CN111257569B - Marker for diagnosing recurrent abortion and application thereof - Google Patents

Abstract

The invention discloses a group of recurrent abortion diagnosis markers Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3, MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA-3, HVEM, S100A8 and GRoa, and application of the markers in preparing recurrent abortion diagnosis products. The inventor can greatly improve the accuracy of early diagnosis of recurrent abortion by simultaneously detecting a plurality of diagnostic markers related to recurrent abortion.

Description

Marker for diagnosing recurrent abortion and application thereof

Technical Field

The invention relates to the field of biological medicine, in particular to a group of markers for diagnosing recurrent abortion and application thereof.

Background

Humans have about 35000 genes, but human proteins are as many as 100000, and one gene expresses not only one protein. To study life phenomena and elucidate the laws of life activities, it is far from sufficient to know the structure of the genome, and it is necessary to understand the importance of the direct executor of life activities, protein, and Proteomics (Proteomics), one of the important contents of functional genomics, has been developed. The concept of "proteome" was proposed by Wilkins and wiliams in australia in 1994, which is defined as all corresponding proteins expressed by the genome of a cell or a tissue, which is an integral whole of all proteins corresponding to a genome, not limited to one or several proteins, and which is a new research field revealing protein functions and cell vital activity laws. The protein chip method is a new technology developed in recent years along with the development of gene chips. The basic principle is that various proteins are orderly fixed on a medium carrier such as a glass slide to form a detected chip, then an antibody marked with a specific fluorescent substance is used for acting on the chip, the antibody matched with the proteins on the chip is combined with the corresponding proteins, and the fluorescence on the antibody indicates the corresponding proteins and the expression quantity thereof. After washing the antibody which is not complementarily combined with the protein on the chip, the fluorescence intensity of each point on the chip is measured by using a fluorescence scanner or a laser copolymerization scanning technology, and the interaction relation between the protein and the protein is analyzed by the fluorescence intensity, thereby achieving the aim of measuring the expression functions of various genes. The technology shows the capability of processing information rapidly, efficiently and with high flux in the aspects of researches such as antigen antibody detection, disease diagnosis, drug development and the like. The traditional ELISA method is based on unidirectional reaction or single index, and if a large amount of disease information is required to be obtained, more specimens are required to be collected and experiments are respectively carried out. If one wants to further separate the subtypes, one needs to do more individual experiments. Compared with the traditional ELISA method, the detection result of the protein chip has good consistency with the ELISA method, and the protein chip has the characteristic of high flux, can quantitatively detect various proteins at one time, is more concise, convenient and quick compared with the ELISA method, and is worthy of clinical popularization.

At present, the protein chip technology is widely applied to specific protein profile analysis of more than ten malignant tumors such as prostate cancer, ovarian cancer, bladder cancer, pancreatic cancer, breast cancer, liver cancer and the like, and a meaningful protein marker is found and used for early diagnosis of the malignant tumors; there is also a broad search space for early prediction of the occurrence and prognosis of pregnancy related diseases. The measurement of serum from 25 normal pregnant women and 20 women who are clinically suffering from premature birth by using protein chip technology such as stillalcL, and the like, shows that the peak of protein with the mass-to-charge ratio of 7783 is up-regulated, the peak of protein with the mass-to-charge ratio of 3164 is down-regulated, and the preliminary deduction of serum protein which is differentially expressed from normal pregnancy is probably a factor causing premature birth initiation, and the discovery of the two peaks of protein is probably helpful for early prediction of premature birth, so that the best opportunity is provided for preventing premature birth. BuSChA et al, using SELDI-TOF and gene chip technology, determined 24 cases of maternal serum of trisomy 21 syndrome from 10 weeks to 14 weeks and 24 cases of differential proteins from normal pregnancy, initially obtained a panel 1 of characteristic proteomes, considered to be useful for early prediction of trisomy 21 syndrome, and providing the potential for the development of noninvasive prenatal diagnosis.

