Use of actin 3 in the preparation of a product for diagnosing aortic dissection

Abstract

The application discloses application of actin 3 in preparation of a product for diagnosing aortic dissection, and belongs to the field of medicine. The application obtains the aortic dissection differential expression gene actin 3 through spatial transcriptome screening, and the application verifies the actin 3 through ELISA, proves that the actin 3 can participate in aortic dissection pathogenesis, can be used as an early diagnosis biomarker and a new treatment target of acute aortic dissection, and provides a new direction for aortic dissection clinical early diagnosis and long-term prognosis evaluation. It can be seen that the application has great clinical value and practical significance for early diagnosis of aortic dissection through screening of serum markers for early diagnosis of aortic dissection patients, early diagnosis of aortic dissection, long-term prognosis and improvement of life quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of medicine, in particular to the application of actin 3 (PLS3) in the preparation of a product for diagnosing aortic dissection. BACKGROUND

[0002] Aortic dissection is a critical cardiovascular disease that has a high mortality rate and poses a serious threat to human life and health. International Aortic Dissection Registry (IRAD) data shows that the annual incidence of aortic dissection in Europe and the United States is 3-5 / 100,000. Prospective studies have also shown that the incidence of aortic dissection can be 15 / 100,000 per year, and even as high as 35 / 100,000 per year among 65-75 year olds. The 2019 China Cardiovascular Health and Disease Report shows that the annual incidence of aortic dissection in China is 2.8 / 100,000, and with the increasing incidence of hypertension, the incidence of aortic dissection in China is on the rise.

[0003] As a critical cardiovascular disease, aortic dissection lacks an effective early warning system. Aortic dissection usually has no obvious symptoms before onset, and patients often seek medical attention with sudden chest pain or abdominal pain. If not treated in time, the early mortality rate is extremely high. The main causes of death include aortic rupture, aortic regurgitation, acute cardiac tamponade, acute myocardial infarction, acute heart failure, and other cardiac complications and complications of poor organ perfusion. With the development of minimally invasive endovascular repair technology, the development of new aortic interventional devices, and the continuous improvement of surgical procedures, the diagnosis and treatment rate of aortic dissection has greatly improved, but the difficulty of surgery is still great, and the mortality rate is still high. Therefore, early diagnosis and prevention of aortic dissection is crucial. Currently, the diagnosis of aortic dissection mainly relies on medical history, electrocardiogram, X-ray, aortic angiography, transesophageal echocardiography, and aortic computed tomography imaging. Among them, aortic angiography and aortic computed tomography imaging have a sensitivity close to 100% for diagnosing aortic dissection, but imaging tests are time-consuming, and most patients only undergo imaging tests when they have suspected diseases, which cannot effectively prevent the occurrence of aortic dissection. It is crucial to seek biomarkers for early diagnosis and prevention of aortic dissection.

[0004] In recent years, the peripheral blood biomarker research of aortic dissection mainly focuses on smooth muscle myosin heavy chain, soluble elastin fragment, D-dimer, soluble oncogenic suppressor 2, matrix metalloproteinase and other protein macromolecules and a part of small molecule markers including microRNA and small molecule metabolites. Smooth muscle myosin heavy chain and soluble elastin fragment are increased in the early stage of the disease, so the clinical application is limited, and it cannot be used routinely. D-dimer is widely used, but due to the low D-dimer value in the plasma of young patients and patients with short tear length and false embolism, it may lead to misdiagnosis, and the clinical application has certain limitations. Therefore, it is of important practical significance to seek a biomarker with high sensitivity and specificity, convenience, safety and economy for disease prevention and diagnosis. SUMMARY

[0005] The application aims to provide the application of actin 3 in the preparation of a product for diagnosing aortic dissection, so as to solve the problems in the prior art, and can be used for accurately distinguishing aortic dissection and healthy people, providing a serum marker for aortic dissection, and providing a scientific basis for the early clinical diagnosis and prognosis evaluation of aortic dissection.

