Application of specific antibodies and humanized antibodies in the preparation of detection reagents for improving the accuracy of prediction of severe dengue infection individuals

Abstract

The present invention discloses a clustering method for improving the prediction accuracy of severe dengue infection individuals. The method simultaneously detects and cross-compares whether an in vitro biological sample contains non-structural protein 1 (NS1) of dengue virus and endogenous anti-NS1 antibodies, which can effectively reduce the false negative rate of the test results and improve the clustering accuracy of severe dengue patients.

Description

Technical Field

[0001] The present invention relates to a medical detection method, and more particularly to a clustering method for improving the prediction accuracy of severe dengue fever individuals by detecting dengue virus non-structural protein 1 (NS1) and endogenous anti-NS1 antibodies in an in vitro biological sample. Background Art

[0002] Dengue fever is a fast-spreading disease with a short course. Every year, approximately 390 million people worldwide are infected with dengue virus. The clinical symptoms of dengue patients vary greatly, ranging from fever similar to the common cold to fatal dengue shock syndrome or dengue hemorrhagic fever. If severe dengue fever can be diagnosed early, timely disease monitoring and management can be provided; however, currently available testing technology cannot meet the clinical needs of predicting the severity of dengue fever. New studies in recent years have found that NS1 is an important viral toxin, which is known to cause important pathogenic effects such as plasma leakage, coagulation disorders and low platelets during severe dengue. In addition, anti-NS1 antibodies have been shown in animal experiments to be effective in treating hemorrhagic lesions caused by dengue infection.

[0003] Previous studies have found that the viral toxin NS1 in the serum samples of dengue-infected patients will form a complex with thrombin or prothrombin, prolonging the activation time of some thromboplastins and causing severe bleeding. Therefore, the current testing process will conduct a first test (referred to as the first test) and a rapid screening of the NS1 antigen of the dengue virus for suspected dengue infection cases. If the result of the first test is negative, a second test (referred to as the second test) will be conducted and dengue virus-specific real-time PCR, RT-PCR, IgM / IgG and other tests will be conducted. Among them, the IgM / IgG test refers to the anti-dengue virus IgM or IgG antibody seroconversion (seroconversion) of the second test serum or the increase of IgG antibodies by at least four times as a positive.

[0004] However, the current testing process has a high false negative rate for patients with mild dengue fever, which can easily lead to misjudgment. In view of this, it is urgent to provide a clustering method that improves the accuracy of prediction of severe dengue infection to improve the problem of high false negative rate in the test results of conventional dengue fever patients. Summary of the invention

[0005] Therefore, one aspect of the present invention is to provide a clustering method for improving the accuracy of predicting severe dengue infection, which simultaneously detects and cross-compares whether an in vitro biological sample contains the non-structural protein 1 (NS1) of the dengue virus and endogenous anti-NS1 antibodies, thereby effectively reducing the false negative rate of the test results and improving the accuracy of clustering of severe dengue patients.

[0006] According to the above aspects of the present invention, a clustering method for improving the accuracy of prediction of severe dengue infection is provided. In one embodiment, the clustering method includes providing an in vitro biological sample, performing at least one detection step on the in vitro biological sample to obtain a first detection result and a second detection result, and cross-comparing the first detection result and the second detection result to obtain a clustering result.

[0007] In the above embodiments, the ex vivo biological sample has not been diagnosed or differentially diagnosed as being infected with dengue virus or suspected of being infected with dengue virus.

[0008] In the above embodiment, the first detection result corresponds to the non-structural protein 1 (NS1) of dengue virus and / or the NS1 complex, and the second detection result corresponds to the endogenous anti-NS1 antibody.

[0009] In the above embodiment, when at least one of the first test result and the second test result is positive, it is determined that the individual corresponding to the ex vivo biological sample is classified as a severe dengue infection group.

[0010] In the above embodiments, the in vitro biological sample includes blood, urine, saliva, tissue fluid and / or lymph fluid.

