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

Abstract

The invention relates to a urine protein marker for differential diagnosis of acute myocarditis and acute myocardial infarction and application of the urine protein marker. The protein marker comprises one or more of a tumor necrosis factor receptor superfamily member 1A, a blood coagulation factor IX and peroxidoreductase 3. The expression levels of the three markers have relatively strong differential diagnosis capability on patients with acute myocarditis and acute myocardial infarction, so that a novel non-invasive differential diagnosis method for the two diseases is provided.

Description

Technical Field

[0001] This application belongs to the field of medical diagnostic reagent technology, specifically relating to urinary protein markers for the differential diagnosis of acute myocarditis and acute myocardial infarction and their applications. Background Technology

[0002] Acute myocarditis and acute myocardial infarction are two cardiovascular emergencies with vastly different pathological mechanisms but highly overlapping clinical manifestations. Acute myocarditis is characterized by inflammation of the myocardial tissue and is often triggered by viral infection, autoimmune reactions, or physical and chemical factors. It is an acquired inflammatory disease of the myocardium with high rates of disability and mortality. According to the 2021 Global Burden of Disease Study, the age-standardized incidence rate of myocarditis worldwide in 2021 was 16.16 per 100,000, and the age-standardized mortality rate was 0.40 per 100,000. Acute myocardial infarction, on the other hand, is myocardial ischemia and necrosis caused by significant restriction or interruption of coronary artery blood flow. In 2019, ischemic cardiomyopathy caused 9.14 million deaths and affected 197 million people worldwide. Both can present with paroxysmal chest pain, ST-T changes on electrocardiogram, and elevated myocardial enzyme levels. However, their treatment strategies are drastically different: acute myocardial infarction requires emergency revascularization, while acute myocarditis is mainly treated with anti-inflammatory and circulatory support therapies. Misdiagnosing acute myocardial infarction as acute myocarditis can delay the optimal treatment window, leading to irreversible myocardial damage or even death. Conversely, misdiagnosing acute myocarditis as acute myocardial infarction can result in adverse outcomes due to overtreatment or delays in anti-inflammatory and supportive care. Therefore, rapid and accurate differential diagnosis between acute myocarditis and acute myocardial infarction is crucial.

[0003] However, differentiating between the two remains challenging. First, existing biomarkers lack specificity: while cardiac troponin is a sensitive indicator of myocardial injury, it can be elevated in both acute myocarditis and acute myocardial infarction, making it impossible to distinguish between the two diagnoses. Other biomarkers, such as creatine kinase isoenzymes and B-type natriuretic peptide, present similar problems, and combined detection still struggles to differentiate the cause. Second, imaging techniques have limitations: a definitive diagnosis of acute myocardial infarction relies on coronary angiography, which requires radiation exposure, and in some patients, coronary angiography only shows mild lesions or even normal findings, making a definitive diagnosis impossible even after completion. While contrast-enhanced cardiac magnetic resonance imaging (MRI) can assess myocardial edema and fibrosis through T1 / T2 mapping and delayed gadolinium enhancement sequences, thus serving as evidence for clinical diagnosis of myocarditis, this technology has low availability and high cost in primary care hospitals. Furthermore, cardiac MRI is time-consuming, typically requiring 30 to 90 minutes, necessitating prolonged rest for the patient, making it unsuitable for many critically ill patients with acute chest pain. Secondly, the limitations of implementing the gold standard: Endocardial biopsy is the gold standard for the diagnosis of acute myocarditis, but its invasiveness, procedural complexity, and risk of complications (such as perforation and arrhythmia) mean that it can only be performed in a few experienced medical centers.

