A reagent kit for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure and its application.

Abstract

This invention belongs to the field of biomedical technology and relates to a reagent kit for diagnosing Yang deficiency and blood stasis syndrome in chronic heart failure and its application. The reagent kit for diagnosing Yang deficiency and blood stasis syndrome in chronic heart failure provided by this invention contains reagents for detecting the expression levels of biomarkers, wherein the biomarkers are at least one selected from F2 protein, TFRC protein, APOC1 protein, APOC3 protein, and HSPA8 protein; the reagents detect the expression levels of the protein biomarkers in the sample using immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), iPRM method, liquid chromatography-mass spectrometry (LC-MS), or mass spectrometry. By detecting the expression levels of the above biomarkers in the plasma of patients with chronic heart failure, this reagent kit can effectively diagnose and differentiate patients with Yang deficiency and blood stasis syndrome in chronic heart failure from those without, thus achieving auxiliary diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to a reagent kit for diagnosing Yang deficiency and blood stasis syndrome in chronic heart failure and its application. Background Technology

[0002] Heart failure (HF), often referred to as the "last battleground of heart disease," is characterized by high morbidity, high readmission rates, high mortality, and a heavy economic burden, making it a major chronic disease that seriously impacts public health. Currently, modern medicine has made significant progress in the prevention and treatment of HF, particularly in standardized drug therapy. The combination of RAAS inhibitors (ACEI / ARB / ARNI) + β-blockers + MRA + SGLT2i + sGC stimulators has become the "five golden flowers" of treatment for HF. However, ideal treatment strategies are still lacking for problems such as diuretic resistance, recurrent hospitalizations, and declining quality of life in the prevention and treatment of chronic HF, necessitating the exploration of new treatment approaches and methods.

[0003] In Traditional Chinese Medicine (TCM), heart failure falls under the categories of "palpitation," "edema," and "dyspnea," and is further classified into different syndrome types based on syndrome differentiation and treatment. Yang deficiency and blood stasis syndrome is one of the common and important syndrome types in heart failure. For this syndrome type, the application of methods that tonify Qi and warm Yang, and promote blood circulation and diuresis, has shown unique advantages in improving patient symptoms and quality of life, reflecting the precise essence of TCM syndrome differentiation and treatment. However, currently, the diagnosis of Yang deficiency and blood stasis syndrome in heart failure in TCM mainly relies on the four diagnostic methods of observation, auscultation, inquiry, and palpation, which is highly subjective and experience-dependent, lacking objective modern biological diagnostic indicators. This seriously restricts the standardization and normalization of TCM syndrome differentiation and the in-depth development of integrated TCM and Western medicine treatment. Therefore, exploring objective biomarkers that can specifically reflect Yang deficiency and blood stasis syndrome has become an urgent need and an important bridge connecting traditional TCM theory and modern precision medicine. In recent years, with the development of systems biology technology, researchers have begun to explore the potential material basis of TCM syndromes in heart failure from multiple dimensions, providing important clues and evidence for discovering specific biomarkers for Yang deficiency and blood stasis syndrome. However, significant limitations remain. For example, most of the biomarkers identified in studies, such as BNP, NT-proBNP, and inflammatory factors, while important indicators of heart failure, lack specificity for the specific syndrome of Yang deficiency and blood stasis. Therefore, there is an urgent need to research effective biomarkers for the diagnosis of Yang deficiency and blood stasis syndrome in heart failure. Summary of the Invention

[0004] In view of the problems and shortcomings of the existing technology, the purpose of this invention is to provide a reagent kit for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure and its application.

[0005] The first aspect of the present invention provides a biomarker for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure, wherein the biomarker is at least one of F2 protein (coagulation factor II), TFRC protein (transferrin receptor), APOC1 protein (apolipoprotein C1), APOC3 protein (apolipoprotein C3) and HSPA8 protein (heat shock protein A8).

[0006] The second aspect of the present invention provides the use of reagents for detecting the biomarkers described in the first aspect in the preparation of products for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure.

[0007] According to the above application, preferably, the product is used to detect the expression level of the biomarker in the sample by immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), iPRM, chromatography-mass spectrometry (GC-MS), or mass spectrometry. More preferably, the chromatography is liquid chromatography.

[0008] According to the above application, preferably, the product contains an antibody that specifically binds to the biomarker or a standard of the biomarker.

[0009] According to the above application, preferably, the antibody is a monoclonal antibody, a polyclonal antibody, or a single-domain antibody.

[0010] According to the above application, preferably, the sample is a blood sample. More preferably, the sample is plasma.

[0011] According to the above applications, preferably, the product is a chip, a formulation, or a reagent kit.

[0012] According to the above application, preferably, when the biomarker is a combination of APOC1 protein and HSPA8 protein; the probability calculation formula for the product to diagnose and predict chronic heart failure with yang deficiency and blood stasis syndrome is: Logit(P) = -1.436-0.006701×HSPA8 +0.000023×APOC1; where Logit(P) represents the probability, HSPA8 represents the expression level of HSPA8 protein, and APOC1 represents the expression level of APOC1 protein.

