Sudden coronary artery death specific biomarker combination and application and product thereof

Abstract

The invention provides a sudden coronary artery death specificity biomarker combination as well as application and a product thereof, and belongs to the technical field of forensic medicine. The biomarker combination disclosed by the invention is prepared from ascorbic acid, docosahexaenoic acid, carnitine, glutamine and n-leucine. The biomarker combination is obviously changed in serum samples of sudden coronary artery death individuals, and shows good diagnostic performance after ROC verification, which prompts that the biomarker combination has the potential of being applied to sudden coronary artery death forensic medicine identification. The potential application value of the non-targeted metabonomics strategy in difficult and complex cause identification provides a new thought for molecular diagnosis of death cause investigation.

Description

Technical Field

[0001] The present invention belongs to the technical field of forensic medicine, and in particular relates to the application of biomarkers in the preparation of forensic diagnosis products for sudden coronary death. Background Art

[0002] Sudden cardiac death refers to natural death caused by cardiac reasons, preceded by a sudden loss of consciousness, and usually occurs within 1 hour after the onset of symptoms. Sudden coronary death (SCD) refers to sudden cardiac death caused by coronary artery abnormalities, and is the most common type of sudden cardiac death. In forensic practice, the vast majority of sudden coronary deaths are caused by atherosclerosis of one or more coronary arteries, leading to stenosis or obstruction of the lumen. Some cases are complicated by thrombosis, and a few cases are caused by severe contraction of the coronary vessels due to coronary artery spasm, leading to lumen occlusion. In this case, the coronary arteries have only mild or even no atherosclerotic lesions.

[0003] Coronary atherosclerosis, also known as coronary heart disease (CHD), is the main cause of coronary artery abnormalities. There are currently four main theories about the pathogenesis of atherosclerosis, namely, the lipid infiltration theory, the endothelial injury-reaction theory, the platelet aggregation and thrombosis theory, and the smooth muscle cell cloning theory. The formation of coronary atherosclerosis specifically includes a series of vascular pathophysiological changes such as vascular intima damage, lipid deposition, atherosclerotic plaque formation, fibrosis, and vascular wall sclerosis. Among them, the stability of coronary atherosclerotic plaques is the main determinant of sudden death. Coronary artery spasm (CAS) refers to the incomplete or complete occlusion of blood vessels caused by transient contraction of the coronary artery, which leads to myocardial ischemia and even sudden death. Coronary artery spasm often coexists with coronary atherosclerosis, but in a few cases, patients without atherosclerosis may also experience coronary artery spasm. Age, smoking, hypertension and high cholesterol have been reported as risk factors for coronary artery spasm. The pathogenesis of coronary artery spasm has not yet been elucidated, but it is currently believed that autonomic nervous system dysfunction, endothelial dysfunction and vascular smooth muscle cell hyperreactivity may be closely related to the onset of coronary artery spasm.

[0004] Although the pathogenesis of coronary atherosclerosis and coronary artery spasm is different, from the perspective of the pathological mechanism of sudden death caused by coronary artery abnormalities, both conditions can cause stenosis or blockage of the coronary arteries, leading to acute myocardial ischemia (AMI), causing local electrophysiological disorders, triggering severe arrhythmias and then cardiac arrest leading to death. Among them, acute myocardial ischemia is the most common potential pathological basis for sudden coronary death.

[0005] In forensic identification practice, cases of sudden coronary death are common, most of which have coronary atherosclerosis stenosis of grade III or IV, and old or new myocardial infarction foci and myocardial fibrosis can be seen. Combined with clinical history and case investigation, it is relatively easy to explain the cause of death. However, in some cases, only grade II to III coronary artery stenosis or even no obvious coronary artery stenosis can be seen, which is speculated to be related to the combination of coronary artery spasm on the basis of this lesion. Due to the rapid death process and short myocardial ischemia time, histological examination can only observe wavy changes in myocardial fibers or unclear horizontal stripes, which does not have specific diagnostic value. However, detection methods such as myocardial enzyme spectrum are easily affected by postmortem blood autolysis and cannot be realized, making it difficult to determine the cause of death from the heart in such cases. In addition, most sudden coronary deaths occur suddenly and are easily mistaken for violent deaths. They are often questioned by many parties, which further increases the difficulty of identification. Therefore, it is crucial to accurately understand the essential characteristics of sudden coronary death and screen accurate and reliable diagnostic markers for scientific and objective identification of the cause of death.