[0004] Recent research has focused on discovering novel biomarkers with higher specificity, non-invasiveness, and speed as diagnostic tools to overcome existing diagnostic bottlenecks. A study published in the *New England Journal of Medicine*, titled "Novel circulating microRNAs for detecting acute myocarditis," found that detecting hsa-miR-Chr8:96 in plasma can differentiate between patients with acute myocarditis and those with acute myocardial infarction. However, blood tests remain invasive procedures. Summary of the Invention

[0005] Based on this, one embodiment of this application provides the application of urinary protein markers and their detection reagents for the differential diagnosis of acute myocarditis and acute myocardial infarction in the preparation of products for the differential diagnosis of acute myocarditis and acute myocardial infarction.

[0006] The technical solution is as follows:

[0007] Urinary protein markers 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.

[0008] In one embodiment, compared to patients with acute myocardial infarction, patients with acute myocarditis showed decreased expression levels of tumor necrosis factor receptor superfamily member 1A and coagulation factor IX, and increased expression levels of peroxidoreductase 3.

[0009] In one embodiment, the above-mentioned reagent for detecting the expression level of urinary protein markers is used in the preparation of products for the differential diagnosis of acute myocarditis and acute myocardial infarction.

[0010] In one embodiment, the sample being tested is urine.

[0011] In one embodiment, the detection reagent is selected from reagents used in the following methods: mass spectrometry, immunoassay, Western blot analysis, radioimmunoassay, immunofluorescence assay, immunoprecipitation, balanced 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 employed.

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

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

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

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

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

[0019] In one embodiment, mass spectrometry identification of the tagged peptide refers to its use in a data-independent mass spectrometry acquisition mode.

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

[0021] Products used for the differential diagnosis of acute myocarditis and acute myocardial infarction, the products including reagents for detecting the expression levels of urinary protein markers as defined above.

[0022] Systems used to differentiate between acute myocarditis and acute myocardial infarction include:

[0023] The detection module is used to detect the content of the above-mentioned urinary protein markers in the sample to be tested;

[0024] The input module is used to input the data of the sample to be tested, including the content of urine protein markers;

[0025] The analysis module is used to analyze the data of the sample to determine whether it is acute myocarditis or acute myocardial infarction.

[0026] The output module is used to output the analysis results from the analysis module.

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

[0028] It should be noted that, in addition to logistic regression, other machine learning algorithms can also be used for modeling, such as linear regression, support vector machine, nearest neighbor / k-nearest neighbor, decision tree, k-means, random forest, naive Bayes, dimensionality reduction, and gradient enhancement. Any system that uses the content or expression level detected by the urinary protein biomarker of this application to build a model is within the scope of protection of this application.

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

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

[0031] Among them, PRDX3, F9 and TNFRSF1A represent the expression level (i.e., expression level or content) of the corresponding proteins.

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

[0033] In one embodiment, the analysis module includes comparing the sample to a control sample to determine whether the sample is indicative of acute myocarditis or acute myocardial infarction. The control sample is a sample from a patient with acute myocardial infarction or acute myocarditis.

[0034] In one embodiment, when compared with a sample from a patient with acute myocardial infarction, if the expression levels of the tumor necrosis factor receptor superfamily member 1A and the coagulation factor IX are significantly reduced and the expression level of peroxidoreductase 3 is significantly increased in the sample to be tested, then the sample to be tested is identified as a patient with acute myocarditis.

[0035] In one embodiment, the test samples include patients clinically suspected of having acute myocarditis or acute myocardial infarction who present to the emergency department with chest pain as their chief complaint.

[0036] A computer-readable storage medium includes a computer program that is executed by a processor, and when executed by the processor, the computer program implements the functions of different modules in the system.

[0037] An apparatus includes the computer-readable storage medium and a processor for executing programs and implementing the functions of the system.

[0038] In this application, the device is a method for distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they can be replaced by other expressions. Those skilled in the art will recognize that this application can be implemented as a device, method, or computer program product. Therefore, the disclosure of this application can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. Furthermore, in some specific embodiments, this application can also be implemented as a computer program product in one or more computer-readable media containing computer-readable program code.

