cardiomyopathy.
  • Pseudomonadales, Bacillales, Acidobacteriales, Sphingomonadales, Verrucomicrobiales, Turicibacterales, Acidimicrobiales, Ellin6513, Xanthomonadales, and Gemmatales derived from one or more species (order) bacteria derived from It may be to diagnose cardiomyopathy by comparing the increase and decrease of the content of extracellular vesicles.
  • step (c) Pseudomonadaceae, Clostridiaceae, Comamonadaceae, Oxalobacteraceae, Moraxellaceae, Verrucomicrobiaceae, Koribacteraceae, Sphingomonadaceae, Turicibacteraceae, Xanthomonadaceae, Gemmataceae, and Staphylococcaceae selected from the group consisting of It may be to diagnose cardiomyopathy by comparing the increase or decrease of the bacterial extracellular vesicles.
  • Pseudomonas Clostridium, Cupriavidus, Acinetobacter, Citrobacter, Sphingomonas, Candidatus Koribacter, Staphylococcus, Thermoanaerobacterium, Micrococcus, Akkermansia, Neisseria, Enhydrobacter, Actinomyces, Turicibacter, P. It may be to diagnose cardiomyopathy by comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Delftia, and Stenotrophomonas.
  • comparing the increase or decrease of the content of one or more phylum bacteria-derived extracellular vesicles selected from the group consisting of Verrucomicrobia, Acidobacteria, Planctomycetes, Gemmatimonadetes, Chloroflexi, and Euryarchaeota in the step (c) It may be to diagnose dysplastic angina.
  • comparing the increase or decrease of the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of Verrucomicrobiae, Acidobacteriia, Fimbriimonadia, Erysipelotrichi, Ktedonobacteria, and Deltaproteobacteria in step (c) It may be to diagnose dysplastic angina.
  • step (c) in the step (c), Pseudomonadales, Erysipelotrichales, Fimbriimonadales, Acidobacteriales, Verrucomicrobiales, Xanthomonadales, Myxococcales, Deinococcales, and Rhodospirillales selected from the group consisting of one or more extracellular bacteria derived cells Compared with the increase and decrease of the contents of the vesicles may be to diagnose dysplastic angina.
  • step (c) Koribacteraceae, Oxalobacteraceae, Comamonadaceae, Moraxellaceae, Pseudomonadaceae, Hyphomicrobiaceae, Erysipelotrichaceae, Deinococcaceae, Clostridiaceae, Verrucomicrobiaceae, Sinobacteraceae, Rhodospirillaceae, Methylobacteriaaceae, Fumberoaceae, Fumberoaceae It may be to diagnose heteroangular angina by comparing the increase or decrease in the content of one or more family bacteria-derived extracellular vesicles selected from the group consisting of Planococcaceae.
  • By comparing the increase and decrease of the content of one or more genus bacteria-derived extracellular vesicles may be to diagnose heteroangular angina.
  • step (c) by comparing the increase or decrease in the content of one or more phylum bacteria-derived extracellular vesicles selected from the group consisting of Proteobacteria, TM7, Chloroflexi, Acidobacteria, and Cyanobacteria It may be to diagnose fibrillation.
  • step (c) of Clostridia, Bacteroidia, Actinobacteria, Flavobacteriia, Erysipelotrichi, TM7-3 Chloroplast of one or more class bacteria-derived extracellular vesicles selected from the group consisting of It may be to diagnose atrial fibrillation by comparing the increase and decrease of the content.
  • step (c) Pseudomonadales, Clostridiales, Bacteroidales, Enterobacteriales, Xanthomonadales, Bifidobacteriales, Pasteurellales, Flavobacteriales, Actinomycetales, Rhodobacterales, Coriobacteriales, Erysipelotrichales, and Streptophyta selected from the group consisting of at least one species It may be to diagnose atrial fibrillation by comparing the increase and decrease of the content of the order bacteria-derived extracellular vesicles.
