Relative changes in monocyte and lymphocyte cd45 molecule expression for diagnosis of infection and inflammation

Abstract

The application discloses application of relative changes of CD45 molecule expression of monocytes and lymphocytes in diagnosis of infection and inflammation, and creatively finds for the first time that the index of relative changes of CD45 molecule expression of monocytes and lymphocytes can be used for quickly and accurately judging whether a patient is accompanied by infection, and effectively distinguishing whether it is viral infection or bacterial infection, and has high diagnostic efficiency, high AUC value, sensitivity and specificity, can be used for guiding clinical treatment decision and antibiotic use, and is used in early screening, prevention, treatment and post-treatment monitoring of infection, and has important transformation significance.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of biomedical technology, and in particular, relates to the application of relative changes in CD45 molecule expression of monocytes and lymphocytes in the diagnosis of infection. BACKGROUND

[0002] In recent years, the prevalence of drug-resistant bacteria and viruses such as the novel coronavirus, influenza virus, respiratory syncytial virus, and adenovirus has significantly increased. With the development of globalization, the speed and scope of bacterial and viral transmission are also expanding. Judging infection and effectively distinguishing between bacterial and viral infections is crucial for reducing antibiotic misuse, the occurrence of clinically drug-resistant bacteria, and the effective treatment of infectious diseases. Traditional detection methods, including culture, microscopic examination, biochemical identification, and serological detection, have important significance in pathogen detection, but they have been gradually replaced by modern molecular biology techniques (such as PCR and high-throughput sequencing) due to their long time-consuming, low sensitivity, and insufficient specificity. Although the use of PCR and high-throughput sequencing technology has greatly improved the sensitivity and specificity of pathogenic microorganism detection and significantly accelerated the detection speed, PCR technology still has some limitations due to the diversity of virus species and the high requirements for laboratories to carry out PCR detection. There is an urgent need for a simple and rapid detection method to assist clinical treatment decisions and antibiotic use to distinguish between infection types.

[0003] CD45 antigen, also known as PTPRC, is encoded by the PTPRC gene in humans. PTPRC, originally known as leukocyte common antigen (LCA), is a receptor-type protein tyrosine phosphatase (PTP) that is universally expressed in all nucleated hematopoietic cells, accounting for about 10% of lymphocyte surface proteins. CD45 glycoprotein plays a crucial role in lymphocyte development and antigen signaling and is an important regulator of Src family kinases. Due to alternative splicing, CD45 protein exists in multiple isoforms, which differ in their extracellular domains but have identical transmembrane and cytoplasmic domains. CD45RA is a CD45 complex isoform with limited expression in different subtypes of lymphoid cells. CD45 isoforms differ in their ability to transport to membrane domains rich in sphingolipids, and their expression depends on cell type and cell physiological state. CD45 has been shown to be an important regulator of T cell and B cell antigen receptor signaling and inhibits JAK kinases to regulate cytokine receptor signaling. CD45 also plays an important role in promoting cell survival by regulating integrin-mediated signal transduction pathways, DNA breaks during apoptosis, and inhibiting or upregulating various immune functions.

[0004] Currently, there is no relevant research or report on using the relative changes in CD45 molecule expression of monocytes and lymphocytes as an indicator to diagnose infection and distinguish between bacterial and viral infections. SUMMARY

[0005] Therefore, the present application aims to provide the application of the relative change of CD45 molecule expression of monocytes and lymphocytes in diagnosing infection and inflammation. The present application uses the ratio of CD45 molecule expression level of peripheral blood monocytes and lymphocytes to quickly and effectively determine whether the patient is accompanied by infection, and effectively distinguish whether it is viral infection or bacterial infection, which can be used to guide clinical treatment decision and antibiotic use.

[0006] The present application realizes the above-mentioned application purposes by using the following technical solutions:

[0007] The first aspect of the present application provides the application of the reagent for detecting the relative expression level of CD45 molecule of monocytes and lymphocytes in the preparation of the product for diagnosing infection or identifying infection type.

[0008] Further, the reagent comprises:

[0009] the reagent for detecting the relative expression level of CD45 protein of monocytes and lymphocytes in the sample;

[0010] the reagent for detecting the relative level of DNA of CD45 of monocytes and lymphocytes in the sample; or

[0011] the reagent for detecting the relative level of RNA of CD45 of monocytes and lymphocytes in the sample.

[0012] Further, the relative expression level of CD45 molecule of monocytes and lymphocytes comprises the ratio of CD45 molecule expression level of monocytes and lymphocytes, the ratio of CD45 molecule expression level of lymphocytes and monocytes, the difference of CD45 molecule expression level of monocytes and lymphocytes, and / or the difference of CD45 molecule expression level of lymphocytes and monocytes.

[0013] Further, the reagent for detecting the relative expression level of CD45 protein of monocytes and lymphocytes in the sample comprises the affinity protein specifically binding to CD45 protein of monocytes and lymphocytes;

[0014] Optionally, the affinity protein comprises the antibody, antibody functional fragment, agglutination agent, receptor and / or conjugated antibody specifically binding to CD45 protein of monocytes and lymphocytes;

[0015] Optionally, the reagent for detecting the relative level of DNA of CD45 of monocytes and lymphocytes in the sample comprises the reagent for detecting the relative level of DNA, DNA methylation level and / or DNA phosphorylation level of CD45 of monocytes and lymphocytes in the sample;

[0016] Optionally, the reagent for detecting the relative DNA level of monocyte and lymphocyte CD45 in the sample comprises a reagent for detecting the relative DNA level by sequencing technology.

[0017] Optionally, the reagent for detecting the relative RNA level of monocyte and lymphocyte CD45 in the sample comprises a reagent for detecting the relative expression level of mRNA and / or miRNA of monocyte and lymphocyte CD45 in the sample.

