Fluorescent antibody composition and kit for predicting SLE activity level, and use

Abstract

The present application relates to the technical field of biomedicine, and provides a fluorescent antibody composition and a kit for predicting SLE activity level, and a use. In the use, SLE activity level is predicted on the basis of a subset proportion value which is obtained by using an antibody within an antibody composition to label an Unswitched memory B (UMB) cell subset. By identifying a significant decrease in the proportion of UMB cells in peripheral blood of an SLE patient, the present application provides a novel immunological detection index, enabling more accurate distinguishing between SLE patients in active and inactive phases. The method for using the antibody to label UMB cells and calculating the proportion thereof exhibits high sensitivity and specificity, providing a new tool and data support for immunological research and clinical treatment of SLE, thereby improving the accuracy and efficiency of research.

Description

Fluorescent antibody compositions, kits and uses for predicting SLE activity level

[0001] Cross-reference to related applications

[0002] This application claims priority to the Chinese patent application No. 202411353241.4, filed on September 26, 2024, and entitled “Fluorescent antibody compositions, kits and uses for predicting SLE activity level”, the entire content of which is incorporated herein by reference. TECHNICAL FIELD

[0003] The present application relates to the field of biomedical technology, in particular, to a fluorescent antibody composition, a kit and uses for predicting SLE activity level. BACKGROUND

[0004] Systemic lupus erythematosus (SLE) is a chronic, inflammatory and autoimmune disease, whose pathological features mainly manifest as the production of multiple autoantibodies and immune complexes, leading to multiple organ and tissue damage in the liver, kidney and other organs. The global incidence and prevalence of SLE show significant regional differences, but it is generally believed that the prevalence in women is higher than that in men. The clinical manifestations of this disease are complex and variable, and the individual differences are significant, which brings great challenges to the diagnosis and treatment of clinicians, and also limits the in-depth study of the disease mechanism of SLE. In the pathological process of SLE, the abnormal balance of peripheral blood B cell subsets, such as the increase of regulatory B cells, double negative B cells and plasma cells, is closely related to the activity and organ damage of the disease.

[0005] In the existing technology, the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) is a widely used assessment and prediction tool in clinical practice. Doctors quantitatively evaluate the patient's symptoms in the past 10 days, and divide the patients into different activity levels to develop effective treatment strategies. Although SLEDAI score has certain clinical application value, it has limitations and may not be suitable for all SLE patients, especially those with special clinical manifestations or combined with other diseases. The existing assessment and prediction tools are single, and lack comprehensive, accurate and objective laboratory indicators to assess disease activity, which limits the accurate assessment of SLE disease activity.

[0006] The imbalance and dysfunction of B cell subsets play an important role in the progression of SLE patients. Studies have shown that in the peripheral blood of SLE patients in the active stage, the number of B cells is significantly reduced, while certain specific B cell subsets such as CD27 ++ CD38 + CD138 + Plasma cells and CD27 +The number and proportion of memory B cells significantly increased and were positively correlated with the amount of anti-dsDNA antibodies in the patient's serum. These findings suggest that B cell subpopulation abnormalities may serve as a clinical indicator for assessing the activity of SLE patients. However, current research on B cell dysfunction in SLE patients has mainly focused on exploring the mechanisms of B cell immune abnormalities in SLE patients, and there is a lack of characteristic immune-related indicators and immune indicators for B cell activation to judge the disease activity of SLE.

[0007] In summary, the existing methods for assessing and predicting the activity of SLE have obvious shortcomings. First, the assessment and prediction tools are single, mainly relying on the clinical symptoms of patients, and lack laboratory support. Second, the existing assessment and prediction methods may not be suitable for all SLE patients, especially those with special clinical manifestations, whether they are treated with drugs or have other diseases. In addition, although the abnormalities of B cell subpopulations have been confirmed to be related to the disease activity of SLE, there is currently a lack of effective immune markers to accurately assess the changes in B cell subpopulations in SLE patients. These defects collectively lead to inaccurate assessment of the disease activity of SLE, limiting the ability to accurately diagnose and treat SLE patients. Therefore, developing new and more accurate methods for assessing and predicting the disease activity of SLE, especially immune markers that can reflect changes in B cell subpopulations in SLE patients, has important clinical significance for improving the diagnosis and treatment of SLE.

[0008] In view of the above, the present application is proposed.

[0009] SUMMARY

[0010] The purpose of the present application is to provide a fluorescent antibody composition, kit and application for predicting the activity level of SLE. Among them, the application is for the prediction and evaluation of the non-diagnostic purpose of the SLE activity of the to-be-tested personnel, which has the advantages of being able to effectively predict the activity level of SLE of the to-be-tested personnel, simple operation, easy popularization, etc.