[0006] To achieve the above object, the application provides the following scheme.

[0007] The application provides the application of actin 3 in the preparation of a biomarker for diagnosing aortic dissection.

[0008] The application also provides the application of a reagent for detecting the expression level of actin 3 in the preparation of a reagent or kit for diagnosing aortic dissection, wherein the actin 3 serves as a biomarker for diagnosing the aortic dissection.

[0009] Preferably, the expression level of the actin 3 in the sample of the subject is detected by using an ELISA method.

[0010] Preferably, the sample of the subject is the plasma of a patient to be detected.

[0011] Preferably, when the content of the actin 3 in the plasma of the patient to be detected is lower than the content of the actin 3 in a control sample, it indicates that the patient to be detected is aortic dissection; and the control sample is the plasma of a healthy person.

[0012] The application also provides a reagent or kit for diagnosing aortic dissection, comprising a reagent for detecting the expression level of actin 3.

[0013] The application discloses the following technical effects:

[0014] The application has great clinical value and practical significance for early diagnosis, long-term prognosis and improvement of life quality of acute aortic dissection by screening plasma markers for early diagnosis of aortic dissection patients. The screened PLS3 gene is screened by spatial transcriptomics, has higher sensitivity and specificity as a molecular marker, and is verified by ELISA, which proves that the gene may be involved in the pathogenesis of aortic dissection and can be used alone as an early diagnostic biomarker and a new therapeutic target for aortic dissection, which provides a new direction for early diagnosis and long-term prognosis evaluation of aortic dissection. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0016] Figure 1 Genes specific to different severity of ascending aorta of aortic dissection; A: stage 1-mild aortic dissection specific genes and spot distribution map, the closer the color is to red, the higher the expression is; B: stage 1 specific gene function annotation, different colors represent different pathways; C: stage 2-moderate ascending aorta of aortic dissection specific genes and spot distribution map, the closer the color is to red, the higher the expression is; D: stage 2 specific gene function annotation, different colors represent different pathways; E: stage 3-severe aortic dissection specific genes and spot distribution map, the closer the color is to red, the higher the expression is; F: stage 3 specific gene function annotation, different colors represent different pathways;

[0017] Figure 2 Expression level concentration values of PLS3 factor as a biomarker in normal control group and aortic dissection group; (*P<0.05)

[0018] Figure 3 ROC curve of PLS3 as a biomarker for comparative analysis of normal control group and aortic dissection group. DETAILED DESCRIPTION

[0019] The various exemplary embodiments of the present application will now be described in detail, which should not be considered as limiting the present application, but should be understood as a more detailed description of certain aspects, characteristics and embodiments of the present application.

[0020] It should be understood that the terms described in the present application are only for describing the specific embodiments, and are not used to limit the present application.

[0021] Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as those commonly understood by one of ordinary skill in the art to which this application pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present application, the preferred methods and materials are described. All publications mentioned in this specification are herein incorporated by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. In case of conflict between the content of the specification and that of any incorporated literature, the content of the specification controls.

[0022] Many modifications and variations of this application of the application can be made without departing from its spirit or scope, which will be apparent to those skilled in the art. Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. The specification and examples given are exemplary only. It is to be understood that the application is not limited in scope by the specific embodiments described herein. Rather, the intent is to embrace all changes and modifications that will become apparent to those skilled in the art as a result of the completion of the teachings of the application.

[0023] As used herein, the terms "comprises", "comprising", "includes", "including", "has", "having", "contains", "containing", or variations thereof, are intended to be open-ended terms that mean inclusion, but not limited to, the listed material or step.

[0024] CXCL1 : Chemokine (C-X-C motif) ligand 1 ;

[0025] PLS3: Actin 3;

[0026] PTMA: Prothymosin alpha;

[0027] SPARC: Secreted protein acidic and rich in cysteine / human bone morphogenic protein;

[0028] ADAMTS8: Disintegrin and metallopeptidase with thrombospondin type 1 motif 8;

[0029] CD36: Scavenger receptor class B member 2 / human platelet membrane glycoprotein IV.

