Protein marker for identifying right ventricular dysfunction in idiopathic dilated cardiomyopathy and application thereof

Abstract

The invention relates to a protein marker for identifying right ventricular dysfunction in idiopathic dilated cardiomyopathy and application of the protein marker. RARRES1, MVB12B and GSK3A proteins are found to be remarkably related to right ventricular dysfunction in urine of a patient with idiopathic dilated cardiomyopathy, the three proteins have good diagnosis or prognosis prediction performance in diagnosis and prognosis evaluation, and an economic, non-invasive and accurate right ventricular dysfunction diagnosis and prognosis tool is provided.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of medical diagnostic reagents, and particularly relates to a protein marker for identifying right ventricular dysfunction in idiopathic dilated cardiomyopathy and application thereof. BACKGROUND

[0002] Idiopathic dilated cardiomyopathy (iDCM) is a type of cardiomyopathy characterized by left ventricular systolic dysfunction and cardiac chamber enlargement in the absence of an identifiable cause. It is an important cause of heart failure and sudden cardiac death, especially in young patients. In recent years, with the progress of molecular characterization and imaging phenotype research, the identification of iDCM subtypes has become increasingly accurate. However, due to the lack of targeted treatment, the overall prognosis of patients remains poor, and even after standard drug therapy, the mortality rate within 5 years is still as high as about 20%.

[0003] In iDCM patients, right ventricular dysfunction (RVD) is a common and underestimated complication with a high incidence of 36-75%. RVD is independently associated with heart failure hospitalization, cardiac death, left heart assist device implantation, and heart transplantation, and is an important determinant of poor prognosis. However, due to the complex structure of the right ventricle and its strong load dependence, current imaging methods such as cardiac magnetic resonance are considered the gold standard for assessing right ventricular ejection fraction, but in actual clinical practice, they are difficult to be widely used due to high cost, limited equipment and personnel; and echocardiography has low sensitivity in detecting RVD, resulting in insufficient diagnostic rate. Therefore, it is urgent to develop a simple, accurate, and non-invasive method for early identification of RVD patients to guide individualized treatment and risk assessment.

[0004] In recent years, urinary proteomics has received widespread attention as a new non-invasive detection method. Urine is not only widely available and easy to collect, but also can enrich low-abundance proteins in plasma, reflecting the pathophysiological state of the cardiovascular system. Compared with serum or tissue, urine is more suitable for high-throughput screening and disease monitoring. However, current research on the application of urinary proteins in right ventricular dysfunction in iDCM patients is still very limited, and there is no proven urinary marker for the diagnosis and prognosis of RVD. SUMMARY

[0005] Therefore, an embodiment of the present application provides a protein marker for diagnosing right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy and evaluating the prognosis thereof, and proposes the application thereof in preparing a diagnostic or prognostic product for identifying right ventricular dysfunction in patients with dilated cardiomyopathy.

[0006] The technical solutions include the following.

[0007] In a first aspect, the present application provides a protein marker for differential diagnosis of right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy or a protein marker for predicting the prognosis risk of patients with idiopathic dilated cardiomyopathy, wherein the protein marker comprises one or more of Retinoic Acid Receptor Responder Protein 1 (RARRES1), Multivesicular Body Subunit 12B (MVB12B), and Glycogen Synthase Kinase-3 Alpha (GSK3A).

[0008] In one embodiment, the expression level of RARRES1 and MVB12B is significantly increased, and the expression level of GSK3A is significantly decreased in the sample of the patient with right ventricular dysfunction as compared with the patient without right ventricular dysfunction.

[0009] In one embodiment, the sample comprises urine.

[0010] In a second aspect, the present application provides use of a detection reagent for the expression level of the above protein marker in the preparation of a diagnostic product for identifying or differentiating right ventricular dysfunction in patients with dilated cardiomyopathy.

[0011] In a third aspect, the present application provides use of a detection reagent for the expression level of the above protein marker in the preparation of a product for predicting the prognosis risk of patients with idiopathic dilated cardiomyopathy.

[0012] In one embodiment, the product is used for predicting the risk of occurrence of a composite endpoint event of cardiovascular death, heart failure re-hospitalization, left ventricular assist device implantation, or heart transplantation.

