Biomarker for detecting coronary heart disease and application thereof

Abstract

The invention discloses a biomarker for detecting coronary heart disease and application of the biomarker, and relates to the technical field of molecular biology and bioinformatics. And the biomarker comprises CTNNB1 (Cytotoxic Nuclear Number B1). The invention provides a novel method for coronary heart disease screening, diagnosis, prognosis evaluation and potential targeted therapy by utilizing the mRNA expression level of the CTNNB1 gene. According to the method, the expression of CTNNB1 mRNA in a peripheral blood sample of a subject is detected through qPCR (quantitative polymerase chain reaction), and the expression levels of CTNNB1 in different crowds are compared, so that a coronary heart disease high-risk individual is identified. According to the method, the protection effect of CTNNB1 in CHD is determined for the first time, effective data of a non-invasive detection means is provided, an important theoretical basis and practical support are provided for CHD screening and precise treatment of old people, and a new direction is provided for a precise intervention strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of molecular biology and bioinformatics, and in particular to a biomarker for detecting coronary heart disease and application thereof. Background Art

[0002] In the context of an aging society, coronary heart disease (CHD) has become a major health burden worldwide, with its morbidity and mortality rates increasing significantly in the elderly. Existing diagnostic methods for CHD mainly rely on clinical examinations and imaging techniques, such as coronary angiography and blood biochemical tests. However, these traditional methods are somewhat invasive and costly, and lack sensitivity in early CHD screening, making it difficult to meet the needs of an aging society for non-invasive, efficient, and accurate diagnosis.

[0003] In recent years, genomic studies have gradually revealed genetic susceptibility genes associated with CHD risk, but these studies have mainly focused on traditional lipid metabolism and blood pressure regulation genes (such as LDL, HDL and APOE, etc.), and have limited contribution to individualized risk assessment, especially in the elderly. In contrast, the role of aging-related genes (ARGs) in the occurrence and development of CHD has not been fully studied, especially the CTNNB1 (also known as Beta-Catenin, β-catenin) gene as a key factor in ARGs, although it plays an important role in the Wnt signaling pathway, participates in cell proliferation and differentiation, and its abnormal expression may affect vascular health, but its specific protective mechanism in CHD is still unclear. Understanding the genetic basis between aging and coronary heart disease can provide new insights into its pathogenesis and potential therapeutic targets. Summary of the invention

[0004] The purpose of the present invention is to provide a biomarker for detecting coronary heart disease and its application, so as to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] Technical solution 1: A biomarker for detecting coronary heart disease, wherein the biomarker includes CTNNB1.

[0007] Technical Solution 2: A detection reagent for detecting coronary heart disease, the detection reagent comprising a reagent for detecting the biomarker.

[0008] Technical solution three: A kit for detecting coronary heart disease, the kit comprising the detection reagent.

[0009] Technical Solution 4: A biochip for detecting coronary heart disease, the biochip comprising the detection reagent.

[0010] Technical Solution 5: Application of the biomarker in the preparation of detection reagents for diagnosing patients with coronary heart disease.

[0011] Technical Solution 6: Application of the detection reagent, the test kit and the biochip in the preparation of diagnostic products for coronary heart disease.

[0012] Furthermore, the diagnostic product is used for screening, diagnosis and / or prognosis assessment of coronary heart disease.

[0013] The present invention discloses the following technical effects:

[0014] The present invention strictly screened and determined the causal relationship between the CTNNB1 gene and CHD through Mendelian randomization (MR) analysis, revealing the key mechanism of CTNNB1 in alleviating CHD. The MR method uses gene variation as an instrumental variable, which can effectively control confounding factors and reverse causality, thereby verifying the protective effect of CTNNB1 at the genetic level. In addition, the present invention further combines transcriptomics and single-cell analysis to explore the differential expression of CTNNB1 in CHD-related cells from multiple dimensions, revealing the mechanism of action of this gene in maintaining vascular health and alleviating inflammatory response. In order to verify the potential clinical application value of CTNNB1, the present invention further verified the expression of CTNNB1 by qPCR, and the results showed that it has high sensitivity and specificity in CHD screening (CTNNB1 can be detected by qPCR or ELISA alone, and CHD high-risk individuals can be efficiently screened under non-invasive conditions). This discovery of the present invention has laid a solid foundation for CTNNB1 as a biomarker for early screening and personalized treatment of CHD, and demonstrated its great application potential in non-invasive detection. This invention clarifies for the first time the protective effect of CTNNB1 in CHD and provides effectiveness data of non-invasive detection methods, which provides important theoretical basis and practical support for CHD screening and precision treatment in the elderly population and provides a new direction for precision intervention strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 For technology roadmap;