In the early-stage research on the correlation between recurrent abortion thrombosis and kidney deficiency and blood stasis, the inventor screens two specific proteins IGFBP-rPl and VEGF through protein chip technology, wherein IGFBP-rPl as a secretory protein possibly influences embryo growth and development by inhibiting an EMT process, and causes abortion to occur; VEGF may cause vasoconstriction by its receptor KDR protein distribution, promoting platelet aggregation, forming a pre-thrombotic state, ultimately leading to the occurrence of abortion. Based on the previous study, the inventor further explores specific markers of recurrent abortion and mechanisms for abortion by screening serum of patients with recurrent abortion caused by pre-thrombus state, patients with recurrent abortion caused by non-pre-thrombus state and normal people, so as to predict early treatment of recurrent abortion in an early stage.

Disclosure of Invention

The invention aims at solving the technical problems, provides a group of markers for diagnosing recurrent abortion and application thereof, and further provides related detection products thereof.

To achieve the above object, the present invention provides, first, the use of an agent for detecting a protein, which is one or a combination of several of Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3, MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA-3, HVEM, S100A8, GROa, for preparing a diagnostic product for recurrent abortion.

Preferably, the Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3 are down-regulated in serum from patients with recurrent abortion, and MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA15-3, HVEM, S100A8, GROa are up-regulated in serum from patients with recurrent abortion.

Preferably, the use of an agent for detecting a protein, which is one or a combination of several of G-CSF R, CNTF, MIG, MDC, ANG-2, syndecan-3, HVEM, MIF, S100A8, GROa, in the preparation of a diagnostic product for recurrent abortion.

Preferably, the recurrent abortion includes recurrent abortion caused by a pre-thrombotic state and recurrent abortion caused by a non-thrombotic state.

Further, the present invention provides the use of an agent for detecting a protein Furin, prolactin, B2M, hCGb, MMP-3, TACE, IGF-1R, G-CSF, ADAM12, CEA, IL-1RII, G-CSF R, IL-17, JAM-B, BLC, VEGF R1, ADAM8, SLAM, CNTF, MIG, MDC, syndecan-3, MIF, MCP-4, NRG1-b1, IL-15R in the preparation of a diagnostic product for recurrent abortion caused by a non-thrombotic pre-condition.

Preferably, the Furin, prolactin, B2M, hCGb, MMP-3, TACE, IGF-1R, G-CSF, ADAM12, CEA, IL-1RII, G-CSF R, IL-17, JAM-B, BLC, VEGF R1, ADAM8, SLAM, CNTF, MIG, MDC, syndecan-3 is down-regulated in serum of patients with recurrent abortion caused by non-thrombotic conditions, and MIF, MCP-4, NRG1-b1, IL-15R is up-regulated in serum of patients with recurrent abortion caused by non-thrombotic conditions.

Preferably, the diagnostic product is a protein level diagnostic product; the diagnostic product for protein levels is a protein level detection by immunodetection, westernblotting or protein chip.

Preferably, the product comprises a protein chip or kit.

Further, the invention provides a protein chip for detecting recurrent abortion, which can detect recurrent abortion by detecting the expression level of a protein, wherein the protein is one or a combination of a plurality of G-CSF R, CNTF, MIG, MDC, ANG-2, syndecan-3, HVEM, MIF, S A8 and GROa.

Preferably, the protein chip comprises a solid support and antibodies specific for the protein immobilized on the solid support.

The beneficial effects of the invention are as follows:

the invention discloses the application of protein chips in Prolactin, MMP-3, furin, IGF-1R, B-2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3, MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA-3, HVEM, S100A8 and GRoa differential proteins in recurrent abortion diagnosis products, and the application of the differential proteins in the recurrent abortion diagnosis products is provided, and the value of the differential proteins in early diagnosis is revealed. Therefore, the invention can diagnose whether recurrent abortion occurs or not by detecting differential expression of Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3, MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA15-3, HVEM, S100A8 and GROa proteins, and further develop diagnostic chips, kits or biological agents for recurrent abortion, which can rapidly and effectively diagnose early and provide the best early intervention time for patients.

