WO2019153241A1

WO2019153241A1 - Single nucleotide polymorphism loci associated with major adverse cardiovascular events and application thereof

Info

Publication number: WO2019153241A1
Application number: PCT/CN2018/075986
Authority: WO
Inventors: 刘小敏; 徐怀前; 刘晓
Original assignee: 深圳华大生命科学研究院
Priority date: 2018-02-09
Filing date: 2018-02-09
Publication date: 2019-08-15
Also published as: CN111670256A; CN111670256B

Abstract

Disclosed in the present invention are 17 single nucleotide polymorphism (SNP) loci associated with major adverse cardiovascular events (MACEs) and an application thereof. The 17 SNP loci provided by the present application are obtained on the basis of large-scale follow-up visits and data analysis on patients suffering from coronary heart disease, and may be used as markers for predicting the occurrence of major adverse cardiovascular events. In addition, further comprised by the present application is a kit for predicting the occurrence of MACEs in a subject, which comprises primer pairs and probe pairs used for amplifying and detecting the described 17 SNP loci, being capable of predicting the risk of MACEs in subjects.

Description

Single nucleotide polymorphism loci associated with major adverse cardiovascular events and their applications

Technical field

The present application relates to the field of biotechnology and, more particularly, to single nucleotide polymorphism sites associated with major adverse cardiovascular events and their use.

Background technique

As the global aging trend becomes more prominent, heart disease has become one of the leading causes of human death. Percutaneous coronary intervention (PCI) is the main treatment for coronary artery disease (CAD). However, postoperative platelet coagulation is likely to cause cardiac adverse events such as stent thrombosis. The combination of clopidogrel and aspirin anticoagulant therapy can significantly reduce the incidence of adverse cardiac events after PCI, and has become the gold standard for related treatment. However, despite the significant efficacy of dual anticoagulant therapy, some patients have ischemic events such as stent stenosis and stent thrombosis after PCI. Incomplete platelet inhibition may be associated with clopidogrel in this group of patients. Not responding. When endothelial cells are damaged, adenosine diphosphate can act as a platelet agonist, and surrounding platelets activate more platelets to participate in the hemagglutination reaction by releasing adenosine diphosphate. Clopidogrel is a prodrug that produces an antagonist of the adenosine diphosphate receptor P2Y12 through the liver cytochrome P450 enzyme system, thereby inhibiting platelet function. Therefore, when clopidogrel does not respond in patients, platelet activity in patients after PCI cannot be reasonably controlled. A large number of reports have confirmed that these postoperative differences are closely related to the individual genotypes of patients, and the CYP2C19 gene is the most widely reported.

There has been a large number of studies on the safety of clopidogrel medications in pharmacogenomics. Polymorphisms in the CYP2C19 and CYP2C9 genes have been shown to affect the pharmacokinetic and pharmacodynamic response of clopidogrel, and studies have demonstrated that CYP2C19 Loss-of Function (LOF)*2 and *3 variants result Reduced enzyme catalytic activity, resulting in low clopidogrel metabolic rate, leading to decreased antiplatelet effect, and may increase ischemic events, especially stent thrombosis; CYP2C19*17 function gain gene (Gain-of function, GOF) and hemorrhage Risk-related; there are similar reports showing that the polymorphism of the ABCB1 gene is associated with clopidogrel drug metabolism in humans. It has been reported in the literature that ABCB1 low expression type (TT type) patients with higher expression (CC type), intermediate expression type (CT type) clopidogrel absorption decreased, and is associated with early thrombosis in the stent. Similarly, another association between the gene PON1 and clopidogrel, which is highly associated with adverse cardiac events after PCI, has also been reported. The QQ type of PONI Q192R gene is the lowest than RR type, QR type paraoxonase activity, clopidogrel active metabolite concentration and platelet inhibition, and is more prone to early stent thrombosis.

Although studies have used gene chips or PCR amplification techniques to find genetic factors for adverse reactions after taking clopidogrel, and found some new sites. However, most of the current studies focus on the relationship between specific genotypes and diseases, and there is no full exon study or target region study for major adverse cardiovascular events (MACE) after PCI. Second, most of the study of susceptible sites of coronary artery disease are concentrated in Western populations. Genome-wide association study (GWAS) has identified multiple related variant sites in the Caucasian population, but it was not until 2011. There is a GWAS study of coronary artery disease in Chinese population. Later, some studies have verified some sites in the East Asian population. Although there are studies on finding new sites in the Chinese population, there are still no large-scale clinical data and large sample studies in this area, and most of the discovered susceptible sites. The applicability in the Chinese population remains unclear.

Summary of the invention

The following is an overview of the topics detailed in this document. This Summary is not intended to limit the scope of the claims.

In view of the above-mentioned deficiencies in the prior art, the present application provides 17 single nucleotide polymorphism (SNP) sites which are significantly associated with major adverse cardiovascular events (MACE), which are SNP sites. It has important guiding role in predicting whether a subject has a major adverse cardiovascular event (MACE).

In a first aspect, the present invention provides a single nucleotide polymorphism site associated with a major adverse cardiovascular event selected from the group consisting of the rs17064642 site of the MYOM2 gene, the rs11640115 site of the WDR24 gene, and the rs74569896 site of the NECAB1 gene, Rs4736529 of EFR3A gene, rs3851808 of EFCAB13 gene, rs188799 of CDC27 gene, rs2340917 of TMEM43 gene, rs1048425 of GBP1 gene, rs7913176 of NHLRC2 gene The rs4646487 locus of the gene, the rs754615 locus of the CAST gene, the rs4729631 locus of the MUC12 gene, the rs28384507 locus of the GPA33 gene, the rs60257337 locus of the GP2 gene, the rs2241046 locus of the IL17RA gene, and the rs1060561 locus of the DOCK1 gene. One or a combination of at least two; where:

The rs17064642 site of the MYOM2 gene is the 61th position of the sequence represented by SEQ ID NO: 1 from the 5' end, and the allelic type is C/T;

The rs11640115 locus of the WDR24 gene is the 61th position of the sequence represented by SEQ ID NO: 2 from the 5' end, and the allelic type is A/G;

The rs74569896 site of the NECAB1 gene is the 61th position of the sequence shown in SEQ ID NO: 3 from the 5' end, and the allelic type is G/A;

The rs4736529 site of the EFR3A gene is the 61th position of the sequence shown in SEQ ID NO: 4 from the 5' end, and the allelic type is G/C;

The rs3851808 locus of the EFCAB13 gene is the 61th position of the sequence represented by SEQ ID NO: 5 from the 5' end, and the allelic type is C/T;

The rs188799 locus of the CDC27 gene is the 61th position of the sequence shown in SEQ ID NO: 6 from the 5' end, and the allelic type is T/C;

The rs2340917 locus of the TMEM43 gene is the 61th position of the sequence shown in SEQ ID NO: 7 from the 5' end, and the allelic type is T/C;

The rs1048425 site of the GBP1 gene is the 61th position of the sequence shown in SEQ ID NO: 8 from the 5' end, and the allelic type is G/C;

The rs7913176 site of the NHLRC2 gene is the 61th position of the sequence shown in SEQ ID NO: 9 from the 5' end, and the allelic type is A/G;