[0006] Metabolomics, as the omics technology closest to phenotype, focuses on the metabolic pathways of endogenous metabolites in organisms as a whole, organs or tissues, the influence of genetic or environmental factors on them, and the laws of their changes over time. Metabolites are the terminal link in the regulation of biochemical activities of biological systems. The analysis of metabolic changes in biological fluids can more directly and accurately reflect the pathophysiological state of the body. In recent years, the application potential of metabolomics in forensic identification research has also been fully demonstrated. In the identification of causes of death such as sudden cardiac death, mechanical asphyxiation, electric shock death, hypothermia, and sudden infant death syndrome, the discovery of related metabolic markers and metabolic pathways provides a certain basis for analyzing the metabolic changes and lethal mechanisms of complex causes of death.

[0007] In summary, in order to solve the forensic identification problems caused by sudden coronary death, a non-targeted metabolomics method was used to detect differential metabolites in rat serum, explore the metabolic pathways of sudden coronary death, screen specific diagnostic markers of sudden coronary death, and verify them in human case samples of sudden coronary death, so as to provide a reference for the forensic identification of sudden coronary death. Summary of the invention

[0008] In view of the above-mentioned deficiencies, the present invention provides a biomarker combination specific for sudden coronary death, and its application and product. The biomarker combination described in the present invention is composed of ascorbic acid, docosahexaenoic acid, carnitine, glutamine and norleucine. The biomarker combination undergoes significant changes in serum samples of individuals with sudden coronary death, and shows good diagnostic performance after ROC verification, suggesting that it has the potential to be applied in forensic identification of sudden coronary death. The potential application value of the non-targeted metabolomics strategy of the present invention in the identification of difficult and complex causes of death provides a new idea for the molecular diagnosis of the cause of death investigation.

[0009] The technical solution of the present invention includes:

[0010] In a first aspect, the present invention provides a biomarker combination specific for sudden coronary death, wherein the biomarker combination consists of ascorbic acid, docosahexaenoic acid, carnitine, glutamine and norleucine.

[0011] In a second aspect, the present invention provides the use of a biomarker combination in the preparation of a product for forensic diagnosis of sudden coronary death.

[0012] Preferably, the biomarker combination consists of ascorbic acid, docosahexaenoic acid, carnitine, glutamine and norleucine.

[0013] Further preferably, the biomarker combination may also include: one or more of ascorbic acid, creatine, and spermidine.

[0014] Specifically, the application determines whether it is sudden coronary death by detecting the expression level of biomarkers in the sample to be tested.

[0015] Preferably, the criteria for sudden coronary death are: ascorbic acid expression level>35.50 μg / mL; docosahexaenoic acid expression level>155.74 pg / mL; carnitine expression level>343.35 ng / mL; glutamine expression level<172.17 μmol / L; norleucine expression level

[0016] <44.12μmol / L.

[0017] Specifically, the forensic diagnostic product for sudden coronary death is used to distinguish sudden coronary death from death due to other causes.

[0018] Preferably, the sudden coronary death includes, but is not limited to: sudden death due to coronary atherosclerotic heart disease and sudden death due to acute myocardial ischemia.

[0019] Preferably, the death caused by other reasons includes but is not limited to: death from severe craniocerebral injury, death from hemorrhagic shock, death from freezing, and death from burning.

[0020] Preferably, the sample to be tested is blood.

[0021] More preferably, the sample to be tested is serum.

[0022] Preferably, the forensic diagnostic product for sudden coronary death comprises a kit.

[0023] In a third aspect, the present invention provides a product for forensic diagnosis of sudden coronary death, wherein the product comprises a kit.

[0024] Specifically, the product may also include other markers, including but not limited to: one or more of ascorbic acid, creatine, and spermidine.

[0025] The beneficial effects of the present invention are:

[0026] The biomarker combination of the present invention has significant changes in the serum samples of individuals with sudden coronary death, and shows good diagnostic performance after ROC verification, suggesting that it has the potential to be applied in the forensic identification of sudden coronary death. The potential application value of the non-targeted metabolomics strategy of the present invention in the identification of difficult and complex causes of death provides a new idea for the molecular diagnosis of the cause of death investigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Experimental protocols prepared for each group of animal models.

[0028] Figure 2 Figure 2 shows the histopathological changes of coronary arteries and myocardium in rats of each group (H&E×200). In the figure, A, B, D, and E represent the normal coronary arteries and myocardium in the NC and Sham groups; C represents the AMI group, which shows no obvious abnormalities in the coronary arteries; F represents the myocardial contraction band necrosis in the AMI group; G and H represent the thickening of the coronary artery intima, endothelial disorder, and inflammatory cell infiltration around the blood vessels in the AS and SCAD groups; I represents the small focal inflammatory cell infiltration in the myocardial interstitium in the AS group; and J represents the myocardial contraction band necrosis and sarcoplasmic coagulation in the SCAD group.