[0013] A third aspect of the present invention provides a kit containing reagents for detecting the biomarkers described in the first aspect, the kit being used for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure.

[0014] According to the above-described kit, preferably, the reagent is used to detect the expression level of the biomarker in a sample by immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), iPRM, chromatography-mass spectrometry (GC-MS), or mass spectrometry. More preferably, the chromatography is liquid chromatography. According to the kit described above, preferably, the kit contains an antibody that specifically binds to the biomarker and / or a standard of the biomarker.

[0015] According to the kit described above, preferably, the antibody is a monoclonal antibody, a polyclonal antibody, or a single-domain antibody.

[0016] According to the kit described above, preferably, the sample is a blood sample.

[0017] According to the above-mentioned kit, preferably, when the biomarker is a combination of APOC1 and HSPA8; the probability calculation formula for the kit to diagnose and predict chronic heart failure with yang deficiency and blood stasis syndrome is: Logit(P) = -1.436-0.006701×HSPA8 +0.000023×APOC1; where Logit(P) represents the probability, HSPA8 represents the expression level of HSPA8 protein, and APOC1 represents the expression level of APOC1 protein.

[0018] Compared with the prior art, the advantages of this invention are: (1) This invention first discovered that the expression levels of F2 protein, TFRC protein, APOC1 protein, APOC3 protein and HSPA8 protein in the blood of patients with chronic heart failure with Yang deficiency and blood stasis syndrome are significantly different from those in patients with chronic heart failure without Yang deficiency and blood stasis syndrome, and the differences are statistically significant. By detecting the expression levels of F2, TFRC, APOC1, APOC3 and HSPA8 proteins in the blood of patients with chronic heart failure, Yang deficiency and blood stasis syndrome can be effectively diagnosed. It has been verified that when any one of the five biomarkers is used alone for the diagnosis of coronary heart disease with heart failure with Qi deficiency and blood stasis syndrome, the AUC of the ROC curve can reach above 0.75. Therefore, the five biomarkers can be used for the auxiliary diagnosis of chronic heart failure with Yang deficiency and blood stasis syndrome.

[0019] (2) When any two, three, four, or five of the F2, TFRC, APOC1, APOC3, and HSPA8 proteins are combined for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure, the AUC of the ROC curve can reach above 0.77; among them, when APOC1 protein and HSPA8 are combined for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure, the AUC of the ROC curve reaches 0.87, with a sensitivity of 95% and a specificity of 70%; the combination of F2 protein, APOC1 protein, and HSPA8 protein... When used to diagnose Yang deficiency and blood stasis syndrome in chronic heart failure, the AUC of the ROC curve reached 0.87, with a sensitivity of 95% and a specificity of 70%. When the combination of APOC1, TFRC, and HSPA8 proteins was used to diagnose Yang deficiency and blood stasis syndrome in chronic heart failure, the AUC of the ROC curve reached 0.89, with a sensitivity of 95% and a specificity of 70%. When the combination of APOC1, APOC3, TFRC, and HSPA8 proteins was used to diagnose Yang deficiency and blood stasis syndrome in chronic heart failure, the AUC of the ROC curve reached 0.903, with a sensitivity of 85% and a specificity of 80%. When the combination of F2, APOC1, APOC3, TFRC, and HSPA8 proteins was used to diagnose Yang deficiency and blood stasis syndrome in chronic heart failure, the AUC of the ROC curve reached 0.903, with a sensitivity of 80% and a specificity of 85%. Therefore, combining any two, three, four, or five of the F2, TFRC, APOC1, APOC3, and HSPA8 proteins can significantly improve the diagnostic efficacy of Yang deficiency and blood stasis syndrome in chronic heart failure. This combination has strong diagnostic potential and reliability, providing clinicians with a new reference for diagnosing Yang deficiency and blood stasis syndrome in chronic heart failure. It also provides a widely applicable molecular basis for the precise treatment of Yang deficiency and blood stasis syndrome in chronic heart failure.

[0020] (3) The test sample of the kit of the present invention is blood, which can avoid invasive diagnosis. The diagnosis of chronic heart failure with yang deficiency and blood stasis can be achieved by taking blood through minimally invasive means. It requires less blood, causes less pain to the test subjects, and has high compliance. Moreover, it is simple to operate and the test results are obtained in a short time, which has broad market prospects and social benefits.

