Urine protein markers for differential diagnosis of acute myocarditis and acute myocardial infarction and application thereof

Abstract

The application relates to urine protein markers for differential diagnosis of acute myocarditis and acute myocardial infarction and application thereof, the protein markers including one or more of tumor necrosis factor receptor superfamily member 1A, blood coagulation factor IX and peroxidase 3. The three markers have strong differential diagnosis ability to patients with acute myocarditis and acute myocardial infarction, thereby providing a new noninvasive differential diagnosis method for the two diseases.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of medical diagnostic reagents, and specifically relates to a urine protein marker for differential diagnosis of acute myocarditis and acute myocardial infarction and application thereof. BACKGROUND

[0002] Acute myocarditis and acute myocardial infarction are two cardiovascular emergencies with different pathological mechanisms but highly overlapping clinical manifestations. Acute myocarditis is characterized by myocardial inflammation, often triggered by viral infection, autoimmune response or physical and chemical factors, and is an acquired myocardial inflammatory disease with high disability and mortality. According to the Global Burden of Disease Study in 2021, the age-standardized incidence of myocarditis worldwide in 2021 was 16.16 / 100,000, and the age-standardized mortality was 0.40 / 100,000. Acute myocardial infarction is caused by significant restriction or interruption of coronary blood flow, leading to myocardial ischemic necrosis. In 2019, the number of deaths caused by global ischemic cardiomyopathy reached 9.14 million, and the number of patients reached 197 million. Both can present with paroxysmal chest pain, ECG ST-T changes, and elevated myocardial enzyme spectrum. However, their treatment strategies are completely different: acute myocardial infarction requires emergency revascularization, while acute myocarditis mainly relies on anti-inflammatory and circulatory support therapy. Misdiagnosis of acute myocardial infarction as acute myocarditis may delay the best treatment time window, causing irreversible myocardial damage or even death; misdiagnosis of acute myocarditis as acute myocardial infarction may lead to adverse outcomes due to over-treatment or delayed anti-inflammatory and supportive therapy. Therefore, rapid and accurate differential diagnosis of acute myocarditis and acute myocardial infarction is crucial.

[0003] However, there are still difficulties in the differential diagnosis of the two. First, the specificity of existing biomarkers is insufficient: although cardiac troponin is a sensitive indicator of myocardial damage, it can be elevated in both acute myocarditis and acute myocardial infarction, and cannot distinguish between the two diagnoses. Other markers such as creatine kinase isoenzyme and B-type natriuretic peptide also have similar problems, and joint detection still cannot achieve etiological differentiation. Second, there are limitations in imaging techniques: the diagnosis of acute myocardial infarction relies on coronary angiography, which requires radiation exposure, and some acute myocardial infarction patients have only mild lesions or even normal coronary angiography. Even if coronary angiography is completed, it still cannot provide a definitive diagnosis; enhanced cardiac magnetic resonance imaging can assess myocardial edema and fibrosis through T1 / T2 mapping imaging and delayed gadolinium enhancement sequences, thus serving as evidence for clinical diagnosis of myocarditis. However, this technology has low popularity in primary hospitals and is expensive. Cardiac magnetic resonance imaging takes a long time, usually 30 to 90 minutes, and patients need to remain still for a long time. Many critically ill patients with acute chest pain do not have the conditions to complete this examination. Third, limitations of the gold standard: endomyocardial biopsy is the gold standard for the diagnosis of acute myocarditis, but its invasiveness, complexity of operation and risk of complications (such as perforation and arrhythmia) make it only available in a few experienced medical centers.

[0004] Recent research has focused on mining higher specificity, non-invasive, rapid new biomarkers as a diagnostic tool to break through the existing diagnostic bottleneck. The study published in the New England Journal of Medicine titled "New Circulating MicroRNAs for Detection of Acute Myocarditis" found that detecting hsa-miR-Chr8:96 in plasma can distinguish between acute myocarditis patients and acute myocardial infarction patients. But blood testing is still an invasive procedure. SUMMARY

[0005] Based on this, an embodiment of the present application provides the use of a urine protein marker for differential diagnosis of acute myocarditis and acute myocardial infarction and a detection reagent thereof in the preparation of a product for differential diagnosis of acute myocarditis and acute myocardial infarction.