Further, the inventors screened Furin, prolactin, B2M, hCGb, MMP-3, TACE, IGF-1R, G-CSF, ADAM12, CEA, IL-1RII, G-CSF R, IL-17, JAM-B, BLC, VEGF R1, ADAM8, SLAM, CNTF, MIG, MDC, syndecan-3, MIF, MCP-4, NRG1-b1, IL-15R differential proteins by protein chip on blood samples of non-thrombotic pre-condition-induced recurrent abortion patients and normal persons and provided their use in diagnostic products for non-thrombotic pre-condition-induced recurrent abortion.

In addition, the inventors have found a set of recurrent abortion diagnostic markers Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3, MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA15-3, HVEM, S100A8, GROa, which can greatly improve the accuracy of early diagnosis of recurrent abortion by simultaneously detecting a plurality of diagnostic markers associated with recurrent abortion.

Drawings

FIG. 1 is a summary of protein chip differences in 48 serum samples;

FIG. 2 is a cluster analysis of differential expression cytokine abundance in a disease group versus a normal group, black for up-regulated expression and grey for down-regulated expression;

FIG. 3 is a diagram of FUNRICH analysis biological process;

FIG. 4 is a signal pathway involved in differential proteins;

FIG. 5 is a graph showing the analysis of the differential protein interactions between the disease group and the normal group;

FIG. 6 is a cluster analysis of non-thrombotic pre-status group versus normal group differentially expressed cytokine abundance, black for up-regulated expression and grey for down-regulated expression;

FIG. 7 is a cluster analysis of differential expression cytokine abundance for validation of disease versus normal groups, black for up-regulated expression and grey for down-regulated expression;

FIG. 8 is a cluster analysis of differential expression cytokine abundance in a non-thrombotic pre-status group versus a normal group, black for up-regulated expression and grey for down-regulated expression;

FIG. 9 is a ROC graph of serum markers of the invention used to distinguish recurrent abortion patients from normal controls;

fig. 10 is a ROC curve analysis of 38 serum markers.

Detailed Description

The following examples are illustrative of the invention and are not intended to limit the scope of the invention. Unless otherwise indicated, the technical means used in the examples are conventional means well known to those skilled in the art, and the reagents used are commercially available.

According to the invention, the protein chip is used for screening 12 women with normal pregnancy history, 24 recurrent abortion patients caused by the pre-thrombus state, and 12 recurrent abortion patients caused by the non-thrombus state, so that 38 abortion-specific proteins are screened. By establishing an unsupervised clustering model for the 38 differential protein expression analysis, a disease diagnosis model is established, namely, a multiparameter mathematical model is utilized to predict risks of normal and unknown cause abortion, and a basis is provided for clinically developing accurate treatment. Subsequently, the inventors further analyzed the functions of the differential proteins using bioinformatics techniques, and found that most of these differential proteins are involved in the development process of cells or embryos, and that the disease group had 26 proteins down-regulated and 12 proteins up-regulated.

Down-regulated proteins Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3. Wherein, for example, MMP-3 matrix glycoprotein can promote the remodelling of tissues; the Prolactin can fully develop the mammary gland in the gestation period, so that the duct at the tail end of the lobule of the mammary gland can be developed into a small acinus; G-CSF R, a polypeptide factor that promotes hematopoietic cell proliferation, and G-CSF binds to G-CSF R to regulate proliferation and differentiation of granulocytes and enhance the function of mature granulocytes; desmoglein2, an intercellular desmosome linked component, is involved in the interaction of plaque proteins and intermediate filaments that mediate intercellular adhesion; participate in EMT regulation; most are associated with cell adhesion, proliferation, cell differentiation, epithelial-to-mesenchymal transition, microvascular generation, etc., suggesting that down-regulation of these proteins increases the risk of abortion.

To further confirm the primary screening results, the inventors selected 20 proteins for corresponding validation. The samples tested were in the pre-thrombotic state group 58, the non-pre-thrombotic state group 34, and the normal group 25. In the disease group (pre-thrombotic + non-pre-thrombotic) 10 proteins were differentially expressed compared to the normal group, 4 of which were up-regulated and 6 of which were down-regulated.

