Application of a group of plasma protein markers in the preparation of a device for predicting acute coronary syndrome in young people

Abstract

The present invention discloses the application of a group of plasma protein markers in the preparation of a device for predicting acute coronary syndrome in young people, and provides a computer device, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the following steps: S1) data reception: receiving the expression levels of six proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in the plasma sample of the patient to be tested; S2) data processing: substituting the expression levels of the six proteins into the prognostic risk prediction model to calculate the risk score value of the patient to be tested suffering from acute coronary syndrome; S3) data output: analyzing the possibility of the patient to be tested suffering from acute coronary syndrome according to the risk score value. The present invention comprehensively predicts the possibility of a patient suffering from ACS by combining a variety of plasma protein schemes.

Description

Technical Field

[0001] The present invention relates to the field of clinical diagnosis, and relates to a group of applications in early diagnosis kits for predicting acute coronary syndrome in young people based on plasma protein detection Background Art

[0002] Acute Coronary Syndrome (ACS) is a clinical syndrome of acute onset of coronary heart disease. It is a disease with coronary artery intimal damage, calcification, lipid deposition and plaque formation as the main pathological manifestations. 1 ACS is currently the leading cause of disability and death in humans, and it seriously endangers human health. 2 With the advancement of diagnostic technology, improved treatment methods and increased social attention to the disease, the mortality rate of ACS has dropped significantly, and the beneficiaries are mainly the elderly. The improvement in the mortality rate of young people is very limited. With the increase of unhealthy lifestyle habits and chronic stress, the incidence of acute coronary syndrome in young people has tended to increase. 3 Young people have completely different disease development characteristics, and most of the theories and foundations of coronary heart disease come from research on the elderly population. 4 , which increases the difficulty of early identification of high-risk young people with ACS. If young people with acute coronary syndrome do not receive timely and effective treatment, it will lead to serious social problems and public health burdens. 5 Therefore, how to effectively screen young patients with acute coronary syndrome at an early stage and identify high-risk young ACS population has important social significance.

[0003] At present, the main methods for clinically diagnosing acute coronary syndrome are: 1. The doctor asks about the medical history and understands the onset symptoms such as chest pain, syncope, heart failure, etc., especially the characteristics of angina symptoms and their inducing factors, and then further examinations are needed. 2. Electrocardiogram examination, in which the typical ischemic electrocardiogram changes are new or transient ST segment depression ≥ 0.1mV, or T wave inversion ≥ 0.2mV. 3. Determination of myocardial injury markers (cTnT, cTnI or CK-MB), the increased level is clearly related to the extent of myocardial infarction and prognosis. 4. Coronary angiography is still the "gold standard" for diagnosing coronary heart disease.

[0004] Olink technology is a new type of high-sensitivity plasma protein detection technology 6, by coupling two specific antibodies to unique DNA oligonucleotide chains respectively, a pair of highly specific proximity probes are formed. A pair of proximity probes is used to perform dual recognition of the target molecule, which has the characteristics of high throughput and can be used for large-scale targeted detection of protein components in plasma. Based on the technology of complementary pairing of DNA oligonucleotide chains, it has the advantages of high sensitivity and high specificity. The detection principle is that after binding with the object to be detected, the probe is complementary through the terminal 5bp paired bases, and a new DNA molecule template is generated under the action of the extension enzyme. It is then amplified by qPCR to amplify the signal for detection. Olink is currently maturely applied in plasma testing. And a series of special cardiovascular tests have been developed 7 Due to its high throughput, high sensitivity, high specificity and high repeatability, it has a wide range of applications in disease prediction and prognostic biomarker screening research. 8 .