[0017] Figure 2Scatter plot of the estimated Mendelian randomization effect for gene CTNNB1 and coronary heart disease;

[0018] Figure 3 The chromosome localization map of gene CTNNB1 (A), the group comparison map of gene CTNNB1 in the coronary heart disease group and the control group in the integrated GEO dataset (B), the ROC curve of gene CTNNB1 in the integrated GEO dataset (C) and the protein-protein interaction network of gene CTNNB1 and its related genes calculated by STRING database (D), where * represents p value < 0.05, which is statistically significant, and AUC has a certain accuracy when it is 0.7-0.9, purple is the coronary heart disease (CHD) group, and cyan is the control group;

[0019] Figure 4 Quality control of single-cell datasets; A is a bubble chart visualization of the expression levels of hub genes in four cell types: Tissue stem cells, Endothelial cells, Smooth muscle cells, and Monocytel; B is the use of the R package SingleR to identify cell clusters into a total of four cell types (Fig.9E), namely Tissue stem cells, Endothelial cells, Smooth muscle cells, and Monocyte;

[0020] Figure 5 This is a laboratory qPCR validation graph. The ordinate is the expression level of CTNNB1. The Normal group is a group of 45 healthy people. The NCAD group is a group of 45 patients with hypertension, diabetes, and hyperlipidemia after excluding coronary heart disease. The CAD group is a group of 38 patients with a definite diagnosis of coronary heart disease.

[0021] Figure 6 The present invention obtains the transcriptome coronary heart disease data set through the GEO database and uses R language data analysis to analyze the ROC;

[0022] Figure 7 The AUC results of the single-cell data set obtained by the present invention through the GEO database for R language data analysis: the AUC scores of single-cell cluster differentially expressed genes (scDEGs) are visualized in the UMAP graph (A) and the group comparison graph (B) between different cell clusters;

[0023] Figure 8 Clinical data set of 128 patients from 2 centers, such as gender, age, VLDL, LDL, HDL, APOE, etc.;

[0024] Fig. 9This is the normalized 128-column patient CTNNB1 partial data table;

[0025] Fig.10 ROC results of combined patient clinical data and laboratory qPCR data of CTNNB1 using R language data analysis;

[0026] Fig.11 ROC results of R language data analysis combining patient clinical data and laboratory qPCR data of CTNNB1. DETAILED DESCRIPTION

[0027] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0028] It should be understood that the terms described in the present invention are only for describing a particular embodiment and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. The intermediate value in any stated value or stated range, and each smaller range between any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0029] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art. Although the present invention describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials associated with the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0030] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present invention description and examples are exemplary only.

[0031] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0032] The present invention screened out the aging-related gene CTNNB1, which is significantly causally associated with coronary heart disease, through Mendelian randomization (MR) analysis, metabolic biomarker analysis, transcriptome analysis, gene function enrichment analysis and single-cell RNA sequencing (scRNA-seq), and revealed its protective regulatory role in coronary heart disease. For details of the technical roadmap, please see Figure 1 .

[0033] Example 1

[0034] Specific steps to screen and validate CTNNB1 as a key gene for diagnosis, prognosis and treatment of coronary heart disease:

[0035] 1. Select working variables

[0036] Based on the aging-related gene expression data obtained from the eQTLGen database, cis-eQTLs significantly associated with CTNNB1 expression were selected as instrumental variables (SNPs). These SNPs met the strict criteria of p-value < 5e-08 and F-statistic > 10 to ensure the robustness of the instrumental variables. LD clumping filtering (r2 < 0.001) was used to remove SNPs with high linkage disequilibrium and retain only independent genetic variations. Specifically, 183 genes were obtained by intersecting 252 aging-related genes with 19128 genes in eQTLGen. Then, the cis-eQTL data of these 183 genes were analyzed with coronary heart disease (CHD) by TwoSampleMR. The p.value < 0.05 after Bonferroni correction was used as the screening condition for significant causality, and genes with strong causal association with CHD were further determined.