[0013] In one embodiment, the detection reagent is selected from the reagents used in one or more of the following methods: liquid chromatography, mass spectrometry, and immunoassay.

[0014] In one embodiment, the immunoassay comprises one or more of western blot analysis, radioimmunoassay, immunofluorescence, immunoprecipitation, immunodiffusion, electrochemiluminescence immunoassay, ELISA assay, and immunopolymerase chain reaction.

[0015] In one embodiment, the detection reagent is suitable for liquid chromatography-tandem mass spectrometry (LC-MS / MS) or double antibody sandwich ELISA.

[0016] In one embodiment, mass spectrometry based on protein signature peptides is used.

[0017] In one embodiment, the detection reagent comprises an antibody or a functional fragment thereof.

[0018] In one embodiment, the product comprises a kit, a chip, a test strip, a system or a device.

[0019] In one embodiment, the kit is a mass spectrometry identification kit or an enzyme-linked immunosorbent assay kit.

[0020] In one embodiment, the mass spectrometry identification kit refers to the use in data-independent mass spectrometry acquisition mode.

[0021] In a fourth aspect, the present application provides a product for differential diagnosis of the right ventricular function status of patients with idiopathic dilated cardiomyopathy, wherein the product comprises a detection reagent for the expression level of the protein marker defined above.

[0022] In a fifth aspect, the present application provides a diagnostic model for identifying right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy, wherein the diagnostic model comprises RARRES1, MVB12B and GSK3A protein markers, and the diagnostic model comprises the following calculation formula:

[0023] logit(p) = 1.5205 + 0.4729 x RARRES1 + 0.5582 x MVB12B - 0.5875 x GSK3A

[0024] Wherein, logit(p) represents the probability value, RARRES1 represents the expression amount of RARRES1 protein, MVB12B represents the expression amount of MVB12B protein, and GSK3A represents the expression amount of GSK3A protein.

[0025] In one embodiment, when p≥0.5, it is determined that the patient with idiopathic dilated cardiomyopathy is combined with right ventricular dysfunction; when p<0.5, it is determined that the patient with idiopathic dilated cardiomyopathy does not have right ventricular dysfunction.

[0026] In a sixth aspect, the present application provides a diagnostic system for identifying the right ventricular function status of patients with idiopathic dilated cardiomyopathy, wherein the diagnostic system comprises a data acquisition module, an analysis module and a result output module:

[0027] (1) The data acquisition module is used to acquire the expression amount of the protein marker in the sample of the subject to be tested, wherein the protein marker comprises one or more of RARRES1, MVB12B and GSK3A.

[0028] (2) an analysis module, configured to analyze the expression of the protein markers obtained by the data acquisition module, and analyze whether the subject has right ventricular dysfunction.

[0029] In one embodiment, the analysis module is configured to construct a diagnostic model based on the expression of the protein markers obtained by the data acquisition module, so as to realize diagnosis and prognosis risk assessment of right ventricular dysfunction.

[0030] In one embodiment, the analysis module is configured to provide the expression of the protein markers obtained by the data acquisition module as input data to the constructed diagnostic model, and analyze whether the subject has right ventricular dysfunction or not.

[0031] In one embodiment, the diagnostic model is constructed based on the expression data of the protein markers in patients with idiopathic dilated cardiomyopathy, and a logistic regression algorithm or other machine learning algorithm is used. Alternatively, the diagnostic model is the diagnostic model of the fifth aspect.

[0032] 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 expression or content of the protein markers detected in the present application to construct the model is within the protection scope of the present application.

[0033] (3) a result output module, configured to output the analysis result of the analysis module, and obtain the diagnosis result of whether the patient has right ventricular dysfunction.

[0034] In a seventh aspect, the present application provides a risk score model for prognosis prediction of idiopathic dilated cardiomyopathy, wherein the risk score model comprises RARRES1, MVB12B and GSK3A protein markers, and the risk score model is calculated by the following formula:

[0035] Risk Score = 0.594 x RARRES1 + 0.738 x MVB12B - 0.637 x GSK3A

[0036] wherein, Risk Score represents the risk score, RARRES1 represents the expression of RARRES1 protein, MVB12B represents the expression of MVB12B protein, and GSK3A represents the expression of GSK3A protein.