[0021] (4) Based on the screened protein markers, this invention constructs a diagnostic model for chronic heart failure with Yang deficiency and blood stasis syndrome with good sensitivity and specificity, realizing accurate identification and classification of chronic heart failure with Yang deficiency and blood stasis syndrome, and improving the scientificity and standardization of TCM diagnosis. Attached Figure Description

[0022] Figure 1The results of DIA proteomics screening for differentially expressed proteins for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure were characterized. The results included: (A) PCA analysis results of the HC, HF-YXXYZ, and HF-NYXXYZ groups; (B) Volcano plot of differentially expressed proteins between the HF-YXXYZ and HC groups; (C) Volcano plot of differentially expressed proteins between the HF-NYXXYZ and HC groups; (D) Venn diagram of differentially expressed proteins between the HF-YXXYZ and HC groups and between the HF-NYXXYZ and HC groups; (E) KEGG pathway enrichment analysis results of differentially expressed proteins; (F) PPI network analysis results of differentially expressed proteins; (G) Interaction network diagram of core differentially expressed proteins; (H) LASSO screening results; (I) SVM screening results; (J) RF screening results; and (K) Venn diagrams of LASSO, SVM, and RF screening results. Figure 2 ROC curves for five protein biomarkers used in the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure are shown below: A is the ROC curve of F2 protein; B is the ROC curve of TFRC protein; C is the ROC curve of APOC1 protein; D is the ROC curve of APOC3 protein; and E is the ROC curve of HSPA8 protein. Figure 3 The results of iPRM assay for the expression levels of F2 protein, TFRC protein, APOC1 protein, APOC3 protein, and HSPA8 protein in the blood of patients with chronic heart failure and Yang deficiency and blood stasis syndrome; Figure 4 ROC curves for five protein biomarkers in the external cohort for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure are shown below: A is the ROC curve of F2 protein; B is the ROC curve of TFRC protein; C is the ROC curve of APOC1 protein; D is the ROC curve of APOC3 protein; E is the ROC curve of HSPA8 protein; and F is the ROC curve of the combination of APOC1 and HSPA8 proteins for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below with reference to specific embodiments.

[0024] The following detailed description is exemplary and intended to provide further illustration of the invention. Unless otherwise specified, 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 invention pertains.

[0025] It should be noted that the terminology used herein is for the purpose of describing specific embodiments only and is not intended to limit the exemplary embodiments of the present invention. Experimental methods in the following embodiments, unless otherwise specified, employ conventional techniques in this art or follow the conditions recommended by the manufacturer; reagents or instruments whose manufacturers are not specified are all commercially available conventional products.

[0026] Example 1: Screening of protein biomarkers and preliminary evaluation of their diagnostic value for chronic heart failure with yang deficiency and blood stasis syndrome 1. Experimental Samples Between June 2022 and July 2023, 80 eligible subjects were enrolled from the outpatient department of the Department of Cardiovascular Diseases at the First Affiliated Hospital of Henan University of Traditional Chinese Medicine or from surrounding communities. Among them, 30 patients with chronic heart failure of Yang deficiency and blood stasis syndrome (denoted as HF-YXXYZ group), 30 patients with chronic heart failure without Yang deficiency and blood stasis syndrome (denoted as HF-NYXXYZ group), and 20 healthy controls (denoted as HC group).

[0027] Inclusion and exclusion criteria: Patients meeting the following criteria were eligible for inclusion: 1) Age 40-80 years; 2) Patients with chronic heart failure meeting the 2018 Chinese Guidelines for the Diagnosis and Treatment of Heart Failure and the 2022 AHA / ACC / HFSA Guidelines for the Management of Heart Failure; 3) Patients with heart failure of Yang deficiency and blood stasis syndrome or heart failure without Yang deficiency and blood stasis syndrome meeting the guidelines for the diagnosis and treatment of chronic heart failure using traditional Chinese medicine (2022); 4) Left ventricular ejection fraction (LVEF) ≤50% on echocardiography using the modified Simpson method; 5) NYHA functional class II-IV; 6) Written informed consent obtained. Healthy adults with normal physical examinations were also included. To reduce diagnostic bias and improve consistency, all researchers completed standardized training in TCM syndrome differentiation, including a 4-hour workshop and certification exam. Subsequently, two independent associate chief TCM physicians conducted syndrome differentiation strictly according to the guidelines for the diagnosis and treatment of chronic heart failure without knowing the patients' biochemical and imaging data. Diagnostic discrepancies were resolved through group discussions with a third senior TCM expert. Exclusion criteria include: 1) pulmonary embolism, acute coronary syndrome or acute cerebrovascular disease; 2) other heart diseases, such as valvular heart disease, severe valvular abnormalities, myocardial disease, congenital heart disease, pulmonary heart disease, etc.; 3) liver and kidney dysfunction, malignant tumors or autoimmune diseases; 4) mental illness or drug abuse; 5) pregnancy, planned pregnancy or breastfeeding.

[0028] The demographic and clinical biochemical parameters of the 80 subjects are shown in Table 1. There were no significant differences in gender, sitting diastolic blood pressure (DBP), and body mass index (BMI) among the HF-YXXYZ group, HF-NYXXYZ group, and HC group.P >0.05), but there were differences in age, sitting systolic blood pressure (SBP), total cholesterol, triglycerides, low-density lipoprotein cholesterol, glucose, and prothrombin time and activated partial thromboplastin time levels, reflecting glucose and lipid metabolism disorders and coagulation dysfunction in heart failure patients. There were no statistically significant differences in age, sex, SBP, DBP, BMI, comorbid medical history, and laboratory data between the HF-YXXYZ and HF-NYXXYZ groups.

