WO2023080663A1 - Metabolite marker for diagnosis of mycobacterium avium complex infectious disease or for prediction of severity - Google Patents

Abstract

The present invention relates to a composition for accurately diagnosing infection with nontuberculous mycobacteria and for predicting severity of infected diseases by measuring a specific metabolite in blood. In the present invention, the metabolites, as biomarkers for rapid, accurate, and highly reliable measurement, are applied to nontuberculous mycobacteria (NTM), especially, Mycobacterium avium complex (MAC) for which objective and highly reliable diagnostic markers are insufficient, and thus can be advantageously used for more effective diagnosis of nontuberculous mycobacterial infection diseases. In the present invention, the metabolites, as markers for predicting the progression and severity of diseases with high accuracy, are applied to nontuberculous mycobacteria (NTM), especially, Mycobacterium avium complex (MAC) for which objective and highly reliable diagnostic markers are not present at all with respect to the progression of diseases, whereby the severity of patients infected with nontuberculous mycobacteria is determined to establish a patient-specific therapeutic strategy at an early stage and thus the present invention can be advantageously used to significantly improve the survival rate of patients.

Description

Metabolic markers for diagnosis or severity prediction of Mycobacterium avium complex infectious diseases

The present invention relates to metabolomic markers for diagnosing Mycobacterium avium complex infectious diseases or predicting therapeutic response.

Mycobacterium includes not only species that cause serious diseases to humans and animals, such as tuberculosis, Mycobacterium bovis, and Mycobacterium leprae, but also species that are referred to as opportunistic infections, and About 72 species are known to date, including saprophytic species that can be seen in the natural environment, and among them, 25 species are known to be related to human diseases. These Mycobacterium genus are not easily dyed with commonly used staining solutions, but once dyed, they are also called acid-fast bacteria because they are not easily discolored even when treated with alcohol or hydrochloric acid.

Nontuberculous mycobacteria (NTM) means mycobacteria other than Mycobacterium tuberculosis complex and Mycobacterium leprae. On the other hand, among non-tuberculous mycobacterium strains belonging to the Mycobacterium avium complex (MAC), about 180 or more strains that commonly cause lung diseases in humans have been officially identified. MAC mainly includes M. avium ( M. avium ) and M. intracellulare ( M. intracellulare ), and Mycobacterium abscessus ( MAB ) is mainly M. abscessus subspecies Absesu. ( M. abscessus subspecies abscessus ) and M. abscessus subspecies massiliense ( M. abscessus subspecies massiliense ). Recently, reports of lung infections caused by non-tuberculous mycobacteria are increasing worldwide, but there is a lack of biomarkers for distinguishing patients with non-tuberculous mycobacteria lung infections from healthy populations, or studies on the pathophysiology of the disease.

The present inventors studied patients infected with Nontuberculous mycobacteria (NTM), in particular, Mycobacterium avium complex (MAC), which causes lung diseases very common in humans, for which it is difficult to develop objective and reliable diagnostic markers. Efforts were made to discover diagnostic markers for distinguishing from healthy subjects and diagnostic markers for determining the severity of infected patients. As a result, 24 types of lipid metabolites were found as diagnostic markers that can clearly distinguish non-tuberculosis mycobacterium-infected patients from non-infected subjects, and as diagnostic markers that can reflect the severity of non-tuberculosis mycobacterial infections with high reproducibility and reliability. , 25 species of polar and lipid metabolites were discovered.

Accordingly, an object of the present invention is to provide a composition for diagnosis of non-tuberculous mycobacterial infectious diseases and a diagnosis method using the same.

Another object of the present invention is to provide a composition for predicting the severity of non-tuberculous mycobacterial infection disease.

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

Hereinafter, various embodiments described herein are described with reference to the drawings. In the following description, numerous specific details are set forth, such as specific forms, compositions and processes, etc., in order to provide a thorough understanding of the present invention. However, certain embodiments may be practiced without one or more of these specific details, or with other known methods and forms. In other instances, well known processes and manufacturing techniques have not been described in specific detail in order not to unnecessarily obscure the present invention. Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, form, composition or characteristic described in connection with the embodiment is included in one or more embodiments of the invention. Thus, the appearances of "in one embodiment" or "an embodiment" in various places throughout this specification do not necessarily refer to the same embodiment of the invention. Additionally, particular features, forms, compositions, or properties may be combined in one or more embodiments in any suitable way.

Unless there is a specific definition within the present invention, all scientific and technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

According to one aspect of the present invention, the present invention provides lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin ( Provided is a composition for diagnosing infectious diseases of non-tuberculous mycobacteria comprising, as an active ingredient, an agent for measuring one or more metabolites selected from the group consisting of sphingomyeline (SM) and triacylglycerol (TAG).

The inventors of the present invention are infected with Nontuberculous mycobacteria (NTM), in particular, Mycobacterium avium complex (MAC), which causes lung diseases very common in humans, for which it is difficult to develop objective and reliable diagnostic markers. Efforts were made to discover diagnostic markers for distinguishing patients from healthy subjects. As a result, 24 types of lipid metabolites were discovered as diagnostic markers that can clearly distinguish non-tuberculosis mycobacterium-infected patients from non-infected subjects.

In the present specification, the term "non-tuberculosis mycobacteria" refers to acid-fast bacteria other than Mycobacterium tuberculosis, and specifically includes all mycobacteria that do not cause tuberculosis and leprosy. Anti-acid bacteria, unlike general bacteria, mean strains that do not dissolve and have the ability to withstand the addition of acid during the dyeing process. Mycobacterium tuberculosis is representative of these mycobacteria, and mycobacteria other than Mycobacterium tuberculosis are called nontuberculous mycobacteria (NTM), and new nontuberculous mycobacteria are discovered almost every year.

As used herein, the term “diagnosis” refers to determining the susceptibility of a subject to a specific disease or disorder, determining whether a subject currently has a specific disease or disorder (e.g., non-tuberculous mycobacteria) infection), determining the prognosis of a subject suffering from a particular disease or condition, or therametrics (e.g., monitoring the condition of a subject to provide information about the efficacy of a treatment). . Specifically, for purposes of the present invention, the term diagnosis herein means determining whether a subject currently has a particular disease or condition.

Underout the term “Diagnostic composition” herein, the Lysophosphatidylcholine, Lysophosphatidylcholine (Lysophosphatidylcholine), Lysophosphatidylethanolamin to determine whether or not to develop the likelihood of a non -nucleic acid disease of the subject. e), phosphatidylcholine, force party deal It means an integrated mixture or device that includes a means for measuring the concentration of metabolites of ethanolamine (Phosphatidylethanolamine), sphingomyeline, and triacylglycerol, and is therefore referred to as a "diagnostic kit". may be expressed. Since the diagnostic composition of the present invention includes a means for measuring the metabolite discovered in the present invention, the term “diagnostic composition” may also be expressed as a “quantitative device” for metabolites.

As used herein, the term "metabolite", also referred to as a metabolite or metabolite, is an intermediate or product of metabolism. These metabolites are fuel, structure, signal transduction, stimulatory and inhibitory effects on enzymes, their own catalytic activity (usually as cofactors for enzymes), defense, and interactions with other organisms (e.g., pigments, aromatic compounds). , pheromones). Primary metabolites are directly involved in normal growth, development and reproduction. Secondary metabolites are not directly involved in these processes, but usually have important ecological functions.

According to the present invention, the metabolite refers to a metabolite obtained from a sample of biological origin, that is, a biological sample, and the biological sample refers to a biological fluid, tissue or cell.

According to the present invention, the metabolite may be a metabolite obtained from a liquid sample derived from blood, specifically serum.

According to a specific embodiment of the present invention, the lysophosphatidylcholine is at least one lysophosphatidylcholine selected from the group consisting of LPC (18:0) and LPC (20:5).

According to a specific embodiment of the present invention, the lysophosphatidylethanolamine is at least one lysophosphatidylethanolamine selected from the group consisting of LPE (18:2) and LPE (20:4).

According to a specific embodiment of the present invention, the phosphatidylcholine is PC 36:5 (20:5/16:0), PC 28:0 (14:0/14:0), PC 30:0 (14:0/16 :0), PC 32:2 (18:2/14:0), PC 33:2 (18:2/15:0), PC 34:2 (18:2/16:0), PC 34:3 (16:1/18:2), PC 36:4(20:4/16:0), PC O--36:3(O--18:1/18:2), PC O--36: 5 (O--16:1/20:4) and PC O-36:5 (O--16:1/20:4).

According to a specific embodiment of the present invention, the phosphatidylethanolamine is PE-NME 34:1 (18:1/16:0).

According to a specific embodiment of the present invention, the sphingomyelin is SM d34: 1 (d18: 1/16: 0), SM d42: 1 (d18: 1/24: 0) and SM d42: 2 (d18: 1/24: 1) is at least one sphingomyelin selected from the group consisting of.

According to a specific embodiment of the present invention, the triacylglycerol is TAG 54:5 (18:1/18:1/18:3), TAG 55:7 (21:5/18:2/16:0), TAG 58:11 (22:6/20:5/16:0), TAG 60:11 (22:6/20:4/18:1) and TAG 60:12 (22:6/22:6/16 :0) is at least one triacylglycerol selected from the group consisting of.