[0018] Optionally, the reagent for detecting the relative RNA level of monocyte and lymphocyte CD45 in the sample comprises primers specifically amplifying monocyte and lymphocyte CD45 and / or probes specifically recognizing monocyte and lymphocyte CD45.

[0019] Further, the diagnosis of infection is diagnosis of whether the subject is infected, diagnosis of whether the subject is infected with a viral infection or diagnosis of whether the subject is infected with a bacterial infection.

[0020] Optionally, the identification of infection type is identification of distinguishing viral infection from bacterial infection.

[0021] Further, the sample is a peripheral blood sample, a tissue sample, a serum sample, a plasma sample, a cell sample, a urine sample and / or an exosome sample derived from the subject.

[0022] In the present application, as long as the relative expression level of monocyte and lymphocyte CD45 molecules is used as the index for diagnosing infection or identifying infection type as described above, such methods fall within the protection scope of the present application, and are not limited to the specific methods using the relative expression level of monocyte and lymphocyte CD45 molecules as described above, as long as the relative expression level of monocyte and lymphocyte CD45 molecules as described above can achieve or substantially achieve the purpose of diagnosing infection or identifying infection type, which will fall within the protection scope of the present application.

[0023] In a specific embodiment of the present application, in the peripheral blood sample, monocyte and lymphocyte are selected by flow cytometry analysis, and the mean fluorescence intensity (MFI) or Geometric Mean of CD45 molecules of the monocyte and lymphocyte are counted respectively by using FlowJo or other software, and then the relative expression level of CD45 molecules of the monocyte and lymphocyte (CD45 MFI monocyte / CD45 MFI lymphocyte) is calculated.

[0024] In some embodiments, the software for counting the mean fluorescence intensity (MFI) of CD45 molecules of monocytes and lymphocytes includes, but is not limited to, FlowJo, ImageJ, Kaluza, SPSS, BD FACSDiva, or CellProfiler.

[0025] In some embodiments, the detection method for detecting the relative expression level of CD45 molecules of monocytes and lymphocytes of the present application as described above is not limited to the flow cytometry used in the specific embodiments of the present application, and other techniques for distinguishing monocytes and lymphocytes, in combination with fluorescence method, chemiluminescence method, immunohistochemical method, flow cytometry, Western blotting, enzyme-linked immunosorbent assay, and other methods for detecting the expression of CD45 molecules of monocytes and lymphocytes also fall within the scope of the present application.

[0026] In some embodiments, the other techniques for distinguishing monocytes and lymphocytes include, but are not limited to, morphological analysis techniques (e.g., optical microscope observation, electron microscope observation), cytochemical staining techniques (e.g., peroxidase staining, non-specific esterase staining, acid phosphatase staining), immunological analysis techniques (e.g., immunohistochemical technique, immunofluorescence technique), and molecular biology techniques (e.g., gene expression analysis, DNA methylation analysis).

[0027] In the present application, the monocytes originate from hematopoietic stem cells in the bone marrow. In the bone marrow, they develop from pro-monocytes and young monocytes to mature monocytes, and then are released into the blood circulation. The functions of monocytes include phagocytosis, antigen presentation, and secretion of cytokines.

[0028] In the present application, the lymphocytes originate from hematopoietic stem cells in the bone marrow. A part of the hematopoietic stem cells develop into B lymphocytes in the bone marrow, and another part of the hematopoietic stem cells migrate with the blood flow to the thymus, where they develop into T lymphocytes. The lymphocytes are divided into T lymphocytes, B lymphocytes, and natural killer cells (NK cells).

[0029] In some embodiments, the primer or amplification primer refers to a nucleic acid fragment comprising 5-100 nucleotides. In preferred embodiments, the primer or amplification primer comprises 15-30 nucleotides that can initiate an enzymatic reaction (e.g., an enzymatic amplification reaction). In specific embodiments of the present application, the primer refers to a primer that specifically amplifies CD45 of monocytes and lymphocytes.

[0030] In some embodiments, the probe refers to a molecule that binds to a particular sequence or subsequence or other portion of another molecule. In the detailed description of the application, the probe refers to a probe that specifically recognizes monocyte and lymphocyte CD45. Unless otherwise indicated, a probe generally refers to a polynucleotide probe that binds to another polynucleotide (often referred to as a target polynucleotide) through complementary base pairing.

[0031] Depending on the stringency of the hybridization conditions, a probe can bind to a target polynucleotide that lacks perfect sequence complementarity to the probe. Hybridization formats include, but are not limited to, solution phase, solid phase, mixed phase, or in situ hybridization assays. Illustratively, the probe includes a gene-specific DNA oligonucleotide probe, such as a microarray probe immobilized on a microarray substrate, a quantitative nuclease protection assay probe, a probe linked to a molecular barcode, and a probe immobilized on a bead.

[0032] The stringency of a hybridization reaction can be readily determined by one of ordinary skill in the art, and is generally a function of the length of the probe, the temperature of the wash, and the concentration of salt in the wash. Generally, longer probes require higher temperatures for proper annealing, while shorter probes require lower temperatures. Hybridization is often dependent on the ability of the denatured DNA to renature to form stable duplexes when the complementary strands are present in an environment below their melting temperature. The higher the degree of homology between the probe and the hybridizable sequence, the higher the relative temperature that can be used. As a result, it is inferred that higher relative temperatures will tend to make the reaction conditions more stringent, while lower temperatures will make the conditions less stringent.

[0033] In some embodiments, the agent that specifically binds to the monocyte and lymphocyte CD45 protein includes, but is not limited to, an antibody, an affinity protein, and further includes a peptide, an aptamer, and / or a compound that specifically binds to the monocyte and lymphocyte CD45 protein.