[0005] The existing methods for diagnosing acute coronary syndrome have the following main disadvantages: 1. Doctors' medical history can only provide references and cannot accurately determine whether they have acute coronary syndrome, especially for elderly women and diabetic patients, who often do not have typical angina symptoms. 2. Electrocardiogram is the first-line diagnostic tool for acute coronary syndrome, but its changes can disappear completely or partially as angina is relieved, and continuous electrocardiogram monitoring is often required. 3. The sensitivity and specificity of myocardial injury markers (cTnT, cTnI or CK-MB) vary, and they have their own diagnostic time windows, and multiple indicators are often required for continuous monitoring. 4. Coronary angiography is an invasive examination method. In addition, the angiography equipment is inconvenient to move, and the cost of each measurement is high. Therefore, an improved product for early diagnosis of acute coronary syndrome in young people is currently needed in the market. Through clinical trials, we clearly distinguished patients with acute coronary syndrome from non-ACS patients through medical history collection, biochemical testing, electrocardiogram analysis and coronary angiography, collected blood from patients, and used Olink technology to high-throughput screening of proteomic cardiovascular disease-related expression data in patients' peripheral plasma. Through machine learning methods, we screened out molecules that play an important role in predicting diseases, built a risk prediction system, and scored the system according to the expression of relevant molecules in patients. We evaluated the prediction efficiency of the prediction system through receiver operating curve analysis, and evaluated the prediction accuracy in the training set and validation set respectively. Summary of the invention

[0006] The purpose of the present invention is to provide a diagnostic kit for early screening of high-risk patients with acute coronary syndrome in young people.

[0007] The present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the following steps:

[0008] S1) Data reception: receiving the expression levels of six proteins, ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2, in the plasma samples of the patients to be tested;

[0009] S2) Data processing: Substituting the expression levels of the six proteins into the prognostic risk prediction model to calculate the risk score value of the patient suffering from acute coronary syndrome; the risk prediction model for suffering from acute coronary syndrome is as follows:

[0010] Risk score = risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression Formula 1,

[0011] S3) Data output: Analyze the possibility of the patient suffering from acute coronary syndrome according to the risk score value.

[0012] Furthermore, in the step S3), the possibility of the patient to be tested with a risk score ≥ 0.603 suffering from the acute coronary syndrome is greater than the possibility of the patient to be tested with a risk score < 0.603 suffering from the acute coronary syndrome.

[0013] The present invention provides a computer-readable storage medium, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the steps of the method are implemented.

[0014] Furthermore, the computer-readable storage medium refers to a carrier for storing data, which may be a floppy disk, a CD, a DVD, a hard disk, a flash memory, a USB flash drive, a CF card, a SD card, an MMC card, a SM card, a memory stick or an xD card.

[0015] The present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0016] S1) Data reception: receiving the expression levels of six proteins, ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2, in the plasma samples of the patients to be tested;

[0017] S2) Data processing: Substituting the expression levels of the six proteins into the prognostic risk prediction model to calculate the risk score value of the patient suffering from acute coronary syndrome; the risk prediction model for suffering from acute coronary syndrome is as follows:

[0018] Risk score = risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression Formula 1,

[0019] S3) Data output: Analyze the possibility of the patient suffering from acute coronary syndrome according to the risk score value.

[0020] Furthermore, in step S3), the possibility that the patient to be tested with a risk score ≥ 0.603 suffers from the acute coronary syndrome according to claim 1 is greater than the possibility that the patient to be tested with a risk score < 0.603 suffers from the acute coronary syndrome.

[0021] Any of the following applications of proteins and / or substances for detecting the proteins should also be within the scope of protection of the present invention:

[0022] D1) Use in the preparation of a product for predicting or assisting in predicting the likelihood of a patient suffering from acute coronary syndrome;

[0023] D2) Use in a device for predicting or assisting in predicting the likelihood of a patient suffering from an acute coronary syndrome;

[0024] The proteins are ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2.

[0025] Furthermore, the substance is a reagent, a kit and / or an instrument.

[0026] The present invention screened ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 as plasma markers of great significance for constructing a prediction model through the machine learning scheme of LASSO. The above plasma markers were constructed into a risk prediction model scoring system through the logistic regression scheme with the best explanatory power, and the scoring weights of different protein markers were successively accumulated, combined with the constant term, to obtain a total risk score. Through this scheme combining multiple plasma proteins, the possibility of a patient suffering from ACS is comprehensively predicted.