The rs11228762 locus of the OR9G4 gene is the 61th position of the sequence represented by SEQ ID NO: 10 from the 5' end, and the allelic type is A/G;

The rs4646487 site of the CYP4B1 gene is the 61th position of the sequence represented by SEQ ID NO: 11 from the 5' end, and the allelic type is T/C;

The rs754615 site of the CAST gene is the 61th position of the sequence represented by SEQ ID NO: 12 from the 5' end, and the allelic type is C/G;

The rs4729631 site of the MUC12 gene is the 61th position of the sequence represented by SEQ ID NO: 13 from the 5' end, and the allelic type is T/C;

The rs28384507 locus of the GPA33 gene is the 61th position of the sequence represented by SEQ ID NO: 14 from the 5' end, and the allelic type is T/G;

The rs60257337 site of the GP2 gene is the 61th position of the sequence shown in SEQ ID NO: 15 from the 5' end, and the allelic type is C/G;

The rs2241046 locus of the IL17RA gene is the 61st position of the sequence represented by SEQ ID NO: 16 from the 5' end, and the allelic type is C/T;

The rs1060561 site of the DOCK1 gene is the 61st position of the sequence represented by SEQ ID NO: 17 from the 5' end, and the allelic type is A/G.

Further, the major adverse cardiovascular event is selected from the group consisting of cardiac death, stroke, myocardial infarction, and revascularization.

Further, the main adverse cardiovascular event is cardiac death, and the single nucleotide polymorphism site associated therewith is the rs2241046 site of the IL17RA gene;

The major adverse cardiovascular event is stroke, and the single nucleotide polymorphism site associated therewith is selected from the rs4736529 site of the EFR3A gene and the rs188799 site of the CDC27 gene;

The main adverse cardiovascular event is myocardial infarction, and the single nucleotide polymorphism site associated with it is selected from the rs17064642 locus of the MYOM2 gene, the rs11640115 locus of the WDR24 gene, the rs3851808 locus of the EFCAB13 gene, and the rs2340917 of the TMEM43 gene. Site, rs1048425 locus of GBP1 gene, rs7913176 locus of NHLRC2 gene, rs11228762 locus of OR9G4 gene, rs4646487 locus of CYP4B1 gene, rs4729631 locus of MUC12 gene, rs28384507 locus of GPA33 gene, rs60257337 locus of GP2 gene Point and rs1060561 locus of the DOCK1 gene; or

The main adverse cardiovascular event is revascularization, and the single nucleotide polymorphism site associated therewith is selected from the rs74569896 site of the NECAB1 gene and the rs754615 site of the CAST gene.

In a second aspect, the present application further provides a primer pair for amplifying the single nucleotide polymorphism site of the first aspect, which is selected from any one of the sequence pairs shown below or a combination of at least two :

Primer pair for amplifying the rs17064642 site SEQ ID NO: 18 and SEQ ID NO: 19;

Primer pair for amplifying the rs11640115 site SEQ ID NO: 20 and SEQ ID NO: 21;

Primer pair for amplifying the rs74569896 site SEQ ID NO: 22 and SEQ ID NO: 23;

Primer pair for amplifying the rs4736529 site SEQ ID NO: 24 and SEQ ID NO: 25;

Primer pair for amplifying the rs3851808 site SEQ ID NO: 26 and SEQ ID NO: 27;

Primer pair for amplifying the rs188799 site SEQ ID NO: 28 and SEQ ID NO: 29;

Primer pair for amplifying the rs2340917 site SEQ ID NO: 30 and SEQ ID NO: 31;

Primer pair for amplifying the rs1048425 site SEQ ID NO: 32 and SEQ ID NO: 33;

Primer pair for amplification of rs7913176 site SEQ ID NO: 34 and SEQ ID NO: 35;

Primer pair for amplifying the rs11228762 site SEQ ID NO: 36 and SEQ ID NO: 37;

Primer pair for amplifying the rs4646487 site SEQ ID NO: 38 and SEQ ID NO: 39;

Primer pair for amplifying rs754615 site SEQ ID NO: 40 and SEQ ID NO: 41;

Primer pair for amplifying the rs4729631 site SEQ ID NO: 42 and SEQ ID NO: 43;

Primer pair for amplifying the rs28384507 site SEQ ID NO: 44 and SEQ ID NO: 45;

Primer pair for amplifying the rs60257337 site SEQ ID NO: 46 and SEQ ID NO: 47;

Primer pair for amplifying the rs2241046 site SEQ ID NO: 48 and SEQ ID NO: 49;

Primer pairs for amplifying the rs1060561 site were SEQ ID NO: 50 and SEQ ID NO: 51.

In a third aspect, the present application provides a probe pair for detecting a single nucleotide polymorphism site according to the first aspect, which is selected from any one or at least two of the probe pairs shown below. combination:

Probe pair for detecting rs17064642 site pairs SEQ ID NO: 52 and SEQ ID NO: 53;

Probe pair for detecting rs11640115 site pairs SEQ ID NO: 54 and SEQ ID NO: 55;

Probe pair for detecting rs74569896 site SEQ ID NO: 56 and SEQ ID NO: 57;

Probe pair for detecting rs4736529 site pairs SEQ ID NO: 58 and SEQ ID NO: 59;

Probe pair for detecting rs3851808 site SEQ ID NO: 60 and SEQ ID NO: 61;

Probe pair for detecting rs188799 site SEQ ID NO: 62 and SEQ ID NO: 63;

Probe pair for detecting rs2340917 site SEQ ID NO: 64 and SEQ ID NO: 65;

Probe pair for detecting rs1048425 site pairs SEQ ID NO: 66 and SEQ ID NO: 67;

Probe pair for detecting rs7913176 site pairs SEQ ID NO: 68 and SEQ ID NO: 69;

Probe pair for detecting rs11228762 site pairs SEQ ID NO: 70 and SEQ ID NO: 71;

Probe pair for detecting rs4646487 site SEQ ID NO: 72 and SEQ ID NO: 73;

Probe pair for detecting rs754615 site pair SEQ ID NO: 74 and SEQ ID NO: 75;

Probe pair for detecting rs4729631 site SEQ ID NO: 76 and SEQ ID NO: 77;

Probe pair for detecting rs28384507 site SEQ ID NO:78 and SEQ ID NO:79;

Probe pair for detecting rs60257337 site SEQ ID NO: 80 and SEQ ID NO: 81;

Probe pair for detecting rs2241046 site SEQ ID NO: 82 and SEQ ID NO: 83;

Probe pairs for detecting the rs1060561 site were SEQ ID NO: 84 and SEQ ID NO: 85.

In a fourth aspect, the present application further provides the single nucleotide polymorphism site of the first aspect, the primer pair of the second aspect, or the probe pair of the third aspect is mainly caused in predicting a subject. Use in adverse cardiovascular events.

Further, the subject underwent percutaneous coronary intervention.

Further, the primary adverse cardiovascular event comprises any one or a combination of at least two of cardiac death, stroke, myocardial infarction, and revascularization.

Further, the subject is a Chinese population, preferably a Han population.