[0006] The technical solution is as follows:

[0007] The urine protein marker for differential diagnosis of acute myocarditis and acute myocardial infarction includes one or more of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxiredoxin 3.

[0008] In one embodiment, the expression levels of tumor necrosis factor receptor superfamily member 1A and coagulation factor IX are reduced in acute myocarditis patients compared to acute myocardial infarction patients, and the expression level of peroxiredoxin 3 is increased.

[0009] In one embodiment, the use of the above-mentioned urine protein marker expression level detection reagent in the preparation of a product for differential diagnosis of acute myocarditis and acute myocardial infarction.

[0010] In one embodiment, the sample to be detected is urine.

[0011] In one embodiment, the detection reagent is selected from the reagents used in the following methods: mass spectrometry method, immunoassay method, western blot analysis, radioimmunoassay method, immunofluorescence method, immunoprecipitation, equilibrium dialysis, immunodiffusion, electrochemiluminescence immunoassay, ELISA assay, and / or immunopolymerase chain reaction.

[0012] In one embodiment, the mass spectrometry detection method is LC-MS / MS.

[0013] In one embodiment, a mass spectrometry detection method based on protein characteristic tag peptides is used.

[0014] In one embodiment, the ELISA assay is a double antibody sandwich ELISA assay.

[0015] In one embodiment, the immunoassay comprises electrochemiluminescence, chemiluminescence, fluorescent chemiluminescence, or fluorescence polarization and time.

[0016] In one embodiment, the detection reagent comprises an antibody or an antibody functional fragment.

[0017] In one embodiment, the product comprises a kit, a chip, a test strip, a system, or a device.

[0018] In one embodiment, the kit is a mass spectrometry identification tag peptide or an enzyme-linked immunosorbent assay kit.

[0019] In one embodiment, the mass spectrometry identification tag peptide is used in a data-independent mass spectrometry acquisition mode.

[0020] In one embodiment, the enzyme-linked immunosorbent assay kit uses a double antibody sandwich enzyme-linked immunosorbent assay for protein identification.

[0021] The product for differential diagnosis of acute myocarditis and acute myocardial infarction comprises a detection reagent for the expression level of the urine protein marker defined above.

[0022] The system for differential diagnosis of acute myocarditis and acute myocardial infarction comprises:

[0023] A detection module for detecting the content of the urine protein marker in the sample to be tested;

[0024] An input module for inputting sample data to be tested, the sample data to be tested comprising the content of the urine protein marker;

[0025] An analysis module for analyzing whether it is acute myocarditis or acute myocardial infarction by the sample data to be tested;

[0026] An output module for outputting the analysis result of the analysis module.

[0027] In one embodiment, the analysis module uses a logistic regression algorithm to model and analyze whether it is acute myocarditis or acute myocardial infarction.

[0028] It should be noted that in addition to the logistic regression algorithm, other machine learning algorithms can also be used for modeling, such as linear regression algorithm, support vector machine algorithm, nearest neighbor / k-nearest neighbor algorithm, decision tree algorithm, k-means algorithm, random forest algorithm, naive Bayes algorithm, dimensionality reduction algorithm, gradient boosting algorithm, as long as the system using the content or expression level of the urine protein marker detected by the present application to construct the model is within the protection scope of the present application.

[0029] In one embodiment, the model adopts the following formula:

[0030] logit(p) = -0.6278 - 2.1160 x PRDX3 + 1.4732 x F9 + 1.4193 x TNFRSF1A; or logit(p) = 3.650565 - 0.058221 x PRDX3 + 0.101719 x F9 + 0.008661 x TNFRSF1A.

[0031] wherein PRDX3, F9 and TNFRSF1A represent the expression amount (i.e. expression level or content) of the corresponding protein.

[0032] In one embodiment, the model outputs a probability p, and when p≥0.5, it is determined as acute myocardial infarction; and when p<0.5, it is determined as acute myocarditis.

[0033] In one embodiment, the analysis module includes analyzing whether the test sample is acute myocarditis or acute myocardial infarction by comparing with a control sample. The control sample is a sample from an acute myocardial infarction patient or an acute myocarditis patient.

[0034] In one embodiment, when compared with the sample from an acute myocardial infarction patient, the expression amount of TNFRSF1A and F9 in the test sample is significantly reduced, and the expression amount of PRDX3 is significantly increased, it is analyzed that the test sample is an acute myocarditis patient.

