Method for detecting aortic dissection based on peripheral blood brd4 detection by flow cytometry and application thereof

Abstract

The application discloses a method for detecting aortic dissection based on peripheral blood BRD4 by using flow cytometry and application thereof. The application belongs to the technical field of biology and particularly relates to a method for detecting aortic dissection based on peripheral blood BRD4 by using flow cytometry and application thereof. The method for detecting the content or expression level of bromodomain-containing protein 4 in a to-be-detected sample established by the application comprises the following steps: 1) processing a to-be-detected sample to obtain single nucleus cells; 2) determining a fluorescein-coupled antibody composition of a detection index according to a flow cytometry color matching scheme; 3) mixing the single nucleus cells in step 1) and the fluorescein-coupled antibody in step 2) uniformly, and performing staining by incubation in the dark; 4) performing sample testing on a spectrum flow cytometer; and 5) performing data result analysis. The detection index in step 2) is CD45, CD11B, CD66B, CD14, CC16 and BRD4.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of biotechnology, and particularly relates to a method for detecting aortic dissection based on peripheral blood BRD4 by flow cytometry and application thereof. BACKGROUND

[0002] Aortic dissection has a high mortality rate and poor prognosis. If not treated in time, the mortality rate within 48 hours is as high as 50%. The pathological features in the progression of aortic dissection include excessive activation of extracellular matrix (ECM) degradation and progressive phenotypic transformation of vascular smooth muscle cells (VSMCs). Damaged aortic cells release a large number of molecules to activate inflammatory cells, and inflammatory cells secrete ECM-degrading enzymes (such as Matrix Metalloproteinase, MMP) and trigger further aortic injury. A prospective analysis shows that there are 15 cases of aortic dissection risk per 100,000 patients, and in the population aged 65-75 years, there are 35 cases per 100,000 people per year. If not treated by surgery in time, the mortality rate of aortic dissection rupture is more than 80%. Aortic dissection is acute, and once misdiagnosed and given the wrong treatment plan, the consequences are often disastrous. Therefore, it is particularly important to find a marker that can sensitively and specifically diagnose aortic dissection or predict the occurrence of aortic dissection through simple and rapid blood tests.

[0003] With the completion of the human genome sequencing project and the development of high-throughput sequencing technology, medical researchers have a deeper understanding of the human genome, and the understanding of disease-related genetic variations, related gene functions and regulatory networks has also gradually deepened. High-throughput sequencing is widely used. In recent years, more and more studies have found genes related to aortic dissection through high-throughput sequencing, but most of the studies are based on biomarkers in aortic tissue. Since obtaining aortic tissue is traumatic to the human body, it is difficult to apply to clinical practice, so it may not be appropriate to use differentially expressed RNA or protein in aortic tissue as a biomarker for aortic dissection.

[0004] Aortic dissection has a high rate of disability and mortality and is difficult to detect early. Although aortic enhanced CT is the gold standard for diagnosing aortic dissection, it is expensive and time-consuming for patients, and many primary hospitals do not have the conditions to complete this examination. Aortic tissue is difficult to obtain, and it is difficult to use differentially expressed proteins as biomarkers. Therefore, differentially expressed proteins screened from peripheral blood can be more conveniently used as biomarkers for aortic dissection and applied to clinical practice.

[0005] Epigenetic readers recognize covalent epigenetic modifications on nucleosomes, which promote chromatin remodeling, transcription initiation and elongation. One of them, the bromodomain motif, which interacts with acetylated lysine side chains, is part of many chromatin-associated proteins. In addition to the bromodomain motif, bromodomain-containing proteins (BRD) 2, 3 and 4 and the bromodomain testis-specific protein (BRDT) contain an extra-terminal molecular interaction site and are therefore classified as bromodomain and extra-terminal (BET) proteins. In inflammation-related diseases, BRD4 is often up-regulated in immune and non-immune cells, can regulate the inflammatory program of macrophages, is associated with macrophage infiltration in the tumor microenvironment, and appears to dynamically increase or be suppressed at the mRNA / protein level under various cell stimulation conditions: BRD4 expression is positively correlated with the level of macrophage infiltration in glioblastoma; in the IL-4-induced M2 macrophage polarization model, the mRNA and protein expression levels of BRD4 are increased; in experimental renal injury and cultured renal tubular epithelial cells under inflammatory conditions, the BRD4 inhibitor JQ1 can reduce the expression of many pro-inflammatory mediators. Drugs targeting the BET pathway (such as BET inhibitors) have been extensively studied, and BRD4 is expected to serve as a companion indicator for drug response and dose optimization for dynamic assessment of inflammatory activity and treatment response. These studies suggest that BRD4 has both mechanism-related and detectable properties, and has the potential to become an excellent biomarker for disease identification, risk stratification, and treatment response monitoring. SUMMARY