[0034] Further, the antibody refers to a specific immunoglobulin directed against an antigenic site, which is well known in the art. The antibody of the present application refers to an antibody that specifically binds to the monocyte and lymphocyte CD45 protein of the present application, which can be produced according to conventional methods in the art. The form of the antibody includes a polyclonal antibody or a monoclonal antibody, an antibody fragment such as a Fab, Fab', F(ab')2, and Fv fragment, a single chain Fv (scFv) antibody, a multispecific antibody such as a bispecific antibody, a monospecific antibody, a monovalent antibody, a chimeric antibody, a humanized antibody, a human antibody, a fusion protein comprising an antigen-binding site of an antibody, and any other modified immunoglobulin molecule comprising an antigen-binding site, as long as the antibody exhibits a desired biological binding activity.

[0035] In some embodiments, the peptide has the ability to bind to a target substance (the monocyte and lymphocyte CD45 protein according to the present application) with high affinity, and does not undergo denaturation during heat or chemical treatment. Also, due to its small size, it can be used as a fusion protein by attaching it to other proteins. Specifically, because it can be specifically attached to a high-molecular protein chain, it can be used as a diagnostic kit and a drug delivery substance.

[0036] In some embodiments, the aptamer refers to a polynucleotide composed of a specific type of single-stranded nucleic acid (DNA, RNA, or modified nucleic acid) that has a stable tertiary structure by itself, and has the property of being able to bind to a target molecule (the monocyte and lymphocyte CD45 protein according to the present application) with high affinity and specificity. As described above, since the aptamer can specifically bind to an antigenic substance like an antibody, but is more stable than a protein, has a simpler structure, and is composed of a polynucleotide that is easy to synthesize, it can be used instead of an antibody.

[0037] In some embodiments, the sample includes any sample collected from a cell, tissue, or body fluid (subject source), wherein the sample includes, but is not limited to: a tissue or cell sample can be derived from a solid tissue of a fresh, frozen, and / or preserved organ or tissue sample, or a biopsy or aspirate, blood or any blood component; a body fluid such as cerebrospinal fluid, amniotic fluid, peritoneal fluid, or interstitial fluid. The tissue sample can be a primary or in vitro cultured cell or cell line. Alternatively, the tissue or cell sample is obtained from a disease tissue / organ. The tissue sample can contain compounds naturally mixed with the tissue, such as preservatives, anticoagulants, buffers, fixatives, nutrients, antibiotics, or similar compounds.

[0038] In some embodiments, the sample includes, but is not limited to: tissue, blood, tissue-derived cells, blood-derived cells, serum, plasma, lymph fluid, synovial fluid, exosomes, cell extracts, fecal matter, urine, saliva, sputum, joint cavity fluid, pleural fluid, peritoneal fluid, lymph fluid, cerebrospinal fluid, uterine fluid, digestive fluid, bile, alveolar bronchial lavage fluid, organs, and any combination thereof, and in a preferred embodiment, the sample is a peripheral blood sample from a subject.

[0039] In the present application, the finding that the relative expression level of monocyte and lymphocyte CD45 molecules is a highly diagnostic indicator for diagnosing infection or differentiating infection types is verified by real clinical samples collected in the present application, which has high accuracy, AUC value, sensitivity and specificity. The diagnostic performance is verified by the receiver operating characteristic curve (ROC), and the area under the curve (AUC) is the area under the ROC curve well known to those skilled in the art, and the determination of the area under the curve (AUC) is helpful for comparing the accuracy of the classifier through the overall data range.

[0040] A classifier with a larger area under the curve (AUC) has a greater ability to accurately classify unknowns between two groups of interest (e.g., disease samples and normal or control samples). In distinguishing between two populations (e.g., disease group and healthy control group), the receiver operating characteristic curve (ROC) is used to graphically represent the performance of a particular feature (e.g., the relative expression level of monocyte and lymphocyte CD45 molecules described in the present application and / or any item of additional biomedical information).

[0041] Generally, the feature data of the entire population (e.g., disease group and control group) is sorted in ascending order based on a single feature value. Then, for each value of the feature, the true positive rate and the false positive rate of the data are calculated. The true positive rate is determined by calculating the number of cases above the value of the feature and dividing by the total number of cases. The false positive rate is determined by calculating the number of control groups above the value of the feature and dividing by the total number of control groups. Although this definition refers to the case where the feature of the patient group is high relative to the control group, it also applies to the case where the feature of the patient group is low relative to the control group (in which case the number of samples below the value of the feature can be calculated).

[0042] The receiver operating characteristic curve (ROC) can be generated for other single calculations, and for single properties in order to provide a single sum value, for example, two or more properties can be mathematically combined (e.g., addition, subtraction, multiplication, etc.), which can be represented by the receiver operating characteristic curve (ROC). Additionally, combinations of multiple properties that can derive a single calculation value can be plotted in the receiver operating characteristic curve (ROC). These property combinations can constitute a test. The receiver operating characteristic curve (ROC) is a graph representing the true positive rate (sensitivity) of a test relative to the false positive rate (1-specificity) of the test.

[0043] The second aspect of the present application provides a diagnostic product for diagnosing infection or identifying the type of infection.

[0044] Further, the diagnostic product comprises the reagent of the first aspect of the present application.

[0045] Further, the diagnostic product is a detection kit, a detection chip and / or a detection test strip.

[0046] In some embodiments, the detection kit comprises primers, probes, chips or specific binding proteins that specifically bind to CD45 of monocytes and lymphocytes. In some embodiments, the detection kit can further comprise containers, instructions for use, positive controls, negative controls, buffers, adjuvants or solvents. For example, one or more of solutions for suspending or fixing cells, detectable labels or markers, solutions for lysing cells, etc.

[0047] In some embodiments, the detection kit can further be accompanied by instructions for use of the detection kit, which describe how to use the detection kit provided by the present application to perform detection, and how to use the results of the detection to determine whether the subject is infected and the type of infection.