According to a specific embodiment of the present invention, when the concentration of the lysophosphatidylcholine, phosphatidylcholine, sphingomyelin or triacylglycerol is increased compared to the normal control group, infection by non-tuberculous mycobacteria is predicted.

According to the present invention, the "control group" means a normal subject not infected by non-tuberculous mycobacteria.

The term "increase in concentration" used while referring to "diagnostic composition" in the composition of the present invention refers to a case in which the concentration of a major body in the serum of an infected patient is significantly higher than that of a normal person who is not infected with Mycobacterium. Specifically, means an increase of about 10% or more, an increase of about 20% or more, an increase of about 30% or more, an increase of about 40% or more, or an increase of about 50% or more, more specifically, an increase of about 40% or more compared to the normal person and the control group It means a case, and does not exclude the scope outside of this.

According to a specific embodiment of the present invention, when the concentration of lysophosphatidylethanolamine, phosphatidylcholine or phosphatidylethanolamine is decreased compared to the normal control group, infection by non-tuberculous mycobacteria is predicted.

The term “decrease in concentration” used while referring to the “diagnostic composition” in the composition of the present invention refers to a case in which the concentration of a major body in the serum of an infected patient is significantly lower than that of a normal person who is not infected with Mycobacterium. Specifically, It means a decrease of about 10% or more, a decrease of about 20% or more, or a decrease of about 30% or more compared to the normal person and the control group, and more specifically, a case of about 40% or more decrease, excluding the range outside this no.

According to a specific embodiment of the present invention, the metabolite is whole blood, leukocytes, peripheral blood mononuclear cells, leukocyte buffy coat, plasma, serum ), sputum, tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva ), peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid ), pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cell, It is present in cell extracts and cerebrospinal fluid. Specifically, it may be serum, but is not limited thereto.

More specifically, whole blood, plasma or serum may be pretreated to detect the metabolite. For example, it may include filtration, distillation, extraction, separation, concentration, inactivation of interfering components, addition of reagents, and the like. In addition, the metabolites may include substances produced by metabolism and metabolic processes or substances generated by chemical metabolism by biological enzymes and molecules.

According to a specific embodiment of the present invention, the non-tuberculous mycobacteria are Mycobacterium avium ( M. avium ), Mycobacterium abscessus ( M. abscessus ), Mycobacterium flavecens ( M. flavescence ), Mycobacterium africanum ( M. africanum ), Mycobacterium bovis ( M. bovis ), Mycobacterium chelone ( M. chelonae ), Mycobacterium cellatum ( M. celatum ), Mycobacterium Fortuitum ( M. fortuitum ), Mycobacterium Gordone ( M. gordonae ), Mycobacterium gastri ( M. gastri ), Mycobacterium hemophilum ( M. haemophilum ), Mycobacterium Cobacterium intracellular lare ( M. intracellulare ), Mycobacterium kansasii ( M. kansasii ), Mycobacterium malmoenseu ( M. malmoense ), Mycobacterium marinum ( M. marinum ), mycobac Therium suzulgai ( M. szulgai ), Mycobacterium terre ( M. terrae ), Mycobacterium scrofulaceum ( M. scrofulaceum ), Mycobacterium Ulceranseu ( M. ulcerans ), Mycobacterium It may be selected from the group consisting of Leeum simiae ( M. simiae ) and Mycobacterium xenopi ( M. xenopi ), but is not limited thereto.

According to a specific embodiment of the present invention, the infectious disease of the non-tuberculous mycobacteria is lung disease, lymphadenitis, skin, soft tissue, bone infection, or disseminated disease.

According to the present invention, the non-tuberculous mycobacterium infection disease includes all clinical symptoms caused by infection with non-tuberculous mycobacteria.

According to another aspect of the present invention, the present invention provides Lysophosphatidylcholine, Lysophosphatidylethanolamine, Phosphatidylcholine, Phosphatidylethanolamine, Sphingomyeline and Triacylglycerol ) Provides an information method for diagnosing an infectious disease of non-tuberculous mycobacteria comprising measuring one or more metabolites selected from the group consisting of.

Since the non-tuberculosis mycobacteria to be diagnosed in the present invention and metabolites, which are diagnostic markers, have already been described above, their descriptions are omitted to avoid excessive redundancy.

According to a specific embodiment of the present invention, the step of measuring the concentration of the metabolite may use a quantitative device such as chromatography or mass spectrometry, but is not limited thereto.

The chromatography used in the present invention includes High Performance Liquid Chromatography (HPLC), Liquid-Solid Chromatography (LSC), Paper Chromatography (PC), and Thin Layer Chromatography (Thin Chromatography). -Layer Chromatography (TLC), Gas-Solid Chromatography (GSC), Liquid-Liquid Chromatography (LLC), Foam Chromatography (FC), Emulsion Chromatography Chromatography (EC), Gas-Liquid Chromatography (GLC), Ion Chromatography (IC), Gel Filtration Chromatography (GFC) or Gel Permeation Chromatography (GLC) GPC), but is not limited thereto, and all quantitative chromatography commonly used in the art may be used.

In the present invention, the mass spectrometer may use a conventionally known mass spectrometer without particular limitation, but specifically, for example, a Fourier transform mass spectrometer (FTMS), a Maldi-TOF mass spectrometer (MALDI-TOF MS), It may be Q-TOF MS or LTQ-Orbitrap MS, but is not limited thereto.

According to another aspect of the present invention, the present invention is lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), Uses of sphingomyelin (SM) and triacylglycerols (TAG) are provided.

According to one aspect of the present invention, the present invention is a non-tuberculosis drug comprising, as an active ingredient, an agent for measuring at least one metabolite selected from the group consisting of lipid metabolites, amino acids, and amino acid derivatives. A composition for predicting the severity of infectious diseases caused by acid-fast bacteria,

The lipid metabolite is at least one selected from the group consisting of lysophosphatidylcholine (LPC), phosphatidylcholine (PC), sphingomyeline (SM) and triacylglycerol (TAG),

The amino acids and amino acid derivatives include glutamine, histidine, methionine, asgparagine, glutamate, lysine, glycine, N,N-dimethylglycine (N, N-Dimethylglycine), threonine, homoserine, tryptophan, and citrulline.

The present inventors studied patients infected with Nontuberculous mycobacteria (NTM), in particular, Mycobacterium avium complex (MAC), which causes lung diseases very common in humans, for which it is difficult to develop objective and reliable diagnostic markers. An earnest effort was made to discover diagnostic markers to determine the severity of the disease. As a result, 25 types of polar and lipid metabolites were discovered as diagnostic markers that can reflect the severity of non-tuberculous mycobacterial infections with high reproducibility and reliability.

In the present specification, the term "non-tuberculosis mycobacteria" refers to acid-fast bacteria other than Mycobacterium tuberculosis, and specifically includes all mycobacteria that do not cause tuberculosis and leprosy. Anti-acid bacteria, unlike general bacteria, mean strains that do not dissolve and have the ability to withstand the addition of acid during the dyeing process. Mycobacterium tuberculosis is representative of these mycobacteria, and mycobacteria other than Mycobacterium tuberculosis are called nontuberculous mycobacteria (NTM), and new nontuberculous mycobacteria are discovered almost every year.

As used herein, the term “prediction” means evaluating whether a specific disease or disorder is currently severely advanced or has a risk of developing severe disease in the future based on a marker having a significant correlation with severity.

As used herein, the term “composition for prediction” refers to lipid metabolites, amino acids or amino acid derivatives in order to predict whether a subject's non-tuberculous mycobacterium infection has changed to severe or has a risk of developing severe disease in the future. It means an integrated mixture or device that includes a means for measuring the concentration of, and may be expressed as a “prediction kit”. Since the composition for prediction of the present invention includes a means for measuring the metabolite discovered in the present invention, the term "composition for prediction" may also be expressed as a "device for quantification" of metabolites.

As used herein, the term "metabolite", also referred to as a metabolite or metabolite, is an intermediate or product of metabolism. These metabolites are fuel, structure, signal transduction, stimulatory and inhibitory effects on enzymes, their own catalytic activity (usually as cofactors for enzymes), defense, and interactions with other organisms (e.g., pigments, aromatic compounds). , pheromones). Primary metabolites are directly involved in normal growth, development and reproduction. Secondary metabolites are not directly involved in these processes, but usually have important ecological functions.

According to the present invention, the metabolite refers to a metabolite obtained from a sample of biological origin, that is, a biological sample, and the biological sample refers to a biological fluid, tissue or cell.

According to the present invention, the metabolite may be a metabolite obtained from a liquid sample derived from blood, specifically serum.

According to a specific embodiment of the present invention, the lysophosphatidylcholine is at least one lysophosphatidylcholine selected from the group consisting of LPC (14:0), LPC (15:0) and LPC (20:3).