[0011] In order to achieve the above-mentioned purpose of the present application, the following technical solutions are adopted:

[0012] In a first aspect, the present application provides an antibody composition for preparing a kit for predicting the activity level of SLE, wherein the prediction of the activity level of SLE is obtained by using the antibodies in the antibody composition to label the subpopulation of UMB cells to obtain a subpopulation proportion value, and the prediction result is obtained according to the subpopulation proportion value.

[0013] In an optional embodiment, the method for predicting the activity level of SLE comprises:

[0014] Collecting the peripheral blood of the to-be-tested personnel as a target sample;

[0015] labeling the UMB cell subpopulation in the target sample with the fluorescent antibody composition based on flow cytometry, and obtaining a UMB subpopulation proportion value;

[0016] obtaining the prediction result according to the UMB subpopulation proportion value.

[0017] In an optional implementation, the fluorescent antibody composition comprises:

[0018] anti-human CD19 antibody, anti-human CD27 antibody and anti-human IgD antibody with fluorescent labels.

[0019] In an optional implementation, the obtaining the prediction result according to the UMB subpopulation proportion value comprises:

[0020] obtaining a median of the UMB subpopulation proportion value as an evaluation value;

[0021] obtaining the prediction result according to the evaluation value and a preset evaluation threshold.

[0022] In an optional implementation, the preset evaluation threshold is 5.295%.

[0023] The obtaining the prediction result according to the evaluation value and a preset evaluation threshold comprises:

[0024] comparing the evaluation value with the preset evaluation threshold;

[0025] if the evaluation value is not greater than 5.295%, the prediction result is that the target sample corresponds to the subject in an SLE active stage;

[0026] if the evaluation value is greater than 5.295%, the prediction result is that the target sample corresponds to the subject in an SLE inactive stage.

[0027] In an optional implementation, the collecting peripheral blood of a subject to be tested as a target sample comprises:

[0028] collecting peripheral blood of the subject to be tested with a blood collection container containing an EDTA anticoagulant to obtain the target sample.

[0029] In an optional implementation, the labeling the UMB cell subpopulation in the target sample with the fluorescent antibody composition based on flow cytometry, and obtaining a UMB subpopulation proportion value comprises:

[0030] processing the target sample into a single cell suspension;

[0031] adding the fluorescent antibody composition into the single-cell suspension to obtain a mixed sample to be tested;

[0032] detecting the mixed sample to be tested based on flow cytometry to obtain the UMB subpopulation ratio value corresponding to the target sample.

[0033] In an optional embodiment, the processing of the target sample into a single-cell suspension comprises:

[0034] lysis of the target sample using a red blood cell lysis solution;

[0035] centrifuging to remove supernatant, adding PBS buffer for washing, again removing supernatant, adding cell staining buffer for resuspension to obtain the single-cell suspension.

[0036] In a second aspect, the present application provides a fluorescent antibody composition for predicting the activity level of SLE, comprising: anti-human CD19 antibody, anti-human CD27 antibody and anti-human IgD antibody with fluorescent labels.

[0037] In a third aspect, the present application provides a kit, comprising: the fluorescent antibody composition according to the foregoing embodiments, a whole blood red blood cell lysis solution, a PBS buffer and a cell staining buffer.

[0038] Compared with the prior art, the present application has the following beneficial effects:

[0039] (1) By first discovering the significant decrease of UMB cell ratio in the peripheral blood of SLE patients, the present application provides a new laboratory immune-related detection index for SLE. The discovery and application of this index help to improve the prediction accuracy of SLE, especially in distinguishing active and non-active SLE patients.

[0040] (2) The method of the present application for labeling UMB cell subpopulation by antibodies and obtaining subpopulation ratio value can predict the activity level of SLE. The prediction result of this method has high sensitivity and specificity, and compared with conventional laboratory indexes, it can provide more accurate disease activity-related data for further research work.

[0041] (3) By providing a detection method for UMB cell subpopulation, the present application provides a new tool for researchers, which helps to further study the immunological mechanism of SLE. The application of this tool can promote the understanding of the pathological process of SLE, especially the research on the changes of B cell subpopulation.

[0042] (4) The method of using antibody to label UMB cell subpopulation to obtain subpopulation proportion value can provide a quantitative index, which helps researchers to more accurately evaluate the immune status of SLE patients. The application of this quantitative method can improve the reliability and repeatability of research data.

[0043] (5) By predicting the disease activity of SLE patients, it helps medical staff to further develop effective treatment plans and provides theoretical and data support for scientific researchers.

[0044] In summary, the present application has significant beneficial effects in providing new research tools, improving research accuracy, improving research efficiency, and promoting interdisciplinary research. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the description of the specific embodiments or the prior art will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings without creative labor on the basis of these drawings.

