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

Abstract

The invention provides a fluorescent antibody composition for predicting SLE activity level, a kit and application, and relates to the technical field of biomedicine. In the application, the prediction of the SLE activity level comprises the following steps: marking a UMB (Unswitched memory B) cell subset by using an antibody in the antibody composition to obtain a subset proportion value, and obtaining a prediction result according to the subset proportion value. According to the invention, a new immunodetection index is provided by finding that the UMB cell proportion is obviously reduced in peripheral blood of the SLE patient, and the SLE patients in the active stage and the inactive stage can be more accurately distinguished. According to the present invention, the UMB cells are labeled by using the antibody, and the ratio of the UMB cells is calculated, such that the high sensitivity and the high specificity are represented, the new tool and the data support are provided for the immunological research and the clinical treatment of the SLE, and the research accuracy and the research efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of biomedical technology, and in particular to a fluorescent antibody composition, a kit and an application thereof for predicting the activity level of SLE. Background Art

[0002] Systemic lupus erythematosus (SLE) is a chronic, inflammatory, and autoimmune disease, the pathological features of which are mainly the production of a variety of autoimmune antibodies and immune complexes, leading to damage to multiple organs and tissues such as the liver and kidneys. There are significant regional differences in the global incidence and prevalence of SLE, 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 varied, with significant individual differences, which poses a great challenge to clinicians' diagnosis and treatment, and also limits in-depth research on 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 of the disease and organ damage.

[0003] Among the existing technologies, the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) is a widely used assessment and prediction tool in clinical practice. Doctors conduct quantitative assessments based on the patient's symptoms over the past 10 days and classify the patient into different levels of disease activity in order to develop effective treatment strategies. Although the 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 comorbidities 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.

[0004] The imbalance and dysfunction of B cell subsets play an important role in the progression of SLE. Studies have shown that the number of B cells in the peripheral blood of patients with active SLE 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 increased significantly and were positively correlated with the amount of anti-double-stranded DNA antibodies (Anti-dsDNA) in the patient's serum. These findings suggest that abnormalities in B cell subsets may serve as clinical indicators to assist in judging the disease activity of SLE patients. However, current research on B cell dysfunction in SLE patients mainly focuses on exploring the mechanism of B cell immune abnormalities in SLE patients, lacks characteristic immune-related indicators, and has no immune indicators of B cell activation for judging the disease activity of SLE.

[0005] In summary, the existing methods for assessing and predicting SLE disease activity have obvious deficiencies. First, the assessment and prediction tools are single, mainly relying on the patient's clinical symptoms, and lack the support of laboratory tests. Second, the existing assessment and prediction methods may not be suitable for all SLE patients, especially those with special clinical manifestations, whether they are undergoing drug treatment, or with other diseases. In addition, although abnormalities in B cell subsets have been shown to be associated with the disease activity of SLE, there is currently a lack of effective immune markers to accurately assess the changes in B cell subsets in SLE patients. These defects together lead to inaccurate assessments of SLE disease activity and limit the ability to accurately diagnose and treat SLE patients. Therefore, the development of new and more accurate methods for assessing and predicting SLE disease activity, especially immune markers that can reflect changes in B cell subsets in SLE patients, is of great clinical significance for improving the diagnosis and treatment of SLE.

[0006] In view of this, the present invention is proposed. Summary of the invention

[0007] The object of the present invention is to provide a fluorescent antibody composition, a kit and an application for predicting the activity level of SLE. The application is for the prediction and evaluation of the SLE activity level of a person to be tested for non-diagnostic purposes, and has the advantages of being able to effectively predict the activity level of SLE in the person to be tested, being simple to operate and easy to promote.

[0008] In order to achieve the above-mentioned purpose of the present invention, the following technical solutions are particularly adopted:

[0009] In a first aspect, the present invention provides an application of an antibody composition in the preparation of a kit for predicting SLE activity levels, wherein the SLE activity levels are predicted by using antibodies in the antibody composition to label UMB cell subpopulations to obtain subpopulation ratio values, and obtaining prediction results based on the subpopulation ratio values.

[0010] In an alternative embodiment, the method for predicting the SLE activity level comprises:

[0011] Collect peripheral blood from the person to be tested as a target sample;

[0012] Based on flow cytometry, the UMB cell subpopulation in the target sample is labeled with a fluorescent antibody composition, and a UMB subpopulation ratio value is obtained;

[0013] The prediction result is obtained according to the UMB subgroup ratio value.