[0027] The present invention is based on comparing the expression of proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in peripheral venous blood plasma of young patients with acute coronary syndrome and young patients with stable angina pectoris and normal coronary arteries, and finds that the content of target plasma proteins in samples of patients with acute coronary syndrome is higher than that of patients with stable angina pectoris and normal coronary arteries, and proposes that target protein combination detection can be used as an early screening indicator for markers of young acute coronary syndrome. By detecting the expression of proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in peripheral venous blood plasma of young patients, it can be quickly determined that the patient has acute coronary syndrome, and the detection is non-invasive, the diagnosis is fast and accurate, the operation is simple, and the repeatability is good. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 The figure is a schematic diagram of the process of screening the markers of the present invention and constructing the relevant model (kit).

[0029] Figure 2 The volcano plot of differentially expressed proteins in peripheral blood mononuclear cells of young ACS and non-ACS patients screened by Olink technology, ACS group: young acute coronary syndrome group; NC group: normal young people group.

[0030] Figure 3 The corresponding risk assessment systems for ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in the training set and validation set, as well as the subject characteristic curves for predicting ACS in young people.

[0031] Figure 4 This is the subgroup analysis of young ACS after ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 were processed as categorical variables in the training set and validation set. *P<0.05 indicates that they are independent risk predictors for young ACS.

[0032] Figure 5 The following is a flow chart of the steps for implementing the computer program of the present invention. DETAILED DESCRIPTION

[0033] The present invention is further described in detail below in conjunction with specific embodiments, and the examples provided are only for illustrating the present invention, rather than for limiting the scope of the present invention. The examples provided below can be used as a guide for further improvements by those of ordinary skill in the art, and do not constitute a limitation of the present invention in any way.

[0034] The experimental methods in the following examples, unless otherwise specified, are all conventional methods, and are performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can all be obtained from commercial channels.

[0035] This study provides an early diagnosis kit based on the protein components of ITGB1BP2, FGF21, IL-1ra, BNP, KIM1 and THBS2 for the detection of markers of acute coronary syndrome in young people. The diagnostic kit determines whether the subject has acute coronary syndrome by detecting the expression level of related proteins and combining risk prediction factors. This is the first time that protein molecules screened by Olink technology have been used as early diagnostic markers for acute coronary syndrome in young people. Compared with traditional methods such as medical history inquiry, electrocardiogram, myocardial injury marker detection and coronary angiography, this diagnostic kit can directly determine whether the subject has acute coronary syndrome at the molecular level. In addition, this scheme is compatible with methods and equipment for detecting other molecular target substances in the laboratory, and has the ability to perform batch detection.

[0036] The present invention provides a scoring system for distinguishing high-risk young patients with coronary heart disease.

[0037] The present invention provides a kit for early diagnosis of ACS in young people to detect the expression of plasma proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2, and analyzes the possibility of patients suffering from acute coronary syndrome through a risk assessment system. The target population of high-risk young patients with coronary heart disease is screened early by non-invasive methods, risk factor management is strengthened in a targeted manner, and early coronary intervention is performed when necessary, so as to further improve the accuracy of coronary heart disease management in young people and better improve the long-term prognosis of high-risk young patients with ACS.

[0038] Preferably, the test sample of the acute coronary syndrome early diagnosis kit includes peripheral venous blood plasma;

[0039] Preferably, the expression levels of proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in peripheral venous plasma are quantitatively detected;

[0040] Preferably, when the subject's risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression, ≥ 0.603 is considered to be ACS in young people, and < 0.603 is considered to be non-ACS.