[0035] In one embodiment, the test sample includes a patient who is clinically suspected to have acute myocarditis or acute myocardial infarction and visits an emergency department with chest pain as the chief complaint.

[0036] A computer readable storage medium, the computer readable storage medium comprising a computer program, the computer program being executed by a processor, and the computer program being executed by the processor to realize the functions of different modules in the system.

[0037] An apparatus comprising the computer readable storage medium, and a processor for executing the program and realizing the functions of the system.

[0038] In this application, the device is a method for distinguishing different levels of different components, elements, parts, or assemblies. However, if other words can achieve the same purpose, the words can be replaced by other expressions. Those skilled in the art of the technical field to which the application belongs are familiar that the application can be implemented as a device, a method, or a computer program product. Therefore, the content disclosed in the application can be specifically implemented in the form of a complete hardware, a complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. In addition, in some specific embodiments, the application can also be implemented in the form of a computer program product in one or more computer readable media, which contains computer readable program code.

[0039] A method for differentiating acute myocarditis and acute myocardial infarction, the method comprising the steps of:

[0040] (1) detecting the expression level of the above-mentioned urine protein marker in a sample derived from a subject;

[0041] (2) diagnosing whether the subject has acute myocarditis or acute myocardial infarction according to the expression level of the detected urine protein marker.

[0042] In this application, the subject refers to any animal, also refers to human and non-human animals. Non-human animals include all vertebrates, for example, mammals, such as non-human primates (especially higher primates), sheep, dogs, rodents (e.g., mice or rats), guinea pigs, goats, pigs, cats, rabbits, cows, and any livestock or pets; and non-mammals, such as chickens, amphibians, reptiles, etc. In a preferred embodiment, the subject is a human.

[0043] Compared with the prior art, the application has the following beneficial effects:

[0044] The expression levels of peroxiredoxin 3, tumor necrosis factor receptor superfamily member 1A and coagulation factor IX in urine are detected by a mass spectrometry detection method based on protein characteristic signature peptides. The expression levels of the three markers have strong differential diagnosis ability for patients with acute myocarditis and acute myocardial infarction, thereby providing a new non-invasive differential diagnosis method for the two diseases. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the application, more completely understand the application and its beneficial effects, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and those skilled in the art can obtain other drawings according to these drawings without any creative effort.

[0046] Figure 1 PCA plot of urine proteome for distinguishing patients with acute myocarditis and acute myocardial infarction in data-independent acquisition mode, urine proteome of healthy people as control; red represents healthy control group, green represents acute myocardial infarction group, purple represents acute myocarditis group; three groups show intra-group aggregation and inter-group separation.

[0047] Figure 2 Content changes of tumor necrosis factor receptor superfamily member 1A, blood coagulation factor IX and peroxidase 3 in patient urine detected by mass spectrometry in data-independent acquisition mode; (*P<0.05, **P<0.01, ***P<0.001).

[0048] Figure 3 ROC curves of urine protein markers tumor necrosis factor receptor superfamily member 1A, blood coagulation factor IX and peroxidase 3 respectively and in combination for identifying patients with acute myocarditis and acute myocardial infarction in the training set detected by mass spectrometry.

[0049] Figure 4 ROC curves of urine protein markers tumor necrosis factor receptor superfamily member 1A, blood coagulation factor IX and peroxidase 3 respectively and in combination for identifying patients with acute myocarditis and acute myocardial infarction in the validation set detected by mass spectrometry.

[0050] Figure 5 Content changes of tumor necrosis factor receptor superfamily member 1A, blood coagulation factor IX and peroxidase 3 in patient urine detected by ELISA; (*P<0.05, **P<0.01, ***P<0.001).

[0051] Figure 6 ROC curves of urine tumor necrosis factor receptor superfamily member 1A, blood coagulation factor IX and peroxidase 3 respectively and in combination for identifying acute myocarditis and acute myocardial infarction detected by ELISA method. DETAILED DESCRIPTION

[0052] In order to make the above purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below. In the following description, a large number of specific details are set forth in order to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the spirit of the present application, therefore the present application is not limited by the specific embodiments disclosed below.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application.