[0014] In an optional embodiment, the fluorescent antibody composition comprises:

[0015] Fluorescently labeled anti-human CD19 antibody, anti-human CD27 antibody, and anti-human IgD antibody.

[0016] In an optional embodiment, obtaining the prediction result according to the UMB subgroup ratio value includes:

[0017] Obtaining the median of the UMB subgroup ratio value as the value to be evaluated;

[0018] The prediction result is obtained according to the value to be evaluated and a preset evaluation threshold.

[0019] In an optional embodiment, the preset evaluation threshold is 5.295%;

[0020] The step of obtaining the prediction result according to the value to be evaluated and the preset evaluation threshold value includes:

[0021] Comparing the value to be evaluated with the preset evaluation threshold;

[0022] If the value to be evaluated is not greater than 5.295%, the prediction result is that the person to be tested corresponding to the target sample is in the SLE active period;

[0023] If the value to be evaluated is greater than 5.295%, the prediction result is that the person to be tested corresponding to the target sample is in the SLE inactive period.

[0024] In an optional embodiment, the collecting of peripheral blood from a person to be tested as a target sample comprises:

[0025] The peripheral blood of the person to be tested is collected using a blood collection container containing EDTA anticoagulant to obtain the target sample.

[0026] In an optional embodiment, the method of labeling the UMB cell subpopulation in the target sample using the fluorescent antibody composition based on flow cytometry and obtaining the UMB subpopulation ratio value comprises:

[0027] Processing the target sample into a single cell suspension;

[0028] adding the fluorescent antibody composition to the single cell suspension to obtain a mixed sample to be tested;

[0029] Based on flow cytometry, the mixed sample to be tested is detected to obtain the UMB subpopulation ratio value corresponding to the target sample.

[0030] In an optional embodiment, processing the target sample into a single cell suspension comprises:

[0031] The target sample is subjected to a lysis treatment using a red blood cell lysis solution;

[0032] The supernatant was removed by centrifugation, and PBS buffer was added for washing. After the supernatant was discarded again, a cell staining buffer was added for re-suspending to obtain the single cell suspension.

[0033] In a second aspect, the present invention provides a fluorescent antibody composition for predicting the activity level of SLE, comprising: an anti-human CD19 antibody, an anti-human CD27 antibody and an anti-human IgD antibody with a fluorescent label.

[0034] In a third aspect, the present invention provides a kit comprising: the fluorescent antibody composition as described in the above embodiments, whole blood red blood cell lysate, PBS buffer and cell staining buffer.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] (1) Through the first discovery of a significant decrease in the proportion of UMB cells in the peripheral blood of SLE patients, the present invention provides a new SLE laboratory immune-related detection index. The discovery and application of this index helps to improve the accuracy of SLE assessment and prediction, especially in distinguishing active and inactive SLE patients.

[0037] (2) The present invention uses an antibody to label UMB cell subpopulations and obtain a subpopulation ratio value to predict the activity level of SLE. The prediction results of this method have high sensitivity and specificity, and compared with conventional laboratory indicators, can provide more accurate disease activity related data for further research.

[0038] (3) By providing a method for detecting UMB cell subsets, the present invention provides researchers with a new tool that 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 study of changes in B cell subsets.

[0039] (4) The method of using antibodies to label UMB cell subsets to obtain subset ratio values ​​can provide a quantitative indicator that helps researchers more accurately assess the immune status of SLE patients. The application of this quantitative method can improve the reliability and repeatability of research data.

[0040] (5) By predicting the disease activity of SLE patients, it helps to provide a reference for medical staff to further formulate effective treatment plans and provide theoretical and data support for scientific researchers.

[0041] In summary, the present invention has significant beneficial effects in providing new research tools, improving research accuracy, improving scientific research efficiency, and promoting interdisciplinary research. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 This is a flow chart of a method for predicting SLE activity level in an embodiment of the present application;

[0044] Figure 2 The total CD19 in the peripheral blood of the healthy control group, the inactive SLE patients and the active SLE patients in the embodiment of this application + Representative flow cytometry analysis of B cell (A) and UMB cell subset (B) ratios;

[0045] Figure 3 The following is a diagram showing the proportion of peripheral blood UMB cell subsets in the healthy control group, inactive SLE patients and active SLE patients in the embodiment of the present application (A is the healthy control group and the total SLE patients, B is the healthy control group, inactive SLE patients and active SLE patients);

[0046] Figure 4 Schematic diagram of the correlation analysis of plasma C3 level (A), anti-dsDNA antibody level (B) and disease activity in SLE patients in the examples of the present application;