[0048] In some embodiments, the detection chip comprises a solid support, probes or specific antibodies or ligands against CD45 of monocytes and lymphocytes that specifically recognize CD45 of monocytes and lymphocytes attached to the solid support. In some embodiments, the solid support used to prepare the detection chip of the present application comprises various materials commonly used in the field of gene chips or protein chips, including but not limited to nylon membranes, glass or silicon sheets modified with active groups such as aldehyde groups, amino groups, etc., unmodified glass sheets, plastic sheets, etc. In some embodiments, the detection chip comprises a gene chip or a protein chip.

[0049] In some embodiments, the gene chip comprises a solid support, and oligonucleotide probes that specifically correspond to part or all of the sequence of CD45 of monocytes and lymphocytes are fixed in order on the solid support. The protein chip comprises a solid support, and specific antibodies or ligands against CD45 of monocytes and lymphocytes are fixed on the solid support, etc. The solid support can be made of various materials commonly used in the field of chips, including but not limited to plastic products, microparticles, membrane supports, etc.

[0050] In some embodiments, the detection test strip comprises a sample pad, a conjugate pad, a nitrocellulose membrane, and an absorbent pad.

[0051] Exemplarily, the sample pad is usually made of glass fiber or the like, for dropping the biological sample (e.g. peripheral blood) to be detected, so that the sample can be rapidly absorbed and spread to other areas. The conjugate pad generally contains a label such as colloidal gold, fluorescent microspheres or the like, which is combined with a specific antibody against CD45 molecules of mononuclear cells and lymphocytes in advance. When the sample passes through the conjugate pad, the CD45 molecules in the sample can specifically bind to the label combined with the antibody. The nitrocellulose membrane is the core part of the test strip, and usually has a detection line (T line) and a control line (C line) drawn thereon. The detection line is fixed with an antibody capable of specifically binding to CD45 molecules, and the control line is fixed with a substance capable of binding to the label of the labeled antibody. When the sample solution containing the label combined with the CD45 molecules of mononuclear cells and lymphocytes flows to the detection line, the CD45 molecules are captured by the antibody on the detection line, so that the label is aggregated and colored at the detection line; and the control line is used to verify the effectiveness of the test strip, and the label will be combined with the substance on the control line to be colored, regardless of whether the sample contains CD45 molecules or not. The absorbent pad is generally made of an absorbent material and located at the end of the test strip, which functions to absorb the liquid passing through the nitrocellulose membrane, so that the liquid can flow in one direction on the test strip continuously, ensuring the smooth progress of the detection process.

[0052] The third aspect of the present application provides the use of a reagent for detecting the relative expression level of CD45 molecules of mononuclear cells and lymphocytes in a sample in the preparation of a system and / or device for diagnosing infection or differentiating infection types.

[0053] In the present application, the system and / or device is a method for distinguishing different levels of different components, elements, parts, portions or assemblies. However, if other words can achieve the same purpose, the words can be replaced by other expressions. Those skilled in the art of the technical field to which the present application pertains are fully aware that the present application can be implemented as an apparatus, a method or a computer program product. Therefore, the disclosure of the present application can be embodied in the form of an entirely hardware, an entirely software (including firmware, resident software, microcode, etc.) or a combination of hardware and software. In addition, in some specific embodiments, the present application can also be embodied in the form of a computer program product in one or more computer readable media, which contains computer readable program codes.

[0054] Any combination of one or more computer readable medium can be employed. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. In the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program used, or that can be used by, the instruction execution system, apparatus, or device.

[0055] In addition, the present application also provides a method for diagnosing infection or identifying infection type, the method comprising:

[0056] obtaining the relative expression level data of CD45 molecules of monocytes and lymphocytes in the sample to be tested;

[0057] performing classification prediction based on the relative expression level data of CD45 molecules of monocytes and lymphocytes to obtain the classification result of whether the sample to be tested is accompanied by infection or the type of infection.

[0058] The classification result is obtained based on a prediction model;

[0059] The method for constructing the prediction model comprises: obtaining the relative expression level data of CD45 molecules of monocytes and lymphocytes and the corresponding clinical characteristics of the sample in the training set, the clinical characteristics including healthy people, infected patients (including viral infection patients and bacterial infection patients), viral infection patients, and bacterial infection patients; extracting the relative expression level data of CD45 molecules of monocytes and lymphocytes in the training set to input a machine learning model to construct a prediction model, obtaining the constructed prediction model, and generating a corresponding threshold value.

[0060] In some embodiments, the machine learning model comprises a linear regression model, a logistic regression model, a random forest model, a Lasso regression model, a neural network model, a decision tree model, a perception model, a support vector machine model, and / or a naive Bayes model.

[0061] Further, the relative expression level of CD45 molecules of monocytes and lymphocytes comprises the ratio of the expression level of CD45 molecules of monocytes and lymphocytes, the ratio of the expression level of CD45 molecules of lymphocytes and monocytes, the difference between the expression level of CD45 molecules of monocytes and lymphocytes, and / or the difference between the expression level of CD45 molecules of lymphocytes and monocytes.

[0062] Further, the sample to be tested is a peripheral blood sample, a tissue sample, a serum sample, a plasma sample, a cell sample, a urine sample, and / or an exosome sample derived from a subject.

[0063] The fourth aspect of the present application provides a system for diagnosing infection or identifying infection type.

[0064] Further, the system comprises a processor, an input module, an output module;

[0065] The processor is configured to perform logical operation on the inputted information by bioinformatics method; the input module is configured to input the relative expression level of CD45 molecule in monocytes and lymphocytes in the sample of the subject; the computer readable medium comprising instructions which, when executed by the processor, performs an algorithm on the inputted relative expression level of CD45 molecule in monocytes and lymphocytes; and the output module is configured to output whether the subject is accompanied by infection, the type of infection accompanied or the risk of infection accompanied.

