CN117143989A - miRNA marker for acute myocardial infarction and application thereof - Google Patents
miRNA marker for acute myocardial infarction and application thereof Download PDFInfo
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Abstract
The invention provides a miRNA marker for acute myocardial infarction and application thereof, and belongs to the field of medical diagnosis. The miRNA markers of the acute myocardial infarction are the combination of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504. The invention also provides a detection kit based on miRNA markers of acute myocardial infarction, and the detection kit can be used for effectively identifying the acute myocardial infarction by combining machine learning, and the accuracy rate can reach 86.1%.
Description
Technical Field
The invention belongs to the field of medical diagnosis, and particularly relates to a miRNA marker for acute myocardial infarction and application thereof.
Background
Myocardial infarction is a critical cardiovascular disease with a high incidence. Because the early myocardial infarction has no obvious symptoms, corresponding therapeutic measures cannot be found and given in time, complications such as heart failure, malignant arrhythmia and the like are easily caused when acute myocardial infarction (acute myocardial infarction, AMI) occurs, and the patients can die seriously, so that the acute myocardial infarction becomes one of main causes of death in cardiovascular diseases. In clinic, creatine kinase isozymes (CK-MB), troponin (cTn) and myoglobin (Mvo) are commonly used for diagnosing acute myocardial infarction, but the specificity is not very good, so that the efficiency of identifying the acute myocardial infarction is not high.
Exosomes (exosomes) are a class of extracellular vesicles containing nucleic acids, proteins, lipids secreted by cells, which play roles in substance transport, signal communication, etc. among cells, and are also involved in pathophysiological processes such as immune responses, cell differentiation, tumor invasion, etc. in the body. AMI increases the content of exosomes secreted by many cells in the body, and therefore the RNA content transported by exosomes varies. Thus, the use of miRNA content variation for the identification of healthy and AMI patients is an important point of research in the field.
Machine learning is a scientific study of algorithms and statistical models used by computer systems to efficiently perform specific tasks without using explicit instructions, but relying on patterns and reasoning. The machine learning covers probability theory knowledge, statistical knowledge, approximate theory knowledge and complex algorithm knowledge, and is widely applied to the fields of data mining, voice recognition, statistics and the like. At present, there is no report that machine learning and exosome miRNAs are effectively combined for identifying AMI.
Disclosure of Invention
Accordingly, the present invention aims to provide miRNA markers for acute myocardial infarction, which can be used for identifying acute myocardial infarction in combination.
The invention also aims to provide a kit for diagnosing acute myocardial infarction, and the kit can be used for AMI identification with high accuracy and high sensitivity through machine learning construction combination.
In order to achieve the above object, the present invention provides the following technical solutions:
the invention provides miRNA markers of acute myocardial infarction, which are a combination of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504.
Preferably, the miRNA marker is expressed at a higher level in the plasma exosomes of patients with acute myocardial infarction than in healthy people.
The invention also provides application of the miRNA marker in preparation of a prospective diagnosis kit for acute myocardial infarction.
The invention provides a kit for acute myocardial infarction diagnosis, which comprises a reverse transcription reagent and a PCR primer for detecting a reverse transcription product of a plasma exosome miRNA marker, wherein the exosome miRNA marker is a combination of six of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504.
Preferably, the kit comprises a negative control which is the plasma exosome of a normal healthy population.
Preferably, the PCR primer includes:
PCR primer for detecting rno-miR-3473 reverse transcription product, the nucleotide sequence of which is shown in SEQ ID NO. 1; PCR primer for detecting reverse transcription product of rno-miR-107-3p, with nucleotide sequence shown in SEQ ID NO. 2; PCR primer for detecting reverse transcription product of rno-miR-218a-2-3p, wherein the nucleotide sequence is shown in SEQ ID NO. 3; PCR primer for detecting reverse transcription product of rno-miR-760-3p, wherein the nucleotide sequence is shown as SEQ ID NO. 4; PCR primer for detecting reverse transcription product of rno-miR-490-5p, the nucleotide sequence of which is shown as SEQ ID NO. 5; PCR primer for detecting reverse transcription product of rno-miR-504, and the nucleotide sequence is shown in SEQ ID NO. 6.
The invention provides a device for diagnosing acute myocardial infarction, which comprises the kit.