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

[0040] (1) Detect the expression levels of the above-mentioned urinary protein markers in samples from subjects;

[0041] (2) Diagnose whether the subject has acute myocarditis or acute myocardial infarction based on the expression level of the detected urinary protein markers.

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

[0043] Compared with traditional technologies, this application has the following advantages:

[0044] The expression levels of peroxidase 3, tumor necrosis factor receptor superfamily member 1A, and coagulation factor IX in urine were detected using mass spectrometry based on characteristic protein-tagged peptides. The expression levels of these three biomarkers demonstrate strong diagnostic capability for acute myocarditis and acute myocardial infarction, thus providing a novel non-invasive method for the differential diagnosis of these two diseases. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application and to more completely understand this application and its beneficial effects, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 PCA plots were used to differentiate between patients with acute myocarditis and acute myocardial infarction based on urinary protein groups under a data-independent acquisition mode. The urinary protein group of healthy individuals served as a control. Red represents the healthy control group, green represents the acute myocardial infarction group, and purple represents the acute myocarditis group. The three groups showed a state of clustering within groups and separation between groups.

[0047] Figure 2 In a data-independent acquisition mode, mass spectrometry was used to detect changes in the levels of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3 in the urine of patients; (*P<0.05,**P<0.01,***P<0.001).

[0048] Figure 3 For training purposes, mass spectrometry was used to detect urinary protein markers, including tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3, and their combinations to differentiate patients with acute myocarditis and acute myocardial infarction.

[0049] Figure 4 To validate the results, mass spectrometry was used to detect the ROC curves of urinary protein markers tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidase 3, respectively, and in combination, to differentiate patients with acute myocarditis and acute myocardial infarction.

[0050] Figure 5 The changes in the levels of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3 in the urine of patients were detected by ELISA; (*P<0.05,**P<0.01,***P<0.001).

[0051] Figure 6 ROC curves were obtained for the detection of urinary tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3 by ELISA method, and for the differentiation of acute myocarditis and acute myocardial infarction by combination. Detailed Implementation

[0052] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, a detailed description of specific embodiments of this application is provided below. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to 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 herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0054] In this document, the term "and / or" includes any and all combinations of one or more of the related listed items.

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

[0056] Whether the levels of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3 in urine can differentiate between acute myocarditis and acute myocardial infarction has not yet been reported or applied. If the combination of these three urinary proteins could differentiate between acute myocarditis and myocardial infarction at the initial presentation of acute chest pain, it would undoubtedly greatly facilitate the early diagnosis of these two diseases.

[0057] Given the current lack of economical and non-invasive biomarkers for the differential diagnosis of acute myocarditis and acute myocardial infarction in clinical practice, this study, based on quantitative proteomics using mass spectrometry, identified a novel set of protein biomarkers in the urine of patients with acute myocarditis and acute myocardial infarction presenting to the emergency department. These biomarkers effectively differentiate between the two types of patients, including tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3. This application investigates the combination of urinary tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3 as biomarkers for the differential diagnosis of acute myocarditis and acute myocardial infarction, and its application, providing a new method for differentiating between the two types of patients.

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

[0059] Urine samples were obtained from subjects when they first sought medical attention in the emergency department for chest pain, and urinary proteins were enriched, digested with enzymes, and libraries were constructed. The samples were analyzed by 1D-LC-MS / MS. Data-independent detection results showed that tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidase 3 were significantly differentially expressed proteins.

[0060] Mass spectrometry quantitatively detected tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidase 3 in urine. The results showed that compared with patients with acute myocardial infarction, patients with acute myocarditis had significantly lower expression levels of tumor necrosis factor receptor superfamily member 1A and coagulation factor IX in urine, while the expression level of peroxidase 3 was significantly higher. The AUC value of the three protein combinations in the differential diagnosis between acute myocarditis and acute myocardial infarction was between 0.9 and 1.0, demonstrating strong diagnostic ability.