[0006] The main problem to be solved by the present application is how to quickly and efficiently detect the content or expression level of bromodomain-containing protein 4 so as to accurately identify aortic dissection-related diseases.

[0007] To solve the above problems, the present application provides a method for detecting the content or expression level of bromodomain-containing protein 4 in a test sample.

[0008] The method for detecting the content or expression level of bromodomain-containing protein 4 in a test sample provided by the present application comprises the following steps:

[0009] 1) processing the test sample to obtain single nucleated cells;

[0010] 2) determining the composition of fluorescein-conjugated antibodies for detecting indicators according to the color matching scheme of flow cytometry;

[0011] 3) mixing the single nucleated cells of step 1) and the fluorescein-conjugated antibodies of step 2), and incubating for staining in the dark;

[0012] 4) testing on a spectral flow cytometer;

[0013] 5) analyzing the data results;

[0014] The detection index in step 2) is CD45, CD11B, CD66B, CD14, CC16 and BRD4.

[0015] The color matching principle in step 2) is briefly described as follows: in the selection of fluorescein, all fluoresceins in the same experiment have a unique spectrum; high expression antigen is matched with weak fluorescein, and low expression antigen is matched with strong fluorescein.

[0016] In the above method, the fluorescein-conjugated antibody in step 2) is: Alexa Fluor 700 anti-human CD45 Antibody, excitation light 696nm, emission light 719nm; Brilliant Violet 605 anti-human CD11b Antibody, excitation light 406nm, emission light 603nm; PerCP / Cyanine5.5 anti-human CD66b Antibody, excitation light 482nm, emission light 690nm; PE anti-human CD16 Antibody, excitation light 565nm, emission light 576nm; Brilliant Violet 421 anti-human CD14 Antibody, excitation light 406nm, emission light 423nm; Alexa Fluor 647 anti-human BRD4 Antibody, excitation light 652nm, emission light 668nm.

[0017] In a specific embodiment, the fluorescein of CD45 in step 2) is Alexa Fluor 700, the fluorescein of CD11B is Brilliant Violet 605, the fluorescein of CD66B is Percpcy5.5, the fluorescein of CD16 is PE, the fluorescein of CD14 is Brilliant Violet 421, and the fluorescein of BRD4 is Alexa Flura 647.

[0018] The amino acid sequence of BRD4 is sequence 1.

[0019] In the above method, the mononuclear cells can be obtained by processing blood samples of healthy volunteers and aortic dissection patients, and in a specific embodiment, the processing method comprises: taking 200μL of peripheral blood, adding 1mL of 1×red blood cell lysis solution into the tube, vortexing and mixing, avoiding light, lysing for 10min, centrifuging at 1500rpm at room temperature for 5min, discarding the supernatant, resuspending the cells with 1mL of PBS / Stain buffer, centrifuging, discarding the supernatant, and obtaining a mononuclear cell suspension.

[0020] In the above method, the staining in step 3) comprises surface staining and intracellular marker staining.

[0021] The method of surface staining comprises adding an appropriate amount of surface marker flow antibody (1:100), mixing, incubating at room temperature in the dark for 25-30 minutes. The surface marker flow antibody can be CD45, CD11B, CD66B, CD14, CD16.