[0011] In the above embodiment, the first detection result is to detect NS1 and / or NS1 complex using an antibody, the antibody is an exogenous anti-NS1 antibody, and the NS1 complex comprises the aforementioned NS1-thrombin or NS1-prothrombin.

[0012] In the above embodiment, the serotypes of dengue virus may include type 1, type 2, type 3 and type 4.

[0013] In the above embodiment, the endogenous anti-NS1 antibody is a humanized antibody, and the endogenous anti-NS1 antibody comprises a first antibody and a second antibody, wherein the first antibody can, for example, specifically recognize the 109th to 122th amino acid residues of the NS1, and the second antibody can, for example, specifically recognize the 114th to 119th amino acid residues of the NS1. In one example, the type of the endogenous anti-NS1 antibody is IgG and / or IgM, and the second detection result refers to the content ratio of the first antibody to the second antibody.

[0014] In the above embodiments, the individual may be, for example, a mammal, such as a human.

[0015] In the above embodiment, when both the first test result and the second test result are negative results, it is determined that the individual corresponding to the ex vivo biological sample is classified as non-dengue infection severe disease.

[0016] In the above embodiments, at least one detection step comprises enzyme-linked immunosorbent assay (ELISA), Western blot analysis, lateral flow immunoassay, multiplex immunoassay, radioimmunoassay, immunoradiometric assay, fluorescent immunoassay, chemiluminescent immunoassay and / or immunoturbidimetric assay.

[0017] The clustering method for improving the accuracy of prediction of severe dengue infection of the present invention simultaneously detects and cross-compares whether the in vitro biological sample contains NS1 of the dengue virus and endogenous anti-NS1 antibodies, which can effectively reduce the false negative rate of the test results and improve the accuracy of clustering of severe dengue patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To make the above and other objects, features, advantages and embodiments of the present invention more clearly understood, the detailed description of the accompanying drawings is as follows:

[0019] Figure 1 The figure shows the content ratio of modified NS1 flanking domain (NS1-WD) IgG / NS1 IgG in the sera of various dengue patients according to one embodiment of the present invention.

[0020] Figure 2 The figure shows the consistency results of the specificity and sensitivity of the conventional method for predicting severe dengue infection.

[0021] Figure 3 The figure shows the consistency results of the specificity and sensitivity of the NS1 antigen in the serum of dengue patients for the prediction of severe dengue infection according to one embodiment of the present invention.

[0022] Figure 4 The figure shows the consistency results of the specificity and sensitivity of the endogenous anti-NS1 antibody ratio in the serum of dengue patients for the prediction of severe dengue infection according to one embodiment of the present invention.

[0023] Figure 5 The results are shown to show the consistency of the specificity and sensitivity of predicting severe dengue infection by detecting the endogenous anti-NS1 antibody ratio in the serum of dengue patients using the mouse antibody of the comparative example. DETAILED DESCRIPTION

[0024] The following detailed description and the accompanying drawings are used to describe the embodiments of the present invention in detail. The same figure numbers used in the drawings and the specification refer to the same or similar parts as much as possible.

[0025] All references cited herein are treated as if each individual reference or patent application was specifically and individually incorporated by reference. If a definition or use of a term in a referenced document is inconsistent or contrary to the definition of that term herein, the definition of that term herein applies and the definition of that term in the referenced document does not apply.

[0026] For purposes of interpreting the specification, the following definitions shall apply and, where appropriate, singular terms shall include the plural and vice versa. Additional definitions are set forth throughout the detailed description.

[0027] Unless the context is inappropriate, "a", "an" and "the", "said" as used herein are defined as "one or more" and include the plural.

[0028] As mentioned above, the present invention provides a clustering method for improving the accuracy of predicting severe dengue infection, which simultaneously detects and cross-compares whether an in vitro biological sample contains the non-structural protein 1 (NS1) of the dengue virus and endogenous anti-NS1 antibodies, which can effectively reduce the false negative rate of the test results and improve the accuracy of clustering of severe dengue patients.

[0029] The term "dengue virus" as used herein may be used interchangeably with "dengue fever virus" and "DENV". The serotypes of the dengue virus may include, but are not limited to, type 1, type 2, type 3, and type 4.