Further, the inventors plotted ROC curves to compare the diagnostic ability of the 38 serum markers described above to distinguish recurrent abortion patients from healthy controls. 38 serum markers were found to have good specificity and sensitivity.

The inventor adopts a novel bioinformatics analysis technology and performs analysis by an unsupervised clustering method. Since diagnosis of clinical diseases is often performed with reference to various indexes, such as imaging, pathology, and physiological and biochemical indexes, diagnosis is performed by various means. The meaning of the single index is not strong, and the clinical requirement cannot be met. The analysis model is built by adopting multiple indexes and multiple parameters, different groups are distinguished in a clustering mode, the clinical coincidence rate can be greatly improved, and particularly the coincidence rate between a non-thrombotic pre-state abortion group and a normal group is completely consistent, so that the modeling mode has important significance for clinical accurate diagnosis and treatment.

Example 1 differential protein screening

1. Clinical data

1.1 case sources:

1.2 case grouping: serum samples of women with normal pregnancy history were 12 (normal group), serum samples of patients with recurrent abortion caused by pre-thrombotic state were 24 (pre-thrombotic state group), and serum samples of patients with recurrent abortion caused by non-thrombotic state were 12 (non-thrombotic state group).

1.3 cases count:

protein chip detection: normal group 12, 24 prethrombotic group, and non-prethrombotic group 12.

2. The invention uses materials and instruments

2.1 kit: a QAH-CAA-440 kit comprising the contents:

the kit is stored at-20 ℃, and after the kit starts to be used, slide chips, cytokine standard mixed powder, detection antibody mixture and Cy 3-streptavidin should be stored at-20 ℃ and other reagents are stored at 4 ℃ so as to avoid repeated freezing and thawing.

The box composition is shown in Table 1.

TABLE 1 kit components

2.2 materials and instruments required except for the kit:

plastic centrifuge tube (2-5 ml,50 ml); shaking table; plastic preservative film; aluminum foil paper; double distilled water; innoScan300Microarray Scanner fluorescence scanner; thermo Scientific WellwashVersa chip washer.

2.3 samples: 48 sera.

3. Experimental procedure

3.1 complete drying of slide chips

The slide chip was taken out of the box, after 20-30min equilibration at room temperature, the package was opened, the sealing tape was peeled off, and the chip was then dried in a vacuum drier or at room temperature for 1 hour.

3.2 configuration of standards

(1) Cytokine standards were diluted in gradient.

(2) Add 500. Mu.l of sample dilution to the vial of cytokine standard mixture and redissolve the standard. Before opening the small tube, the small tube is rapidly centrifuged, dissolved powder is gently whipped up and down, and the small tube is marked as Std 1.

(3) 6 clean centrifuge tubes Std2, std3 through Std7, respectively, were labeled, and 200. Mu.l of sample diluent was added to each vial.

(4) 100 μl of Std1 was added to Std2 and gently mixed, and then 100 μl was added to Std3 from Std2, and the mixture was diluted to Std7 in a gradient.

(5) 100 μl of the sample dilution was drawn into another new centrifuge tube, labeled CNTRL, as a negative control.

Note that: because the initial concentration of each cytokine is different, the serial concentration of each cytokine is different after a gradient dilution of Std1 to Std7.

3.3 chip operation flow

(1) 100 μl of sample dilution was added to each well, incubated for 1h on a room temperature shaker, and the quantitative antibody chip was blocked.

(2) The buffer in each well was removed, 60 μl of standard solution and sample was added to the wells and incubated overnight (2.5 fold dilution of sample loading) on a shaker at 4deg.C.