In a fifth aspect, the present invention also provides a method of predicting a risk of a major adverse cardiovascular event in a subject, comprising: detecting a single nucleotide polymorphism as described in the first aspect of the subject to be tested The genotype of the locus; predicts the risk of major adverse cardiovascular events in the subject based on the resulting genotype.

Therein, according to a specific example of the present invention, the relationship between the genotype of some single nucleotide polymorphism sites and the risk of major adverse cardiovascular events is detected in the subject:

Subjects with the C allele at the rs17064642 locus in the MYOM2 gene were 2.76 times more likely to develop a major adverse cardiovascular event than subjects with the T allele at that locus;

Subjects with the A allele at the rs11640115 locus in the WDR24 gene were 0.47 times more likely to develop a major adverse cardiovascular event than subjects with the G allele at that locus;

Subjects with the G allele at the rs74569896 locus in the NECAB1 gene were 1.93 times more likely to develop a major adverse cardiovascular event than subjects with the A allele at that locus;

Subjects with a G allele at the rs4736529 site in the EFR3A gene are 2.33 times more likely to develop a major adverse cardiovascular event than subjects with a C allele at that site;

Subjects with the C allele at the rs3851808 locus in the EFCAB13 gene were 1.65 times more likely to develop a major adverse cardiovascular event than subjects with the T allele at that locus;

Subjects with the T allele at the rs188799 locus in the CDC27 gene were 1.91 times more likely to develop a major adverse cardiovascular event than subjects with the C allele at that locus;

Subjects with a T allele at the rs2340917 site in the TMEM43 gene are 0.56 times more likely to develop a major adverse cardiovascular event than subjects with a C allele at that site;

Subjects with the G allele at the rs1048425 locus in the GBP1 gene are at a risk of major adverse cardiovascular events 1.61 times that of subjects with the C allele at this locus;

Subjects with the A allele at the rs7913176 locus in the NHLRC2 gene were 1.56 times more likely to develop a major adverse cardiovascular event than subjects with the G allele at that locus;

Subjects with the A allele at the rs11228762 locus in the OR9G4 gene were 0.61 times more likely to develop a major adverse cardiovascular event than subjects with the G allele at that locus;

Subjects with the T allele at the rs4646487 locus in the CYP4B1 gene are 0.53 times more likely to develop a major adverse cardiovascular event than subjects with the C allele at that locus;

Subjects with the C allele at the rs754615 locus in the CAST gene are at a risk of major adverse cardiovascular events 1.87 times that of subjects with the G allele at this locus;

Subjects with a T allele at the rs4729631 locus in the MUC12 gene were 0.46 times more likely to develop a major adverse cardiovascular event than subjects with the C allele at that locus;

Subjects with a T allele at the rs28384507 locus in the GPA33 gene were 0.48 times more likely to develop a major adverse cardiovascular event than subjects with a G allele at that locus;

Subjects with the C allele at the rs60257337 locus in the GP2 gene are 1.56 times more likely to develop a major adverse cardiovascular event than subjects with the G allele at that locus;

Subjects with the C allele at the rs2241046 locus in the IL17RA gene are at a risk of major adverse cardiovascular events 1.64 times that of subjects with the T allele at this locus;

Subjects with the A allele at the rs1060561 locus in the DOCK1 gene are at a risk of major adverse cardiovascular events 1.67 times that of subjects with the G allele at this locus.

Further, it will be understood by those skilled in the art that, based on statistically significant considerations, the risk multipliers for all of the above adverse cardiovascular events can be extended left and right within a 95% confidence interval. specifically:

For example, subjects with the C allele at the rs17064642 locus in the MYOM2 gene had a 2.72-fold higher risk of major adverse cardiovascular events than subjects with the T allele, with a 95% confidence interval ranging from 1.98- 3.87 times, it should be understood that the risk multiple range of 1.98-3.87 times falls within the scope of the claimed invention.

For example, subjects with the A allele at the rs11640115 locus in the WDR24 gene have a 0.47-fold higher risk of major adverse cardiovascular events than subjects with the G allele, with a 95% confidence interval ranging from 0.35- 0.63 times, it should be understood that a risk multiplier range of 0.35-0.63 times falls within the scope of the claimed invention.

......

From this, it can be determined that:

Further, the relationship between the genotype of the following single nucleotide polymorphism sites detected in the subject and the risk of major adverse cardiovascular events including:

A subject having a C allele at the rs17064642 site in the MYOM2 gene is at a higher risk of major adverse cardiovascular events than a subject having a T allele at that site, preferably 1.98-3.87 times more likely More preferably 2.76 times;

A subject with an A allele at the rs11640115 locus in the WDR24 gene has a lower risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 0.35-0.63 times More preferably 0.47 times;

Subjects with the G allele in the rs74569896 locus in the NECAB1 gene are at a higher risk of major adverse cardiovascular events than subjects with the A allele at this locus, preferably 1.49-2.51 times More preferably 1.93 times;

A subject having a G allele at the rs4736529 site in the EFR3A gene is at a higher risk of major adverse cardiovascular events than a subject having a C allele at that site, preferably 1.65-3.31 times More preferably 2.33 times;

Subjects with the C allele at the rs3851808 locus in the EFCAB13 gene are at a higher risk of major adverse cardiovascular events than subjects with the T allele at this locus, preferably 1.32-2.06 times More preferably 1.65 times;

A subject having a T allele at the rs188799 locus in the CDC27 gene is at a higher risk of major adverse cardiovascular events than a subject having a C allele at that locus, preferably 1.43-2.55 times More preferably 1.91 times;

A subject with a T allele at the rs2340917 site in the TMEM43 gene has a lower risk of major adverse cardiovascular events than a subject with a C allele at that site, preferably 0.43-0.72 times More preferably 0.56 times;

A subject with a G allele at the rs1048425 locus in the GBP1 gene has a higher risk of major adverse cardiovascular events than a subject with a C allele at that locus, preferably 1.30-1.99 times its , more preferably 1.61 times;

A subject with an A allele at the rs7913176 locus in the NHLRC2 gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 1.26-1.93 times More preferably 1.56 times;

A subject with an A allele at the rs11228762 locus in the OR9G4 gene has a lower risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 0.48-0.77 times More preferably 0.61 times;

A subject with a T allele at the rs4646487 site in the CYP4B1 gene has a lower risk of major adverse cardiovascular events than a subject with a C allele at that site, preferably 0.40-0.72 times More preferably 0.53 times;

A subject with a C allele at the rs754615 locus in the CAST gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 1.38-2.53 times More preferably 1.87 times;

A subject with a T allele at the rs4729631 locus in the MUC12 gene has a lower risk of major adverse cardiovascular events than a subject with a C allele at that locus, preferably 0.31-0.67 times More preferably 0.46 times;

A subject with a T allele at the rs28384507 locus in the GPA33 gene is at a lower risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 0.34-0.69 times More preferably 0.48 times;

A subject with a C allele at the rs60257337 locus in the GP2 gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably, it is 1.25-1.94 times more likely More preferably 1.56 times;

A subject with a C allele at the rs2241046 locus in the IL17RA gene is at a higher risk of major adverse cardiovascular events than a subject with a T allele at that locus, preferably 1.28-2.10 times more likely More preferably 1.64 times;

A subject with an A allele at the rs1060561 locus in the DOCK1 gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 1.29-2.16 times more More preferably, it is 1.67 times.