[0037] The results showed that there was a causal relationship between the CTNNB1 gene and coronary heart disease (CHD), β = -0.164385101, odds ratio (OR) = 0.85 (95% confidence interval: 0.78, 0.93) and P value = 0.000214069. And there was a negative correlation between the gene CTNNB1 and the risk of CHD. The scatter plot of the Mendelian randomization effect estimate of the gene CTNNB1 and CHD is shown in Figure 2 , it can be seen from the figure that the intercept of the model line on the ordinate is close to 0.

[0038] 2. MR Analysis of Aging-related Genes

[0039] Before conducting the MR analysis, the present invention performed data coordination (Harmonisation) to ensure that the effect allele direction between exposure (CTNNB1 expression) and outcome (coronary heart disease events) was consistent, and SNPs with palindromic structures or allele mismatches were excluded to reduce chain bias. In the MR analysis, the present invention used the inverse variance weighted (IVW) method to estimate the causal effect of CTNNB1 expression on CHD risk. To verify the robustness of the results, the present invention performed a variety of sensitivity analyses, including MR-Egger regression, weighted median method, and weighted mode method. Horizontal pleiotropy (lateral pleiotropy) was evaluated by the MR-Egger intercept test, and the effect of a single SNP on the overall effect was evaluated by Leave-one-out analysis. In addition, the present invention uses the Steiger directional test to verify the directionality of the causal relationship to ensure that genetic variation affects the risk of coronary heart disease by affecting CTNNB1 expression, rather than reverse causality.

[0040] 3. SMR Analysis and Colocalization Analysis

[0041] The present invention uses summary data Mendelian randomization (SMR) and colocalization (coloc) analysis to explore the mediating effect of metabolic biomarkers between CTNNB1 and coronary heart disease. In addition, Bayesian colocalization analysis is used to rank the SNPs located between the gene CTNNB1 and the risk of coronary heart disease ± 50kb. The results show that the p_SMR of the CTNNB1 gene SMR analysis result is <0.05, which further proves that there is a causal relationship between the gene CTNNB1 and coronary heart disease.

[0042] 4. Gene-wide association analysis

[0043] Using the PheWAS Portal and PheWeb databases, a phenomenological Mendelian randomization was performed to identify possible side effects of targeting CTNNB1. The results showed that there was no significant relationship between CTNNB1 and other diseases at the genome-wide significance level in both the PheWeb and PheWAS Portal databases (p value>5e-08).

[0044] 5. Mendelian Multivariate Analysis

[0045] The present invention uses Mendelian multivariate analysis to study the mediating role of metabolic biomarkers between CTNNB1 and coronary heart disease. Specifically, the present invention evaluates whether metabolic markers such as very low density lipoprotein (VLDL) play a mediating role in the effect of CTNNB1 on CHD risk. The present invention performs multivariate MR analysis and calculates the mediating proportion of metabolic features in the total effect.

[0046] 6. Transcriptome Functional Analysis

[0047] Including expression difference, ROC, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analysis, continued to verify the protective effect and diagnostic value of CTNNB1 on coronary heart disease. And revealed the role of CTNNB1 and its related genes in key biological processes and pathways such as Wnt signaling pathway and TGF-β signaling pathway.

[0048] 7. Single Cell RNA Analysis

[0049] The present invention demonstrates the differential expression of CTNNB1 in different cell types (such as endothelial cells, smooth muscle cells, monocytes and tissue stem cells) by principal component analysis (PCA) and unified manifold approximation and projection (UMAP) clustering. Gene activity was evaluated using the AUCell algorithm, and combined with single-cell differentially expressed gene (scDEG) analysis, the activity and differential expression of CTNNB1 in patients with coronary heart disease were further verified. The present invention uses the Wilcoxon rank sum test to evaluate statistical significance, and evaluates the predictive ability of CTNNB1 as a CHD biomarker by receiver operating characteristic (ROC) curve analysis. The results showed that CTNNB1 was significantly underexpressed in the coronary heart disease group, and the ROC analysis suggested that the area under the curve (AUC) was 0.772, indicating that it has potential as a diagnostic biomarker.