[0022] The method of intracellular marker staining comprises adding 500 μL of 1x Fix / Perm to the cell suspension for fixation and permeation, treating in the dark for 35 min, adding an equal volume of 1x Perm / Wash for buffer stop permeation, centrifuging at 1500 rpm at room temperature for 5 min, and discarding the supernatant. Add intracellular flow antibody (1:100) to 100 μL of 1x Perm / Wash, incubate in the dark for 40 min, resuspend the cells with 500 μL of 1x Perm / Wash, and centrifuge at 1500 rpm at room temperature for 5 min. The intracellular flow antibody can be BRD4.

[0023] In the above method, after the light-protected incubation step in step 3), the method further comprises a step of washing, fixing and permeating the cells.

[0024] In the above method, the data result analysis in step 5) is gate analysis and / or dimensionality reduction analysis.

[0025] The gate analysis method can be: using FlowJo software to perform gate analysis on the data, and displaying the expression of activated molecules in each subpopulation.

[0026] The dimensionality reduction analysis method can be: checking whether the instrument state is stable when collecting data by Time / FSC H, removing adhesion by FSC A / FSC H, distinguishing lymphocytes from mononuclear cells by CD45 / SSC-A, and distinguishing neutrophils by CD11B / CD66B. Differentiate different differentiation stages of mononuclear cells by the expression of CD14 and CD16: classical mononuclear cells (CD14 ++ CD16 - ), intermediate mononuclear cells (CD14 + CD16 + ), and non-classical mononuclear cells (CD14 + CD16 ++ ).

[0027] The use of the fluorescein-conjugated antibody composition in the preparation of a kit product for detecting the content of BRD4 also belongs to the scope of protection of the present application.

[0028] The present application also provides the use of the fluorescein conjugated antibody composition as described above in the manufacture of a kit for detecting the expression level of BRD4 in a sample.

[0029] The present application also provides the use of the fluorescein conjugated antibody composition as described above in the manufacture of a reagent for diagnosing aortic dissection disease in a subject, wherein the CD45 antibody specifically binds to the biomarker leukocytes, the CD11B, CD66B antibody specifically binds to the biomarker neutrophils, wherein the CD14, CD16 antibody specifically binds to the biomarker circulating monocytes;

[0030] wherein the BRD4 antibody specifically detects whether the number of high expression cells of the biomarker BRD4 in a body sample from a subject is elevated relative to the number of high expression cells in a normal reference sample, wherein the detection of elevated expression level of the biomarker BRD4 specifically identifies a sample indicative of high aortic dissection disease.

[0031] The body sample of the subject can be leukocytes (CD45 + ), neutrophils (CD45 + CD11b + CD66b + ), intermediate monocytes (CD14 + CD16 + ) of the subject.

[0032] In the present application, the expression of the marker in healthy and diseased populations has significant differential expression, which is used for the diagnosis of thoracic aortic dissection, and the thoracic aortic dissection can be accurately diagnosed.

[0033] The combined marker described in the present application is used for the diagnosis of thoracic aortic dissection, and the diagnosis result is accurate and reliable, and the diagnosis effect is more accurate compared with other combined markers. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 Flow cytometry gating strategy for determining the expression amount of BRD4 from human peripheral blood cells.

[0035] Figure 2 Representative flow cytometry images of CD45+BRD4+ expression from healthy controls and aortic dissection patients.

[0036] Figure 3 Differentially expressed cells leukocytes (CD45 + ), neutrophils (CD45 + CD11b + CD66b +Monocytes (CD14 + CD14 + CD16 + BRD4 expression levels and percentage quantification.

[0037] Figure 4 ROC curve of peripheral blood BRD4+ cells combined to distinguish healthy controls and aortic dissection patients. DETAILED DESCRIPTION

[0038] The application will be further described in conjunction with the specific embodiments. The examples given are only to illustrate the application, and are not intended to limit the scope of the application. The examples provided below can serve as a guide for further improvement by those of ordinary skill in the art, and do not in any way constitute a limitation on the application.

[0039] The experimental methods in the following examples are all routine methods, unless otherwise specified, which are carried out according to the techniques or conditions described in the literature in the art or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can be obtained commercially.

[0040] The quantitative tests in the following examples, unless otherwise specified, were set up in triplicate, and the results were averaged.

