Biomarker for predicting pneumonia

Abstract

To provide means for predicting pneumonia in a subject.SOLUTION: A method uses any one or more relative amounts selected from the following in a subject as an index for predicting pneumonia in the subject: (1) a relative amount of CCR4-CCR6+cell subpopulation in CD4+T cell population of a subject; (2) a relative amount of CTLA-4+cell subpopulation in CD4+CCR4+CCR6+CXCR3-T cell population of the subject; (3) a relative amount of the CTLA-4+cell subpopulation in regulatory T cell population of the subject; (4) a relative amount of CD27+cell subpopulation in CD8+T cell population of the subject; (5) a relative amount of CD127+cell subpopulation in the CD8+T cell population of the subject. The method includes the steps for determining a relative amount of the cell subpopulation in a sample derived from the subject. The relative amount is used as an index for predicting pneumonia in the subject.SELECTED DRAWING: None

Description

[Technical field]

[0001] The present invention relates to the field of pneumonia prediction, and more particularly to a method for predicting whether a subject will develop pneumonia based on the subject's T cell composition. [Background technology]

[0002] While most patients with respiratory infections have mild symptoms and do not require hospitalization, some develop severe pneumonia and require hospitalization for treatment. For example, most patients infected with SARS-CoV-2 recover naturally with mild symptoms without developing pneumonia. However, about 10% of patients develop pneumonia and hypoxemia. In about 3% of cases, a cytokine storm occurs, leading to severe disease.

[0003] Because pneumonia patients need to be given priority for treatment, there is a high need for a method to predict pneumonia. Summary of the Invention [Means for solving the problem]

[0004] In the case of pneumonia and severe diseases, it is believed that the immune response to destroy the virus is insufficient while the unfavorable immune response that causes organ damage is excessive, but almost nothing is known about the mechanism of action. In view of this situation, the present invention has found a marker for predicting pneumonia in a patient by evaluating the immune status of the patient. And, since the composition of a cell subpopulation in a sample obtained from a subject is used as an indicator for predicting pneumonia in the subject, it has been found that the composition of a specific cell subpopulation can be a new indicator for predicting pneumonia.

[0005] Thus, the present invention provides the following: (Item 1) A method for using a relative amount of one or more of the following in a subject as an index for predicting pneumonia in the subject, comprising: (1) CD4 count of the subject+ CCR4 in T cell populations - CCR6 + the relative abundance of cell subpopulations; (2) CD4 count of the subject + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + the relative abundance of cell subpopulations; (3) CTLA-4 in the subject's regulatory T cell population + the relative abundance of cell subpopulations; (4) CD8 of the subject + CD27 in T cell populations + the relative abundance of cell subpopulations; (5) CD8 of the subject + CD127 in T cell populations + the relative abundance of cell subpopulations; determining the relative abundance of said cell subpopulations in a sample from said subject; The relative amount is used as an index for predicting pneumonia in the subject. (Item 2) The method according to the above-mentioned item, wherein a comparison between the relative amount and a reference value is used as an index for predicting pneumonia in the subject. (Item 3) The method of any one of the preceding claims, wherein the prediction comprises a prediction of whether pneumonia will develop in the subject. (Item 4) The method of any one of the preceding items, wherein the relative amount being equal to or less than a reference value indicates a high likelihood that the subject will develop pneumonia, or the relative amount being equal to or greater than a reference value indicates a low likelihood that the subject will develop pneumonia. (Item 5) CCR4 - CCR6 + A subpopulation of cells further expressed CXCR3 + The method according to any one of the preceding claims, wherein the cell is a subpopulation. (Item 6) CCR4 - CCR6 +A subpopulation of cells further expressed CXCR3 - The method according to any one of the preceding claims, wherein the cell is a subpopulation. (Item 7) The CD8 + The method of any one of the preceding claims, wherein the T cell population is an effector memory T cell population. (Item 8) The CD8 + The T cell population is CD8 + CCR7 - CD45RA + The method according to any one of the preceding claims, wherein the effector memory T cell population. (Item 9) The method of any one of the preceding claims, wherein the pneumonia is caused by a respiratory infection. (Item 10) The method of any one of the preceding claims, wherein the respiratory infection comprises a coronavirus infection or an influenza virus infection. (Item 11) The method according to any one of the preceding items, wherein the coronavirus is an α-coronavirus, a β-coronavirus, a γ-coronavirus, or a δ-coronavirus. (Item 12) The method of any one of the preceding items, wherein the β-coronavirus comprises a virus selected from the group consisting of SARS-CoV-2, HCoV-OC43, HCoV-HKU1, SARS-CoV, Bat SL-CoV-WIV1, BtCoV-HKU4, BtCoV-HKU5, MERS-CoV, and BtCoV-HKU9. (Item 13) The method according to any one of the preceding claims, characterized in that the relative amount of the cells is measured using a peripheral blood sample. (Item 14) The method of any one of the preceding claims, wherein the subject is selected from the group consisting of subjects suffering from a virus and / or bacteria that causes pneumonia and subjects suspected of having pneumonia. (Item 15) 1. A kit for predicting pneumonia in a subject, comprising: (a) a detection agent for CD4, a detection agent for CCR4, and a detection agent for CCR6; (b) a detecting agent for CD4, a detecting agent for CCR4, a detecting agent for CCR6, a detecting agent for CXCR3, and a detecting agent for CTLA-4; (c) a detection agent for FOXP3 and a detection agent for CTLA-4; (d) a detection agent for CD8, and a detection agent for CD27; and (e) a detection agent for CD8 and a detection agent for CD127; and wherein the prediction is performed by using a relative amount of any one or more selected from the following as an index for predicting pneumonia in the subject: (1) CD4 count of the subject + CCR4 in T cell populations - CCR6 + the relative abundance of cell subpopulations; (2) CD4 count of the subject + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + the relative abundance of cell subpopulations; (3) CTLA-4 in the subject's regulatory T cell population + the relative abundance of cell subpopulations; (4) CD8 of the subject + CD27 in T cell populations + the relative abundance of cell subpopulations; (5) CD8 of the subject + CD127 in T cell populations + Relative abundance of cell subpopulations (Item 16) The kit according to any one of the preceding items, wherein a comparison of the relative amount with a reference value is used as an index for predicting pneumonia in the subject. (Item 17) The kit of any one of the preceding items, wherein the prediction includes a prediction of whether the subject will develop pneumonia. (Item 18) The kit of any one of the preceding claims, wherein the detection agent is an antibody.

[0006] It is contemplated that one or more of the above features may be provided in combinations other than those specifically stated. Still further embodiments and advantages of the present disclosure will be recognized by those skilled in the art upon reading and understanding the following detailed description, if necessary.

[0007] Furthermore, features and notable actions and effects of the present disclosure other than those described above will become apparent to those skilled in the art by referring to the following description of the preferred embodiments of the present invention and the drawings. [Brief description of the drawings]

[0008] [Figure 1-1] Figure 1A shows the results of unsupervised clustering of CD4+ T cells in one embodiment of the present invention. Figure 1B shows the results of clustering in Figure 1A and the results of annotation of each marker. Figure 1C is a graph showing an analysis of clusters characteristic of pneumonia patients and non-pneumonia patients for clustering of CD4+ T cells in one embodiment of the present invention. [Figure 1-2] Fig. 1D is a graph showing the results of comparing each cell subpopulation in CD4+ T cells between healthy subjects, pneumonia patients, and non-pneumonia patients in one embodiment of the present invention. Fig. 1E is a graph showing the results of ROC analysis of Th1 / 17 cell subpopulation in one embodiment of the present invention. [Figure 1-3] FIG. 1F is a graph showing the results of comparing CTLA-4 cell subpopulations in each cell population among healthy subjects, pneumonia patients, and non-pneumonia patients in one embodiment of the present invention. [Figure 2-1]Figure 2A shows the results of unsupervised clustering of CD8+ T cells in one embodiment of the present invention. Figure 2B shows the results of clustering in Figure 2A and the results of annotation of each marker. Figure 2C is a graph showing an analysis of clusters characteristic of pneumonia patients and non-pneumonia patients for clustering of CD8+ T cells in one embodiment of the present invention. [Figure 2-2] Figure 2D is a graph showing the results of comparing each cell subpopulation in CD8+ T cells among healthy subjects, pneumonia patients, and non-pneumonia patients in one embodiment of the present invention. Figure 2E is a graph showing the results of analyzing the correlation between each CD8+ T cell ratio and CD4+ T cell cluster. [Figure 2-3] Figure 2F is a graph showing the results of comparing CD27 and CD127 cell subpopulations in each CD8+ T cell cluster between healthy subjects, pneumonia patients, and non-pneumonia patients. Figures 2G and H are graphs showing the results of analyzing the correlation between each CD8+ T cell cluster and CD27 or CD127 cell subpopulations. [Figure 3-1] FIG. 3A shows the results of an analysis of changes over time in CD8+ T cells in pneumonia patients and non-pneumonia patients in one embodiment of the present invention. [Figure 3-2] Figure 3B shows the results of an analysis of changes in CD8+ T cells over time at the time of admission and one week after admission in one embodiment of the present invention. Figure 3C shows a graph showing the results of a comparison of each cell subpopulation in a CD8+ T cell population among healthy subjects, pneumonia patients, and non-pneumonia patients in one embodiment of the present invention. [Figure 3-3] 3D and E show the results of an analysis of the time course of changes in CD27 or CD127 cell subpopulations in each CD8+ T cell cluster in one embodiment of the present invention. [Figure 4-1] Figure 4A shows the results of analyzing the time course of each CD4+ T cell cluster in pneumonia patients and non-pneumonia patients in one embodiment of the present invention. Figure 4B shows the results of analyzing the time course of Th17 cell subpopulation in pneumonia patients and non-pneumonia patients in one embodiment of the present invention. [Figure 4-2]Figure 4C is a graph showing the results of comparing each cell subpopulation in CD4+ T cells among healthy subjects, pneumonia patients, and non-pneumonia patients in one embodiment of the present invention. Figure 4D is a graph showing the analysis of clusters characteristic of pneumonia patients and non-pneumonia patients in one embodiment of the present invention. [Figure 4-3] Figure 4E is a graph showing the results of comparing CTLA-4 cell subpopulations in Th17 and Treg cell populations between pneumonia and non-pneumonia patients in one embodiment of the present invention. Figure 4F is a graph showing the results of analyzing the correlation between CD8+ T cell clusters and CD4+ T cell clusters in one embodiment of the present invention. [Diagram 5] FIG. 5 is a schematic diagram showing the gating strategy for mass cytometry analysis in one embodiment of the present invention. [Figure 6] FIG. 6 is a graph showing the results of comparing Th7R (CCR4-CCR6+) T cell clusters in healthy subjects, non-pneumonia patients, and pneumonia patients in one embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The present disclosure will be described below while showing the best mode. Throughout this specification, the expression of the singular form should be understood to include the concept of the plural form, unless otherwise specified. Therefore, the singular article (for example, in the case of English, "a", "an", "the", etc.) should be understood to include the concept of the plural form, unless otherwise specified. In addition, it should be understood that the terms used in this specification are used in the sense commonly used in the field, unless otherwise specified. Therefore, unless otherwise defined, all technical terms and scientific and technical terms used in this specification have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. In case of conflict, the present specification (including definitions) will take precedence.