[0030] Example 1 Spatial transcriptomic analysis of differentially expressed genes in patients with aortic dissection

[0031] A total of 15 patients with aortic dissection were enrolled in this study. After surgical vascular replacement, the pathological aorta was collected. After HE staining and RIN detection, 8 samples were finally included. According to the results of aortic computed tomography imaging, the aortic dissection cases were divided into 3 groups according to the widest diameter of the ascending aorta: 35-40 mm, 2 cases; 41-45 mm, 4 cases; 46-50 mm, 2 cases. A total of 19 sections of different parts of the aorta (ascending aorta, brachiocephalic trunk, left subclavian artery, left common carotid artery) were collected. Spatial transcriptomics technology was used to analyze the differentially expressed genes in patients with aortic dissection. The research objects signed the written informed consent form, and this study was approved by the Ethics Committee of the First Affiliated Hospital of Xinjiang Medical University. The spatial transcriptomics technology and analysis methods are as follows:

[0032] 1. Collection, quick freezing and embedding of human aortic tissue

[0033] The pathological tissue collected after vascular replacement was quickly placed in a frozen tissue bottle within 30 minutes. After removing the excess tissue and blood clots from the aortic adventitia, the tissue was trimmed to a cross-sectional area of about 6x6 mm. The quick-frozen tissue was placed in a properly sized embedding box, and the tissue sample was quickly embedded with OCT embedding medium and placed on dry ice until the OCT solidified and turned white. The embedded OCT tissue was transported to the cryostat, and the temperature was balanced in the low-temperature incubator for more than 20 minutes. The thickness of the section was adjusted, and 20-30 consecutive tissue sections were cut. The sections were stacked in a labeled and pre-cooled 1.5 mL centrifuge tube.

[0034] 2. RNA extraction, RIN value evaluation and patching

[0035] Trizol method and Qiagen RNeasy Mini kit (Qiagen, Germany) were used to extract RNA. The purified RNA was stored at -80℃ for long-term storage, or immediately used for RIN detection with Agilent RNA 6000 Nano or Pico kit (Agilent, USA). The specific steps are described in the Agilent RNA 6000 Nano kit instructions, and the detection was performed according to the Agilent 2100 bioanalyzer system operation guide. The detection results were analyzed, and the sections with RNA quality detection RIN>7 were considered as qualified samples. The qualified samples were selected and patched on the Visium spatial gene slide prepared in the low-temperature incubator.

[0036] 3. Preparation of spatial tissue optimized slide and spatial gene expression slide

[0037] The Visium Spatial Gene Expression solution is a method for spatially resolved visualization and quantification of the transcriptome in individual tissue samples by applying spatial transcriptomics technology to standard methods of tissue sectioning and staining. The whole transcriptome mRNA expression is investigated at spatial resolution, while histology-related information is obtained in the same tissue section. There are four capture areas (6.5x6.5mm) on each slide for library construction, each containing 5000 barcoded spots with a diameter of 55μm, each spot has a unique barcode sequence. When the RNA is released from the cells of the tissue section, the RNA migrated to each spot will be labeled with the corresponding barcode sequence, then library construction and sequencing are performed. After that, the data is allocated according to the barcode information of the data to determine the location of the data source, and finally the visualization of spatial gene expression is realized.

[0038] The Spatial Gene Expression Solution Kit includes two types of Visium Spatial Gene Tissue Optimization Slide and Visium Spatial Gene Expression Slide:

[0039] (1) Visium Spatial Gene Tissue Optimization Slide: used to determine the optimal permeabilization time for a specific tissue type. It includes 8 capture areas, each area covers mRNA capture oligonucleotides, and each capture area is surrounded by an 8x8mm reference frame. The active surface of the slide is the readable label (serial number and two-dimensional code).

