Application of marker combination in prediction or diagnosis of gout

Abstract

The invention discloses an application of a marker combination in prediction or diagnosis of gout, the marker combination comprises an immune cell subset and clinical data, and the immune cell subset comprises virus-specific cytotoxic NK cells and inhibitory Vdelta2 cells. The marker combination comprises immune cell subgroups and clinical data, different immune cell subgroups are matched with different clinical data when a gout attack stage and a gout remission stage are distinguished, or when the gout remission stage and a healthy subject are distinguished, and high-sensitivity and high-specificity diagnosis results are achieved. Therefore, the marker combination disclosed by the invention has a wide prospect in the aspect of predicting different processes of gout, and can provide more basic research data for health management of gout high-risk people.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine, and in particular to the application of a marker combination in predicting or diagnosing gout. Background Art

[0002] Gout is a crystal-related arthritis caused by the deposition of monosodium urate (MSU) in the joints. It is directly related to hyperuricemia caused by purine metabolism disorders and / or reduced uric acid excretion. Hyperuricemia is an important pathological basis for the occurrence of gout. With the change of dietary structure, the prevalence of gout has been increasing year by year, and the age of onset tends to be younger. It has become the second largest metabolic disease after diabetes, and the incidence rate in coastal and plateau areas is higher than that in inland areas. In addition to causing gout, elevated blood uric acid levels are also related to the occurrence and development of systemic diseases such as kidneys, endocrine metabolism, and cardiovascular and cerebrovascular diseases. Gout is a common and complex type of arthritis. The deposition of MSU crystals in joints and tissues can cause systemic inflammation and tissue damage. In the remission period after a gout attack, patients may still experience relapses despite uric acid-lowering treatment and urine alkalinization. Therefore, it is still challenging in clinical practice to effectively predict the risk of relapse in gout patients and accurately assess whether gout patients are completely relieved.

[0003] Hyperuricemia (HUA) is a possible prerequisite for gouty arthritis. Nearly 90% of HUA is caused by impaired renal uric acid excretion, and about 10% is caused by excessive uric acid secretion. Under the influence of HUA, uric acid exceeds the physiological dissolution threshold in the body and is prone to form MSU crystals. Although MSU crystal deposition in the joints can lead to the onset of gouty arthritis, many people with severe HUA or MSU crystal deposition do not have gout attacks, which means that gout attacks are not inevitable.

[0004] In the past two decades, immune cells have been identified as key factors in gout attacks, and some progress has been made in the study of innate immunity in gout inflammation. MSU crystals deposited in joints activate macrophages, neutrophils, and monocytes, which release cytokines such as TNF-α, IL-1β, and IL-6 through the NLRP3 inflammasome pathway. These inflammatory factors will further recruit and activate more monocytes and neutrophils, which secrete more proinflammatory cytokines, triggering a cascade of inflammatory responses and ultimately triggering gout attacks.

[0005] Considering the importance of immune cells in immune homeostasis and their potential role in the progression and recovery of gout, as well as the fact that studying each cell individually may involve interference from other subsets, it is necessary to study the distribution and function of immune cell subsets in gout attacks. At present, there is no unified laboratory standard related to peripheral blood lymphocyte subsets for effectively predicting the risk of recurrence in gout patients and accurately evaluating the complete remission of gout patients; the industry has not conducted a comprehensive discussion and analysis of the lymphocyte spectrum in gout patients. Therefore, there is an urgent need for a solution that integrates the distribution information of lymphocyte subsets in healthy people, patients with acute gout attacks, and patients in remission of gout, and can effectively predict the risk of gout recurrence and accurately evaluate the complete remission of gout. Summary of the invention

[0006] In order to solve the above technical problems, the present invention discloses an application of a marker combination in predicting or diagnosing gout, the marker combination including immune cell subsets and clinical data, the immune cell subsets including virus-specific cytotoxic NK cells and inhibitory Vδ2 cells. The marker combination of the present invention includes immune cell subsets and clinical data, and different immune cell subsets are used to match different clinical data when distinguishing gout attacks from gout remission, or when distinguishing gout remission from healthy subjects, to achieve high sensitivity and high specificity diagnostic results, so the marker combination of the present invention has broad prospects in predicting different processes of gout, and can provide more basic research data for the health management of people at high risk of gout.

[0007] First, on one hand, the present invention provides an application of a marker combination in the preparation of a drug for predicting and / or diagnosing gout, wherein the marker combination includes immune cell subpopulations and clinical data, and the immune cell subpopulations include one or more of T cell subpopulations, γδT subpopulations, B cell subpopulations and NK cell subpopulations.

[0008] In a preferred embodiment, the NK cell subpopulation includes virus-specific cytotoxic NK cells, and / or naive NK cells.

[0009] In a preferred embodiment, the T cell subsets include one or more of the following: non-activated terminally differentiated virus-specific CD8 + T cells, peripheral helper T cells, activated Tfh cells, total memory CD8 T cells;

[0010] In a preferred embodiment, the γδT subset includes suppressive Vδ1 cells and / or suppressive Vδ2 cells.

[0011] In a preferred embodiment, the immune cell subpopulation includes virus-specific cytotoxic NK cells and inhibitory Vδ2 cells.

[0012] In a preferred embodiment, the gout is a gout attack or a gout remission, i.e., different stages of gout progression.

[0013] In a preferred embodiment, the immune cell subset also includes non-activated terminally differentiated virus-specific CD8 + T cells, activated Tfh cells, and suppressive Vδ1 cells.

[0014] In a preferred embodiment, when the drug is used to distinguish between subjects with gout attack and subjects with gout remission, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells;

[0015] In a preferred embodiment, when the drug is used to distinguish between gout remission subjects and healthy subjects, the immune cell subpopulations include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells and activated Tfh cells;

[0016] Preferably, the immune cell subpopulation further includes: one or more of peripheral helper T cells, total memory CD8 T cells and naive NK cells.

[0017] In a preferred embodiment, when the drug is used to distinguish between subjects with gout attacks and subjects in gout remission, the clinical data include one or more of the subject's white blood cell level, platelet level, lymphocyte level, eosinophil level, basophil level and glomerular filtration rate level.

[0018] In a preferred embodiment, when the drug is used to distinguish between gout remission subjects and healthy subjects, the clinical data include one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

[0019] In a specific embodiment, when the drug is used to distinguish between subjects with gout attack and subjects with gout remission, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells, and at the same time the clinical data include the subject's white blood cell level, platelet level, lymphocyte level, eosinophil, basophil and glomerular filtration rate level.

[0020] In a specific embodiment, when the drug is used to distinguish between gout remission subjects and healthy subjects, the immune cell subpopulations include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells and activated Tfh cells; and at the same time, the clinical data include one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

[0021] In a preferred embodiment, the immune cell subpopulations are labeled using different antibodies.

[0022] The antibodies of the present invention are shown in Table 3 below.

[0023] In a preferred embodiment, the antibody markers of the immune cell subpopulations are shown in Table 1-1 to Table 1-4.