[0010] The following provides definitions of terms particularly used in this specification and / or explains basic technical content as appropriate.

[0011] As used herein, "about" means ±10% of the preceding numerical value.

[0012] As used herein, the term "biomarker" refers to a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathological processes, or pharmacological responses to a therapeutic intervention.

[0013] As used herein, the term "respiratory infection" refers to a disease caused by a pathogen infecting respiratory organs such as the nasal cavity, pharynx, trachea, bronchi, and alveoli.

[0014] As used herein, the term "coronavirus" refers to a single-stranded RNA virus that belongs to the Coronaviridae family and is involved in human infections, and in particular, refers to a virus that utilizes the binding of the S protein (more specifically, S1) on its envelope with ACE2 on the human cell membrane when invading human cells. Examples of such coronaviruses include α-coronavirus, β-coronavirus, γ-coronavirus, and δ-coronavirus, and examples of β-coronaviruses include, but are not limited to, SARS-CoV-2, HCoV-OC43, HCoV-HKU1, SARS-CoV, Bat SL-CoV-WIV1, BtCoV-HKU4, BtCoV-HKU5, MERS-CoV, and BtCoV-HKU9. Preferably, in the present invention, the "coronavirus" refers to the novel coronavirus / SARS-CoV-2.

[0015] The novel coronavirus / SARS-CoV-2 is the virus that infects humans and causes COVID-19. The main symptoms of COVID-19 include fever, respiratory symptoms (cough, sore throat, runny nose, nasal congestion, etc.), pneumonia, headache, fatigue, loss of smell, and loss of taste. While most infected patients (approximately 80%) are asymptomatic or have mild symptoms, some patients (e.g., elderly patients, patients with underlying diseases (cardiovascular disease, diabetes, chronic respiratory disease, chronic kidney disease, etc.), patients with high blood pressure, obese patients, etc.) may develop severe symptoms or die.

[0016] The genome sequence of the novel coronavirus / SARS-CoV-2 can be confirmed in GenBank at the website of the National Center for Biotechnology Information, National Library of Medicine. For example, the genome sequence of the novel coronavirus / SARS-CoV-2 is registered in GenBank under the accession number NC_045512.2, etc. (but not limited to these). Those skilled in the art can identify or distinguish the novel coronavirus / SARS-CoV-2 from other viruses based on the genome sequence.

[0017] Coronaviruses exist as RNA viruses wrapped in an envelope. Their diameter is about 80-120 nm, and their genetic material is the largest among all RNA viruses. There are three glycoproteins on the surface of the virus particle: S, Spike Protein, receptor binding site, cell lysis and antigen; E, Envelope Protein, small, protein that binds to cell membrane; and M, Membrane Protein, nutrient transporter, assembles new virus budding and viral envelope formation. There is a small variety of hemoglobin glycoprotein (HE protein, Haemaglutinin Hemagglutinin-esterase). The virus mainly enters the host cell through the binding of the Spike protein (S protein) to the host cell receptor, and determines the tissue or host of the virus. Both the N-terminal domain (S1-NTD) and the C-terminal domain (S1-CTD) of the coronavirus S protein S1 subunit can be receptor-binding domains (RBDs). S1-NTD is thought to bind to sugar receptors, and S1-CTD is thought to bind to protein receptors.

[0018] In this specification, the term "influenza virus" refers to an enveloped single-stranded negative-strand RNA virus belonging to the family Orthomyxoviridae. It has a particle size of about 100 nm in diameter, and is divided into types A, B, and C based on the antigenicity of the internal protein. Influenza, which is widespread around the world, is mainly caused by influenza type A viruses, which have two types of envelope glycoproteins, hemagglutinin (HA) and neuraminidase (NA), and are classified into 16 subtypes of HA (H1 to H16 types) and 9 subtypes of NA (N1 to N9 types) based on the difference in antigenicity, and are classified into subtypes from H1N1 to H16N9 based on the combination of these. For example, there is H1N1, known as "Soviet type A," H3N2, H1N2, and H2N2, known as "Hong Kong type A," and H5N1, which has become famous as a highly pathogenic avian influenza. The subtypes of influenza A and B viruses are not particularly limited, and may be subtypes that have been isolated so far or subtypes that will be isolated in the future.

[0019] As used herein, a "sample" may be any, including but not limited to serum, plasma, peripheral blood, blood, urine, saliva, etc. In one embodiment, a peripheral blood sample is used. Thus, in one embodiment of the present invention, the method of the present invention is carried out using a peripheral blood sample taken from a subject.

[0020] As used herein, the term "symptom" refers to a deviation from normal function or sensation in a patient, reflecting the presence of an abnormal condition or disease, and includes subjective and objective symptoms. In the present invention, symptoms can be expressed in terms of the degree of symptoms (or severity), and may be classified into, for example, severe, moderate (which may be divided into levels, for example, moderate (I), moderate (II), mild, asymptomatic (subclinical), etc.), and expressed as such.

[0021] As used herein, "aggravation" of symptoms of a respiratory infection refers to the development of pneumonia symptoms, particularly pneumonia requiring oxygen inhalation, or the need for intensive care including artificial respiration.

[0022] In this specification, "pneumonia" refers to a general term for pulmonary inflammatory diseases, which are mainly caused by infection with pathogens such as bacteria and viruses. Pneumonia is classified into a detailed category according to the cause of onset, including atypical pneumonia such as bacterial pneumonia, viral pneumonia, and mycoplasma pneumonia, and pneumonia caused by causes other than bacteria and viruses, such as aspiration pneumonia, hypersensitivity pneumonia, and eosinophilic pneumonia. Pneumonia can be diagnosed by physical examination, chest X-ray examination, chest CT examination, blood test, etc.

[0023] As used herein, "prediction of pneumonia" refers to prediction of the onset, symptoms, condition, and / or severity of pneumonia.

[0024] As used herein, "correlate" refers to two events having a statistically significant correlation. For example, "a relative amount of B correlated with A" refers to the occurrence of event A, whereby the relative amount of B is affected (e.g., increased or decreased) in a statistically significant manner.

[0025] As used herein, the term "cell subpopulation" refers to any collection of cells that share some common characteristic in a cell population that contains cells with diverse characteristics. If a specific name is known in the art, such a term can be used to refer to a specific cell subpopulation, or any property (e.g., expression of a cell surface marker) can be described to refer to a specific cell subpopulation.

[0026] As used herein, the term "relative amount" with respect to cells is used interchangeably with "proportion." Typically, the terms "relative amount" and "proportion" refer to the amount of a particular cell population (e.g., CD4 + The number of cells forming a desired cell subpopulation (e.g., CCR4 T cell population) - CCR6 + The term "cell subpopulation" refers to the number of cells that form a pluripotent cell population.

[0027] As used herein, the term "relative value" refers to a value calculated for a given value in comparison with another value.

[0028] As used herein, the term "detection agent" refers broadly to any agent capable of detecting a substance of interest (eg, a cell surface marker, etc.).

[0029] As used herein, the "amount" of a cell subpopulation includes the absolute number of a cell and the relative amount as a percentage of a cell population.

[0030] As used herein, "reference" or "reference value" refers to a quantity to be compared for determining the increase or decrease of the amount of a marker described herein.When determining the increase or decrease of a certain amount before and after a certain treatment (e.g., cancer immunotherapy), for example, the "reference value" includes the amount before the treatment.The reference or reference value can also be the amount or relative amount of a certain cell known to show a certain quantity (e.g., progression-free survival time).

[0031] In this specification, "flow cytometry" refers to a technique for measuring the number of cells, solids, and other biological particles suspended in a liquid, as well as the physical, chemical, and biological properties of each particle. The results of flow cytometry can typically be expressed as a dot plot with FSC on the X-axis and SSC on the Y-axis. Each cell is represented by a dot in the diagram, and their positions are determined by the relative values ​​of FSC and SSC. Lymphocytes, which are relatively small in size and have a simple internal structure, are displayed in the lower left, granulocytes, which are large in size and have granules inside, are displayed in the upper right, and monocytes, which are large in size but have a simple internal structure, are displayed as separate groups between lymphocytes and granulocytes. The results of flow cytometry can also be displayed as histograms or dot plots.

[0032] As used herein, the term "effector cells" refers to immune cells that have differentiated from naive cells that have not been stimulated by antigens and have acquired the function of actually acting in immunity. In particular, three types of human helper T cells are known: Th1, Th2, and Th17. Each can release characteristic cytokines such as interferon gamma (IFNγ) and interleukin 17 (IL-17). In addition, there are transcription factors characteristic of each Th subset, such as Th1 expressing T-bet and Th2 expressing GATA-3, but there are also cells that express both T-bet and GATA-3, and such cells are expressed as "Th1 / Th2" or "Th1 / 2". As used herein, "Th1 / Th17" or "Th1 / 17" expresses both T-bet, which is characteristic of Th1, and RORγt, which is characteristic of Th17.