[0030] In the serum samples of dengue infected patients, the non-structural protein 1 (NS1) of dengue virus will form a complex with thrombin or prothrombin, prolonging the activation time of the activated part of thrombin, and then causing severe bleeding. Although the conventional technology uses the detection of the presence of a complex containing NS1 and thrombin or a complex containing NS1 and prothrombin in an in vitro biological sample to determine whether an individual is infected with dengue virus. However, among dengue infected patients, there is a considerable difference in the severity of the disease among different patients, and those with severe illness may even die. The current testing process only detects the complex of NS1 and thrombin or the complex containing NS1 and prothrombin, and the false negative rate of the test result is high, which cannot accurately determine the severity of the disease, and may neglect the condition and delay the treatment schedule.

[0031] Therefore, the method of the present invention is to perform at least one detection step on the ex vivo biological sample, cross-compare the obtained first detection result and the second detection result and obtain the grouping result to determine whether the ex vivo biological sample contains NS1 of dengue virus and endogenous anti-NS1 antibodies, thereby effectively reducing the false negative rate of the detection result and improving the accuracy of grouping of severe dengue patients. It should be noted that the "detection" described here can be used interchangeably with "testing", and "accuracy" can also be used interchangeably with "accuracy rate".

[0032] The above-mentioned "ex vivo biological sample" generally refers to the range that can be affected in an individual infected with dengue virus, and there is no special limitation. It may include but is not limited to blood (such as serum, plasma or whole blood), urine, saliva, lymph or tissue fluid, or nearby tissues or cells through which blood, urine, lymph or tissue fluid flow. In some examples, the above-mentioned in vitro biological sample is preferably one containing cells infected by dengue virus, and these cells may include but are not limited to nerve cells, muscle cells, liver cells, endothelial cells, blood cells and lymphocytes, and it is preferably one containing endothelial cells or blood cells of mammals. In other examples, the above-mentioned in vitro biological sample may be, for example, a fresh, tissue cultured, or refrigerated or frozen sample. In some specific examples, the above-mentioned in vitro biological sample may be subjected to conventional pretreatment (such as purification, centrifugation, extraction or concentration methods) to increase the concentration of the analyte (such as NS1 and / or NS1 complex, endogenous anti-NS1 antibody, etc.).

[0033] The above-mentioned "first detection result" corresponds to the non-structural protein 1 (NS1) of dengue virus and / or the NS1 complex. In other words, the above-mentioned first detection result is to detect NS1 and / or the NS1 complex using an antibody, wherein the antibody is an exogenous anti-NS1 antibody. In one example, the NS1 complex comprises NS1-thrombin or NS1-prothrombin.

[0034] The aforementioned "exogenous antibody" may be, for example, a monoclonal antibody or a polyclonal antibody. In some embodiments, the antibody that specifically recognizes NS1 may be, for example, a monoclonal antibody. In other embodiments, the antibody that specifically recognizes the NS1 complex may be, for example, a polyclonal antibody.

[0035] The aforementioned exogenous antibodies include antibody-based binding moieties, immunoglobulin molecules and their immunologically active determinants, such as molecules containing an antigen-binding site that immunospecifically binds to NS1 or the aforementioned complex. The antibody type of the exogenous antibodies is not limited, and may include, but is not limited to, IgG, IgA, IgM, and IgE.

[0036] The above-mentioned exogenous antibodies may also include antigen-binding fragments that specifically react with NS1 or the aforementioned NS1 complex. The structure of the antigen-binding fragment is not limited. Under the premise of taking into account the structural stability of the complementarity-determining region (CDR), it can be a complete antibody structure or a simplified antibody structure, such as a single-chain variable fragment (scFv), a single-chain variable fragment dimer ((scFv)2), a single-chain variable fragment trimer ((scFv)3), a variable fragment (Fv), a Fab fragment, a Fab' fragment, a F(ab')2 fragment, a nanobody (also known as a single-domain antibody (sdAb) or a heavy-chain antibody) or any combination thereof.