[0040] (2) Visium Spatial Gene Expression Slide: generate Visium Spatial Gene Expression Library, including 4 capture areas, each capture area is 6.5x6.5mm, and there are about 5000 unique gene expression Barcoded Spots, surrounded by a reference frame with a total area of 8x8mm.

[0041] The primer sequence of the active surface of the Visium Spatial Gene Expression Slide is:

[0042] 5'-CTACACGACGCTCTTCCGATCT-NNNNNNNNNNNNNNNN-NNNNNNNNNNNN-TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTVN-3'(SEQ ID NO:1).

[0043] 4. Tissue optimization

[0044] Prior to library construction, Visium spatial organization optimization can optimize the penetration conditions of the tissue of interest. The tissue section is stained with HE, and the bright field image is taken using a Leica SCN 400 slide scanner; the fixed and stained tissue section is treated with different times of permeabilization enzyme (permeabilization enzyme treatment for 3 min, 6 min, 12 min, 18 min, 24 min, 30 min, respectively), and the tissue patch is captured in the Visium spatial tissue optimization slide capture area. The section is fixed and stained, and different times of penetration are performed. During the penetration process, the tissue releases mRNA, which is captured by the slide capture area. A mixture containing reverse transcription reagents and fluorescently labeled nucleotides is added to the surface of the tissue patch to produce fluorescently labeled cDNA. After that, the tissue is removed with a tissue removal enzyme, leaving the fluorescent cDNA covalently linked to the oligonucleotide on the tissue optimization slide. The fluorescent cDNA is visualized by imaging with a Leica DMi8 fluorescence microscope, and the morphology of the tissue is compared between the HE staining bright field image and the fluorescence image. The penetration time that produces the maximum fluorescence signal is the optimal one.

[0045] 5. Visium spatial gene expression

[0046] The Visium spatial gene expression solution is to measure the total mRNA in a whole tissue section and map the location of active gene expression. Each spatial gene expression slide contains capture areas with gene expression dots, which include primers and polyadenylated mRNA substrates required for capturing mRNA. The tissue section placed in these capture areas is fixed, stained, and permeabilized with a permeabilization enzyme. After that, the cellular mRNA is captured by the primers on the gene expression dots, and all cDNA generated from the mRNA captured by the primers at a specific site has a common spatial barcode. The single-cell 3' gene expression library is generated from the cDNA and sequenced, and the read content is associated with the tissue section image using the spatial barcode, so as to map the spatial gene expression. The steps in this stage include the following parts:

[0047] (1) Tissue section, fixation, and staining;

[0048] (2) Tissue permeabilization, reverse transcription, and optimal conditions selected by "tissue optimization" to obtain cDNA;

[0049] (3) Double-strand synthesis and denaturation: double-strand synthesis primer: 5'-AAGCAGTGGTATCAACGCAGAG-3' (SEQ ID NO: 3);

[0050] (4) cDNA amplification and quality control:

[0051] The cDNA primers include a forward primer: 5'-CTACACGACGCTCTTCCGATCT-3' (SEQ ID NO: 2) and a reverse primer: 5'-AAGCAGTGGTATCAACGCAGAG-3' (SEQ ID NO: 3);

[0052] The cDNA quality was detected using an Agilent 2100 Bioanalyzer.

[0053] 6. Visium spatial gene expression library construction

[0054] The Visium spatial gene expression library was constructed using the cDNA obtained in the previous step. The steps include the following parts:

[0055] (1) The sample was fragmented using a PCR instrument to start the fragmentation program; (2) after fragmentation, end repair, A tailing, and SPRI double-end screening of the sample were performed according to the SPRI screening kit (Beckman Coulter Company); (3) adapter ligation; (4) purification after adapter ligation, SPRI screening; (5) sample with double-end Index, PCR; (6) after the sample with double-end Index, PCR double-end SPRI screening; (7) library construction quality inspection.