[0041] The following examples use SPSS 11.5 statistical software to process the data, and the experimental results are expressed as mean ± standard deviation. One-way ANOVA test was used, P<0.05 (*) indicates a significant difference, P<0.01 (**) indicates a highly significant difference, and P<0.001 (*** ) indicates a highly significant difference.

[0042] Example 1, establishment of a method for detecting the content of peripheral blood BRD4 by flow cytometry

[0043] This study was conducted at the Anzhen Hospital of Capital Medical University (November 2023 to June 2024). All patients signed an informed consent form. This study was approved by the Ethics Committee of the Anzhen Hospital of Capital Medical University.

[0044] Study subjects

[0045] Inclusion criteria for aortic dissection: ① Han population aged 18-85 years; ② Patients with aortic dissection diagnosed by aortic whole-enhancement scan and confirmed intraoperatively.

[0046] Exclusion criteria: ① Patients with cardiovascular diseases caused by genetic diseases or genetic cardiovascular diseases such as Marfan syndrome, Ehlers-Danlos syndrome, familial thoracic aortic aneurysm, and laceration caused by trauma; ② Patients with non-aortic dissection proved by intraoperative; ③ Patients with malignant tumors; ④ Patients with other conditions considered by the investigator to be unsuitable for inclusion in the study.

[0047] Inclusion criteria: 1:1 matching of controls with AD cases by age (± 3 years), gender, and individual.

[0048] Exclusion criteria: Patients with severe heart, brain, lung, kidney diseases and tumors.

[0049] Finally, 30 aortic dissection patients and 30 healthy volunteers were collected and examined by venous blood samples. Peripheral blood was collected using EDTA anticoagulant tubes, stored at room temperature, and processed on the day of blood collection.

[0050] Test samples: blood of aortic dissection patients and healthy volunteers.

[0051] 1. Blood sample processing

[0052] The blood sample processing method is as follows:

[0053] 1) Take 200 μL of peripheral blood from aortic dissection patients and healthy volunteers, add 1 mL of 1x red blood cell lysis solution (BD Pharm Lyse, 555899) to the tube, vortex mix, avoid light lysis for 10 min, observe the solution whether clear and transparent, transparent indicates lysis is complete, 1500 rpm room temperature centrifugation for 5 min, discard the supernatant, resuspend the cells with 1 mL PBS / Stain buffer, centrifuge, discard the supernatant, and obtain a single nuclear cell suspension.

[0054] 2) Add appropriate amount of marker labeled flow cytometry antibody (1:100), mix well, incubate at room temperature for 25-30 minutes.

[0055] 3) Add 1 mL of stain buffer to wash the single nuclear cell suspension at 1500 rpm and room temperature for 5 min, discard the supernatant.

[0056] 4) Add 500 μL of 1x Fix / Perm (BD, 562574) to the cell suspension for fixation and permeabilization for 35-40 min, then add an equal volume of 1x Perm / Wash (BD, 562574) to stop permeabilization, centrifuge at 1500 rpm and room temperature for 5 min, discard the supernatant.

[0057] 5) Add intracellular flow antibody (1:100) to 100 μL 1x Perm / Wash, incubate for 40 min in the dark, then resuspend the cells in 500 μL 1x Perm / Wash, centrifuge at 1500 rpm for 5 min at room temperature.

[0058] 6) Resuspend the cells in 400 μL stain buffer and analyze immediately, or fix in 400 μL 4% formaldehyde, store at 2-8°C in the dark, and analyze the fixed cells within 24 hours.

[0059] Finally, single cells (Peripheral Blood Mononuclear Cells, PBMC) are obtained for surface and intracellular staining to obtain test samples.

[0060] 2. Fluorescein-conjugated antibodies for detecting the following indicators according to the flow cytometry color matching scheme

[0061] The detection indicators are selected according to the immune characteristics of patients with aortic dissection, including CD45, CD11B, CD66B, CD14, CC16, and BRD4.

