Coronary artery sudden death specific biomarker combination, and applications and products thereof

Abstract

The application provides a biomarker combination specific to coronary sudden death and application and products thereof, and belongs to the technical field of forensic science.The biomarker combination comprises ascorbic acid, docosahexaenoic acid, carnitine, glutamine and norleucine.The biomarker combination is significantly changed in serum samples of individuals with coronary sudden death, and after ROC verification, shows good diagnostic performance, indicating that it has the potential to be applied to forensic identification of coronary sudden death.The potential application value of the non-targeted metabolomics strategy of the application in difficult and complex death cause identification provides a new idea for molecular diagnosis of death cause investigation.

Description

Technical Field

[0001] This invention belongs to the field of forensic medicine technology, specifically relating to the application of biomarkers in the preparation of forensic diagnostic products for coronary sudden death. Background Technology

[0002] Sudden cardiac death refers to natural death caused by cardiac reasons, preceded by sudden loss of consciousness, and usually occurs within one hour of symptom onset. 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 death cases are caused by stenosis or blockage of one or more coronary arteries due to atherosclerosis. Some cases are complicated by thrombosis, while a few cases are caused by severe coronary artery vasoconstriction due to coronary artery spasm, leading to luminal occlusion. In these cases, 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. Currently, there are four main theories regarding the pathogenesis of atherosclerosis: the lipid infiltration theory, the endothelial injury-response theory, the platelet aggregation and thrombosis theory, and the smooth muscle cell clonal theory. The formation of coronary atherosclerosis specifically includes a series of vascular pathophysiological changes such as damage to the vascular intima, lipid deposition, atherosclerotic plaque formation, fibrosis, and hardening of the vessel wall. Among these, the stability of coronary atherosclerotic plaques is a major determinant of sudden cardiac death. Coronary artery spasm (CAS) refers to transient constriction of the coronary arteries, causing incomplete or complete occlusion of the vessel, leading to myocardial ischemia and even sudden death. CAS often coexists with coronary atherosclerosis, but in rare 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 is not yet fully understood, but it is currently believed that autonomic nervous system dysfunction, vascular endothelial dysfunction, and vascular smooth muscle cell hyperresponsiveness may be closely related to the occurrence of coronary artery spasm.

[0004] Although the pathogenesis of coronary atherosclerosis and coronary artery spasm differs, both conditions lead to narrowing or blockage of the coronary arteries, resulting in acute myocardial infarction (AMI). This causes local electrophysiological disturbances, triggering severe arrhythmias and ultimately cardiac arrest, leading to death. Acute myocardial infarction is the most common underlying pathological basis for sudden coronary death.

[0005] In forensic practice, cases of sudden coronary artery death are common. Most of these cases involve coronary artery atherosclerosis reaching grade III or IV, with old or new myocardial infarction foci and myocardial fibrosis. Combining clinical history and case investigation, clarifying the cause of death is relatively straightforward. However, some cases only show grade II or III stenosis, or even no obvious coronary artery stenosis, suggesting coronary artery spasm on top of this lesion. Due to the rapid death process and short myocardial ischemia time, histological examination can only observe wavy changes or blurred striations in myocardial fibers, lacking specific diagnostic value. Furthermore, detection methods such as myocardial enzyme profiles are easily affected by post-mortem blood autolysis, making it difficult to determine the cause of death as cardiac. In addition, most cases of sudden coronary artery death occur suddenly and are easily mistaken for violent deaths, often leading to multiple doubts and further increasing the difficulty of identification. Therefore, accurately understanding the essential characteristics of sudden coronary artery death and screening accurate and reliable diagnostic markers are crucial for the scientific and objective identification of the cause of death.

[0006] Metabolomics, as the omics technology closest to phenotype, focuses on studying the metabolic pathways of endogenous metabolites in organisms as a whole, organs, or tissues, the influence of genetic or environmental factors, and their changes over time. Metabolites, as the final link in the regulation of biochemical activities in biological systems, allow for a more direct and accurate reflection of the body's pathophysiological state through the analysis of metabolic changes in bodily fluids. In recent years, the application potential of metabolomics in forensic identification research has been fully demonstrated. In the identification of causes of death such as sudden cardiac death, mechanical asphyxiation, electric shock, hypothermia, and sudden infant death syndrome, the discovery of relevant metabolic markers and pathways has provided a basis for elucidating the metabolic changes and lethal mechanisms of complex causes of death.