[0056] 7. Sequencing

[0057] The Visium spatial gene expression library is a standard Ilumina paired structure starting with P5 and ending with P7. Sequencing of these libraries generates a standard Illumina BCL output data folder.

[0058] (1) Sequencing depth estimation: calculated according to the size of the area covered by the capture region in the tissue HE staining bright field imaging, total sequencing depth = (capture region (%) x total number of capture region spots (5000)) x 50000 read pairs / spot.

[0059] (2) Library sequencing was completed by Shanghai Jingneng Bio Company, using an Ilumina Nova 6000 sequencing platform for sequencing.

[0060] 8. Bioinformatics analysis of data

[0061] Raw data was processed using the official analysis pipeline and software of 10x Genomics. The raw data obtained after sequencing of the samples was analyzed according to the quality control method and data analysis pipeline: SCTransform normalization + PCA dim30 + t-SNE + UMAP, and the data was analyzed. The differences in gene expression and cell types in different parts of the aorta and different severity of the ascending aorta under the condition of aortic dissection were analyzed in detail, and the gene expression and cell atlas of aortic dissection were established.

[0062] Differential gene expression analysis of ascending aorta with different severity: a sample with different severity of ascending aorta was randomly selected for analysis. Seurat was used for differential gene expression analysis, including common differentially expressed genes and differentially expressed genes specific to each sample with different severity. Then Metascape software was used for functional annotation, and several space-related genes were selected to show the distribution.

[0063] 9. Gene expression pattern of ascending aorta with different severity in aortic dissection

[0064] The results showed that in the ascending aorta of aortic dissection at different stages, there were 103 genes specific to stage 1 - mild aortic dissection, 72 genes specific to stage 2 - severe aortic dissection, and 268 genes specific to stage 3 - severe aortic dissection. There were 181 genes commonly expressed in the three stages.

[0065] Among them, the gene expression pattern specific to the ascending aorta with different severity in aortic dissection was: stage 1 - mild aortic dissection, 2 genes were selected according to gene expression position, including CXCL1 and PLS3, which were mainly distributed in the intima of the ascending aorta. The number of spots was visualized (see Figure 1 A), and the Top20 pathways involved in these two genes were annotated, mainly involved in interleukin-mediated signaling pathways, inflammatory factor signaling pathways, and related to inflammatory response (see Figure 1 B); stage 2 - moderate aortic dissection, 2 genes were selected according to gene expression position, including PTMA and SPARC, which were mainly distributed in the middle tear of the ascending aorta. The number of spots was visualized (see Figure 1 C), and the Top20 pathways involved in these two genes were annotated, mainly involved in the maintenance of extracellular matrix structure organization, bone development, and vascular development pathways, which were related to vascular remodeling (see Figure 1 D); similarly, stage 3 - severe aortic dissection, 2 genes were selected according to gene expression position, including ADAMTS8 and CD36, which were mainly distributed in the adventitia of the ascending aorta. The number of spots was visualized (see Figure 1In E), the two genes were functionally annotated, and the top 20 pathways involved were shown to be involved in cell adhesion regulation, hypoxia signaling pathways, which are related to cell activity and oxygen homeostasis (see Figure 1 In F).

[0066] Example 2 Validation of serum markers in a larger sample of aortic dissection patients

[0067] 1. Test method

[0068] According to the inclusion and exclusion criteria, patients diagnosed with aortic dissection by aortic CT angiography and healthy control population were included. 88 patients with aortic dissection and 88 healthy controls were selected. ELISA was used to verify whether the above factors could determine whether the patient had aortic dissection. PLS3 ELISA detection kit (JL52785, Shanghai Jianglai Company, China) was used for detection. Inclusion criteria for aortic dissection patients: patients diagnosed with acute aortic dissection by aortic CT angiography, age ≥18 years, and signed informed consent form; exclusion criteria: patients with a history of rheumatic disease, autoimmune disease, aortitis, pregnancy or genetic syndrome (such as Marfan syndrome, etc.). Inclusion criteria for healthy control blood samples: healthy subjects aged ≤65 years, without hypertension or drug-controlled hypertension, no history of cardiovascular disease and no coronary heart disease by coronary angiography; exclusion criteria: patients with cardiovascular disease and systemic disease.