[0041] The present invention screened ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 as plasma markers of great significance for constructing a prediction model through the machine learning scheme of LASSO. The above plasma markers were constructed into a risk prediction model scoring system through the logistic regression scheme with the best explanatory power, and the scoring weights of different protein markers were successively accumulated, combined with the constant term, to obtain a total risk score. Through this scheme combining multiple plasma proteins, the possibility of a patient suffering from ACS is comprehensively predicted.

[0042] The present invention is based on comparing the expression of proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in peripheral venous blood plasma of young patients with acute coronary syndrome and young patients with stable angina pectoris and normal coronary arteries, and finds that the content of target plasma proteins in samples of patients with acute coronary syndrome is higher than that of patients with stable angina pectoris and normal coronary arteries, and proposes that target protein combination detection can be used as an early screening indicator for markers of young acute coronary syndrome. By detecting the expression of proteins ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 in peripheral venous blood plasma of young patients, it can be quickly determined that the patient has acute coronary syndrome, and the detection is non-invasive, the diagnosis is fast and accurate, the operation is simple, and the repeatability is good.

[0043] Based on the above content, the present invention provides a computer device, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the following steps (such as Figure 5 shown):

[0044] S1) Data reception: receiving the expression levels of six proteins, ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2, in the plasma samples of the patients to be tested;

[0045] S2) Data processing: Substituting the expression levels of the six proteins into the prognostic risk prediction model to calculate the risk score value of the patient suffering from acute coronary syndrome; the risk prediction model for suffering from acute coronary syndrome is as follows:

[0046] Risk score = risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression Formula 1,

[0047] S3) Data output: Analyze the possibility of the patient suffering from acute coronary syndrome according to the risk score value.

[0048] Furthermore, in the step S3), the possibility of the patient to be tested with a risk score ≥ 0.603 suffering from the acute coronary syndrome is greater than the possibility of the patient to be tested with a risk score < 0.603 suffering from the acute coronary syndrome.

[0049] Example 1 Construction and verification of the model

[0050] 1. Obtaining sample proteome data

[0051] The present invention collected 165 young patients (18-45 years old) with chest pain from Shenzhen People's Hospital, and made a clear diagnosis through medical history collection, physical examination, biochemical and imaging examinations and coronary angiography. The 165 young patients with chest pain were divided into young patients with acute coronary syndrome (114 cases) and non-young patients with acute coronary syndrome (51 cases).

[0052] The above patients were divided into a training set (114 cases, including 79 ACS patients and 35 controls) and a validation set (51 cases, including 35 ACS patients and 16 controls). Peripheral blood was collected from the above patients, and peripheral plasma proteomics analysis was performed according to the OLINK detection method.

[0053] The Olink Target Cardiovascular Disease [CVD] II kit from Olink Proteomics (Uppsala, Sweden) was used to perform protein detection based on the Olink method, including the following steps:

[0054] 1. Data output software:

[0055] OlinkNPX Signature 1.5.3.0(Olink)

[0056] 2. Experimental process:

[0057] 4.1 Sample randomization: Use the RAND function in the Excel table to output the numerical value corresponding to each sample, and then arrange the values ​​from small to large so that the samples are randomly distributed in the 96-well plate.

[0058] 4.2 Sample sampling: According to the randomized sample distribution table, take 10-40 μL of each sample into a 96-well plate. External control: add 5 μL of mixed plasma sample to wells A12 and B12, 5 μL of Negative Control (NC) to wells C12, D12, and E12, and 5 μL of Interplate Control (IPC) to wells F12, G12, and H12.

[0059] 4.3 Hybridization incubation: Prepare hybridization mixture first, take out the reagent and thaw it at room temperature, vortex and centrifuge, take a nuclease-free 1.5ml centrifuge tube, add 280μL of Incubation Solution, 40μL of IncubationStabilizer, 40μL of A-probes, and 40μL of B-probes in sequence, vortex and centrifuge. Take out an 8-tube strip and add 47μL of hybridization mixture to each well. Take out a 96-well plate, mark it as an incubation plate, use an 8-channel pipette to add 3μL of hybridization mixture to each well, and then add 1μL of sample to each well one by one. After sticking the sealing film, centrifuge at 400g for 1 minute, put it in the PCR instrument, set it to 4℃ infinity, record the time of putting it into the PCR instrument, and the incubation time must meet 16-24 hours.