(3) Cleaning:

the slide was washed with a Thermo Scientific WellwashVersa chip plate washer, in two steps, first with 1 Xwash I, 10 times with 250. Mu.L 1 Xwash I per well, 10s of shaking each time, high shaking intensity selection, and dilution of 20 Xwash I with deionized water. Then, the 1 Xwashing reagent II channel was changed to wash, and 250. Mu.L of 1 Xwashing reagent II per well was washed 6 times with 10s shaking for each time, the shaking intensity was selected to be high, and 20 Xwashing reagent II was diluted with deionized water.

(4) Incubation of the detection antibody mixture:

the antibody mixture vials were centrifuged and then 1.4ml of sample diluent was added and mixed well before rapid centrifugation again. Mu.l of detection antibody was added to each well and incubated for 2 hours on a shaker at room temperature.

(5) Cleaning: the same as in the step (3).

(6) Incubation of Cy 3-streptavidin:

the Cy 3-streptavidin vial was centrifuged, then 1.4ml of sample dilution was added, mixed well and centrifuged again rapidly. Mu.l of Cy 3-streptavidin was added to each well and incubated with aluminum foil paper wrapped glass slide in the dark for 1 hour on a shaking table at room temperature.

(7) Cleaning: the same as in the step (3).

(8) Fluorescence detection:

1) The slide frame was removed and careful not to touch the side of the slide where the antibodies were printed by hand.

2) Scanning the signal with a laser scanner, e.g. InnoScan300, with Cy3 or green channel (excitation frequency=532 nm):

instrument model: innoScan300Microarray Scanner;

the manufacturer: innopsys;

3) The production place: parc d' Activates Activate; 31390Carbonne France;

4) Scanning parameters: wavelength; 532nm; resolution:10 μm.

(9) Data analysis was performed using data analysis software for QAH-CAA-440.

4. Statistical method

After Normalization of the raw data with software, normalization data was selected for analysis. The analysis method is moderatedt-statistics, the data packet is limma, and the data packet is from R/Bioconductor; the differential proteins were screened using an adjustp value (p value corrected by BH method) and logFC (fold difference in expression, base 2) under the following conditions:

logFC > log2 (1.2), the difference threshold is 1.2.

Corrected p value: adj.p.val <0.05.

Finding out a protein regulated by difference by using cluster analysis and intersection analysis-Venn Diagram (Venn Diagram); and carrying out GO/GO-net analysis and KEGG pathway/pathway-net analysis on the differential protein to obtain the recurrent abortion related protein caused by the pre-thrombus state.

5. Protein chip detection

5.1 proteomic differences between disease groups and normal humans

The test uses protein chips to quantitatively detect 440 cytokines in 48 serum samples in total, wherein the detected samples are 24 cases in a pre-thrombus state group, 12 cases in a non-pre-thrombus state group and 12 cases in a normal group. The results are shown in FIG. 1.

5.1.1 group of diseases and Normal group Cluster analysis

First, the inventors performed differential analysis of cytokine expression between the normal and disease groups (pre-thrombotic+non-pre-thrombotic abortions) measured, 38 proteins showed significant differences between the two groups. Then, the inventor performs cluster analysis on the 38 differential proteins, and adopts an unsupervised cluster layering analysis method, and the result shows (figure 2) that the normal group and the disease group are obviously divided into two main groups, and the disease group 36/36 and the normal group 9/12 have the consistency rate of 100% and 75% respectively. The overall consistency is 93.75%, which shows that the 38 protein indexes can effectively distinguish normal groups from disease groups, and provide reference basis for clinical accurate treatment.

5.1.2 disease group and Normal group differential protein analysis

Among the measured values of each group protein concentration, PValue, logFC, FDR, logCPM was calculated, and FDR <0.05, logFC >1 was set as a screening condition, with 26 significantly down-regulated proteins and 12 significantly up-regulated proteins in the disease group compared to the normal group (see tables 2-3).

TABLE 2 differential protein (Down) between normal and disease groups

TABLE 3 differential protein (up) between normal and disease groups

5.1.3 disease group and Normal group differential protein Signal pathway analysis

By analyzing 38 differential proteins (Table 4), it was found that the differential proteins were mainly exhibited in the regulation of biological processes, the regulation of cell processes, cell communication, and the like. Funrich analysis (FIG. 3) differential proteins are associated with cell growth, adhesion anti-apoptosis, and the like. These analysis results indicate that the differential protein may be associated with early embryonic growth development or endometrial changes.