[0050] 8. Laboratory qPCR Detection Validation

[0051] RNA was extracted from the peripheral blood of subjects, including young healthy people (Control-1 group), patients with CHD risk factors such as hypertension, hyperlipidemia, and diabetes (Control-2 group), and patients diagnosed with CHD (Patient group). The relative mRNA expression level of the CTNNB1 gene was determined using the qPCR method. Standardization with internal reference genes such as GAPDH ensured data accuracy and comparability. Statistical analysis was performed on the differences in CTNNB1 expression between different groups. Statistical tests (such as ANOVA test) verified that CTNNB1 was significantly lower in the CHD patient group than in the healthy group and non-CHD other disease groups.

[0052] qPCR method: (1) RNA extraction and reverse transcription: The total RNA from peripheral blood was extracted by magnetic bead method (Cat#DA0620, DAAN GENE, China), and reverse transcription was performed using SweScript All-in-one RT SuperMix for qPCR reverse transcription kit (Cat#G3337, Servicebio).

[0053] Nucleic acid amplification: qPCR amplification was performed on an ABI7500 nucleic acid amplifier (Applied Biosystems, Irvine, CA) using the 2xUniversal Blue SYBR Green qPCR Master Mix kit (Cat#G3326, Servicebio). (3) Internal reference data analysis: GAPDH was used as an internal reference gene, and the ΔΔCt method (ΔCt of the experimental group minus ΔCt of the control group) was used to calculate the RQ value to analyze the expression difference of CTNNB1 in different samples.

[0054] The CTNNB1 primer sequences are: CTNNB1-F: 5'-GGCTACTCAAGCTGATTTGATGG-3' (SEQ ID NO.1); CTNNB1-R: 5'-CAGGGAACATAGCAGCTCGT-3' (SEQ ID NO.2); GAPDH-F: 5'-GGAAGCTTGTCATCAATGGAAATC-3' (SEQ ID NO.3); GAPDH-R: 5'-TGATGACCCTTTTGGCTCCC-3' (SEQ ID NO.4).

[0055] The sequence of the CTNNB1 gene is (SEQ ID NO.5):

[0056]

[0057] The present invention verifies the importance of CTNNB1 in coronary heart disease by laboratory q-PCR, and further statistical analysis shows that CTNNB1 has a high predictive ability as a diagnostic biomarker (AUC=0.780).

[0058] The results showed that the chromosome location map of gene CTNNB1 is shown in Figure 3 A. The group comparison of gene CTNNB1 in the coronary heart disease (CHD) group and the control (Control) group of the integrated GEO dataset (CombinedDatasets) is shown in Figure 3 B. ROC curve of gene CTNNB1 in the integrated GEO dataset (Combined Datasets) is shown in Figure 3 C. The protein-protein interaction network (PPI Network) of gene CTNNB1 and its related genes calculated by STRING database is shown in Figure 3 D. CHD, Coronary Heart Disease; PPI Network: Protein-protein Interaction Network, * represents pvalue < 0.05, which is statistically significant, and AUC has a certain accuracy when it is 0.7-0.9. Purple represents the coronary heart disease (CHD) group, and cyan represents the control group.

[0059] Quality control of single-cell datasets can be found in Figure 4 . Figure 4 A: Bubble chart visualization of the expression levels of hub genes in four cell types: tissue stem cells, endothelial cells, smooth muscle cells, and monocytes. The darker the color, the higher the expression level, and the larger the circle, the higher the expression ratio of the gene in the cell population. Figure 4 B: The present invention uses the R package SingleR to identify the cell clusters into a total of 4 cell types (Fig.9E), namely tissue stem cells, endothelial cells, smooth muscle cells, and monocytes.