[0037] Based on the risk score model constructed by the protein markers, the risk score of the patient for developing composite adverse events is calculated, which can effectively distinguish high-risk and low-risk patients, and the risk of cardiovascular death, heart failure rehospitalization, left ventricular assist device implantation or heart transplantation in the high-risk group is significantly increased.

[0038] In one embodiment, when the Risk Score is greater than or equal to 0.86, the patient is determined to be high risk; when the Risk Score is less than 0.86, the patient is determined to be low risk.

[0039] In an eighth aspect, the present application provides a device or system for predicting the prognosis risk of idiopathic dilated cardiomyopathy, which comprises:

[0040] (1) a data acquisition module for acquiring the expression level of protein markers in the sample of the subject to be tested, wherein the protein markers comprise one or more of RARRES1, MVB12B and GSK3A.

[0041] (2) an analysis module for providing the expression level of the urine protein markers obtained by the data acquisition module as input data to the constructed risk score model.

[0042] Optionally, the risk score model is a Cox regression model.

[0043] Optionally, the risk score model is the risk score model of the seventh aspect described above.

[0044] (3) an output module for outputting the prognosis risk stratification result of the risk score model.

[0045] In a ninth aspect, the present application provides a computer readable storage medium comprising a computer program, wherein the computer program is executed by a processor, and the computer program, when executed by the processor, realizes the functions of different modules in the system.

[0046] In a tenth aspect, the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to realize the functions of the diagnostic system.

[0047] It should be understood that the terms "system," "apparatus," and / or "device" as used herein are used to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions. Those skilled in the art will recognize that this application can be implemented as a method or a 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 contained in one or more computer-readable media, which contains computer-readable program code.

[0048] Based on a quantitative proteomics method using mass spectrometry, this application found that the above three proteins in the urine of patients with idiopathic dilated cardiomyopathy were significantly associated with right ventricular dysfunction. A diagnostic model was constructed and a prognostic evaluation was conducted, providing an economical, non-invasive, and accurate tool for the diagnosis and prognosis of right ventricular dysfunction.

[0049] Eleventhly, this application provides a method for differential diagnosis of right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy or for prognostic risk assessment or diagnosis of patients with idiopathic dilated cardiomyopathy, comprising:

[0050] (1) Collect urine samples from the subjects;

[0051] (2) Detect the expression levels of RARRES1, MVB12B and GSK3A proteins in urine samples;

[0052] (3) Based on the protein expression level, a pre-established risk scoring model or diagnostic model is applied for analysis to determine whether the subject has right ventricular dysfunction, or

[0053] Patients are stratified clinically based on risk scores calculated using a risk scoring model.

[0054] The above method is a non-invasive diagnostic and / or prognostic stratification method for right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy, developed based on urinary proteomics and machine learning.

[0055] Compared with traditional technologies, this application has the following advantages:

[0056] This application employs a mass spectrometry method based on protein characteristic tag peptides to detect the expression levels of RARRES1, MVB12B, and GSK3A in urine. The expression levels of these three biomarkers demonstrate strong ability to differentiate between idiopathic dilated cardiomyopathy and right ventricular dysfunction, and possess significant prognostic value, thus providing a novel non-invasive diagnostic and risk assessment method for identifying this disease state.

[0057] This application provides a non-invasive, stable urine testing method suitable for clinical translation, offering a new approach for the accurate identification and individualized management of right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy. Attached Figure Description

[0058] 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.

[0059] Figure 1 This is a volcano plot showing differentially expressed proteins in urine between the right ventricular dysfunction (RVD) group and the non-RVD group. Red indicates proteins upregulated in RVD, and blue indicates proteins downregulated. Dashed lines represent the fold change threshold (1.5-fold) and the statistical significance threshold (adjusted P-value = 0.05), respectively. Gene names are used instead of full protein names in the plot.