According to a specific embodiment of the present invention, the phosphatidylcholine is PC 32:2 (18:2/14:0), PC 34:3 (16:1/18:2), PC 36:1 (18:0/18 :1), selected from the group consisting of PC 36:3 (16:0/20:3), PC 36:6 (14:0/22:6) and PC 38:7 (16:1/22:6) is one or more phosphatidylcholines.

According to a specific embodiment of the present invention, the sphingomyelin is SM d34: 1 (d18: 1/16: 0), SM d36: 1 (d18: 1/18: 0) or SM d42: 2 (d18: 1/24: 1) is at least one sphingomyelin selected from the group consisting of.

According to a specific embodiment of the present invention, the triacylglycerol is TAG 58:11 (22:6/20:5/16:0).

According to a specific embodiment of the present invention, the glutamine, histidine, methionine, asparagine, glutamic acid, threonine, lysine, and tryptophan are L-forms.

According to a specific embodiment of the present invention, the concentration of glutamine, histidine, methionine, asparagine, lysine, glycine, N,N-dimethylglycine, threonine, homoserine, tryptophan or citrulline is in the upper lobe cavity type (Upper lobe caviary form) patient If the contrast is low, it is determined as severe non-tuberculous mycobacteria.

In the present invention, the infectious lung disease caused by the non-tuberculous mycobacterium is an upper lobe cavitary form or a nodular bronchiectatic form. In addition, the severity of the infectious disease caused by the non-tuberculous mycobacteria means upper lobe cavity type.

In the present invention, the measured metabolite concentration can be diagnosed by distinguishing whether a disease developed in a subject after infection with a non-tuberculous mycobacterium is an upper lobe cavity type lung disease or a nodular bronchiectasis type lung disease.

In the present invention, the term "upper lobe cavity type" is a well-known disease from a long time ago, and it occurs frequently in middle-aged men in their 40s and 50s with a long history of smoking and drinking, and if not treated, extensive lung disease occurs within 1-2 years. It refers to a disease that leads to death due to parenchymal destruction and respiratory failure. In chest radiography, upper lobe cavity and fibrotic lesion similar to pulmonary tuberculosis are observed, but contact spread is more distinct and pleural invasion is more marked than spread of lesion through the thin-walled cavity and bronchus surrounded by the lung parenchyma. Have.

In the present invention, the term “nodular bronchiectasis” is a disease known only in the late 1980s, and is mainly found in middle-aged or older non-smokers without underlying disease, and is also called “Lady Windermere syndrome”, It is a disease that progresses very slowly compared to type MAC lung disease and requires long-term follow-up. This disease has characteristic high-resolution computed tomography findings, with multiple bronchiectasis in the center and small nodules and infiltrates around it, mainly in the right middle lobe and the left upper lingual lobe.

The term "decreased or low concentration" used while referring to "composition for prediction" in the composition of the present invention refers to a case in which the concentration of a metabolite in the serum of patients with upper lobe cavity type is significantly lower than that of patients with nodular bronchiectasis. As a, the concentration of the metabolite is reduced by about 5% or more, about 10% or more, about 15% or more, about 20% or more, or about 25% or more, compared to nodular bronchiectasis patients and upper lobe cavity patients. It means, and more specifically, it means a case of decreasing by about 30% or more, and does not exclude a range outside this range.

According to a specific embodiment of the present invention, when the concentration of glutamic acid is higher than that of upper lobe cavity type patients , it is determined as severe non-tuberculous mycobacteria.

The term "increased or high concentration" used while referring to the "composition for prediction" in the composition of the present invention refers to a case in which the concentration of the major body in the serum of patients with upper lobe cavity type is significantly higher than that of patients with nodular bronchiectasis. By means that the concentration of the metabolite is increased by about 5% or more, about 10% or more, or about 15% or more, more specifically, about 20% or more, compared to the nodular bronchiectasis type patient and the upper lobe cavity type patient. It means the case of increasing, and does not exclude the range beyond this.

According to a specific embodiment of the present invention, when the concentration of the lysophosphatidylcholine or triacylglycerol is lower than that of upper lobe cavity type patients, it is determined as severe non-tuberculous mycobacteria.

The term "decreased or low concentration" used while referring to the "composition for prediction" in the composition of the present invention refers to a case in which the concentration of the allele in the serum of patients with upper lobe cavity type is significantly lower than that of patients with nodular bronchiectasis, Specifically, it means a decrease of about 10% or more, about 20% decrease, or about 30% or more decrease in the concentration of a metabolite compared to a patient with nodular bronchiectasis and a patient with upper lobe cavity type, and more specifically, a decrease of about 40% or more It means the case of, and does not exclude the scope outside of this.

According to a specific embodiment of the present invention, when the concentration of the sphingomyelin is higher than that of upper lobe cavity type patients, it is determined as severe non-tuberculous mycobacteria.

The term "increased or high concentration" used while referring to the "composition for prediction" in the composition of the present invention refers to a case in which the concentration of the major body in the serum of patients with upper lobe cavity type is significantly higher than that of patients with nodular bronchiectasis. As a metabolite concentration, it means an increase of about 10% or more, an increase of about 20% or more, or an increase of about 30% or more, more specifically, an increase of about 35% or more compared to patients with nodular bronchiectasis and upper lobe cavity patients. It means the case of, and does not exclude the scope outside of this.

According to a specific embodiment of the present invention, the phosphatidylcholine PC 32:2 (18:2/14:0), PC 34:3 (16:1/18:2), PC 36:6 (14:0/22: 6) Or, if the concentration of PC 38:7 (16:1/22:6) is lower than that of upper lobe cavitary form patients, it is judged as severe non-tuberculous mycobacteria.

According to a specific embodiment of the present invention, the concentration of the phosphatidylcholine PC 36: 1 (18: 0 / 18: 1) or PC 36: 3 (16: 0 / 20: 3) is the upper lobe cavity form If it is high compared to patients, it is determined as severe non-tuberculous mycobacteria.

According to a specific embodiment of the present invention, the lipid metabolites, amino acids and amino acid derivatives can be used in whole blood, leukocytes, peripheral blood mononuclear cells, leukocyte buffy coat, plasma ( plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate, breath, urine, semen ( semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid ), lymph fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions , present in cells, cell extracts and cerebrospinal fluid. Specifically, it may be serum, but is not limited thereto.

Specifically, whole blood, plasma or serum may be pretreated to detect the metabolites. For example, it may include filtration, distillation, extraction, separation, concentration, inactivation of interfering components, addition of reagents, and the like. In addition, the metabolites may include substances produced by metabolism and metabolic processes or substances generated by chemical metabolism by biological enzymes and molecules.

According to a specific embodiment of the present invention, the non-tuberculous mycobacteria are Mycobacterium avium ( M. avium ), Mycobacterium abscessus ( M. abscessus ), Mycobacterium flavecens ( M. flavescence ), Mycobacterium africanum ( M. africanum ), Mycobacterium bovis ( M. bovis ), Mycobacterium chelone ( M. chelonae ), Mycobacterium cellatum ( M. celatum ), Mycobacterium Fortuitum ( M. fortuitum ), Mycobacterium Gordone ( M. gordonae ), Mycobacterium gastri ( M. gastri ), Mycobacterium hemophilum ( M. haemophilum ), Mycobacterium Cobacterium intracellular lare ( M. intracellulare ), Mycobacterium kansasii ( M. kansasii ), Mycobacterium malmoenseu ( M. malmoense ), Mycobacterium marinum ( M. marinum ), mycobac Therium suzulgai ( M. szulgai ), Mycobacterium terre ( M. terrae ), Mycobacterium scrofulaceum ( M. scrofulaceum ), Mycobacterium Ulceranseu ( M. ulcerans ), Mycobacterium It may be selected from the group consisting of Leeum simiae ( M. simiae ) and Mycobacterium xenopi ( M. xenopi ), but is not limited thereto.

According to the present invention, the non-tuberculous mycobacterial infectious disease includes all clinical symptoms caused by infection with the non-tuberculous mycobacterium, and the infectious disease is lung disease, lymphadenitis, skin, soft tissue, bone infection, or disseminated disease. diseases and the like.

According to another aspect of the present invention, the present invention is a non-tuberculous mycobacteria comprising the step of measuring one or more metabolites selected from the group consisting of lipid metabolites, amino acids and amino acid derivatives. As an information providing method for predicting the severity of an infectious disease,

The lipid metabolite is at least one selected from the group consisting of Lysophosphatidylcholine, Phosphatidylcholine, Sphingomyeline and Triacylglycerol,

The amino acids and amino acid derivatives include glutamine, histidine, methionine, asgparagine, glutamate, lysine, glycine, N,N-dimethylglycine (N, N-Dimethylglycine), threonine, homoserine, tryptophan, and citrulline.

Lipid metabolites, amino acids, and amino acid derivatives, which are targets of measurement of non-tuberculous mycobacteria in the present invention, have already been described in detail, and thus description thereof is omitted to avoid excessive redundancy.

According to a specific embodiment of the present invention, the step of measuring the concentration of the metabolite uses a quantitative device such as chromatography or mass spectrometry.