As described above, those skilled in the art can understand that according to the statistical method, the risk multipliers of all adverse cardiovascular events obtained according to the embodiment of the present invention are extended in the 95% confidence interval, and the specific risk multiples are obtained. The range of risk multiples of the 95% confidence interval range can fall within the scope of the claimed invention. Further, the method specifically includes:

1) extracting the genomic DNA of the subject;

2) performing PCR amplification on the single nucleotide polymorphism site of claim 1;

3) detecting the amplification product and genotyping the amplification product;

4) Predict the risk of adverse cardiovascular events in the subject based on genotype.

Further, the subject underwent percutaneous coronary intervention.

Further, the subject is a Chinese population, preferably a Han population.

Further, the method may also be combined with a prediction method based on epidemiological factors, preferably, the epidemiological factors include any one or a combination of at least two of: patient's gender, age, body Quality index, previous history of myocardial infarction, diabetes, hypertension; administration of angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta-blockers, calcium channel inhibitors, proton pumps before the end point event Inhibitors, statins, high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, glycosylated hemoglobin, alanine aminotransferase, aspartate aminotransferase, creatinine, creatine kinase and their isoenzymes .

In a sixth aspect, the present invention also provides a kit for predicting a major adverse cardiovascular event in a subject, comprising a primer pair for amplifying the single nucleotide polymorphism site described in the first aspect and / or a probe pair for detecting the single nucleotide polymorphism site described in the first aspect.

Further, the kit comprises the primer pair of the second aspect and/or the probe pair of the third aspect.

The 17 single nucleotide polymorphism sites associated with major adverse cardiovascular events (MACE) provided by the present application are 18 months after the inventors have taken clopidogrel for the largest coronary heart disease patient in China. The recorded results of the follow-up visit were used to define the endpoint events, based on the genotype data from the whole exon and target region sequencing of the MACE sample and the control sample, and then combined with the clinical phenotypic data for cox regression analysis. Based on the large sample size of clinical information and high-throughput gene sequencing data, the 17 single nucleotide polymorphism sites provided by this application are the most complete and accurate at present and can be used to predict adverse cardiovascular disease. A marker that occurs in an event (MACE). This application lays an important foundation for further research on gene expression regulation, metabolic pathway and protein function, in-depth study of the pathogenesis of MACE, development of new therapeutic drugs and gene therapy, and realization of individualized diagnosis and treatment based on genetic background.

The kits provided herein are prepared based on the 17 newly discovered single nucleotide polymorphism (SNP) sites described above, and the primer sequences for each site are specifically screened. Genomic DNA derived from the peripheral blood of the subject is taken, genotyping is performed on the kit of the present invention, and then PCR amplification and Taqman probe are used for genotyping, single nucleotide sites are detected, and comprehensive analysis is performed. Patient clinical phenotypic information (gender, age, BMI, diabetes, hypertension, medication and clinical indicators, etc.) and 17 single nucleotide polymorphism (SNP) information, combined with genetic risk factors A comprehensive model of epidemiological factors that predicts the risk of major adverse cardiovascular events (MACE) in individuals and can be used for early prediction and screening of people who have not had a MACE event after PCI but who have a high risk of MACE. Early detection of high-risk groups of MACE events, so that they take appropriate health care measures and regularly go to the hospital for examination, reducing the incidence or time of MACE. At the same time, it can also provide guidance and help for doctors to judge the occurrence of MACE and to choose medication.

DRAWINGS

1 is a survival curve of different genotype individuals with rs17064642 locus having the MYOM2 gene described in Example 1 with respect to MACE; wherein the ordinate shows the survival rate of individuals who did not have a MACE event, and the abscissa is displayed on a monthly basis. Time and the number of individuals whose genotypes did not have a MACE event at the time point corresponding to the abscissa;

2 is a graph of AUC results for predicting the accuracy of MACE for the three models described in Example 2; wherein the abscissa represents (1-specificity) (ie, 1 minus specificity) and the ordinate represents sensitivity.

Detailed ways

To facilitate an understanding of the present application, the present application enumerates the embodiments as follows. It should be understood by those skilled in the art that the present invention is only to be understood as an understanding of the present application and should not be construed as a limitation.

Example 1 Determination of Single Nucleotide Polymorphism Sites Significantly Associated with Major Adverse Cardiovascular Events (MACE)

I. Selection criteria for MACE samples and control samples

All patient samples were from the Guangdong Provincial People's Hospital and all belonged to the Han population. Each patient received dual antiplatelet agglutination therapy with clopidogrel and aspirin after PCI. The dose of clopidogrel was 300 mg for the first load and 75 mg/day for the maintenance dose. The primary endpoints defined in this study were major adverse cardiovascular events, including cardiac death, stroke, myocardial infarction, and revascularization. All patients with major adverse cardiovascular events within 1.5 years after PCI were defined as the MACE case group and the remaining patients were assigned to the MACE control group.

Second, the method

The research design of this application is divided into two phases:

The first phase was a study of the discovery data set. 51 patients with MACE events and 117 control patients were selected as subjects, and the NimbleGen seqcap EZ exon (44M) chip was used to map the genome of each of the 170 patients. DNA is targeted for capture. Each sample capture data was then sequenced independently using the Illumina HiSeq2000 platform. Each sample was designed to cover ~210 times to obtain high quality bases. All Illumina sequencing data were compared to the GRCh37/hg19 human reference genome using soap2 software, and then the results of the alignment were analyzed using soapsnp software to detect SNPs. For the SNPs variation, we adopted the following filtering conditions: base sequencing quality ≥ 20, sequencing depth ≥ 8 ×, sequencing depth ≤ 500 ×, non-reference type allele ≥ 4 ×. After the initial SNPs are completed, we further filter the population variation data set: (1) SNPs detection rate ≥ 90%; (2) Hardy-Weinberg test P value > 1 × 10 ^-6 ; (3) their minor allele frequency (MAF) > 0.01. The plink software performed logistic regression analysis to assess the significance of each SNP locus and MACE endpoint event, calculated the relative risk (ORdds ratio, OR) and 95% confidence interval of the risk allele, and obtained the OR value directly in the analysis. The confidence interval and the P value, resulting in a dangerous allele at the site.

The second phase was a study of the validation dataset. A total of 123 patients with MACE events and 1580 control patients were selected. For the 6168 SNPs and 798 and MACE that were significantly associated with MACE in the first phase. For the significantly related genes, we designed a 6M target region chip and then used the CG sequencing platform to perform high-depth sequencing of the 1703 validated samples. Each sample was designed to cover ~210 times to obtain high quality bases. All CG sequencing data were compared to the GRCh37/hg19 human reference genome, and then the CG analysis tool (CGATools, http://cgatools.sourceforge.net/) was used to analyze the alignment and detect SNPs variation. After the initial SNPs are completed, we further filter the population variation data set: (1) SNPs detection rate ≥ 90%; (2) Hardy-Weinberg test P value > 1 × 10 ^-6 ; (3) their minor allele frequency (MAF) > 0.01. A multivariate COX regression analysis model was used to evaluate the correlation between SNPs and MACE. The relative risk (hazards ratio, HR) and the 95% confidence interval were calculated. The HR value, confidence interval and P value were obtained directly in the analysis to obtain the dangerous allele at the site.