[0061] The above results indicate that the combination of tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidase 3 in the patient's urine can be used to differentiate between 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-mentioned quantitative mass spectrometry detection is based on the detection of protein characteristic tag peptides. A tag peptide is a peptide segment that can represent a specific protein and exists only specifically in the amino acid sequence of that protein.

[0063] A mass spectrometry method based on characteristic protein-tagged peptides was used to detect the expression levels of peroxidase 3, tumor necrosis factor receptor superfamily member 1A, and coagulation factor IX in urine. Baseline ranges of these three proteins in healthy individuals were established by combining their expression levels with standards. By comparing the levels of these three proteins in patients with acute myocarditis and acute myocardial infarction, a novel non-invasive diagnostic method for these two diseases was provided.

[0064] The embodiments of this application will be described in detail below with reference to examples. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of this application. For experimental methods in the following embodiments where specific conditions are not specified, please refer to the guidelines given in this application, or follow experimental manuals or conventional conditions in the art, or follow the conditions recommended by the manufacturer, or refer to experimental methods known in the art.

[0065] In the specific embodiments described below, the measurement parameters involving raw material components may have slight deviations within the weighing accuracy range unless otherwise specified. For temperature and time parameters, acceptable deviations due to instrument testing accuracy or operational precision are permissible.

[0066] Example 1: Detection of proteins related to the differential diagnosis of acute myocarditis and acute myocardial infarction in urine.

[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, 60mg, Waters); C18 reversed phase chromatography column (4.6mm×250mm, C18, 3μm, Waters).

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

[0071] We used a data-independent acquisition (DIA) method to screen for and identify relevant proteins in urine from patients with acute myocarditis and acute myocardial infarction.

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

[0073] Urine was collected during the first medical visit, centrifuged (3000×g, 10 minutes) to remove cell debris, and the supernatant was used for subsequent testing.

[0074] 2. Proteolytic enzyme digestion

[0075] Protein digestion was performed using an on-membrane enzymatic digestion method. The supernatant was used for alkylation with 20 mM DTT (95°C, 10 min) followed by 50 mM iodoacetamide (incubated in the dark, 45 min). Proteins were precipitated using six volumes of pre-chilled acetone (-20°C, 30 min), and the precipitate was collected by centrifugation (14000×g, 10 min, 4°C) and dissolved in 25 mM ammonium bicarbonate buffer. Before use, the 30 kDa ultrafiltration apparatus was pretreated by washing three times with 25 mM ammonium bicarbonate buffer (14000×g, 3 min each time, 4°C). The protein solution was loaded into the pretreated ultrafiltration apparatus and concentrated by centrifugation at 14000×g for 10 min at 4°C. Buffer replacement was performed by three dilution-concentration cycles 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 centrifugation filtration (14000×g).

[0076] 3. Building a document library

[0077] To construct the spectral library, all urine samples (disease group and control group) were mixed in equal volumes and separated by offline high-pH high-performance liquid chromatography. The collected eluent was placed in a rotary vacuum dryer, dried under vacuum, and then reconstituted in 1‰ formic acid for LC-MS / MS analysis. Raw data for each component were acquired using data-independent acquisition (DIA). The acquired raw data were processed using Spectronaut Pulsar 19.0 software (Biognosys) with default parameters. The analysis workflow was as follows: after importing the DIA file into Spectronaut Pulsar, the data were analyzed against the Swiss-Prot Human Proteome Database (Homo A database search was performed using sapiens (May 2019 version, containing 20,358 protein entries). Search parameters were set as follows: trypsin digestion (allowing a maximum of 2 missed cleavage sites), cysteine ​​carbamoyl methylation as a fixed modification, and methionine oxidation, lysine deamidation, and lysine carbamoylation (+43 Da) as variable modifications. Subsequently, the dynamic iRT retention time prediction algorithm was enabled and MS1 level interference correction was turned on. Peptide intensity was calculated by accumulating the peak areas of the corresponding MS1 fragment ions, and protein intensity was obtained by summing the intensities of its associated peptides. 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 a 1% false discovery rate, FDR).