Preferably, the method further comprises an AMI authentication machine learning model established by utilizing orange software.
Compared with the prior art, the invention has the following beneficial effects:
the miRNA markers for acute myocardial infarction comprise six miRNAs, and can be used for identifying acute myocardial infarction in a combined way. Compared with methods of pathological morphology, immunohistochemistry, metabolism and the like, the miRNA marker provided by the invention has the advantages that the miRNA marker has smaller factors such as environment and temperature, the expression quantity of miRNA related to the acute myocardial infarction is obtained from the aspect of molecular biology, and the identification rate of the acute myocardial infarction is improved by combining machine learning, and the miRNA marker has high accuracy and strong sensitivity.
Drawings
Fig. 1: AMI group miRNA and control group miRNA high-throughput sequencing volcanic image;
fig. 2: relative gene expression levels of 6 mirnas;
fig. 3: ROC curves for multifactor analysis of 6 mirnas.
Detailed Description
The invention provides miRNA markers of acute myocardial infarction, which are a combination of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504. The invention combines six miRNAs, can be used for identifying acute myocardial infarction, provides better basis for early diagnosis of acute myocardial infarction, and predicts disease risk.
Of the six miRNAs, the nucleic acid sequence of rno-miR-3473 is UCUAGGGCUGGAGAGAUGGCUA, and is shown in SEQ ID NO. 7; the nucleic acid sequence of rno-miR-107-3p is AGCAGCAUUGUACAGGGCUAUCA, and is shown in SEQ ID NO. 8; the nucleic acid sequence of rno-miR-218a-2-3p is CAUGGUUCUGUCAAGCACCGCG, and is shown as SEQ ID NO. 9; the nucleic acid sequence of rno-miR-760-3p is CGGCUCUGGGUCUGUGGGGA, and is shown as SEQ ID NO. 10; the nucleic acid sequence of rno-miR-490-5p is CCAUGGAUCUCCAGGUGGGU, and is shown as SEQ ID NO. 11; the nucleic acid sequence of rno-miR-504 is AGACCCUGGUCUGCACUCUGUC, and is shown in SEQ ID NO. 12.
The miRNA marker has higher expression level in the plasma exosomes of acute myocardial infarction patients than in healthy people.
The invention also provides application of the miRNA marker in preparation of a prospective diagnosis kit for acute myocardial infarction.
The invention also provides a kit for diagnosing acute myocardial infarction, which comprises a reverse transcription reagent and a PCR primer for detecting a reverse transcription product of a plasma exosome miRNA marker, wherein the exosome miRNA marker is a combination of six of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504. The kit also comprises a negative control, wherein the negative control is the plasma exosome of normal healthy people. Preferably, the reverse transcription reagent of the present invention adopts the reagent in the Tiangen reverse transcription kit. According to the invention, whether the acute myocardial infarction is in an early stage can be judged by detecting and comparing the expression levels of six miRNAs in the plasma exosomes to be detected with the expression levels of six miRNAs in the plasma exosomes of healthy people.
The PCR primer in the kit comprises:
PCR primer for detecting rno-miR-3473 reverse transcription product, the nucleotide sequence of which is shown in SEQ ID NO. 1; PCR primer for detecting reverse transcription product of rno-miR-107-3p, with nucleotide sequence shown in SEQ ID NO. 2; PCR primer for detecting reverse transcription product of rno-miR-218a-2-3p, wherein the nucleotide sequence is shown in SEQ ID NO. 3; PCR primer for detecting reverse transcription product of rno-miR-760-3p, wherein the nucleotide sequence is shown as SEQ ID NO. 4; PCR primer for detecting reverse transcription product of rno-miR-490-5p, the nucleotide sequence of which is shown as SEQ ID NO. 5; PCR primer for detecting reverse transcription product of rno-miR-504, and the nucleotide sequence is shown in SEQ ID NO. 6.
The invention also provides a device for diagnosing acute myocardial infarction, which comprises the kit. According to the invention, the results obtained by the detection of the kit are combined with machine learning, an AMI identification machine learning model is established by utilizing the orange software, the identification rate of acute myocardial infarction is improved, the factors such as environment and temperature are small, and the accuracy rate can reach 86.1%.
The technical solutions provided by the present invention are described in detail below with reference to examples, but they should not be construed as limiting the scope of the present invention.