[0046] Figure 1 is a flowchart of the method for predicting the activity level of SLE in the embodiments of the present application;

[0047] Figure 2 is a representative flow cytometry result analysis chart of the proportion of total CD19 + B cells (A) and UMB cell subpopulation (B) in the peripheral blood of healthy controls, non-active SLE patients and active SLE patients in the embodiments of the present application;

[0048] Figure 3 is a chart of the proportion of UMB cell subpopulation in the peripheral blood of healthy controls, non-active SLE patients and active SLE patients in the embodiments of the present application (A is the healthy control group and the total SLE patient group, B is the healthy control group, the non-active SLE patient group and the active SLE patient group);

[0049] Figure 4 is a schematic diagram of the correlation analysis of SLE patient plasma C3 level (A), anti-dsDNA antibody level (B) and disease activity in the embodiments of the present application;

[0050] Figure 5 is a schematic diagram of the proportion of UMB cell subpopulation in the peripheral blood of SLE patients to distinguish the overall disease activity of SLE children (A is the ROC curve of healthy controls and non-active SLE patients, B is the ROC curve of healthy controls and active SLE patients). DETAILED DESCRIPTION

[0051] The embodiments of the present application will be described in detail below with examples, but those skilled in the art will understand that the following examples are only used to illustrate the present application, and should not be regarded as limiting the scope of the present application. The specific conditions are not specified in the examples, and the conventional conditions or the conditions recommended by the manufacturer are used. The reagents or instruments used are not specified by the manufacturer, and are conventional products that can be obtained by purchase.

[0052] In the embodiments of the present application, the application of the antibody composition in the preparation of a kit for predicting the activity level of SLE is provided. The prediction of the activity level of SLE is obtained by using the antibodies in the antibody composition to mark the subpopulation of UMB cells to obtain a subpopulation ratio value, and obtaining a prediction result according to the subpopulation ratio value.

[0053] It should be noted that the application of the antibody composition provided in the embodiments of the present application in the preparation of a kit for predicting the activity level of SLE, wherein the evaluation method, evaluation index, antibody composition, and kit are applied for non-diagnostic purposes, and cannot directly obtain the disease diagnosis result or health status of the testee. The prediction result obtained is also a probabilistic activity prediction result, and is at the basic research level. The correlation between the activity level of SLE and UMB cells is discussed through the kit and related antibodies and methods, and the evaluation structure is used to provide qualitative and quantitative data support and theoretical support for in-depth research of researchers.

[0054] It should be noted that B cells can differentiate into multiple different subpopulations, each of which plays a different role in the immune response. The use of antibodies helps to distinguish these subpopulations, including UMB cells and other such as switched memory B cells.

[0055] UMB cells, also known as Unswitched Memory B cells, are a special subpopulation of B cells. During the development and differentiation of B cells, they can remember the pathogen they have encountered without producing antibodies, forming memory B cells. These memory B cells can be further subdivided into different subpopulations according to their surface markers and functional characteristics.

[0056] Antibodies can specifically recognize and bind to specific antigens on the surface of target cells. By using antibodies against UMB cell surface markers, UMB cell subpopulations can be accurately identified and distinguished. Antibody labeling allows quantitative analysis of UMB cells by flow cytometry and other devices. By measuring the intensity of fluorescence or other detection signals bound to the antibody, the proportion of UMB cells in total B cells can be calculated.

[0057] In summary, the use of antibodies to label UMB cell subpopulations is to enable accurate identification and quantification of these cells, thereby providing valuable information in immunological research and clinical applications.

[0058] The embodiments of the present application provide a new laboratory immune-related detection index by the first discovery of the significant decrease of the proportion of UMB cells in the peripheral blood of SLE patients, which helps to improve the accuracy of SLE evaluation and prediction, especially in distinguishing active and non-active SLE patients. Using the method of labeling UMB cell subpopulations with antibodies and obtaining subpopulation proportion values, the embodiments of the present application can predict the activity level of SLE, and compared with conventional laboratory indicators, provide prediction results with higher sensitivity and specificity. In addition, the UMB cell subpopulation detection method provided by the embodiments of the present application provides a new tool for researchers, which helps to further study the immunological mechanism of SLE, especially the changes in B cell subpopulations, thereby promoting the understanding of the pathological process of SLE. Through quantitative indicators, the application provided by the embodiments of the present application helps researchers to more accurately evaluate the immune status of SLE patients and improve the reliability and repeatability of research data. In summary, the embodiments of the present application have significant beneficial effects in providing new research tools, improving research accuracy, improving research efficiency, and promoting interdisciplinary research.

[0059] Optionally, with reference to FIG. 1, the method for predicting the activity level of SLE comprises:

[0060] Step S1, collecting peripheral blood of a person to be tested as a target sample;

[0061] Step S2, labeling UMB cell subpopulations in the target sample using a fluorescent antibody composition based on flow cytometry, and obtaining a UMB subpopulation proportion value;

[0062] Step S3, obtaining the prediction result according to the UMB subpopulation proportion value.