[0047] Figure 5 Schematic diagram of the overall disease activity of SLE children based on the proportion of UMB cell subsets in the peripheral blood of SLE patients in the embodiment of the present application (A is the ROC curve of healthy controls and inactive SLE patients, B is the ROC curve of healthy controls and active SLE patients). DETAILED DESCRIPTION

[0048] The embodiments of the present invention will be described in detail below in conjunction with the examples, but it will be appreciated by those skilled in the art that the following examples are only used to illustrate the present invention and should not be considered as limiting the scope of the present invention. If no specific conditions are specified in the examples, the conditions are carried out according to normal conditions or the conditions recommended by the manufacturer. If the manufacturer of the reagents or instruments used is not specified, they are all conventional products that can be obtained commercially.

[0049] In an embodiment of the present application, there is provided an application of an antibody composition in the preparation of a kit for predicting the activity level of SLE. The prediction of the activity level of SLE is performed by using the antibodies in the antibody composition to label UMB cell subpopulations to obtain subpopulation ratio values, and a prediction result is obtained based on the subpopulation ratio values.

[0050] It should be noted that the use of the antibody composition provided in the examples of the present application in the preparation of a kit for predicting the activity level of SLE, the evaluation method, evaluation index, antibody composition, and kit included therein, are all used for non-diagnostic purposes and cannot directly derive the disease diagnosis results or health status of the person to be tested. The obtained prediction results are also probabilistic activity prediction results, but at the basic research level, the correlation between the SLE activity level and UMB cells is explored 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 the in-depth research of scientific researchers.

[0051] It should be noted that B cells can differentiate into a variety of different subsets, each of which plays a different role in the immune response. The use of antibody markers helps to distinguish these subsets, including UMB cells and others such as switched memory B cells.

[0052] UMB cells, the full name of which is Unswitched Memory Bcells (UMBcells), are a special subpopulation of B cells. During the development and differentiation of B cells, they can remember pathogens they have encountered without producing antibodies, forming memory B cells. These memory B cells can be further subdivided into different subpopulations based on their surface markers and functional characteristics.

[0053] Antibodies are able to specifically recognize and bind to specific antigens on the surface of target cells. By using antibodies against UMB cell surface markers, UMB cell subsets can be accurately identified and distinguished. Antibody labeling allows for quantitative analysis of UMB cells using equipment such as flow cytometry. By measuring the intensity of the fluorescein or other detection signal bound to the antibody, the proportion of UMB cells in total B cells can be calculated.

[0054] In summary, the use of antibodies to label UMB cell subsets is intended to enable precise identification and quantification of these cells, thereby providing valuable information in immunological research and clinical applications.

[0055] The present application embodiment provides a new laboratory immune-related detection index through the phenomenon of significant reduction of UMB cell ratio in peripheral blood of SLE patients discovered for the first time, which helps to improve the accuracy of SLE assessment prediction, especially in distinguishing active and inactive SLE patients. The method of using antibodies to mark UMB cell subpopulations and deriving subpopulation ratio values ​​can predict the activity level of SLE, and provides a prediction result with higher sensitivity and specificity compared to conventional laboratory indicators. In addition, the UMB cell subpopulation detection method provided in the present application embodiment provides researchers with a new tool that helps to further study the immunological mechanism of SLE, especially in the study of changes in B cell subpopulations, thereby promoting the understanding of the pathological process of SLE. Through quantitative indicators, the application provided by the present application embodiment helps researchers to more accurately evaluate the immune status of SLE patients and improve the reliability and repeatability of research data. In summary, the present application embodiment has significant beneficial effects in providing new research tools, improving research accuracy, improving scientific research efficiency, and promoting interdisciplinary research.

[0056] For further reference, Figure 1 Methods for predicting SLE activity level include:

[0057] Step S1, collecting peripheral blood from a person to be tested as a target sample;

[0058] Step S2, based on flow cytometry, using a fluorescent antibody composition to label the UMB cell subpopulation in the target sample, and obtaining a UMB subpopulation ratio value;

[0059] Step S3, obtaining the prediction result according to the UMB subgroup ratio value.

[0060] Furthermore, the fluorescent antibody composition comprises:

[0061] Fluorescently labeled anti-human CD19 antibody, anti-human CD27 antibody, and anti-human IgD antibody.

[0062] The anti-human CD19 antibody, anti-human CD27 antibody and anti-human IgD antibody mentioned above are all antibodies with fluorescent labels.