[0007] In summary, to address the challenges of forensic identification of sudden coronary death, this study employed non-targeted metabolomics to detect differentially expressed metabolites in rat serum, explore the metabolic pathways of sudden coronary death, screen for specific diagnostic biomarkers for sudden coronary death, and validate these biomarkers in human cases of sudden coronary death. This approach provides a valuable reference for the forensic identification of sudden coronary death. Summary of the Invention

[0008] To address the aforementioned shortcomings, this invention provides a specific biomarker combination for sudden coronary artery death, along with its applications and products. The biomarker combination of this invention comprises ascorbic acid, docosahexaenoic acid (DHA), carnitine, glutamine, and leucine. This biomarker combination showed significant alterations in serum samples from individuals with sudden coronary artery death and demonstrated good diagnostic performance after ROC validation, suggesting its potential application in forensic identification of sudden coronary artery death. The non-targeted metabolomics strategy of this invention has potential application value in identifying complex causes of death, providing a new approach to molecular diagnosis in death investigations.

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

[0010] In a first aspect, the present invention provides a combination of biomarkers specific to sudden coronary death, the combination of biomarkers comprising ascorbic acid, docosahexaenoic acid, carnitine, glutamine and leucine.

[0011] Secondly, this invention provides the application of biomarker combinations in the preparation of products for forensic diagnosis of sudden coronary death.

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

[0013] More preferably, the combination of biomarkers may further include one or more of ascorbic acid, creatine, and spermidine.

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

[0015] Preferably, 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; and leucine expression level <35.50 μg / mL.

[0016] <44.12 μmol / L.

[0017] Specifically, the aforementioned forensic diagnostic product for sudden coronary death is used to distinguish sudden coronary death from death caused by other reasons.

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

[0019] Preferably, the other causes of death include, but are not limited to: death from severe traumatic brain 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 includes a reagent kit.

[0023] Thirdly, the present invention provides a product for forensic diagnosis of sudden coronary artery death, the product comprising a reagent 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 this invention are as follows:

[0026] The biomarker combination of this invention showed significant alterations in serum samples from individuals with sudden coronary artery death, and demonstrated good diagnostic performance after ROC validation, suggesting its potential application in forensic identification of sudden coronary artery death. The non-targeted metabolomics strategy of this invention has potential application value in identifying complex causes of death, providing a new approach to molecular diagnosis for investigating causes of death. Attached Figure Description

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

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

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

[0030] Figure 4The following are the electrocardiogram results of rats in each group; in the figure, 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 image shows the superimposed total ion chromatograms of serum samples from each group of rats; A represents the positive ion mode and B represents the negative ion mode.

[0032] Figure 6 The overall distribution of PCA scores for rat serum samples in each group is shown in the graph.

[0033] Figure 7 PLS-DA score distribution of rat serum samples in each group.

[0034] Figure 8 The OPLS-DA score plots are shown between different groups; in the plot, A represents the NC group-AS group; B represents the Sham group-AMI group; and C represents the Sham group-SCAD group.

[0035] Figure 9 The figure shows the validation diagram of the OPLS-DA model between different groups; in the figure, A represents the NC group-AS group; B represents the Sham group-AMI group; and C represents the Sham group-SCAD group.

[0036] Figure 10 S-plots showing the differences between different groups; in the figure, A represents the NC group-AS group; B represents the Sham group-AMI group; and C represents the Sham group-SCAD group.

[0037] Figure 11 The diagram shows the MetPA pathway analysis of differentially metabolites among different groups; in the diagram, A represents the NC group-AS group; B represents the Sham group-AMI group; and C represents the Sham group-SCAD group.

[0038] Figure 12 ROC curves for diagnosing coronary sudden death and other causes of death using metabolic biomarkers in each group; in the figure, A represents the coronary atherosclerotic heart disease sudden death group; B represents the acute myocardial ischemia sudden death group; and C represents the group with coronary atherosclerosis but died from other causes of death. Detailed Implementation

[0039] To make the technical means, creative features, and achieved objectives and effects of this invention easier to understand, the invention is further illustrated below with specific embodiments. However, the following embodiments are merely preferred embodiments of this invention and not all embodiments. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention. Unless otherwise specified, the operating methods and equipment used in the following embodiments are conventional operating methods, and the materials and equipment used in each embodiment are the same.

[0040] Example 1: Animal Grouping and Model Establishment

[0041] 1.1 Animal grouping

[0042] Thirty male SPF-grade SD rats, 6-8 weeks old, were housed in well-ventilated, clean cages. After one week of acclimatization, the rats were randomly divided into four groups: normal control (NC), coronary atherosclerosis (AS), sham surgery (Sham), acute myocardial ischemia (AMI), and sudden coronary artery death (SCAD), with six rats in each group. The AS and SCAD groups were fed a high-fat diet for 12 weeks to induce coronary atherosclerosis, while the NC, Sham, and AMI groups were fed a normal diet. All rats had free access to food and water during this period. The experimental protocols for establishing animal models in each group are detailed below. Figure 1 In the diagram, CAL represents ligation of the left anterior descending coronary artery.