[0063] Optionally, the fluorescent antibody composition comprises:

[0064] Anti-human CD19 antibody, anti-human CD27 antibody and anti-human IgD antibody with fluorescent labeling.

[0065] The above-mentioned anti-human CD19 antibody, anti-human CD27 antibody and anti-human IgD antibody are all antibodies with fluorescent labeling.

[0066] In one embodiment, after being labeled with different fluorescent labels, they can be respectively:

[0067] Anti-human CD19-FITC antibody, anti-human-CD27-PerCP-Cy5.5 antibody and anti-human IgD-APC-Cy7 antibody.

[0068] Optionally, the step S3 of obtaining the prediction result according to the UMB subpopulation ratio value comprises:

[0069] S31, obtaining the median of the UMB subpopulation ratio value as an evaluation value;

[0070] S32, obtaining the prediction result according to the evaluation value and a preset evaluation threshold.

[0071] Optionally, the preset evaluation threshold is 5.295%.

[0072] The step of obtaining the prediction result according to the evaluation value and a preset evaluation threshold comprises:

[0073] comparing the evaluation value with the preset evaluation threshold;

[0074] if the evaluation value is not greater than 5.295%, the prediction result is that the target sample corresponds to a person to be tested in the SLE active period;

[0075] if the evaluation value is greater than 5.295%, the prediction result is that the target sample corresponds to a person to be tested in the SLE inactive period.

[0076] In the above steps, the method provided is to compare the ratio value of UMB cell subpopulation (evaluation value) with the preset evaluation threshold (5.295%) to obtain a specific method for predicting the results of SLE active period.

[0077] In the above steps, a specific preset evaluation threshold is set, i.e. 5.295%. This threshold is based on the median of the UMB cell subpopulation ratio value to distinguish the active period and the inactive period of SLE.

[0078] In the above method, a binary prediction model is proposed, i.e.

[0079] (1) If the UMB cell subpopulation ratio value is not greater than 5.295%, the prediction result indicates that the target sample corresponds to a person to be tested in the SLE active period.

[0080] (2) If the UMB cell subpopulation ratio value is greater than 5.295%, the prediction result indicates that the target sample corresponds to a person to be tested in the SLE inactive period.

[0081] Among them, as a prediction result, it is a result with a certain probability, and the probability of the evaluation result of the person to be tested with respect to the activity of systemic lupus erythematosus disease is obtained by analysis.

[0082] If the proportion of UMB cell subpopulation is not greater than 5.295%, it can be indicated that the probability of the to-be-tested person being in the active stage of SLE is greater.

[0083] If the proportion of UMB cell subpopulation is greater than 5.295%, the prediction result indicates that the probability of the to-be-tested person corresponding to the target sample being in the inactive stage of SLE is greater.

[0084] In the method, the prediction result cannot directly obtain the diagnosis result or health status of the to-be-tested person, but is a tendency on the probability level, so the prediction result can be used as one of the references for researchers to conduct research and medical staff to further comprehensively evaluate other test indicators.

[0085] Optionally, the step S1 of collecting peripheral blood of the to-be-tested person as a target sample comprises:

[0086] The step S11 comprises collecting peripheral blood of the to-be-tested person by using a blood collection container containing an EDTA anticoagulant to obtain the target sample.

[0087] EDTA, which is the full name of Ethylenediaminetetraacetic acid, is an anticoagulant that can effectively prevent a series of reactions in the blood coagulation process by combining with calcium ions in the blood, thereby achieving the anticoagulation effect on the blood.

[0088] In the experiment of predicting the activity of systemic lupus erythematosus (SLE), the EDTA-anticoagulated peripheral blood sample can ensure that the proportion of UMB cell subpopulation needs to be accurately measured in flow cytometry, and the use of EDTA anticoagulation helps to maintain the original state of the cells, thereby obtaining accurate data. By preventing blood coagulation, cell damage or analysis errors caused by blood coagulation are avoided, and the reliability of the experimental results is improved.

[0089] Optionally, the step S2 of marking the UMB cell subpopulation in the target sample by using the fluorescent antibody composition based on flow cytometry and obtaining a UMB subpopulation proportion value comprises:

[0090] The step S21 comprises processing the target sample into a single-cell suspension.

[0091] The step S22 comprises adding the fluorescent antibody composition to the single-cell suspension to obtain a to-be-tested mixed sample.

[0092] The step S23 comprises detecting the to-be-tested mixed sample based on flow cytometry to obtain the UMB subpopulation proportion value corresponding to the target sample.

[0093] The flow cytometry is a technology applied in the fields of biology and medicine, and the core of the technology is to analyze each cell in a cell suspension at a high speed and classify the cells according to the measured parameters.