[0060] 4.4 Extension and amplification: Set the PCR program to 50℃ for 20 minutes; 95℃ for 5 minutes; 95℃ for 30 seconds, 54℃ for 1 minute, and 60℃ for 1 minute for 17 cycles; maintain at 10℃. After the settings are completed, run the PCR instrument, and then press the pause button to maintain the temperature of the PCR instrument at 50℃. Prepare the extension and amplification mixture. Take a 15ml centrifuge tube, add 9385μL of High Purity Water, 1100μL of PEASolution, 55μL of PEAEnzyme, and 22μL of PCR Polymerase in sequence, vortex and centrifuge. Take out the incubation plate from the PCR instrument and centrifuge. Use an 8-channel pipette to add 96μL of extension and amplification mixture to each well, seal the film, vortex and centrifuge, place it on the PCR instrument preheated at 50℃, and then resume the program.

[0061] 4.5 Chip pretreatment: Unpack and take out the chip, check whether the chip and syringe are damaged. Take out the syringe, press down the piston hole, and push the liquid in the syringe. Click the instrument Target 96 option, the instrument pushes out the sample stage, puts in the chip and cover, and automatically returns to the sample stage. Click Start, and the chip pretreatment begins.

[0062] 4.6 Operation on the machine: Take out a 1.5ml centrifuge tube, add 550μL of Detection Solution, 230μL of HighPurity Water, 7.8μL of Detection Enzyme, and 3.1μL of PCR Polymerase in sequence, vortex and centrifuge. Take out another strip tube and dispense it into 95μL per well. Take out a 96-well plate, add 7.2μL of the mixture to each well, and after the extension amplification program is completed, add 2.8μL of the product, vortex and mix well for use. Prepare the diluted sample plate, primer plate and pre-treated chip, add 5μL of primers to the left side of the chip, and add 5μL of diluted product to the right side in sequence to avoid bubbles. After the sample is added, put it into the sample loading station, set the run name, and click Run.

[0063] 4.7 Data analysis and export: After the instrument is shut down, export the run name file and open OlinkNPXSignature

[0064] 1.5.3.0 software, set the reagent panel information, reagent version number, sample name, click "OK", the software automatically analyzes and outputs NPX Excel document and QCAR PDF document.

[0065] 2. Construction and verification of risk model

[0066] 2.1 Screening of markers

[0067] ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 were screened as markers associated with acute coronary syndrome in young people through the machine learning scheme of LASSO (as recorded in Tang G, Qi L, Sun Z, Liu J, Lv Z, Chen L, Huang B, Zhu S, Liu Y, Li Y. Evaluation and analysis of incidence and risk factors of lower extremity venous thrombosis after urologic surgeries: A prospective two-center cohort study using LASSO-logistic regression. Int J Surg. 2021; 89: 105948. doi: 10.1016 / j.ijsu.2021.105948). Figure 2The results in the table show the distribution of differentially expressed proteins in young people with coronary heart disease. The specific information of ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2 is shown in the table below.

[0068]

[0069]

[0070] 2.2 Construction of prediction model

[0071] like Figure 3 As shown, a risk model including six protein expression levels is constructed in the overall sample data of the training set. The risk prediction model for acute coronary syndrome obtained based on the coefficient and protein expression level of each protein is as follows:

[0072] Risk score = risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression - Formula 1.

[0073] The median value of the risk score of the training set patients, 0.603, was used as the threshold. Based on this value, the risk of acute coronary syndrome in the training set patients was divided into two groups: low risk and high risk. The area under the curve of the training set was 0.939, indicating that the model prediction has a very strong ability to identify patients. Figure 3 As shown in B.