  • Lachnospiraceae, Bacillaceae, Streptococcaceae, Bacteroidaceae, Moraxellaceae, Ruminococcaceae, Weeksellaceae, Bifidobacteriaceae, Clostridiaceae, Desulfovibrionaceae, Veillonellaceae, Coriobacteriaceae, Flavobacteriaceae, Rikenhoaceae bacteraceae in step (c) Atrial fibrillation may be diagnosed by comparing the increase or decrease of the content of one or more family bacteria-derived extracellular vesicles selected from the group consisting of Pseudomonadaceae, Gordoniaceae, and Enterococcaceae.
  • step (c) Acinetobacter, Stenotrophomonas, Chryseobacterium, Enterococcus, Pseudomonas, Delftia, Alcanivorax, Psychrobacter, Streptococcus, Ochrobactrum, Bifidobacterium, Coprococcus, Bacteroters, Agrobacterium bacterium, Agrobacterium bacterium Atrial by comparing the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Geobacillus, Clostridium, Bacillus, Haemophilus, Veillonella, Actinomyces, Paracoccus, Kocuria, Halomonas, Micrococcus, Ruminococcus, and Porphyromonas It may be to diagnose fibrillation.
  • the blood may be whole blood, serum, or plasma.
  • Diagnosing the causative agent of heart disease through metagenomic analysis of bacteria-derived extracellular vesicles using a human-derived sample diagnoses and predicts risk groups of heart disease early and delays the onset time through appropriate management. It can be prevented and diagnosed early after the onset, which can lower the incidence of heart disease and increase the therapeutic effect.
  • metagenome analysis in patients diagnosed with heart disease may prevent exposure to the causative agent to improve the course of heart disease or prevent relapse.
  • Figure 1 is for evaluating the distribution of bacteria-derived extracellular vesicles in the body
  • Figure 1a after the administration of oral intestinal bacteria (Bacteria) and bacteria-derived vesicles (EV) in the mouth hourly (0, 5min, 3h, 6h, and 12h) is a photograph taken of their distribution
  • Figure 1b is 12 hours after the oral administration of intestinal bacteria (Bacteria) and bacteria-derived extracellular vesicles (EV) to the blood and various organs (heart, Lung, liver, kidney, spleen, adipose tissue, and muscles), and the photographs of the distribution of the bacterial and extracellular vesicles.
  • Figure 2 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level after meta-genomic analysis of vesicle-derived vesicles in myocardial infarction patients and normal blood.
  • EVs bacteria-derived vesicles
  • Figure 3 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level after meta-genomic analysis of bacterial vesicles in myocardial infarction patients and normal blood.
  • EVs bacteria-derived vesicles
  • Figure 4 is a result showing the distribution of bacteria-derived vesicles (EVs) of significant diagnostic performance at the order level after the meta-genomic analysis of bacterial vesicles in myocardial infarction patients and normal blood.
  • EVs bacteria-derived vesicles
  • Figure 5 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level after metagenome analysis of bacteria-derived vesicles in myocardial infarction patients and normal blood.
  • EVs bacteria-derived vesicles
  • FIG. 6 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance after genome analysis of bacterial vesicles in myocardial infarction patients and normal blood.
  • EVs bacterial vesicles
  • EVs bacteria-derived vesicles
  • FIG. 8 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the class level after metagenome analysis of bacterial vesicles in cardiomyopathy patients and normal blood.
  • FIG. 9 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order level after analyzing the metagenome of bacteria-derived vesicles in patients with cardiomyopathy and normal blood.
  • EVs bacteria-derived vesicles
  • Figure 10 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the family level after meta-genomic analysis of bacterial vesicles in cardiomyopathy patients and normal blood.
  • EVs bacterial vesicles
  • FIG. 11 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the genus level after metagenome analysis of bacterial vesicles in cardiomyopathy patients and normal blood.