[0029] Figure 3 Masson staining of coronary arteries of rats in each group (400×, blue indicates collagen fibers); A represents the Sham group; B represents the AMI group; C represents the AS group; and D represents the SCAD group.

[0030] Figure 4The electrocardiogram results of rats in each group; A represents the NC group; B represents the AS group; C represents the Sham group; D represents the AMI group; and E represents the SCAD group.

[0031] Figure 5 The total ion currents of serum samples from rats in each group are overlapped. A represents the positive ion mode, and B represents the negative ion mode.

[0032] Figure 6 This is the PCA score diagram for the overall distribution of serum samples of rats in each group.

[0033] Figure 7 This is the PLS-DA score diagram for the overall distribution of serum samples of rats in each group.

[0034] Figure 8 Figure 2 is the OPLS-DA score diagram between different groups; A represents NC group-AS group; B represents Sham group-AMI group; C represents Sham group-SCAD group.

[0035] Fig. 9 This is a validation diagram of the OPLS-DA model between different groups; A represents the NC group-AS group; B represents the Sham group-AMI group; and C represents the Sham group-SCAD group.

[0036] Fig.10 These are S-plots between different groups; A represents NC group-AS group; B represents Sham group-AMI group; and C represents Sham group-SCAD group.

[0037] Fig.11 This is a diagram for analyzing the MetPA pathway of differential metabolites among different groups; A in the figure represents NC group-AS group; B represents Sham group-AMI group; C represents Sham group-SCAD group.

[0038] Fig.12 ROC curves of each group of metabolic biomarkers for diagnosing sudden coronary death and other causes of death; in the figure, A represents the group of sudden death due to coronary atherosclerosis; B represents the group of sudden death due to acute myocardial ischemia; and C represents the group of people with coronary atherosclerosis but died of other causes of death. DETAILED DESCRIPTION

[0039] In order to make the technical means, creative features, purpose and efficacy of the present invention easy to understand, the present invention is further explained in conjunction with specific embodiments below, but the following embodiments are only preferred embodiments of the present invention, not all. Based on the embodiments in the implementation mode, other embodiments obtained by those skilled in the art without creative work all belong to the protection scope of the present invention. In the following embodiments, unless otherwise specified, the operating methods used are conventional operating methods, the equipment used are conventional equipment, and the equipment materials used in each embodiment are the same.

[0040] Example 1 Animal grouping and model establishment

[0041] 1.1 Animal grouping

[0042] Thirty SPF SD male rats, 6-8 weeks old, were housed in ventilated, clean animal cages. After one week of adaptive feeding, the rats were randomly divided into normal control group (NC), coronary atherosclerosis group (AS), sham surgery group (Sham), acute myocardial ischemia group (AMI), and sudden coronary artery death (SCAD), with 6 rats in each group. Among them, the AS group and the SCAD group maintained a high-fat diet for 12 weeks to induce coronary atherosclerosis, and the NC group, Sham group, and AMI group were fed a normal diet. All rats had free access to food and water during the period. The experimental scheme for the preparation of animal models in each group can be found in Figure 1 , in the figure, CAL stands for left anterior descending coronary artery ligation.

[0043] 1.2 Animal model establishment

[0044] a. Coronary atherosclerosis group (AS): Coronary atherosclerosis animal model was established by intraperitoneal injection of vitamin D3 combined with high-fat emulsion gavage. Vitamin D3 (600,000 IU / kg) was injected intraperitoneally before the experiment, and then vitamin D3 100,000 IU / kg was injected intraperitoneally again at weeks 3, 6, and 9. After the initial vitamin D3 injection, high-fat emulsion gavage was performed for 12 consecutive weeks, 1 mL / 100 g, twice a day. After the modeling period, blood was collected from the orbital vein of the rats, and serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) were detected using an automatic biochemical analyzer, and the atherosclerosis index (AI) was calculated according to the formula, AI = (TC-HDL) / HDL. AI greater than 3.8 indicates the occurrence of coronary atherosclerosis. The blood lipid indexes of rats in other groups were tested by the same method after 12 weeks.