[0037] In addition to detecting NS1 and / or NS1 complexes in ex vivo biological samples, after a patient is infected with dengue virus, "endogenous antibodies" against NS1 will be produced in the body. The inventors also found that the concentration of NS1 and / or NS1 complexes in the patient's body and the concentration of endogenous antibodies against specific NS1 peptide sequences are related to the severity of dengue disease. In one embodiment, endogenous anti-NS1 antibodies in an ex vivo biological sample can be detected to obtain a second test result.

[0038] In this embodiment, the type of endogenous anti-NS1 antibody is not limited, and may include but is not limited to a first antibody and a second antibody. In some examples, the first antibody refers to an endogenous antibody that specifically recognizes the 109th to 122nd amino acid residues of dengue virus NS1, wherein the 109th to 122nd amino acid residues of NS1 can be defined as a modified NS1-WD peptide, hereinafter referred to as an antibody against a modified NS1-WD peptide or an antibody against NS1-WD peptide. Past clinical studies have found that the higher the concentration of such anti-NS1-WD peptide antibodies in patients, the less likely they are to develop severe disease. In addition, the quality and quantity of anti-NS1-WD peptide antibodies are also related to the severity of the disease.

[0039] In other examples, the second antibody refers to an endogenous antibody that specifically recognizes the 114th to 119th amino acid residues of dengue virus NS1, wherein the 114th to 119th amino acid residues of NS1 belong to the conserved sequence of the four serotypes of dengue virus, which is conducive to the recognition of NS1 of the four serotypes of dengue virus, and is also called "antibody against all serotypes of NS1" or "anti-NS1 antibody".

[0040] In other embodiments, the endogenous anti-NS1 antibody is of any type, and may be, for example, IgG and / or IgM. In some specific examples, the second detection result refers to the content ratio of the first antibody to the second antibody.

[0041] In some specific examples, for example, humanized antibodies (hAb) can be used to specifically identify the above-mentioned endogenous anti-NS1 antibodies. The method of producing humanized antibodies is common knowledge in the technical field to which the present invention belongs. In some examples, a humanized antibody framework can be used to replace the corresponding sequence of the human antibody with the CDR sequence of the rodent antibody to obtain a humanized antibody, and this type of humanized antibody belongs to a human-mouse chimeric antibody. In the case of human-mouse chimeric antibodies, the human antibody germline sequence obtained from the public database can be selected for the human antibody framework of the acceptor human antibody, and the human race of the acceptor human antibody framework is not particularly limited, depending on the in vitro biological sample to be detected.

[0042] The term "individual", "subject" or "patient" as used herein refers to a mammal. In one embodiment, the individual, subject or patient may be a human.

[0043] The dengue patients with "mild symptoms" mentioned here refer to those who present "warning signs" (or "warning symptoms") or have no warning signs, wherein the warning signs may include, but are not limited to, abdominal pain or tenderness, persistent vomiting, clinical fluid accumulation, and mucosal bleed. In other examples, mild patients without warning signs can be classified as group A patients, and mild patients with warning signs can be classified as group B patients. The relevant judgment principles can be referred to the Handbook for Clinical Management of Dengue published by the World Health Organization (WHO).

[0044] The "severe" dengue patients mentioned here refer to those who present with symptoms such as severe plasma leakage causing shock and fluid accumulation and respiratory distress, severe bleeding or severe organ impairment. In other examples, severe patients can also be classified as group C patients. The relevant judgment principles can refer to the above-mentioned WHO dengue clinical treatment manual.

[0045] The "dengue infection severe group" described herein refers to those determined according to the grouping method of the present invention. Generally speaking, in the field of medical testing, α represents false positive, or the opposite of specificity (also known as specificity); and β represents false negative, or the opposite of sensitivity. When applied, the grouping method of the present invention is to simultaneously detect and cross-compare whether the in vitro biological sample contains NS1 and endogenous anti-NS1 antibodies of the dengue virus, and classify it into the dengue infection severe group when at least one of the first test result and the second test result is positive, thereby effectively reducing the β value (i.e., reducing the "false negative rate"), and then improving the "grouping accuracy" of dengue fever severe patients (i.e., equivalent to increasing the value of "1-β", also referring to the grouping accuracy). In addition, when both the first test result and the second test result are negative results, it is judged that the individual corresponding to the in vitro biological sample is classified as non-dengue infection severe.