[0060] Figure 2 The performance of the three-protein diagnostic model on the training and validation sets is shown, along with comparisons with NT-proBNP, TAPSE, and their combinations. The three-protein model (GSK3A, MVB12B, and RARRES1) demonstrated superior diagnostic efficacy compared to single proteins, NT-proBNP, TAPSE, and their combinations in both the training (A) and validation (B) sets, exhibiting higher AUC, sensitivity, and specificity. GSK3A: Glycogen synthase kinase 3α; MVB12B: Multivesicular body sorting protein 12B; RARRES1: Retinoic acid regulation-associated protein 1; NT-proBNP: N-terminal pro-brain natriuretic peptide; TAPSE: Tricuspid annular systolic displacement.

[0061] Figure 3Kaplan-Meier survival curves are used to stratify patient survival using a Cox risk score model based on three urinary protein markers (GSK3A, MVB12B, and RARRES1). Patients were divided into high-risk and low-risk groups based on median risk score (cut-off = 0.86). Patients in the high-risk group had a significantly increased risk of cardiovascular death or hospitalization for heart failure (HR = 3.24, 95% CI: 1.56–6.71, P = 0.001). Detailed Implementation

[0062] 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.

[0063] 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 in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application.

[0064] In this document, the term "and / or" includes any and all combinations of one or more of the related listed items.

[0065] In this article, the term "prognosis" refers to the prediction of disease progression and outcome based on clinical data, including two types: natural prognosis (the outcome without treatment) and interventional prognosis (the outcome after medical intervention).

[0066] In this article, the term "NT-proBNP" refers to N-terminal pro-B-type natriuretic peptide, a biomarker secreted by ventricular myocytes when cardiac pressure load increases. It reflects cardiac function and is widely used to assess the severity and prognostic risk of heart failure.

[0067] In this article, the term "TAPSE" refers to Tricuspid Annular Plane Systolic Excursion, an important echocardiographic indicator for assessing right ventricular longitudinal systolic function. The lower the value, the more likely it is that right ventricular systolic function is impaired.

[0068] This application relates to three biomarkers in urine: retinoic acid regulation-associated protein 1 (RARRES1), multivesicular body sorting protein 12B (MVB12B), and glycogen synthase kinase 3α (GSK3A). RARRES1 (Retinoic Acid Receptor Responder Protein 1, UniProt ID: P49788) is a protein associated with cell differentiation and tumor suppression; MVB12B (Multivesicular Body Subunit 12B, UniProt ID: Q9H7P6) participates in the formation of intracellular multivesicular bodies and regulates the transport and degradation of membrane proteins; GSK3A (Glycogen Synthase Kinase-3 Alpha, UniProt ID: P49840) is a serine / threonine protein kinase that is widely involved in the regulation of multiple signaling pathways and affects cell metabolism and proliferation.

[0069] Currently, there are no publicly available reports on the expression of RARRES1, MVB12B, and GSK3A in urine and their combined use in the diagnosis and prognostic evaluation of right ventricular dysfunction in dilated cardiomyopathy.

[0070] This application utilizes data-independent acquisition (DIA) mass spectrometry analysis and multivariate statistical modeling to screen and establish three urinary proteins—retinoic acid regulation-related protein 1 (RARRES1), multivesicular body sorting protein 12B (MVB12B), and glycogen synthase kinase 3α (GSK3A)—as core biomarkers. The logistic regression model constructed based on these three proteins demonstrated excellent diagnostic efficacy (AUC = 0.946) on both the training and validation sets, significantly outperforming traditional indicators such as NT-proBNP and TAPSE. Furthermore, the protein risk score constructed using a Cox regression model effectively differentiated patient prognostic risks and predicted composite endpoint events such as cardiovascular death and heart failure readmission, exhibiting good independent prognostic predictive ability.

[0071] 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.

[0072] 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. Temperature and time parameters are subject to acceptable deviations due to instrument testing accuracy or operational precision.

[0073] The following examples

[0074] Example 1: Mass spectrometry detection of right ventricular dysfunction-related proteins in urine of patients with dilated cardiomyopathy

[0075] Materials and reagents:

[0076] 1) Instrument: Orbitrap Exploris 480 mass spectrometer (Thermo Scientific).