[0024] In a specific embodiment, if different antibody markers are used to represent the immune cell subsets, the virus-specific cytotoxic NK cells are CD3 - CD56 + NKP46 + Virus-specific cytotoxic NK cells, wherein the naive NK cells are CD3 - CD56 bright Naive NK cells, the non-activated terminally differentiated virus-specific CD8 + T cells are CD3 + CD8 + CD45RA + CCR7 - CD127 + Non-activated terminally differentiated virus-specific CD8 + T cells, wherein the peripheral helper T cells are CD3 + CD4 + CXCR5 - PD-1 + Peripheral helper T cells, the activated Tfh cells are CD3 + CD4 + CXCR5 + PD-1 + Activated Tfh cells, the total memory CD8 T cells are CD3 + CD8 + HLA-DR + Total memory CD8 T cells, the suppressive Vδ1 cells are CD3 + γδT + Vδ1 + PD-1 + Suppressive Vδ1 cells, or, the suppressive Vδ2 cells are CD3+ γδT + Vδ2 + PD-1 + Suppressive Vδ2 cells.

[0025] Secondly, another aspect of the present invention provides an application of a reagent for determining a marker combination in the preparation of a kit for determining the gout progression of a subject, wherein the gout progression of the subject is divided into: gout attack period, gout remission period and healthy period, and the marker combination is defined as in the application described in one aspect of the present invention, and the kit has the function of the drug described in the application described in one aspect of the present invention.

[0026] That is, the use of a reagent for determining a marker combination described in the present invention in the preparation of a kit for determining the progression of gout in a subject refers to: the use of a reagent for determining a marker combination including immune cell subpopulations and clinical data in the preparation of a kit for determining the progression of gout in a subject, wherein the immune cell subpopulations include virus-specific cytotoxic NK cells and inhibitory Vδ2 cells.

[0027] In a preferred embodiment, when the kit is used to determine whether a subject is in a gout attack or gout remission period, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells.

[0028] In a preferred embodiment, when the kit is used to determine whether a subject is in a gout remission period or a healthy period, the immune cell subpopulation includes: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells, and activated Tfh cells;

[0029] Preferably, the immune cell subpopulation further includes: one or more of peripheral helper T cells, total memory CD8 T cells and naive NK cells.

[0030] In a preferred embodiment, when the kit is used to determine whether a subject is in a gout attack or a gout remission period, the clinical data includes one or more of the subject's white blood cell level, platelet level, lymphocyte level, eosinophil, basophil and glomerular filtration rate level.

[0031] In a preferred embodiment, when the kit is used to determine whether a subject is in a gout remission period or a healthy period, the clinical data includes one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

[0032] In a specific embodiment, when the kit is used to determine whether a subject is in a gout attack or gout remission period, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells, and at the same time the clinical data include the subject's white blood cell level, platelet level, lymphocyte level, eosinophil, basophil and glomerular filtration rate level.

[0033] In a specific embodiment, when the kit is used to determine whether a subject is in a gout remission period or a healthy period, the immune cell subpopulations include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells and activated Tfh cells; and at the same time, the clinical data include one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

[0034] In a preferred embodiment, the immune cell subpopulation and the clinical data are obtained from a biological sample of a subject.

[0035] In a preferred embodiment, the biological sample is selected from one or more of peripheral blood, lymph node, bone marrow, cerebrospinal fluid and urine.

[0036] In a preferred embodiment, the biological sample is at least 2-10 ml, for example 4 ml, of peripheral blood.

[0037] In a preferred embodiment, the reagent is a reagent for determining the level of an immune cell subpopulation or a reagent for determining clinical data.

[0038] In a specific embodiment, the reagent is a reagent used in flow cytometry.

[0039] In a specific embodiment, the flow cytometry comprises the following steps: taking a peripheral blood sample into a flow tube, staining it with a fluorescent antibody, and then placing it in a flow cytometer for detection and analysis.

[0040] In a specific embodiment, the reagents used in flow cytometry include antibodies for labeling the immune cell subpopulation and reagents commonly used in flow cytometry.

[0041] In a specific embodiment, the antibodies are as shown in Table 3 below, and the immune cells are marked by antibody markers as shown in Tables 1-1 to 1-5 below.

[0042] In addition, another aspect of the present invention provides a reagent for detecting a marker combination, wherein the marker combination is as defined in the application described in the above first aspect of the present invention, and the reagent is as defined in the application described in the above first aspect of the present invention.

[0043] In addition, another aspect of the present invention provides a kit for determining the progression of gout in a subject, which includes the reagent as described in the above aspect of the present invention and other reagents commonly used in the kit, such as reference substances or standard substances.

[0044] The gout progression of the subject is divided into: gout attack period, gout remission period and healthy period, and the kit has the function of the drug in the application described in the above one aspect of the present invention.

[0045] In a specific embodiment, when the kit is used to determine whether a subject is in a gout attack or gout remission period, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells, and at the same time the clinical data include the subject's white blood cell level, platelet level, lymphocyte level, eosinophil, basophil and glomerular filtration rate level.

[0046] In a specific embodiment, when the kit is used to determine whether a subject is in a gout remission period or a healthy period, the immune cell subpopulations include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells and activated Tfh cells; and at the same time, the clinical data include one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

[0047] In addition, another aspect of the present invention provides a diagnostic system or prediction model for gout, which includes a detection module and an analysis and judgment module; the detection module detects the level of the marker combination in the biological sample to be tested, and transmits the level data to the analysis and judgment module; the analysis and judgment module judges the level data of the marker combination, and outputs a prediction or diagnosis result: the sample is in a gout attack period, a gout remission period or a healthy period; wherein, the marker combination is defined in the application described in the above aspect of the present invention.

[0048] In a preferred embodiment, the biological sample is as defined in the application described in the above aspect of the present invention.

[0049] In addition, another aspect of the present invention provides a computer-readable storage medium storing a computer program for implementing the functions of the diagnostic system or prediction model as described in the above aspect of the present invention.

[0050] In addition, another aspect of the present invention provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the processor is used to execute the computer program to implement the function of the prediction system or prediction model described in the above aspect of the present invention.

[0051] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present invention.

[0052] Unless otherwise specified, the reagents and raw materials used in the present invention are commercially available.

[0053] The positive progressive effect of the present invention is that the present invention discloses an application of a marker combination in predicting or diagnosing gout, the marker combination comprising immune cell subpopulations and clinical data, the immune cell subpopulations comprising virus-specific cytotoxic NK cells and inhibitory Vδ2 cells. The marker combination of the present invention comprises immune cell subpopulations and clinical data, and different immune cell subpopulations are used in combination with different clinical data when distinguishing between gout attack and gout remission, or when distinguishing between gout remission and healthy subjects, to achieve high sensitivity and high specificity diagnostic results. Therefore, the marker combination of the present invention has broad prospects in predicting different processes of gout, and can provide more basic research data for the health management of people at high risk of gout. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 :Differences in some peripheral blood T lymphocyte subsets between healthy controls, patients with acute gout flare, and patients with gout remission: Normal control refers to healthy controls, Acute flare refers to patients with acute gout flare, and Remission refers to patients with gout remission. ns indicates P≥0.05, * indicates P<0.05, ** indicates P<0.01, *** indicates P<0.001, and **** indicates P<0.0001.

[0055] Figure 2 :Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) among the three groups of healthy control (NC), acute gout (AG), and gout remission (RG). A: PCA analysis; B PLS-DA analysis.