[0033] Effector cells such as Th1, Th2, and Th17 can also be classified according to the type of chemokine receptor (CCR) they express. For example, Th1 expresses CXCR3, Th2 expresses CCR4, and Th17 expresses CCR4 and CCR6. The classification of Th subsets can be shown, for example, as shown in Fig. 1 of Annual Review of Immunology, Vol. 34:317-334 Heterogeneity of Human CD4+ T Cells Against Microbes. In this specification, "Th1 / Th17" or "Th1 / 17" expresses CXCR3 characteristic of Th1 and CCR6, which is one of two CCRs characteristic of Th17, CCR4 and CCR6. In this specification, "CCR6 SP (single positive)" is a Th subset that expresses only CCR6 among CCR4, CCR6, and CXCR3. In addition, as used herein, "TP (triple positive)" refers to a type that has not been classified in the Th type classification by CCR, and is a Th subset that expresses CCR4, CCR6, and CXCR3. In addition, as used herein, "Th7R" refers to a cell subpopulation that includes "Th1 / 17" and "CCR6 SP", and CCR4 - CCR6+ It is expressed by:

[0034] (Preferred embodiment) Preferred embodiments of the present disclosure are described below. The embodiments provided below are provided for a better understanding of the present disclosure, and it is understood that the scope of the present disclosure should not be limited to the following description. Therefore, it is clear that a person skilled in the art can make appropriate modifications within the scope of the present disclosure in light of the description in this specification. It is also understood that the following embodiments of the present disclosure can be used alone or in combination.

[0035] (Prediction of symptoms of respiratory infections) According to the present invention, there is provided a method for predicting pneumonia in a subject, the method comprising the steps of: (1) determining the relative amount of one or more of the following in a subject as an index for predicting pneumonia in the subject; + CCR4 in T cell populations - CCR6 + (2) the relative abundance of cell subpopulations; + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + (3) the relative abundance of cell subpopulations; and (4) CTLA-4 in the regulatory T cell population of the subject. + the relative abundance of cell subpopulations; (4) CD8 of the subject + CD27 in T cell populations + (5) the relative abundance of cell subpopulations; + CD127 in T cell populations + Relative amounts of cell subpopulations; determining the relative amounts of said cell subpopulations in a sample from said subject, and using said relative amounts as an indicator for predicting pneumonia in said subject.

[0036] In one embodiment of the present invention, pneumonia is a general term for pulmonary inflammatory diseases, which are mainly caused by infection with pathogens such as bacteria and viruses, or may develop as a result of infection with a respiratory tract infection. Respiratory tract infection refers to a disease caused by infection with a pathogen in respiratory organs such as the nasal cavity, pharynx, trachea, bronchi, and alveoli. Pathogens that cause pneumonia are not particularly limited, and examples thereof include viruses, bacteria, fungi, and parasites. Viruses that cause pneumonia are not particularly limited, and examples thereof include viruses (including DNA viruses and RNA viruses) that infect animals (e.g., humans), and include rhinoviruses, respiratory syncytial viruses, parainfluenza viruses, adenoviruses, coronaviruses, and influenza viruses, which are viruses that infect humans and cause cold-like symptoms. Examples of bacteria include Mycoplasma pneumoniae and Chlamydophila pneumoniae. Examples of coronaviruses are not particularly limited, and examples thereof include α-coronavirus, β-coronavirus, γ-coronavirus, and δ-coronavirus. Examples of β-coronaviruses include SARS-CoV-2, HCoV-OC43, HCoV-HKU1, SARS-CoV, Bat SL-CoV-WIV1, BtCoV-HKU4, BtCoV-HKU5, MERS-CoV, and BtCoV-HKU9. The so-called novel coronavirus (2019-nCoV, SARS-CoV-2) that emerged in 2019 is classified as the same betacoronavirus genus as SARS coronavirus, and the genes of the novel coronavirus are highly homologous (about 80%) to those of SARS coronavirus. Furthermore, it has been reported that the novel coronavirus uses a receptor (ACE1 or ACE2) similar to that of SARS coronavirus to adsorb and invade human cells. It has also been reported that differences in ACE1 or ACE2 subtypes result in differences in infectivity. The clinical symptoms of the novel coronavirus range from flu-like symptoms such as headache, high fever, fatigue, and cough, to pneumonia with dyspnea as the main complaint in severe cases. Symptomatic treatments such as reducing fever and respiratory support are being implemented, and efforts are being made to repurpose or develop new vaccines, antiviral drugs (favipiravir, remdesivir, etc.), and immunotherapy agents.Tests are being developed to measure viral genes, such as PCR and other rapid diagnostics. The genetic sequence of the new coronavirus is close to that of SARS coronavirus and also has homology to SARS-like coronaviruses derived from bats, which suggests that bats are probably the reservoir of the virus that is the origin of this new coronavirus. For example, the WHO-China Joint Mission Report on Novel Coronavirus Disease (COVID-19) showed that the virus has typical characteristics of the coronavirus family and belongs to the betacoronavirus 2B lineage, and a comparison of the complete genome sequence of the COVID-19 virus with other available genome sequences of betacoronaviruses showed that the closest relationship is the bat SARS-like coronavirus strain BatCov RaTG13, with 96% identity. Virus isolation has been performed in various cell lines, such as human airway epithelial cells, Vero E6, and Huh-7, and these samples are also available.

[0037] In one embodiment of the present invention, the pneumonia may be caused by a respiratory infection. The respiratory infection may include a coronavirus infection or an influenza virus infection. As described above, all of these viruses are viruses that infect the respiratory tract, such as the nasal cavity, pharynx, trachea, and bronchi, and are RNA viruses that exhibit cold-like symptoms. Without being bound by theory, it is believed that the mechanism of viral pneumonia onset is due to an immune response occurring around virus-infected cells, rather than epithelial cell damage caused by the virus itself. Therefore, in both coronavirus infection and influenza virus infection, the mechanism of pneumonia onset is thought to be increased vascular permeability caused by excessive cytokines resulting from an immune response. Therefore, without being bound by theory, it can be said that pneumonia caused by many viral infections occurs by a similar mechanism, and the excessive activation of Th17 involved in the mechanism of viral pneumonia onset and the decreased function of Th7R involved in virus expulsion can predict a high risk of pneumonia. In a preferred embodiment, the pneumonia in the present invention may be caused by a coronavirus infection. In a preferred embodiment, the pneumonia in the present invention may be caused by an influenza virus infection.

[0038] In one embodiment of the present invention, the subject includes a subject infected with a virus and / or bacteria that causes pneumonia and a subject suspected of having pneumonia. A subject infected with a virus and / or bacteria that causes pneumonia refers to a person whose infection has been confirmed by detection of a pathogen such as a virus and / or bacteria, and preferably refers to a person who has not yet developed pneumonia. A subject suspected of having pneumonia includes, for example, a person who has cold symptoms such as fever, cough, runny nose, and sore throat, and / or symptoms specific to a specific respiratory infection such as shortness of breath, shortness of breath on exertion, and abnormal taste and smell, a person who has come into contact with a patient with a respiratory infection, and a person who is suspected of having come into contact with a patient with a respiratory infection. Contact with a patient with a respiratory infection refers to, for example, conversation with the patient at a distance of about 1 m or less, staying in an enclosed space where the patient is present, being exposed to droplets of the patient's saliva, cough, etc.

[0039] In one embodiment, the sample is not particularly limited as long as it is collected from a subject and may contain the biomarker of the present invention. Examples of such samples include blood (peripheral blood) samples, cerebrospinal fluid, sputum, bronchoalveolar lavage fluid, nasopharyngeal swabs, lymph, urine, stool, saliva, etc. Among these, blood samples are preferred. Examples of blood samples include whole blood, peripheral blood, plasma, and serum, with peripheral blood being particularly preferred.

[0040] When the sample contains insoluble impurities such as cells, the impurities may be removed from the sample by known means such as centrifugation or filtration. The sample may also be diluted with an appropriate aqueous medium as necessary. Such an aqueous medium is not particularly limited as long as it does not interfere with the measurement of the present invention, and examples thereof include water, physiological saline, and buffer solutions. The buffer solution is not particularly limited as long as it has a buffering effect at a pH near neutral (e.g., a pH of 6 to 8). Examples of such buffer solutions include Good's buffers such as HEPES, MES, Tris, and PIPES, and phosphate buffered saline (PBS).

[0041] In one embodiment of the present invention, the "symptoms" of respiratory infection include a state in which normal function or sensation in a subject deviates due to the presence of a respiratory infection, such as pneumonia, and may be subjective or objective. In one embodiment, the prediction by the method of the present invention may include whether or not a subject develops pneumonia. The symptoms of respiratory infection may be expressed by whether or not pneumonia has developed, or by the degree of symptoms (or severity). The symptoms of respiratory infection may be expressed by classifying them into, for example, severe, moderate (may be divided into levels, such as moderate (I), moderate (II), mild, asymptomatic (subclinical)), etc.).

[0042] The respiratory infection may progress to a more severe form of pneumonia, and in one embodiment, the respiratory infection may progress to a more severe form of pneumonia, particularly pneumonia requiring oxygen or requiring intensive care, including mechanical ventilation.

[0043] In one embodiment of the present invention, the following indexes are used to predict pneumonia in a subject: (1) CD4 + CCR4 in T cell populations - CCR6 + (2) the relative abundance of cell subpopulations; + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + (3) the relative abundance of cell subpopulations; and (4) CTLA-4 in the regulatory T cell population of the subject. + (4) the relative abundance of cell subpopulations; and (5) the subject's CD8 + CD27 in T cell populations + (5) the relative abundance of cell subpopulations; + CD127 in T cell populations + Any one or more relative amounts selected from the relative amounts of cell subpopulations can be used.

[0044] In one embodiment of the invention, a comparison of these relative amounts to a reference value can be used as an indicator of prognosis of pneumonia in a subject, where the relative amounts less than or equal to the reference value can indicate a high likelihood of pneumonia developing in the subject, or the relative amounts greater than or equal to the reference value can indicate a low likelihood of pneumonia developing in the subject.

[0045] Most patients infected with SARS-CoV-2 recover spontaneously with mild symptoms without developing pneumonia. However, about 10% of patients develop pneumonia and hypoxemia. In about 3% of cases, a cytokine storm occurs, leading to severe disease. In cases of pneumonia and severe disease, it is believed that an insufficient immune response to destroy the virus is accompanied by an adverse excessive immune response that leads to organ damage, but little is known about the mechanism of action.

[0046] Known factors that contribute to the development of pneumonia include age, obesity, diabetes, and hypertension. In contrast, steroid therapy is known to be effective against pneumonia, and anti-IL-6 antibodies and other treatments that suppress the excessive immune response are known to be effective against cytokine storm. Without being bound by theory, it is believed that in cases of pneumonia and severe disease, the immune response is insufficient to destroy the virus while the unfavorable immune response that causes organ damage is excessive. Genetic abnormalities of TLR3 and TLR7, which are involved in type I IFN production, and the presence of anti-IFN antibodies have been reported as possible causes of such immune conditions, but many aspects remain unknown.