[0077] 2) Main reagents: trypsin (Promega); C18 solid phase extraction column (3CC, 60mg, Waters); C18 reversed phase chromatography column (4.6mm×250mm, C18, 3μm, Waters).

[0078] 3) Samples: Urine samples were collected from patients with idiopathic dilated cardiomyopathy at the time of initial diagnosis, including a group with normal right ventricular function (n=83) and a group with right ventricular dysfunction (n=64), from Peking Union Medical College Hospital.

[0079] We used data-independent acquisition (DIA) to screen for proteins in urine that are associated with RVD in dilated cardiomyopathy.

[0080] 1. Collection of human urine samples and enrichment of urinary protein

[0081] Collect urine from the first medical visit, centrifuge at 1000g for 20 minutes to remove sediment. Use the supernatant for subsequent testing.

[0082] 2. Proteolytic enzyme digestion

[0083] Protein digestion was performed using an on-membrane enzymatic digestion method. Protein samples were first reduced with 20 mM DTT at 95°C for 5 min, followed by alkylation of exposed thiol groups with 50 mM MIAAA at room temperature in the dark for 45 min. The reductively alkylated protein solution was transferred to a 30 kDa ultrafiltration tube, centrifuged, and the lower layer was discarded. The on-membrane protein samples were washed twice with UA solution (containing 8 M urea) and twice with 25 mM ammonium bicarbonate solution. The on-membrane protein samples were then digested with 1:50 trypsin overnight at 37°C, and the resulting peptides were collected by centrifugation. The digested peptide solution was purified using a C18 extraction column, and the purified product was dried under vacuum. After reconstitution, the peptide concentration was determined using a BCA kit.

[0084] 3. Building a document library

[0085] To construct the spectral library, all urine samples were mixed in equal volumes and separated by offline high-pH high-performance liquid chromatography (HPLC). The collected eluent was dried under vacuum and then reconstituted in 1‰ formic acid for LC-MS / MS analysis. Data for each fraction was acquired using a data-independent acquisition (DIA) method. The raw data were retrieved using Proteome Discoverer (Thermo Scientific, Germany) software with the following search criteria: enzyme digestion: trypsin; maximum of two missed cleavage sites allowed; fixed modification: cysteine ​​alkylation; variable modification: aspartate and glutamine deamination, methionine oxidation; lysine and N-terminal carbamylation of peptides; precursor ion mass error: 10 ppm; daughter ion mass error: 0.02 Da. Protein level FDR <1%, and each protein contained at least one unique peptide. The search results were imported into Spectronaut Pulsar (Biognosys, Switzerland) software to generate the database.

[0086] 4. DIA analysis of experimental data:

[0087] 147 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.

[0088] Differential expression analysis (Fold change > 1.5 or < 0.68, FDR-adjusted P value < 0.05) identified a total of 46 differentially expressed proteins (23 upregulated and 23 downregulated). Figure 1 Subsequently, multivariate logistic regression models were constructed for each of the 46 differentially expressed proteins, with age, sex, body mass index, left ventricular ejection fraction, N-terminal pro-brain natriuretic peptide (PPB), and systolic blood pressure as covariates for adjustment. After multivariate adjustment, 15 proteins were found to be independently associated with RVD.

[0089] After initial protein screening based on the above criteria, all patients (64 with right ventricular dysfunction and 83 with normal right ventricular function) were randomly assigned in a 3:1 ratio (stratified by age and sex) to a training set (48 with right ventricular dysfunction and 61 with normal right ventricular function) and a validation set (16 with right ventricular dysfunction and 22 with normal right ventricular function). In the training set, LASSO regression was used for feature selection, identifying 11 variables with predictive value. Based on the LASSO coefficient, ROC analysis results, and the biological mechanisms of these proteins in cardiovascular disease, RARRES1, MVB12B, and GSK3A were ultimately identified as the core biomarkers.

[0090] 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:

[0091] logit(p)=1.5205+0.4729×RARRES1+0.5582×MVB12B-0.5875×GSK3A

[0092] Wherein, RARRES1, MVB12B, and GSK3A represent the expression levels of the corresponding proteins. In this embodiment, the probability value output by the model is p. When p ≥ 0.5, the patient is determined to have right ventricular dysfunction (RVD); when p < 0.5, the patient is determined to not have RVD.