[0056] Figure 3: Screening of characteristic immune indicators for gout recurrence: (A) OPLS-DA analysis of acute gout attack (AG) and remission (RG); (B): S-plot after OPLS-DA, (C): Volcano plot showing the difference in immune cells between acute gout attack and remission; (D): Heat map showing the difference in immune cells between acute gout attack and remission.

[0057] Figure 4 : Screening diagnostic indicators for gout recurrence: (A) The AUC value of the ROC curve was compared with other factors to show the prediction accuracy of the training cohort; (B) The AUC value of the ROC curve was compared with the prediction accuracy of the validation cohort and other factors; (C) Pearson correlation analysis was used to describe the relationship between the predictive factors of acute gout attack.

[0058] Figure 5 : Screening of characteristic immune indicators for complete remission of gout: (A) OPLS-DA analysis of healthy people and gout remission; (B) S-plot after OPLS-DA; (C) Volcano plot showing the difference in immune cells between healthy people and gout remission; (D) Heat map showing the difference in immune cells between healthy people and gout remission.

[0059] Figure 6 :Screening diagnostic indicators for complete remission of gout: (A) The prediction accuracy of the AUC value of the ROC curve compared with other factors; (B) Pearson correlation analysis was used to describe the relationship between the predictive factors of gout remission; (C): Pearson correlation analysis showed that the level of inhibitory Vδ2 cells in patients with gout remission was positively correlated with UA (uric acid).

[0060] Figure 7 :The inhibition of inhibitory Vδ2 cells and virus-infected specific cytotoxic NK cells was significantly different among the three groups, and the inhibition of inhibitory Vδ2 cells and virus-infected specific cytotoxic NK cells showed an inverse trend. Among them, compared with the acute gout attack (AG) group, the inhibitory Vδ2 cells were lowest in the healthy population (NC) group and highest in the gout remission (RG) group, while the virus-infected specific cytotoxic NK cells were lowest in the NC group and highest in the RG group.

[0061] Figure 8 :Nomogram for predicting gout recurrence: (A) Nomogram for predicting gout recurrence. (B) Calibration chart for evaluating the predictive effect of the nomogram. (C) Decision curve analysis (DCA) shows that the probability of gout recurrence can be predicted using the nomogram.

[0062] Fig. 9: Development of a nomogram for predicting complete recovery in patients with gout remission: (A) Nomogram for predicting complete recovery in patients with gout remission; (B) Calibration chart used to evaluate the predictive validity of the nomogram; (C) Decision curve analysis (DCA) showed the probability of predicting gout remission using the nomogram. DETAILED DESCRIPTION

[0063] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0064] Before further describing the specific embodiments of the present invention, it should be understood that the scope of protection of the present invention is not limited to the specific specific embodiments described below; it should also be understood that the terms used in the examples of the present invention are for describing the specific specific embodiments rather than for limiting the scope of protection of the present invention; in the present specification and claims, unless otherwise expressly stated herein, the singular forms "a", "an" and "the" include plural forms.

[0065] When the embodiments give numerical ranges, it should be understood that, unless otherwise specified in the present invention, both endpoints of each numerical range and any numerical value between the two endpoints can be selected. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those generally understood by those skilled in the art. In addition to the specific methods, equipment, and materials used in the embodiments, according to the grasp of the prior art by those skilled in the art and the record of the present invention, any methods, equipment, and materials of the prior art similar or equivalent to the methods, equipment, and materials described in the embodiments of the present invention can also be used to realize the present invention.

[0066] The present invention provides an application of a marker combination in predicting or diagnosing gout, wherein the marker combination includes immune cell subpopulations and clinical data. When distinguishing between a gout attack and a gout remission period, or when distinguishing between a gout remission period and healthy subjects, different immune cell subpopulations are used in combination with different clinical data to achieve a highly sensitive and highly specific diagnostic result.

[0067] The present invention first provides an application of a marker combination in the preparation of a drug for predicting and / or diagnosing gout, wherein the marker combination comprises immune cell subpopulations and clinical data, wherein the immune cell subpopulations comprise virus-specific cytotoxic NK cells and inhibitory Vδ2 cells.

[0068] In a preferred embodiment, when the drug is used to distinguish between subjects with gout attack and subjects with gout remission, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells;

[0069] In a preferred embodiment, when the drug is used to distinguish between gout remission subjects and healthy subjects, the immune cell subpopulations include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells and activated Tfh cells; preferably, the immune cell subpopulations also include: one or more of peripheral helper T cells, total memory CD8 T cells and naive NK cells.

[0070] The immune cell subpopulations described in the present invention refer to different types of immune cells in the immune system that are subdivided according to their surface markers, functions, and sources. These subpopulations have unique phenotypes and functions and play specific roles in different immune responses and pathological processes. The immune cell subpopulations described in the present invention also refer to a system formed by two or more immune cells, which play an important role in the immune response process.

[0071] The virus-infected specific cytotoxic NK cells described in the present invention refer to a type of natural killer cells that recognize and kill virus-infected cells through a specific mechanism after viral infection. Such cells play a key role in antiviral immune responses.

[0072] The inhibitory Vδ2 cells (Inhibition of Vδ1 cells) described in the present invention refer to: a subtype of γδT cells, which mainly exist in the peripheral blood circulation, and have natural killing and antibody-dependent cytotoxic effects, making them play an important role in the immune system. The inhibitory Vδ2 cells described in the present invention refer to inhibitory immune cells produced against Vδ2 cells in order to avoid immune damage caused by excessive immune response.

[0073] The non-activated terminally differentiated virus-specific CD8 + T cells (Inactive and terminal differentiation virus-specific CD8+T cells) refer to CD8+T cell subsets that develop in chronic viral infections due to continuous antigen stimulation. They have unique phenotypes and functions, such as expressing specific surface molecules, having ADCC ability, and may play a role in maintaining long-term immune memory and controlling viral replication.

[0074] The activated Tfh cells described in the present invention refer to a class of CD4+T cells that play a key role in immune response, especially in the production of antibodies mediated by B cells. Such cells support the function of B cells by expressing specific surface molecules and secreting key cytokines. Tfh cells promote the activation, proliferation and differentiation of B cells by secreting IL-21 and other cytokines, thereby enhancing the production and diversity of antibodies, which is crucial for B cells to adaptive immune responses, especially in fighting infections and autoimmune diseases.

[0075] Inhibition of Vδ1 cells described in the present invention: Vδ1 cells are mainly distributed in the thymus and mucosal epithelial tissues, can be activated to produce a large amount of IL-10, a small amount of IL-2, IL-4, INF-γ, and can also produce cytotoxic effects through apoptosis-related factor ligand interactions and perforin granulin and other pathways. The inhibitory Vδ1 cells described in the present invention refer to inhibitory immune cells produced against Vδ1 cells in order to avoid immune damage caused by excessive immune response.

[0076] The peripheral helper T cells (Peripheral Th cells) described in the present invention are usually referred to as Tph cells, which are a specific CD4+T cell subset. These cells show abnormal expression in a variety of autoimmune diseases and are related to the pathogenesis of the diseases.