[0094] In step S23, the flow cytometry can be used to detect the mixed sample to be tested. After the raw data are obtained, the FlowJo_V10 analysis software can be used to analyze the raw data, so as to obtain the UMB subpopulation ratio value.

[0095] Optionally, in step S21, the target sample is processed into a single cell suspension, including:

[0096] In step S211, the target sample is lysed by using a red blood cell lysis solution.

[0097] In step S212, the supernatant is removed by solid-liquid separation, and then the PBS buffer is added for washing. After the supernatant is removed again, the cell staining buffer is added for resuspension, so as to obtain the single cell suspension.

[0098] In the above steps, the red blood cells are removed, because the number of red blood cells is much larger than that of white blood cells, and the red blood cells may interfere with the subsequent cell analysis. The blood sample is mixed with the red blood cell lysis solution, so that the red blood cells are broken and hemoglobin is released, and the white blood cells remain intact.

[0099] Then, the red blood cell fragments and hemoglobin after lysis are removed. The cell fragments and hemoglobin can be separated from the white blood cells by centrifugation, and then the supernatant is removed. This step is used to purify the sample, so as to provide a clear background for subsequent cell labeling and analysis.

[0100] Optionally, in step S212, the PBS buffer is added to remove the residual red blood cell fragments and hemoglobin, and to balance the ion concentration inside and outside the cells. The phosphate buffer solution (PBS) is added to the precipitated white blood cells, and then the cells are washed by centrifugation and removal of the supernatant. Thus, the activity and stability of the cells are improved, and non-specific binding is reduced.

[0101] Finally, the cell staining buffer is added for resuspension, so as to uniformly disperse the white blood cells, and facilitate subsequent antibody labeling and flow cytometry detection. After the supernatant of the last washing is removed, an appropriate amount of cell staining buffer is added, and the cells are gently suspended. Thus, a uniform single cell suspension is formed, and a standardized sample is provided for subsequent experiments.

[0102] In the embodiments of the present application, a fluorescent antibody composition for predicting the activity level of SLE is also provided, including: an anti-human CD19 antibody, an anti-human CD27 antibody and an anti-human IgD antibody with fluorescent labels.

[0103] In the embodiments of the present application, a kit is also provided, comprising: the fluorescent antibody composition, the whole blood red blood cell lysate, the PBS buffer and the cell staining buffer as described in the foregoing embodiments.

[0104] The present application is further illustrated by specific examples below, but it should be understood that these examples are only used for more detailed illustration, and should not be understood as limiting the present application in any form.

[0105] Example 1:

[0106] In the embodiments, statistical analysis, correlation investigation and ROC curve analysis of the proportion of UMB cell subgroups are performed.

[0107] 1. Experimental samples:

[0108] In the embodiments, the peripheral blood and laboratory-related indicators (Tables 1-3) of 25 healthy control groups (HC1-HC25), 20 non-active SLE patients and 20 active SLE patients (SLE1-SLE40) are collected; among them, the age and gender distribution of the patients are similar, and they have not received targeted B cell antibody drug treatment, and the active (SLEDAI≥4) and non-active (SLEDAI<4) patients are distinguished according to SLEDAI score.

[0109] 2. Kit:

[0110] Whole blood red blood cell lysate (purchased from BD Biosciences), 1×PBS buffer (purchased from BD Biosciences), cell staining buffer (1% FBS-containing 1×PBS buffer) and fluorescent antibody composition.

[0111] The fluorescent antibody composition comprises:

[0112] (1) Anti-human CD19-FITC antibody (clone number HIB19);

[0113] (2) Anti-human-CD27-PerCP-Cy5.5 antibody (clone number M-T271);

[0114] (3) Anti-human IgD-APC-Cy7 antibody (clone number IA6-2).

[0115] 3. Experimental method:

[0116] (1) Collect 1-2 mL of peripheral blood of healthy controls and SLE patients with purple vacuum blood collection tubes containing EDTA anticoagulant;

[0117] (2) Process the peripheral blood sample to be detected to form a single cell suspension:

[0118] First, the collected peripheral blood is lysed with red blood cell lysate. 2 mL of red blood cell lysate is added to every 200 μL of peripheral blood, and lysed at room temperature for 10 min. During the lysis, the mixture is gently mixed once with a pipette.

[0119] Then, centrifuge at 350 g for 5 min, discard the supernatant, add 1xPBS to 2 mL;

[0120] Finally, centrifuge at 350 g for washing, discard the supernatant, and resuspend in 100 μL of cell staining buffer to form a single cell suspension.

[0121] (3) In the single cell suspension obtained in step (2), different fluorescently labeled monoclonal antibodies in the fluorescent antibody composition are added for staining:

[0122] First, for each sample, prepare 2 flow tubes, 1 tube as the test tube, and 1 tube as the isotype control tube. Each tube contains the single cell suspension prepared in step (2).