  • EVs bacterial vesicles
  • EVs bacterial vesicles
  • Figure 13 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the class level after metagenome analysis of bacterial vesicles in patients with angina and normal blood.
  • EVs bacterial vesicles
  • FIG. 14 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the order level after metagenome analysis of bacterial vesicles in patients with angina and normal blood.
  • EVs bacterial vesicles
  • Figure 15 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level after metagenome analysis of bacteria-derived vesicles in patients with angina and normal blood.
  • EVs bacteria-derived vesicles
  • FIG. 16 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after metagenome analysis of bacteria-derived vesicles in patients with angina and normal blood.
  • EVs bacteria-derived vesicles
  • FIG. 17 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the phylum level after a metagenomic analysis of bacterial vesicles in atrial fibrillation patients and normal blood.
  • EVs bacterial vesicles
  • FIG. 18 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the class level after metagenome analysis of bacterial vesicles in atrial fibrillation patients and normal blood.
  • EVs bacterial vesicles
  • FIG. 20 shows the distribution of bacterial vesicles (EVs) with significant diagnostic performance at the family level after metagenome analysis of bacterial vesicles in atrial fibrillation patients and normal blood.
  • EVs bacterial vesicles
  • EVs bacterial vesicles
  • the present invention relates to a method for diagnosing heart disease through bacterial metagenomic analysis, and the present inventors extracted a gene from bacterial extracellular vesicles using a sample derived from a subject, and performed a metagenome analysis on the cardiac disease. Bacterial-derived extracellular vesicles that could act as causative factors were identified.
  • the present invention comprises the steps of (a) extracting DNA from the extracellular vesicles isolated from the subject sample;
  • (C) provides an information providing method for diagnosing heart disease comprising the step of comparing the increase and decrease of the content of the normal-derived sample and bacterial-derived extracellular vesicles through the sequencing of the PCR product.
  • the term "prediction of the risk of developing heart disease” refers to determining whether a heart disease is likely to develop, whether the heart disease is relatively high, or whether the disease has already occurred. it means.
  • 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 heart disease for any particular patient.
  • the methods of the present invention can be used clinically to determine treatment by early diagnosis of heart disease and selecting the most appropriate treatment regimen.
  • the heart disease may be myocardial infarction, cardiomyopathy, heteroangular angina, or atrial fibrillation.
  • metagenome is also referred to as a military genome, refers to the total of the genome including all viruses, bacteria, fungi, etc. in an isolated area, such as soil, animal intestine, is not mainly cultured It is used as a concept of genome to explain the identification of many microorganisms at once using sequencer to analyze microorganisms.
  • 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.
  • 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.
  • metagenome analysis was preferably performed using bacterial-derived extracellular vesicles isolated from blood.
  • the subject sample may preferably be whole blood, serum, or plasma, but is not limited thereto.
  • the metagenome analysis of the bacterial-derived extracellular vesicles was performed, and analyzed at the phylum, class, order, family, and genus levels, respectively. By identifying the bacterial vesicles that can actually cause the development of heart disease.
  • the results of analysis of the bacteria-derived metagenomics present in myocardial infarction patients and normal blood at a strong level Acidobacteriia, DA052, Methanomicrobia, Thaumarchaeota, Clostridia, Coriobacteriia, Betaproteobacteria, Ktedonobacteria, Planctomycetia, Solibacteres, Erysipelotrichi, Verrucomicrobiae, TM7-3, Bacteroidia, Phycisphaerae, MCG, Nitrospira, Pedosphaerae, Thermoleophilia, Saprospirae, PRR-12, Spartobacteria, Acidimicrobiia, TM1, Deltaproteobacteria, Anaerolineae, Thermoplasm-6, Chloroacidata, Chthonomonate Bacterial-derived vesicles were significantly different between myocardial infarction patients and
  • the results of analysis of the meta-genomics derived from bacteria in the myocardial infarction patients and normal blood at the neck level Lactobacillales, Acidobacteriales, Enterobacteriales, Xanthomonadales, Clostridiales, Coriobacteriales, Ellin6513, Burkholderiales, Erysipelotrichales, Solibacterales, Verrucomicrobiales, Rhodospirillales, Gemmatales, Thermogemmatisporales, Saprospirales, Acidimicrobiales, Pedosphaerales, Bifidobacteriales, Chthoniobacterales, Solirubrobacterales, Syntrophobacterales, Bacteroidales, Nitrospirales, Ktedonobacterales, Myoclrichales 3 Bacterial-derived vesicles were significantly different between myocardial infarction patients and normal individuals (see Example 4).