[0066] In some embodiments, the system comprises:

[0067] The data acquisition unit is configured to acquire the data of the relative expression level of CD45 molecule in monocytes and lymphocytes in the sample to be tested;

[0068] The analysis and prediction unit is configured to perform classification prediction based on the data of the relative expression level of CD45 molecule in monocytes and lymphocytes, to obtain the classification result of whether the sample to be tested is accompanied by infection or the type of infection accompanied.

[0069] The classification result is obtained based on a prediction model;

[0070] The method for constructing the prediction model comprises: acquiring the data of the relative expression level of CD45 molecule in monocytes and lymphocytes in the training set sample and the corresponding clinical characteristics of the sample, the clinical characteristics including healthy people, infected patients (including viral infection patients and bacterial infection patients), viral infection patients, bacterial infection patients, extracting the data of the relative expression level of CD45 molecule in monocytes and lymphocytes in the training set to input a machine learning model to construct a prediction model, obtaining the constructed prediction model, and generating a corresponding threshold value.

[0071] In some embodiments, the machine learning model comprises a linear regression model, a logistic regression model, a random forest model, a Lasso regression model, a neural network model, a decision tree model, a perception model, a support vector machine model and / or a naive Bayes model.

[0072] Further, the relative expression level of CD45 molecule in monocytes and lymphocytes comprises the ratio of the expression level of CD45 molecule in monocytes and lymphocytes, the ratio of the expression level of CD45 molecule in lymphocytes and monocytes, the difference of the expression level of CD45 molecule in monocytes and lymphocytes, and / or the difference of the expression level of CD45 molecule in lymphocytes and monocytes.

[0073] Further, the sample to be tested is a peripheral blood sample, a tissue sample, a serum sample, a plasma sample, a cell sample, a urine sample and / or an exosome sample derived from a subject.

[0074] Further, the present application also provides an electronic device comprising a memory and a processor; the memory is used to store program instructions; the processor is used to invoke the program instructions, when the program instructions are executed, to perform the steps of the method for diagnosing infection or identifying infection type as described above.

[0075] Further, the present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method for diagnosing infection or identifying infection type as described above.

[0076] Further, the present application also provides an index for diagnosing whether a subject is accompanied by an infection, an infection type or a risk of infection, and the index is a relative expression level of CD45 molecules of monocytes and lymphocytes.

[0077] Further, the relative expression level of CD45 molecules of monocytes and lymphocytes comprises a ratio of expression levels of CD45 molecules of monocytes and lymphocytes, a ratio of expression levels of CD45 molecules of lymphocytes and monocytes, a difference of expression levels of CD45 molecules of monocytes and lymphocytes, and / or a difference of expression levels of CD45 molecules of lymphocytes and monocytes.

[0078] Further, the present application also provides a method for diagnosing whether a subject is accompanied by an infection, an infection type or a risk of infection, and the method comprises the following steps:

[0079] (1) collecting a sample derived from a subject in need;

[0080] (2) detecting a relative expression level of CD45 molecules of monocytes and lymphocytes in the sample derived from the subject;

[0081] (3) determining whether the subject is accompanied by an infection, an infection type or a risk of infection according to the detected relative expression level of CD45 molecules of monocytes and lymphocytes in the sample derived from the subject.

[0082] Further, the relative expression level of CD45 molecules of monocytes and lymphocytes comprises a ratio of expression levels of CD45 molecules of monocytes and lymphocytes, a ratio of expression levels of CD45 molecules of lymphocytes and monocytes, a difference of expression levels of CD45 molecules of monocytes and lymphocytes, and / or a difference of expression levels of CD45 molecules of lymphocytes and monocytes.

[0083] Further, the infection is whether accompanied by bacterial or viral infection; the type of infection accompanied is whether the infection is bacterial infection or viral infection; the risk of infection accompanied is the risk of bacterial or viral infection, the risk of bacterial infection or the risk of viral infection.

[0084] In some embodiments, the subject refers to any animal, and also refers to human and non-human animals. Non-human animals include all vertebrates, for example, mammals, such as non-human primates (especially higher primates), sheep, dogs, rodents (e.g., mice or rats), guinea pigs, goats, pigs, cats, rabbits, cows, and any livestock or pets; and non-mammals, such as chickens, amphibians, reptiles, etc. In a preferred embodiment, the subject is a human.

[0085] Compared with the prior art, the present application has the advantages and beneficial effects as follows:

[0086] (1) The present application first creatively finds that the ratio of peripheral blood mononuclear cell and lymphocyte CD45 molecule expression level can quickly and effectively determine whether the patient is accompanied by infection, and effectively distinguish viral infection or bacterial infection. The present application finds that the relative change of mononuclear cell and lymphocyte CD45 molecule expression in the collected clinical samples has high diagnostic efficiency for determining whether the patient is accompanied by infection or distinguishing viral infection or bacterial infection, and the AUC value is as high as 0.9994, the sensitivity and specificity are high, which can be used to guide clinical treatment decision and antibiotic use, and for early screening, prevention, treatment and post-treatment monitoring of infection, and has important transformation significance.

[0087] (2) The present application only uses the ratio of mononuclear cell and lymphocyte CD45 molecule expression level to determine whether the subject has infection inflammation and effectively distinguish bacterial infection and viral infection, which is simple and fast in operation and easy to automate. Compared with the conventional CD64 infection index of the same type commonly used by those skilled in the art, it is more effective in distinguishing the type of infection, especially for the judgment of the type of infection of fever clinic patients, which has high application value for assisting clinicians to quickly and accurately determine infection and infection type and guide antibiotic use. BRIEF DESCRIPTION OF DRAWINGS

[0088] Figure 1 : The result figure of setting gate for peripheral blood mononuclear cells and lymphocytes of healthy examination, bacterial and viral infection patients according to CD45 / SSA;

[0089] Figure 2 : The result figure of CD45 protein expression change of peripheral blood mononuclear cells and lymphocytes of healthy examination, bacterial and viral infection patients;

[0090] Figure 3 Figure 1: Change in CD45 MFI on monocytes and ROC curve results in the screening cohort for patients with bacterial and viral infections.