[0077] The total memory CD8 T cells described in the present invention refer to a CD8+T cell subpopulation with long-term survival ability in the immune system. These cells can remember specific antigens and respond quickly to re-exposure to pathogens. Such cells can persist in the body for decades and circulate in the blood and lymphoid organs. Total memory CD8 T cells are divided into multiple subpopulations, including central memory T cells (TCM), effector memory T cells (TEM), stem cell-like memory T cells (TSCM) and tissue-resident memory T cells (TRM). These subpopulations differ in function. For example, TCM cells have the ability to self-regenerate and rapidly proliferate, while TRM cells reside in non-lymphoid tissues, such as the skin, to respond to local reinfection. In summary, total memory CD8 T cells are an important component of immune memory. They protect the body from repeated infections through long-term survival and rapid response.

[0078] The immature NK cells described in the present invention are an immature stage of natural killer cells in the development process. Such cells gradually mature in the bone marrow through a series of differentiation steps. As the development proceeds, the immature NK cells gradually acquire more mature markers and downregulate the expression of certain inhibitory receptors, and finally differentiate into mature NK cells (mNK).

[0079] In a preferred embodiment, when the drug is used to distinguish between subjects with gout attacks and subjects in gout remission, the clinical data include one or more of the subject's white blood cell level, platelet level, lymphocyte level, eosinophil level, basophil level and glomerular filtration rate level.

[0080] In a preferred embodiment, when the drug is used to distinguish between gout remission subjects and healthy subjects, the clinical data include one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

[0081] Clinical data refers to: baseline data and blood test data measured during the clinical process. Baseline data refers to data collected at the beginning of a clinical trial to assess the basic characteristics and health status of the subjects. Blood test data refers to data collected after obtaining blood from the subjects. Common blood test data include red blood cell count, white blood cell count, platelet count, hemoglobin, biochemical indicators, immune indicators, etc.

[0082] The clinical data specified in the present invention is one or more of the subject's body mass index, uric acid level, leukocyte level, platelet level, lymphocyte level, eosinophil, basophil and glomerular filtration rate level.

[0083] The white blood cell level: White blood cells (WBC) are an important component of the blood, and their counting and classification are important for diagnosing various infectious diseases and other blood diseases.

[0084] Platelet level: Platelets (PLT) are involved in the blood coagulation process. Abnormal platelet count can reflect problems with blood or coagulation function.

[0085] Lymphocyte level: Lymphocytes are an important component of the immune system, and changes in their number can reflect the body's immune status.

[0086] Eosinophils and basophils: These two types of white blood cells play an important role in regulating allergic reactions and certain parasitic infections. Changes in their numbers can help diagnose specific types of illnesses.

[0087] Glomerular filtration rate level: The estimated glomerular filtration rate (eGFR) is an important indicator for assessing kidney function and is valuable for the diagnosis and staging of chronic kidney disease (CKD), disease risk assessment, and prognosis prediction.

[0088] Body mass index (BMI): It is mainly used to assess the degree of obesity, but it can also indirectly reflect an individual's overall health status, such as nutritional status and metabolic health.

[0089] The method for measuring the clinical indicators of the present invention may be a conventional method used in the art, such as using a fully automatic blood analyzer for measurement.

[0090] In a preferred embodiment, the gout is a gout attack or a gout remission, which represents different stages of gout progression.

[0091] Acute gout attack, also referred to as "acute gout attack period", "gout attack", or "gout attack period" in the present invention, refers to the subject being in the process of gout attack, and its diagnostic criteria are:

[0092] 1. Urate crystals in joint fluid: This is the gold standard for acute gouty arthritis. The presence of urate crystals in gouty nodules is confirmed by chemical methods or polarized light microscopy.

[0093] 2. Acute monoarthritis attacks: usually limited to individual joints, such as swelling and pain in the first metatarsal joint.

[0094] 3. The inflammatory response reaches its peak within one day: Acute attacks are rapid and severe.

[0095] 4. Elevated serum uric acid levels: Most patients have significantly elevated serum uric acid levels during acute attacks, with males >420 μmol / L (7 mg / dL) and females >357 μmol / L (6 mg / dL) having diagnostic value.

[0096] 5. Other symptoms: including redness, swelling, pain and tenderness.

[0097] Gout remission, also referred to as gout remission period in the present invention, refers to the subject being in the process of gout remission period, and its diagnostic criteria include:

[0098] 1. Normal serum uric acid level: Serum uric acid level can be normal during remission, but it may not increase if uricosuric drugs or cortical hormones have been used.

[0099] 2. Lack of acute attack characteristics: There are no symptoms such as acute monoarthritis attack and the inflammatory response quickly reaches its peak.

[0100] 3. Imaging examinations: X-rays help rule out other bone lesions, and CT scans and MRI can identify soft tissue changes and related bone lesions.

[0101] Comprehensive differentiation of gout remission or acute gout attack includes:

[0102] Laboratory tests: Serum uric acid levels increase significantly during acute attacks and may return to normal during remission.

[0103] The present invention refers to a "subject", "patient" or "individual" to be treated, particularly a mammalian subject. Mammalian subjects include humans, non-human primates, farm animals (e.g., cows), sports animals or pet animals, such as dogs, cats, guinea pigs, rabbits, rats or mice. In some embodiments, the subject is a human. In alternative embodiments, the subject is a non-human mammal, such as a mouse.

[0104] In a preferred embodiment, the immune cell subpopulations are labeled using different antibodies.

[0105] The antibodies of the present invention are shown in Table 3 below.

[0106] In a preferred embodiment, the antibody markers of the immune cell subpopulations are shown in Table 1-1 to Table 1-4.

[0107] In a specific embodiment, if different antibody markers are used to represent the immune cell subsets, the virus-specific cytotoxic NK cells are CD3 - CD56 + NKP46 + Virus-specific cytotoxic NK cells, wherein the naive NK cells are CD3 - CD56 bright Naive NK cells, the non-activated terminally differentiated virus-specific CD8 + T cells are CD3 + CD8 + CD45RA + CCR7 - CD127 + Non-activated terminally differentiated virus-specific CD8 + T cells, wherein the peripheral helper T cells are CD3 + CD4 + CXCR5 - PD-1 + Peripheral helper T cells, the activated Tfh cells are CD3 + CD4 + CXCR5 + PD-1 +Activated Tfh cells, the total memory CD8 T cells are CD3 + CD8 + HLA-DR + Total memory CD8 T cells, the suppressive Vδ1 cells are CD3 + γδT + Vδ1 + PD-1 + Suppressive Vδ1 cells, or, the suppressive Vδ2 cells are CD3 + γδT + Vδ2 + PD-1 + Suppressive Vδ2 cells.

[0108] The immune cell antibody calibration conditions are shown in Tables 1-1 to 1-4 below:

[0109] Table 1-1 Changes in T cell markers in gout patients

[0110]

[0111]

[0112] Table 1-2 Changes in γδT cell markers in gout patients

[0113]

[0114]

[0115] Table 1-3 Changes in markers of B cell spectrum in gout patients

[0116]

[0117] Table 1-4 Changes in markers of NK cell spectrum in gout patients

[0118]

[0119] The present invention also provides an application of a reagent for determining a marker combination in the preparation of a kit for determining the gout progression of a subject, wherein the gout progression of the subject is divided into: a gout attack period, a gout remission period, and a healthy period, and the marker combination is defined as in the application described in the above-mentioned first aspect of the present invention, and the kit has the function of the drug described in the application described in the above-mentioned first aspect of the present invention.

[0120] In a preferred embodiment, the immune cell subpopulation and the clinical data are obtained from a biological sample of a subject.