  • the results of the analysis of bacteria-derived metagenomics present in myocardial infarction patients and normal blood at the excessive level Koribacteraceae, Comamonadaceae, Enterobacteriaceae, Streptococcaceae, Coriobacteriaceae, Lachnospiraceae, Prevotellaceae, Ruminococcaceae, Xanthomonadaceae, Propionibacteriaceae, Hyphomicrobiaceae, Verrucomicrobiaceae, Solibacteraceae, Acidobacteriaceae, Erysipelotrichaceae, Ktedonobacteraceae, Thermogemmatisporaceae, Moraxellaceae, Veillonellaceae, Burkholderiaceae, Rhodospirillaceae, Bifidobacteriaceae, Gemmataceae, Streptomycetaceae, Chitinophagaceae, Brucellaceae, Rhizo
  • the bacterial-derived metagenomics present in cardiomyopathy patients and normal blood at the gate level the results of Verrucomicrobia, Acidobacteria, Gemmatimonadetes, and Planctomycetes phylum bacteria-derived extracellular vesicles
  • the contents of cardiomyopathy patients were significantly different from those of normal patients (see Example 5).
  • Bacterial-derived vesicles were significantly different between cardiomyopathy and normal subjects (see Example 5).
  • the bacterial-derived metagenomics present in cardiomyopathy patients and normal blood at the neck level Pseudomonadales, Bacillales, Acidobacteriales, Sphingomonadales, Verrucomicrobiales, Turicibacterales, Acidimicrobiales, Ellin6513, Xanthomonadales, And Gemmatales order bacteria-derived vesicles were significantly different between cardiomyopathy and normal (see Example 5).
  • the present invention as a result of analyzing the bacteria-derived metagenomics present in the cardiomyopathy patients and normal blood at the excessive level, Pseudomonadaceae, Clostridiaceae, Comamonadaceae, Oxalobacteraceae, Moraxellaceae, Verrucomicrobiaceae, Koribacteraceae, Sphingomonadaceae, Turicibacteraceae, Bacterial-derived vesicles from the family Xanthomonadaceae, Gemmataceae and Staphylococcaceae were significantly different between cardiomyopathy and normal (see Example 5).
  • the present invention as a result of analyzing the bacteria-derived metagenomics present in the cardiomyopathy and normal blood at the genus level, Pseudomonas, Clostridium, Cupriavidus, Acinetobacter, Citrobacter, Sphingomonas, Candidatus Koribacter, Staphylococcus, Thermoanaerobacterium There was a significant difference between cardiomyopathy and normal individuals in the vesicles of Micrococcus, Akkermansia, Neisseria, Enhydrobacter, Actinomyces, Turicibacter, Phascolarctobacterium, Lactococcus, Delftia, and Stenotrophomonas genus (see Example 5).
  • bacteria-derived metagenomes present in patients with heteroangular angina and normal blood were analyzed at the gate level, resulting from Verrucomicrobia, Acidobacteria, Planctomycetes, Gemmatimonadetes, Chloroflexi, and Euryarchaeota phylum bacteria.
  • the content of extracellular vesicles was significantly different from those of patients with heteroangular angina (see Example 6).