[0029]

[0030] 2. Comparative analysis of cardiac function indicators between the HF-YXXYZ group and the HF-NYXXYZ group The cardiac function indicators (NYHA cardiac function classification, NT-proBNP, LVEF, LVEDD, LVEDV, SV, and 6-minute walking distance) of the HF-YXXYZ group and the HF-NYXXYZ group in the above experimental samples were detected, compared and analyzed.

[0031] NYHA Classification of Heart Failure: ① Class I (Compensated Heart Failure): The patient has heart disease, but their daily activity level is not restricted. Normal, mild activity does not cause fatigue, palpitations, shortness of breath, or angina. ② Class II (Heart Failure I): The patient usually has no noticeable symptoms at rest, but may experience fatigue, palpitations, shortness of breath, or angina during daily activities. ③ Class III (Heart Failure II): The patient's physical activity is significantly restricted; even activity below normal intensity causes the above symptoms. ④ Class IV (Heart Failure III): The patient is unable to perform any physical activity; symptoms of heart failure occur even at rest, and these symptoms are significantly aggravated upon engaging in physical activity.

[0032] NT-proBNP detection: The NT-proBNP level of the subjects was detected using a colloidal gold detection kit (Nanjing Getein Biotechnology Co., Ltd., catalog number 6033200811).

[0033] Echocardiography: A color Doppler ultrasound diagnostic instrument (GE Vivid E95, USA) with an M5S probe was used, with a frequency of 1.7–3.4 MHz and a frame rate of 40–80 Hz / s. Two-dimensional ultrasound Simpson method was used to acquire 3–5 cardiac cycles of apical four-chamber and apical two-chamber views to detect left ventricular ejection fraction (LVEF), left ventricular end-diastolic dimension (LVEDD), left ventricular end-diastolic volume (LVEDV), and stroke volume (SV).

[0034] 6-minute walk distance (6MWD): This is assessed by researchers who have undergone standardized training. Subjects walk as fast as possible in a straight corridor to measure their 6MWD.

[0035] The results of the comparative analysis of cardiac function indicators between the HF-YXXYZ group and the HF-NYXXYZ group are shown in Table 2. Compared with the HF-NYXXYZ group, patients in the HF-YXXYZ group had higher levels of NT-proBNP and LVEF, and a greater number of patients in the NYHA functional class III to IV. Their 6WMD level was also lower, reflecting that the cardiac function impairment in the HF-YXXYZ group was more severe and that the disease was in a later stage.

[0036]

[0037] 3. Screening of protein biomarkers and preliminary evaluation of their diagnostic value for Yang deficiency and blood stasis syndrome in chronic heart failure. DIA quantitative proteomics technology was used to detect proteins in plasma samples from coronary heart disease patients with heart failure due to Yang deficiency and blood stasis, those without Yang deficiency and blood stasis, and healthy individuals. P The threshold for significant differential expression was 0.05 and FC < 0.67 or FC > 1.5. Differentially expressed proteins (DEPs) in the syndrome of Yang deficiency and blood stasis in chronic heart failure were screened by (HF-YXXYZ.vs.HC)-(HF-NYXXYZ.vs.HP).

[0038] The specific steps are as follows: Whole blood was collected using EDTA anticoagulant tubes, and plasma was obtained by centrifugation and stored at -80°C for subsequent analysis. To reduce interference from high-abundance proteins, BioRAD proteominer beads were used to remove high-abundance proteins from the plasma samples. Total protein was then extracted using lysis buffer and subjected to reductive alkylation. Protein concentration was determined using the Bradford method, and the protein sample quality was verified by SDS-polyacrylamide gel electrophoresis. Subsequently, trypsin was used to digest the proteins, generating a peptide mixture, which was then desalted and purified using a C18 desalting column. After reconstitution and centrifugation, 200 ng of the supernatant was collected for liquid chromatography-mass spectrometry (LC-MS) analysis.

[0039] The ultra-high performance liquid chromatography (UHPLC) system was upgraded using the Vanquish Neo nano-system. The pre-column was 174500 nm (5 mm × 300 μm, 5 μm, Thermo), heated in a column oven at 50 °C. The analytical column was an ES906 (PepMap™ NeoUHPLC 150 µm x 15 cm, 2 μm, Thermo). HPLC elution conditions are shown in Table 3. Mass spectrometry was performed using a Thermo Orbitrap Astral mass spectrometer in data-independent acquisition (DIA) mode, obtaining raw data (.raw format).

[0040] Using the DIA-NN database search software, based on the homo_sapiens_uniprot_2023_10_18_Swisprot.fasta (20427 sequences) database, the original data underwent in-depth analysis, retaining only peptide spectrum matches (PSMs) and proteins with a confidence level exceeding 99%. A t-test was used for statistical analysis of any two groups. P <0.05 and FC <0.67 or P Proteins with a concentration <0.05 and a functional group (FC) >1.5 were defined as differentially expressed proteins (DEPs). GO and KEGG enrichment analyses were performed on the DEPs. Protein-protein interaction relationships among the differentially expressed proteins (Homo sapiens) were queried using the STRING database, and a network diagram of the DEPs was constructed using Cytoscape software.