[0123] Then, add 1 μL of different fluorescently labeled monoclonal antibodies in the fluorescent antibody composition to the test tube and the isotype tube, respectively, as follows:

[0124] A. In the isotype control tube, only add 1 μL of anti-CD19 antibody;

[0125] B. In the test tube, add 1 μL of anti-CD19 antibody, 1 μL of anti-CD27 antibody, and 1 μL of anti-IgD antibody;

[0126] After gentle mixing, incubate at 4°C in the dark for 15 minutes.

[0127] Finally, add 500 μL of cell staining buffer to wash the cells at 350 g for 5 min; after centrifugation, remove the supernatant, resuspend the cells in 200 μL of cell staining buffer, and obtain the test mixture.

[0128] (4) Detect the sample on the flow cytometer:

[0129] For the resuspended cell sample obtained in step (3), i.e. the test mixture, use the flow analyzer (FACSVerse) to analyze and obtain the raw data of UMB cell subgroups:

[0130] The obtained raw data is analyzed by FlowJo Software, and the analyzed data is summarized and analyzed by Graph pad Prism8.2.1 software, and the P value is calculated.

[0131] 3. Data analysis:

[0132] (1) The method in Example 1 was used to select healthy samples from the experimental samples in Example 1 as healthy controls, non-active SLE patients and active SLE patients, and the peripheral blood of these samples was detected by flow cytometry. The detection results were analyzed by FlowJo_V10 analysis software, and the total CD19 + B cell and UMB subpopulation ratio values (Tables 1-3).

[0133] Table 1, related information and data of the healthy control group

[0134] In the above table, the sample number of the healthy control group is HC, and the sample numbers HC1-HC25 are respectively.

[0135] Table 2, related information and data of the non-active SLE patient group (1-20)

[0136] In the above table, the sample number of the non-active SLE patient group is SLE, and the sample numbers SLE1-SLE20 are respectively.

[0137] Table 3, related information and data of the active SLE patient group (21-40)

[0138] In the above table, the sample number of the active SLE patient group is SLE, and the sample numbers SLE21-SLE40 are respectively.

[0139] Referring to FIG. 2, the flow cytometry results are shown, wherein FIG. 2A shows the representative flow cytometry results of the total CD19 + B cell ratio in the peripheral blood of the healthy control group, non-active SLE patients and active SLE patients, and FIG. 2B shows the representative flow cytometry results of the UMB subpopulation ratio of the total CD19 + B cells from FIG. 2A in the peripheral blood of the healthy control group, non-active SLE patients and active SLE patients.

[0140] (2) Statistical analysis of the change of UMB cell subpopulation ratio in the peripheral blood of the healthy control group, total SLE patients, non-active SLE patients and active SLE patients found that: using Graph pad Prism8.2.1 software to analyze the UMB cell subpopulation ratio in each group in Tables 1-3 by Descriptive statistics, it was found that the median of the UMB cell subpopulation ratio in the healthy control group, total SLE patients, non-active SLE patients and active SLE patients was 7.150%, 5.295%, 7.915% and 3.985% respectively.

[0141] (3) Referring to FIG. 3, the proportions of UMB cell subgroups in each group in Tables 1-3 were subjected to Mann-Whitney test and one-way ANOVA analysis using Graph pad Prism 8.2.1 software. Among them, FIG. 3A shows that the proportion of UMB in the peripheral blood of total SLE patients is significantly lower than that of healthy controls (p=0.005), and FIG. 3B shows that the proportion of UMB in the peripheral blood of active SLE patients is significantly lower than that of healthy controls (p=0.0009) and non-active SLE patients (p=0.0008).

[0142] Therefore, it can be concluded that when the proportion of UMB subgroups in the peripheral blood of SLE patients is not greater than 5.295%, it is more likely to be active SLE, and when the proportion is greater than 5.295%, it is more likely to be non-active SLE.

[0143] (4) Correlation of UMB cell proportion with disease activity and diagnostic analysis:

[0144] For the aforementioned samples, active (SLEDAI≥4) and non-active (SLEDAI<4) patients were distinguished according to SLEDAI scores. Complement C3 and anti-dsDNA antibodies are key indicators of SLE disease activity, and a decrease in C3 and an increase in anti-dsDNA antibodies are associated with SLE disease activity.

[0145] As shown in FIG. 4, Pearson correlation analysis was performed on the proportions of UMB cell subgroups and the corresponding C3 levels or anti-dsDNA antibody concentrations in Tables 2-3 using Graph pad Prism 8.2.1 software. It was found that the proportion of UMB cells was significantly positively correlated with C3 and significantly negatively correlated with anti-dsDNA antibodies.