[0063] In one embodiment, after adding different fluorescent labels, they can be:

[0064] Anti-human CD19-FITC antibody, anti-human-CD27-PerCP-Cy5.5 antibody and anti-human IgD-APC-Cy7 antibody.

[0065] Furthermore, the step S3, obtaining the prediction result according to the UMB subgroup ratio, includes:

[0066] S31, obtaining the median of the UMB subgroup ratio value as the value to be evaluated;

[0067] S32, obtaining the prediction result according to the value to be evaluated and a preset evaluation threshold.

[0068] Furthermore, the preset evaluation threshold is 5.295%;

[0069] The step of obtaining the prediction result according to the value to be evaluated and the preset evaluation threshold value includes:

[0070] Comparing the value to be evaluated with the preset evaluation threshold;

[0071] If the value to be evaluated is not greater than 5.295%, the prediction result is that the person to be tested corresponding to the target sample is in the SLE active period;

[0072] If the value to be evaluated is greater than 5.295%, the prediction result is that the person to be tested corresponding to the target sample is in the SLE inactive period.

[0073] In the above steps, the method provided is to compare the ratio value of the UMB cell subset (the value to be evaluated) with the preset evaluation threshold (5.295%) to obtain a specific method for predicting the SLE activity stage.

[0074] In the above steps, a specific preset evaluation threshold, i.e., 5.295%, is set. This threshold is based on the median of the UMB cell subset ratio value and is used to distinguish between the active and inactive stages of SLE.

[0075] In the above method, a binary prediction model is proposed, namely:

[0076] (1) If the UMB cell subset ratio is not greater than 5.295%, the prediction result indicates that the person to be tested corresponding to the target sample is in the active stage of SLE.

[0077] (2) If the UMB cell subset ratio is greater than 5.295%, the prediction result indicates that the person to be tested corresponding to the target sample is in the inactive stage of SLE.

[0078] Among them, as a prediction result, it is a possible result with a certain probability. The probability of the evaluation result of the disease activity of systemic lupus erythematosus of the person to be tested is obtained through analysis.

[0079] If the UMB cell subset ratio is no greater than 5.295%, it can indicate that the person being tested is more likely to be in the active stage of SLE.

[0080] If the UMB cell subset ratio is greater than 5.295%, the prediction result indicates that the person to be tested corresponding to the target sample is more likely to be in the inactive stage of SLE.

[0081] In this method, the prediction results cannot directly lead to the physical disease diagnosis results or health status of the person being tested, but rather a tendency at the probabilistic level. Therefore, the prediction results can be used as a reference for scientific researchers to conduct research and medical personnel to conduct further comprehensive evaluation in combination with other test indicators.

[0082] Furthermore, the step S1, collecting peripheral blood of the person to be tested as a target sample, includes:

[0083] Step S11, collecting peripheral blood of the person to be tested using a blood collection container containing EDTA anticoagulant to obtain the target sample.

[0084] As mentioned above, EDTA, the full name is ethylenediaminetetraacetic acid (Ethylenediaminetetraacetic acid). EDTA anticoagulant effectively blocks a series of reactions in the blood coagulation process by combining with calcium ions in the blood, thereby achieving an anticoagulant effect on the blood.

[0085] In the experiment of predicting the activity of systemic lupus erythematosus (SLE), the use of EDTA anticoagulated peripheral blood samples can ensure that the proportion of UMB cell subpopulations needs to be accurately measured in flow cytometry. 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 experimental results is improved.

[0086] Furthermore, the step S2, based on flow cytometry, uses the fluorescent antibody composition to mark the UMB cell subpopulation in the target sample and obtains the UMB subpopulation ratio value, including:

[0087] Step S21, processing the target sample into a single cell suspension;

[0088] Step S22, adding the fluorescent antibody composition to the single cell suspension to obtain a mixed sample to be tested;

[0089] Step S23: Detect the mixed sample to be tested based on flow cytometry to obtain the UMB subpopulation ratio value corresponding to the target sample.

[0090] As mentioned above, flow cytometry is a technology used in the fields of biology and medicine. The core of this technology is to analyze each cell in a cell suspension at high speed and classify the cells according to the measured parameters.

[0091] As mentioned above, in step S23, a flow cytometer can be used to perform on-machine detection on the mixed sample to be tested. Moreover, after the raw data are obtained, FlowJo_V10 analysis software can be used for analysis to obtain the UMB subpopulation ratio value.

[0092] Furthermore, the step S21, processing the target sample into a single cell suspension, includes:

[0093] Step S211, performing a lysis treatment on the target sample using a red blood cell lysis solution;

[0094] Step S212, the supernatant is removed by solid-liquid separation, and PBS buffer is added for washing, the supernatant is discarded again, and cell staining buffer is added for resuspending to obtain the single cell suspension.