  • the meta-genomics derived from bacteria in patients with angina and normal blood at the neck level Pseudomonadales, Erysipelotrichales, Fimbriimonadales, Acidobacteriales, Verrucomicrobiales, Xanthomonadales, Myxococcales, Deinococcales, and Rhodospirilla
  • the order bacterial vesicles of the order bacterium had a significant difference between patients with angina and normal subjects (see Example 6).
  • the results of analysis of the genome-derived metagenomics present in patients with heteroangular angina and normal blood at the genus level Citrobacter, Acinetobacter, Cupriavidus, Clostridium, Catenibacterium, Pseudomonas, Lactococcus, Stenotrophomonas, Akkermansia, Vesicles derived from Bacillus, Delftia, Agrobacterium, Deinococcus, Fusobacterium, and Adlercreutzia genus bacteria showed significant differences between patients with angina and normal subjects (see Example 6).
  • the bacteria-derived metagenomics present in patients with atrial fibrillation and normal blood were analyzed at the gate level.
  • the contents of the vesicles were significantly different from those of atrial fibrillation patients compared to normal patients (see Example 7).
  • the analysis of the bacteria-derived metagenome present in atrial fibrillation patients and normal blood at the river level Clostridia, Bacteroidia, Actinobacteria, Flavobacteriia, Erysipelotrichi, TM7-3, and Chloroplast steel ( class) Bacterial-derived vesicles were significantly different between atrial fibrillation patients and normal subjects (see Example 7).
  • the bacterial-derived metagenomics present in atrial fibrillation patients and normal blood at the neck level Pseudomonadales, Clostridiales, Bacteroidales, Enterobacteriales, Xanthomonadales, Bifidobacteriales, Pasteurellales, Flavobacteriales, Actinomycetales, Rhodobacterales, Coriobacteriales, Erysipelotrichales, and Streptophyta order bacterial vesicles were significantly different between atrial fibrillation patients and normal subjects (see Example 7).
  • the results of analysis of bacteria-derived metagenomics present in atrial fibrillation patients and normal blood at the genus level Acinetobacter, Stenotrophomonas, Chryseobacterium, Enterococcus, Pseudomonas, Delftia, Alcanivorax, Psychrobacter, Streptococcus, Ochrobactrum, Bifidobacterium, Coprococcus, Bacteroides, Faecalibacterium, Enhydrobacter, Agrobacterium, Citrobacter, Prevotella, Geobacillus, Clostridium, Bacillus, Haemophilus, Veillonella, Actinomyces, Paracoccus, Kocuria, Halomonas, Rucobacco, Genus Micrococcus There was a significant difference between atrial fibrillation patients and normal subjects (see Example 7).
  • meta-genome analysis was performed on bacterial extracellular vesicles isolated from blood, and the contents were significantly higher in patients with myocardial infarction, cardiomyopathy, heteroangular angina, and atrial fibrillation compared to normal people.
  • Bacterial-derived vesicles were changed, and meta-genomic analysis confirmed that heart disease could be diagnosed by analyzing the increase and decrease of the content of bacterial-derived vesicles at each level.
  • the blood was first centrifuged (3,500 x g, 10 min, 4 ° C.) in a 10 ml tube to settle the suspension and only the supernatant was transferred to a new 10 ml tube. After removing bacteria and foreign substances using a 0.22 ⁇ m filter, it was transferred to centripreigugal filters (50 kD) and centrifuged at 1500 x g and 4 ° C for 15 minutes to discard materials smaller than 50 kD and concentrated to 10 ml.
  • 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.
  • SFF Standard Flowgram Format
  • the clustering was performed according to the sequence similarity using UCLUST and USEARCH for the Operational Taxonomy Unit (OTU) analysis. It was. 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 RNA sequence database (108,453 sequences) (QIIME).
  • OTU Operational Taxonomy Unit
  • Example 3 vesicles were isolated from 57 patients with ST elevation myocardial infarction (STMI) and 163 normal blood of age and sex, and then metagenome sequencing was performed.