Chromatography used in the present invention includes high performance liquid chromatography (HPLC), liquid-solid chromatography (LSC), paper chromatography (PC), thin layer chromatography (Thin -Layer Chromatography (TLC), Gas-Solid Chromatography (GSC), Liquid-Liquid Chromatography (LLC), Foam Chromatography (FC), Emulsion Chromatography Chromatography (EC), Gas-Liquid Chromatography (GLC), Ion Chromatography (IC), Gel Filtration Chromatography (GFC) or Gel Permeation Chromatography (GLC) GPC), but is not limited thereto, and all quantitative chromatography commonly used in the art may be used.

In the present invention, the mass spectrometer may use a conventionally known mass spectrometer without particular limitation, but specifically, for example, a Fourier transform mass spectrometer (FTMS), a Maldi-TOF mass spectrometer (MALDI-TOF MS), It may be Q-TOF MS or LTQ-Orbitrap MS, but is not limited thereto.

According to another aspect of the present invention, the present invention is lysophosphatidylcholine (LPC), phosphatidylcholine (PC), sphingomyelin (SM) and triacylglycerol (TAG ), Glutamine, Histidine, Methionine, Asgparagine, Glutamate, Lysine, Glysine, N,N-Dimethylglycine , Threonine, Homoserine, Tryptophan and Citrulline.

The present invention applies the metabolites as biomarkers for rapid, accurate and highly reliable measurement of non-tuberculous mycobacteria (NTM), especially Mycobacterium avium complex (MAC), which lacks objective and highly reliable diagnostic markers. , can be usefully used for more efficient diagnosis of non-tuberculous mycobacterial infectious diseases.

The present invention relates to non-tuberculous mycobacteria (NTM), especially Mycobacterium avium complex (MAC), which has no objective and highly reliable biomarker for the course of disease, and the metabolites can be used to determine the course and severity of the disease. By applying it as a predictive marker with high accuracy, it can be usefully used to significantly improve the survival rate of patients by determining the severity of patients infected with non-tuberculous mycobacteria and establishing a patient-specific treatment strategy at an early stage.

Figure 1a compares the expression levels of Lysophosphatidylcholine (LPC 18:0) in serum samples from patients with Mycobacterium avium complex (MAC)-infected lung disease and healthy people before antibiotic treatment in one embodiment of the present invention. that shows the graph.

Figure 1b is a comparison of the expression levels of Lysophosphatidylcholine (LPC 20:5) in serum samples from patients with Mycobacterium avium complex (MAC)-infected lung disease and healthy people before antibiotic treatment in one embodiment of the present invention. that shows the graph.

Figure 1c is a phosphatidylcholine (Phosphatidylcholine; PC 36:5 (20:5/16:0; 20:5/16:0 ) It shows a graph comparing the expression levels of)).

1d is a diagram of sphingomyeline (SM d34: 1 (d18: 1/ It shows a graph comparing the expression levels of 16:0)).

1e is a diagram of sphingomyeline (SM d42: 1 (d18: 1/ 24:0)) shows a graph comparing the expression levels.

1f is a diagram of sphingomyeline (SM d42:2 (d18:1/ 24: 1)) shows a graph comparing the expression levels.

Figure 1g is a triacylglycerol (TAG 54: 5 (18: 1/18; 18: 1/18; :1/18:3)) shows a graph comparing the expression levels.

Figure 1h is a triacylglycerol (TAG 55: 7 (21: 5/18; :2/16:0)) shows a graph comparing the expression levels.

Figure 1i shows triacylglycerol (TAG 58: 11 (22: 6/20) in serum samples from patients with Mycobacterium avium complex (MAC)-infected lung disease and healthy people before antibiotic treatment in one embodiment of the present invention. :5/16:0)) shows a graph comparing the expression levels.

Figure 1j shows the triacylglycerol (TAG 60:11 (22:6/20 22:6/20 :4/18:1)) shows a graph comparing the expression levels.

Figure 1k shows the triacylglycerol (TAG 60:12 (22:6/22; 22:6/22 :6/16:0)) shows a graph comparing the expression levels.

Figure 2a shows the expression level of Lysophosphatidylethanolamine (LPE 18:2) in serum samples from Mycobacterium avium complex (MAC) infected lung disease patients and healthy people before antibiotic treatment in one embodiment of the present invention. It shows the comparison graph.

Figure 2b shows the expression level of Lysophosphatidylethanolamine (LPE 20:4) in serum samples from Mycobacterium avium complex (MAC) infected lung disease patients and healthy people before antibiotic treatment in one embodiment of the present invention. It shows the comparison graph.

Figure 2c is a phosphatidylcholine (Phosphatidylcholine; PC 28:0 (14:0/14:0 ) It shows a graph comparing the expression levels of)).

Figure 2d is a phosphatidylcholine (Phosphatidylcholine; PC 30:0 (14:0/16:0 ) It shows a graph comparing the expression levels of)).

Figure 2e is a phosphatidylcholine (Phosphatidylcholine; PC 32:2 (18:2/14:0; PC 32:2 (18:2/14:0 ) It shows a graph comparing the expression levels of)).

Figure 2f is a phosphatidylcholine (Phosphatidylcholine; PC 33:2 (18:2/15:0; 18:2/15:0 ) It shows a graph comparing the expression levels of)).

Figure 2g is a phosphatidylcholine (Phosphatidylcholine; PC 34:2 (18:2/16:0; 18:2/16:0 ) It shows a graph comparing the expression levels of)).

Figure 2h is a phosphatidylcholine (Phosphatidylcholine; PC 34:3 (16:1/18:2; 16:1/18:2 ) It shows a graph comparing the expression levels of)).

Figure 2i is a phosphatidylcholine (Phosphatidylcholine; PC 36:4 (20:4/16:0; 20:4/16:0 ) It shows a graph comparing the expression levels of)).

Figure 2j is a phosphatidylcholine (Phosphatidylcholine; PC O--36:3 (O--18; PC O--36:3 (O--18 :1/18:2)) shows a graph comparing the expression levels.

Figure 2k is a phosphatidylcholine (Phosphatidylcholine; PC O--36:5 (O--16; PC O--36:5 (O--16 :1/20:4)) shows a graph comparing the expression levels.

Figure 2l is a phosphatidylcholine (Phosphatidylcholine; PC O--38:5 (O--18; PC O--38:5 (O--18 :1/20:4)) shows a graph comparing the expression levels.

Figure 2m is in one embodiment of the present invention, phosphatidylethanolamine (PE--NME 34: 1 (18: 18: It shows a graph comparing the expression levels of 1/16:0)).

Figure 3a is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression level of L-glutamine.

Figure 3b is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of L-histidine.

Figure 3c is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of L-methionine.

Figure 3d is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC) infected lung disease It shows a graph comparing the expression level of L-asparagine.

Figure 3e is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of L-glutamic acid (L-Glutamate).

Figure 3f is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of L-threonine.

Figure 3g is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of N,N-dimethylglycine.

Figure 3h is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression level of L- lysine (L-Lysine).

Figure 3i is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of glycine.

Figure 3j is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of homoserine.

Figure 3k is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of citrulline.

Figure 3l is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavitary form among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of L-tryptophan.

Figure 4a is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC) infected lung disease It shows a graph comparing the expression level of Lysophosphatidylcholine (LPC 14:0).

Figure 4b is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of Lysophosphatidylcholine (LPC 15:0).

Figure 4c is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of Lysophosphatidylcholine (LPC 20:3).

Figure 4d is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavitary form among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression levels of phosphatidylcholine (PC 32:2 (18:2/14:0)).

Figure 4e is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression levels of phosphatidylcholine (PC 34:3 (16:1/18:2)).

Figure 4f is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression levels of phosphatidylcholine (PC 36:1 (18:0/18:1)).

Figure 4g is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression levels of phosphatidylcholine (PC 36:3 (16:0/20:3)).

Figure 4h is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression levels of phosphatidylcholine (PC 36:6 (14:0/22:6)).

Figure 4i is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression levels of phosphatidylcholine (PC 38:7 (16:1/22:6)).

Figure 4j is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression level of sphingomyeline (SM d34: 1 (d18: 1/16: 0)).

Figure 4k is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression level of sphingomyeline (SM d36: 1 (d18: 1/18: 0)).

Figure 4l is in one embodiment of the present invention, in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among lung disease patients infected with Mycobacterium avium complex (MAC) It shows a graph comparing the expression levels of sphingomyeline (SM d42:2 (d18:1/24:1)).

Figure 4m is in one embodiment of the present invention in serum samples from patients with nodular bronchiectatic form and patients with upper lobe cavity type among patients with Mycobacterium avium complex (MAC)-infected lung disease It shows a graph comparing the expression level of triacylglycerol (TAG 58:11 (22:6/20:5/16:0)).