[0121] In a preferred embodiment, the biological sample is selected from one or more of peripheral blood, lymph node, bone marrow, cerebrospinal fluid and urine.

[0122] In related aspects and embodiments of the present invention, cells can be obtained and / or separated from a biological sample of a subject using one or more methods selected from the group consisting of size exclusion, immunocapture, erythrocyte lysis, leukocyte depletion, FICOLL, electrophoresis, two-dimensional electrophoresis, flow cytometry, and microfluidic chips, or any combination thereof. The specific steps of the above methods are well known to those skilled in the art and are not particularly limited herein.

[0123] In a specific aspect, the size exclusion method includes the use of a microporous filter. Suitable microporous filters have various pore sizes and shapes. In some aspects, the pore size ranges from 5 microns to 10 microns. The hole can be a circular, racetrack-shaped, oval, square or rectangular hole shape. The microporous filter can have an accurate hole geometry and a uniform hole distribution.

[0124] In a particular aspect, using CellSieve TM The cells are separated by low pressure microfiltration assays, the filter comprising a photodefinable dry membrane. In other aspects, the cells are separated using a microfluidic chip based on physical size sorting, hydrodynamic size sorting, grouping, capture, immunocapture, size-based enrichment of large cells or elimination of small cells.

[0125] In related aspects and embodiments of the invention, cells can be characterized using a device for collecting cells from a biological sample. For example, when immune cells are identified from a population of cells obtained from a biological sample, the phenotypic expression of cell markers can be determined without removing the cells from the device.

[0126] In a specific example, when a microporous filter is used to collect cells, the cell can be characterized while it is on the surface of the microporous filter. In other aspects and embodiments, the cell can be removed from the device and then characterized. In addition, the cell can be fixed or not fixed when the characterization is being performed.

[0127] In a preferred embodiment, the biological sample is at least 2-10 ml, for example 4 ml, of peripheral blood.

[0128] In a preferred embodiment, the reagent is a reagent for determining the level of an immune cell subpopulation or a reagent for determining clinical data.

[0129] In a specific embodiment, the reagent is a reagent used in flow cytometry.

[0130] In a specific embodiment, the reagents used in flow cytometry include antibodies for labeling the immune cell subpopulation and reagents commonly used in flow cytometry.

[0131] The present invention also provides a reagent for detecting a marker combination, wherein the marker combination is as defined in the application described in the above one aspect of the present invention, and the reagent is as defined in the application described in the above one aspect of the present invention.

[0132] In addition, another aspect of the present invention provides a kit for determining the progression of gout in a subject, which includes the reagent as described in the above aspect of the present invention and other reagents commonly used in the kit, such as reference substances or standard substances.

[0133] In addition, another aspect of the present invention provides a diagnostic system or prediction model for gout, which includes a detection module and an analysis and judgment module; the detection module detects the level of the marker combination in the biological sample to be tested, and transmits the level data to the analysis and judgment module; the analysis and judgment module judges the level data of the marker combination, and outputs a prediction or diagnosis result: the sample is in a gout attack period, a gout remission period or a healthy period; wherein, the marker combination is defined in the application described in the above aspect of the present invention.

[0134] In addition, another aspect of the present invention provides a computer-readable storage medium storing a computer program for implementing the functions of the diagnostic system or prediction model as described in the above aspect of the present invention.

[0135] In addition, another aspect of the present invention provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the processor is used to execute the computer program to implement the function of the prediction system or prediction model described in the above aspect of the present invention.

[0136] Unless otherwise indicated, technical terms are used in accordance with conventional usage. Definitions of common terms in molecular biology are readily available, for example, Benjamin Lewin, Genes VII, published by Oxford University Press, 2000 (ISBN 019879276X); Kendrew et al. (eds.); The Encyclopedia of Molecular Biology, published by Blackwell Publishers, 1994 (ISBN 0632021829); and Robert A. Meyers (ed.), Molecular Biology and Biotechnology: a Comprehensive Desk Reference, published by Wiley, John & Sons, Inc., 1995 (ISBN 0471186341) and other similar technical references.

[0137] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples. The experimental methods in the following examples without specifying specific conditions are carried out according to conventional methods and conditions, or selected according to the product specifications.

[0138] Example 1

[0139] This prospective cohort study (NCT05522504) was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board and Medical Ethics Committee of the Tenth People's Hospital Affiliated to Tongji University, Shanghai (SHSY-IEC-4.1 / 21-246 / 01). Written informed consent was obtained from the patients.

[0140] 1. Criteria for Research Subjects

[0141] (1) Participants with acute gout attack were included in the study if they met the following conditions:

[0142] 1) Aged between 18 and 80;

[0143] 2) Acute gout attack within 24 hours, meeting the 2015 ACR / EULAR classification criteria (Neogi, T., et al. 2015 Gout classification criteria: an American College of Rheumatology / European League Against Rheumatism collaborative initiative. Ann Rheum Dis 74, 1789-1798 (2015).);

[0144] 3) not receiving any treatment within three days before blood collection;

[0145] 4) MSU crystals were detected by B-ultrasound or dual-source CT.

[0146] (2) Participants with gout remission were included in the study if they met the following criteria:

[0147] 1) Aged between 18 and 80;

[0148] 2) previous diagnosis of gout, approved by the ACR Board of Directors and the EULAR Executive Committee1;

[0149] 3) The clinical manifestations of local joints or bursae (such as redness, swelling, fever, and pain) have been relieved for at least 3 months since the last gout attack;

[0150] 4) normal erythrocyte sedimentation rate and C-reactive protein levels within the past 3 months;

[0151] 5) MSU crystals were detected by B-ultrasound or dual-source CT.

[0152] (3) Exclusion criteria for gout patients include:

[0153] 1) Unwilling to participate in the study;

[0154] 2) in the acute infection stage or had received treatment for viral, bacterial, fungal, rickettsial, spirochetal or parasitic infection in the past three months;

[0155] 3) Have received any vaccine including rabies, influenza or 2019-nCov vaccine in the past three months;

[0156] 4) had a blood transfusion / blood loss / blood donation of 200 ml or more, received a blood transfusion or used blood products in the past three months;

[0157] 5) Immunodeficiency or receiving immunosuppressive treatment;

[0158] 6) use of corticosteroids or indomethacin in the past 3 months;

[0159] 7) Septic arthritis or other joint diseases (such as rheumatoid arthritis);

[0160] 8) renal insufficiency (estimated glomerular filtration rate <30 mL / min / 1.73 m2);

[0161] 9) Other conditions that may increase blood uric acid levels.

[0162] The inclusion criteria of the control group (i.e., healthy people) were the same as those in previous studies (.Gu, H., et al. MSU crystal deposition contributes to inflammation and immune responses in goutremission. Cell Rep 42, 113139 (2023).):

[0163] 1) Aged between 18 and 80;

[0164] 2) no history of self-reported or clinically diagnosed hyperuricemia or gout;

[0165] 3) Did not receive any treatment within three days before blood collection.

[0166] The exclusion criteria for this group were the same as those for the gout group. The age of the three groups was fully matched, with statistical significance >0.1.