Finally, the 168 patients in the first phase and the 1703 patient samples in the second phase were combined for correlation analysis. In this way, the genotype data of 1871 patients were obtained, and the multivariate COX regression analysis model was also used. Calculate the correlation between these SNPs and MACE. The relative risk (HR) and 95% confidence interval of the risk allele were calculated, and the HR value, confidence interval and P value were directly obtained in the analysis to obtain the dangerous allele at the site. Finally, we selected SNPs that met the following conditions as the final significant sites: (1) SNPs with P<0.05 in the first phase (2) SNPs with P<0.05 in the second phase of the second phase (3) in the combined data analysis <10 ^-4 SNPs.

Third, the results

The first phase was a study of the discovery data set. 51 patients with MACE events and 117 control patients were selected for the study, and the Illumina exon chip was used for sequencing. Each sample reached a sequencing depth of ~210. The data quality is very good, as shown in Table 1.

Table 1. Summary of the first stage sample sequencing data

The second phase was the study of the discovery dataset. 123 patients with MACE events and 1580 control patients were selected for the study. The CG sequencing platform was used for sequencing. Each sample reached a sequencing depth of ~93X, and the data quality. Very good, as shown in Table 2.

Table 2. Summary of second stage sample sequencing data

A multivariate COX regression analysis of genotypic data sets from 1871 patients (including 174 patients with MACE and 1697 control patients) found that 17 SNP loci were significantly associated with MACE.

The 17 SNP loci and their alleles are: rs17064642 of MYOM2 gene, C/T for allele; rs11640115 of WDR24 gene, A/G for allele; rs74569896 for NECAB1 gene, G/ for allele A; EFR3A gene rs4736529, allele is G/C; EFCAB13 gene rs3851808, allele is C/T; CDC27 gene rs188799, allele is T/C; TMEM43 gene rs2340917, allele is T/C; rs1048425 of GBP1 gene, G/C for allele; rs7913176 of NHLRC2 gene, A/G for allele; rs11228762 for OR9G4 gene, A/G for allele; rs4646487 for CYP4B1 gene, allele The gene is T/C; the CAST gene is rs754615, the allele is C/G; the MUC12 gene is rs4729631, the allele is T/C; the GPA33 gene is rs28384507, the allele is T/G; the GP2 gene is rs60257337, The allele is C/G; the IL17RA gene is rs2241046, the allele is C/T; the DOCK1 gene is rs1060561, and the allele is A/G. The correlation between these 17 SNP loci and MACE is shown in Table 3. Among them, the rs17064642 locus of MYOM2 gene was most correlated with the occurrence of MACE (P=2.95×109), and reached the level of whole genome significance. As shown in Figure 1, the cumulative recurrence rate of patients with the TT genotype was 8.1%, and the cumulative recurrence rate for patients with the CC genotype or CT genotype was 17.8%, compared to the accumulation of patients with the TT genotype. The recurrence rate was significantly higher in the case where the 672C/T (rs17064642) site in the MYOM2 gene had the C allele (CC genotype or CT genotype) (HR=2.76). In addition, patients with the A allele at the rs11640115 locus in the WDR24 gene had a 0.46-fold higher risk of MACE than patients with the G allele; MACE occurred in patients with the G allele at the rs74569896 locus in the NECAB1 gene. The risk was 1.93 times higher for patients with the A allele; patients with the G allele at the rs4736529 locus in the EFR3A gene had a 2.38 times higher risk of MACE than patients with the C allele; rs3851808 at the EFCAB13 gene Patients with the C allele had a 1.65-fold higher risk of MACE than patients with a T allele; patients with a T allele at the rs188799 locus in the CDC27 gene had a risk of MACE of 1.91 for patients with C alleles. In patients with T allele at the rs2340917 locus in the TMEM43 gene, the risk of MACE is 0.56 times higher than that of patients with the C allele; MACE occurs in patients with the G allele at the rs1048425 locus in the GBP1 gene. The risk was 1.61 times that of patients with C allele; patients with A allele at rs7913176 locus in NHLRC2 had a risk of MACE 1.56 times higher than patients with G allele; Patients with the A allele at the rs11228762 locus in the 9G4 gene are 0.61 times more likely to have a MACE than those with a G allele; patients with a T allele at the rs4646487 locus in the CYP4B1 gene have a risk of MACE. 0.53 times of patients with C allele; patients with C allele in rs754615 locus in CAST gene have a MACE risk of 1.87 times that of patients with G allele; rs4729631 locus in MUC12 gene has T, etc. Patients with a gene had a risk of MACE 0.46 times more likely to have a C allele; patients with a T allele at the rs28384507 locus in the GPA33 gene had a 0.48-fold higher risk of MACE than patients with a G allele; Patients with the C allele in the rs2257337 locus in the GP2 gene have a risk of MACE 1.56 times higher than those with the G allele; patients with the C allele in the rs2241046 locus in the IL17RA gene have a risk of MACE. The patient with the T allele was 1.64 times; the patient with the A allele at the rs1060561 locus in the DOCK1 gene had a risk of MACE of 1.67 times that of patients with the G allele. Finally, the sequences of these 17 SNP loci are shown in Table 4 below.

Table 3.17 Association results between SNP loci and MACE

Among them, "allele" means a minor allele/major allele, and "gene frequency" means the frequency of a minor allele. "HR (95% CI)" indicates the relative risk of MACE in individuals carrying a minor allele compared to an individual carrying a major allele. In the "function comment", UTR3 represents a 3' uncompiled area, and UTR5 represents a 5' uncompiled area.

Table 4. Sequence of 17 SNP loci identified in this application that are significantly associated with major adverse cardiovascular events (MACE)

Example 2. Kit for predicting major adverse cardiovascular events (MACE) in a subject

The kit for predicting major adverse cardiovascular events (MACE) in a subject described in this example is performed by detecting the above 17 SNP sites that are significantly associated with major adverse cardiovascular events (MACE). Predicted kit.

The kits described herein include: PCR amplification primers (single base forward primer and reverse primer) for detecting 17 SNP sites of the human genome and probes for genotyping. The 17 SNP sites were rs17064642, rs11640115, rs74569896, rs4736529, rs3851808, rs188799, rs2340917, rs1048425, rs7913176, rs11228762, rs4646487, rs754615, rs4729631, rs28384507, rs60257337, rs2241046 and rs1060561.

First, the preparation of the kit:

PCR amplification primers (single base forward primer and reverse primer) for the SNP site and two Taqman-MGB probes for genotyping were designed and synthesized. Primers were designed to specifically amplify the PCR product containing each SNP site while designing two probes for each of the two alleles of each SNP site. Fluorescent groups can be labeled with FAM, VIC, etc. to identify both alleles. Table 5 below is the primer and probe sequences of the design described.