[0041]

[0042] Results of DIA quantitative proteomics analysis: PCA (Principal Component Analysis) was performed on the DIA protein quantification results of the HC, HF-YXXYZ, and HF-NYXXYZ groups. The results are as follows: Figure 1 As shown in Figure A. Figure 1 As shown in A, there is a large difference between the HF-YXXYZ group and the HF-NYXXYZ group and the HC group, while the distribution within the group is relatively clustered, indicating good repeatability.

[0043] The DESeq2 software was used to analyze the differences in protein expression levels between groups, with FC>1.5 and... P Using <0.05 as a criterion, differentially expressed proteins that are upregulated were screened, with FC <0.67 and... P <0.05 was used as a criterion for screening downregulated differentially expressed proteins. Results showed a total of 610 DEPs in the HF-YXXYZ and HC groups, of which 317 were upregulated and 293 were downregulated (e.g., ...). Figure 1 (As shown in B); HF-NYXXYZ and HC groups have a total of 150 DEPs, of which 78 DEPs were increased and 72 DEPs were decreased (e.g., Figure 1 (As shown in C). Cross-analysis of DEGs between the HF-YXXYZ and HC groups and DEPs between the HF-NYXXYZ and HC groups using Venn plots identified 545 DEPs specific to the Yang deficiency and blood stasis syndrome of chronic heart failure (denoted as HF-YXXYZ syndrome), of which 272 DEPs were upregulated and 273 DEPs were downregulated (e.g., ...). Figure 1 (As shown in D). KEGG pathway enrichment analysis was performed on 545 DEPs specific to HF-YXXYZ syndrome. The results showed that these DEPs were mainly enriched in immune-inflammatory and coagulation-related pathways, including the NF-κB signaling pathway, B cell receptor signaling pathway, FcγR-mediated phagocytosis, complement and coagulation cascades, etc. (e.g., Figure 1 E is shown.

[0044] To further explore the key proteins of the HF-YXXYZ evidence, based on the 545 HF-YXXYZ evidence-specific DEPs identified, a protein-protein interaction network (e.g., ) was constructed and optimized in Cytoscape software using the STRING database (https: / / cn.string-db.org / ). This network contains 205 nodes and 307 edges. Figure 1 As shown in F), the PPI network was analyzed using the Maximum Clique Centrality (MCC) algorithm and the Degree algorithm via CytoHubba analysis, which identified 14 core DEPs with high centrality and intermediateness (e.g., ...). Figure 1 (As shown in G). LASSO regression analysis was performed on 14 core DEPS, from which 9 characteristic proteins (such as G) were identified. Figure 1 (As shown in H). The Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithm was used to screen 14 core DEPs, identifying 8 characteristic proteins (such as...). Figure 1 As shown in Figure I). The Random Forest (RF) algorithm was used to screen the 14 core DEPs, identifying 8 characteristic proteins (such as...). Figure 1 (As shown in J). By taking the intersection of the characteristic proteins selected by the above LASSO regression analysis, SVM-RFE algorithm, and RF algorithm using the Vigengraph, five candidate protein biomarkers were obtained, namely: coagulation factor II (F2), transferrin receptor (TFRC), apolipoprotein C1 (APOC1), apolipoprotein C3 (APOC3), and heat shock protein A8 (HSPA8) (as shown in J). Figure 1 (as shown in K).

[0045] Further analysis was conducted using SPSS 27.0 to analyze the expression levels of F2, TFRC, APOC1, APOC3, and HSPA8 proteins in the HF-YXXYZ and HF-NYXXYZ groups. The ability of these five candidate protein biomarkers to independently diagnose and differentiate between HF-YXXYZ and HF-NYXXYZ syndromes (chronic heart failure without Yang deficiency and blood stasis) was performed. The corresponding AUC, 95% confidence interval (calculated using the DeLong nonparametric method), sensitivity, and specificity were calculated. Following the principle of maximizing the Youden index, the expression level of the protein biomarker corresponding to the maximum Youden index was taken as the cut-off value. If the expression levels (abundance values) of F2, TFRC, APOC1, and APOC3 proteins were higher than their corresponding cut-off values, the syndrome was classified as HF-YXXYZ (positive). Conversely, if the expression level (abundance value) of HSPA8 protein was lower than its cut-off value, the syndrome was classified as HF-YXXYZ (positive). ROC curves were plotted using GraphPad Prism 10 to differentiate HF-YXXYZ syndrome from HF-NYXXYZ syndrome using five candidate protein biomarkers for individual diagnosis (e.g., ...). Figure 2 (as shown in the figure), and its AUC value, sensitivity, specificity and Youden index were statistically analyzed. The results are shown in Table 4.

[0046] Depend on Figure 2As shown in Table 4, the results indicate that the AUC values ​​of the ROC curves for differentiating HF-YXXYZ from HF-NYXXYZ using F2, TFRC, APOC1, APOC3, and HSPA8 alone were 0.84, 0.874, 0.931, 0.796, and 0.707, respectively, all exceeding 0.70. This demonstrates that each of the five protein markers can distinguish HF-YXXYZ from HF-NYXXYZ, and that all five protein markers can be used for auxiliary diagnostic differentiation between HF-YXXYZ and HF-NYXXYZ.