[0091] Figure 4 Figure 2: Change in CD45 MFI on lymphocytes and ROC curve results in the screening cohort for patients with bacterial and viral infections.

[0092] Figure 5 Figure 3: Change in CD45 MFI monocyte / lymphocyte ratio and ROC curve results in the exploration cohort for patients with bacterial and viral infections.

[0093] Figure 6 Figure 4: Change in CD45 MFI monocyte / lymphocyte ratio and ROC curve results in the validation cohort for patients with bacterial and viral infections.

[0094] Figure 7 Figure 5: Change in CD64 MFI on neutrophils and ROC curve results in the screening cohort for patients with bacterial and viral infections. DETAILED DESCRIPTION

[0095] The application will be further described below in connection with specific embodiments, which are merely illustrative of the application and should not be understood as limiting the application. It can be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the application, and the scope of the application is defined by the claims and their equivalents.

[0096] The reagents and raw materials used in the application are readily available to those skilled in the art, and can be obtained commercially if not otherwise specified. The experimental methods of the application are generally carried out according to conventional conditions or according to the conditions recommended by the manufacturer. In particular, the following examples are only used to illustrate the application and should not be used to limit the scope of the application in any way. It should be noted that the experimental conditions and results described in the following examples are only used to illustrate the application and should not and will not limit the application as described in detail in the claims.

[0097] Example: Screening and validation of biomarkers for diagnosis of infection and inflammation (relative change in CD45 molecule expression on monocytes and lymphocytes)

[0098] 1. Experimental materials

[0099] (1) Antibodies:

[0100] PE / Cyanine7 Anti-Human CD45 Antibody[HI30](Elabscience, Cat No: E-AB-F1137H), the antibody of HI30 clone number recognizes all subtypes of human CD45 molecules;

[0101] Pacific Blue TM anti-human CD14 antibody(Biolegend, Cat No: 367122);

[0102] APC Anti-human CD64 antibody[10.1](Elabscience, Cat No: E-AB-F1082E).

[0103] (2) Red blood cell lysate: OptiLyse C Lysing Solution(Beckmann, A11895).

[0104] (3) Flow cytometry analyzer: DxFLEX(Beckmann) or BD Lyric.

[0105] 2. Experimental method

[0106] Inclusion of healthy people, virus infection patients(including influenza A virus, influenza B virus, coronavirus, respiratory syncytial virus, adenovirus, parainfluenza virus I-III, rhinovirus, herpes virus(EB virus, cytomegalovirus, etc.) and enterovirus(norovirus, rotavirus, etc.) and human papillomavirus infection patients, nucleic acid detection positive or virus copy number exceeding threshold) and bacterial infection patients(culture positive, including gram-positive bacteria and gram-negative bacteria), take 100 μL of EDTA or sodium citrate anticoagulated peripheral blood whole blood, respectively add PE / Cyanine7 Anti-Human CD45 Antibody, APC Anti-human CD64 antibody and Pacific Blue TMAnti-human CD14 antibody 2 μL each, shake well, incubate at room temperature for 20 minutes in the dark, add 2 mL of red blood cell lysate, shake well, incubate in the dark for 15 minutes. Centrifuge at 2000 rpm for 3 minutes, remove the supernatant, resuspend the cells, add 2 mL of phosphate buffered saline or normal saline, centrifuge at 2000 rpm for 3 minutes, discard the supernatant, resuspend the cell pellet with phosphate buffered saline, and analyze on a flow cytometer (Beckman DxFLEX type). During flow cytometry analysis, according to the FSC / SSC scatter plot, gate the white blood cells, and according to the SSC / CD45 scatter plot, gate the lymphocytes, monocytes and neutrophils, or according to the SSC / CD14 scatter plot, gate the monocytes, and use FlowJo or other software to respectively count the mean fluorescence intensity (MFI) or Geometric Mean of CD45 molecules of monocytes and lymphocytes, calculate the neutrophil CD64 infection index and the CD45 index (CD45 MFI monocytes / CD45 MFI lymphocytes) described in the present application.

[0107] In this embodiment, the peripheral blood samples collected from healthy subjects, the peripheral blood samples from patients with bacterial infection and the peripheral blood samples from patients with viral infection are randomly divided into a screening cohort, an exploration cohort and a validation cohort. In the screening cohort, the ratio of healthy subjects to patients with bacterial infection to patients with viral infection is 50:109:227; in the exploration cohort, the ratio of healthy subjects to patients with bacterial infection to patients with viral infection is 40:61:80; and in the validation cohort, the ratio of healthy subjects to patients with bacterial infection to patients with viral infection is 77:96:193.

[0108] 3. Experimental results

[0109] According to the results of gating healthy subjects, bacterial and viral infection patients peripheral blood monocytes and lymphocytes by CD45 / SSA as shown in Figure 1 , the changes of CD45 protein expression of healthy subjects, bacterial and viral infection patients peripheral blood monocytes and lymphocytes are as shown in Figure 2 .