Table 5.17 PCR amplification primers for the SNP locus (forward and reverse primers) and two Taqman-MGB probe sequences

Further, the kit may further include other components, for example, including: Taq enzyme, dNTP mixture, diluent, buffer, etc., as described in the following detection method.

Second, the detection method (ie, the use of the kit)

1. Configure PCR reaction mix solution

A region containing a single nucleotide polymorphism site was amplified by multiplex PCR. More specifically, first, genomic DNA is isolated from a clinical sample and used as a DNA template for a PCR reaction. The PCR reaction Mix solution was prepared as shown in Table 6. In the following PCR reactions, the forward and reverse primers for each single nucleotide polymorphism site described in Table 5 above and two Taqman-MGB probes were used as primers for the PCR reaction.

Table 6. PCR reaction Mix solution formulation

2. Perform PCR reaction

After the reaction system was good preparation, on ABI 9700PCR instrument selects StepOnePlus ^TM System, pressing conditions shown in Table 7 PCR reaction PCR reaction was performed in the program: denaturation at about 95 deg.] C for about 10 minutes (1 cycle); about The denaturation was carried out at 95 ° C for about 15 seconds, and annealed at about 60 ° C for about 1 minute, which was taken as one cycle (40 cycles in total). After the reaction was completed, the reactants were stored at about 4 °C.

Table 7. PCR reaction conditions

3, genotype results output

After the PCR reaction, Taqman genotyping software was used to perform cluster analysis and report genotype according to the fluorescence signal intensity of different alleles of single nucleotide polymorphism sites. The genotyping results are output in an excel form.

Third, the effect analysis of the kit

For the effects of the kits described in the present application, the applicant constructs mainly based on genetic factors and environmental factors through sensitivity (Sensitivity), specificity (Specificity) and Receiver Operating Characteristic (ROC) curves. The fitting effect of the adverse cardiovascular event (MACE) predictive model was analyzed.

1. Recruiting subjects

The enrolled subjects were 1837 patients with coronary heart disease, including 171 patients with major adverse cardiovascular events (MACE) with complete clinical phenotypic information and 1666 patients with no MACE endpoint. The clinical phenotypic information of patients included: 1. Patient characteristics: gender, age, body-mass index (BMI), previous myocardial infarction (MI), diabetes mellitus, hypertension (hypertension); 2. endpoint events Pre-medication: angiotensin-converting-enzyme inhibitor (ACEI), angiotensin receptor blocker (ARB), beta-blocker (β-blocker) Inhibitor, BBI), calcium channel blocker (CCB), proton pump inhibitor (PPI), statins; 3. clinical indicators during hospitalization: high density lipoprotein High density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), glycerol (Triglyceride), hemoglobinAlc (HbAlc), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CREA), creatine kinase and its isoenzyme (creatine kinase and Creatine kinase MB, CK and CKMB). Together, there are a total of 20 clinical phenotypic data information.

2, build a predictive model

We use the Support Vector Machine (SVM) method in machine learning to model. In the field of machine learning, Support Vector Machine (SVM) is a supervised learning model, usually used for pattern recognition, classification, and regression analysis. SVM involves a wide range of knowledge, objective function, optimization process, parallel method, algorithm convergence, sample complexity and so on. In this embodiment, we use the SVM modeling method to construct a MACE classifier to predict whether a major cardiovascular adverse event (MACE) has occurred in the patient. We use the R language SVM modeling method to implement this process. The e1071 package is required to use the SVM. Then just call the svm function:

Svm(x,y=NULL,scale=TRUE,type=NULL,ker="radial",degree=3,gamma=if(is.vector(x))1else 1/ncol(x),coef0=0,cost =1, nu=0.5, subset, na.action=na.omit)

Here, x can be a data matrix, a data vector, or a sparse matrix. y is the result label for x data, which can be either a character vector or a numeric vector. x and y together specify the training data to be used for modeling and the basic form of the model. In this embodiment, we define x and y as follows: (1) y indicates whether MACE occurs, is a character variable, is represented by 0 and 1, 1 represents MACE, 0 represents no MACE; (2) x represents The eigenvalue data matrix, then the eigenvalues used for training are divided into three parts, namely 1) epidemiological factors, which are all the 20 clinical phenotypic data information mentioned above; 2) genetic risk factors, ie this The genotype data of 17 SNPs sites significantly associated with MACE in the invention; 3) the comprehensive factor, which combines the combined factors of epidemiological factors and genetic risk factors, that is, combines all 20 clinical phenotypes Comprehensive data on data and genotypic data for 17 SNPs. In this embodiment, according to the data feature, the type parameter selects C-classification, the kernel parameter selects radial, the gamma value is 0.015625, the cost value is 2, and the remaining parameters are default values. Then, as described in Example 1, all of the 1871 patient samples (174 patients with MACE events and 1697 control patients) in the first and second phases were selected as training sets to train data on 3 eigenvalues. Then, three prediction models are obtained, which are (1) epidemiological factors prediction model; (2) genetic risk factor prediction model; and (3) comprehensive factor prediction model combining epidemiological factors and genetic risk factors.

3. Evaluate the accuracy of the prediction model

Using the detection kit provided by the present invention, the genotypes of 17 SNPs for predicting MACE of 1837 subjects mentioned in 1 above were obtained, and then 17 SNPs of the 1837 subjects were The genotype data was substituted into the genetic risk factor prediction model as a genetic risk factor, and 20 clinical phenotypic data of 1837 subjects were used as epidemiological factors in the epidemiological factors prediction model, and 17 SNPs of 1837 subjects were used. The genotype data of the locus was used as a genetic risk factor and 20 clinical phenotypic data as epidemiological factors were substituted into the comprehensive factor prediction model, so that the data of the predicted MACE occurrence risk were obtained based on the three models respectively, and then the predicted MACE was obtained. The accuracy of the three models was evaluated by comparing the risk data with whether the subject actually had a MACE. The accuracy of the ROC curve fitting of the three models is shown in Fig. 2. The predicted comprehensive characteristic results are shown in Table 8. The results of Fig. 2 and Table 8 show that the prediction accuracy of the three models is very good; specifically, based on the present invention The predicted model of genetic risk factors for the 17 SNP loci has an AUC of 86%, which is 7 percentage points higher than the AUC (79%) of the epidemiological-based predictive model, while being based on epidemiological factors and The sensitivity and specificity of the comprehensive factor prediction model of genetic risk factors of 17 SNP loci reached high values respectively, and the model accuracy was also the best, with an AUC value of 87%.

Table 8. AUC (area under the curve) assessment of disease risk prediction models based on different factors

In summary, the comprehensive factor prediction model including the epidemiological factors and genetic risk factors of the subject has the highest prediction accuracy; that is, the comprehensive factor prediction model is used and the 17 SNP sites are based on the present invention. Genotype data and corresponding clinical phenotypic data can accurately predict the risk of major adverse cardiovascular events (MACE) in subjects with an accuracy of 87%.

Using the above comprehensive factor prediction model, the inventors predicted the risk of major adverse cardiovascular events (MACE) in multiple subjects with a predictive accuracy of up to 87%, indicating that the 17 SNP loci described in the present invention Genotype data can be used to predict the risk of major adverse cardiovascular events (MACE) with high predictive accuracy.