[0047]

[0048] Example 2: Validation of the value of protein biomarkers in the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure 1. Experimental Samples: From June to September 2023, 50 eligible subjects were enrolled from the outpatient clinic of the Department of Cardiovascular Medicine at the First Affiliated Hospital of Henan University of Traditional Chinese Medicine or from surrounding community clinics. Among them, 20 patients with chronic heart failure exhibiting Yang deficiency and blood stasis syndrome (HF-YXXYZ group), 20 patients with chronic heart failure without Yang deficiency and blood stasis syndrome (HF-NYXXYZ group), and 10 healthy controls (HC group) were included. The inclusion and exclusion criteria were as follows: 1) Age 40-80 years; 2) ... Patients meeting the criteria for inclusion in the study included: 1) Patients with chronic heart failure meeting the 2018 Chinese Guidelines for the Diagnosis and Treatment of Heart Failure and the 2022 AHA / ACC / HFSA Guidelines for the Management of Heart Failure; 2) Patients with heart failure of Yang deficiency and blood stasis syndrome or heart failure without Yang deficiency and blood stasis syndrome as defined in the 2022 Guidelines for the Diagnosis and Treatment of Chronic Heart Failure in Traditional Chinese Medicine; 3) Patients with left ventricular ejection fraction (LVEF) ≤50% on echocardiography using the modified Simpson method; 4) Patients with NYHA functional class II to IV; and 5) Patients with written informed consent. The inclusion criteria for the healthy control group were subjects with normal physical examination results. Exclusion criteria included: 1) Pulmonary embolism, acute coronary syndrome, or acute cerebrovascular disease; 2) Other heart diseases, such as valvular heart disease, severe valvular abnormalities, myocardial disease, congenital heart disease, pulmonary heart disease, etc.; 3) Liver and kidney dysfunction, malignant tumors, or autoimmune diseases; 4) Mental illness or drug abuse; and 5) Pregnancy, planned pregnancy, or breastfeeding.

[0049] 2. Verification of the value of protein biomarkers in the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure Fasting venous blood was collected in the morning from patients with infarct-associated heart failure (IHF) and healthy controls (HC) using EDTA anticoagulant tubes, with a blood volume of ≥3 mL per tube. After collection, the tubes were gently inverted to mix and pretreated within 2 hours. The whole blood was centrifuged at 3000×g for 15 minutes at 4°C, and the supernatant plasma was carefully separated, aliquoted into enzyme-free EP tubes, and stored at -80°C.

[0050] iPRM Targeted Proteomics Detection Method: (1) Sample Preparation: Mix BioRAD proteominer bead with plasma sample, centrifuge, wash, elute with TFA, collect supernatant and freeze-dry. Dissolve protein precipitate with DB protein lysis buffer, add DTT reaction and ice bath, then add IAM reaction. After Bradford protein quantification and SDS-PAGE gel electrophoresis quality control, perform proteolytic digestion: make up the volume with DB protein lysis buffer, add trypsin and TEAB buffer and CaCl2 for enzymatic digestion, adjust pH and centrifuge, take supernatant and pass through C18 desalting column, wash, elute and freeze-dry. (2) Preliminary Experiment: Prepare mobile phase A and B, dissolve freeze-dried powder with A, centrifuge and take supernatant for injection. Use Vanquish Neo nano-scale UHPLC system, set column temperature, pre-column and analytical column, and run according to specific liquid chromatography elution conditions (as shown in Table 5). A Thermo orbitrap astral mass spectrometer with an Easy-spray ion source was used. Parameters such as ion spray voltage and ion transmission tube temperature were set. Peptide information was acquired using the Data-Independent Acquisition (DIA) mode, generating raw data files (.raw) for mass spectrometry detection. Spectronaut software was used to perform protein identification and quantitative analysis on the generated raw data, screening out target peptides and generating an iPRMList containing their parent ion information. (3) Formal Experiment: The chromatographic method for the formal experiment was the same as that for the preliminary experiment. Equal amounts of peptides were taken from each sample after enzymatic digestion, and equal amounts of iRT peptides were incorporated into each sample as internal standards. The iPRMList obtained above was imported into the mass spectrometry acquisition method settings file and edited to form the iPRM acquisition method. Mass spectrometry acquisition mode: FullMS-PRM. FullMS resolution 240,000, AGC set to 500%, MaxIT 100ms, scan range 350-1200 m / z; PRM resolution 80,000, AGC set to 500%, MaxIT 10ms; isolation window 1.6 m / z. iPRM data were directly imported into Spectronaut, and the Direct DIA module was selected for analysis, with parameter settings consistent with the preliminary experiment.