[0054] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0055] The present application relates to three biomarkers in urine: tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxiredoxin 3. Tumor necrosis factor receptor superfamily member 1A (English name: Tumor necrosis factor receptor superfamily member 1A, English abbreviation: TNFRSF1A or TNF-R1, ID in UniProt database: P19438) is one of the main receptors of tumor necrosis factor-α. Coagulation factor IX (English name: Coagulation Factor IX, English abbreviation: Factor IX or F9, ID in UniProt database: P07360) is a core component of the coagulation cascade, existing in an inactive zymogen form, and is a vitamin K-dependent coagulation factor involved in the intrinsic coagulation pathway. The serum level of its activated form, coagulation factor IXa, can predict acute myocardial infarction events in patients with coronary heart disease. Peroxiredoxin 3 (English name: Peroxiredoxin 3, English abbreviation: PRDX3, ID in UniProt database: Q16881) is an important member of the peroxiredoxin family, mainly localized in mitochondria, and is a key antioxidant enzyme in cells, responsible for removing reactive oxygen species (ROS such as H2O2) produced in mitochondria, maintaining redox homeostasis.

[0056] Whether the contents of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxiredoxin 3 in urine can be used to differentiate acute myocarditis and acute myocardial infarction has not been reported or applied. If the combination of the three urine proteins can differentiate acute myocarditis and acute myocardial infarction at the first visit of acute chest pain, it will undoubtedly bring great convenience to the early diagnosis of these two diseases.

[0057] In view of the fact that there is no economical and non-invasive biomarker for differential diagnosis of acute myocarditis and acute myocardial infarction at present, based on the quantitative proteomics method of mass spectrometry, a group of new protein markers that can better distinguish the two types of patients is found in the urine of patients with acute myocarditis and acute myocardial infarction in emergency department, including tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxidase 3. The application studies the combination of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxidase 3 in urine as a biomarker for differential diagnosis of acute myocarditis and acute myocardial infarction, and provides a new method for identifying the two types of patients.

[0058] It should be noted that the differential diagnosis refers to the identification of patients with acute myocarditis and acute myocardial infarction.

[0059] The urine sample of the subject is obtained when the subject first visits the emergency department due to chest pain, and the urine protein is enriched, proteolysis is performed, a library is constructed, and the sample is analyzed by 1D-LC-MS / MS. The data-independent detection results show that tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxidase 3 are significantly different proteins.

[0060] Mass spectrometric quantitative detection of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxidase 3 in urine shows that compared with patients with acute myocardial infarction, the expression levels of tumor necrosis factor receptor superfamily member 1A and coagulation factor IX in patients with acute myocarditis are significantly reduced, while the expression level of peroxidase 3 is significantly increased. The AUC value of the combination of the three proteins in the differential diagnosis of acute myocarditis and acute myocardial infarction is between 0.9-1.0, showing strong differential diagnostic ability.

[0061] The above results show that the combination of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxidase 3 in the urine of patients can be used for the identification of acute myocarditis and acute myocardial infarction, and can be made into reagents or chips for differential diagnosis.

[0062] It should be noted that the above mass spectrometric quantitative detection is based on mass spectrometric detection of protein characteristic signature peptides. Signature peptides refer to peptides that can represent a certain protein and exist only in the amino acid sequence of a certain protein.

[0063] The expression levels of peroxidase 3, tumor necrosis factor receptor superfamily member 1A and coagulation factor IX in urine are detected by mass spectrometric detection method based on protein characteristic signature peptides. The baseline range of the three proteins in healthy population is established by the expression levels of the three markers combined with standard products, and the two diseases are compared by content range comparison, so as to provide a new non-invasive differential diagnosis method for the two diseases.

[0064] The embodiments of the present application will be described in detail below with examples. It should be understood that these examples are only used to illustrate the present application and not to limit the scope of the present application. The experimental methods in the following examples without specific conditions are preferred to refer to the guidance given in the present application, but also can be carried out according to the experimental manual or conventional conditions in the art, or according to the conditions suggested by the manufacturer, or according to the experimental methods known in the art.

[0065] In the following specific examples, the measurement parameters of the raw material components may have slight deviations within the weighing accuracy range if not specifically stated. For temperature and time parameters, acceptable deviations caused by instrument testing accuracy or operation accuracy are allowed.