[0167] 2. Blood Sample Collection

[0168] This study evaluated 165 patients diagnosed with gout who were hospitalized between March 2022 and March 2023, and 24 patients were excluded from the total. Therefore, a total of 141 patients were recruited, of which 78 had acute gout (AG) and 63 had remitted gout (RG). In addition, 66 healthy normal controls were recruited. Tables 2-1 and 2-2 list the baseline clinical characteristics of these patients, and no significant differences were observed between the three groups of patients in age, height, and urea nitrogen levels.

[0169] Table 2-1 Clinical characteristics between normal controls and gout remission

[0170]

[0171]

[0172] Note: Values ​​are expressed as mean ± standard deviation, median (first quartile; third quartile) or percentage (%). BMI, body mass index; RBC, red blood cell; HB, hemoglobin; WBC, white blood cell; PLT, platelet; BUN, urea nitrogen; estimated glomerular filtration rate; SCr, serum creatinine; uric acid.

[0173] Table 2-2 Clinical characteristics between acute gout attack and gout remission

[0174]

[0175] Note: Values ​​are expressed as mean standard deviation, median (interquartile range), or percentage (%). BMI, body mass index; RBC, red blood cell; HB, hemoglobin; WBC, white blood cell; PLT, platelet; BUN, urea nitrogen; estimated glomerular filtration rate; SCr, serum creatinine; uric acid.

[0176] Blood was collected from peripheral veins of patients with gout. 2 ml of venous blood from each patient was placed in a vacuum tube containing an anticoagulant EDTA solution for peripheral blood cell examination and blood biochemistry examination. 4 ml of venous blood from each patient was placed in a vacuum tube for spectral flow cytometry. Weekly blood test T-cell Immunoglobulin and ITIM Domain Contributes to t oCD8(+)T-cell Immunosenescence.Aging Cell 17(2018).). Spectral flow cytometry and blood biochemistry tests were performed on the same blood samples for all patients. All tests were completed in the laboratory of Shanghai Tenth People's Hospital.

[0177] (1) Spectral flow cytometry

[0178] Human peripheral blood sample pretreatment and flow cytometry analysis:

[0179] 1. Preparation of mixed antibody working solution: Take out the antibodies shown in Table 3 from the refrigerator at 4°C, put them into the centrifuge, centrifuge briefly at 3000rpm, prepare the antibody working solution in a 1.5ml eppendorf tube according to the instructions of the corresponding antibodies in Table 3 at a ratio of 1:10 (the ratio of antibodies in the total system is 1:100), then gently blow and mix, and place on ice for use. A blank tube must be set up each time as a control.

[0180] Table 3 List of antibodies required for the kit

[0181] Marker Fluorescence Part Number factory Clone number CD3 APC-H7 560176 BD SK7 CD3 PerCP-Cy5.5 560835 BD UCHT1 CD4 APC-H7 560158 BD RPA-T4 CD8 BV510 563919 BD SK1 CD28 PE-Cy7 560684 BD CD28.2 CD127 BV421 562436 BD HIL-7R-M21 CCR7 AF647 560816 BD 150503 CD45RA FITC 555488 BD HI100 PD-1 PE 557946 BD MIH4 PD-1 BB515 564494 BD EH12.1 CD56 APC 555518 BD B159 NKP46 BV510 564064 BD 9E2 / NKp46 HLA-DR PE 555812 BD G46-6 TCRγδ BV421 744870 BD 11F2 TCRVδ1 percp-vio700 130-120-441 Miltenyi Biotec REA173 TCRVδ2 PE 555739 BD B6 CXCR5 AF647 558113 BD RF8B2

[0182] 2. Sample incubation: Take 100 μl of human whole blood into a marked flow tube, mix the prepared antibody working solution, take 10 μl and add it to the whole blood (or take 10 μl of mixed antibody into the flow tube, then add 100 μl of whole blood), gently shake to mix, and incubate at 4°C in the dark for 30 minutes.

[0183] 4. Sample lysis: After the incubation is completed, add 2 ml of red blood cell lysis buffer to the flow tube, immediately shake and mix, and lyse at room temperature (20-30°C) for 10 minutes. Observe whether the liquid is clear. If it is clear, centrifuge it at 1000 rpm for 5 minutes. If the lysis is not complete, add 200 μL of lysis buffer, mix, lyse at room temperature for 3 minutes, and centrifuge at 1000 rpm for 5 minutes.

[0184] 5. Take out the flow tube from the centrifuge, discard the liquid in the tube into the waste bottle, and gently invert it on paper to absorb the liquid at the tube mouth; add 2ml 1×PBS to wash, centrifuge at 1500rpm for 5min, remove the supernatant, and then add 200μl 1×PBS to resuspend, mix well and test, and test on the machine within 3 hours. The flow cytometer model is BD FACSlyric.

[0185] (2) PCA and PLA-DA analysis

[0186] The above spectral flow cytometry results were obtained, and the three groups of immune cells were further analyzed by PCA and PLA-DA using SIMCA software. The results are as follows Figure 2 As shown, this proves that immune cell subsets as a reference system can well distinguish healthy people, people with acute gout attacks and people with gout remission.

[0187] Example 2: Searching for differential immune cells and clinical indicators and building a prediction model

[0188] 1. Test methods

[0189] Using the car package of R language, we conducted batch differential analysis on the healthy group, gout relief group, and gout acute attack group. The code is as follows:

[0190]

[0191] At the same time, orthogonal partial least squares discriminant analysis (OPLS-DA) was performed on the healthy group, gout remission group and acute gout attack group using simca software to explore the differentiation of lymphocyte subtypes. An S-chart was established to visualize the contribution of lymphocyte subtypes to group differentiation.

[0192] The projected variable importance (VIP) value of each lymphocyte subtype in the model was calculated to indicate its contribution to the sample classification. Variables with a VIP value greater than 1 were considered important in distinguishing between the groups. The lymphocyte immune phenotype candidates (VIP>1 and P<0.05) and significant clinical parameters (P<0.05) were subjected to LASSO regression analysis. The correlation regression coefficients between the factors were then calculated, and the prediction score formula was established based on the expression level of each factor multiplied by its corresponding regression coefficient. The code is as follows:

[0193]

[0194] The receiver operating characteristic (ROC) curve was used to evaluate the predictive efficiency of the model and other lymphocyte immune phenotype candidates. The diagnostic parameters, including the area under the curve (AUC), sensitivity, and specificity, were defined by the “pROC” software package, with the following code:

[0195]

[0196] A nomogram was created to estimate the probability of survival based on the risk score and other factors. All identified biomarkers were then validated using a random forest with 10-fold cross validation using the R package “caret” as follows:

[0197]

[0198] Finally, the locked immune cell subsets are subjected to risk assessment to clarify the correlation between immune cell subsets and complete remission and recurrence of gout. The code is as follows:

[0199]

[0200] In addition, the codes corresponding to the analysis of Table 12-1 to Table 12-3 are as follows:

[0201]

[0202] 2. Results Analysis

[0203] (1) Using prism software to analyze the intergroup differences, the inventors first found that the expression of lymphocyte subsets in the peripheral blood of healthy people, patients with acute gout attacks, and patients in the remission period of gout was related to acute gout attacks and complete remission of gout ( Figure 1 ).