[0095] In the above steps, it is used to remove red blood cells, because the number of red blood cells is much greater than that of white blood cells and may interfere with subsequent cell analysis. The blood sample is mixed with red blood cell lysis buffer, which ruptures the red blood cells and releases hemoglobin, while the white blood cells remain intact.

[0096] Then, remove the lysed red blood cell debris and hemoglobin. Cell debris and hemoglobin can be separated from white blood cells by centrifugation, and then the supernatant is discarded. This step is used to purify the sample and provide a clear background for subsequent cell labeling and analysis.

[0097] Further in step S212, PBS buffer is added to remove residual red blood cell fragments and hemoglobin and balance the ion concentration inside and outside the cells. Phosphate buffered saline (PBS) is added to the precipitated white blood cells, and the cells are washed by centrifugation and discarding the supernatant. This improves the activity and stability of the cells and reduces non-specific binding.

[0098] Finally, add cell staining buffer for resuspending to evenly disperse the white blood cells for subsequent antibody labeling and flow cytometry detection. After discarding the supernatant of the last wash, add an appropriate amount of cell staining buffer and gently suspend the cells. This will form a uniform single-cell suspension, providing standardized samples for subsequent experiments.

[0099] In the examples of the present application, a fluorescent antibody composition for predicting the activity level of SLE is also provided, comprising: an anti-human CD19 antibody, an anti-human CD27 antibody and an anti-human IgD antibody with a fluorescent label.

[0100] In the examples of the present application, a kit is also provided, comprising: the fluorescent antibody composition as described in the above embodiments, whole blood red blood cell lysate, PBS buffer and cell staining buffer.

[0101] The present invention is further described below by means of specific examples, but it should be understood that these examples are only used for more detailed description and should not be construed as limiting the present invention in any form.

[0102] Embodiment 1:

[0103] In this example, statistical analysis, correlation and ROC curve analysis of the proportion of UMB cell subpopulations were performed.

[0104] 1. Experimental samples:

[0105] In this example, peripheral blood and laboratory-related indicators were collected from 25 healthy controls (HC1-HC25), 20 inactive SLE patients and 20 active SLE patients (SLE1-SLE40) (Tables 1-3); among them, the age and gender distribution of the patients were similar, and active (SLEDAI ≥ 4) and inactive patients (SLEDAI < 4) were distinguished according to the SLEDAI score.

[0106] 2. Test kit:

[0107] Whole blood red blood cell lysis solution (purchased from BD Biosciences), 1×PBS buffer (purchased from BD Biosciences), cell staining buffer (1×PBS buffer containing 1% FBS) and fluorescent antibody combination.

[0108] The fluorescent antibody composition includes:

[0109] (1) Anti-human CD19-FITC antibody (clone number HIB19);

[0110] (2) anti-human-CD27-PerCP-Cy5.5 antibody (clone number M-T271);

[0111] (3) Anti-human IgD-APC-Cy7 antibody (clone number IA6-2).

[0112] 3. Experimental methods:

[0113] (1) Collect 1-2 mL of peripheral blood from healthy controls and SLE patients using purple vacuum blood collection tubes containing EDTA anticoagulant;

[0114] (2) Processing the peripheral blood sample to be tested to form a single cell suspension:

[0115] First, the collected peripheral blood was lysed with red blood cell lysis buffer. 2 mL of red blood cell lysis buffer was added to every 200 μL of peripheral blood, and the blood was lysed at room temperature for 10 minutes. During the lysis period, the blood was gently pipetted and mixed once.

[0116] Then, centrifuge at 350 g for 5 min, discard the supernatant, and add 1× PBS to 2 mL;

[0117] Finally, the cells were centrifuged at 350 g for washing, the supernatant was discarded, and 100 μL of cell staining buffer was added for resuspending to form a single cell suspension.

[0118] (3) Adding monoclonal antibodies labeled with different fluorescence in the fluorescent antibody composition to the single cell suspension obtained in step (2) for staining:

[0119] First, for each sample, prepare two flow cytometry tubes, one as a test tube and one as an isotype control tube, and each tube contains the single cell suspension prepared in step (2).