[0146] FIG. 5 is a schematic diagram of patient UMB cell proportion distinguishing disease activity, and ROC analysis was performed on the proportions of UMB cell subgroups in each group in Tables 1-3 using Graph pad Prism 8.2.1 software. Among them, 4A is the ROC curve of healthy controls and non-active SLE patients (p=0.9818), and 4B is the ROC curve of healthy controls and active SLE patients (p<0.0001).

[0147] Example 2:

[0148] In this example, based on the method and kit in Example 1, the prediction of SLE disease activity was performed on the following samples.

[0149] 1. Experimental samples:

[0150] (1) Known non-active SLE patients: Sample 1;

[0151] (2) Known SLE active patients: Sample 2;

[0152] (3) SLE samples with unknown activity: Sample 3 and Sample 4.

[0153] 2. Experimental methods:

[0154] The same as in Example 1.

[0155] 3. Experimental results and analysis:

[0156] Table 4. UMB cell subpopulation ratio prediction data and results for Samples 1-4

[0157] In this example, the experimental methods are the same as in Example 1, including the use of EDTA anticoagulation blood sampling, preparation of single cell suspension, fluorescence antibody staining, flow cytometry detection and data analysis. Then, data analysis is performed for two known samples and two unknown samples, respectively.

[0158] Sample 1: To be evaluated value: 7.312%, higher than the preset evaluation threshold 5.295%. Prediction result: predicted as SLE non-active period, consistent with the known status of the sample in the SLE non-active period, verifying the accuracy of the detection method.

[0159] Sample 2: To be evaluated value: 2.778%, lower than the preset evaluation threshold 5.295%. Prediction result: predicted as SLE active period, consistent with the known status of the SLE active period patient, verifying the effectiveness of the detection method again.

[0160] Sample 3: To be evaluated value: 8.339%, higher than the preset evaluation threshold 5.295%. Prediction result: predicted as SLE non-active period, for unknown samples, the result suggests that the sample may not be in the active period of SLE.

[0161] Sample 4: To be evaluated value: 4.318%, lower than the preset evaluation threshold 5.295%. Prediction result: predicted as SLE active period, for unknown samples, the result suggests that the sample may be in the active period of SLE.

[0162] In summary, by comparing the prediction results of sample 1 and sample 2 with the actual state, the prediction accuracy of this method can be verified. For sample 3 and sample 4, which are unknown states, this method can provide predictions about the activity of SLE, convert quantitative results into qualitative predictions, provide data supplements for scientific research, and provide references for clinical decision-making; through the test results of different samples, the effectiveness of 5.295% as the threshold of the proportion of UMB cell subpopulation in distinguishing SLE active and inactive periods can be further confirmed. Example 2 repeats the experimental process of example 1, showing the reproducibility of this method in different samples. This method can be used as a supplement to existing SLE disease activity assessment tools, providing more objective laboratory indicators.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application. Industrial applicability

[0164] Through the first discovery of the significant decrease of the proportion of UMB cells in the peripheral blood of SLE patients, the present application provides a new laboratory immunological detection indicator for SLE. The discovery and application of this indicator help to improve the prediction accuracy of SLE evaluation, especially in distinguishing active and inactive SLE patients. The method of the present application for labeling UMB cell subpopulation with antibodies and obtaining subpopulation proportion value can predict the activity level of SLE. The prediction results of this method have high sensitivity and specificity, and compared with conventional laboratory indicators, it can provide more accurate disease activity related data for further research. By providing a detection method for UMB cell subpopulation, the present application provides a new tool for researchers, which helps to further study the immunological mechanism of SLE. The application of this tool can promote the understanding of the pathological process of SLE, especially the research on the changes of B cell subpopulation. The method of labeling UMB cell subpopulation with antibodies and obtaining subpopulation proportion value can provide a quantitative indicator, which helps researchers to more accurately evaluate the immune status of SLE patients. The application of this quantitative method can improve the reliability and repeatability of research data. By predicting the disease activity of SLE patients, it helps to provide a reference for medical personnel to further develop effective treatment plans and provide theoretical and data support for researchers.

Claims

1. Use of an antibody composition in the manufacture of a kit for predicting the level of SLE activity, characterized in that, The prediction of the SLE activity level is obtained by marking the UMB cell subpopulation in the antibody composition with antibodies to obtain a subpopulation ratio value, and obtaining a prediction result according to the subpopulation ratio value.

2. Use according to claim 1, wherein The method for predicting the SLE activity level comprises the following steps: Peripheral blood of a to-be-tested person is collected as a target sample; Based on flow cytometry, a UMB cell subpopulation in the target sample is marked by using a fluorescent antibody composition to obtain a UMB subpopulation ratio value; The prediction result is obtained according to the UMB subpopulation ratio value.

3. Use according to claim 2, wherein the compound is ###0002### The fluorescent antibody composition comprises: fluorescently labeled anti-human CD19 antibodies, anti-human CD27 antibodies and anti-human IgD antibodies.