The present invention relates to patients infected with nontuberculous mycobacteria (NTM), in particular, Mycobacterium avium complex (MAC), which causes lung disease very common in humans, for which it is difficult to develop objective and reliable diagnostic markers. It is for discovering diagnostic markers for distinguishing from healthy subjects and discovering diagnostic markers for determining the severity of infected patients. The study was conducted by comparative analysis of serum samples from infected patients before treatment (Tx0) and serum samples from healthy individuals and serum samples from infected patients. As a result, 24 types of lipid metabolites were discovered as diagnostic markers that can clearly distinguish non-tuberculosis mycobacterium-infected patients from non-infected subjects, and as diagnostic markers that can reflect the severity of non-tuberculosis mycobacterium infection with high reproducibility and reliability, 25 species of polar and lipid metabolites were discovered. Accordingly, it is possible to establish a patient-specific treatment strategy at an early stage by more efficiently diagnosing non-tuberculous mycobacterium infectious diseases and determining the severity of patients infected with non-tuberculous mycobacteria.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for explaining the present invention in more detail, and it will be apparent to those skilled in the art that the scope of the present invention is not limited by these examples according to the gist of the present invention. .

Example

[Experimental Example 1] Sample collection of MAC infected patients and healthy people

Patients infected with Mycobacterium avium complex (avium: 80, intracellulare: 65, total 145) collected from Seoul Samsung Hospital for about 6 years from January 2012 to August 2016 145 serum samples before antibiotic treatment and 30 serum samples from healthy people were prepared.

[Experimental Example 2] Pre-treatment of the sample

First, 300 μl chloroform and 150 μl methanol (chloroform-methanol, 2:1, v/v, 4° C.) were added to the serum sample (50 μl) obtained in Experimental Example 1 and mixed for 30 seconds. 150 μl water was added thereto, mixed for 30 seconds, put into ICE, and left for 10 minutes to extract. Thereafter, after centrifugation at 13,000 rpm, 4 ℃ for 10 minutes using a centrifuge, the lower layer (200 μl) was separated and dried using a speed vacuum (full vacuum, no temp, 1-2 hours) to obtain the following metabolism Stored at -20 °C until sieve analysis. For mass spectrometry analysis, the dried sample was re-dissolved in 200 μl isopropanol:acetonitrile:water (2:1:1, v/v) and filtered to remove possible impurities. Analysis was performed after filtering using a filter tube (Costar 8169). As Machinery Quality Control (MQC), it is repeated 6 times per batch using healthy human serum as a sample for Machinery Quality Control (MQC) as a pre-processing method like serum sample to check the MS/MS instrument condition. analyzed. For sample quality control (SQC), in order to compare differences between samples in each batch, 10 μl per sample was collected and sample quality control was prepared and analyzed 6 times per batch.

[Experimental Example 3] Metabolome analysis through UHPLC-MS (Q-Exactive Orbitrap Plus)

In order to analyze lipid metabolites in the analysis sample treated with serum, analysis was performed using chromatography-tandem mass spectrometry (UHPLC-MS). The equipment used was Thermo Scientific's Ultimate 3000RS pump UHPLC and Q-Exactive Orbitrap Plus MS. As chromatographic conditions for hydrophilic interaction, lipid metabolites were separated using an Acquity UPLC BEH C18 (2.1 x 100 mm, 1.7 μm, Waters) column using gradient elution at 35 °C. The first mobile phase includes (A) 10mM Ammonium formate in 50% ACN + 0.1% Formic acid (v/v) and (B) 2mM Ammonium formate in ACN/IPA/Water 10:88:2 + 0.02% Formic acid (v/v). v) was used, and the gradient elution of the next mobile phase was performed in the same manner as in Table 1 below with a total analysis time of 28 minutes. Electrospray Ionization (ESI) was performed in two modes of ionization, positive and negative, and the full scan mass range was 250-1200 m/z with 70,000 resolution. It was used, and the automatic gain control (AGC) target was analyzed with 1x10 ⁶ ions and the maximum injection time (Injection time, IT) was 100 ms. The collision energy (CE) was 20, 30, and 40, the source ionization spray voltage was 3.0 kV, and the capillary temperature was 370 °C. For the results obtained through the analysis, raw data were calculated through Thermo Scientific's analysis software (Compound Discoverer), and lipid metabolites with high significance (p-value <0.05) were calculated.

time (minutes)	Mobile phase A (%)	Mobile phase B (%)	Flow rate (mL/min)
0	65	35	0.30
4	40	60	0.30
12	15	85	0.30
21	0	100	0.30
24	0	100	0.30
28	65	35	0.30

[Experimental Example 4] Results of metabolome analysis in serum samples of non-tuberculous mycobacteria infected patients

In order to compare the concentrations of metabolites between patients with Mycobacterium avium complex (MAC)-infected lung disease and healthy people before antibiotic treatment, Metaboanalyst (data statistics site) and SPSS statistical program were used in the following two statistical tests to compare groups. Lipid metabolites with liver significance (p-value<0.05) were calculated, and using the results, the total number of disease-related metabolites that can distinguish patients with lung disease infected with Mycobacterium avium complex (MAC) before treatment and healthy people 24 species (p-value <0.05) were selected based on each p-value and the fold change value of the expression level compared to healthy people, and the results are shown in Table 2 and FIGS. 1a to 2m. However, in FIGS. 1A to 2M, HC represents the expression level of each metabolite in serum samples of 30 healthy people, and Tx0 represents the expression level of each metabolite in serum samples of 145 patients infected with Mycobacterium avium complex (MAC) before antibiotic treatment. It shows the expression level of each metabolite. In addition, *P<0.05; **P<0.01; ***P<0.001 means.

Increased lipid metabolites in healthy human samples compared to MAC patient samples before treatment
Metabolite types (Compounds)	Significance (p-value)	Fold Change
LPC 18:0	0.038	1.10
LPC 20:5	<0.001	1.63
PC 36:5 (20:5/16:0)	<0.001	1.44
SM d34:1 (d18:1/16:0)	0.003	1.16
SM d42:1 (d18:1/24:0)	0.004	1.20
SM d42:2 (d18:1/24:1)	<0.001	1.29
TAG 54:5 (18:1/18:1/18:3)	0.025	1.31
TAG 55:7 (21:5/18:2/16:0)	<0.001	1.96
TAG 58:11(22:6/20:5/16:0)	<0.001	2.43
TAG 60:11 (22:6/20:4/18:1)	<0.001	1.96
TAG 60:12(22:6/22:6/16:0)	0.002	1.96
Decreased lipid metabolites in healthy human samples compared to MAC patient samples before treatment
LPE 18:2	0.011	0.76
LPE 20:4	<0.001	0.72
PC 28:0 (14:0/14:0)	0.003	0.54
PC 30:0 (14:0/16:0)	0.019	0.79
PC 32:2 (18:2/14:0)	<0.001	0.65
PC 33:2 (18:2/15:0)	0.048	0.87
PC 34:2 (18:2/16:0)	0.032	0.92
PC 34:3 (16:1/18:2)	0.049	0.84
PC 36:4 (20:4/16:0)	<0.001	0.77
PE-NME 34:1 (18:1/16:0)	0.002	0.87
PC O-36:3 (O-18:1/18:2)	<0.001	0.78
PC O-36:5 (O-16:1/20:4)	<0.001	0.69
PC O-38:5 (O-18:1/20:4)	<0.001	0.79

As shown in Table 2 and FIGS. 1A to 2M, among the blood metabolites, Lysophosphatidylcholine (LPC 18:0), lysophosphatidylcholine (LPC 20:5), and phosphatidylcholine (PC 36:5 (20:5/ 16:0)), Sphingomyeline (SM d34:1 (d18:1/16:0)), SM d42:1 (d18:1/24:0), sphingomyelin Myelin (SM d42:2 (d18:1/24:1)), triacylglycerol (TAG 54:5 (18:1/18:1/18:3)), triacylglycerol (TAG 55: 7 (21:5/18:2/16:0)), triacylglycerol (TAG 58:11 (22:6/20:5/16:0)), triacylglycerol (TAG 60:11 (22: 6/20:4/18:1)) and triacylglycerol (TAG 60:12(22:6/22:6/16:0)) were significantly expressed in non-tuberculous mycobacteria infected patients compared to healthy people. In addition, lysophosphatidylethanolamine (LPE 18:2), lysophosphatidylethanolamine (LPE 20:4), phosphatidylcholine (PC 28:0 (14:0/14:0)), phosphatidylcholine ( PC 30:0 (14:0/16:0)), Phosphatidylcholine (PC 32:2 (18:2/14:0)), Phosphatidylcholine (PC 33:2 (18:2/15:0)), Phosphatidylcholine (PC 34:2 (18:2/16:0)), phosphatidylcholine (PC 34:3 (16:1/18:2)), phosphatidylcholine (PC 36:4 (20:4/16:0)), Phosphatidylcholine (PC O-36:3 (O-18:1/18:2)), Phosphatidylcholine (PC O-36:5 (O-16:1/20:4)), Phosphatidylcholine (PC O-36:5 (O-16: 1/20: 4)) and phosphatidylethanolamine (PE-NME 34: 1 (18: 1/16: 0)) showed a significant decrease in their expression in non-tuberculous mycobacteria infected patients compared to healthy people. could confirm that