[0046] In the above embodiments, the above detection step may include but is not limited to enzyme-linked immunosorbent assay (ELISA), Western blot analysis, lateral flow immunoassay, multiplex immunoassay, radioimmunoassay, immunoradiometric assay, fluorescence immunoassay, chemiluminescence immunoassay and / or immunoturbidimetric assay, etc. In other embodiments, other methods may also be used to detect NS1 and endogenous anti-NS1 antibodies in an ex vivo biological sample.

[0047] It is also noted that the conventional testing process mostly judges the severity of dengue fever patients in order based on a single test result, which is actually unable to effectively reduce the false negative rate of the test results. In some specific examples, compared with the false negative rate of about 10% to 30% in the current testing process, the "dengue infection severe group" of the grouping method of the present invention can indeed reduce the false negative rate of the test results to about 4.5% after diagnosis and confirmation by clinical physicians.

[0048] Several embodiments are used below to illustrate the application of the present invention, but they are not intended to limit the present invention. Those with common knowledge in the technical field of the present invention may make various changes and modifications without departing from the spirit and scope of the present invention.

[0049] Embodiment 1

[0050] 1. Virus strain

[0051] Dengue virus serotype 1 (DENV 1, TW strain 8700828), serotype 2 (DENV 2, strain 16681 and strain 454009A), serotype 3 (DENV 3, TW strain 8700829) and serotype 4 (DENV 4, TW strain 59201818) can be replicated in C6 / 36 cells using conventional culture methods. Virus culture is well known to those with common knowledge in the art to which the present invention belongs and will not be described in detail here. The supernatant after removing the cells is centrifuged using a commercially available centrifuge (e.g. The DENV was concentrated into high-virulence DENV at 6000×g at 4°C and then stored at -70°C for later use.

[0052] 2. Serum Collection

[0053] This example uses 67 dengue fever confirmed patients' sera obtained from National Cheng Kung University Hospital during the outbreak of DENV in 2015, during the acute phase (0-7 days after onset) of the above patients. The above sera are tested for dengue virus infection according to the laboratory standards established by the disease prevention and control authorities in Taiwan, China. According to the latest principles issued by WHO, dengue fever patients can be divided into severe patients, mild patients with warning signs, or mild patients without warning signs, etc. according to the severity. In addition, this example uses sera from 26 healthy volunteers as a negative control group.

[0054] 3. Detection of NS1 and / or NS1 complex

[0055] Regarding the detection of NS1 and / or NS1 complex in the serum of the subject, conventional detection methods may be used or reference may be made to the method disclosed in Taiwan Patent Publication No. TW I624668, which is hereby incorporated by reference.

[0056] This embodiment uses a commercially available kit (such as SD BIOLINE TM Dengue Duo kit, Standarddiagnostic Inc.) and according to the manufacturer's operating manual. Briefly, the observation window of the rapid test displays the control line (marked with "C") and the test line (marked with "T"), wherein the test line contains 1 μL of mouse anti-NS1 monoclonal antibody (model 12100 / 12110, Wei Qiao Biomedical Co., Ltd.) as the capture antibody; the colloidal gold pad of the rapid test contains mouse anti-NS1 monoclonal antibody-colloidal gold and 1 μL of sheep anti-thrombin polyclonal antibody as the detection antibody. Then, 80 μL of serum sample was added to the sample pad of the rapid test for reaction. At the 15th minute of the reaction, the result was read by naked eye, which was equivalent to the first test result.