[0078] 4. DIA analysis of experimental data:

[0079] 163 samples were analyzed using 1D-LC-MS / MS. Data was acquired for each sample via DIA. Data acquired via DIA were processed using Spectronaut software. The constructed spectral library was searched using the same search parameters. The results were then exported.

[0080] Differential expression analysis (Fold change > 1.5 or < 0.68, FDR-adjusted P value < 0.05) identified 806 differentially expressed proteins in the acute myocarditis group (366 upregulated and 438 downregulated) and 1098 differentially expressed proteins in the acute myocardial infarction group (557 upregulated and 538 downregulated). Figure 1 PCA plots for differentiating acute myocarditis and acute myocardial infarction patients from urinary protein profiles under data-independent acquisition mode.

[0081] The screening criteria for candidate biomarkers include: (1) significant upregulation in acute myocarditis or acute myocardial infarction compared to healthy controls; (2) significant differential expression between acute myocarditis and acute myocardial infarction. Figure 2 ).

[0082] After initial protein screening based on the above criteria, all patients (42 cases of acute myocarditis and 80 cases of acute myocardial infarction) were randomly divided into a training set (31 cases of acute myocarditis and 60 cases of acute myocardial infarction, totaling 91 cases) and a validation set (11 cases of acute myocarditis and 20 cases of acute myocardial infarction, totaling 31 cases) in a 3:1 ratio (stratified by age and sex).

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

[0084] The three differentially expressed proteins were jointly modeled, and a diagnostic model was constructed using logistic regression to generate a diagnostic score logit(p) for determining the disease type of the urine sample. The logistic regression equation of the constructed joint diagnostic model in the training set is as follows:

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

[0086] Wherein, PRDX3, F9, and TNFRSF1A represent the content of their respective biomarkers (e.g., unit: relative intensity). The model outputs a probability p, which is used to diagnose acute myocardial infarction (AMI) when p ≥ 0.5 and acute myocarditis (AM) when p < 0.5.

[0087] In the training set, the joint model achieved an AUC of 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 combined diagnostic model described above also demonstrated good discriminative ability, with an AUC of 0.905 (95% CI: 0.79-1). Figure 4 ).

[0088] In addition, ROC curves of TNFRSF1A, F9, and PRDX3 in distinguishing between acute myocardial infarction and acute myocarditis were plotted in the training and validation sets. Figures 3-4 It demonstrates a good ability to distinguish.

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

[0090] Materials and reagents:

[0091] 1) Main reagents: Tumor necrosis factor receptor superfamily member 1A protein ELISA kit (Ruixin Biotech, Quanzhou, China), coagulation factor IX ELISA kit (Ruixin Biotech, Quanzhou, China), peroxidoreductase 3 ELISA kit (Ruixin Biotech, Quanzhou, China).

[0092] 2) Samples: Urine from 28 patients with acute myocarditis, 52 patients with acute myocardial infarction (26 patients with acute ST-segment elevation myocardial infarction and 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 urinary protein

[0094] Urine was collected during the first medical visit, centrifuged (3000×g, 10 minutes) to remove cell debris, and the supernatant was used for subsequent testing.

[0095] 2. Enzyme-linked immunosorbent assay (ELISA)

[0096] Set up standard wells, zero-value wells, blank wells, and sample wells. Add 50 μL of standard at different concentrations to each standard well, 50 μL of sample diluent to each zero-value well, nothing to the blank wells, and 50 μL of the sample to be tested to each sample well. Except for the blank wells, add 100 μL of horseradish peroxidase (HRP)-labeled detection antibody to each standard well, zero-value well, and sample well. Cover the reaction plate with sealing film and incubate at 37°C in a water bath or incubator in the dark for 60 min. Wash the plate 5 times using an automatic plate washer and pat the plate dry. Mix substrates A and B in a 1:1 volume ratio and add 100 μL of the substrate mixture to all wells. Cover the reaction plate with sealing film and incubate at 37°C in a water bath or incubator in the dark for 15 min. Add 50 μL of stop solution to each well and read the absorbance (OD value) of each well using a microplate reader.