[0066] Example 1 Urine protein detection for differential diagnosis of acute myocarditis and acute myocardial infarction

[0067] Materials and reagents:

[0068] 1) Instrument: Orbitrap Exploris 480 mass spectrometer (Thermo Scientific).

[0069] 2) Main reagents: Trypsin (Promega); C18 solid phase extraction column (3CC, 60 mg, Waters); C18 reversed-phase chromatographic column (4.6 mm x 250 mm, C18, 3 μm, Waters).

[0070] 3) Samples: Urine of 42 patients with acute myocarditis, 80 patients with myocardial infarction (40 patients with acute ST segment elevation myocardial infarction, 40 patients with acute non-ST segment elevation myocardial infarction) and 41 normal control subjects, from Peking Union Medical College Hospital.

[0071] We used data-independent acquisition (DIA) to screen relevant proteins in urine for differential diagnosis of acute myocarditis and acute myocardial infarction.

[0072] 1. Collection of human urine samples and enrichment of urine proteins

[0073] Urine was collected at the first visit. After centrifugation (3000 x g, 10 min) to remove cell debris, the supernatant was taken for subsequent detection.

[0074] 2. Proteolysis

[0075] Proteolysis was performed using in-solution digestion. The supernatant was alkylated using 20 mM DTT (95 °C, 10 min) and 50 mM iodoacetamide (incubation in the dark, 45 min). Proteins were precipitated using six volumes of pre-chilled acetone (-20 °C, 30 min), the pellet was collected by centrifugation (14000 x g, 10 min, 4 °C) and dissolved in 25 mM ammonium bicarbonate buffer. Prior to use, the 30 kDa molecular weight ultrafiltration device was pre-conditioned by flushing three times with 25 mM ammonium bicarbonate buffer (14000 x g centrifugation for 3 min, 4 °C). The protein solution was loaded into the pre-conditioned ultrafiltration device and concentrated by centrifugation at 14000 x g for 10 min at 4 °C. Buffer exchange was achieved by three cycles of dilution-concentration with fresh ammonium bicarbonate buffer. Trypsin digestion (enzyme to protein ratio 1 :50) was performed overnight at 37 °C, followed by collection of the peptide solution by centrifugal filtration (14000 x g).

[0076] 3. Library construction

[0077] To construct the spectral library, all urine samples (disease and control groups) were mixed equally. Offline high-pH high-performance liquid chromatography separation was performed, and the collected eluate was placed in a rotary vacuum dryer. After vacuum drying, it was re-dissolved in 1‰ formic acid for LC-MS / MS analysis. The raw data of each component sample were collected using a non-dependent acquisition (Data-Independent Acquisition, DIA) method. The raw data collected were processed using Spectronaut Pulsar 19.0 software (Biognosys) according to the default parameters. The analysis process was as follows: after importing the DIA file into Spectronaut Pulsar, database searching was performed against the Swiss-Prot human proteome database (Homo sapiens, 2019_05 version, containing 20,358 protein entries) with the following search parameters: trypsin digestion (allowing up to 2 missed cleavage sites), cysteine carbamidomethylation as a fixed modification, and methionine oxidation, lysine deamidation, and lysine carbamidation (+43 Da) as variable modifications; then the dynamic iRT retention time prediction algorithm was enabled, and MS1 level interference correction was turned on. The peptide intensity was calculated by accumulating the corresponding MS1 fragment ion peak area, and the protein intensity was obtained from the total intensity of the peptides it belonged to. Finally, the built-in IDPicker algorithm was used for protein inference, and all identification results were filtered with a threshold of q value ≤ 0.01 (corresponding to 1% false discovery rate FDR).

[0078] 4. DIA analysis of experimental data:

[0079] 163 samples were analyzed by 1D-LC-MS / MS. Each sample was acquired by DIA. The data acquired by DIA were processed by Spectronaut software. The data results were exported.

[0080] Differential expression analysis (Fold change >1.5 or <0.68, FDR adjusted P value <0.05) identified 806 differentially expressed proteins (366 up-regulated and 438 down-regulated) in the acute myocarditis group and 1098 differentially expressed proteins (557 up-regulated and 538 down-regulated) in the acute myocardial infarction group. Figure 1 PCA plot of urine proteome for distinguishing acute myocarditis and acute myocardial infarction patients in data-independent acquisition mode.