[0110] In the screening cohort, the changes of CD45 MFI of peripheral blood monocytes of patients with bacterial and viral infection and the results of ROC curve are as shown in Figure 3As shown, the results show that the peripheral blood mononuclear cell CD45 MFI of the bacterial and viral infection patients presents significant differential expression relative to the peripheral blood mononuclear cell CD45 MFI of the healthy subjects, and it has high diagnostic efficiency as a biomarker for diagnosing bacterial infection, viral infection, infected patients or identifying the infection type (bacterial infection or viral infection), has high AUC value, and has high sensitivity and specificity, wherein the expression level of peripheral blood mononuclear cell CD45 has an AUC value as high as 0.8679 for diagnosing bacterial infection (healthy VS bacterial infection), a sensitivity of 80.8%, and a specificity of 92.9%; the expression level of peripheral blood mononuclear cell CD45 has an AUC value as high as 0.9219 for diagnosing viral infection (healthy VS viral infection), a sensitivity of 86.6%, and a specificity of 96.4%; the expression level of peripheral blood mononuclear cell CD45 has an AUC value as high as 0.9064 for diagnosing infected patients (healthy VS infected patients), a sensitivity of 86.4%, and a specificity of 92.9%.

[0111] In the screening cohort, the changes of peripheral blood lymphocyte CD45 MFI of the bacterial and viral infection patients and the ROC curve results thereof are as shown in the following table and figure: Figure 4 As shown, the results show that the peripheral blood lymphocyte CD45 MFI of the bacterial and viral infection patients presents differential expression relative to the peripheral blood lymphocyte CD45 MFI of the healthy subjects, however, it has low diagnostic efficiency as a biomarker for diagnosing bacterial infection, viral infection, infected patients or identifying the infection type (bacterial infection or viral infection), and the AUC value is less than 0.7000, it can be seen that the expression level of peripheral blood lymphocyte CD45 alone cannot be used as an effective biomarker for diagnosing bacterial infection, viral infection, infected patients or identifying the infection type (bacterial infection or viral infection), and it is unpredictable for those skilled in the art based on the prior art whether it has better diagnostic efficiency when combined with peripheral blood mononuclear cell CD45 for diagnosing bacterial infection, viral infection, infected patients or identifying the infection type (bacterial infection or viral infection), and how to combine it with peripheral blood mononuclear cell CD45 for diagnosing bacterial infection, viral infection, infected patients or identifying the infection type (bacterial infection or viral infection) to have better diagnostic efficiency.

[0112] In the exploration cohort, the changes of CD45 MFI monocyte / lymphocyte ratio in the bacterial and viral infection patient exploration cohort and the ROC curve results thereof are as shown in the following table and figure: Figure 5As shown, the results show that the peripheral blood CD45 MFI monocyte / lymphocyte ratio of the bacterial and viral infection patients presents significant differential expression relative to the peripheral blood CD45 MFI monocyte / lymphocyte ratio of the healthy subjects, and it has high diagnostic efficiency as a biomarker for diagnosing bacterial infection, viral infection, infected patients or identifying the type of infection (bacterial infection or viral infection), has high AUC value, and has high sensitivity and specificity, wherein the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for diagnosing bacterial infection (healthy VS bacterial infection) is as high as 0.9734, the sensitivity is 91.8%, and the specificity is 95.0%; the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for diagnosing viral infection (healthy VS viral infection) is as high as 0.9994, the sensitivity is 97.5%, and the specificity is 100%; the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for identifying the type of infection (bacterial infection VS viral infection) is as high as 0.918, the sensitivity is 85.0%, and the specificity is 90.2%; the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for diagnosing infected patients (healthy VS infected patients) is as high as 0.9881, the sensitivity is 95.0%, and the specificity is 97.5%.

[0113] Among them, the data distribution and the best cut-off value of the CD45 MFI monocyte / lymphocyte ratio in the exploration cohort are shown in Table 1 and Table 2 below.

[0114] Table 1 Data distribution of exploration cohort

[0115] Group Healthy Bacterial infection Viral infection Number 40 61 80 Minimum 0.3434 0.4871 0.751 Maximum 0.7929 1.586 2.212 Mean 0.4776 0.8543 1.304 Std 0.08344 0.1967 0.2662

[0116] Table 2 Best cut-off value of exploration cohort

[0117] Comparison Best cut-off value Healthy vs bacterial infection 0.589 Healthy vs viral infection 0.818 Bacterial infection vs viral infection 1.025 Healthy vs infected (bacterial or viral) 0.606

[0118] In the validation cohort, the changes of the CD45 MFI monocyte / lymphocyte ratio in the bacterial and viral infection patient validation cohort and the ROC curve results are as follows Figure 6As shown, the results show that the peripheral blood CD45 MFI monocyte / lymphocyte ratio of the bacterial and viral infection patients presents significant differential expression relative to the peripheral blood CD45 MFI monocyte / lymphocyte ratio of the healthy subjects, and has high diagnostic efficiency as a biomarker for diagnosing bacterial infection, viral infection, an infection patient or identifying the infection type (bacterial infection or viral infection), with high AUC value, high sensitivity and high specificity, wherein the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for diagnosing bacterial infection (healthy VS bacterial infection) is as high as 0.9556, the sensitivity is 96.1%, and the specificity is 89.6%; the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for diagnosing viral infection (healthy VS viral infection) is as high as 0.9988, the sensitivity is 100%, and the specificity is 99.5%; the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for identifying the infection type (bacterial infection VS viral infection) is as high as 0.8933, the sensitivity is 82.3%, and the specificity is 82.9%; the AUC value of the peripheral blood CD45 MFI monocyte / lymphocyte ratio for diagnosing an infection patient (healthy VS infection patient) is as high as 0.9845, the sensitivity is 100%, and the specificity is 94.1%.

[0119] The data distribution of the CD45 MFI monocyte / lymphocyte ratio in the verification cohort and the diagnostic efficiency evaluation results of the best cut-off value of the exploration cohort in the verification cohort are shown in Table 3 and Table 4, respectively. The results again prove that the CD45 MFI monocyte / lymphocyte ratio provided by the present application can be used as an effective biomarker for diagnosing bacterial infection, viral infection, an infection patient or identifying the infection type (bacterial infection or viral infection), with high accuracy, sensitivity and specificity.