[0093] In the training set, the AUCs of the individual diagnostic performance of RARRES1, GSK3A, and MVB12B proteins were 0.797 (95% CI: 0.712–0.882), 0.801 (95% CI: 0.705–0.896), and 0.747 (95% CI: 0.652–0.841), respectively. The diagnostic model constructed by combining the three proteins significantly outperformed the single protein, NT-proBNP, and TAPSE models, with an AUC as high as 0.946 (95% CI: 0.908–0.983), sensitivity of 0.854, specificity of 0.918, positive predictive value (PPV) of 0.891, and negative predictive value (NPV) of 0.889. On the validation set, the joint model also demonstrated excellent discriminative ability, with an AUC of 0.946 (95% CI: 0.878–1.000), significantly higher than NT-proBNP (AUC = 0.662), TAPSE (AUC = 0.636), and their combined model (AUC = 0.668). Figure 2 ).

[0094] Example 2: Prognostic evaluation of patients with dilated cardiomyopathy using a combined model of RARRES1, MVB12B, and GSK3A in urine.

[0095] 1. Materials, reagents, and sample sources

[0096] The sample source was the same as in Example 1, consisting of 147 patients diagnosed with idiopathic dilated cardiomyopathy.

[0097] 2. Prognostic follow-up and data collection

[0098] All patients were followed up for a median period of 19.3 months (interquartile range 10.9–28.1 months), and composite endpoint events including cardiovascular death, rehospitalization for heart failure, implantation of left ventricular assist device or heart transplantation were collected. A total of 37 prognostic events were recorded.

[0099] 3. Risk Score Calculation

[0100] Based on the expression levels of three proteins (GSK3A, MVB12B, and RARRES1), and combined with a multivariate Cox regression model (adjusted for age, sex, and NT-proBNP), a protein risk score was calculated for each patient.

[0101] Risk score calculation formula:

[0102] Risk Score=0.594×RARRES1+0.738×MVB12B-0.637×GSK3A

[0103] Here, Risk Score represents the risk score, RARRES1 represents the expression level of RARRES1 protein, MVB12B represents the expression level of MVB12B protein, and GSK3A represents the expression level of GSK3A protein.

[0104] Patients were divided into high-risk and low-risk groups based on the median risk score (cut-off = 0.86).

[0105] 4. Statistical Analysis

[0106] The Cox proportional hazards model was used to assess the correlation between protein risk scores and prognostic events. Kaplan-Meier survival analysis results showed ( Figure 3 Patients in the high-risk group had a significantly increased risk of the composite endpoint event compared to those in the low-risk group (HR = 3.24, 95% CI: 1.56–6.71, P = 0.001). The predictive power of the model was assessed using Harrell's C index, which yielded a value of 0.78 (95% CI: 0.72–0.85), indicating that the model has good discriminative power.

[0107] 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.

[0108] 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. The application of a reagent for detecting the expression level of a protein biomarker in the preparation of a diagnostic product for identifying right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy, wherein the protein biomarker includes one or more of RARRES1, MVB12B, and GSK3A.

2. The application according to claim 1, characterized in that, Compared with patients with normal right ventricular function in idiopathic dilated cardiomyopathy, the expression levels of RARRES1 and MVB12B were increased in the samples of patients with right ventricular dysfunction in idiopathic dilated cardiomyopathy, and the expression level of GSK3A was decreased in the samples of patients with right ventricular dysfunction in idiopathic dilated cardiomyopathy. Optionally, the sample to be tested may include urine.

3. The application of a reagent for detecting the expression level of a protein biomarker in the preparation of a product for predicting the prognostic risk of patients with idiopathic dilated cardiomyopathy, wherein the protein biomarker includes one or more of RARRES1, MVB12B and GSK3A; Optionally, the product is used to predict the risk of a composite endpoint event, including cardiovascular death, readmission from heart failure, implantation of a left ventricular assist device, or heart transplantation.