Through this, as lipid metabolites, Lysophosphatidylcholine (LPC 18:0), Lysophosphatidylcholine (LPC 20:5), Phosphatidylcholine (PC 36:5 (20:5/16:0)), sphingomyelin ( Sphingomyeline; SM d34:1 (d18:1/16:0)), sphingomyelin (SM d42:1 (d18:1/24:0)), sphingomyelin (SM d42:2 (d18:1 /24:1)), triacylglycerol (TAG 54:5 (18:1/18:1/18:3)), triacylglycerol (TAG 55:7 (21:5/18:2/16 :0)), triacylglycerol (TAG 58:11 (22:6/20:5/16:0)), triacylglycerol (TAG 60:11 (22:6/20:4/18:1)) , triacylglycerol (TAG 60:12 (22:6/22:6/16:0)), lysophosphatidylethanolamine (LPE 18:2), lysophosphatidylethanolamine (LPE 20:4), phosphatidylcholine ( Phosphatidylcholine; PC 28:0 (14:0/14:0)), Phosphatidylcholine (PC 30:0 (14:0/16:0)), Phosphatidylcholine (PC 32:2 (18:2/14:0)) , Phosphatidylcholine (PC 33:2 (18:2/15:0)), Phosphatidylcholine (PC 34:2 (18:2/16:0)), Phosphatidylcholine (PC 34:3 (16:1/18:2) ), phosphatidylcholine (PC 36:4 (20:4/16:0)), phosphatidylcholine (PC O-36:3 (O-18: 1/18:2)), phosphatidylcholine (PC O-36:5 (O -16:1/20:4)), phosphatidylcholine (PC O-36:5 (O-16:1/20:4)) and phosphatidylethanolamine (PE-NME 34:1 (18:1/16:0 )) can be used as a biomarker for diagnosing infection or infectious disease caused by non-tuberculous mycobacteria.

[Experimental Example 5] Sample collection of patients with nodular bronchiectatic (NB) and upper lobe cavitary (UC) patients by type of lung disease of patients with MAC infection

Serum samples from patients infected with Mycobacterium avium complex collected at Seoul Samsung Hospital for about 6 years from January 2012 to August 2016 were analyzed in the form of lung disease (NB: 83 patients, UC: 31 people, a total of 114 people) were divided according to extraction and preparation.

[Experimental Example 6] Pre-treatment of the sample

First, for lipid metabolome analysis, 300 μl chloroform and 150 μl methanol (chloroform-methanol, 2: 1, v / v, 4 ℃) were added to the serum sample (50 μl) obtained in Experimental Example 1, and for 30 seconds mixed it up 150 μl water was added thereto, mixed for 30 seconds, put into ICE, and left for 10 minutes to extract. Thereafter, after centrifugation at 13,000 rpm, 4 ° C. for 10 minutes using a centrifuge, the lower layer (200 μl) was separated and dried using a speed vacuum (full vacuum, no temp, 1-2 hours) to obtain the following Stored at -20 °C until metabolome analysis. After re-dissolving the dried sample in 200 μl isopropanol:acetonitrile:water (2:1:1, v/v) for mass spectrometry analysis, filter to remove possible impurities. Analysis was performed after filtering using a filter tube (Costar 8169). For polar metabolomic analysis, 86μl water and 201μl acetonitrile (total of 287μl 70% Acetonitrile, 4°C, v/v) were added to serum sample (10μl), and 3μl internal standard mixture (Isotopic solution from Cambridge Isotope Laboratories) was added. and 13C labeled taurine, allantoin, hypoxanthine), mixed for 30 seconds, put in ICE and left for 10 minutes for extraction, and analysis was performed after filtration using a filter tube (Costar 8169) to remove impurities. As machine quality control (MQC), human serum samples purchased to check the MS/MS device status are used as samples for mechanical quality control (MQC) in the same pre-processing method as patient serum samples, per batch. Six replicates were analyzed. For sample quality control (SQC), in order to compare differences between samples in each batch, 10 μl per sample was collected and sample quality control was prepared and analyzed 6 times per batch.

[Experimental Example 7] Metabolome analysis through HPLC-Triple Quad-MS

In order to analyze polar metabolites in the analysis sample treated with serum, analysis was performed using chromatography-tandem mass spectrometry (HPLC-MS/MS). The equipment used was Agilent 1200 HPLC and Sciex API4000 triple quadrupole MS. As chromatographic conditions for hydrophilic interaction, polar metabolites were separated using a Luna PFPP (2.0 x 150 mm, 3 μm, Phenomenex) column at 20° C. using gradient elution in two ways depending on the solvent. (A) H2O (v/v) and (B) Acetonitrile (v/v) were used as the first mobile phase, and (A) H2O (v/v, 0.1% formic acid) and (B) Acetonitrile were used as the second mobile phase. (v / v) was used, and the gradient elution of each condition was performed in the same manner as in Table 3 below with a total analysis time of 15 minutes. The atomizer gas (Ion-Source Gas 1/2) unit was 50/50 arbitrary units, and the gas curtain (Curtain Gas) unit was 25 arbitrary units. The source temperature was 500 °C, the ion-spray floating voltage was 5,5 kV (negative -4.5 kV), and the mass range was 50-1000 m/z. Sample injection was performed by 3 μl using the HTC_PAL system/CTC analytics auto-sampler, and the tandem mass spectrometry conditions (Scheduled Multiple Reaction Monitoring, sMRM) were performed as shown in Tables 3 to 7 below. Table 4 is Water method (+), and 21 metabolites, Table 5 is Water method (-), and 12 metabolites, Table 6 is Formic acid method (+), and 32 metabolites, 7 is the formic acid method (-), and 24 metabolites.

time (minutes)	Mobile phase A (%)	Mobile phase B (%)	Flow rate (mL/min)
0	100	0	0.35
8	73	27	0.35
9	15	85	0.35
10	100	0	0.35
15	100	0	0.35

Metabolite types (Compounds)	m/z	Product ion	RT	CE
Tyrosine (L-Tyrosine)	182	77	2.8	41
Cystathionine (L-Cystathionine)	223	134	0.9	11
Betaine	118	58	1.32	39
Thiamine	127	110	5.43	21
Ornithine	133	70	0.95	25
Guanine	152	110	2.2	27
Histidine	156	110	1.32	12
Acetylornithine (N-Acetylornithine)	175	115	1.14	14
Glucosamine	180	162	1.4	10
Uracil	113	70	1.85	23
Deoxyuridine	229	113	6.21	11
Cytidine	244	112	2.44	12
Deoxyadenosine	252	136	8.5	20
Deoxyinosine	253	137	6.58	12
Adenosine	268	136	7.72	27
Deoxyguanosine	268	152	6.84	15
Inosine	269	137	6.24	14
Guanosine	284	152	6.55	17
Xanthosine	285	153	6.97	20
Cyclic AMP	328	287	0.86	9
S-Adenosylmethionine S-Adenosylmethionine (SAH)	385	136	0.46	19

Metabolite types (Compounds)	m/z	Product ion	RT	CE
Glucose (D-Glucose)	179	89	0.92	-12
Hydroxybutyrate (3-hydroxybutyric acid)	103	41	0.96	-32
Taurine	124	80	0.9	-16
Anthranilate	136	92	3.68	-16
Hydroxybenzoate (p-Hydroxybenzoate)	137	93	1.6	-21
Citrulline	174	131	1.21	-13
Hydroxyphenylpyruvate (p-Hydroxybenzoate)	179	107	0.97	-11
Myo-Inositol	179	161	0.94	-15
Thymidine	241	125	7.02	-10
Uridine	243	111	4.22	-12
Nicotinate	122	78	1.54	-14
Uric acid	167	124	1.35	-22

Metabolite types (Compounds)	m/z	Product ion	RT	CE
Serine (L-Serine)	106	60	0.9	15
Proline (L-Proline)	116	70	1.13	21
Valine (L-Valine)	118	72	1.41	15
Threonine (L-Threonine)	120	74	0.96	15
Isoleucine (L-isoLeucine)	132	86	1.93	15
Leucine (L-Leucine)	132	86	2.3	15
Asparagine (L-Asparagine)	133	74	0.9	17
Glutamine (L-Glutamine)	147	84	0.95	23
Lysine (L-Lycine)	147	84	0.74	23
Glutamate (L-Glutamate)	148	84	One	23
Methionine (L-Methionine)	150	104	1.8	11
Phenylalanine (L-Phenylalanine)	166	120	6.41	17
Arginine (L-Arginine)	175	70	0.8	35
Tryptophan (L-Tryptophan)	205	188	8.4	13
Dimethylglycine (N,N-Dimethylglycine)	104	58	1.21	27
Choline	104	60	0.9	19
Glycine	76	30	1.06	16
Folate	442	295	9.58	19
Adenine	136	119	1.75	24
Homocysteine	136	90	1.26	15
Hypoxanthine	137	110	2.8	29
Xanthine	153	110	2.5	23
Allantoin	159	99	1.17	13
Cytosine	112	95	0.98	17
Homoserine	120	56	1.03	27
Thiamine	265	122	0.96	17
Cysteine	122	59	1.24	27
Cytidine monophosphate (CMP)	324	112	1.68	16
Uridine monophosphate (UMP)	325	97	3	49
adenosine monophosphate Adenosine monophosphate (AMP)	348	136	1.99	21
inosine monophosphate Inosine monophosphate (IMP)	349	137	5.7	17
Spermine	203	112	0.53	27