[0081] The screening criteria of candidate biomarkers included: (1) significantly up-regulated in acute myocarditis or acute myocardial infarction compared with healthy controls; (2) significantly differentially expressed between acute myocarditis and acute myocardial infarction Figure 2 ).

[0082] After preliminary screening of proteins according to the above criteria, all patients (42 cases of acute myocarditis and 80 cases of acute myocardial infarction) were randomly divided into training set (31 cases of acute myocarditis and 60 cases of acute myocardial infarction, a total of 91 cases) and validation set (11 cases of acute myocarditis and 20 cases of acute myocardial infarction, a total of 31 cases) in a ratio of 3:1 (age and gender stratification).

[0083] In the training set, LASSO regression algorithm was used for feature selection, and the optimal λ value was determined to be 0.0432, and a total of 25 variables with predictive value were screened out. Based on the LASSO coefficients, ROC analysis results and the biological mechanism of proteins in cardiovascular diseases, TNFRSF1A, F9 and PRDX3 were finally determined as core markers.

[0084] The above three differential proteins were combined to build a diagnostic model, and a logistic regression was used to construct a diagnostic model to generate a diagnostic score logit(p) for determining the disease type of the urine sample. In the training set, the logistic regression equation of the combined diagnostic model constructed was as follows:

[0085] logit(p) = -0.6278 - 2.1160 x PRDX3 + 1.4732 x F9 + 1.4193 x TNFRSF1A

[0086] Wherein, PRDX3, F9, TNFRSF1A represent the content of each marker (e.g. unit: relative intensity) respectively. The model output probability p, when p≥0.5 is judged as acute myocardial infarction (AMI); when p<0.5 is judged as acute myocarditis (AM).

[0087] In the training set, the AUC value of the joint model reached 0.945 (95% CI: 0.895-0.995), with a sensitivity of 0.95, a specificity of 0.87, a positive predictive value (PPV) of 0.93, and a negative predictive value (NPV) of 0.90. Figure 3 ) In the validation set, the above-mentioned joint diagnostic model also showed good discrimination ability, with an AUC of 0.905 (95% CI: 0.79-1) Figure 4 ).

[0088] In addition, in the training set and the validation set, the ROC curves of TNFRSF1A, F9, PRDX3 in distinguishing acute myocardial infarction and acute myocarditis Figures 3-4 ) showed good discrimination ability.

[0089] Example 2 ELISA detection of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX and peroxiredoxin 3 in urine

[0090] Materials and reagents:

[0091] 1) Main reagents: TNFRSF1A protein ELISA kit (Rui Xin Bio, Quanzhou, China), coagulation factor IX ELISA kit (Rui Xin Bio, Quanzhou, China), peroxiredoxin 3 ELISA kit (Rui Xin Bio, Quanzhou, China).

[0092] 2) Samples: Urine of 28 patients with acute myocarditis, 52 patients with acute myocardial infarction (26 patients with acute ST segment elevation myocardial infarction, 26 patients with acute non-ST segment elevation myocardial infarction) and 30 normal control subjects, from Peking Union Medical College Hospital.

[0093] 1. Collection of human urine samples and enrichment of urine proteins

[0094] Collect urine at the first visit, remove cell debris by centrifugation (3000xg, 10 minutes), and take the supernatant for subsequent detection.

[0095] 2. Enzyme-linked immunosorbent assay

[0096] Set standard holes, 0 value holes, blank holes and sample holes, standard holes add different concentrations of standard 50 μL, 0 value holes add sample diluent 50 μL, blank holes do not add, sample holes add 50 μL of sample to be tested. Except for the blank hole, add 100 μL of horseradish peroxidase (HRP) labeled detection antibody to the standard hole, 0 value hole and sample hole. Cover the reaction plate with a sealing film, incubate in a 37°C water bath or incubator for 60 min in the dark. Wash the plate 5 times with an automatic plate washer, and dry the reaction plate thoroughly. Mix substrate A and B at a ratio of 1:1 by volume, and add 100 μL of the substrate mixture to all wells. Cover the reaction plate with a sealing film, incubate in a 37°C water bath or incubator for 15 min in the dark. Add 50 μL of stop solution to all wells, and read the absorbance (OD value) of each well on an enzyme label instrument.