[0069] The experimental principle is to use double antibody sandwich enzyme-linked immunosorbent assay (ELISA). The micro-wells coated with the corresponding index capture antibody are added with samples, standards, biotin-labeled detection antibodies, HRP enzyme conjugate, incubated and washed in between, and colored with substrate TMB. TMB is converted to blue under the catalysis of peroxidase (HRP) and to final yellow under the action of acid. The color depth is positively correlated with the corresponding protein concentration in the sample. The absorbance (OD value) is measured at 450 nm wavelength by a microplate reader, and the sample concentration is calculated. Refer to the kit instruction manual for detailed experimental procedures. Note that:

[0070] (1) Sample processing: blood plasma was used for detection, and the specimen was collected with EDTA or heparin as an anticoagulant, and centrifuged at 1000 x g for 15 minutes at 4°C within 30 minutes after collection. The supernatant can be detected, or the supernatant can be stored at -80°C, but repeated freezing and thawing should be avoided.

[0071] (2) Preparation of standard gradient working solution: the standard gradient working solution was prepared in EP tubes by using the dilution method, and the specific preparation method was described in the kit instruction manual.

[0072] (3) Prepare the biotinylated antibody detection working solution, enzyme conjugate working solution and 1X washing working solution in advance according to the instructions.

[0073] (4) Result Interpretation: 1. Calculate the average OD value of the standard and sample replicates and subtract the OD value of the blank wells as the correction value. Plot the standard curve of the four-parameter logic function on logarithmic graph paper with concentration on the x-axis and OD value on the y-axis (remove the values ​​of the blank group when plotting). 2. If the OD value of the sample is higher than the upper limit of the standard curve, it should be appropriately diluted and retested, and the sample concentration should be multiplied by the corresponding dilution factor when calculating the sample concentration.

[0074] Using the ELISA method described above, PLS3 was used as a biomarker to analyze and detect aortic dissection in the aortic dissection group and the normal healthy group. The obtained data were analyzed using SPSS 26.0 statistical software and receiver operating characteristic (ROC) curves were plotted to determine whether the novel biomarker can become a new diagnostic biomarker for aortic dissection.

[0075] 2. Test Results

[0076] like Figure 2 As shown in Table 1, this figure shows the expression level of PLS3 as a biomarker in the normal control group and the aortic dissection group. The results show that PLS3 can effectively distinguish between healthy individuals and patients with aortic dissection.

[0077] Table 1. PLS3 plasma ELISA concentrations

[0078]

[0079] The ROC curve of PLS3 as a biomarker in distinguishing between the normal control group and the aortic dissection group, such as Figure 3 As shown in Table 2. The results show that an area under the ROC curve greater than 0.7 indicates good diagnostic value for aortic dissection.

[0080] Table 2. ROC analysis of PLS3 in blood for screening aortic dissection.

[0081]

[0082] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. Use of a reagent for detecting the expression level of PLS3 in the preparation of a reagent or a kit for the early diagnosis of aortic dissection, characterized in that, The PLS3 serves as a biomarker for early diagnosis of the aortic dissection.

2. Use according to claim 1, wherein The expression level of the PLS3 in the sample of the subject is detected by ELISA.

3. Use according to claim 2, wherein the compound is ###0002### The sample of the subject is the plasma of a patient to be detected.

4. The use according to claim 3, wherein the compound is ###0002### When the content of the PLS3 in the plasma of the patient to be detected is lower than that in a control sample, it indicates that the patient to be detected has an aortic dissection; the control sample is the plasma of a healthy person.

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