In the following examples, conventional methods are used unless otherwise specified.
Materials, reagents and the like used in the examples described below are commercially available unless otherwise specified.
Example 1
1. Construction of acute myocardial infarction animal model
1. Grouping modeling before experiments
12 Wistar male adult rats with the weight of 210 g-260 g are selected and divided into a pair group and an AMI group for simulating acute myocardial infarction, and 2 groups in total, and are cultured under the condition of 12 hours of day and night alternation constant temperature. Control group: 6 Wistar rats were obtained and sham operated to remove cardiac death after surgery and blood samples were drawn. AMI group: 6 Wistar rats were harvested and subjected to myocardial infarction surgery. After 30min, cardiac death was excised and a blood sample was drawn.
1.2 modeling
Weighing: the rats were placed in a rat holder and their weights were weighed. And taking out the rat, weighing the weight of the rat fixer, and obtaining the weight of the rat. (rats were fasted for 12 hours prior to surgery, were free to drink water.)
Anesthesia: rats were anesthetized with chloral hydrate (30 mg/100 g) at a concentration of 10% by intraperitoneal injection. Anesthesia was considered successful when the rat had reduced muscle tone, slowed breathing, and a slow cornea reflex.
Fixing: the rat operation table forelimb fixing band is sleeved above the rat wrist joint, the hind limb fixing band is sleeved above the ankle joint, the limbs are straightened, the fixing band is tied with 4 movable buckles, and then the head fixing band is used for fixing the head after the upper jaw incisors of the rat, so that the neck of the rat is stretched, and the later operation is convenient.
Shearing: the left hand tightens the skin at the surgical site (chest and neck) and the right hand trims the hair against the skin with a shaver.
Tracheal cannula: perpendicular to the middle upper part of the neck of the rat, making 1-2 cm incision, and separating superficial fascia, thyroid gland, muscle, etc. in turn to expose the trachea. A V-shaped incision is made at the position 1mm above thyroid cartilage, a trachea cannula is connected with a micro animal breathing machine, the frequency is 60 times/minute, the moisture is 6 mL/time, and the breathing ratio is 1:2.
Open chest separation left coronary artery: skin is cut between 3 to 4 intercostals on the left side of the sternum, pectoral muscle is separated in a blunt way, blood vessels are prevented from being damaged as much as possible, bleeding is reduced, and intercostal muscles and ribs are exposed. 3 to 5 costal cartilage is cut off by surgical scissors. The exposed chest wall rim is clamped and secured with hemostats and the chest is opened. The envelope was centrifuged with forceps blunt parts to expose the heart. The left auricle of the heart was found, the left auricle was turned up, the left coronary artery was found to be inferior and branches were developed, wherein the left side was the anterior descending left coronary artery, the myocardium near the anterior descending left coronary artery was gently lifted with forceps about 3mm below the starting position of the branches, and the suture needle line was passed under the anterior descending left coronary artery. The rats of the control group are not ligated through the suture, and the AMI group rats are fastened after passing through the suture.
When the heart electric lead and the BL-420 signal acquisition system are connected, and the rat electrocardiogram is raised from the normal S-T section, the AMI model is initially considered to be successfully constructed.
2. Blood collection
After the control group model and the AMI model are established and reach the expectations, the heart is clamped by forceps, the heart is sheared about 5mm above the root of the aorta, two groups of 5mL syringes are used for sucking outflow blood into 5mL EDTA anticoagulation tubes, and shaking and mixing are carried out uniformly, so that the anticoagulation agent in the tubes and the blood are fully mixed uniformly to avoid coagulation.
3. Separation of plasma
The collected blood is stored in EDTA tube at normal temperature or 4 ℃ to separate plasma as much as possible in 1 h: (1) centrifuging at 4deg.C and 1900 Xg for 10min, and collecting supernatant; (2) centrifuging at 4deg.C for 15min at 3000 Xg, and collecting supernatant. The final result is plasma.
4. Exosome extraction
1. Samples were pretreated, centrifuged at 4℃and 10000 Xg for 20min, and the supernatant was transferred to a new centrifuge tube.
2. 4 volumes of 1 XPBS were added to the pre-treated samples and thoroughly mixed.