[0062] The color matching scheme is based on the color matching principle to allocate fluorescein to the detection indicators. The fluorescein of CD45 is Alexa Fluor 700 (invitrogen, MHCD4529, excitation light 696 nm, emission light 719 nm), the fluorescein of CD11B is Brilliant Violet 605 (eBioscience, 406-0118-42, excitation light 406 nm, emission light 603 nm), the fluorescein of CD66B is Percpcy5.5 (biolegend, 305107, excitation light 482 nm, emission light 690 nm), the fluorescein of CD16 is PE (eBioscience, 12-0167-42, excitation light 565 nm, emission light 576 nm), the fluorescein of CD14 is Brilliant Violet 421 (eBioscience, 404-0149-42, excitation light 406 nm, emission light 423 nm), and the fluorescein of BRD4 is Alexa Flura 647 (abcam, AB197608, excitation light 652 nm, emission light 668 nm).

[0063] 3. Sample testing on a spectral flow cytometer

[0064] The test sample obtained in step 1 and the prepared single-dye reference sample (5 tubes of human peripheral blood samples, each sample has the same number of cells and method as the formal test, and is incubated with CD45, CD11B, CD66B, CD14, CD16 and BRD4 antibodies) and negative sample (5 tubes of human peripheral blood samples, each sample has the same number of cells and method as the formal test, and is not incubated with antibodies) are tested on a spectral flow cytometer, and the data after analysis is obtained according to the test results.

[0065] The specific steps of the test are as follows:

[0066] 1) The above-mentioned negative sample is loaded, and the voltages of FSC and SSC of the high-end flow cytometry system (BD: LSR Fortessa) are adjusted to display all target cell populations. After the setting is completed, it is checked whether the fluorescence intensity of the test sample exceeds the maximum detection range under this setting;

[0067] 2) The above-mentioned single-dye reference sample is loaded in sequence, and whether there is positive expression and whether the spectrum appearing is correct is observed during the collection of information;

[0068] 3) After the information collection of all the above-mentioned single-dye reference samples is completed, the position of the gate is adjusted in the analysis window of the high-end flow cytometry system, the population to be analyzed is selected, and the negative gate and positive gate are moved to the appropriate position in the histogram. It is checked to ensure that the spectrum of the positive area is correct and the background of the negative area is clean;

[0069] 4) Roughly draw a circle around the gate, then load the test sample, save the analysis data after the test is completed.

[0070] 4, data result analysis

[0071] The data after analysis obtained in step 3 is analyzed by using FlowJo software to circle the gate, and the expression of the activated molecules in each subpopulation is displayed. The circle gate method is as shown in Figure 1 , and the analysis results of the immune cell activation state of the aortic dissection patient are obtained.

[0072] The method for dimensionality reduction analysis of the data after analysis is as follows:

[0073] The instrument state is stable when collecting data by Time / FSC H, the adhesion is removed by FSC A / FSC H, and the lymphocytes and mononuclear cells are distinguished by CD45 / SSC-A Figure 1 (middle of the first row), and the neutrophils are distinguished by CD11B / CD66B Figure 1 (middle of the second row).

[0074] Differentiation stages of monocytes were distinguished by the expression of CD14 and CD16: classical monocytes (CD14 ++ CD16 - ), intermediate monocytes (CD14 + CD16 + ), and non-classical monocytes (CD14 + CD16 ++ ) Figure 1 The second left panel of the second row.

[0075] The number of cells with high expression of BRD4 in different types of cells was analyzed (the right panel of the first row, the right panel of the second row, and the third row), and the results are shown in Figure 1 Figure 1

[0076] The results are shown in Figure 1 : the left panel and the middle panel of the first row are the CD45 + leukocyte gate method, the right panel of the first row is the method for determining the population of cells with high expression of BRD4 in CD45 + leukocytes, the middle panel of the second row is the CD11B + , CD66B + neutrophil gate method, the right panel of the second row is the method for determining the population of cells with high expression of BRD4 in CD45 + , CD11B + , CD66B + neutrophils, and the left panel of the second row is the CD45 + , CD14 + , CD16 + monocyte gate method. It can also be seen that the three groups of cells are CD45 + CD14 ++ CD16 - classical, CD45 + CD14 + CD16 ++ non-classical, and CD45 + CD14 + CD16 + intermediate. The three panels of the third row are the methods for determining the population of cells with high expression of BRD4 in classical monocytes, intermediate monocytes, and non-classical monocytes, respectively. In the pictures, the cells will appear as blue dots, and in places where the cell density is relatively high, they will appear as a gradual change from green to yellow to red to show the cell density. The figure only shows the gate method.