[0057] 4. Enzyme-linked immunosorbent assay (ELISA)

[0058] When performing indirect ELISA, 50 μl of NS1, bovine serum albumin (BSA), peptides-conjugated BSA or antibody (2 μg / ml, dissolved in PBS, pH 7.3) was applied to a 96-well ELISA culture plate and placed at 4°C overnight. After blocking with PBS containing 1% BSA for 1 hour, antibodies [i.e., humanized antibodies against NS1-WD peptide, humanized antibodies against all serotypes of NS1 (recognizing the 114th to 119th amino acids of NS1), mouse antibodies against NS1-WD peptide (monoclonal antibody strain 33D2, see SCIENTIFIC REPORTs 7:6975, DOI:10.1038 / s41598-017-07308-3, which are hereby incorporated by reference in the present invention), mouse antibodies against all serotypes of NS1 (monoclonal antibody strain 19-5, recognizing the 114th to 119th amino acid residues of NS1, see SCIENTIFIC REPORTs 7:6975, which are hereby incorporated by reference in the present invention)] or patient serum (diluted 1:50) were incubated in each well and reacted at 37°C for 1 hour. The heavy chain variable region CDRs and light chain variable region CDRs of the humanized antibodies against NS1-WD peptide and all serotypes of NS1 are the same as those of the corresponding mouse monoclonal antibody strains, but the remaining sequences are replaced by the sequences of the humanized antibodies. The results of the above detection using the mouse antibody against NS1-WD peptide and the mouse antibody against all serotypes of NS1 are used as comparative examples. Regarding the sequences of the humanized antibodies other than CDRs, those known to those skilled in the art of the present invention can be used, so they are not described in detail. Next, a secondary antibody conjugated to horseradish peroxidase (HRP) anti-human IgG (Jackson ImmunoResearch Laboratories, West Grove, PA) (diluted 1:10,000) was added to each well and reacted at 37°C for another hour. After each well was rinsed with PBST, tetramethylbenzidine (TMB; Clinical Science Products, Mansfield, MA) was used as a substrate for color reaction. Afterwards, a stop solution (2NH2SO4) was added to each well to stop the reaction, and the absorbance was read at OD450nm using a commercially available microplate reader (e.g., VersaMax microplate reader; Molecular Devices, Sunnyvale, CA), which was equivalent to the second detection result.

[0059] 5. Statistical Analysis

[0060] All values ​​were analyzed using Prism software (GraphPad, San Diego, CA). All results were compared using unpaired Student's t-test or one-way ANOVA to compare two or more independent groups, respectively. All values ​​were obtained from three independent experiments and are expressed as mean ± SD. Statistical significance was set by * for p < 0.05, ** for p < 0.01, *** for p < 0.001, and ns for no significant difference at 95% two-tailed confidence interval.

[0061] Embodiment 2

[0062] The optical density (OD) value of the antibody (IgG) against the modified NS1-WD peptide and the OD value of the antibody (IgG) against all serotypes of NS1 in the patient's serum were detected by the method of Example 1, and the OD ratio of the two (NS1-WD IgG / NS1 IgG) was used to evaluate the dengue patients with different severities. The results are as follows: Figure 1 shown.

[0063] See also Figure 1 , which shows the content ratio of anti-modified NS1 flanking domain (NS1-WD) IgG / anti-NS1 IgG in various dengue patient sera according to one embodiment of the present invention, wherein the figure number * represents p<0.05, the figure number ** represents p<0.01, and the figure number *** represents p<0.001.

[0064] like Figure 1 As shown, the ratio of anti-NS1-WD IgG / anti-NS1 IgG in the sera of patients with severe dengue infection (N=17) was significantly lower than that in the sera of patients with dengue fever with warning signs (N=20) or patients with dengue fever without warning signs (N=30). After further analysis, there was no statistically significant difference in the OD values ​​of anti-NS1 IgG among all patients (results not shown), indicating that the detection of antibodies against the NS1-WD peptide does help improve the accuracy of dengue patient grouping.

[0065] See also Figure 2 , which shows the consistency results between the specificity and sensitivity of predicting severe dengue infection according to conventional methods. Figure 2 Conventional methods used included concordance analysis of both specificity and sensitivity based on patient symptoms, medical history, and simple non-specific test results (including results based on a single test or a test that was not specific for anti-NS1-WD IgG).