[0097] 3. Data processing

[0098] Take the standard concentration as the abscissa (6 standard holes, add 1 0 value hole, a total of 7 concentration points), and the corresponding absorbance (OD value) as the ordinate. Use computer software to create a standard curve equation by fitting a four-parameter Logistic curve. Calculate the concentration value of the sample using the equation based on the absorbance (OD value) of the sample.

[0099] Compared with acute myocardial infarction patients, the expression levels of TNFRSF1A and F9 in the urine of acute myocarditis patients were significantly reduced, while the expression level of PRDX3 was significantly increased. Figure 5 Further ROC analysis was performed to determine the ability of the three proteins to distinguish between acute myocarditis and acute myocardial infarction groups. The combination of the above three proteins was used to predict the following logistic regression model:

[0100] logit(p) = 3.650565 - 0.058221 x PRDX3 + 0.101719 x F9 + 0.008661 x TNFRSF1A

[0101] Where PRDX3, F9, and TNFRSF1A represent the content of each marker (e.g., pg / mL).

[0102] In this external validation population, it showed excellent diagnostic performance (AUC = 0.96, 95% CI: 0.923-0.998) Figure 6 In addition, the ROC curves of TNFRSF1A, F9, and PRDX3 in distinguishing acute myocardial infarction and acute myocarditis Figure 6 showed good discrimination ability.

[0103] Any combination of the technical features in the above-described embodiments can be made, and for the sake of brevity, not all possible combinations are described, however, it is to be understood that the application encompasses all such possible combinations.

[0104] The above-described embodiments only express several implementation manners of the application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the patent scope of the application. It should be pointed out that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the application, and these all belong to the protection scope of the application. Therefore, the patent protection scope of the application should be subject to the appended claims, and the description can be used to explain the content of the claims.

Claims

1. The application of a reagent for detecting the expression level of urinary protein markers in the preparation of products for the differential diagnosis of acute myocarditis and acute myocardial infarction, wherein the urinary protein markers include one or more of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3.

2. The application according to claim 1, characterized in that, The sample tested was urine.

3. The application according to claim 1 or 2, characterized in that, The detection reagents are selected from those used in the following methods: mass spectrometry, Western blot analysis, radioimmunoassay, immunofluorescence assay, immunoprecipitation, balanced dialysis, immunodiffusion, electrochemiluminescence immunoassay, ELISA, or immunopolymerase chain reaction.

4. The application according to claim 1 or 2, characterized in that, The detection reagent is the same reagent used in immunoassay.

5. The application according to claim 3, characterized in that, The mass spectrometry detection method is LC-MS / MS.

6. The application according to claim 3, characterized in that, The ELISA assay is a double-antibody sandwich ELISA assay.

7. The application according to claim 3, characterized in that, The detection reagent includes antibodies or antibody functional fragments.

8. The application according to claim 1 or 2, characterized in that, The products include reagent kits, chips, test strips, or systems.

9. The application according to claim 1 or 2, characterized in that, The product includes a device.

10. The application according to claim 8, characterized in that, The kit is a mass spectrometry identification kit for tagged peptides or an enzyme-linked immunosorbent assay kit.

11. A system for the differential diagnosis of acute myocarditis and acute myocardial infarction, characterized in that, include: The detection module is used to detect the content of urinary protein markers in the sample to be tested, wherein the urinary protein markers include one or more of the following: tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3; The input module is used to input the data of the sample to be tested, including the content of urine protein markers; The analysis module is used to analyze the data from the sample to determine whether the result is acute myocarditis or acute myocardial infarction; and, The output module is used to output the analysis results from the analysis module.

12. The system according to claim 11, characterized in that, The system has one or more of the following characteristics: (1) The analysis module uses logistic regression algorithm to model and analyze whether it is acute myocarditis or acute myocardial infarction; (2) The analysis module includes comparing with the control sample to determine whether the sample to be tested is acute myocarditis or acute myocardial infarction.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a computer program that is executed by a processor, and when executed by the processor, the computer program performs the functions of different modules in the system of claim 11 or 12.

14. An apparatus, characterized in that, It includes the computer-readable storage medium of claim 13, and a processor for executing programs and implementing the functions of the system.

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