TABLE 4 biological Process involving differential proteins

By analyzing the signal pathway (fig. 4), the inventors found that the differential protein involved signal pathways with vascular wall cell surface interactions, epithelial-to-mesenchymal transition, uPA-mediated thrombolysis, hydrolysis of cell adhesion proteins, angiogenesis, and the like. These above-mentioned signal pathways suggest that there may be some correlation with clinical abortion symptoms.

5.1.4 analysis of the interaction of the disease group with the normal group differential protein (PPI)

To explore the interaction relationship between disease group and normal group differential protein, the inventors performed PPI analysis. The results show (fig. 5) that, among 38 differential proteins, 22 proteins constitute an interaction network, play a role in the biological processes (development) of cells, and that most proteins are involved in the central regulation of CD274, SDC1, IL1B, CXCL, ADAM17, MMP 3. In addition, FLT1-FLT4 (VEGFR 1-VEGFR 4) plays an important role in negative feedback regulation of vascular endothelial cell proliferation.

5.2 detection of protein chips of non-thrombotic Pre-State group and Normal group

The samples tested were 24 cases in the pre-thrombotic state group and 12 cases in the normal group. Analysis is carried out on the detection results of the non-thrombotic pre-state group and the normal histone chip, and the results show that: between the non-thrombotic pre-state group and the normal group, 46 cytokines had significant differential expression. In the serum of the non-thrombotic pre-state group 32 cytokine expression was significantly down-regulated and 14 cytokine expression was significantly up-regulated compared to the normal group, and the cytokine expression was as shown in tables 5 and 6.

The 46 differential proteins were subjected to clustering analysis, and the results (FIG. 6) showed that the normal group and the non-thrombotic pre-state group were clearly divided into two major groups, the disease group 24/24 and the normal group 10/12, with a coincidence rate of 100% and 83.3%, respectively. The overall consistency is 84.4%, which shows that the 46 protein indexes can effectively distinguish normal groups from non-thrombotic pre-state groups, and provide reference basis for clinical accurate treatment.

By analyzing 46 differential proteins, the differential proteins are found to be basically consistent with the differential proteins of a disease group and a normal group, and are mainly displayed in the regulation of biological processes, the regulation of cell processes, cell communication and the like. Funrich analysis of differential proteins is associated with cell growth, adhesion anti-apoptosis, etc. In terms of signal pathways, differential proteins are involved in signal pathways such as vascular wall cell surface interactions, epithelial-to-mesenchymal transition, uPA-mediated thrombolysis, hydrolysis of cell adhesion proteins, angiogenesis, and the like. These above-mentioned signal pathways suggest that there may be some correlation with clinical abortion symptoms. These analysis results indicate that the differential protein may be associated with early embryonic growth development or endometrial changes.

TABLE 5 differential protein (Down) between non-thrombotic pre-state and normal groups

TABLE 6 differential protein (up) between non-thrombotic pre-state and normal groups

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The inventors found that Tie-1, periostin, BMPR-IA, LRIG3, IL-15R, IL-1F5 were up-regulated in the non-thrombotic pre-state group of differential proteins, where Tie-1 was associated with angiogenesis and Periostin was involved in cell adhesion, enhancing the integration of BMP1 in the fibronectin matrix of connective tissue. BMPR-IA is a bone morphogenic receptor and plays an important role in embryogenesis. Downregulated differential proteins FOLR1 (folate receptor), fetuinA (fetuin a), G-CSF (granulocyte colony stimulating factor), CEA (carcinoembryonic antigen), which are down regulated perhaps with respect to abortion.

Example 2 differential protein validation

The differential protein validation method was the same as in example 1.