In summary, the kit described in the present application can be applied to predict the occurrence of major adverse cardiovascular events (MACE), and the genotypic data and clinical phenotypic data of the obtained 17 SNP loci are referred to in this application. The comprehensive factor model predicts the risk of major adverse cardiovascular events (MACE) in subjects with an accuracy of 87%.

Claims

A single nucleotide polymorphism site associated with a major adverse cardiovascular event selected from the group consisting of the rs17064642 site of the MYOM2 gene, the rs11640115 site of the WDR24 gene, the rs74569896 site of the NECAB1 gene, the rs4736529 site of the EFR3A gene, and the EFCAB13 The rs3851808 locus of the gene, the rs188799 locus of the CDC27 gene, the rs2340917 locus of the TMEM43 gene, the rs1048425 locus of the GBP1 gene, the rs7913176 locus of the NHLRC2 gene, the rs11228762 locus of the OR9G4 gene, the rs4646487 locus of the CYP4B1 gene, and the CAST gene. a combination of the rs754615 locus, the rs4729631 locus of the MUC12 gene, the rs28384507 locus of the GPA33 gene, the rs60257337 locus of the GP2 gene, the rs2241046 locus of the IL17RA gene, and the rs1060561 locus of the DOCK1 gene; among them:

The rs17064642 site of the MYOM2 gene is the 61th position of the sequence represented by SEQ ID NO: 1 from the 5' end, and the allelic type is C/T;

The rs11640115 locus of the WDR24 gene is the 61th position of the sequence represented by SEQ ID NO: 2 from the 5' end, and the allelic type is A/G;

The rs74569896 site of the NECAB1 gene is the 61th position of the sequence shown in SEQ ID NO: 3 from the 5' end, and the allelic type is G/A;

The rs4736529 site of the EFR3A gene is the 61th position of the sequence shown in SEQ ID NO: 4 from the 5' end, and the allelic type is G/C;

The rs3851808 locus of the EFCAB13 gene is the 61th position of the sequence represented by SEQ ID NO: 5 from the 5' end, and the allelic type is C/T;

The rs188799 locus of the CDC27 gene is the 61th position of the sequence shown in SEQ ID NO: 6 from the 5' end, and the allelic type is T/C;

The rs2340917 locus of the TMEM43 gene is the 61th position of the sequence shown in SEQ ID NO: 7 from the 5' end, and the allelic type is T/C;

The rs1048425 site of the GBP1 gene is the 61th position of the sequence shown in SEQ ID NO: 8 from the 5' end, and the allelic type is G/C;

The rs7913176 site of the NHLRC2 gene is the sequence shown in SEQ ID NO: 9 from the 5' end, and the allelic type is A/G;

The rs11228762 locus of the OR9G4 gene is the 61th position of the sequence represented by SEQ ID NO: 10 from the 5' end, and the allelic type is A/G;

The rs4646487 site of the CYP4B1 gene is the 61th position of the sequence represented by SEQ ID NO: 11 from the 5' end, and the allelic type is T/C;

The rs754615 site of the CAST gene is the 61th position of the sequence represented by SEQ ID NO: 12 from the 5' end, and the allele is C/G;

The rs4729631 site of the MUC12 gene is the 61th position of the sequence represented by SEQ ID NO: 13 from the 5' end, and the allelic type is T/C;

The rs28384507 locus of the GPA33 gene is the 61th position of the sequence represented by SEQ ID NO: 14 from the 5' end, and the allelic type is T/G;

The rs60257337 site of the GP2 gene is the 61th position of the sequence shown in SEQ ID NO: 15 from the 5' end, and the allelic type is C/G;

The rs2241046 locus of the IL17RA gene is the 61st position of the sequence represented by SEQ ID NO: 16 from the 5' end, and the allelic type is C/T;

The rs1060561 site of the DOCK1 gene is the 61st position of the sequence represented by SEQ ID NO: 17 from the 5' end, and the allelic type is A/G.
The single nucleotide polymorphism site according to claim 1, wherein the major adverse cardiovascular event is selected from the group consisting of cardiac death, stroke, myocardial infarction, and revascularization.
The single nucleotide polymorphism site according to claim 1 or 2, wherein the major adverse cardiovascular event is cardiac death, and the single nucleotide polymorphism site associated therewith is the IL17RA gene. Rs2241046 locus; or,

The main adverse cardiovascular event is stroke, and the single nucleotide polymorphism site associated therewith is selected from the rs4736529 site of the EFR3A gene and the rs188799 site of the CDC27 gene; or

The main adverse cardiovascular event is myocardial infarction, and the single nucleotide polymorphism site associated with it is selected from the rs17064642 locus of the MYOM2 gene, the rs11640115 locus of the WDR24 gene, the rs3851808 locus of the EFCAB13 gene, and the rs2340917 of the TMEM43 gene. Site, rs1048425 locus of GBP1 gene, rs7913176 locus of NHLRC2 gene, rs11228762 locus of OR9G4 gene, rs4646487 locus of CYP4B1 gene, rs4729631 locus of MUC12 gene, rs28384507 locus of GPA33 gene, rs60257337 locus of GP2 gene Point and rs1060561 locus of DOCK1 gene; or,

The main adverse cardiovascular event is revascularization, and the single nucleotide polymorphism site associated therewith is selected from the rs74569896 site of the NECAB1 gene and the rs754615 site of the CAST gene.
A primer pair for amplifying a single nucleotide polymorphism site according to any one of claims 1 to 3, which is selected from any one of the sequence pairs shown below or a combination of at least two:

Primer pair for amplifying the rs17064642 site SEQ ID NO: 18 and SEQ ID NO: 19;

Primer pair for amplifying the rs11640115 site SEQ ID NO: 20 and SEQ ID NO: 21;

Primer pair for amplifying the rs74569896 site SEQ ID NO: 22 and SEQ ID NO: 23;

Primer pair for amplifying the rs4736529 site SEQ ID NO: 24 and SEQ ID NO: 25;

Primer pair for amplifying the rs3851808 site SEQ ID NO: 26 and SEQ ID NO: 27;

Primer pair for amplifying the rs188799 site SEQ ID NO: 28 and SEQ ID NO: 29;

Primer pair for amplifying the rs2340917 site SEQ ID NO: 30 and SEQ ID NO: 31;

Primer pair for amplifying the rs1048425 site SEQ ID NO: 32 and SEQ ID NO: 33;

Primer pair for amplification of rs7913176 site SEQ ID NO: 34 and SEQ ID NO: 35;

Primer pair for amplifying the rs11228762 site SEQ ID NO: 36 and SEQ ID NO: 37;

Primer pair for amplifying the rs4646487 site SEQ ID NO: 38 and SEQ ID NO: 39;

Primer pair for amplifying rs754615 site SEQ ID NO: 40 and SEQ ID NO: 41;

Primer pair for amplifying the rs4729631 site SEQ ID NO: 42 and SEQ ID NO: 43;

Primer pair for amplifying the rs28384507 site SEQ ID NO: 44 and SEQ ID NO: 45;

Primer pair for amplifying the rs60257337 site SEQ ID NO: 46 and SEQ ID NO: 47;