[0047] The immune response to viral infection is antigen-specific CD8 + It is known to be the priming of T cells, which leads to the destruction of infected cells. + T cell help is determined by virus-specific CD8 + It is essential for T cell priming. Without being bound by theory, CD4 + T cell help is CD8 + It is believed to be necessary for dendritic cell-mediated license to kill by T cells to destroy infected cells at the site of infection. + When T cell help is insufficient and the virus persists at high levels, T cells become exhausted and CD8 + T cell function is lost. Thus, CD4 + T cells and CD8 + Together with T cells, they must destroy virus-infected cells, which are the source of viral replication.+ When T cells are primed, they primarily produce IFNγ, a helper CD4 + Th cells are polarized into Th1 cells, Th17 cells that produce IL-17, and Th2 cells that produce IL-5. Th cell polarization is mediated by the expression of CD8 as an effector cell to respond to intracellular parasitic microorganisms such as viruses. + It is believed that Th cells respond to infectious microorganisms for which they are specific, such as Th1, which uses T cells, Th2, which uses eosinophils to respond to protozoa, and Th17, which uses neutrophils to respond to bacteria and fungi. If such polarization does not function properly, inappropriate effector cells may be activated, which not only delays the eradication of infectious microorganisms but also causes collateral damage to organs. Th17, which has high inflammation-inducing activity, has been reported to be increased in COVID-19 pneumonia and cytokine storm and is involved in organ damage.

[0048] In the present invention, as shown in the Examples, CD4 + T cells and CD8 + We analyzed the differentiation and activation / exhaustion status of T cells and found differences in the T cell immune status between COVID-19 pneumonia cases and non-pneumonia cases. Specifically, we aimed to clarify the difference in the host immune status between patients who develop pneumonia and those who do not, and used mass cytometry to analyze T cells that destroy virus-infected cells, which are the origin of viral replication. As a result, we found that COVID-19 pneumonia patients have high levels of helper CD4 + They have Th1 cells and follicular helper CD4 counts comparable to those in non-pneumonia patients. + showed a significantly lower Tfh T cell (Tfh) rate but a significantly lower Th1 / 17CD4 + Effector CD8 correlated with T cell ratio and Th1 / 17 + They showed lower expression of CD27 and CD127 on T cells. Pneumonia patients also showed significantly lower expression of CTLA-4 on Th17 and Treg than non-pneumonia patients, suggesting that Th17 is more likely to be activated and Treg function is suppressed. This finding supports the conclusion that pneumonia patients have reduced Th1 / 17 and effector CD8+ These results suggest that Th17-type inflammation, which reduces T cell survival and results in reduced antiviral clearance, contributes to the development of pneumonia. These mechanisms are promising therapeutic targets for preventing severe disease in virus-infected hosts.

[0049] In one embodiment, a sample for fractionation and separation of T cells can be appropriately collected from a subject by a conventional method. For example, the sample can be collected from the subject's peripheral blood, bone marrow, tumor tissue, hematopoietic tissue, spleen, normal tissue, lymph, etc. Collection of a sample from peripheral blood can be advantageous because it is non-invasive and simple.

[0050] The composition of T cells in a sample of a subject can be measured by a person skilled in the art using a conventional method. Usually, the number of cells positive for a marker (e.g., CD4) that defines a target cell subpopulation in a sample can be measured using flow cytometry or the like. The composition of a cell population is generally measured using flow cytometry, but may also be measured using immunostaining of a sample containing cells, a method using an antibody array, protein expression analysis in a sample containing cells (e.g., Western blot, mass spectrometry, HPLC, etc.), mRNA expression analysis in a sample containing cells (e.g., microarray, next-generation sequencing, etc.), etc.

[0051] CCR6 + CCR4 - T cell subpopulations and CXCR3 + CCR6 + CCR4 - T cell subpopulations and CXCR3 - CCR6 + CCR4 - T cell subpopulations and CTLA-4 + Cell subpopulations and CD27 + Cell subpopulations and CD127 + To count the number of cells in each cell subpopulation, the number of cells other than the subpopulation may be determined by experimentally removing the cells other than the subpopulation from the total cells. For example, CD4 +Cells corresponding to the desired T cell subpopulation may be isolated from peripheral blood without using a specific antibody, such as the Effector Memory T cell Isolation Kit, Human (Militenyi Biotech). For example, CD4 + Using the Effector Memory T cell Isolation Kit, Human (Militenyi Biotech), CD4 cells can be isolated from peripheral blood without using CD4 and CD62L antibodies. + CD62L low Cells representing T cell subpopulations can be isolated. Total viable cell counts can be recorded, and the number of cells obtained using this kit can be counted and recorded. CD4 + CD25 + Using the Regulatory T cell isolation kit, human (Militenyi Biotech), CD4 + CD25 + CD4 + Foxp3 + CD25 + The number of cells corresponding to T cell subpopulations can be determined. FoxP3 is localized in the nucleus of cells, which has the advantage of eliminating the step of staining molecules in the nucleus. Similar kits are also available, such as CD4 + CD25 + Also selectable are CD127dim / -Regulatory T cell isolation kit, human (Militenyi Biotech) and CD25+CD49d-Regulatory T cell isolation kit, human (Militenyi Biotech). In one embodiment of the present invention, any kit can be used as long as it can measure the number of cells of each of the target T cell subpopulations.

[0052] It is also possible to use no antibodies. Antibodies can specifically recognize and bind to molecules expressed in individual cells, and when the antibodies bind to molecules expressed on the cell surface or inside the cell, they are colored to detect the number of colored cells. Here, the molecules expressed on the cell surface or inside the cell are proteins, so when the protein is expressed, the mRNA that codes for it is also present inside the cell. In other words, it is sufficient to examine the mRNA in each cell and check for the presence or absence of the mRNA that codes for the protein molecule of interest. This is made possible by single-cell gene expression analysis, that is, mRNA analysis at the single-cell level. Examples of gene expression analysis of single cells include: 1) next-generation sequencing using Quartz-Seq, 2) isolating cells using the Standard Biotools C1 System or ICELL8 Single-Cell System and preparing libraries using SMART-Seq v4, 3) separating cells using a cell sorter and measuring by quantitative PCR using the Ambion Single Cell-to-CT kit, and 4) CyTOF SYSTEM (Helios) (Standard Biotools).

[0053] That is, blood is collected, the number of live cells is counted, and the cells are separated using a cell sorter or the like. For each separated cell, the expression level of a specific gene can be measured using a quantitative PCR device, for example, using the Ambion Single Cell-to-CT kit. Based on the results, it can be determined whether each cell expresses CXCR3 + CCR6 + CCR4 - T cell subpopulations and CXCR3 - CCR6 + CCR4 -It is also possible to examine which T cell subpopulations the cells belong to and count the number of cells belonging to each subpopulation. Candidates for genes to be examined for expression include, but are not limited to, αβTCR, CD3, CD4, CD25, CTLA4, GITR, FoxP3, STAT5, FoxO1, FoxO3, IL-10, TGFbeta, IL-35, SMAD2, SMAD3, SMAD4, CD62L, CD44, IL-7R (CD127), IL-15R, CCR7, BLIMP1, etc., and can be appropriately changed depending on the target cell subpopulation.

[0054] In the present invention, the measurement of the proportion of a cell subpopulation or comparison with a reference value or threshold value may be performed using a standard sample having a specified signal. The amount or proportion of a cell subpopulation in a sample can be measured by comparing the signal between a standard (e.g., particles attached with a fluorescent dye) prepared to generate a fluorescent signal corresponding to a predetermined cell subpopulation and a sample containing a cell population, and comparing with the standard. In addition, the presence or absence or amount of the marker of the present invention in the T cell composition in a sample can be determined by comparing the signal between a standard (e.g., particles attached with a fluorescent dye) prepared to generate a fluorescent signal corresponding to a predetermined reference value or threshold and a sample containing a cell population, and comparing with the standard.

[0055] In the present invention, when determining whether a particular marker is high (high expression) or low (low expression), a person skilled in the art can use classification criteria for expression intensity commonly used in the art. For example, for CD62L, the signal intensity corresponding to the 10E2 signal when a PE-labeled anti-human CD62L antibody is used as the boundary, low and CD62L high It is possible to clearly separate the above (WO2018 / 147291).

[0056] In one embodiment of the present invention, one skilled in the art can appropriately identify the surface markers of the indicated cells to fractionate or count the cells.

[0057] CD4 T cells are known to change into several differentiation states as effector cells. There are Th1, which mainly produces IFNγ and is strongly involved in cellular immunity, Th2, which mainly produces IL-4 and IL-5 and is involved in allergies, and Th17, which is known to be involved in autoimmune diseases and produces IL-17. Each differentiated CD4 T cell is known to express characteristic chemokine receptors (CCRs), and Th types can be classified according to the type of CCR expressed. The Th differentiation of human CD4 T cells is known to be more complex than that of mice, and can be classified, for example, as shown in Fig. 1 of Annual Review of Immunology, Vol. 34:317-334 Heterogeneity of Human CD4+ T Cells Against Microbes.

[0058] In one embodiment of the present invention, CCR4 - CCR6 + In addition to the cell subpopulations, CXCR3 + It is also possible to use a subpopulation of cells. Such a subpopulation of cells may be CCR4 - CCR6 + CXCR3 + When classified by Th type, it is classified as Th1 / 17.

[0059] In one embodiment of the present invention, CCR4 - CCR6 + In addition to the cell subpopulations, CXCR3 - It is also possible to use a subpopulation of cells. Such a subpopulation of cells may be CCR4 - CCR6 + CXCR3 - When classified by Th type, it is classified as CCR6 SP (single positive).

[0060] In yet another embodiment of the present invention, CCR4 - CCR6 + In addition to the cell subpopulations, we also identified FoxP3 -It is also possible to use a subpopulation of cells. Such a subpopulation of cells may be CCR4 - CCR6 + FoxP3 - When classified by Th type, it is a combination of Th1 / 17 and CCR6 SP (Th7R cell cluster).

[0061] In yet another embodiment of the present invention, CCR4 - CCR6 + In addition to the cell subpopulations, CTLA-4 + It is also possible to use subpopulations of cells.