[0060] Laboratory qPCR validation diagram is shown in Figure 5 The vertical axis is the expression level of CTNNB1. The Normal group consists of 45 healthy people, the NCAD group consists of 45 patients with hypertension, diabetes and hyperlipidemia after excluding coronary heart disease, and the CAD group consists of 38 patients with definite diagnosis of coronary heart disease. Figure 5The results showed that the CHD group had significantly lower levels (statistically significant) compared with the healthy group and the hypertension, diabetes and hyperlipidemia groups after excluding CHD, which suggested that CTNNB1 could be used as an indicator for diagnosing CHD. At the same time, it can be seen that CTNNB1 has a decreasing trend in the healthy group, the hypertension, diabetes and hyperlipidemia groups after excluding CHD, and the CHD group, which also suggested that CTNNB1 could be used as an indicator for the prognosis trend of CHD.

[0061] Figure 6 The present invention obtains the transcriptome coronary heart disease data set through the GEO database and analyzes the ROC through R language data analysis;

[0062] Figure 7 This is the AUC result of the single-cell data set obtained by the present invention through the GEO database for R language data analysis: The AUC score of the single-cell cluster differentially expressed genes (scDEGs) is visualized in the UMAP graph (A) and the group comparison graph (B) between different cell clusters. The lighter the color of the UMAP graph, the higher the AUC score;

[0063] Figure 8 It is a clinical data set of 128 patients from two centers, such as gender, age, VLDL, LDL, HDL, APOE, etc.; the present invention collects 128 columns of patient serum from two hospitals for qPCR original Ct value data table of CTNNB1 gene; Fig. 9 This is the normalized 128-column patient CTNNB1 partial data table, which is the relative expression magnitude after calculating the original Ct value of CTNNB1 (by 2 -ΔΔCt method). Fig.10 and 11 This is the ROC result of R language data analysis combining patient clinical data and laboratory qPCR data of CTNNB1.

[0064] Example 2

[0065] The selected individuals were from the Second Affiliated Hospital of Shandong First Medical University and Rizhao People's Hospital, and met the diagnostic criteria for coronary heart disease. Reference source:

[0066] (1)Knuuti,J.,Wijns,W.,Saraste,A.,Capodanno,D.,Barbato,E.,Funck-Brentano,C.,et al.(2019).2019ESC Guidelines for the diagnosis and management of chronic coronary syndromes.European Heart Journal.

[0067] (2)Andreini,D.,Pontone,G.,Mushtaq,S.,Gransar,H.,Conte,E.,Bartorelli,A.,Pepi,M.,Opolski,M.,óHartaigh,B.,Berman,D.,Budoff,M. ,Achenbach,S.,Al-Mallah,M.,Cademartiri,F.,Callister,T.,Chang,H.-J.,Chinnaiyan,K.,Chow,B.,Cury,R.,...Min,J.(2017).Long-term prognostic impact of CT-Leaman score in patients with non-obstructive CAD:Results from the COronary CT Angiography EvaluatioNFor Clinical Outcomes InteRnational Multicenter(CONFIRM) study.InternationalJournal ofCardiology,231,18-25.

[0068] (3)Caselli, C., Liga, R., Prontera, C., Graaf, MA, Lorenzoni, V., Ragusa, R., Ry, S., Turchetti, G., Chiappino, D., Underwood, SR, Knuuti, J., Scholte, A., Clerico, A., Neglia, D. (2017). High-sensitive cardiac troponin I is associated with the extent of coronary atherosclerosis and predicts outcome in patients with suspected stable CAD.European Heart Journal,38.

[0069] (4) Chinese Journal of General Practitioners. (2020). Guidelines for primary care diagnosis and treatment of stable coronary heart disease (2020).

[0070] (5) Chinese Society of Cardiology. (2022). Chinese expert consensus on the diagnosis and management of ischemic non-obstructive coronary artery disease. Chinese Journal of Cardiology.

[0071] (6) China Medical Foundation. (2024). Diagnostic Guidelines for Coronary Heart Disease (Simplified Version), China Medical Foundation.