[0097] 3. Data Processing

[0098] Using the concentration of the standard as the x-axis (6 standard wells plus 1 zero-value well, for a total of 7 concentration points) and the corresponding absorbance (OD value) as the y-axis, a standard curve equation was created using computer software with four-parameter Logistic curve fitting. The concentration of the sample was then calculated using the equation based on the absorbance (OD value) of the sample.

[0099] Compared to patients with acute myocardial infarction, patients with acute myocarditis showed significantly decreased expression levels of tumor necrosis factor receptor superfamily member 1A and coagulation factor IX in their urine, while significantly increased expression levels of peroxidoreductase 3. Figure 5 Furthermore, we conducted a ROC analysis to determine the ability of these three proteins to distinguish between the acute myocarditis group and the acute myocardial infarction group. The three proteins were then combined and predicted using the following logistic regression model:

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

[0101] Here, PRDX3, F9, and TNFRSF1A represent the content of their respective markers (e.g., in pg / mL).

[0102] It demonstrated excellent diagnostic performance in this external validation population (AUC = 0.96, 95% CI: 0.923–0.998). Figure 6 In addition, ROC curves of TNFRSF1A, F9, and PRDX3 in differentiating between acute myocardial infarction and acute myocarditis were plotted. Figure 6 It demonstrates a good ability to distinguish.

[0103] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0104] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims, and the specification can be used to interpret the content of the claims.

Claims

1. A urinary protein marker for the differential diagnosis of acute myocarditis and acute myocardial infarction, characterized in that, The urinary protein markers include one or more of the following: tumor necrosis factor receptor superfamily member 1A, coagulation factor IX, and peroxidoreductase 3.

2. The urinary protein marker according to claim 1, characterized in that, Compared to patients with acute myocardial infarction, patients with acute myocarditis showed decreased expression levels of tumor necrosis factor receptor superfamily member 1A and coagulation factor IX, and increased expression levels of peroxidoreductase 3.

3. The use of the reagent for detecting the expression level of urinary protein markers as described in claim 1 or 2 in the preparation of products for the differential diagnosis of acute myocarditis and acute myocardial infarction.

4. The application according to claim 3, characterized in that, The sample tested was urine.

5. The application according to claim 3 or 4, characterized in that, The detection reagents are selected from those used in the following methods: mass spectrometry, immunoassay, Western blot analysis, radioimmunoassay, immunofluorescence assay, immunoprecipitation, balanced dialysis, immunodiffusion, electrochemiluminescence immunoassay, ELISA assay, or immunopolymerase chain reaction. Optionally, the mass spectrometry detection method is LC-MS / MS; Optionally, the ELISA assay is a double-antibody sandwich ELISA assay. Optionally, the detection reagent includes an antibody or an antibody functional fragment.

6. The application according to claim 3 or 4, characterized in that, The products include reagent kits, chips, test strips, systems, or devices; Optionally, the kit is a mass spectrometry identification tag peptide kit or an enzyme-linked immunosorbent assay kit.

7. A product for the differential diagnosis of acute myocarditis and acute myocardial infarction, characterized in that, The product includes a reagent for detecting the expression level of urinary protein markers as defined in any one of claims 3-6.

8. A system for the differential diagnosis of acute myocarditis and acute myocardial infarction, characterized in that, include: A detection module is used to detect the content of urinary protein markers in a sample to be tested, wherein the urinary protein markers include the urinary protein markers as defined in claim 1 or 2; 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. Optionally, the system has one or more of the following features: (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.

9. 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 8.

10. An apparatus, characterized in that, It includes the computer-readable storage medium of claim 9, and a processor for executing programs and implementing the functions of the system.

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