[0204] (2) To study the distribution and function of lymphocyte subsets in NC, AG, and RG, 75 immune phenotypes were detected by flow cytometry, PCA ( Figure 2 A) and PLS-DA ( Figure 2Middle B) shows that there are differences in the lymphocyte subset spectra between the AG, RG and NC groups, which indicates that peripheral blood lymphocyte subsets can well distinguish healthy people, patients with acute gout attacks and patients in remission of gout, and the present invention has good quality control conditions;

[0205] (3) When comparing AG and RG, the changes and differences in the levels of T cell subsets, γδT subsets, B cell subsets, and NK cell subsets between the two are shown in Tables 4 to 7. Significant changes were found in the levels of the three lymphocyte subsets.

[0206] Table 4 Changes of T cell subsets in AG (Gout flare) and RG (Gout remission)

[0207]

[0208] Note: The values ​​are expressed as mean ± standard deviation, median (first quartile; third quartile), the same as in the following tables.

[0209] Table 5 Changes of γδT cell subsets in AG and RG

[0210]

[0211] Table 6 Changes of B cell subsets in AG and RG

[0212]

[0213] Table 7 Changes of NK cell subsets in AG and RG

[0214]

[0215]

[0216] (4) Figure 3 As shown, in the OPLS-DA analysis ( Figure 3 In Figure A), AG patients were observed to be separated from RG patients, indicating the obvious difference in their peripheral blood lymphocyte profiles; the S-plot and volcano plots showed that ( Figure 3 B and C), virus-specific cytotoxic NK cells (CD3 - CD56 + NKP46 + ), non-activated terminally differentiated virus-specific CD8 + T cells (CD3 + CD8 + CD45RA + CCR7 - CD127 + ), suppressor Vδ2 cells (CD3+ γδT + Vδ2 + PD-1 + ) can well distinguish AG from RG. In terms of clinical indicators, WBC, PLT and neutrophils were significantly increased in AG, while lymphocytes, eosinophils, basophils and eGFR increased in RG.

[0217] (5) Figure 4 As shown, when analyzing AG and RG, the inventors selected three lymphocyte subsets (virus-specific cytotoxic NK cells, non-activated terminally differentiated virus-specific CD8 + T cells, suppressive Vδ2 cells) and 6 clinical data (WBC (white blood cells), PLT (platelets), lymphocytes, eosinophils, basophils and eGFR (glomerular filtration rate)) were used to perform the ROC curve, which achieved an AUC of 0.814 ( Figure 4 A, Table 12-1, Table 12-3), which can well predict the recurrence of gout. In addition, in order to confirm the reliability of the model, the inventors followed up RG patients for one year to observe the possibility of gout recurrence within one year, and used the constructed AG and RG prediction models for verification. The results showed that the model also achieved an AUC value of 0.724 in the verification cohort ( Figure 4 B, Table 12-3). We further evaluated whether the lymphocyte subsets selected in AG were associated with relevant clinical indicators. Figure 4 As shown in C, suppressive Vδ2 cells are closely associated with WBCs.

[0218] (6) Based on the results of lasso regression analysis, a nomogram was further constructed by combining variables including lymphocyte subsets and clinical data ( Figure 8 The value corresponding to the intersection point is the probability of gout attack in the individual. The calibration graph is used to evaluate the predictive effect of the nomogram ( Figure 8 The result of the calibration curve is close to a straight line with a slope of 1, which indicates that the predicted value is in good agreement with the actual value. In addition, the decision curve analysis (DCA) showed that the use of the nomogram to predict the probability of recurrence of gout remission will gain more net benefits in terms of the huge potential for clinical application ( Figure 8 C).

[0219] (7) When comparing NG and RG, the changes and differences in the levels of T cell subsets, γδT subsets, B cell subsets, and NK cell subsets between the two are shown in Tables 8 to 11. Significant changes were found in the levels of 38 lymphocyte subsets.

[0220] Table 8 Changes of T cell subsets in RG (Gout remission) and NG (Normal control) groups

[0221]

[0222]

[0223] Table 9 Changes of γδT subpopulations in RG and NG groups

[0224]

[0225]

[0226] Table 10 Changes of B cell subsets in RG and NG groups

[0227]

[0228] Table 11 Changes in NK cell subsets between RG and NG groups

[0229]

[0230] (8) Figure 5 As shown, the OPLS-DA graph showed that RG patients were significantly different from NC patients ( Figure 5 A), S-plot analysis ( Figure 5 B) shows that virus-specific cytotoxic NK cells (CD3 - CD56 + NKP46 + ), peripheral helper T cells (CD3 + CD4 + CXCR5 - PD-1 + ), activated Tfh cells (CD3 + CD4 + CXCR5 + PD-1 + ), total memory CD8 T cells (CD3 + CD8 + HLA-DR + ), naive NK cells (CD3 - CD56 bright ), suppressor Vδ2 cells (CD3 + γδT + Vδ2 + PD-1 + ), suppressor Vδ1 cells (CD3 + γδT + Vδ1 + PD-1+ ), conventional killer NK cells, and mature NK cells can well distinguish NG and RG patients. Figure 5 As shown in C and D, the potential differential lymphocyte subset variables are VIP value>1.0, P value<0.05 and log2|FC|>0.25, and the heat map results show that seven lymphocyte subsets including peripheral helper T cells, activated Tfh cells, naive NK cells, suppressive Vδ1 cells, suppressive Vδ2 cells, virus-specific cytotoxic NK cells and total memory CD8+T cells are differential immune cells.

[0231] (9) Figure 6 As shown in Figure 2, the inventors selected four lymphocyte subsets (peripheral helper T cells, virus-specific cytotoxic NK cells, suppressive Vδ1 cells, and suppressive Vδ2 cells) and four clinical data (BMI, Hb (hemoglobin), eGFR, and UA (uric acid)) to perform the ROC curve, which obtained a higher AUC of 0.934 ( Figure 6 A, Table 12-2, Table 12-3), which can well predict the complete remission of gout. And Figure 6 Figure B further showed that the lymphocyte subsets selected in RG were associated with relevant clinical indicators. Figure 6 As shown in FIG6C , the inventors observed that UA was positively correlated with inhibitory Vδ2 cells, suggesting that inhibitory Vδ2 cells were associated with complete remission of gout.

[0232] (10) Based on the results of lasso regression analysis, a nomogram was constructed by combining variables such as lymphocyte subsets and clinical data. Fig. 9 The value corresponding to the intersection point is the probability that the individual is in the RG. The calibration graph is used to evaluate the predictive validity of the nomogram ( Fig. 9 The results of the calibration curve are close to a straight line with a slope of 1, which indicates that the predicted value and the actual value have good consistency. In addition, DCA shows that the use of nomograms to predict the likelihood of gout remission will gain more net benefits in terms of great potential for clinical application ( Fig. 9 C) Changes in the number of Tph cells and suppressive Vδ2 cells in the immune microenvironment of peripheral blood may be a decisive factor in the disease trajectory of complete remission of gout.

[0233] Table 12-1 ROC curve analysis of gout attack (training cohort)

[0234]

[0235] Note: Model 1: WBC+PLT+L%+E%+B%+eGFR+virus-specific cytotoxic NK cells+non-activated terminally differentiated virus-specific CD8 +T cells + suppressor Vδ2 cells;

[0236] Model 2: WBC+PLT+L%+E%+B%+eGFR;

[0237] Model 3: virus-specific cytotoxic NK cells + non-activated terminally differentiated virus-specific CD8 + T cells + suppressor Vδ2 cells.