4. Use according to claim 2 or 3, wherein the compound is ###0002### The prediction result obtained according to the UMB subpopulation ratio value comprises the following steps: The median of the UMB subpopulation ratio value is obtained as an evaluation value; The prediction result is obtained according to the evaluation value and a preset evaluation threshold.

5. The use according to claim 4, wherein the compound is ###0002### The preset evaluation threshold is 5.295%. The prediction result obtained according to the evaluation value and the preset evaluation threshold comprises: The evaluation value is compared with the preset evaluation threshold; If the evaluation value is not greater than 5.295%, the prediction result is that the to-be-tested person corresponding to the target sample is in an SLE active period; If the evaluation value is greater than 5.295%, the prediction result is that the to-be-tested person corresponding to the target sample is in an SLE inactive period.

6. Use according to any one of claims 2 to 5, wherein the compound is of formula (I) ###0001### (I) or a pharmaceutically acceptable salt thereof. The peripheral blood of the to-be-tested person is collected as the target sample, comprising the following steps: The peripheral blood of the to-be-tested person is collected in a blood collection container containing an EDTA anticoagulant to obtain the target sample.

7. Use according to any one of claims 2 to 6, wherein the compound is of formula (I) ###0001### (I) or a pharmaceutically acceptable salt thereof. The UMB cell subpopulation in the target sample is marked by using the fluorescent antibody composition based on flow cytometry to obtain a UMB subpopulation ratio value, comprising the following steps: The target sample is processed into a single-cell suspension; The fluorescent antibody composition is added to the single-cell suspension to obtain a to-be-tested mixed sample; The to-be-tested mixed sample is detected based on flow cytometry to obtain the UMB subpopulation ratio value corresponding to the target sample.

8. Use according to claim 7, wherein the compound is ###0002### The target sample is processed into a single-cell suspension, comprising the following steps: The target sample is lysed by using a red blood cell lysis solution; The supernatant is removed by centrifugation, and PBS buffer is added for washing. After the supernatant is discarded again, cell staining buffer is added for resuspension to obtain the single-cell suspension.

9. A fluorescent antibody composition for predicting the level of SLE activity, characterized in that, The fluorescent antibody composition comprises: fluorescently labeled anti-human CD19 antibodies, anti-human CD27 antibodies and anti-human IgD antibodies.

10. A kit characterized in that, The fluorescent antibody composition, the whole blood red blood cell lysis solution, the PBS buffer and the cell staining buffer of claim 9 are included. The method comprises marking the UMB cell subpopulation in the antibody composition with antibodies to obtain a subpopulation ratio value, and obtaining a prediction result according to the subpopulation ratio value.

11. A method of predicting the level of SLE activity, characterized in that, The UMB cell subpopulation in the antibody composition is marked with antibodies to obtain a subpopulation ratio value, comprising the following steps:

12. The method of claim 11, wherein, Peripheral blood of a to-be-tested person is collected as a target sample; ​ Based on flow cytometry, a fluorescent antibody composition is used to label a UMB cell subpopulation in the target sample, and a UMB subpopulation proportion value is obtained.

13. The method of claim 12, wherein, The fluorescent antibody composition comprises: a fluorescently labeled anti-human CD19 antibody, an anti-human CD27 antibody, and an anti-human IgD antibody.

14. The method of claim 12 or 13, wherein, The method further comprises the following steps of: obtaining a median value of the UMB subpopulation proportion value as an evaluation value; obtaining the prediction result according to the evaluation value and a preset evaluation threshold.

15. The method of claim 14, wherein, The preset evaluation threshold is 5.295%. The method further comprises the following steps of: comparing the evaluation value with the preset evaluation threshold; if the evaluation value is not greater than 5.295%, the prediction result is that the target sample corresponds to a SLE active period of the testee; if the evaluation value is greater than 5.295%, the prediction result is that the target sample corresponds to a SLE inactive period of the testee.

16. The method of any one of claims 12-15, wherein, The method further comprises the following steps of: collecting peripheral blood of a testee as a target sample; 17. The method of any one of claims 12-16, wherein, collecting peripheral blood of the testee in a blood collection container containing an EDTA anticoagulant to obtain the target sample. The method further comprises the following steps of: processing the target sample into a single cell suspension; adding the fluorescent antibody composition to the single cell suspension to obtain a test mixture; 18. The method of claim 17, wherein, detecting the test mixture based on flow cytometry to obtain the UMB subpopulation proportion value corresponding to the target sample. The method further comprises the following steps of: lyzing the target sample using a red blood cell lysis solution; centrifuging to remove supernatant, adding PBS buffer for washing, again removing supernatant, and adding cell staining buffer for resuspension to obtain the single cell suspension.

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