[0066] Depend on Figure 2 The results showed that the sensitivity of the conventional method (based only on symptoms, medical history and simple non-specific test results) was higher than the specificity, with an area under the curve (AUC) of 0.7036 (confidence interval of 0.60-0.81).

[0067] See also Figure 3 , which is a graph showing the consistency between the specificity and sensitivity of the NS1 antigen in the serum of dengue patients for the prediction of severe dengue infection according to one embodiment of the present invention (equivalent to the first test result). Figure 3 The results showed that the sensitivity of the test method for NS1 antigen in the serum of dengue patients was also higher than the specificity, with an area under the curve (AUC) of 0.8052 (confidence interval of 0.71-0.90).

[0068] See also Figure 4 , which is a graph showing the consistency of the specificity and sensitivity of the ratio of endogenous anti-NS1 antibodies in the serum of dengue patients for the prediction of severe dengue infection according to one embodiment of the present invention (equivalent to the second test result). Figure 4 The results showed that the sensitivity of the test method for endogenous anti-NS1 antibodies in the sera of dengue patients was also higher than the specificity, with an area under the curve (AUC) of 0.7027 (confidence interval of 0.59-0.81).

[0069] Please refer to Table 1, which lists the number of positive or negative results and the results of differential diagnosis confirmation of the simultaneous detection and cross-comparison of the ratio of NS1 antigen and endogenous anti-NS1 antibody in the serum of dengue patients according to one embodiment of the present invention, wherein severe and mild cases are the results of subsequent differential diagnosis confirmation of the subjects according to the dengue clinical treatment manual published by the WHO.

[0070] [Table 1]

[0071]

[0072] According to Table 1, when the ratio of endogenous anti-NS1 antibodies is detected by humanized antibodies and at least one of NS1 and endogenous anti-NS1 antibodies in the serum of dengue patients is detected to be positive, the subject corresponding to the ex vivo biological sample is judged to be classified as a dengue infection severe group. After confirmation by subsequent diagnosis or differential diagnosis, the accuracy of clustering (also referred to as clustering accuracy) for estimating severe dengue fever using the method of the present invention can be as high as 95.5% (i.e. 62 / 65 = 95.5%), which is equivalent to a false negative rate (i.e. β value) reduced to 4.5%. Therefore, the clustering method of the present invention can be used to estimate severe dengue fever patients, and is also helpful as a reference for clinical medical personnel to assess risks and / or formulate treatment strategies.

[0073] In contrast, the false negative rate of dengue patients was high when using mouse antibodies to detect the proportion of endogenous anti-NS1 antibodies. Figure 5 , which is a graph showing the consistency of the specificity and sensitivity of the ratio of endogenous anti-NS1 antibodies in the serum of dengue patients detected by mouse antibodies in the comparative example for the prediction of severe dengue infection (equivalent to the second test result). Figure 5 The results showed that the sensitivity (72.97%) of the test method for detecting endogenous anti-NS1 antibodies in the serum of dengue patients using mouse antibodies was lower than the specificity (83.33%), and the area under the curve (AUC) was 0.7739 (confidence interval was 0.6557-0.8921).

[0074] Please refer to Table 2, which lists the number of positive or negative endogenous anti-NS1 antibody ratios in the serum of dengue patients detected by mouse antibodies in the comparative example and the results of differential diagnosis confirmation, wherein severe and mild cases are the results of subsequent differential diagnosis confirmation of the subjects according to the dengue clinical treatment manual published by the WHO.

[0075] [Table 2]

[0076]

[0077] As can be seen from Table 2, when the endogenous anti-NS1 antibody in the serum of dengue patients detected by mouse antibodies in the comparative example was positive, the subject corresponding to the in vitro biological sample was judged to be classified as a severe dengue infection group. After confirmation by subsequent diagnosis or differential diagnosis, the estimated clustering accuracy of severe dengue fever (also referred to as clustering accuracy) was only 72.9% (i.e. 27 / 37 = 72.9%), and the false negative rate of clustering was as high as 27.1% (i.e. 10 / 37 = 27.1%), which was indeed much higher than the false negative rate (4.5%) of the clustering method of the present invention.