[0238] Table 12-2 ROC curve analysis for diagnosis of complete remission of gout

[0239]

[0240]

[0241] Note: Model 1: BMI+Hb+eGFR+UA+peripheral helper T cells+virus-specific cytotoxic NK cells+suppressive Vδ1 cells+suppressive Vδ2 cells;

[0242] Model 2: BMI+Hb+eGFR+UA;

[0243] Model 3: peripheral helper T cells + virus-infected specific cytotoxic NK cells + inhibition of vδ1 + inhibition of vδ2.

[0244] Table 12-3 ROC curve results summary

[0245]

[0246] Note: Model 1 is the application of ROC curve analysis in the diagnosis of complete remission of gout: BMI+Hb+eGFR+UA+peripheral helper T cells+virus-specific cytotoxic NK cells+suppressive Vδ1 cells+suppressive Vδ2 cells;

[0247] Model 2 is the application of ROC curve analysis in the diagnosis of gout attacks (training cohort): WBC+PLT+L%+E%+B%+eGFR+virus-specific cytotoxic NK cells+non-activated terminally differentiated virus-specific CD8 + T cells + suppressor Vδ2 cells;

[0248] Model 3 is the application of ROC curve analysis in the diagnosis of gout attacks (validation cohort): WBC+PLT+L%+E%+B%+eGFR+virus-specific cytotoxic NK cells+non-activated terminally differentiated virus-specific CD8 + T cells + suppressor Vδ2 cells.

[0249] (11) Figure 7As shown in Tables 13 and 14, the inventors tend to use one-way analysis of variance or Kruskal-Wallis test to analyze the differences in lymphocyte subsets among the three groups, followed by multiple correction. Figure 7 The results showed that the number of suppressive Vδ2 cells (CD3+γδT+Vδ2+PD-1+) was the lowest in healthy subjects and the highest in gout remission. + γδT + Vδ2 + PD-1 + ) increased by 1%, the adjusted relative risk ratio of complete remission of gout decreased by 37% (Table 13). Virus-specific cytotoxic NK cells (CD3-CD56+NKP46+) were highest in healthy people and lowest in gout remission, and the adjusted relative risk ratio of complete remission of gout increased by 1.3% for every 1% increase in virus-infected specific cytotoxic NK cells (Table 13).

[0250] Table 13 Analysis of threshold effect of immune cells on complete remission of gout (adjusted HR (95% CI)). Model based on age (years), BMI (kg / m 2 ) for correction).

[0251]

[0252] Table 14 Analysis of threshold effect of immune cells on gout recurrence (adjusted HR (95% CI)). Model based on age (years), BMI (kg / m 2 ) for correction).

[0253]

Claims

1. Use of a marker combination in the preparation of a drug for predicting and / or diagnosing gout, wherein: The marker combination includes immune cell subsets and clinical data, the immune cell subsets including virus-specific cytotoxic NK cells and inhibitory Vδ2 cells.

2. The use according to claim 1, characterized in that The gout is gout attack or gout relief; Preferably, the immune cell subset also includes non-activated terminally differentiated virus-specific CD8 + T cells, activated Tfh cells, and suppressive Vδ1 cells; Better: When the drug is used to distinguish between subjects with gout attacks and subjects with gout remission, the immune cell subsets include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells and non-activated terminally differentiated virus-specific CD8 + T cells; And / or, when the drug is used to distinguish between gout remission subjects and healthy subjects, the immune cell subpopulations include: virus-specific cytotoxic NK cells, inhibitory Vδ2 cells, inhibitory Vδ1 cells and activated Tfh cells, and preferably also include: one or more of peripheral helper T cells, total memory CD8 T cells and naive NK cells.

3. The use according to claim 1 or 2, characterized in that: When the drug is used to distinguish between subjects with gout attacks and subjects with gout remission, the clinical data include one or more of the subject's white blood cell level, platelet level, lymphocyte level, eosinophil, basophil and glomerular filtration rate level; And / or, when the drug is used to distinguish between gout remission subjects and healthy subjects, the clinical data includes one or more of body mass index, hemoglobin level, glomerular filtration rate level and uric acid level.

4. The use according to any one of claims 1 to 3, characterized in that: The virus-specific cytotoxic NK cells are CD3 - CD56 + NKP46 + Virus-specific cytotoxic NK cells, wherein the naive NK cells are CD3 - CD56 bright Naive NK cells, the non-activated terminally differentiated virus-specific CD8 + T cells are CD3 + CD8 + CD45RA + CCR7 - CD127 + Non-activated terminally differentiated virus-specific CD8 + T cells, wherein the peripheral helper T cells are CD3 + CD4 + CXCR5 - PD-1 + Peripheral helper T cells, the activated Tfh cells are CD3 + CD4 + CXCR5 + PD-1 + Activated Tfh cells, the total memory CD8 T cells are CD3 + CD8 + HLA-DR + Total memory CD8 T cells, the suppressive Vδ1 cells are CD3 + γδT + Vδ1 + PD-1 + Suppressive Vδ1 cells, or, the suppressive Vδ2 cells are CD3 + γδT + Vδ2 + PD-1 + Suppressive Vδ2 cells.

5. Use of a reagent for determining a combination of markers in the preparation of a kit for determining the progression of gout in a subject, wherein: The subject's gout progression is divided into: gout attack period, gout remission period and healthy period, the marker combination is defined as in the application of any one of claims 1-4, and the kit has the function of the drug in the application of any one of claims 1-4.

6. The use according to claim 5, characterized in that By obtaining the immune cells and the clinical data from a biological sample of a subject; Preferably, the biological sample is selected from one or more of peripheral blood, lymph nodes, bone marrow, cerebrospinal fluid and urine; More preferably, the biological sample is at least 2-10 ml, for example 4 ml, of peripheral blood.

7. The use according to claim 5 or 6, characterized in that The reagent is a reagent for determining the level of an immune cell subpopulation or a reagent for determining clinical data; for example, the reagent is a reagent used in flow cytometry.

8. A reagent for detecting a marker combination, characterized in that: The marker combination is defined in the use according to any one of claims 1 to 4, and the reagent is defined in the use according to any one of claims 5 to 7.

9. A kit for determining the progression of gout in a subject, comprising the reagent and control substance as described in claim 8, wherein the gout progression of the subject is divided into: gout attack period, gout remission period and healthy period, and the kit has the function of the drug in the application as described in any one of claims 1-4.

10. A diagnostic system or prediction model for gout, characterized in that: The diagnostic system or prediction model includes a detection module and an analysis and judgment module; the detection module detects the level of the marker combination in the biological sample to be tested, and transmits the level data to the analysis and judgment module; the analysis and judgment module judges the level data of the marker combination, and outputs a prediction or diagnosis result: the sample is in the gout attack period, gout remission period or healthy period; wherein the marker combination is defined in the application as described in any one of claims 1-4.

11. The diagnostic system or predictive model of claim 10, wherein: The biological sample is defined as in the application of claim 6.

12. A computer-readable storage medium for implementing the functions of the diagnostic system or the prediction model according to claim 10 or 11, wherein the computer-readable storage medium stores a computer program.

13. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: The processor is configured to execute the computer program to implement the functions of the diagnostic system or prediction model as claimed in claim 10 or 11.

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