[0045] Preparation of high-fat emulsion: ① Heat 25g lard to 100℃, add 5g cholesterol, 5g white sugar, 5g egg yolk powder, 1g propylthiouracil and 25mL Tween-80, stir well to make oil phase; ② Add 2g sodium deoxycholate to 30mL distilled water, stir and dissolve to make water phase; ③ Stir and mix the water phase and oil phase to make high-fat emulsion. Refrigerate in a sealed container at 4℃, and melt in a 37℃ water bath when using.

[0046] b. Sudden death due to coronary atherosclerosis (SCAD) group: The coronary atherosclerosis rat model was prepared in the same way as in a. Methods, and then sudden coronary death was induced by ligation of the left anterior descending coronary artery. The surgical procedure was as follows: After inhalation anesthesia with isoflurane (concentration 2%-3%), the rats were fixed on the operating table and ventilated through oral endotracheal intubation. The ventilation frequency was 70 times / min, the tidal volume was 0.8-1mL, and the inspiratory / expiratory ratio was 2:1. The preoperative electrocardiogram of the rats was recorded using the BL-420S biofunction instrument lead. Thoracotomy was performed, the pericardium was stripped to expose the heart, and the left anterior descending coronary artery was ligated 3-5mm below the root of the left atrial appendage with a small amount of myocardial tissue using a 6-0 suture. The occurrence of acute myocardial ischemia was confirmed by the ST segment elevation of the rat electrocardiogram. Four rats died 15-20 minutes after surgery, and two rats had weak vital signs 30 minutes after surgery and were killed by cervical dislocation.

[0047] c. Acute myocardial ischemia sudden death group (AMI): Healthy rats were directly subjected to left anterior descending coronary artery ligation surgery using method b. to establish an acute myocardial ischemia rat model. All six rats died within 30 minutes after the operation.

[0048] d. Sham group: healthy rats were anesthetized, intubated, and performed thoracotomy in the same manner as in b. A 6-0 suture was passed through the myocardial tissue below the root of the left atrial appendage, but the coronary artery was not ligated. The rats were killed by cervical dislocation 30 minutes after the operation.

[0049] e. Blank control group (NC): healthy rats were not treated in any way and were killed by cervical dislocation after the modeling of the rats in the above groups was completed.

[0050] 1.3 Sample collection and preparation

[0051] After the rat models in each group were successfully established and killed, blood was collected from the heart using a common vacuum blood collection tube and placed on ice for 20 minutes. The collected blood was then centrifuged at 4°C and 3000rpm for 10 minutes, and the supernatant was transferred to a sterile EP tube and divided into small portions and stored in a -80°C refrigerator for later use.

[0052] The myocardial tissues of rats in each group were extracted and fixed in 4% paraformaldehyde solution at room temperature for subsequent hematoxylin-eosin staining to observe the morphology of myocardial cells and the degree of coronary artery atherosclerosis.

[0053] 1.4 Metabolomics methods based on UPLC-MS

[0054] 1) Sample pretreatment

[0055] Take the serum sample out of the -80℃ freezer 4h in advance and thaw at 4℃. Take 100μL of serum sample in a 2mL EP tube, add 200μL of 0.1% formic acid / acetonitrile to precipitate protein, vortex for 3min, centrifuge at 4℃, 13 000rpm for 15min, transfer the upper organic phase to a new EP tube, and dry it in a vacuum freeze dryer. Redissolve with 200μL of methanol before instrumental analysis, centrifuge at 4℃, 13000rpm for 15min, take the supernatant and transfer it to a sample bottle for sampling and analysis.

[0056] The quality control sample (QC) is a mixed sample of all the serum samples to be tested. 10 μL of each serum sample was taken and placed in a 2 mL EP tube and vortexed to mix. The pretreatment method was the same as above. During the experiment, 1 QC sample was inserted into every 6 experimental samples to ensure instrument stability and data reliability.

[0057] 2) Chromatographic conditions

[0058] The chromatographic column, column temperature, injection temperature, flow rate, and injection volume conditions for UPLC metabolomics are shown in Table 1 .

[0059] Table 1 UPLC conditions for metabolomics

[0060]

[0061] Before the first injection analysis, the initial mobile phase was used for equilibration for 5 minutes, and then 6 injections of QC samples were injected to ensure the stability of the liquid phase system and chromatographic column. The specific elution program is shown in Table 2.