[0043] 1.2 Establishment of animal models

[0044] a. Coronary Atherosclerosis Group (AS): An animal model of coronary atherosclerosis was established by intraperitoneal injection of vitamin D3 combined with gavage administration of a high-fat emulsion. Before the experiment, rats were injected intraperitoneally with vitamin D3 (600,000 IU / kg), followed by intraperitoneal injections of vitamin D3 at weeks 3, 6, and 9. After the initial vitamin D3 injection, rats were administered a high-fat emulsion via gavage for 12 consecutive weeks, 1 mL / 100g, twice daily. After the modeling period, blood was collected from the orbital vein of rats, and serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) were measured using an automated biochemical analyzer. The atherosclerosis index (AI) was calculated using the formula: AI = (TC - HDL) / HDL. An AI greater than 3.8 indicated the presence of coronary atherosclerosis. The blood lipid levels of rats in the remaining groups were measured using the same method after 12 weeks.

[0045] Preparation of high-fat emulsion: ① Heat 25g of lard to 100℃, add 5g cholesterol, 5g white sugar, 5g egg yolk powder, 1g propylthiouracil, and 25mL Tween-80, stir well to form the oil phase; ② Add 2g sodium deoxycholate to 30mL of distilled water, stir to dissolve, and form the aqueous phase; ③ Mix the aqueous and oil phases well to form the high-fat emulsion. Store in a sealed container at 4℃. Melt in a 37℃ water bath before use.

[0046] b. Sudden Death in Coronary Atherosclerotic Heart Disease Group (SCAD): The rat model of coronary atherosclerosis was established using the same method as in a., followed by inducing sudden coronary death through ligation of the left anterior descending coronary artery. The surgical procedure was as follows: After anesthesia with isoflurane (2%-3%), the rats were fixed on the operating table and ventilated via endotracheal intubation. The ventilation rate was 70 breaths / min, the tidal volume was 0.8-1 mL, and the inspiratory / expiratory ratio was 2:1. Preoperative electrocardiograms were recorded using a BL-420S bio-function analyzer. Open-chest surgery was performed, the pericardium was dissected to expose the heart, and the left anterior descending coronary artery was ligated with a 6-0 suture 3-5 mm below the root of the left atrial appendage, along with a small amount of myocardial tissue. Acute myocardial ischemia was confirmed by ST segment elevation on the rat electrocardiogram. Four rats died 15-20 minutes postoperatively, and two rats with weak vital signs were euthanized by cervical dislocation 30 minutes postoperatively.

[0047] c. Acute myocardial ischemia sudden death group (AMI): Healthy rats underwent ligation surgery of the left anterior descending coronary artery using method b to establish an acute myocardial ischemia rat model. All 6 rats died within 30 minutes after the operation.

[0048] d. Sham operation group: Healthy rats underwent anesthesia, endotracheal intubation, and thoracotomy as in method b. 6-0 sutures were used to pass through the myocardial tissue below the root of the left atrial appendage, but the coronary artery was not ligated. The rats were euthanized by cervical dislocation 30 minutes after the operation.

[0049] e. Blank control group (NC): Healthy rats were euthanized by cervical dislocation after the establishment of the rat model in each of the above groups without any treatment.

[0050] 1.3 Sample Collection and Preparation

[0051] After the rat models were successfully established and the rats were euthanized, blood was collected from the heart using ordinary vacuum blood collection tubes and left to stand on ice for 20 minutes. The collected blood was then centrifuged at 3000 rpm for 10 minutes at 4°C, and the supernatant was transferred to sterile EP tubes, aliquoted, and stored at -80°C for later use.

[0052] Myocardial tissue was extracted from each group of rats and fixed in 4% paraformaldehyde solution at room temperature for subsequent hematoxylin-eosin staining to observe myocardial cell morphology and the degree of coronary artery atherosclerosis.

[0053] 1.4 Metabolomics Methods Based on UPLC-MS

[0054] 1) Sample pretreatment

[0055] Serum samples were removed from the -80℃ freezer 4 hours in advance and thawed at 4℃. 100 μL of serum sample was transferred to a 2 mL EP tube, and 200 μL of 0.1% formic acid / acetonitrile was added to precipitate the protein. The mixture was vortexed for 3 min, then centrifuged at 13,000 rpm for 15 min at 4℃. The supernatant was transferred to a new EP tube and dried using a vacuum freeze dryer. Before analysis, the sample was reconstituted with 200 μL of methanol, centrifuged at 13,000 rpm for 15 min at 4℃, and the supernatant was transferred to a sample vial for analysis.