Primer pair for amplifying the rs2241046 site SEQ ID NO: 48 and SEQ ID NO: 49;

Primer pairs for amplifying the rs1060561 site were SEQ ID NO: 50 and SEQ ID NO: 51.
A probe pair for detecting a single nucleotide polymorphism site according to any one of claims 1 to 3, which is selected from any one or a combination of at least two of the following probe pairs:

Probe pair for detecting rs17064642 site pairs SEQ ID NO: 52 and SEQ ID NO: 53;

Probe pair for detecting rs11640115 site pairs SEQ ID NO: 54 and SEQ ID NO: 55;

Probe pair for detecting rs74569896 site SEQ ID NO: 56 and SEQ ID NO: 57;

Probe pair for detecting rs4736529 site pairs SEQ ID NO: 58 and SEQ ID NO: 59;

Probe pair for detecting rs3851808 site SEQ ID NO: 60 and SEQ ID NO: 61;

Probe pair for detecting rs188799 site SEQ ID NO: 62 and SEQ ID NO: 63;

Probe pair for detecting rs2340917 site SEQ ID NO: 64 and SEQ ID NO: 65;

Probe pair for detecting rs1048425 site pairs SEQ ID NO: 66 and SEQ ID NO: 67;

Probe pair for detecting rs7913176 site pairs SEQ ID NO: 68 and SEQ ID NO: 69;

Probe pair for detecting rs11228762 site pairs SEQ ID NO: 70 and SEQ ID NO: 71;

Probe pair for detecting rs4646487 site SEQ ID NO: 72 and SEQ ID NO: 73;

Probe pair for detecting rs754615 site pair SEQ ID NO: 74 and SEQ ID NO: 75;

Probe pair for detecting rs4729631 site SEQ ID NO: 76 and SEQ ID NO: 77;

Probe pair for detecting rs28384507 site SEQ ID NO:78 and SEQ ID NO:79;

Probe pair for detecting rs60257337 site SEQ ID NO: 80 and SEQ ID NO: 81;

Probe pair for detecting rs2241046 site SEQ ID NO: 82 and SEQ ID NO: 83;

Probe pairs for detecting the rs1060561 site were SEQ ID NO: 84 and SEQ ID NO: 85.
The single nucleotide polymorphism site according to any one of claims 1 to 3, the primer pair of claim 4 or the probe pair of claim 5, which causes a major adverse cardiovascular disease in a predicted subject The purpose of the event.
The use according to claim 6, wherein the subject is treated with percutaneous coronary intervention;

Preferably, the primary adverse cardiovascular event comprises any one or a combination of at least two of cardiogenic death, stroke, myocardial infarction, and revascularization.
A method of predicting a risk of a major adverse cardiovascular event in a subject, comprising: detecting a gene of a single nucleotide polymorphism site according to any one of claims 1 to 3 in a subject to be tested Type; predicts the risk of major adverse cardiovascular events in the subject based on the resulting genotype.
The method of claim 8, wherein the relationship between the genotype of the following single nucleotide polymorphism site detected in the subject and the risk of developing a major adverse cardiovascular event comprises:

A subject having a C allele at the rs17064642 site in the MYOM2 gene is at a higher risk of major adverse cardiovascular events than a subject having a T allele at that site, preferably 1.98-3.87 times more likely More preferably 2.76 times;

A subject with an A allele at the rs11640115 locus in the WDR24 gene has a lower risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 0.35-0.63 times More preferably 0.47 times;

Subjects with the G allele in the rs74569896 locus in the NECAB1 gene are at a higher risk of major adverse cardiovascular events than subjects with the A allele at this locus, preferably 1.49-2.51 times More preferably 1.93 times;

A subject having a G allele at the rs4736529 site in the EFR3A gene is at a higher risk of major adverse cardiovascular events than a subject having a C allele at that site, preferably 1.65-3.31 times More preferably 2.33 times;

Subjects with the C allele at the rs3851808 locus in the EFCAB13 gene are at a higher risk of major adverse cardiovascular events than subjects with the T allele at this locus, preferably 1.32-2.06 times More preferably 1.65 times;

A subject having a T allele at the rs188799 locus in the CDC27 gene is at a higher risk of major adverse cardiovascular events than a subject having a C allele at that locus, preferably 1.43-2.55 times More preferably 1.91 times;

A subject with a T allele at the rs2340917 site in the TMEM43 gene has a lower risk of major adverse cardiovascular events than a subject with a C allele at that site, preferably 0.43-0.72 times More preferably 0.56 times;

A subject with a G allele at the rs1048425 locus in the GBP1 gene has a higher risk of major adverse cardiovascular events than a subject with a C allele at that locus, preferably 1.30-1.99 times its , more preferably 1.61 times;

A subject with an A allele at the rs7913176 locus in the NHLRC2 gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 1.26-1.93 times More preferably 1.56 times;

A subject with an A allele at the rs11228762 locus in the OR9G4 gene has a lower risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 0.48-0.77 times More preferably 0.61 times;

A subject with a T allele at the rs4646487 site in the CYP4B1 gene has a lower risk of major adverse cardiovascular events than a subject with a C allele at that site, preferably 0.40-0.72 times More preferably 0.53 times;

A subject with a C allele at the rs754615 locus in the CAST gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 1.38-2.53 times More preferably 1.87 times;

A subject with a T allele at the rs4729631 locus in the MUC12 gene has a lower risk of major adverse cardiovascular events than a subject with a C allele at that locus, preferably 0.31-0.67 times More preferably 0.46 times;

A subject with a T allele at the rs28384507 locus in the GPA33 gene is at a lower risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 0.34-0.69 times More preferably 0.48 times;

A subject with a C allele at the rs60257337 locus in the GP2 gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably, it is 1.25-1.94 times more likely More preferably 1.56 times;

A subject with a C allele at the rs2241046 locus in the IL17RA gene is at a higher risk of major adverse cardiovascular events than a subject with a T allele at that locus, preferably 1.28-2.10 times more likely More preferably 1.64 times;

A subject with an A allele at the rs1060561 locus in the DOCK1 gene is at a higher risk of major adverse cardiovascular events than a subject with a G allele at that locus, preferably 1.29-2.16 times more More preferably, it is 1.67 times.
A method according to claim 8 or claim 9, comprising:

1) extracting the genomic DNA of the subject;

2) PCR amplification of the single nucleotide polymorphism site according to any one of claims 1 to 3;

3) detecting the amplification product and genotyping the amplification product;

4) Predict the risk of adverse cardiovascular events in the subject based on genotype.
The method of claim 8 wherein said subject is subjected to percutaneous coronary intervention;

Preferably, the primary adverse cardiovascular event comprises any one or a combination of at least two of cardiogenic death, stroke, myocardial infarction, and revascularization.
A kit for predicting a major adverse cardiovascular event in a subject, comprising a primer pair for amplifying a single nucleotide polymorphism site according to any one of claims 1 to 3 and/or A probe pair for detecting a single nucleotide polymorphism site according to any one of claims 1-3.
The kit according to claim 12, comprising the primer pair according to claim 4 and/or the probe pair according to claim 5.