[0062] Table 2 UPLC elution gradient for metabolomics

[0063] Gradient time (min) Mobile phase A (%) Mobile phase B (%) Flow rate (ml / min) 3.0 99 1 0.25 13.0 80 20 0.25 15.0 75 25 0.25 18.0 70 30 0.25 20.0 60 40 0.25 23.0 40 60 0.25 25.0 1 99 0.25

[0064] 3) Mass spectrometry conditions

[0065] ESI electrospray ionization was used: the acquisition mode was switched between positive and negative ions. Scan mode: Full Scan / dd-MS2, the acquisition range was m / z 80-1200Da. The spray voltage was set to 3.5 kV for the positive electrode and 2.5 kV for the negative electrode. The capillary temperature was 320°C and the heater temperature was 300°C. The sheath gas was 35 Arb and the auxiliary gas was 10 Arb. The normalized collision energy (NCE) was set to 12.5 eV, 25 eV and 37.5 eV.

[0066] 1.5 Data processing and statistical analysis

[0067] 1) Data preprocessing

[0068] The collected UPLC-MS raw data files were imported into Compound Discoverer3.1 software to obtain matching and aligned peak data. Based on the relative molecular mass and mass spectrometry fragment ion data of the compound, a target list including peak data of retention time, molecular formula, accurate molecular weight, mass-to-charge ratio and peak area information was created and imported into Excel. After the data was normalized for peak area, it was organized into a two-dimensional data matrix for subsequent analysis. Metabolites were identified by searching the HMDB database, and comparison analysis was performed based on molecular weight and secondary fragment information. Compounds with good secondary fragment matching were used as identified metabolites.

[0069] Subsequently, the experimental groups were divided into QC sample group-experimental sample group, NC group-AS group, Sham group-AMI group, and Sham group-SCAD group.

[0070] 2) Statistical analysis

[0071] The data matrix after peak area normalization was imported into SIMCA-P 14.1 software for multivariate statistical analysis. First, principal component analysis (PCA) was used to analyze the QC samples to ensure good instrument stability and high data quality credibility during the detection process. In view of the "high-dimensional and massive" characteristics of metabolomics data, in order to screen out key differential metabolites with biological significance, multivariate statistical methods are usually required to analyze metabolomics data, including partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), etc.

[0072] PLS-DA is a supervised discriminant statistical method that can further ignore inter-group errors, eliminate irrelevant random errors, and highlight the differences between different groups within the model. In order to prevent the model from overfitting, a permutation test is usually required to evaluate the model quality, with the number of verifications set to 200 times. As an orthogonal correction to PLS-DA, OPLS-DA has a stronger ability to identify metabolic differences between sample groups. The variable importance for the projection (VIP) is used to identify metabolites with stronger predictive and discriminative abilities for the classification of each group of samples, thereby further screening metabolic biomarkers. In the S-plot curve analysis of OPLS-DA, the farther the point in the curve is from the origin, the greater its contribution to the discrimination of sample groups. SPSS21.0 software was then used to perform an independent sample t-test on the metabolites between different groups, and VIP>1 and P<0.05 were finally used as the screening criteria for differential metabolites.

[0073] 3) Metabolic pathway analysis and diagnostic marker performance evaluation

[0074] In order to further clarify the metabolic mechanism of sudden coronary death, the statistically significant differential metabolites between different groups were imported into the MetaboAnalyst 5.0 online database for metabolic pathway analysis, and the significantly enriched action pathways were screened according to P-values ​​and Impactvalues. The KEGG online database and related literature reports were used to analyze the related metabolic pathways involved in the differential metabolites.

[0075] In order to further screen stable and specific diagnostic markers, the Biomarker Analysis in the MetaboAnalyst 5.0 online database was used to perform ROC curve analysis on the screened differential metabolites to evaluate their diagnostic performance for the cause of death. Metabolites with AUC values ​​≥ 0.8, P < 0.05, and |Fold Change| ≥ 2.5 were selected as diagnostic biomarkers for sudden coronary death, and the ELISA method was used to verify the diagnostic efficacy of the corresponding biomarkers in human blood samples. SPSS26.0 statistical software was used for comparative analysis of the experimental data, and the quantitative data were analyzed using The comparison between the groups was analyzed by ANOVA, and the comparison between the two groups was analyzed by LSD test, with the test level α = 0.05.