1. Verification of non-thrombotic preoperative Condition group and prethrombotic Condition group and Normal group differential protein

In the results of the preliminary screening, the inventors found that 38 proteins were significantly up-or down-regulated in the disease group compared to the normal group, and in order to further confirm the differential expression of these proteins, the inventors selected 20 proteins for verification. The samples tested were 58 cases in the pre-thrombotic state group, 34 cases in the non-pre-thrombotic state group, and 25 cases in the normal group.

The results show that: in the results of the validation 10 proteins were differentially expressed compared to the normal group in the disease group, 4 of which were up-regulated and 6 of which were down-regulated, as shown in table 7.

Table 7 demonstrates the differential proteins between the disease and normal groups

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In addition, the results of the unsupervised cluster analysis showed (fig. 7) that 117 samples tested were grouped into two distinct categories, normal and disease groups, clustered results and clinical classifications were completely identical. The 10 differential proteins are suggested to be able to distinguish well between normal and disease groups.

2. Verification of non-thrombotic preoperative and Normal group differential proteins

To understand the differences between the non-thrombotic and normal groups, the inventors analyzed the results of protein chips of the non-thrombotic and normal groups of 34 and 25 cases.

The results show that: in the results of the validation, 14 proteins were differentially expressed compared to the normal group in the non-thrombotic pre-state group, 6 of which were up-regulated and 8 of which were down-regulated, as shown in Table 8.

In addition, the results of the unsupervised cluster analysis showed (FIG. 8) that 59 samples tested were grouped into two distinct classes, the non-thrombotic pre-status group and the normal group, with the clustered results being in complete agreement with the clinical classification. These 14 differential proteins were suggested to distinguish well between the non-thrombotic pre-state group and the normal group.

Table 8 demonstrates the differential proteins between the non-thrombotic pre-state and normal groups

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Example 3 subject operating characteristic (ROC) Curve analysis

ROC curves were constructed to compare the diagnostic ability of 38 serum markers to distinguish recurrent abortion patients from healthy controls. Due to the high number, a curve of 6 serum markers ROC is given as a reference example, as shown in fig. 9. Under the optimal cutoff value, the sensitivity of 38 serum markers is between 0.741 and 0.920, the specificity is between 0.603 and 0.845, and the AUC value is between 0.750 and 0.901.

The AUC for the 38 serum markers combined could reach 0.966, with sensitivities and specificities of 1.00 and 0.862, respectively (as shown in figure 10). These results demonstrate that the 38 marker combinations have a relatively high sensitivity and specificity for early detection of recurrent abortion compared to 38 individual recurrent abortion protein markers.

While the invention has been described in detail in the foregoing general description and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.

Claims (6)

1. Use of a reagent for detecting proteins in the preparation of a diagnostic product for recurrent abortion, said proteins being a combination of 38 proteins: prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3, MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA15-3, HVEM, S100A8, GROa.

2. The use of claim 1, wherein Prolactin, MMP-3, furin, IGF-1R, B2M, hCGb, testican2, SLAM, G-CSF R, JAM-B, desmoglein2, CEA, ADAM12, IL-1RII, ADAM8, BLC, TACE, VEGF R1, IL-17C, syndecan-1, ANGPTL4, CNTF, MIG, MDC, ANG-2, syndecan-3 are down-regulated in serum of patients with recurrent abortion and MIF, MCP-4, NRG1-B1, MCP-3, B7-H1, VEGF R3, BMP-4, IL-15R, CA-3, HVEM, S100A8, GROa are up-regulated in serum of patients with recurrent abortion.

3. The use of claim 1, wherein the recurrent abortion comprises recurrent abortion caused by a pre-thrombotic state and recurrent abortion caused by a non-thrombotic state.

4. The use according to claim 1, wherein the diagnostic product is a protein level diagnostic product; the diagnostic product for protein levels is protein levels detected by immunodetection, western blotting or protein chips.

5. The use of claim 4, wherein the diagnostic product comprises a protein chip or a kit.

6. The use of claim 5, wherein the protein chip comprises a solid support and antibodies specific for the protein immobilized on the solid support.