[0062] In yet another embodiment of the present invention, CCR4 - CCR6 + In addition to the cell subpopulation, CD62L low A subpopulation of cells may also be used. - CCR6 + In addition to the cell subpopulations, CD45RA - It is also possible to use subpopulations of cells.

[0063] In yet another embodiment of the present invention, CD8 + The T cell population may be an effector memory (EM) T cell population. + The T cell population is CD8 + CCR7 - CD45RA + It may be a population of effector memory T cells. Such a subpopulation of cells is referred to as an EMRA cell population.

[0064] In the present invention, as described above, CD62L low CD4 + CD3 + By further classifying T cells into Th clusters by CCR type and analyzing the Th clusters that correlate most strongly with pneumonia, new biomarkers were obtained. Elimination of infected cells that enable viral replication is essential for the cure of respiratory infections such as pneumonia. CD4 + T cells are CD8 +T cell priming and clonal expansion, as well as migration from the circulation to the site of infection and CD8 + It helps provide T cells with a license to kill at the site of infection. + T cells play multiple roles in supporting antiviral immunity. As shown in the examples of the present invention, by analyzing peripheral blood T cells from patients infected with SARS-CoV-2, we found that CD4 T cells were significantly associated with pneumonia in patients who were infected but did not develop pneumonia, and those who developed COVID-19 pneumonia. + Significant differences in T cell immunity have been found, and Th1 / 17 cells are the most common T cell type, with effector CD8 T cells required for survival. + In non-pneumonia patients, expression of CD27 and CD127 on T cells was relatively maintained. In contrast, pneumonia patients showed terminally differentiated EMRA CD8 T cells that lost CD27 and CD127 expression along with loss of Th1 / 17. + These results suggest that patients with COVID-19 pneumonia had more CD8 T cells with high cell killing activity. + This is consistent with previous reports showing improved T cell proportions.

[0065] SARS-CoV-2 membrane antigen-specific CD4 + T cells and nucleocapsid antigen-specific CD4 + It has been demonstrated that T cells are biased toward differentiation into Th1 and Th1 / 17. Therefore, without being bound by theory, it can be said that Th1 and Th1 / 17 contribute to the elimination of infected cells. In the present invention, Th1 and Th1 / 17 are CD8 + We found that Th1 cells positively correlated with EMRA and negatively correlated with CD27 expression. Effector CD8 + T cells are CD27 + CD28 + From the state of CD27 + CD28 - and finally differentiate into CD27 - CD28 -It has been reported that Th1 differentiates into a CD8+ state, acquires cell killing function but loses the ability to maintain survival. Thus, without being bound by theory, Th1 differentiates into a CD8+ state that has high cell killing activity and reduced survival. + Th1 / 17 promotes the terminal differentiation of T cells. On the other hand, Th1 / 17 promotes the effector CD8 + CD127 is an IL-7 receptor and is required for homeostatic T cell proliferation and effector cell survival. Thus, without being bound by theory, CD8 + While T cells have a balanced function between killing and maintaining survival, CD8 + T cells may have enhanced killing function but reduced viability, which may interfere with their ability to destroy virus-infected cells.

[0066] We have previously reported that the antitumor effect of anti-PD-1 antibodies in lung cancer is closely related to the ratio of Th1 / 17 cells in peripheral blood before treatment. Antitumor immunity is thought to be equivalent to that against intracellular parasitic infectious microorganisms, because they present non-self neoantigens derived from gene mutation products. Th1 / 17 is equally important for antitumor immunity and antiviral immunity against SARS-CoV-2, and it is suggested that they require cell killing and durability in T cell immunity.

[0067] It has been shown that the high proinflammatory potential of Th17 can lead to the development of acute respiratory distress syndrome. Interestingly, many risk factors for the development of COVID-19 pneumonia, such as age over 65 years, hypertension, diabetes, obesity, and male gender, are associated with increased Th17 cell numbers. Indeed, some studies have reported that Th17 may play an important role in the development of pneumonia in patients infected with SARS-CoV-2, in light of the high proportion of Th17 in the peripheral blood of patients with COVID-19 pneumonia. In the examples of the present invention, we found that the expression of CTLA-4 in Th17 and Treg was significantly lower in patients with COVID-19 pneumonia. This suggests that the loss of an important inhibitory mechanism of Th17 is likely due to activation and impaired Treg function. It has been shown that the increased Th17 / Treg ratio is associated with LPS-induced acute lung injury and respiratory syncytial virus infection. Without being bound by theory, these findings suggest that low expression of CTLA-4 in Th17 and Treg is involved in the pathogenesis of pneumonia by strongly inducing Th17-type inflammation. The ratio of CTLA-4+ in Th17 did not change significantly even in patients who recovered from viral infection after one week. Without being bound by theory, this suggests that low expression of CTLA-4 in Th17 may be a property of the host rather than a transient response caused by viral infection.

[0068] As shown in the Examples herein, in patients with COVID-19 pneumonia, deficiency of Th1 / 17 leads to terminally differentiated effector CD8 T cells with poor survival signals that result in less efficient viral clearance. + It is suggested that the increase in CTLA-4 in Th17 and Tregs leads to an increase in and activation of Th17 that causes organ damage. These mechanisms may be important therapeutic targets to prevent severe disease in hosts infected with viruses such as SARS-CoV-2.

[0069] In one aspect of the present invention, the present invention provides a method for exploring or determining an indicator for predicting pneumonia in a subject, comprising: CD4 count of subjects before pneumonia treatment+ correlating T cell subpopulations with the subject's response to a pneumonia treatment; Based on the correlation, the subpopulation correlated with the pneumonia treatment is used as an index for predicting response to the pneumonia treatment. In a preferred embodiment, the subpopulations are classified into five Th classes: Th1 (CXCR3 + CCR6 - CCR4 - ), Th1 / 17(CXCR3 + CCR6 + CCR4 - ), Th17(CXCR3 - CCR6 + CCR4 + ), CCR6 SP(CXCR3 - CCR6 + CCR4 - ), TP(CXCR3 + CCR6 + CCR4 + In another embodiment, the method of the present invention may be - CCR6 + CCR4 + ) CTLA-4 in T cell or regulatory T cell populations + The cell subpopulations may also be correlated with the subject's response to treatment for lung inflammation.

[0070] That is, the present invention relates to CD62L low CD4 + A method can be provided in which a cluster or cell subpopulation capable of appropriately evaluating an immune state according to a treatment for a respiratory infection, particularly a pneumonia symptom, is selected from the five types of Th classifications contained in T cells, and the abundance or relative amount of the cell subpopulation is used as an index for predicting a subject's response to a treatment for a respiratory infection, particularly a pneumonia symptom. In addition to or instead of the five types of Th classifications, examples of clusters or cell subpopulations capable of appropriately evaluating an immune state according to a treatment for a respiratory infection, particularly a pneumonia symptom, include CD62L high CD4 +There are six types of Th classifications in T cells, namely, CD62L high Th1(CXCR3 + CCR4 - CCR6 - ) cell subpopulation, CD62L high Th1 / 17(CXCR3 + CCR4 - CCR6 + ) cell subpopulation, CD62L high CCR6 SP(CXCR3 - CCR4 - CCR6 + ) cell subpopulation, CD62L high Th17(CXCR3 - CCR4 + CCR6 + ) cell subpopulation, CD62L high Th2(CXCR3 - CCR4 + CCR6 - ) cell subpopulation, CD62L high TN(CXCR3 - CCR4 - CCR6 - ) cell subpopulations.

[0071] Furthermore, effector CD4+ cells can be included in the Th subpopulation to adequately assess immune status. + As a T cell subpopulation, CCR7 + CD62L low CD4 + T cell subpopulations, PD1 + CCR7 + CD62L low CD4 + T cell subpopulation, LAG-3 + CCR7 + CD62L low CD4 + T cell subpopulation, CD45RA - Foxp3 - CD4 + The T cell subpopulation was classified as a regulatory T cell subpopulation, CD127 + CD25 + CD4 + T cell subpopulation, CD45RA - Foxp3 +CD4 + T cell subpopulation, Foxp3 + CD25 + CD4 + T cell subpopulations are classified as effector CD8 + As a T cell subpopulation, CD62L low CD8 + T cell subpopulations can be individually named.

[0072] In one aspect of the present invention, the present invention provides a method for exploring or determining an indicator for predicting pneumonia in a subject, comprising: CD8 of subjects before pneumonia treatment + correlating T cell subpopulations with the subject's response to a pneumonia treatment; Based on the correlation, the subpopulation correlated with the pneumonia treatment is used as an index for predicting response to the pneumonia treatment. In a preferred embodiment, the subpopulation may include CD27 + Cells and / or CD127 + It may be a cell.

[0073] That is, the present invention relates to a method for detecting CD8 + It is possible to provide a method for selecting a cluster or cell subpopulation that can appropriately evaluate the immune state in response to a treatment for a respiratory infection, particularly a pneumonia symptom, from among cell subpopulations contained in T cells, and using the abundance or relative amount of the cell subpopulation as an index for predicting the response of a subject to treatment for a respiratory infection, particularly a pneumonia symptom.

[0074] (kit) In one aspect of the present invention, a kit is provided that includes a detection agent for a cell surface marker for predicting pneumonia in a subject. The present inventors have found that these cell surface markers expressed by T cells of a subject are related to pneumonia in the subject. This makes it understood that a kit that includes a detection agent for these cell surface markers is useful for predicting pneumonia. Such a kit may include one or more detection agents for molecules suitable for detecting the cell subpopulations described herein. A combination of such detection agents can be used to determine the T cell composition of a subject. Such a kit can be used to measure the proportion of a specific cell subpopulation in a subject as a novel biomarker described herein.

[0075] In one embodiment of the present invention, the kit of the present invention can predict pneumonia in a subject by using a relative amount of any one or more selected from the following as an index for predicting pneumonia in a subject: (1) CD4 + CCR4 in T cell populations - CCR6 + (2) the relative abundance of cell subpopulations; + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + (3) the relative abundance of cell subpopulations; and (4) CTLA-4 in the regulatory T cell population of the subject. + (4) the relative abundance of cell subpopulations; and (5) the subject's CD8 + CD27 in T cell populations + (5) the relative abundance of cell subpopulations; + CD127 in T cell populations + Relative abundance of cell subpopulations.

[0076] In one embodiment of the present invention, the kit of the present invention can predict pneumonia in a subject by using a comparison of the relative amount of any one or more of the above in a subject with a reference value as an index for predicting pneumonia in the subject. In one embodiment, the kit of the present invention can be used to predict whether or not a subject will develop pneumonia.