[0077] Example 2: Application of the method for detecting the content of BRD4 in peripheral blood by flow cytometry in the identification of aortic dissection

[0078] ​​Peripheral blood of healthy volunteers was selected, age and gender matched with the patients with dissection, to exclude errors caused by gender and age difference. As shown in Table 1, in addition to age and gender matching, the basic indicators of healthy people and aortic dissection patients were normal, which excluded experimental errors caused by samples.

[0079]

[0080] Based on the flow cytometry procedure established in Example 1 of the present application, peripheral blood of 30 healthy volunteers and 30 aortic dissection (AD) patients listed in Table 1 was detected.

[0081] The results showed that, compared with healthy controls, the proportion of BRD4 high expression cells in leukocytes (CD45 + ), neutrophils (CD45 + CD11b + CD66b + ), and intermediate monocytes (CD45 + CD14 + CD16 + ) of AD patients were significantly increased (P<0.05). Figure 2 and Figure 3 ).

[0082] On the basis of the same subject cohort, the proportion of BRD4 high expression cells in neutrophils (CD45 + CD11b + CD66b + ), classical monocytes (CD45 + CD14 ++ CD16 - ), intermediate monocytes (CD45 + CD14 + CD16 + ), and non-classical monocytes (CD45 + CD14 + CD16 ++ ) were extracted, respectively, to construct a joint discriminant model for identifying AD.

[0083] A multivariate logistic model was used to establish a joint discriminant, and the linear predictor (joint score) was denoted as Score = Σ(β_k× cell(BRD4+)_k) + b. Wherein, β_k is the regression coefficient of the "BRD4 high expression proportion" of the kth cell subpopulation, cell(BRD4+)_k is the proportion of BRD4 high expression cells in the corresponding subpopulation, and b is a constant term. This Score reflects the weighted superposition of the "BRD4 high expression" information of different subpopulations: the coefficient β_k>0 indicates that the increase of the proportion of this subpopulation makes Score increase (favorable to AD determination), and β_k<0 is the opposite.

[0084] In the present embodiment, the specific calculation formula of the joint score is: Score = 0.06 x neutrophil (CD45 + CD11b + CD66b + BRD4 + ) - 2.93 x classic monocyte (CD45 + CD14 ++ CD16 - BRD4 + ) + 7.50 x intermediate monocyte (CD45 + CD14 + CD16 + BRD4 + ) + 0.10 x non-classic monocyte (CD45 + CD14 + CD16 ++ BRD4 + ) - 1.54.

[0085] Wherein: neutrophil (CD45 + CD11b + CD66b + BRD4+) represents the proportion of cells positive for BRD4 within the neutrophil subpopulation (gated as CD45 + CD11b + CD66b + );

[0086] Classic monocyte (CD45 + CD14 ++ CD16 - BRD4 + ) represents the proportion of BRD4 positive cells within the classic monocyte subpopulation (gated as CD14 high expression / CD16 positive);

[0087] Intermediate monocyte (CD45 + CD14 + CD16 + BRD4 + ) represents the proportion of BRD4 positive cells within the intermediate monocyte subpopulation (CD14 and CD16 positive);

[0088] Non-classic monocyte (CD45 + CD14 + CD16 ++ BRD4 + ) represents the proportion of BRD4 positive cells within the non-classic monocyte subpopulation (CD16 high expression).

[0089] The cutoff value is the optimal threshold value obtained by calculating the Youden index (Youden index = sensitivity + specificity - 1).