  • STMI ST elevation myocardial infarction
  • 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, and then the logistic regression analysis method is used for AUC (area). under curve), accuracy, sensitivity, and specificity.
  • biomarkers were selected from Acidobacteria, Firmicutes, Crenarchaeota, Planctomycetes, Chloroflexi, Euryarchaeota, WS3, Nitrospirae, WPS-2, and AD3 portal bacteria When developed, diagnostic performance for myocardial infarction was significant (see Table 2 and Figure 2).
  • Acidobacteriia DA052, Methanomicrobia, Thaumarchaeota, Clostridia, Coriobacteriia, Betaproteobacteria, Ktedonobacteria, Planctomycetia, Solibacteres, Erysipelotrichi, Verrucomicrobiae, TM7-3, BactGeraci Myocardial infarction when developing a diagnostic model with one or more biomarkers selected from Nitrospira, Pedosphaerae, Thermoleophilia, Saprospirae, PRR-12, Spartobacteria, Acidimicrobiia, TM1, Deltaproteobacteria, Anaerolineae, Thermoplasmata, Chthonomonadetes, and Acidobacteria-6 strong bacteria Diagnostic performance was significant (see Table 3 and FIG. 3).
  • Cardiomyopathy was diagnosed as one or more biomarkers for the development of one or more biomarkers for the selection of one or more biomarkers selected from the Bifidobacteriales, Chthoniobacterales, Solirubrobacterales, Syntrophobacterales, Bacteroidales, Nitrospirales, Ktedonobacterales, WD2101, iii1-15, Ellin329, Thiotrichales, Myxococcales, Stramenopiles, and Vibrionales neck bacteria. Diagnostic performance was significant (see Table 4 and FIG. 4).
  • metagenome sequencing was performed after separating vesicles from blood of 72 patients with dilated cardiomyopathy (DCMP) and 163 normal blood of age and gender.
  • DCMP dilated cardiomyopathy
  • 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, and then the logistic regression analysis method is used for AUC (area). under curve), accuracy, sensitivity, and specificity.
  • cardiomyopathy was developed when one or more biomarkers were selected from Verrucomicrobiae, Fusobacteriia, Acidobacteriia, Planctomycetia, DA052, Deltaproteobacteria, and Acidimicrobiia river bacteria. Diagnostic performance was significant (see Table 8 and FIG. 8).
  • Biomarkers selected from Pseudomonadaceae, Clostridiaceae, Comamonadaceae, Oxalobacteraceae, Moraxellaceae, Verrucomicrobiaceae, Koribacteraceae, Sphingomonadaceae, Turicibacteraceae, Xanthomonadaceae, Gemmataceae, and Staphylococcaceae
  • biomarkers selected from Pseudomonadaceae, Clostridiaceae, Comamonadaceae, Oxalobacteraceae, Moraxellaceae, Verrucomicrobiaceae, Koribacteraceae, Sphingomonadaceae, Turicibacteraceae, Xanthomonadaceae, Gemmataceae, and Staphylococcaceae
  • the diagnostic performance for cardiomyopathy was significant (see Table 10 and FIG. 10).
  • Example 3 vesicles were isolated from 80 patients with variant angina and 80 normal humans whose age and sex matched, followed by metagenome sequencing.
  • 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, and then the logistic regression analysis method is used for AUC (area). under curve), accuracy, sensitivity, and specificity.
  • vesicle-derived vesicles in the blood at the class level revealed that diagnosing for angina with development of one or more biomarkers selected from Verrucomicrobiae, Acidobacteriia, Fimbriimonadia, Erysipelotrichi, Ktedonobacteria, and Deltaproteobacteria river bacteria. Performance was significant (see Table 13 and FIG. 13).