[0072] Forty-five healthy young individuals were selected as the Normal group. RNA was extracted from peripheral blood, and the relative mRNA expression of CTNNB1 was determined by qPCR. The results showed that the expression of CTNNB1 was higher in this group.

[0073] 45 patients with hypertension, hyperlipidemia or diabetes (without history of coronary heart disease) were selected as the NCAD group, and the same method was used to detect the expression of CTNNB1. The analysis results showed that the expression of CTNNB1 in this group of individuals was not significantly different from that in the Normal group (p value = 0.7382), suggesting that the expression level of CTNNB1 in healthy people and patients with coronary heart disease risk group but without coronary heart disease did not decrease significantly (not statistically significant).

[0074] 38 patients diagnosed with coronary heart disease were selected as the CAD group, and the relative expression level of CTNNB1 was detected by qPCR. The results showed that the expression of CTNNB1 gene in this group was significantly lower than that in the Normal group and NCAD group (p values ​​were 3.71E-6 and 0.0001, respectively). The median expression of CTNNB1 in the CAD group, NCAD group, and Normal group was 0.15, 0.733, and 1.14, respectively. These results suggest that the expression level of CTNNB1 gradually decreased in the healthy group, patients with coronary heart disease risk group, and patients with coronary heart disease, and decreased significantly in patients with coronary heart disease (statistically significant).

[0075] As mentioned above, the present invention uses the GSE121893 single-cell RNA sequencing data set to show the expression differences of CTNNB1 in different cell types (such as endothelial cells, smooth muscle cells, monocytes, and tissue stem cells) through principal component analysis (PCA) and unified manifold approximation and projection (UMAP) cluster analysis. The AUCell algorithm was used to evaluate gene activity, and the activity and differential expression of CTNNB1 in patients with coronary heart disease were further verified in combination with single-cell differentially expressed gene (scDEG) analysis. The present invention uses the Wilcoxon rank sum test to evaluate statistical significance, and the receiver operating characteristic (ROC) curve analysis is used to evaluate the predictive ability of CTNNB1 as a CHD biomarker. The present invention also uses laboratory q-PCR technology to detect the expression of CTNNB1 in three groups of 127 individuals, and uses the Kruskal-Wallis non-parametric test to compare the expression of CTNNB1 between groups. The results showed that the expression of CTNNB1 in patients with coronary heart disease was significantly reduced in the CAD group compared with the NCAD group and the CAD group compared with the healthy physical examination group, and both were statistically significant (P-value<0.01). The clinical data and routine metabolic test indicators of 127 subjects in three groups were included, and the diagnostic performance of CTNNB1 was analyzed by univariate Logistic regression. The results showed that the AUC between the CAD group and NCAD+Normal, the CAD group and NCAD, the CAD group and Normal, and the NCAD group and Normal were 0.772, 0.762, 0.782, and 0.538, respectively. The P-values ​​of the first three groups were all <0.05, indicating that CTNNB1 has a high efficacy in the diagnosis of coronary heart disease. In multivariate Logistic regression analysis, the OR value of CTNNB1 was 0.389 and the P-value was 0.000372. The standardized regression coefficient was used to evaluate the feature importance, and CTNNB1 ranked first.

[0076] The embodiments described above are only descriptions of the preferred modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A biomarker for detecting coronary heart disease, characterized in that: The biomarkers include CTNNB1.

2. A detection reagent for detecting coronary heart disease, characterized in that: The detection reagent comprises a reagent for detecting the biomarker according to claim 1.

3. A kit for detecting coronary heart disease, characterized in that: The kit comprises the detection reagent as claimed in claim 2.

4. A biochip for detecting coronary heart disease, characterized in that: The biochip comprises the detection reagent as claimed in claim 2.

5. Use of the biomarker according to claim 1 in preparing a detection reagent for diagnosing patients with coronary heart disease.

6. Use of the detection reagent according to claim 2, the kit according to claim 3 and the biochip according to claim 4 in preparing a diagnostic product for coronary heart disease.

7. The use according to claim 6, characterized in that The diagnostic product is used for screening, diagnosis and / or prognosis assessment of coronary heart disease.

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