[0076] 1.6 Results Analysis

[0077] 1) Changes in the concentrations of four blood lipids in rats of each group

[0078] During the preparation of the coronary atherosclerosis model, rats were divided into two groups according to their diet: normal diet group and high-fat diet group. Therefore, the concentrations of TC, TG, HDL, and LDL in the serum of each group of rats were detected before ligation surgery, and the atherosclerosis index (AI) was calculated. Compared with the normal diet group, the concentrations of TC and LDL in the high-fat diet group were significantly increased (Table 3). According to literature reports, an AI greater than 3.8 can indicate the formation of coronary atherosclerosis. The results showed that the AI ​​of the normal diet group was within the normal range, while the AI ​​of the high-fat diet group was significantly increased (P<0.05) and greater than 3.8, indicating that coronary atherosclerosis occurred in rats in the AS and SCAD groups.

[0079] Table 3 Changes of blood lipid concentration in rats

[0080]

[0081] Note: In the table, the normal diet group includes the NC group, the Sham group, and the AMI group, and the high-fat diet group includes the AS group and the SCAD group. *Compared with the normal diet group: P<0.05.

[0082] 2) Histological changes of coronary arteries in rats of each group

[0083] H&E staining results showed that there were no obvious abnormalities in the coronary arteries and myocardium in the NC and Sham groups; no obvious abnormalities in the coronary arteries in the AMI group; disordered arrangement of endothelial cells, thickening of the intima, and stenosis of the lumen in the coronary arteries in the AS and SCAD groups; small focal inflammatory cell infiltration in the myocardial interstitium in the AS group; structural destruction of myocardial cells, contraction band necrosis, and blurred striations were observed in the AMI and SCAD groups. The above changes indicate that rats in the AS and SCAD groups have coronary atherosclerosis, and rats in the AMI and SCAD groups have acute myocardial ischemia ( Figure 2 ).

[0084] Masson staining results showed that there was no obvious abnormality in the coronary arteries of the Sham group and the AMI group; proliferating collagen fibers were observed in the coronary artery intima and around the wall of the AS group; and proliferating collagen fibers were observed in the coronary artery intima and around the wall of the SCAD group. The above changes indicate that rats in the AS and SCAD groups have coronary atherosclerosis ( Figure 3 ).

[0085] 3) ECG changes of rats in each group

[0086] The electrocardiogram rhythm of the NC group, Sham group and AS group was stable and normal; about 5 minutes after the ligation of the left anterior descending coronary artery, the electrocardiogram of the AMI group and the SCAD group showed ST segment elevation, and they died after about 30 minutes of ischemia. Figure 4 ). This indicated that acute myocardial ischemia occurred in the AMI group and the SCAD group, indicating that the sudden coronary death model was successfully established.

[0087] Example 2 Metabonomic Analysis of Serum Samples from Each Group of Rats

[0088] 2.1 UPLC-MS metabolic profiles of total serum samples

[0089] The total ion current (TIC) shows the relative abundance of all ions detected in the mass spectrometer over time. The chromatograms of serum metabolite analysis of rats in the NC group, AS group, AMI group, SCAD group and Sham group in positive and negative ion modes are shown in Figure 2. Figure 5 As shown, the horizontal axis represents the retention time, and the vertical axis represents the peak intensity of the ion. It can be seen from TIC that there are differences in peak intensity between groups at the same retention time in positive and negative ion modes, indicating that there may be different metabolites between the samples in each group.

[0090] 2.2 Data quality control

[0091] After data filtering and normalization, principal component analysis (PCA) was used to separate samples and visualize the overall differences in the dataset ( Figure 6). All QC samples were closely clustered together and did not show obvious discrete trends in PCA, which indicated that the injection steps, metabolite extraction, data collection, and data analysis processes were stable and reliable, supporting further analysis. In addition, the distribution of the five groups of serum samples was observed to be slightly different based on the score plots of different PC combinations, indicating that there may be differences in the metabolic characteristics between the groups. However, the separation trend was not obvious enough, and further modeling was needed to achieve differential analysis between different groups.

[0092] 2.3 Multivariate statistical analysis

[0093] The serum samples of rats in each group were analyzed using supervised partial least squares discriminant analysis (PLS-DA). The PLS-DA score graph showed that the separation trend of each group of samples was good, indicating that their endogenous metabolites had changed significantly ( Figure 7 ). The present invention mainly focuses on the specific differences in endogenous metabolites between the NC group and the AS group, the Sham group and the AMI group, and the Sham group and the SCAD group. Therefore, the data of each group are then compared and analyzed in pairs to find the differential metabolites between different groups and analyze their changing trends.

[0094] Orthogonal partial least squares discriminant analysis (OPLS-DA) as a correction to PLS-DA can further reduce the random error within the group and make the difference between the groups more significant. According to the OPLS-DA score chart, it can be seen that the three comparison groups of NC group-AS group, Sham group-AMI group, and Sham group-SCAD group can achieve good separation ( Figure 8 ).