3. To the PBS diluted sample, the reagent 41202-A in the "serum/plasma exosome rapid extraction kit" was added in an amount equal to the initial sample volume. Vortex vibration mixing for 1min, and standing in refrigerator at 4deg.C for 2 hr.
4. After removal, the supernatant was discarded as much as possible by centrifugation at 10000 Xg at 4℃for 60min, and the exosome-rich pellet was collected.
5. According to an initial sample: 1×pbs=2.5:1, the pellet after centrifugation was blow-mixed with 1×pbs solution, and the exosomes were resuspended in PBS and transferred to a new centrifuge tube.
5. RNA extraction of exosomes
1. Adding miRNA detection external parameters of 0.5-1 mu L into PBS solution of exosomes, adding equal-volume lysate MZ into the exosome solution, and uniformly mixing for 30s by oscillation of an oscillator.
2. And standing at room temperature for 5min to completely separate the nucleic acid protein complex.
3. Centrifuge at 12000rpm (13400 Xg) for 10min, collect supernatant and transfer to a new RNase-free centrifuge tube.
4. 200. Mu.L of chloroform was added thereto, the tube was covered with a cap, vigorously shaken for 15s, and left at room temperature for 5 minutes.
5. Centrifuge at 12000rpm (13400 Xg) for 15min at room temperature, the sample will separate into three layers: the yellow organic phase, the middle layer and the colorless aqueous phase, the RNA being predominantly in the aqueous phase, the aqueous phase is transferred to a new tube for the next operation.
6. Measuring the volume of the transfer liquid, slowly adding 1/3 of the volume of the transfer liquid into the absolute ethyl alcohol, and uniformly mixing. Transferring the obtained solution and precipitate into an adsorption column miRspin, standing at room temperature for 2min, centrifuging at 12000rpm (13400 Xg) at room temperature for 30s, centrifuging, discarding the adsorption column miRspin, and retaining the effluent.
7. Measuring the volume of the effluent, slowly adding 2/3 of the volume of absolute ethyl alcohol into the effluent, and uniformly mixing. Transferring the obtained solution and precipitate into an adsorption column miralute, standing at room temperature for 2min, centrifuging at 12000rpm (13400 Xg) for 30s, centrifuging, discarding the effluent, and retaining the adsorption column miralute.
8. 500. Mu.L of deproteinized solution MRD was added to the column mirilute, allowed to stand at room temperature for 2min, centrifuged at 12000rpm (13400 Xg) for 30s, and the waste solution was discarded.
9. To the column mirinlite, 500. Mu.L of a rinse solution RW was added, and the mixture was allowed to stand at room temperature for 2 minutes, centrifuged at 12000rpm (13400 Xg) at room temperature for 30 seconds, and the waste liquid was discarded.
10. The operation 9 is repeated.
11. The column mirilute was placed in a 2mL collection tube and centrifuged at 12000rpm (13400 Xg) for 1min at room temperature to remove residual liquid. Placing on an ultra-clean workbench for ventilation for 30min to fully dry.
12. Transferring the adsorption column miralute into a new RNase-Free 1.5mL centrifuge tube, adding 15-30 mu L of RNase-Free ddH 2 O, left at room temperature for 2min, and centrifuged at 12000rpm (13400 Xg) for 2min.
And performing small RNA library sequencing on the obtained RNA, performing bioinformatics analysis on the obtained data, and comparing miRNAs differentially expressed in an AMI experimental group and a control group to obtain miRNAs with obvious differences, wherein the miRNAs are shown in figure 1. In fig. 1, there were 138 up-regulated and 124 down-regulated mirnas in the AMI experimental group compared to the control group. Up-regulated miRNAs which accord with the upward trend are obtained through RT-PCR verification, and the six miRNAs comprise rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504.
Example 2
qRT-PCR was performed on rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504 using the exosome RNA obtained in example 1.
1. Reverse transcription reaction
The miRNA concentration in the sample was measured using NanoDrop. A20 mu L reverse transcription system is prepared by using a root kit, and is subjected to reverse transcription by a PCR instrument. The cDNA was stored in a refrigerator at 4℃for a short period.
Reverse transcription system: (1) 2X miRNA RT Reaction Buffer: 10. Mu.L; (2) miRNA RT Enzyme Mix: 2. Mu.L; (3) total RNA: 2. Mu.L (containing 2ng RNA); (4) RNase-Free ddH 2 O: 6. Mu.L; reverse transcription was performed to obtain cDNA according to the following conditions: 42 ℃ 60min,95 ℃ 3min,4 ℃ 5min.