[0090] If the joint cutoff value of the model is greater than or equal to 0.5932 (with a sensitivity of 86.67% and a specificity of 96.43%), the diagnosis is AD, and the joint detection has good discriminant efficiency. The area under the receiver operating characteristic curve (AUC) is 0.94, and the 95% confidence interval is 0.87-1.00, indicating that the joint detection can accurately distinguish AD patients from healthy individuals (P < 0.001). Figure 4

[0091] The above has been described in detail. For those skilled in the art, without departing from the purpose and scope of the present application, and without unnecessary experiments, the present application can be implemented in a wider range under the same parameters, concentrations and conditions. Although the present application gives a special example, it should be understood that further improvements can be made to the present application. In summary, according to the principle of the present application, this application intends to include any change, use or improvement of the present application, including changes made by conventional techniques known in the art, which deviates from the range disclosed in the present application.​

Claims

1. The use of a fluorescein-conjugated antibody composition in the preparation of a reagent for diagnosing aortic dissection in subjects, wherein the fluorescein-conjugated antibody composition comprises CD45 antibody, CD11B antibody, CD66B antibody, CD14 antibody, CD16 antibody and bromine domain protein 4 (BRD4) antibody, wherein the CD45 antibody specifically binds to the biomarker leukocytes, the CD11B antibody and CD66B antibody specifically bind to the biomarker neutrophils, and the CD14 antibody and CD16 antibody specifically bind to the biomarker circulating monocytes; The BRD4 antibody specifically detects whether the number of cells highly expressing the biomarker BRD4 in a body sample from a subject is increased relative to the number of cells highly expressing BRD4 in a normal reference sample, and the detection of elevated expression levels of the biomarker BRD4 specifically identifies samples indicating severe aortic dissection disease.

2. The application according to claim 1, characterized in that: A method for detecting the content or expression level of BRD4 in a sample includes the following steps: 1) Process the sample to be tested to obtain mononuclear cells; 2) Luciferin-conjugated antibody compositions for determining detection indicators based on flow cytometry colorimetric schemes; 3) Mix the mononuclear cells described in step 1) and the fluorescein-conjugated antibody described in step 2), and incubate in the dark for staining; 4) Sample loading and testing using a flow cytometer; 5) Data results analysis; The detection indicators mentioned in step 2) are CD45, CD11B, CD66B, CD14, CD16 and BRD4.

3. The application according to claim 2, characterized in that: The fluorescein-conjugated antibodies mentioned in step 2) are Alexa Fluor 700 anti-human CD45 Antibody, Brilliant Violet 605 anti-human CD11b Antibody, PerCP / Cyanine5.5 anti-human CD66b Antibody, PE anti-human CD16 Antibody, Brilliant Violet 421 anti-human CD14 Antibody, and Alexa Fluor 647 anti-human BRD4 Antibody.

4. The application according to claim 2, characterized in that, In step 2), the fluorescein for CD45 is Alexa Fluor 700, the fluorescein for CD11B is Brilliant Violet 605, the fluorescein for CD66B is Percpcy 5.5, the fluorescein for CD16 is PE, the fluorescein for CD14 is Brilliant Violet 421, and the fluorescein for BRD4 is Alexa Flura 647.

5. The application according to claim 2, characterized in that, Step 3) describes staining that includes surface staining and intracellular marker staining.

6. The application according to claim 2, characterized in that, Step 3) includes a light-protected incubation step followed by a cell washing, fixation, and permeabilization step.

7. The application according to claim 2, characterized in that, Step 5) describes the data result analysis as gate analysis and / or dimensionality reduction analysis.

8. The application of a fluorescein-conjugated antibody composition in the preparation of a kit for diagnosing aortic dissection, wherein the fluorescein-conjugated antibody composition comprises CD45 antibody, CD11B antibody, CD66B antibody, CD14 antibody, CD16 antibody and bromine domain protein 4 (BRD4) antibody, wherein the CD45 antibody specifically binds to the biomarker leukocytes, the CD11B antibody and CD66B antibody specifically bind to the biomarker neutrophils, and the CD14 antibody and CD16 antibody specifically bind to the biomarker circulating monocytes; The BRD4 antibody specifically detects whether the number of cells highly expressing the biomarker BRD4 in a body sample from a subject is increased relative to the number of cells highly expressing BRD4 in a normal reference sample, and the detection of elevated expression levels of the biomarker BRD4 specifically identifies samples indicating severe aortic dissection disease.

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