[0095] In order to avoid overfitting of the model, the permutation test was used to evaluate the effectiveness of the OPLS-DA model. 2 and Q 2 The values ​​of all show a downward trend, indicating that the model has a good fit and the experimental results are reliable ( Fig. 9 ). S-plots were further used to preliminarily screen all variables. The S-plots of different groups were as follows: Fig.10 shown.

[0096] 2.4 Screening of serum differential metabolites

[0097] In the OPLS-DA model, variable projection importance (VIP) represents the contribution rate of each variable in the classification of samples between groups. The size of the VIP value represents the influence of metabolites on the classification between groups, and is often used as a screening index for differential metabolites in metabolomics. In the present invention, VIP>1 and independent sample t-test P<0.05 were used as screening thresholds, and the HMDB database was used for metabolite identification.

[0098] Compared with the NC group, a total of 22 endogenous metabolites in the AS group changed significantly, and the relative contents of all 22 metabolites were down-regulated. Compared with the Sham group, a total of 5 endogenous metabolites in the AMI group changed significantly, and the relative contents of all 5 metabolites were down-regulated. Compared with the Sham group, a total of 39 endogenous metabolites in the SCAD group changed significantly, of which the relative contents of 10 metabolites were up-regulated and the relative contents of 29 metabolites were down-regulated. The specific differential metabolite information is shown in Table 4.

[0099] Table 4 Identification of differential metabolites in serum samples between different groups based on UPLC-MS technology

[0100]

[0101]

[0102]

[0103] Note: “↑” and “↓” in the table indicate up- and down-regulation of metabolites in serum samples.

[0104] 2.5 Pathway enrichment analysis of serum differential metabolites

[0105] MetaboAnalyst 5.0 was used to analyze the metabolic pathways of the differential metabolites among different groups. Fig.11 shown.

[0106] The metabolic pathways mainly involved in the differential metabolites associated with AS were: (a) phenylalanine, tyrosine and tryptophan biosynthesis; (b) taurine and hypotaurine metabolism; (c) phenylalanine metabolism; (d) arginine and proline metabolism; and (e) citric acid cycle (TCA cycle).

[0107] The metabolic pathways mainly involved in the differential metabolites associated with AMI were: (a) histidine metabolism; (b) alanine, aspartate and glutamate metabolism.

[0108] The metabolic pathways mainly involved in the differential metabolites associated with SCAD were: (a) phenylalanine, tyrosine and tryptophan biosynthesis; (b) D-glutamine and D-glutamate metabolism; (c) phenylalanine metabolism; (d) alanine, aspartate and glutamate metabolism; (e) niacin and nicotinamide metabolism; (f) arginine and proline metabolism; and (g) arginine biosynthesis.

[0109] Example 3 Screening and verification of potential diagnostic markers

[0110] 3.1 Screening of potential diagnostic biomarkers

[0111] ROC curve analysis was performed on the screened differential metabolites to evaluate whether they have the potential to serve as diagnostic markers for sudden coronary death. The results are shown in Table 5.

[0112] Table 5 ROC curve analysis results of differential metabolites in each group

[0113]

[0114]

[0115]

[0116] Under the conditions of AUC value ≥ 0.8, P < 0.05 and |Fold Change| ≥ 2.5, three metabolites of ascorbic acid (ASA), docosahexaenoic acid (DHA) and carnitine (CNT) were screened as diagnostic biomarkers of sudden coronary death in the SCAD group. Under the conditions of AUC value ≥ 0.8, P < 0.05 and |Fold Change| ≥ 2, ascorbic acid (ASA), creatine (Cr) and spermidine (SMD) were screened as diagnostic biomarkers of stable coronary atherosclerosis in the AS group. There were no differential metabolites in the AMI group that met the above conditions, so two metabolites, glutamine (Gln) and norleucine (Nle), with AUC values ​​≥ 0.8, P < 0.05, and FoldChange > 0.7, were selected as biomarkers of acute myocardial ischemia.