[0051]

[0052] The results of iPRM targeted proteomics detection of the expression levels of five protein markers in the HF-YXXYZ, HF-NYXXYZ, and HC groups are as follows: Figure 3 As shown. By Figure 3The results showed that the expression levels (abundance values) of F2, TFRC, APOC1, and APOC3 proteins in the HF-YXXYZ group were significantly higher than those in the HF-NYXXYZ group, while the expression level (abundance value) of HSPA8 protein was significantly lower in the HF-NYXXYZ group. All these differences were statistically significant. P <0.05).

[0053] Further analysis was conducted using SPSS 27.0 to analyze the expression levels of five protein biomarkers in the HF-YXXYZ and HF-NYXXYZ groups obtained from iPRM detection. The ability of each biomarker to independently diagnose and differentiate HF-YXXYZ from HF-NYXXYZ was analyzed. The corresponding AUC, 95% confidence intervals of AUC (calculated using the DeLong nonparametric method), sensitivity, and specificity were calculated. Following the principle of maximizing the Youden index, the expression level of the protein biomarker corresponding to the maximum Youden index was taken as the cut-off value. If the expression levels (abundance values) of F2, TFRC, APOC1, and APOC3 proteins were higher than their corresponding cut-off values, it was considered a positive result for HF-YXXYZ; if the expression level (abundance value) of HSPA8 was lower than its cut-off value, it was considered a positive result for HF-YXXYZ. ROC curves were plotted using GraphPad Prism 10 (e.g.,...). Figure 4 (as shown in the figure), and its AUC value, sensitivity, specificity and Youden index were statistically analyzed. The results are shown in Table 6.

[0054]

[0055] Table 6 shows that the AUC values ​​of the ROC curves for differentiating HF-YXXYZ syndrome from HF-NYXXYZ syndrome using F2 protein, TFRC protein, APOC1 protein, APOC3 protein, and HSPA8 protein alone were 0.755 (0.595, 0.915), 0.793 (0.652, 0.933), 0.755 (0.633, 0.917), 0.753 (0.602, 0.903), and 0.80 (0.654, 0.946), respectively, all exceeding 0.75. This indicates that each of the five protein markers can distinguish between HF-YXXYZ and HF-NYXXYZ, demonstrating that all five markers can be used for auxiliary diagnostic differentiation of these two syndromes.

[0056] To evaluate the diagnostic efficacy of combinations of five protein biomarkers (F2, TFRC, APOC1, APOC3, and HSPA8) in differentiating between HF-YXXYZ and HF-NYXXYZ syndromes, a series of logistic regression models were constructed and compared. The method for constructing the logistic regression models was as follows: the abundance data of the five protein biomarkers from all patients in the HF-YXXYZ and HF-NYXXYZ groups were imported into SPSS 21.0 software. Using syndrome grouping (HF-YXXYZ = 1, HF-NYXXYZ = 0) as the dependent variable and the expression levels (abundance values) of the five protein biomarkers as independent variables, logistic regression models were constructed for different combinations of biomarkers. Model combinations included: all possible combinations of two, three, four, and all five protein biomarkers. For each Logistic regression model, its predicted probability value was calculated, and receiver operating characteristic (ROC) curve analysis was performed to calculate the area under the curve (AUC). The optimal diagnostic cutoff value and its corresponding sensitivity and specificity were determined based on the maximum value of the Youden index. The method for determining the results of using the Logistic regression model to differentiate between HF-YXXYZ syndrome and HF-NYXXYZ syndrome was as follows: the expression level (i.e., abundance value) of the protein marker was input into the Logistic regression equation, and the predicted probability value was calculated. If the predicted probability value was greater than the optimal diagnostic cutoff value, the patient was determined to have chronic heart failure with Yang deficiency and blood stasis syndrome. The statistical results of AUC, cutoff value, sensitivity, specificity, and Youden index of all constructed Logistic regression models in differentiating between HF-YXXYZ syndrome and HF-NYXXYZ syndrome are shown in Table 6.

[0057] Based on the AUC values ​​in Table 6, all constructed Logistic regression models were sorted from largest to smallest according to their predicted AUC values ​​for the HF-YXXYZ syndrome. If there were no statistically significant differences in the AUC values ​​of the five models pairwise, the model with the fewest independent variables was selected as the optimal diagnostic model, following the principle of parsimony. If there were differences in AUC values, the model with the highest AUC was selected as the optimal diagnostic model. Based on AUC value ranking analysis, the top five Logistic regression models are: the Logistic regression model obtained by combining APOC1+APOC3+TFRC+HSPA8, the Logistic regression model obtained by combining F2+APOC1+APOC3+TFRC+HSPA8, the Logistic regression model obtained by combining APOC1+TFRC+HSPA8, the Logistic regression model obtained by combining F2+APOC1+HSPA8, and the Logistic regression model obtained by combining APOC1+HSPA8 (the Logistic regression equation of this model is: Logit(P) = -1.436-0.006701×HSPA8 +0.000023×APOC1; Logit(P) represents probability, HSPA8 represents the expression level of HSPA8 protein, and APOC1 represents the expression level of APOC1 protein). The AUC values ​​of the ROC curves of the five Logistic regression models used to diagnose and differentiate HF-YXXYZ syndrome and HF-NYXXYZ syndrome all reached above 0.86, which is significantly higher than the AUC values ​​of the five protein biomarkers used for diagnosis alone. This indicates that the five Logistic regression models can be used to diagnose and differentiate HF-YXXYZ syndrome and HF-NYXXYZ syndrome and have good diagnostic value.