2. qRT-PCR reaction
1. cDNA samples were diluted 5-fold.
Using TIANGEN qRT-PCR kit, 20 μl of qRT-PCR system was formulated: (1) 2X miRcute Plus miRNAPreMix (SYBR)&ROX): 10. Mu.L; (2) forward primer: 0.4. Mu.L; (3) reverse Primer: 0.4. Mu.L; (4) miRNA first strand cDNA: 2. Mu.L; (5) ddH 2 O：7.2μL。
The qRT-PCR reaction primer sequences of the rno-miR-3473, the rno-miR-107-3p, the rno-miR-218a-2-3p, the rno-miR-760-3p, the rno-miR-490-5p and the rno-miR-504 are shown as SEQ ID NO. 1-SEQ ID NO.6 in sequence:
SEQ ID NO.1：GCTCTAGGGCTGGAGAGATGGCTA；
SEQ ID NO.2：GGAGCAGCATTGTACAGGGCTATCA；
SEQ ID NO.3：CCATGGTTCTGTCAAGCACCGC；
SEQ ID NO.4：CGGCTCTGGGTCTGTGGGG；
SEQ ID NO.5：GCCATGGATCTCCAGGTGGGT；
SEQ ID NO.6：GGAGACCCTGGTCTGCACTCTGTC。
the experiment was completed using a fluorescent quantitative PCR instrument, and the PCR reaction experiment was performed under the following conditions: 95℃15min,94℃20s,65℃30s,5 cycles, 72℃34s,94℃20s,45 cycles, 60℃34s.
The external reference (CR 100-01) was detected by TIANGEN External control for miRNAs, and the external reference name was RNU6B, and the external reference upstream detection primer (CD 200-01) was used in combination with the external reference. The results were analyzed using the ΔΔct method using the SYBR dye method.
Quantification by fluorescenceObtaining Ct of each group by PCR, wherein miRNA detection external reference primer is used as reference; delta Ct is obtained by subtracting the Ct of the external reference from the Ct of the miRNA related to AMI, and comparing the relative expression amounts of genes between different groups according to the following formula: relative gene expression = 2 ^ -
(. DELTA.Ct sample-DELTA.Ct control).
The delta Ct values of the control group (the difference between the CT values of the target miRNA and the external reference) and the AMI experimental group are shown in Table 1, and the relative gene expression amounts of 6 miRNAs are shown in FIG. 2.
TABLE 1 DeltaCt values for the experimental and control groups
| miRNA | Control delta Ct value | Experimental group delta Ct values |
| rno-miR-3473 | 4.183202 | 2.81904 |
| rno-miR-107-3p | 8.278244 | 7.303816 |
| rno-miR-218a-2-3p | 11.01309 | 10.27661 |
| rno-miR-760-3p | 8.821072 | 7.748212 |
| rno-miR-490-5p | 15.47776 | 14.79969 |
| rno-miR-504 | 8.084871 | 6.051089 |
As can be seen from FIG. 2, after 30min of myocardial infarction, 6 miRNAs were expressed in an increased amount, rno-miR-3473 was 1.9371 times that of the control group, rno-miR-107-3p was 1.62054 times that of the control group, rno-miR-218a-2-3p was 1.38407 times that of the control group, rno-miR-760-3p was 1.9046 times that of the control group, rno-miR-490-5p was 2.27318 times that of the control group, and rno-miR-504 was 3.98914 times that of the control group.
Multifactor analysis was performed on the 6 mirnas above to obtain ROC curves, the results are shown in fig. 3. As can be seen from fig. 3, the AUC is 0.944, and the correlation is high, which indicates that the above 6 mirnas can be used for identifying myocardial infarction in combination.