[0117] 3.2 Validation of potential diagnostic biomarkers

[0118] A total of 48 human autopsy case samples were collected from four independent centers, including the Shanxi Medical University Forensic Identification Center, the Inner Mongolia Medical University Forensic Identification Center, the Southern Medical University Forensic Identification Center, and the Shanxi Dian Farun Forensic Identification Institute. The cause of death of each case was determined by more than two forensic pathology experts. The samples were divided into the following four groups:

[0119] ① Sudden death due to coronary atherosclerosis (n=12): patients with coronary atherosclerosis, 1 or more coronary arteries with stenosis of grade III or above, and old / new myocardial infarction or myocardial fibrosis;

[0120] ② Acute myocardial ischemia sudden death group (n=12): no or mild (coronary artery stenosis grade I-II) atherosclerotic changes in the coronary artery, no obvious pathological changes in the myocardium, sudden death with or without inducements, excluding other heart diseases and deaths caused by poisoning, mechanical injury, mechanical asphyxiation, etc.;

[0121] ③ Patients with coronary atherosclerosis but died of other causes (n=12): Patients with coronary atherosclerosis but with mild stenosis (grade I-II) not enough to cause death, no obvious pathological changes in the myocardium, and died of craniocerebral injury or hemorrhagic shock, strictly excluding those who had other heart diseases or fatal diseases before death;

[0122] ④ Control group (n=12): including those who died of craniocerebral injury, hemorrhagic shock, freezing and burning, strictly excluding those who suffered from coronary heart disease, heart disease or other fatal diseases before death. Detailed information of samples in each group is shown in Table 6.

[0123] Table 6 Statistics of human autopsy case samples

[0124] Grouping Control group SCAD Group AMI group AS Group Male (Female) 9(3) 9(3) 10(2) 10(2) Age (years) 31.85±20.3 52.9±14.02 50.17±16.32 59.5±6.36 PMI(h) 281.56±255.8 292.56±320.83 302.5±215.29 694.5±41.72 Body length (cm) 151.56±33.48 166.2±6.88 168.08±9.93 166±5.66 Heart weight (g) 246.08±109.88 425.59±67.82** 393±109.14* 355.15±13.93

[0125] Note: * indicates P<0.05 compared with the control group, ** indicates P<0.01 compared with the control group.

[0126] The expression of the above biomarkers in the human serum samples of each group was detected by ELISA method, and the diagnostic efficacy was evaluated by ROC curve. The diagnostic efficacy of each marker was good and could clearly distinguish the control group from the sudden death of coronary atherosclerotic heart disease, sudden death of acute myocardial ischemia and the death of coronary atherosclerosis but other causes ( Fig.12 ). It has been verified that the criteria for the determination of sudden coronary death by each biomarker are: ascorbic acid expression level>35.50μg / mL, docosahexaenoic acid expression level>155.74pg / mL, carnitine expression level>343.35ng / mL, glutamine expression level>343.35ng / mL.

[0127] <172.17 μmol / L or the expression level of norleucine <44.12 μmol / L.

[0128] The above detailed description is a specific description of one of the feasible embodiments of the present invention, and the embodiment is not intended to limit the scope of the present invention. It should be pointed out that any equivalent implementation or change that does not deviate from the present invention should be included in the scope of the technical solution of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached requirements.

Claims

1. A biomarker combination specific for sudden coronary death, characterized in that: The biomarker combination consists of ascorbic acid, docosahexaenoic acid, carnitine, glutamine and norleucine.

2. Use of the biomarker combination according to claim 1 in the preparation of a forensic diagnostic product for sudden coronary death.

3. The use according to claim 2, characterized in that: The application determines whether it is sudden coronary death by detecting the expression level of biomarkers in the sample to be tested.

4. The use according to claim 3, characterized in that: The criteria for determining sudden coronary death are: ascorbic acid expression level>35.50 μg / mL, docosahexaenoic acid expression level>155.74 pg / mL, carnitine expression level>343.35 ng / mL, glutamine expression level<172.17 μmol / L or norleucine expression level<44.12 μmol / L.

5. The use according to claim 4, characterized in that: The forensic diagnostic product for sudden coronary death is used to distinguish sudden coronary death from death caused by other reasons.

6. The use according to claim 5, characterized in that: The sudden coronary death mentioned includes: sudden death due to coronary atherosclerotic heart disease and sudden death due to acute myocardial ischemia; death caused by other reasons includes: death from severe craniocerebral injury, death from hemorrhagic shock, death from freezing, and death from burning.

7. The use according to claim 3, characterized in that: The sample to be tested includes: blood.

8. The use according to claim 2, characterized in that: The forensic diagnostic product for sudden coronary death includes a kit.

9. A product for forensic diagnosis of sudden coronary death, characterized in that: The product includes a kit, and the product includes the biomarker combination according to claim 1.

10. The product according to claim 9, characterized in that The product may also include other markers, including one or more of ascorbic acid, creatine, and spermidine.

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