Metabolite types (Compounds)	m/z	Product ion	RT	CE
Aspartate (L-Aspartate)	132	88	0.96	-17
Lactate ((S)-Lactate)	89	43	1.74	-18
Phosphoglycerate (3-Phosphoglycerate)	185	97	2.11	-22
Succinate	117	73	3.88	-18
Malate (L-Malic acid)	133	115	1.78	-16
Citrate	191	111	3.58	-12
Hydroglutarate (D-2-Hydroyglutaric acid)	147	129	1.03	-14
Guanosine triphosphate (GTP)	522	424	1.6	-30
Acetylphosphate	139	79	1.65	-22
Carbamoyl-phosphate	140	79	0.9	-22
Glycerate	105	75	1.24	-15
Phosphoenolpyruvate	167	79	2.3	-16
dihydroxyacetone phosphate (Dihydroxyacetonephosphate)	169	79	1.7	-38
Glycerol 3-Phosphate	171	79	1.5	-22
Shikimate	173	93	1.65	-16
Allontoate	175	132	1.05	-12
Deoxyribose 1-phosphate (Deoxyrebose 1-Phosphate)	213	79	1.6	-33
Ribulose 5-Phosphate (D-Ribulose 5-Phosphate)	229	79	1.3	-48
Glucose 6-Phosphate	259	79	1.73	-40
Fructose 1,6-bisphosphate (Fructose1,6-Bisphosphate)	339	271	0.98	-18
Deoxyguanosine Monophosphate Deoxyguanosine monophosphate (dGMP)	346	79	2.02	-20
Phosphoribosyl pyrophosphate (PRPP)	389	291	1.4	-18
Itaconate	129	85	6.4	-14
Fructose 6-Phosphate	259	79	1.23	-54

- m/z means mass to charge ratio.

- RT means retention time.

- CE means collision energy.

- (+) means positive ion mode and (-) means negative ion mode.

- For the results obtained through sMRM analysis, raw data was calculated through Sciex's Quantitative Analysis Software, and polar metabolites with a relative standard deviation (RSD<20) or less were calculated using the average value of MQC data.

[Experimental Example 8] Metabolome analysis through UHPLC-MS (Q-Exactive Orbitrap Plus)

In order to analyze lipid metabolites of analysis samples isolated from serum, analysis was performed using chromatography-tandem mass spectrometry (UHPLC-MS). The equipment used was Thermo Scientific's Ultimate 3000RS pump UHPLC and Q-Exactive Orbitrap Plus MS. As chromatographic conditions for hydrophilic interaction, lipid metabolites were separated using an Acquity UPLC BEH C18 (2.1 x 100 mm, 1.7 μm, Waters) column using gradient elution at 35°C. As mobile phase, (A) 10mM Ammonium formate in 50% ACN + 0.1% Formic acid (v/v) and (B) 2mM Ammonium formate in ACN/IPA/Water 10:88:2 + 0.02% Formic acid (v/v) was used, and the gradient elution of the next mobile phase was performed in the same manner as in Table 8 below with a total analysis time of 28 minutes.

Electrospray Ionization (ESI) was performed with positive and negative two modes of ionization, and the full scan mass range was 250-1200 m/z with a resolution of 70,000 and automatic gain control. (Automatic gain control, AGC) The target was 1x106ion and the maximum injection time (Injection time, IT) was analyzed at 100ms. The collision energy (CE) was 20, 30, and 40, the source ionization spray voltage was 3.0 kV, and the capillary temperature was 370 °C. For the results obtained through the analysis, raw data were calculated through Thermo Scientific's analysis software (Compound Discoverer), and lipid metabolites with high significance (p-value <0.05) were calculated.

time (minutes)	Mobile phase A (%)	Mobile phase B (%)	Flow rate (mL/min)
0	65	35	0.30
4	40	60	0.30
12	15	85	0.30
21	0	100	0.30
24	0	100	0.30
28	65	35	0.30

[Experimental Example 9] Metabolome analysis results in serum samples of non-tuberculous mycobacteria infected patients

To compare polarity and lipid metabolite concentrations in serum samples from 83 patients with nodular bronchiectatic (NB) and 31 patients with upper lobe cavity (UC) among MAC-infected patients before antibiotic treatment With the following statistical test method, Metaboanalyst (statistical site), Quantitative Analysis Software of SCIEX ^TM , Compound Discoverer of Thermofisher ^TM , SPSS (statistical program) Unpaired, Welch's T-test test showed high significance between groups (p-value <0.05), polar and lipid metabolites with a high probability (p-value <0.09) were calculated, and using the results, 12 polar metabolites and lipid metabolites that can be indicators to predict the severity of MAC patients before treatment A total of 25 metabolites, including 13, were selected based on the p-value and the fold change value of the expression level compared to the upper lobe cavity (UC), and the results are shown in Figures 3a to 4m shown in However, in FIGS. 3A to 4M, NB_Tx0 shows the expression levels of each metabolite in serum samples from 83 patients with bronchiectasis before starting antibiotic treatment, and UC_Tx0 shows the expression level of each metabolite in serum samples from 31 patients with upper lobe cavity before starting antibiotic treatment. It shows the expression level of the body. In addition, significance unpaired, Welch's t-test *P<0.05;**P<0.01;***P<0.001 means.

Since the specific parts of the present invention have been described in detail above, it is clear that these specific techniques are only preferred embodiments for those skilled in the art, and the scope of the present invention is not limited thereto. Accordingly, the practical scope of the present invention will be defined by the appended claims and equivalents thereof.

The present invention relates to patients infected with nontuberculous mycobacteria (NTM), in particular, Mycobacterium avium complex (MAC), which causes lung disease very common in humans, for which it is difficult to develop objective and reliable diagnostic markers. It is for the discovery of diagnostic markers for distinguishing from healthy subjects and the development of diagnostic markers for determining the severity of infected patients. Recently, reports of lung infections caused by non-tuberculous mycobacteria are increasing worldwide, but there is a lack of biomarkers for differentiating patients with non-tuberculous mycobacteria lung infections from healthy populations, or studies on the pathophysiology of the disease. In addition, the lack of research to distinguish and diagnose the severity of infection in patients has been reported as a problem, and the need for its development is required. The present invention relates to more efficient diagnosis of non-tuberculous mycobacterial infectious diseases and prediction of the severity of patients infected with non-tuberculous mycobacteria, and is useful for significantly improving the survival rate of patients by establishing a treatment strategy tailored to patients with infectious diseases at an early stage. expected to be used.

Claims (32)

1. Lysophosphatidylcholine (LPC), Lysophosphatidylethanolamine (LPE), Phosphatidylcholine (PC), Phosphatidylethanolamine (PE), Sphingomyeline (SM) and triacylglycerol; A composition for diagnosis of an infectious disease of non-tuberculous mycobacteria comprising, as an active ingredient, an agent for measuring one or more metabolites selected from the group consisting of (TAG).
2. According to claim 1,

   The composition, characterized in that the lysophosphatidylcholine is at least one lysophosphatidylcholine selected from the group consisting of LPC (18:0) and LPC (20:5).
3. According to claim 1,

   The composition, characterized in that the lysophosphatidylethanolamine is at least one lysophosphatidylethanolamine selected from the group consisting of LPE (18:2) and LPE (20:4).
4. According to claim 1,

   The phosphatidylcholine is PC 36:5 (20:5/16:0), PC 28:0 (14:0/14:0), PC 30:0 (14:0/16:0), PC 32:2 ( 18:2/14:0), PC 33:2 (18:2/15:0), PC 34:2 (18:2/16:0), PC 34:3 (16:1/18:2) , PC 36:4(20:4/16:0), PC O--36:3(O--18:1/18:2), PC O--36:5(O-16:1/20 :4) and at least one phosphatidylcholine selected from the group consisting of PC O--36:5 (O--16:1/20:4).
5. According to claim 1,

   The composition, characterized in that the phosphatidylethanolamine is PE--NME 34: 1 (18: 1 / 16: 0).
6. According to claim 1,

   The sphingomyelin is a group consisting of SM d34:1 (d18:1/16:0), SM d42:1 (d18:1/24:0) and SM d42:2 (d18:1/24:1) A composition, characterized in that at least one sphingomyelin selected from.
7. According to claim 1,

   The triacylglycerol is TAG 54:5 (18:1/18:1/18:3), TAG 55:7 (21:5/18:2/16:0), TAG 58:11 (22:6/ 20:5/16:0), TAG 60:11 (22:6/20:4/18:1) and TAG 60:12 (22:6/22:6/16:0) A composition characterized in that it is at least one triacylglycerol.
8. According to claim 1,

   When the concentration of the lysophosphatidylcholine, phosphatidylcholine, sphingomyelin or triacylglycerol is increased compared to the normal control, a composition predicted to be infected by non-tuberculous mycobacteria.
9. According to claim 1,