2. After 50 times dilution of cDNA sample, qRT-PCR was performed using rno-miR-3473 as an example, and CT values are shown in Table 2 (S is control diluted sample, A30 is experimental diluted sample):
TABLE 2 Ct values of target gene and external reference at 50-fold dilution
3. After 100 times dilution of cDNA sample, qRT-PCR was performed on rno-miR-3473, and CT values are shown in Table 3 (S is control diluted sample, A30 is experimental diluted sample):
TABLE 3 Ct values of the target gene and the external reference at 100-fold dilution
| Sample of | Ct value of target gene | External Ct value |
| S-256 | 27.0893 | 22.99484 |
| S-277 | 26.90666 | 21.00208 |
| S-279 | 27.05719 | 22.47003 |
| A30-254 | 26.64666 | 22.90053 |
| A30-311 | 26.91617 | 22.88509 |
| A30-319 | 26.62717 | 23.0691 |
As can be seen from tables 2 and 3, the cDNA was diluted 50-fold and 100-fold, and the sample was subjected to the desired gene rno-miR-3473 can still detect CT value of target gene, target gene can still be effectively expressed and detected, and can be used for 2 ^-△△ct And calculating, wherein the calculating is used for carrying out data analysis on the AMI authentication model.
Similarly, qRT-PCR is performed on the rno-miR-107-3p, the rno-miR-218a-2-3p, the rno-miR-760-3p, the rno-miR-490-5p and the rno-miR-504, cDNA of the miRNAs is subjected to 50-time dilution and 100-time dilution, and according to the relation between CT values and concentration, the CT value difference is 1 and the initial concentration difference is doubled, and as the CT values of the miRNAs are 22-28, the CT values can still be detected after 100 times dilution, and the miRNAs can be detected for data analysis.
CT values of 6 miRNAs were 2 ^-△△CT The data of Table 4 were calculated, and each of Sram and each of AMI in Table 4 for 30min was a sample. Based on the data set shown in Table 4, machine learning model construction was performed using the orange software (https:// orange. Biolab. Si /).
Table 4 data set used to build the model
3. Machine learning
Subjecting the CT value obtained after qRT-PCR to 2 ^-ΔΔCt After the method analysis, an AMI authentication machine learning model is established by utilizing the orange software.
Based on the KNN model established by the data set of Table 4, unknown samples are subjected to 2 by inputting the expression amounts of 6 miRNAs ^-△△ct And (5) calculating to judge whether AMI occurs or not, wherein the accuracy is 86.1%. The AMI identification accuracy and sensitivity of the model are higher, and the results are shown in Table 5.
TABLE 5 AMI discrimination accuracy and sensitivity results for model
The parameters for the KNN model construction are as follows: number of neighbors:5, a step of; metric: euclidean; weight: form.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (8)
1. The miRNA marker for acute myocardial infarction is characterized by comprising a combination of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504.
2. The miRNA marker of claim 1, wherein the miRNA marker is expressed at a higher level in the plasma exosomes of the patient suffering from acute myocardial infarction than in healthy people.
3. Use of the miRNA marker of claim 1 for the preparation of a prospective diagnostic kit for acute myocardial infarction.
4. A kit for diagnosing acute myocardial infarction, which is characterized by comprising a reverse transcription reagent and a PCR primer for detecting a reverse transcription product of a plasma exosome miRNA marker, wherein the exosome miRNA marker is a combination of six of rno-miR-3473, rno-miR-107-3p, rno-miR-218a-2-3p, rno-miR-760-3p, rno-miR-490-5p and rno-miR-504.
5. The kit of claim 4, wherein the kit comprises a negative control that is plasma exosomes in a normal healthy population.
6. The kit of claim 4, wherein the PCR primers comprise:
PCR primer for detecting rno-miR-3473 reverse transcription product, the nucleotide sequence of which is shown in SEQ ID NO. 1; PCR primer for detecting reverse transcription product of rno-miR-107-3p, with nucleotide sequence shown in SEQ ID NO. 2; PCR primer for detecting reverse transcription product of rno-miR-218a-2-3p, wherein the nucleotide sequence is shown in SEQ ID NO. 3; PCR primer for detecting reverse transcription product of rno-miR-760-3p, wherein the nucleotide sequence is shown as SEQ ID NO. 4; PCR primer for detecting reverse transcription product of rno-miR-490-5p, the nucleotide sequence of which is shown as SEQ ID NO. 5; PCR primer for detecting reverse transcription product of rno-miR-504, and the nucleotide sequence is shown in SEQ ID NO. 6.
7. A device for diagnosis of acute myocardial infarction, comprising a kit according to any one of claims 4 to 6.
8. The apparatus of claim 7, further comprising an AMI authentication machine learning model established using orage software.
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