[0058] The pairwise Delong test was performed on the AUC of the five Logistic regression models obtained from the above screening, and the results are shown in Table 7.

[0059]

[0060] As shown in Table 7, there was no statistically significant difference in the pairwise AUC values ​​of these five models. P >0.05), and based on the principle of simplicity, the APOC1+HSPA8 combined model was ultimately selected as the optimal diagnostic model. The AUC value of this model's ROC curve was 0.87 (0.76, 0.98), significantly higher than the AUC of the five protein biomarkers alone, with a sensitivity of 95% and a specificity of 70.00% (see [link to relevant documentation]). Figure 4 F) indicates that the APOC1+HSPA8 combined model is more conducive to the diagnostic differentiation of HF-YXXYZ and HF-NYXXYZ, and has strong diagnostic efficacy and reliability. Example

[0061] A kit for diagnosing Yang deficiency and blood stasis syndrome in chronic heart failure, the kit containing reagents for detecting the expression levels of biomarkers. The biomarkers are at least one selected from F2 protein, TFRC protein, APOC1 protein, APOC3 protein, and HSPA8 protein. The reagents are used to detect the expression levels of the protein biomarkers in a sample by immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), iPRM method, liquid chromatography-mass spectrometry (LC-MS), or mass spectrometry, preferably plasma. The reagents contain antibodies that specifically bind to the biomarkers and / or standards for the biomarkers.

[0062] When the biomarker is a combination of APOC1 and HSPA8 proteins, the probability calculation formula for predicting the diagnosis of chronic heart failure with Yang deficiency and blood stasis syndrome using this kit is: Logit(P) = -1.436 - 0.006701 × HSPA8 + 0.000023 × APOC1, where Logit(P) represents the probability, HSPA8 represents the expression level of HSPA8 protein, and APOC1 represents the expression level of APOC1 protein. The diagnostic result interpretation standard for this kit is as follows: input the expression levels (i.e., abundance values) of APOC1 and HSPA8 proteins into the probability calculation formula to obtain the predicted probability value. If the predicted probability value > 0.428, the diagnosis is chronic heart failure with Yang deficiency and blood stasis syndrome.

[0063] The above embodiments are merely illustrative of the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Those skilled in the art can modify or make equivalent substitutions to the technical solutions of the present invention based on the concept of the present invention, without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. The application of a reagent for detecting the expression level of a biomarker in the preparation of a product for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure; wherein the biomarker is at least one of F2 protein, TFRC protein, APOC1 protein, APOC3 protein, and HSPA8 protein.

2. The application according to claim 1, characterized in that, The product is used to detect the expression level of the biomarker in the sample by immunohistochemistry, enzyme-linked immunosorbent assay, iPRM, liquid chromatography-mass spectrometry or mass spectrometry.

3. The application according to claim 2, characterized in that, The product contains antibodies that specifically bind to the biomarker and / or standards for the biomarker.

4. The application according to claim 3, characterized in that, The antibody is a monoclonal antibody, a polyclonal antibody, or a single-domain antibody.

5. The application according to claim 2, characterized in that, The sample is a blood sample; the product is a chip, formulation, or reagent kit.

6. The application according to any one of claims 1-5, characterized in that, When the biomarker is a combination of APOC1 protein and HSPA8 protein, the probability calculation formula for the product in diagnosing and predicting chronic heart failure with yang deficiency and blood stasis syndrome is: Logit(P) = -1.436-0.006701×HSPA8 +0.000023×APOC1, where Logit(P) represents the probability, HSPA8 represents the expression level of HSPA8 protein, and APOC1 represents the expression level of APOC1 protein.

7. A reagent kit, characterized in that, The kit contains reagents for detecting the expression levels of biomarkers, wherein the biomarkers are at least one of F2 protein, TFRC protein, APOC1 protein, APOC3 protein, and HSPA8 protein; the kit is used for the diagnosis of Yang deficiency and blood stasis syndrome in chronic heart failure.

8. The reagent kit according to claim 7, characterized in that, The reagents are used to detect the expression level of the protein biomarkers in the sample by immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), iPRM, liquid chromatography-mass spectrometry (LC-MS) or mass spectrometry.

9. The reagent kit according to claim 8, characterized in that, The reagent contains an antibody that specifically binds to the biomarker and / or a standard of the biomarker.

10. The kit according to any one of claims 7-9, characterized in that, When the biomarker is a combination of APOC1 protein and HSPA8 protein, the probability calculation formula for the kit to diagnose and predict chronic heart failure with yang deficiency and blood stasis syndrome is: Logit(P) = -1.436-0.006701×HSPA8 +0.000023×APOC1, where Logit(P) represents the probability, HSPA8 represents the expression level of HSPA8 protein, and APOC1 represents the expression level of APOC1 protein.

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