[0077] In one embodiment of the present invention, the kit of the present invention may include any one or more detection agent sets selected from: (a) a detection agent for CD4, a detection agent for CCR4, and a detection agent for CCR6; (b) a detection agent for CD4, a detection agent for CCR4, a detection agent for CCR6, a detection agent for CXCR3, and a detection agent for CTLA-4; (c) a detection agent for FOXP3 and a detection agent for CTLA-4; (d) a detection agent for CD8 and a detection agent for CD27; and (e) a detection agent for CD8 and a detection agent for CD127. In one embodiment, the detection agent is an antibody. Preferably, the antibody is appropriately labeled to facilitate detection of the marker.

[0078] In one embodiment, the composition of T cells of a subject is the composition of T cells in a sample obtained from the subject, and preferably, the sample is a peripheral blood sample. The biomarkers provided in the present invention can be measured using a peripheral blood sample, and therefore have great advantages in clinical application, such as being non-invasive, inexpensive, and capable of being performed over time.

[0079] In one embodiment, if a subject is shown to develop pneumonia symptoms, e.g., CD4 + CCR4 in T cell populations - CCR6 + If the amount or relative amount of the cell subpopulation is below the reference value, it is considered that additional therapeutic and / or preventative measures should be taken.

[0080] A further aspect of the present invention provides a method for predicting pneumonia in a subject using the composition of the subject's T cells, and treating, improving, and / or preventing the subject. Alternatively, a method for treating, improving, and / or preventing pneumonia in a subject having a specific T cell composition, or a composition therefor, is provided. Conventionally, it has been difficult to predict whether a subject will develop pneumonia, so selecting a subject using the biomarker of the present invention to treat or prevent pneumonia can realize efficient medical care.

[0081] In another aspect of the present invention, there is provided a method for treating, improving, or preventing a subject suffering from a virus and / or bacteria that causes pneumonia and / or a subject suspected of having pneumonia, comprising the steps of: determining a relative amount of any one or more of the following in a sample derived from the subject; determining that the subject will develop pneumonia if the relative amount is lower than a reference value; and treating, improving, or preventing pneumonia in the subject. + CCR4 in T cell populations - CCR6 + (2) the relative abundance of cell subpopulations; + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + (3) the relative abundance of cell subpopulations; and (4) CTLA-4 in the regulatory T cell population of the subject. + (4) the relative abundance of cell subpopulations; and (5) the subject's CD8 + CD27 in T cell populations + (5) the relative abundance of cell subpopulations; + CD127 in T cell populations + Relative abundance of cell subpopulations.

[0082] In another aspect of the present invention, there is provided a method for treating, improving, or preventing a subject infected with a virus and / or bacteria that causes pneumonia and / or a subject suspected of having pneumonia, comprising the steps of: determining the relative amount of any one or more of the following in a sample derived from the subject; determining that the subject will develop pneumonia if the relative amount is higher than a reference value; and treating, improving, or preventing pneumonia in the subject. + CCR4 in T cell populations - CCR6 + (2) the relative abundance of cell subpopulations; + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + (3) the relative abundance of cell subpopulations; and (4) CTLA-4 in the regulatory T cell population of the subject. + (4) the relative abundance of cell subpopulations; and (5) the subject's CD8 + CD27 in T cell populations + (5) the relative abundance of cell subpopulations; + CD127 in T cell populations + Relative abundance of cell subpopulations.

[0083] (Cell therapy and proliferation of target cells for that purpose) The present inventors have + CCR4 in T cell populations - CCR6 + Cell subpopulation, CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations + Cell Subpopulation, CTLA-4 in Regulatory T Cell Population + Cell subpopulation, CD8 + CD27 in T cell populations + Cell subpopulations, or CD8 + CD127 in T cell populations +It has been found that there is a clear correlation between the proportion of a particular cell population, such as a cell subpopulation, and the onset of symptoms of respiratory infection, in particular pneumonia, in a subject, and in particular that in order to prevent the onset of pneumonia, it is essential to have a high content of the particular cell subpopulation of the present invention.

[0084] Without wishing to be bound by theory, this finding suggests that CD4 + CCR4 in the T cell population - CCR6 + Cell subpopulations (especially CD62L low CCR4 - CCR6 + cell subpopulation), CCR4 - CCR6 + CXCR3 + Cell subpopulations (especially CD62L low CCR4 - CCR6 + CXCR3 + cell subpopulation), or CCR4 - CCR6 + CXCR3 - Cell subpopulations (especially CD62L low CCR4 - CCR6 + CXCR3 - cell subpopulation), or CD8 + CD127 in T cell populations + Cell subpopulations, or CD27 + cell subpopulations, or CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 in T cell populations or in regulatory T cell populations + Patients with high levels of certain cell populations, such as cell subpopulations, are thought to have immunity that prevents respiratory infections from becoming more severe, particularly pneumonia, whereas patients with low levels of these cell populations are thought to have a lack of immunity that prevents respiratory infections from becoming more severe, particularly pneumonia, leading to more severe symptoms.

[0085] From the above, CD4 +In the T cell population, CD62L low CCR4 - CCR6 + Cell subpopulation, CD62L low CCR4 - CCR6 + CXCR3 + Cell subpopulations, or CD62L low CCR4 - CCR6 + CXCR3 - Cell subpopulations, or CCR4 - CCR6 + Cell Subpopulation, CCR4 - CCR6 + CXCR3 + Cell Subpopulations, or CCR4 - CCR6 + CXCR3 - Certain cell populations, such as CD8 + In the T cell population, CD127 + Cell subpopulations, or CD27 + Certain cell populations, such as CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 in the T cell population or in the regulatory T cell population + It is believed that for patients at risk of developing severe symptoms of respiratory infection, particularly pneumonia symptoms, due to the low abundance of certain cell populations, such as cell subpopulations, it is possible to treat and / or prevent the development of severe symptoms of respiratory infection, particularly pneumonia symptoms, by administering these particular cell populations.

[0086] Thus, according to a further aspect of the present invention, there is provided a method for treating, ameliorating, or preventing pneumonia in a subject by transferring specific cells, or a composition therefor.

[0087] CD62L low CCR4 - CCR6 + CD4 + T cells, CCR4 - CCR6+ CD4 + T cells, CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 + T cells, CTLA-4 + Treg cells, CD27 + CD8 + T cells, and / or CD127 + CD8 + It has been found that T cells are important for the subject's response to pneumonia in a subject, and it is believed that such T cells can be used to treat, ameliorate, or prevent pneumonia in a subject. low CCR4 - CCR6 + CD4 + T cells, CCR4 - CCR6 + CD4 + T cells, CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 + T cells, CTLA-4 + Treg cells, CD27 + CD8 + T cells, and / or CD127 + CD8 + A composition comprising T cells. low CCR4 - CCR6 + CD4 + T cells, CCR4 - CCR6 + CD4 + T cells, CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 + T cells, CTLA-4 + Treg cells, CD27 + CD8 + T cells, and / or CD127 + CD8 +The T cells, or compositions comprising them, are useful in combination with drugs to treat and / or ameliorate respiratory infections, such as pneumonia.

[0088] For example, CD62L low CCR4 - CCR6 + CD4 + T cells, CCR4 - CCR6 + CD4 + T cells, CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 + T cells, CTLA-4 + Treg cells, CD27 + CD8 + T cells, and / or CD127 + CD8 + The method for producing a composition comprising T cells comprises the steps of: low CCR4 - CCR6 + CD4 + T cells, CCR4 - CCR6 + CD4 + T cells, CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 + T cells, CTLA-4 + Treg cells, CD27 + CD8 + T cells, and / or CD127 + CD8 + The purification step may include purifying the T cells. low CCR4 - CCR6 + CD4 + T cells or CCR4 - CCR6 + CD4 + In the case of T cells, CCR6 + CD4 + CD62L from T cells high Cells and CCR4+ This may include removing cells that are CCR4 - CCR6 + CD4 + It is preferable to purify T cells by negative selection using antibodies and / or magnetic beads, sorting methods, etc., because contaminants such as antibodies and magnetic beads do not remain on the cells to be used. low CCR4 - CCR6 + CD4 + T cells express CD62L high cells, CCR4 + CCR6 from negatively selected cells + These are obtained by positive selection of cells through sorting. CD4 + CCR4 + CCR6 + CXCR3 - CTLA-4 + T cells, CTLA-4 + Treg cells, CD27 + CD8 + T cells, and CD127 + CD8 + T cells can also be purified using a similar technique.

[0089] T lymphocytes can be collected according to known techniques and enriched or depleted by known techniques such as affinity binding to antibodies, such as flow cytometry and / or immunomagnetic selection. After the enrichment and / or depletion steps, in vitro expansion of the desired T lymphocytes can be carried out according to known techniques (including but not limited to those described in U.S. Patent No. 6,040,177 to Riddell et al.) or variations thereof that would be apparent to one of skill in the art.

[0090] For example, a desired T cell population or subpopulation may be expanded in vitro by adding an initial T lymphocyte population to a culture medium, followed by adding feeder cells to the medium (e.g., such that the resulting cell population contains at least about 5, 10, 20, or 40 or more feeder cells for every T lymphocyte in the initial population to be expanded), and incubating the culture (e.g., for a time sufficient to expand the number of T cells). The culture may typically be incubated under conditions, such as temperature, that are suitable for the growth of T lymphocytes. For the growth of human T lymphocytes, for example, the temperature will generally be at least about 25 degrees Celsius, preferably at least about 30 degrees, and more preferably about 37 degrees.

[0091] Once the cells have been isolated and / or expanded according to methods described herein or known in the art, they can be stored, if desired, and then administered to a subject.

[0092] The cells of interest (e.g., CCR4 - CCR6 + CD4 + The amount of T cells can be appropriately determined by those skilled in the art so as to achieve the intended effect, but is preferably at least 2 x 10 8 Pieces, preferably at least 6x10 8 pieces, more preferably at least 2x10 9 There can be one.