[0120] Then, 1 μL of monoclonal antibodies labeled with different fluorescence in the corresponding fluorescent antibody composition were added to the test tube and the isotype tube respectively as follows:

[0121] A. Only 1 μL of anti-CD19 antibody was added to the isotype control tube;

[0122] B. Add 1 μL of anti-CD19 antibody, 1 μL of anti-CD27 antibody and 1 μL of anti-IgD antibody to the test tube;

[0123] After gentle mixing, incubate at 4°C in the dark for 15 minutes.

[0124] Finally, 500 μL of cell staining buffer was added and the cells were washed at 350 g for 5 min. After centrifugation, the supernatant was removed and the cells were resuspended with 200 μL of cell staining buffer to obtain a mixed sample to be tested.

[0125] (4) Flow cytometer to test samples:

[0126] For the resuspended cell sample obtained in step (3), i.e., the mixed sample to be tested, a flow cytometer (FACSVerse) is used to analyze and obtain the raw data of the UMB cell subpopulation:

[0127] The obtained raw data were analyzed using FlowJo Software. After the analysis data were summarized, Graph padPrism8.2.1 software was used for data analysis and P value was calculated.

[0128] 3. Data analysis:

[0129] (1) Using the method in Example 1, healthy samples were selected as healthy controls, inactive SLE patients and active SLE patients from the experimental samples in Example 1, and peripheral blood of these samples was selected for flow cytometry. The test results were analyzed using FlowJo_V10 analysis software to obtain the total CD19 +The proportion values ​​of B cells and UMB subsets (Tables 1 to 3).

[0130] Table 1. Relevant information and data of the healthy control group

[0131]

[0132] In the above table, the samples of the healthy control group are numbered HC, and they are samples HC1-HC25.

[0133] Table 2. Relevant information and data of the inactive SLE patient group (1-20)

[0134] serial number B cells UMB gender age C3(g / L) Anti-dsDNA (IU / mL) SLEDAI ≥ 4 SLE1 3.49％ 7.97％ M 35 0.93 95.74 no SLE2 8.85％ 2.59％ F 36 0.806 27.65 no SLE3 4.71％ 10.2％ F 37 0.998 16.83 no SLE4 5.57％ 1.91％ F 33 0.521 59.72 no SLE5 10.2％ 8.06％ F 33 0.844 29.49 no SLE6 4.28％ 3.26％ F 48 1.09 59.22 no SLE7 5.23％ 15.5％ F 33 0.602 6.61 no SLE8 7.38％ 4.64％ F 26 0.964 29.05 no SLE9 6.44％ 8.66％ F 77 1.1 26.76 no SLE10 16.2％ 5.89％ F 25 0.789 84.93 no SLE11 6.85％ 8.93％ F 77 1.1 26.76 no SLE12 17.6％ 6.37％ F 25 0.789 84.93 no SLE13 1.98％ 7.86％ F 41 0.873 18.38 no SLE14 1.71％ 15.3％ F 49 0.784 4.43 no SLE15 9.23％ 21.1％ M 35 0.93 95.74 no SLE16 8.08％ 18.2％ F 20 0.771 30.24 no SLE17 4.40％ 6.84％ F 38 0.998 16.83 no SLE18 9.78％ 18.0％ F 33 0.602 5.16 no SLE19 15.8％ 2.48％ F 42 0.716 53.51 no SLE20 1.71％ 4.82％ F 52 118.62 no

[0135] In the above table, the sample number of the inactive SLE patient group is SLE, and the table contains samples SLE1-SLE20 respectively.

[0136] Table 3. Relevant information and data of the active SLE patient group (21-40)

[0137] serial number B cells UMB gender age C3(g / L) Anti-dsDNA (IU / mL) SLEDAI ≥ 4 SLE21 1.81％ 1.85％ F 31 0.448 1310.88 yes SLE22 4.50％ 0.94％ F 22 0.357 361.63 yes SLE23 1.98％ 5.45％ F 35 0.604 677.53 yes SLE24 3.31％ 4.05％ F 44 0.667 994 yes SLE25 8.12％ 9.56％ F 32 0.9 297.76 yes SLE26 2.08％ 0.77％ F 31 0.448 1310.88 yes SLE27 1.82％ 4.08％ F 38 0.472 465.07 yes SLE28 7.95％ 5.16％ M 18 0.526 530.72 yes SLE29 1.14％ 3.35％ F 38 0.967 245.15 yes SLE30 8.63％ 5.43％ F 32 0.519 98.96 yes SLE31 3.05％ 1.38％ F 33 0.947 215.59 yes SLE32 4.12％ 6.83％ M 37 0.641 353.55 yes SLE33 8.92％ 5.44％ F 33 0.947 215.59 yes SLE34 3.58％ 4.38％ F 45 0.741 78.78 yes SLE35 2.96％ 6.57％ F 38 0.518 556.66 yes SLE36 5.83％ 1.11％ F 22 0.357 361.63 yes SLE37 6.02％ 3.92％ F 29 0.483 321.49 yes SLE38 1.34％ 1.68％ F 40 0.43 128.42 yes SLE39 3.81％ 3.78％ F 46 0.378 916.92 yes SLE40 10.5％ 3.41％ F 25 0.568 472.49 yes