[0078] In summary, the above-mentioned specific antigens, specific antibodies, specific patient groups, specific analysis modes or specific evaluation methods are only used to illustrate the grouping method for improving the accuracy of prediction of severe dengue infection. However, those with common knowledge in the technical field to which the present invention belongs should understand that without departing from the spirit and scope of the present invention, other antigens, other antibodies, other patient groups, other analysis modes or other evaluation methods can also be used to improve the accuracy of prediction of severe dengue infection. The method of grouping is not limited to the above. For example, without affecting the accuracy of grouping, the first test result can use other methods to detect NS1 and / or NS1 complex, or the second test result can use other methods to detect endogenous anti-NS1 antibodies.

[0079] It can be seen from the above embodiments that the clustering method for improving the accuracy of prediction of severe dengue infection of the present invention simultaneously detects and cross-compares whether the in vitro biological sample contains NS1 of the dengue virus and endogenous anti-NS1 antibodies, which can effectively reduce the false negative rate of the test results and improve the accuracy of clustering of severe dengue patients.

[0080] Although the present invention has been disclosed as above with several specific embodiments, various modifications, changes and substitutions may be made to the aforementioned disclosure, and it should be understood that in some cases, certain features of the embodiments of the present invention will be adopted but other features will not be used accordingly without departing from the spirit and scope of the present invention. Therefore, the spirit and scope of the claims of the present invention should not be limited to the above exemplary embodiments.

Claims

1. Use of a specific antibody and a humanized antibody in the preparation of a detection reagent for improving the accuracy of prediction of severe dengue infection individuals, characterized in that: The detection reagent is used to detect an in vitro biological sample, wherein the in vitro biological sample has not been diagnosed or differentially diagnosed as a dengue virus infection or a suspected dengue virus infection, and comprises: The ex vivo biological sample is subjected to a plurality of detection steps to obtain a first detection result and a second detection result, wherein the ex vivo biological sample is tested for the presence of NS1 and / or NS1 complex of dengue virus by using a specific antibody that recognizes NS1 and / or NS1 complex, wherein the specific antibody is an exogenous anti-NS1 antibody, and the NS1 complex comprises NS1-thrombin or NS1-prothrombin; Detecting whether endogenous anti-NS1 antibodies are present in an ex vivo biological sample by using a humanized antibody that recognizes endogenous anti-NS1 antibodies in the ex vivo biological sample, wherein the endogenous anti-NS1 antibodies comprise a first antibody and a second antibody, wherein the first antibody specifically recognizes the 109th to 122th amino acid residues of the NS1, and the second antibody specifically recognizes the 114th to 119th amino acid residues of the NS1, and the second detection result refers to the content ratio of the first antibody to the second antibody; and The first test result and the second test result are cross-compared to obtain a grouping result, wherein the multiple testing steps and the cross-comparison are performed simultaneously, and when at least one of the first test result and the second test result is positive, it is determined that an individual corresponding to the ex vivo biological sample is classified into a dengue infection severe group.

2. The use according to claim 1, characterized in that: The in vitro biological sample includes blood, urine, saliva, tissue fluid and / or lymph fluid.

3. The use according to claim 1, characterized in that: The dengue virus serotype includes type 1, type 2, type 3 and type 4.

4. The use according to claim 1, characterized in that: One type of the endogenous anti-NS1 antibody is IgG and / or IgM.

5. The use according to claim 1, characterized in that: The individual is a mammal.

6. The use according to claim 1, characterized in that: Wherein the individual is a human being.

7. The use according to claim 1, characterized in that: When both the first test result and the second test result are negative results, it is determined that the individual corresponding to the ex vivo biological sample is classified as a non-dengue infection severe disease.

8. The use according to claim 1, characterized in that: The at least one detection step comprises enzyme-linked immunosorbent assay, Western blot analysis, lateral flow immunoassay, multiplex immunoassay, radioimmunoassay, immunoradiometric assay, fluorescent immunoassay, chemiluminescent immunoassay and / or immunoturbidimetric assay.

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