[0093] The compositions comprising the cells described herein can be used to treat cells of interest (e.g., CCR4 - CCR6 + CD4 +In addition to the injectable composition (cells), the composition may contain a pharma- ceutically acceptable carrier or excipient. As used herein, "pharmaceutical acceptable" means approved by a government regulatory agency or listed in a pharmacopoeia or other generally recognized pharmacopoeias for use in animals, and more particularly in humans. As used herein, "carrier" refers to a culture medium, infusion medium, perfusion medium, diluent, adjuvant, excipient, or vehicle with which the therapeutic agent is administered. Since the composition containing the cells of the present invention contains cells as a major component, the carrier is preferably one that can support the cells, such as a culture medium, infusion medium, or perfusion medium. For example, when the pharmaceutical composition is administered intravenously, saline and aqueous dextrose are preferred carriers. Preferably, saline solution and aqueous dextrose and glycerol solutions are used as liquid carriers for injectable solutions. When the pharmaceutical is administered orally, water is the preferred carrier. Suitable excipients include light anhydrous silicic acid, crystalline cellulose, mannitol, starch, glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silica gel, sodium stearate, glycerol monostearate, talc, sodium chloride, skimmed milk powder, glycerol, propylene, glycol, water, ethanol, carmellose calcium, carmellose sodium, hydroxypropyl cellulose, hydroxypropyl methyl cellulose, polyvinyl acetal diethyl amino acetate, polyvinyl pyrrolidone, gelatin, medium chain triglyceride, polyoxyethylene hydrogenated castor oil 60, sucrose, carboxymethyl cellulose, corn starch, inorganic salts, etc. The composition can also contain a small amount of a wetting or emulsifying agent, or a pH buffer, if desired. These compositions can take the form of a solution, suspension, emulsion, tablet, pill, capsule, powder, sustained release formulation, etc. The composition can also be formulated as a suppository, using traditional binders and carriers, such as triglycerides. Oral formulation can include standard carriers such as pharmaceutical grades of mannitol, lactose, starch, magnesium stearate, sodium saccharin, cellulose, magnesium carbonate, etc.Examples of suitable carriers are described in EW Martin, Remington's Pharmaceutical Sciences (Mark Publishing Company, Easton, USA). Such compositions contain a therapeutically effective amount of the therapeutic agent, preferably in purified form, together with a suitable amount of carrier to provide a form that is properly administered to a patient. The formulation must be suitable for the mode of administration. In addition to these, for example, surfactants, excipients, coloring agents, flavoring agents, preservatives, stabilizers, buffers, suspending agents, isotonicity agents, binders, disintegrants, lubricants, flow enhancers, flavoring agents, etc. may be included.

[0094] (General technology) The molecular biological, biochemical and microbiological techniques used herein are well known and commonly used in the art, and are described, for example, in Sambrook J. et al. al.(1989).Molecular Cloning: A Laboratory Manual,Cold Spring Harbor and its 3rd Ed.(2001);Ausubel,FM(1987).Current Protocols in Molecular Biology,Greene Pub.AssociatESand Wiley-Interscience;Ausubel,FM(1989).Short Protocols in Molecular Biology:A Compendium of Methods from Current Protocols in Molecular Biology,Greene Pub.Associates and Wiley-Interscience;Innis, MA(1990).PCR Protocols: A Guide to Methods and Applications, Academic Press;Ausubel,FM(1992).Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology,Greene Pub.Associates;Ausubel,FM(1995).Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology,Greene Pub.Associates;Innis,MAet al.(1995).PCR Strategies,Academic Press;Ausubel,FM(1999).Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology,Wiley,and annual updates;Sninsky,JJet al.(1999).PCR Applications: Protocols for Functional Genomics,Academic Press, Special Edition Experimental Medicine "Gene Introduction & Expression Analysis Experimental Methods", Yodosha, 1997, etc., the relevant parts of which (possibly in their entirety) are incorporated herein by reference.

[0095] In this specification, "or" is used when "at least one or more" of the items listed in the sentence can be employed. The same applies to "alternative." In this specification, when "within the range of" two values ​​is specified, the range includes the two values ​​themselves.

[0096] All references cited herein, including scientific literature, patents, patent applications, and the like, are hereby incorporated by reference in their entirety to the same extent as if each was specifically set forth.

[0097] The present invention has been described above by showing preferred embodiments for ease of understanding. The present invention will be described below based on examples, but the above description and the following examples are provided for illustrative purposes only and are not provided for the purpose of limiting the present invention. Therefore, the scope of the present invention is not limited to the embodiments or examples specifically described in this specification, but is limited only by the scope of the claims. EXAMPLES

[0098] The present invention has been described above by showing preferred embodiments for ease of understanding. The present invention will be described below based on examples, but the above description and the following examples are provided for illustrative purposes only and are not provided for the purpose of limiting the present invention. Therefore, the scope of the present invention is not limited to the embodiments or examples specifically described in this specification, but is limited only by the scope of the claims.

[0099] Example 1: Proportion of T cell subpopulations in SARS-CoV-2-infected individuals patient The study included 49 consecutive patients with confirmed SARS-CoV-2 infection by PCR testing who were admitted to Saitama Medical University Hospital or Saitama Medical University International Medical Center between December 4, 2020 and January 17, 2022. Twenty-nine of the 49 patients were diagnosed with COVID-19 pneumonia by computed tomography (CT) imaging (Table 1). [Table 1]

[0100] Peripheral blood samples were also obtained from 15 healthy volunteers. All samples were collected after written informed consent was obtained. The study protocol was approved by the Internal Review Board of Saitama Medical University International Medical Center.

[0101] Blood Sample Analysis Peripheral blood mononuclear cell (PBMC) samples were collected at admission, 1 week later, and at discharge using heparinized Vacutainer CPT tubes (BD Vacutainer System, Franklin Lakes, NJ, USA). Samples were frozen in a liquid nitrogen bath using a CELLBANKER 2 (Nihon Zenyaku Kogyo Co., Ltd., Koriyama, Japan). For analysis of T cell subsets, cells were incubated in culture medium consisting of RPMI1640 and 10% fetal bovine serum for 32–48 h before cell staining.

[0102] Mass Cytometry The mAbs used for Helios™ mass cytometry analysis are shown in Table 2. [Table 2] According to the manufacturer's instructions, up to 2.5 x 10 6 Cells were stained with mass cytometry antibodies (Fluidigm Corp., San Francisco, CA, USA). For intracellular staining, samples were prepared using the FoxP3 fixation and permeabilization kit according to the manufacturer's instructions before staining. After washing twice with Maxpar Cell Staining Buffer, samples were fixed using 1.6% paraformaldehyde in PBS supplemented with 100 nM iridium nucleic acid intercalator (Fluidigm). Following fixation, cells were washed twice with PBS containing 0.5% bovine serum albumin (BSA) and water containing 0.1% BSA, and resuspended in water containing 0.1% BSA. A total of 20,000 cells were analyzed using Helios and Cytobank (https: / / www.cytobank.org) software used in viSNE. The gating strategy is shown in Figure 5.

[0103] statistical analysis Statistical analysis was performed using Prism 9 (GraphPad Software, San Diego, CA, USA). Data are presented as mean ± standard error of the mean unless otherwise stated. Tests for differences between two groups were performed using Student's t-test. Multiple comparisons were performed using one-way ANOVA with Tukey post-hoc test. All p-values ​​were two-sided, and P<0.05 was considered statistically significant.

[0104] result CD4 + T cell immunity differs between SARS-CoV-2 patients without pneumonia, patients with COVID-19 pneumonia, and healthy controls Using T cells obtained from peripheral blood samples obtained at the time of admission and one week after admission from SARS-CoV-2-infected non-pneumonia patients (n=2) and SARS-CoV-2-infected pneumonia patients (COVID-19 pneumonia patients, n=3), expression analysis was performed using scRNAseq based on the expression of approximately 2000 genes. + We performed unsupervised clustering of T cells (Figure 1A). Using this tSNE analysis, we performed cell-level annotation based on the expression patterns of chemokine receptors CXCR3, CCR4, and CCR6, and the expression of CD45RA and CD62L (Figure 1B). The area enclosed by the line in the upper left of the figure is mostly composed of naive CD4 + T cells, CD45RA + CD62L high The area enclosed by the line in the lower left of the figure is composed of FoxP3. + The area on the right side of the figure is composed of CD45RA cells and is considered to be the region of regulatory T cells. - CD62L low CD4 + The metacluster A was composed of T cells and was considered to be an effector-type region. The components abundant in SARS-CoV-2-infected non-pneumonia patients are shown in purple, and those abundant in COVID-19 pneumonia patients are shown in red (Figure 1C). low CXCR3 + CCR4 - CCR6 + It was composed mainly of Th1 / 17.

[0105] Next, mass cytometry analysis was used to identify CD4 + We checked whether the differences in T cell polarization patterns were observed in all patients (n=49). + T cell polarization uses chemokine receptor expression patterns to regulate CXCR3 + CCR4 - CCR6 - Th1 type, CXCR3 - CCR4 + CCR6 - Th2 type, CXCR3 - CCR4 + CCR6 + Th17 type, CXCR5 + Tfh type, FoxP3 + CD45RA - were classified as regulatory T cell (Treg) type.

[0106] Peripheral blood CD4 count at admission + T cell analysis revealed that CD62L low CD4 + The ratio of T cells and Th1 was found to be significantly increased in SARS-CoV-2-infected patients compared to healthy subjects (not shown). In a comparison of the three groups of healthy subjects, non-pneumonia patients, and pneumonia patients, Th1 / 17 was significantly lower in COVID-19 pneumonia patients, consistent with the results of scRNAseq (P = 0.0040 between healthy subjects and pneumonia patients, P = 0.0018 between non-pneumonia patients and pneumonia patients, Figure 1D). The results of ROC analysis (Figure 1E) showed that pneumonia patients and non-pneumonia patients had a significantly higher Th1 / CCR6 single positive (CCR6 SP) CD4 + There was a significant difference in the T cell clusters, which were significantly lower in pneumonia patients than in non-pneumonia patients (P = 0.020). As shown in Figure 6, pneumonia patients and non-pneumonia patients had significantly higher Th7R (CCR4 - CCR6 + ) There were significant differences in T cell clusters, which were significantly lower in pneumonia patients than in non-pneumonia patients (P = 0.0023, P = 0.0013).

[0107] It is known that the expression of immune checkpoint molecules has a significant effect on the function of T cells in antiviral immunity. + The expression of CTLA-4 and PD-1 was analyzed for each T cell cluster (Figure 1F). As a result, the proportion of CTLA-4 expression in Th17 and Treg was significantly lower in the pneumonia group (P = 0.0056, P = 0.014). In terms of gene expression, CTLA-4 expression in Treg was also significantly lower in the pneumonia group (FDR < 0.05). These results suggest that not only was the control ability of Th17 weaker in the pneumonia group, but the regulatory T cell function was also poor.