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

[0139] refer to Figure 2 is the flow cytometry result, where Figure 2 A shows the total CD19 in peripheral blood of healthy control group, inactive SLE patients and active SLE patients + Representative flow cytometry results of B cell ratios, Figure 2 B shows the peripheral blood of healthy control group, inactive SLE patients and active SLE patients Figure 2 ATotalCD19 + Representative flow cytometry results of UMB subset ratios of B cells.

[0140] (2) Statistical analysis of the changes in the proportion of UMB cell subsets in the peripheral blood of healthy control group, total SLE patients, inactive SLE patients and active SLE patients: Descriptive statistics analysis was performed on the proportion of UMB cell subsets in each group in Tables 1 to 3 using Graph pad Prism8.2.1 software. It was found that the median proportion of UMB cell subsets in the healthy control group, total SLE patients, inactive SLE patients and active SLE patients were 7.150%, 5.295%, 7.915% and 3.985%, respectively.

[0141] (3)Reference Figure 3Graph pad Prism 8.2.1 software was used to perform Mann-Whitney test and one-way ANOVA analysis on the proportion of UMB cell subsets in each group in Tables 1 to 3. Figure 3 A shows that the proportion of UMB in peripheral blood of SLE patients was significantly lower than that of healthy controls (p=0.005). Figure 3 B shows that the proportion of UMB in the peripheral blood of active SLE patients was significantly lower than that of healthy controls (p=0.0009) and inactive SLE patients (p=0.0008).

[0142] Therefore, it can be concluded that when the proportion of UMB subpopulations in the peripheral blood of SLE patients is no more than 5.295%, it is more likely that they are in the active stage of SLE, and when the proportion is greater than 5.295%, it is more likely that they are in the inactive stage of SLE.

[0143] (4) Correlation between the proportion of UMB cells and disease activity and diagnostic analysis:

[0144] For the above samples, active patients (SLEDAI ≥ 4) and inactive patients (SLEDAI < 4) were distinguished according to the SLEDAI score. Complement C3 and anti-dsDNA antibodies are key indicators of SLE disease activity. The decrease of C3 and the increase of anti-dsDNA antibodies are correlated with the disease activity of SLE.

[0145] like Figure 4 As shown, Graph pad Prism 8.2.1 software was used to perform Pearson correlation analysis on the UMB cell subset ratios and the corresponding C3 levels or anti-dsDNA antibody concentrations in Tables 2 and 3. It was found that the UMB cell ratio was significantly positively correlated with C3 and significantly negatively correlated with anti-dsDNA antibodies.

[0146] Figure 5 Graph pad Prism 8.2.1 software was used to perform ROC analysis on the proportion of UMB cell subsets in each group in Tables 1 to 3. 4A is the ROC curve of healthy controls and inactive SLE patients (p = 0.9818), and 4B is the ROC curve of healthy controls and active SLE patients (p < 0.0001).

[0147] Embodiment 2:

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

[0149] 1. Experimental samples:

[0150] (1) Patients with known inactive SLE: Sample 1;

[0151] (2) Patients with known active SLE: Sample 2;

[0152] (3) Unknown samples: Sample 3 and Sample 4.

[0153] 2. Experimental methods:

[0154] Same as in Example 1.

[0155] 3. Experimental results and analysis:

[0156] Table 4. Prediction data and results of UMB cell subset ratios of samples 1 to 4

[0157] sample Value to be evaluated Preset evaluation threshold Compare Prediction results Sample 1 7.312％ 5.295％ Value to be evaluated > preset evaluation threshold Inactive phase of SLE Sample 2 2.778％ 5.295％ The value to be evaluated is less than the preset evaluation threshold SLE active period Sample 3 8.339％ 5.295％ Value to be evaluated > preset evaluation threshold Inactive phase of SLE Sample 4 4.318％ 5.295％ The value to be evaluated is less than the preset evaluation threshold SLE active period

[0158] In this embodiment, the experimental method is the same as that in embodiment 1, including using EDTA anticoagulation to collect blood, preparing single cell suspension, fluorescent antibody staining, flow cytometer detection and data analysis. Then, data analysis is performed for two known samples and two position samples respectively.