[0120] Table 3 Data distribution in the verification cohort

[0121] Group Healthy Bacterial infection Viral infection Number 77 96 193 Minimum 0.3311 0.4342 0.5666 Maximum 0.6404 1.472 4.642 Mean 0.5164 0.8406 1.246 Std 0.0662 0.2006 0.34

[0122] Table 4 Diagnostic efficiency evaluation of the best cut-off value of the exploration cohort in the verification cohort

[0123]

[0124] Comparative Example Comparison of the diagnostic efficiency of the monocyte and lymphocyte CD45 molecular expression relative change index provided by the present application and the CD64 infection index commonly used as a biomarker of pathogenic infection in the prior art for diagnosing infection

[0125] It is well known in the art that the neutrophil CD64 infection index is a sensitive indicator for assessing infection or inflammatory response based on the expression level of CD64 receptors on the surface of neutrophils. CD64 is a high-affinity Fc gamma receptor on the surface of neutrophils, and its expression is significantly up-regulated during infection and inflammatory response. Therefore, the expression level of CD64 is often used as a biomarker for pathogenic infection.

[0126] Principle of CD64 infection index: CD64 receptor is an immune receptor on the surface of neutrophils, and its expression level is low under normal circumstances, but it significantly increases during bacterial infection or immune activation. This up-regulated CD64 level helps neutrophils recognize and eliminate pathogens. In the state of infection, the up-regulation of CD64 not only enhances the phagocytic ability of neutrophils, but also activates the function of neutrophils by binding with immune complexes, including the release of cytokines and chemokines, etc.

[0127] Method for calculating neutrophil CD64 index: the average fluorescence intensity data of CD64 expression of neutrophils, monocytes and lymphocytes in adult samples are substituted into the following formula to calculate the neutrophil CD64 index of the sample, and finally the detection result is obtained according to the reference range.

[0128]

[0129] In order to further verify that the relative change of CD45 molecule expression of monocytes and lymphocytes provided by the present application can be used for accurate diagnosis of infection, the present comparative example verifies the diagnostic efficiency of the conventional index for diagnosing infection, i.e. neutrophil CD64 infection index, for diagnosing infection in the screening cohort collected by the present application. The changes of neutrophil CD64 infection index in peripheral blood of bacterial and viral infection patients and the ROC curve results are as follows: Figure 7As shown, the results show that there is no significant difference in the peripheral blood neutrophil CD64 infection index of the virus infected patients relative to the peripheral blood neutrophil CD64 infection index of the healthy subjects, and it cannot be used as an effective biomarker for diagnosing viral infection and infected patients, and the AUC values are low, being 0.4691 and 0.6452 respectively, and the sensitivity and specificity are also low, and in addition, the AUC value of using it as a biomarker for diagnosing bacterial infection or identifying the type of infection (bacterial infection or viral infection) is also significantly lower than the index of the relative change of the CD45 molecular expression of monocytes and lymphocytes provided by the present application, and the above results show that the index of the relative change of the CD45 molecular expression of monocytes and lymphocytes provided by the present application can be used in the accurate diagnosis of infection, and its diagnostic performance is significantly better than the neutrophil CD64 infection index disclosed in the prior art, which is a conventional index for infection diagnosis, and a technical effect that cannot be expected by those skilled in the art according to the content disclosed in the prior art is achieved.

Claims

1. Use of a reagent for detecting relative expression level of monocyte and lymphocyte CD45 protein in a sample in the preparation of a product for diagnosing infection or differentiating infection type; the relative expression level of monocyte and lymphocyte CD45 protein is the ratio of the expression level of monocyte and lymphocyte CD45 protein, or the ratio of the expression level of lymphocyte and monocyte CD45 protein; the diagnosing infection is diagnosing whether a subject has viral infection or diagnosing whether a subject has bacterial infection; the differentiating infection type is differentiating viral infection and bacterial infection.

2. Use according to claim 1, characterized in that, the reagent is an affinity protein specifically binding monocyte and lymphocyte CD45 protein.

3. Use according to claim 2, characterized in that, the affinity protein is an antibody or a receptor specifically binding monocyte and lymphocyte CD45 protein.

4. Use according to claim 2, characterized in that, the affinity protein is an antibody functional fragment specifically binding monocyte and lymphocyte CD45 protein.

5. Use according to claim 2, characterized in that, the affinity protein is a conjugated antibody specifically binding monocyte and lymphocyte CD45 protein.

6. Use according to claim 1, characterized in that, the sample is a peripheral blood sample, a tissue sample, a serum sample, a plasma sample, a cell sample, a urine sample and / or an exosome sample derived from a subject.

7. Use of a reagent for detecting relative expression level of monocyte and lymphocyte CD45 protein in a sample in the preparation of a system and / or device for diagnosing infection or differentiating infection type; the relative expression level of monocyte and lymphocyte CD45 protein is the ratio of the expression level of monocyte and lymphocyte CD45 protein, or the ratio of the expression level of lymphocyte and monocyte CD45 protein; the diagnosing infection is diagnosing whether a subject has viral infection or diagnosing whether a subject has bacterial infection; the differentiating infection type is differentiating viral infection and bacterial infection.

8. A system for diagnosing an infection or differentiating a type of infection, characterized in that, the system comprises a processor, an input module and an output module; wherein the processor is used for logical operation on input information by bioinformatics method; the input module is used for inputting relative expression level of monocyte and lymphocyte CD45 protein in a sample of a subject, computer readable medium comprising instructions which, when executed by the processor, perform an algorithm on the inputted relative expression level of monocyte and lymphocyte CD45 protein; the output module is used for outputting whether a subject is accompanied by viral infection, bacterial infection or the infection type is viral infection or bacterial infection; the relative expression level of monocyte and lymphocyte CD45 protein is the ratio of the expression level of monocyte and lymphocyte CD45 protein, or the ratio of the expression level of lymphocyte and monocyte CD45 protein.

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