[0108] Example 2: CD8 + T cell response to SARS-CoV-2 infection Next, CD4 + Like T cells, CD8 + Unsupervised clustering based on gene expression was also performed on the T cell clusters (Figure 2A-C). The area enclosed by the line on the left in the figure shows the CD45RA + CCR7 - CD8 + This shows the effector memory (EMRA) region with re-expression of CD45RA in T cells, and the boxed region to the right of this region shows CD45RA - CCR7 - The region enclosed by a line to the right of EM is CD45RA. - CCR7 + CM, the rightmost boxed area is CD45RA + CCR7 + Naïve CD8 + This is the T cell region. Mass cytometry analysis showed that SARS-CoV-2-infected individuals had fewer naive and more EMRA than healthy controls (Figure 2D). CM was less in the pneumonia group than in the non-pneumonia group, but the results of the time course changes described below showed that the non-pneumonia group was in the recovery phase.

[0109] CD8 is thought to directly eradicate virus-infected cells + CD4 for T cells +To examine the effect of T cells, each CD8 + T cell ratio and CD4 + We analyzed the correlation of T cell clusters (Figure 2E). As a result, only Th1 showed a positive correlation with EMRA, a weak negative correlation with CM, and a weak positive correlation with EM.

[0110] each CD8 + Molecular expression analysis of T cell clusters showed that the expression ratios of CD27 and CD127 (IL-7 receptor) in EM and EMRA were significantly different between the pneumonia and non-pneumonia groups (Figure 2F), but showed a significant positive correlation (Figure 2G). + The expression of IL-7 receptors on Th1 cells was positively correlated with the expression of IL-7 receptors on Th1 cells (Fig. 2H). + Th1 / 17 promotes differentiation of T cells into a cytotoxic T cell state and reduces their proliferative potential, whereas Th8 + It was suggested that it is involved in maintaining a state in which T cells are more susceptible to receiving survival signals.

[0111] Example 3: CD8 + T cell immunity) After admission, 2 of 20 patients without pneumonia and 27 of 29 patients with pneumonia received steroid therapy. Seven of the patients with pneumonia were placed on mechanical ventilation, but all eventually recovered. + The time course of T cell immunity was analyzed (Figure 3A, B). + When comparing T cell fractions, the difference observed between healthy subjects and SARS-CoV-2-infected subjects was maintained in the naive fraction. On the other hand, the difference between healthy subjects and SARS-CoV-2-infected subjects observed in EMRA was no longer observed, and the percentage of cells corresponding to a decrease in EMRA increased in the CM fraction, and the SARS-CoV-2-infected group was significantly higher than the healthy group (Figure 3C). This is due to the CD8 +This indicates that T cell differentiation shifted to induction toward the CM fraction as the virus recovered from infection. In addition, the effector CD8 + The decrease in CD27 and CD127 in the T cell fraction was also restored, and no significant difference was observed in the ratio of CD27 and CD127 positive cells between the pneumonia and non-pneumonia groups (Figures 3D and E). + The difference in the proportion of T cells disappeared as the patient recovered from SARS-CoV-2 infection (the virus disappeared). This is thought to be because the virus no longer existed, and therefore the significant differences in the proportions of CD27 and CD127 positive cells also disappeared.

[0112] Example 4: CD4 + T cell immunity differs between non-pneumonia and pneumonia patients after recovery from SARS-CoV-2 infection CD4 during recovery from SARS-CoV-2 infection + Changes in T cell clusters were analyzed. Th1 decreased in both the pneumonia and non-pneumonia groups (non-pneumonia group P = 0.0043, pneumonia group P = 0.0006, Fig. 4A). On the other hand, Th17 increased, and the degree of increase was higher in the pneumonia group (Fig. 4B). On the other hand, Th1 / 17, which was shown to be significantly lower in the pneumonia group at the time of admission, tended to decrease in the pneumonia group. As a result, in grid subtraction of unsupervised clustering based on gene expression using peripheral blood 1 week after admission, metacluster A, which has Th1 / 17 as its main component, was decreased in the pneumonia group, as it was at the time of admission (Fig. 4C). In mass cytometry analysis of all cases, Th1 / 17 remained significantly lower in the pneumonia group than in healthy subjects and the non-pneumonia group (P = 0.0021, P = 0.039, Fig. 4D). That is, CD4 + In the T cell cluster, the difference in the Th1 / 17 cell population remained even after recovery (when the virus was gone), suggesting that this difference does not reflect the outcome of symptoms, but that this cell population can predict symptoms.

[0113] The difference in CTLA-4 positivity between Th17 and Treg, as shown by peripheral blood analysis at admission, persisted one week later and was lower in the pneumonia group (P = 0.023, P = 0.0041, Fig. 4E). + T cell cluster, effector CD8 + T cell-based CD27 + , and CD127 + Percentage of CD4 + The correlation observed between T cell clusters was maintained in peripheral blood analysis 1 week later, with Th1 being predominantly CD8 + The Th1 / 17 positively correlated with the EM and EMRA ratios of T cells, whereas the effector CD8 + This correlated positively with CD27 and CD127 positivity on T cells (Figure 4F).

[0114] (Note) Although the present disclosure has been illustrated using the preferred embodiments thereof, it is understood that the present disclosure should be interpreted in scope only by the claims. It is understood that the patents, patent applications, and other documents cited in this specification are incorporated by reference into this specification in the same manner as if the contents themselves were specifically set forth herein. [Industrial Applicability]

[0115] The biomarkers provided by the present invention can be used to predict symptoms of respiratory infections simply, inexpensively, and accurately, and are essential medically and socially. Since the present invention makes it possible to predict pneumonia, which affects a huge number of patients worldwide, it is believed to have extremely high commercial value.

Claims

1. A method for using a relative amount of one or more of the following in a subject as an index for predicting pneumonia in the subject, comprising: (1) CD4 of the subject ＋ CCR4 in T cell populations - CCR6 ＋ Relative abundance of cell subpopulations; (2) CD4 of the subject ＋ CCR4 ＋ CCR6 ＋ CXCR3 - CTLA-4 in T cell populations ＋ Relative abundance of cell subpopulations; (3) CTLA-4 in the subject's regulatory T cell population ＋ Relative abundance of cell subpopulations; (4) CD8 of the subject ＋ CD27 in T cell populations ＋ Relative abundance of cell subpopulations; (5) CD8 of the subject ＋ CD127 in T cell populations ＋ Relative abundance of cell subpopulations; determining the relative abundance of said cell subpopulations in a sample from said subject; The relative amount is used as an index for predicting pneumonia in the subject.

2. The method of claim 1, wherein a comparison of the relative amount with a reference value is used as an index for predicting pneumonia in the subject.

3. 3. The method of claim 1 or 2, wherein the prediction comprises a prediction of whether pneumonia will develop in the subject.

4. The method of any one of claims 1 to 3, wherein the relative amount being equal to or less than a reference value indicates a high likelihood that the subject will develop pneumonia, or the relative amount being equal to or greater than a reference value indicates a low likelihood that the subject will develop pneumonia.

5. CCR4 - CCR6 ＋ A subpopulation of cells further comprises CXCR3 ＋ The method according to any one of claims 1 to 4, which is a cell subpopulation.

6. CCR4 - CCR6 ＋ A subpopulation of cells further comprises CXCR3 - The method according to any one of claims 1 to 4, which is a cell subpopulation.

7. The CD8 ＋ The method of any one of claims 1 to 6, wherein the T cell population is an effector memory T cell population.

8. The CD8 ＋ The T cell population is CD8 ＋ CCR7 - CD45RA ＋ The method according to any one of claims 1 to 7, which is an effector memory T cell population.

9. The method of any one of claims 1 to 8, wherein the pneumonia is caused by a respiratory infection.

10. 10. The method of claim 9, wherein the respiratory infection comprises a coronavirus infection or an influenza virus infection.

11. The method of claim 10, wherein the coronavirus is an α-coronavirus, a β-coronavirus, a γ-coronavirus, or a δ-coronavirus.

12. 12. The method of claim 11, wherein the β-coronavirus comprises a virus selected from the group consisting of SARS-CoV-2, HCoV-OC43, HCoV-HKU1, SARS-CoV, Bat SL-CoV-WIV1, BtCoV-HKU4, BtCoV-HKU5, MERS-CoV, and BtCoV-HKU9.

13. The method according to any one of claims 1 to 12, characterized in that the relative amount of cells is measured using a peripheral blood sample.

14. The method of any one of claims 1 to 13, wherein the subject is selected from the group consisting of subjects suffering from a virus and / or bacteria that causes pneumonia and subjects suspected of having pneumonia.

15. 1. A kit for predicting pneumonia in a subject, comprising: (a) a detection agent for CD4, a detection agent for CCR4, and a detection agent for CCR6; (b) a detecting agent for CD4, a detecting agent for CCR4, a detecting agent for CCR6, a detecting agent for CXCR3, and a detecting agent for CTLA-4; (c) a detection agent for FOXP3 and a detection agent for CTLA-4; (d) a detection agent for CD8 and a detection agent for CD27; and (e) a detection agent for CD8, and a detection agent for CD127; and wherein the prediction is performed by using a relative amount of any one or more selected from the following as an index for predicting pneumonia in the subject: (1) CD4 of the subject ＋ CCR4 in T cell populations - CCR6 ＋ Relative abundance of cell subpopulations; (2) CD4 of the subject ＋ CCR4 ＋ CCR6 ＋ CXCR3 - CTLA-4 in T cell populations ＋ Relative abundance of cell subpopulations; (3) CTLA-4 in the subject's regulatory T cell population ＋ Relative abundance of cell subpopulations; (4) CD8 of the subject ＋ CD27 in T cell populations ＋ Relative abundance of cell subpopulations; (5) CD8 of the subject ＋ CD127 in T cell populations ＋ Relative abundance of cell subpopulations

16. The kit of claim 15, wherein a comparison of the relative amount with a reference value is used as an index for predicting pneumonia in the subject.

17. 17. The kit of claim 15 or 16, wherein the prediction comprises a prediction of whether the subject will develop pneumonia.

18. The kit of any one of claims 15 to 17, wherein the detection agent is an antibody.

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