[0056] The quality control (QC) sample is a mixture of all serum samples to be tested. Pipette 10 μL of each serum sample into a 2 mL EP tube and vortex to mix. Pretreatment is the same as above. During the experiment, insert one QC sample into every six test samples to ensure instrument stability and data reliability.

[0057] 2) Chromatographic conditions

[0058] Table 1 shows the chromatographic column, column temperature, injection temperature, flow rate, and injection volume conditions for UPLC metabolomics.

[0059] Table 1. UPLC conditions for metabolomics

[0060]

[0061] Before the first injection analysis, equilibrate with the initial mobile phase for 5 minutes, and then inject 6 QC samples to ensure the stability of the liquid chromatography system and column. The specific elution procedure is shown in Table 2.

[0062] Table 2. UPLC elution gradients 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 employed, with a switching acquisition mode between positive and negative ions. Scan mode: Full Scan / dd-MS2, acquisition range: m / z 80-1200 Da. Spray voltage was set to 3.5 kV for the positive electrode and 2.5 kV for the negative electrode. Capillary temperature was 320℃, and heater temperature was 300℃. Sheath gas was 35 Arb, and auxiliary gas was 10 Arb. 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 acquired UPLC-MS raw data files were imported into Compound Discoverer 3.1 software to obtain matched and aligned peak data. Based on the relative molecular mass and mass spectrometry fragment ion data of the compounds, a target list containing peak data including retention time, molecular formula, precise molecular weight, mass-to-charge ratio, and peak area information was created and imported into Excel. After peak area normalization, the data was organized into a two-dimensional data matrix for subsequent analysis. Metabolite identification was performed by searching the HMDB database. Based on molecular weight and secondary fragment information, comparative analysis was conducted, and compounds with good secondary fragment matching were identified as metabolites.

[0069] The experiments were then divided into groups, including 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 peak area-normalized data matrix was imported into SIMCA-P 14.1 software for multivariate statistical analysis. Principal component analysis (PCA) was first used to analyze the QC samples to ensure good instrument stability and high data quality reliability during the detection process. Given the "high-dimensional and massive" nature of metabolomics data, multivariate statistical methods are typically used to analyze the data in order to screen for key biologically significant differentially expressed metabolites, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA).

[0072] PLS-DA is a supervised discriminant statistical method that can further ignore between-group errors, eliminate irrelevant random errors, and highlight the differences between different groups within the model. To prevent overfitting, a permutation test is usually performed to assess model quality, with the number of validations set to 200. OPLS-DA, as an orthogonal correction to PLS-DA, has a stronger ability to distinguish metabolic differences between sample groups. Variable Importance for the Projection (VIP) is used to identify metabolites with stronger predictive and discriminative abilities for classifying each group, thereby further screening for metabolic biomarkers. In the S-plot analysis of OPLS-DA, points farther from the origin contribute more to the discrimination of sample groups. Subsequently, SPSS 21.0 software was used to perform independent samples t-tests on metabolites between different groups, and finally, VIP>1 and P<0.05 were used as the screening criteria for differentially expressed metabolites.

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

[0074] To further elucidate the metabolic mechanisms of sudden coronary death, statistically significant differentially expressed metabolites from different groups were imported into the MetaboAnalyst 5.0 online database for metabolic pathway analysis. Significantly enriched pathways were screened based on P-values ​​and impact values. The relevant metabolic pathways involved in the differentially expressed metabolites were analyzed using the KEGG online database and relevant literature reports.

[0075] To further screen stable and specific diagnostic biomarkers, ROC curve analysis was performed on the selected differentially expressed metabolites using the Biomarker Analysis database in MetaboAnalyst 5.0 to evaluate their diagnostic performance for causes 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. The diagnostic efficacy of these biomarkers in human blood samples was verified using ELISA. SPSS 26.0 statistical software was used for comparative analysis of experimental data. Quantitative data were analyzed using... The results indicate that ANOVA analysis was used for comparisons between groups, and LSD test was used for comparisons between two groups, with a significance level of α = 0.05.