[0074] Furthermore, the above risk prediction model was used to predict the patients in the validation set. The results are as follows: Figure 3 As shown in Figure 3C, the results show that the constructed prediction model has excellent extrapolation ability and is consistent with the clear diagnosis based on biochemical and imaging examinations and coronary angiography.

[0075] The above results show that the model of the present application has excellent disease prediction ability (ROC of the training set and validation set are 0.94 and 0.89, respectively).

[0076] 2.3 Subgroup analysis

[0077] Further analysis of the acute subgroup of the training set data showed the following results: Figure 4 As shown, from Figure 4 It can be seen that the high expression of the above molecules is related to the progression of ACS, among which ITGB1BP2, FGF21, BNP and KIM1 are independent risk factors.

[0078] The present invention has been described in detail above. It will be apparent to those skilled in the art that the present invention may be implemented in a wide range under equivalent parameters, concentrations and conditions without departing from the spirit and scope of the present invention and without the need for unnecessary experimentation. Although the present invention provides specific embodiments, it should be understood that further improvements may be made to the present invention. In short, according to the principles of the present invention, this application intends to include any changes, uses or improvements to the present invention, including changes made by conventional techniques known in the art that depart from the scope disclosed in this application. Applications of some of the basic features may be made within the scope of the following appended claims.

Claims

1. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the following steps: S1) Data reception: receiving the expression levels of six proteins, ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2, in the plasma samples of the patients to be tested; S2) Data processing: Substituting the expression levels of the six proteins into the prognostic risk prediction model to calculate the risk score value of the patient suffering from acute coronary syndrome; the risk prediction model for suffering from acute coronary syndrome is as follows: Risk score = risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression Formula 1, S3) Data output: Analyze the possibility of the patient suffering from acute coronary syndrome according to the risk score value.

2. The computer device according to claim 1, characterized in that: In step S3), the possibility that the patient to be tested with a risk score ≥ 0.603 suffers from the acute coronary syndrome according to claim 1 is greater than the possibility that the patient to be tested with a risk score < 0.603 suffers from the acute coronary syndrome.

3. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to claim 1 are implemented.

4. The computer-readable storage medium according to claim 31, wherein: The computer-readable storage medium refers to a carrier for storing data, which may be a floppy disk, a CD, a DVD, a hard disk, a flash memory, a USB flash drive, a CF card, a SD card, an MMC card, a SM card, a Memory Stick or an xD card.

5. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the following steps are implemented: S1) Data reception: receiving the expression levels of six proteins, ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2, in the plasma samples of the patients to be tested; S2) Data processing: Substituting the expression levels of the six proteins into the prognostic risk prediction model to calculate the risk score value of the patient suffering from acute coronary syndrome; the risk prediction model for suffering from acute coronary syndrome is as follows: Risk score = risk score = -26.27006 + 1.9280 × ITGB1BP2 expression + 0.6347 × FGF21 expression + 0.7993 × IL-1ra expression + 0.5231 × BNP expression + 0.7727 × KIMI1 expression + 2.1321 × THBS2 expression Formula 1, S3) Data output: Analyze the possibility of the patient suffering from acute coronary syndrome according to the risk score value.

6. The computer program product according to claim 5, characterized in that In step S3), the possibility that the patient to be tested with a risk score ≥ 0.603 suffers from the acute coronary syndrome according to claim 1 is greater than the possibility that the patient to be tested with a risk score < 0.603 suffers from the acute coronary syndrome.

7. Any of the following uses of a protein and / or a substance for detecting the protein: D1) Use in the preparation of a product for predicting or assisting in predicting the likelihood of a patient suffering from acute coronary syndrome; D2) Use in a device for predicting or assisting in predicting the likelihood of a patient suffering from an acute coronary syndrome; The proteins are ITGB1BP2, FGF21, IL-1ra, BNP, KIM1, and THBS2.

8. The use according to claim 7, characterized in that: The substance is a reagent, a kit and / or an instrument.

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