4. The application according to any one of claims 1 to 3, characterized in that, The detection reagent is selected from one or more of the following methods: liquid chromatography, mass spectrometry and immunoassay. Optionally, the immunoassay includes one or more of the following: Western blot analysis, radioimmunoassay, immunofluorescence assay, immunoprecipitation, immunodiffusion, electrochemiluminescence immunoassay, ELISA assay, and immunopolymerase chain reaction. Optionally, the detection reagent is a reagent suitable for liquid chromatography-tandem mass spectrometry (LC-MS / MS) or double antibody sandwich ELISA. Optionally, the detection reagent contains specific antibodies or functional fragments thereof against RARRES1, MVB12B and GSK3A.

5. The application according to any one of claims 1 to 3, characterized in that, The products are reagent kits, chips, test strips, detection systems, or devices; Optionally, the kit is a mass spectrometry labeled peptide detection kit or an enzyme-linked immunosorbent assay kit.

6. A diagnostic model for identifying right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy, characterized in that, The diagnostic model includes RARRES1, MVB12B, and GSK3A protein markers, and the diagnostic model includes the following calculation formula: logit(p)=1.5205+0.4729×RARRES1+0.5582×MVB12B-0.5875×GSK3A Where logit(p) represents the probability value, RARRES1 represents the expression level of RARRES1 protein, MVB12B represents the expression level of MVB12B protein, and GSK3A represents the expression level of GSK3A protein. Optionally, when p≥0.5, patients with idiopathic dilated cardiomyopathy are considered to have right ventricular dysfunction; when p<0.5, patients with idiopathic dilated cardiomyopathy are considered to have no right ventricular dysfunction.

7. A diagnostic device or system for identifying the right ventricular functional status in patients with idiopathic dilated cardiomyopathy, characterized in that, The diagnostic device or system includes: The data acquisition module is used to acquire the expression levels of protein biomarkers in the samples of the subjects to be tested, wherein the protein biomarkers include one or more of RARRES1, MVB12B and GSK3A; The analysis module is used to analyze the expression levels of protein biomarkers obtained by the data acquisition module to analyze whether the subject has right ventricular dysfunction; The result output module is used to output the analysis results of the analysis module to obtain the diagnostic result of whether the patient has right ventricular dysfunction; Optionally, the analysis module is used to provide the expression levels of protein markers obtained by the data acquisition module as input data to the constructed diagnostic model to analyze whether the result is combined with or without right ventricular dysfunction. Optionally, the diagnostic model is constructed using logistic regression based on the expression levels of the protein biomarkers in patients with idiopathic dilated cardiomyopathy. Optionally, the diagnostic model includes the diagnostic model of claim 6; Optionally, the subjects include patients with idiopathic dilated cardiomyopathy.

8. A risk scoring model for predicting the prognosis of idiopathic dilated cardiomyopathy, characterized in that, The risk scoring model includes RARRES1, MVB12B, and GSK3A protein biomarkers, and the risk score is calculated using the following formula: Risk Score=0.594×RARRES1+0.738×MVB12B-0.637×GSK3A Wherein, Risk Score represents the risk score, RARRES1 represents the expression level of RARRES1 protein, MVB12B represents the expression level of MVB12B protein, and GSK3A represents the expression level of GSK3A protein. Optionally, patients are classified as high-risk when the Risk Score is ≥0.86, and as low-risk when the Risk Score is <0.

86. High-risk patients have a significantly increased risk of cardiovascular death, heart failure rehospitalization, left ventricular assist device implantation, or heart transplantation.

9. A device or system for predicting the prognostic risk of idiopathic dilated cardiomyopathy, characterized in that, The prediction device or system includes: The data acquisition module is used to acquire the expression levels of protein biomarkers in the samples of the subjects to be tested, wherein the protein biomarkers include one or more of RARRES1, MVB12B and GSK3A; The analysis module is used to provide the expression levels of urinary protein biomarkers obtained by the data acquisition module as input data to the constructed risk scoring model; The output module is used to output the prognostic risk stratification results of the risk scoring model; Optionally, in the analysis module, the risk scoring model is modeled using Cox regression; Optionally, the risk scoring model is the risk scoring model described in claim 8.

10. A computer-readable storage medium, characterized in that, It stores a computer program for performing the system functions as described in claim 7 or 9.

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