  • Bacterial-derived vesicles in the blood were analyzed at the genus level and Citrobacter, Acinetobacter, Cupriavidus, Clostridium, Catenibacterium, Pseudomonas, Lactococcus, Stenotrophomonas, Akkermansia, Bacillus, Delftia, Agrobacterium, Deinococcus, Fusobacteruta,
  • Citrobacter Acinetobacter
  • Cupriavidus Clostridium
  • Catenibacterium Pseudomonas
  • Lactococcus Stenotrophomonas
  • Akkermansia Bacillus
  • Delftia Agrobacterium
  • Deinococcus Fusobacteruta
  • Example 3 By the method of Example 3, vesicles were isolated from blood of 34 patients with atrial fibrillation and 62 healthy subjects whose age and gender were matched, followed by metagenome sequencing.
  • 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, and then the logistic regression analysis method is used for AUC (area). under curve), accuracy, sensitivity, and specificity.
  • Atrial was developed when one or more biomarkers were selected from Clostridia, Bacteroidia, Actinobacteria, Flavobacteriia, Erysipelotrichi, TM7-3, and Chloroplast river bacteria. Diagnostic performance for fibrillation was significant (see Table 18 and FIG. 18).
  • Diagnosing the causative agent of heart disease through metagenomic analysis of bacteria-derived extracellular vesicles using a human-derived sample diagnoses and predicts risk groups of heart disease early and delays the onset time through appropriate management. It can be prevented and diagnosed early after the onset, which can lower the incidence of heart disease and increase the therapeutic effect.
  • metagenome analysis in patients diagnosed with heart disease may prevent exposure to the causative agent to improve the course of heart disease or prevent relapse.

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Abstract

La présente invention concerne un procédé de diagnostic d'une maladie cardiaque par analyse de métagénome bactérien. Plus particulièrement, la présente invention concerne un procédé de prédiction du facteur causal et de l'apparition d'une maladie cardiaque, de diagnostic précoce d'une maladie cardiaque et de prodiction d'un pronostic par analyse de l'augmentation ou de la diminution du contenu d'une vésicule extracellulaire dérivée de bactéries spécifiques par réalisation d'une analyse de métagénome bactérien à l'aide d'un échantillon dérivé d'un spécimen. Par l'analyse du métagénome d'une vésicule extracellulaire dérivée de bactéries à l'aide d'un échantillon dérivé du corps humain selon la présente invention, le risque d'apparition d'une maladie cardiaque est prédit à l'avance et ainsi un groupe de risque pour une maladie cardiaque est diagnostiqué et prédit précocement. Par conséquent, grâce à une gestion appropriée, le moment d'apparition d'une maladie peut être retardé ou l'apparition de la maladie peut être empêchée et un diagnostic précoce peut être effectué même après l'apparition d'une maladie. Par conséquent, le taux d'apparition d'une maladie cardiaque peut être réduit et l'effet de traitement peut être amélioré. De plus, étant donné que la soumission à des facteurs responsables est évitée par l'analyse de métagénome d'un patient chez qui une maladie cardiaque a été diagnostiquée, le pronostic de maladie cardiaque peut être amélioré ou la réapparition d'une maladie cardiaque peut être empêchée.
PCT/KR2017/014815 2016-12-16 2017-12-15 Procédé de diagnostic d'une maladie cardiaque par analyse de métagénome bactérien Ceased WO2018111028A1 (fr)

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EP17880997.6A EP3567118B1 (fr) 2016-12-16 2017-12-15 Procédé de diagnostic d'une maladie cardiaque par analyse de métagénome bactérien
JP2019531913A JP6830693B2 (ja) 2016-12-16 2017-12-15 細菌メタゲノム解析による心臓疾患診断方法
US16/469,193 US20200071748A1 (en) 2016-12-16 2017-12-15 Method of diagnosing heart disease through bacterial metagenome analysis
CN201780077972.2A CN110392741B (zh) 2016-12-16 2017-12-15 通过细菌宏基因组分析来诊断心脏病的方法

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CN117106669A (zh) * 2023-09-28 2023-11-24 浙江中医药大学 具有改善酒精性心肌病的微嗜酸寡养单胞菌及其应用

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