   When the concentration of lysophosphatidylethanolamine, phosphatidylcholine or phosphatidylethanolamine is decreased compared to the normal control, a composition predicted to be infected by non-tuberculous mycobacteria.
10. According to claim 1,

    The metabolites are whole blood, leukocytes, peripheral blood mononuclear cells, leukocyte buffy coat, plasma, serum, sputum, tears ( tears, mucus, nasal washes, nasal aspirates, breath, urine, semen, saliva, peritoneal washings, Ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple Nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cells, cell extract and cerebrospinal fluid ( A composition characterized by being present in cerebrospinal fluid).
11. According to claim 1,

    The non-tuberculous acidophilus is Mycobacterium avium ( M. avium ), Mycobacterium absesus ( M. abscessus ), Mycobacterium flavescence ( M. flavescence ), Mycobacterium africanum ( M. africanum ), Mycobacterium bovis ( M. bovis ), Mycobacterium chelone ( M. chelonae ), Mycobacterium cellatum ( M. celatum ), Mycobacterium fortuitum ( M. fortuitum ), Mycobacterium gordonae ( M. gordonae ), Mycobacterium gastri ( M. gastri ), Mycobacterium hemophilum ( M. haemophilum ), Mycobacterium intracellurare ( M. intracellulare ), Mycobacterium Kansasii ( M. kansasii ), Mycobacterium malmoenseu ( M. malmoense ), Mycobacterium marinum ( M. marinum ), Mycobacterium suzulgai ( M. szulgai ) , Mycobacterium terae ( M. terrae ), Mycobacterium scrofulaceum ( M. scrofulaceum ), Mycobacterium Ulceranseu ( M. ulcerans ), Mycobacterium simiae ( M. simiae ) and A composition characterized in that it is selected from the group consisting of Mycobacterium xenopi ( M. xenopi ).
12. According to claim 1,

    The non-tuberculous mycobacterium infectious disease is a composition characterized in that lung disease, lymphadenitis, skin, soft tissue, bone infection or disseminated disease.
13. At least one metabolite selected from the group consisting of Lysophosphatidylcholine, Lysophosphatidylethanolamine, Phosphatidylcholine, Phosphatidylethanolamine, Sphingomyeline and Triacylglycerol Information providing method for diagnosing infectious diseases of non-tuberculous mycobacteria comprising the step of measuring.
14. According to claim 13,

    Wherein the step of measuring the concentration of the metabolite is performed using a quantitative device such as chromatography or mass spectrometry.

    Lysophosphatidylcholine (LPC), Lysophosphatidylethanolamine (LPE), Phosphatidylcholine (PC), Phosphatidylethanolamine (PE), Sphingomyeline (SM) and triacylglycerol; A composition for diagnosis of an infectious disease of non-tuberculous mycobacteria comprising, as an active ingredient, an agent for measuring one or more metabolites selected from the group consisting of (TAG).
15. Lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM) and triacylglycerol ( TAG) use.
16. A composition for predicting the severity of infectious diseases caused by non-tuberculosis mycobacteria, comprising as an active ingredient an agent measuring one or more metabolites selected from the group consisting of lipid metabolites, amino acids, and amino acid derivatives. as,

    The lipid metabolite is at least one selected from the group consisting of lysophosphatidylcholine (LPC), phosphatidylcholine (PC), sphingomyeline (SM) and triacylglycerol (TAG),

    The amino acids and amino acid derivatives include glutamine, histidine, methionine, asgparagine, glutamate, lysine, glycine, N,N-dimethylglycine (N, N-Dimethylglycine), threonine (Threonine), homoserine (Homoserine), tryptophan (Tryptophan) and citrulline (Citrulline) a composition characterized in that at least one selected from the group consisting of.
17. According to claim 16,

    The composition, characterized in that the lysophosphatidylcholine is at least one lysophosphatidylcholine selected from the group consisting of LPC (14:0), LPC (15:0) or LPC (20:3).
18. According to claim 16,

    The phosphatidylcholine is PC 32:2 (18:2/14:0), PC 34:3 (16:1/18:2), PC 36:1 (18:0/18:1), PC 36:3 ( 16:0/20:3), PC 36:6 (14:0/22:6) and PC 38:7 (16:1/22:6), characterized in that at least one phosphatidylcholine selected from the group consisting of composition
19. According to claim 16,

    The sphingomyelin is a group consisting of SM d34:1 (d18:1/16:0), SM d36:1 (d18:1/18:0) or SM d42:2 (d18:1/24:1) A composition characterized in that at least one sphingomyelin selected from
20. According to claim 16,

    The composition, characterized in that the triacylglycerol is TAG 58: 11 (22: 6 / 20: 5 / 16: 0).
21. According to claim 16,

    Wherein the glutamine, histidine, methionine, asparagine, glutamic acid, threonine, lysine, and tryptophan are L-forms.
22. According to claim 16,

    If the concentration of glutamine, histidine, methionine, asparagine, lysine, glycine, N, N-dimethylglycine, threonine, homoserine, tryptophan or citrulline is lower than that of upper lobe cavity type patients, severe non-tuberculous anti-acids A composition characterized in that it is determined as a fungus.
23. According to claim 16,

    When the concentration of glutamic acid is higher than that of upper lobe cavitary form patients , a composition characterized in that it is determined as a severe non-tuberculous mycobacteria.
24. According to claim 16,

    When the concentration of the lysophosphatidylcholine or triacylglycerol is lower than that of upper lobe cavity type patients, the composition characterized in that it is determined as severe non-tuberculous mycobacteria.
25. According to claim 19,

    A composition characterized in that when the concentration of the sphingomyelin is higher than that of upper lobe cavity type patients, it is determined as a severe non-tuberculous mycobacteria.
26. According to claim 18,

    The phosphatidylcholine PC 32:2 (18:2/14:0), PC 34:3 (16:1/18:2), PC 36:6 (14:0/22:6) or PC 38:7 (16 :1/22:6) composition characterized in that it is determined as a severe non-tuberculosis mycobacterium when the concentration is lower than that of upper lobe cavitary form patients.
27. According to claim 18,

    If the concentration of the phosphatidylcholine PC 36:1 (18:0/18:1) or PC 36:3 (16:0/20:3) is higher than that of upper lobe cavity type patients, severe non-tuberculosis A composition characterized in that it is determined as an acid-fast bacterium.
28. According to claim 16,

    The lipid metabolites, amino acids and amino acid derivatives are whole blood, leukocytes, peripheral blood mononuclear cells, leukocyte buffy coat, plasma, serum, sputum (sputum), tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, abdominal cavity peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid (pleural fluid), nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cells, cell extracts ( A composition characterized in that it is present in cell extract) and cerebrospinal fluid.
29. According to claim 16,

    The non-tuberculous acidophilus is Mycobacterium avium ( M. avium ), Mycobacterium absesus ( M. abscessus ), Mycobacterium flavescence ( M. flavescence ), Mycobacterium africanum ( M. africanum ), Mycobacterium bovis ( M. bovis ), Mycobacterium chelone ( M. chelonae ), Mycobacterium cellatum ( M. celatum ), Mycobacterium fortuitum ( M. fortuitum ), Mycobacterium gordonae ( M. gordonae ), Mycobacterium gastri ( M. gastri ), Mycobacterium hemophilum ( M. haemophilum ), Mycobacterium intracellurare ( M. intracellulare ), Mycobacterium Kansasii ( M. kansasii ), Mycobacterium malmoenseu ( M. malmoense ), Mycobacterium marinum ( M. marinum ), Mycobacterium suzulgai ( M. szulgai ) , Mycobacterium terae ( M. terrae ), Mycobacterium scrofulaceum ( M. scrofulaceum ), Mycobacterium Ulceranseu ( M. ulcerans ), Mycobacterium simiae ( M. simiae ) and A composition characterized in that it is selected from the group consisting of Mycobacterium xenopi ( M. xenopi ).
30. A method for providing information for predicting the severity of an infectious disease caused by non-tuberculous mycobacteria comprising the step of measuring one or more metabolites selected from the group consisting of lipid metabolites, amino acids and amino acid derivatives As,

    The lipid metabolite is at least one selected from the group consisting of Lysophosphatidylcholine, Phosphatidylcholine, Sphingomyeline and Triacylglycerol,

    The amino acids and amino acid derivatives include glutamine, histidine, methionine, asgparagine, glutamate, lysine, glycine, N,N-dimethylglycine (N, N-Dimethylglycine), Threonine (Threonine), Homoserine (Homoserine), Tryptophan (Tryptophan) and Citrulline (Citrulline) A method characterized in that it comprises as an active ingredient an agent for measuring one or more metabolites selected from the group consisting of .
31. 31. The method of claim 30,

    Wherein the step of measuring the concentration of the metabolite is performed using a quantitative device such as chromatography or mass spectrometry.
32. Lysophosphatidylcholine (LPC), phosphatidylcholine (PC), sphingomyelin (SM) and triacylglycerol (TAG), glutamine, histidine, Methionine, Asgparagine, Glutamate, Lysine, Glysine, N,N-Dimethylglycine, Threonine, Homoserine, Uses of Tryptophan and Citrulline.

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