[0159] Sample 1: Value to be evaluated: 7.312%, higher than the preset evaluation threshold of 5.295%. Prediction result: The prediction is that SLE is inactive, which is consistent with the known state of the sample in the inactive stage of SLE, verifying the accuracy of the detection method.

[0160] Sample 2: Value to be evaluated: 2.778%, which is lower than the preset evaluation threshold of 5.295%. Prediction result: The prediction is SLE active stage, which is consistent with the known status of SLE active stage patients, which once again verifies the effectiveness of the detection method.

[0161] Sample 3: Value to be evaluated: 8.339%, higher than the preset evaluation threshold of 5.295%. Prediction result: Predicted to be in the inactive stage of SLE. For unknown samples, the results suggest that the sample may not be in the active stage of SLE.

[0162] Sample 4: Value to be evaluated: 4.318%, which is lower than the preset evaluation threshold of 5.295%. Prediction result: Predicted to be in the active stage of SLE. For unknown samples, the results suggest that the sample may be in the active stage of SLE.

[0163] In summary, by comparing the predicted results of samples 1 and 2 with known status with the actual status, the prediction accuracy of this method can be verified. For samples 3 and 4 with unknown status, this method can provide predictions about SLE activity, 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, it can be further confirmed that 5.295% is the threshold of the proportion of UMB cell subpopulations in distinguishing the active and inactive phases of SLE. Example 2 repeats the experimental process of Example 1 to demonstrate the repeatability of this method in different samples. This method can be used as a supplement to existing SLE disease activity assessment tools to provide more objective laboratory indicators.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, 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 invention.

Claims

1. Use of an antibody composition in preparing a kit for predicting the activity level of SLE, characterized in that: The prediction of the SLE activity level is achieved by using the antibodies in the antibody composition to label UMB cell subpopulations to obtain subpopulation ratio values, and then obtaining a prediction result based on the subpopulation ratio values.

2. The use according to claim 1, characterized in that Methods for predicting SLE activity level include: Collect peripheral blood from the person to be tested as a target sample; Based on flow cytometry, the UMB cell subpopulation in the target sample is labeled with a fluorescent antibody composition, and a UMB subpopulation ratio value is obtained; The prediction result is obtained according to the UMB subgroup ratio value.

3. The use according to claim 2, characterized in that The fluorescent antibody composition comprises: Fluorescently labeled anti-human CD19 antibody, anti-human CD27 antibody, and anti-human IgD antibody.

4. The use according to claim 2, characterized in that Obtaining the prediction result according to the UMB subgroup ratio value includes: Obtaining the median of the UMB subgroup ratio value as the value to be evaluated; The prediction result is obtained according to the value to be evaluated and a preset evaluation threshold.

5. The use according to claim 4, characterized in that The preset evaluation threshold is 5.295%; The step of obtaining the prediction result according to the value to be evaluated and the preset evaluation threshold value includes: Comparing the value to be evaluated with the preset evaluation threshold; If the value to be evaluated is not greater than 5.295%, the prediction result is that the person to be tested corresponding to the target sample is in the SLE active period; If the value to be evaluated is greater than 5.295%, the prediction result is that the person to be tested corresponding to the target sample is in the SLE inactive period.

6. The use according to claim 2, characterized in that The method of collecting peripheral blood of a person to be tested as a target sample includes: The peripheral blood of the person to be tested is collected using a blood collection container containing EDTA anticoagulant to obtain the target sample.

7. The use according to claim 2, characterized in that The method of labeling the UMB cell subpopulation in the target sample by using the fluorescent antibody composition based on flow cytometry and obtaining the UMB subpopulation ratio value comprises: Processing the target sample into a single cell suspension; adding the fluorescent antibody composition to the single cell suspension to obtain a mixed sample to be tested; Based on flow cytometry, the mixed sample to be tested is detected to obtain the UMB subpopulation ratio value corresponding to the target sample.

8. The use according to claim 7, characterized in that The step of processing the target sample into a single cell suspension comprises: The target sample is subjected to a lysis treatment using a red blood cell lysis solution; The supernatant was removed by centrifugation, and PBS buffer was added for washing. After the supernatant was discarded again, a cell staining buffer was added for re-suspending to obtain the single cell suspension.

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

10. A kit, characterized in that: include: The fluorescent antibody composition as claimed in claim 9, whole blood red blood cell lysate, PBS buffer and cell staining buffer.

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