[0076] 1.6 Results Analysis

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

[0078] In the preparation of the coronary atherosclerosis model, rats were divided into two groups based on their diet: a normal diet group and a high-fat diet group. Therefore, before the ligation surgery, the serum concentrations of TC, TG, HDL, and LDL in each group were measured, and the Atherosclerosis Index (AI) was calculated. Compared with the normal diet group, the TC and LDL concentrations 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 ​​in the normal diet group was within the normal range, while the AI ​​in the high-fat diet group was significantly increased (P<0.05) and greater than 3.8, indicating that coronary atherosclerosis occurred in the AS and SCAD groups.

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

[0080]

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

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

[0083] H&E staining results showed no obvious abnormalities in the coronary arteries and myocardium of the NC and Sham groups; no obvious abnormalities were found in the coronary arteries of the AMI group; the coronary artery endothelial cells of the AS and SCAD groups were disordered, the intima was thickened, and the lumen was narrowed; small focal inflammatory cell infiltration was observed in the myocardial interstitium of the AS group; myocardial cell structure was destroyed in the AMI and SCAD groups, and necrosis of the systolic band and blurred striations were observed. These changes indicate that the rats in the AS and SCAD groups developed coronary atherosclerosis, and the rats in the AMI and SCAD groups developed acute myocardial ischemia. Figure 2 ).

[0084] Masson staining results showed no obvious abnormalities in the coronary arteries of the Sham and AMI groups; proliferating collagen fibers were observed in the coronary intima and perivascular wall of the AS group; and proliferating collagen fibers were also observed in the coronary intima and perivascular wall of the SCAD group. These changes indicate that coronary atherosclerosis occurred in the AS and SCAD groups of rats. Figure 3 ).

[0085] 3) Changes in electrocardiograms of rats in each group

[0086] The electrocardiograms of the NC, Sham, and AS groups showed stable and normal rhythms; approximately 5 minutes after ligation of the left anterior descending coronary artery, the electrocardiograms of the AMI and SCAD groups showed ST-segment elevation, and the patients died after approximately 30 minutes of continuous ischemia. Figure 4 The presence of acute myocardial ischemia in both the AMI and SCAD groups indicates that the coronary artery sudden death model was successfully established.

[0087] Example 2: Metabolomics analysis of rat serum samples from each group

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

[0089] The total ion current (TIC) chromatogram shows the relative abundance of all ions detected by the mass spectrometer over time. Chromatograms of serum metabolites from rats in the NC, AS, AMI, SCAD, and Sham groups under both positive and negative ion modes are shown below. Figure 5 As shown, the horizontal axis represents retention time, and the vertical axis represents the peak intensity of ions. The TIC data reveals differences in peak intensity among groups with the same retention time under both positive and negative ion modes, suggesting the possible presence of differentially expressed metabolites among the sample groups.

[0090] 2.2 Data Quality Control

[0091] After data filtering and normalization, principal component analysis (PCA) is used to separate samples and visualize the overall differences in the dataset. Figure 6All QC samples clustered tightly together, showing no significant dispersion trend in PCA. This indicates that the injection procedure, metabolite extraction, data collection, and data analysis processes were stable and reliable, supporting further analysis. Furthermore, the fractional plots based on different PC combinations showed slightly different distributions among the five serum sample groups, suggesting potential differences in metabolic characteristics between groups. However, the separation trend was not clear enough, requiring further modeling to achieve differential analysis between different groups.

[0092] 2.3 Multivariate statistical analysis

[0093] Supervised partial least squares discriminant analysis (PLS-DA) was used to analyze serum samples from each group of rats. The PLS-DA score plots showed a good separation trend among the samples, indicating that there were significant changes in their endogenous metabolites. Figure 7 This invention focuses on the specific differences in endogenous metabolites among the NC-AS group, the Sham-AMI group, and the Sham-SCAD group. Therefore, the data from each group will be compared pairwise to identify the differential metabolites between the different groups and their trends will be analyzed.

[0094] Orthogonal partial least squares discriminant analysis (OPLS-DA), as a modification of PLS-DA, can further reduce intra-group random error and make inter-group differences more significant. According to the OPLS-DA score plots, good separation was achieved in the three comparison groups: NC-AS, Sham-AMI, and Sham-SCAD. Figure 8 ).

[0095] To avoid overfitting, a permutation test is used to evaluate the effectiveness of the OPLS-DA model. As the permutation retention decreases, R0... 2 and Q 2 The values ​​all showed a downward trend, indicating that the model had a good fit and the experimental results were reliable. Figure 9 Further S-plots were used to perform preliminary screening of all variables. The S-plots between different groups are shown below. Figure 10 As shown.

[0096] 2.4 Screening of serum differential metabolites

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

[0098] Compared to the NC group, 22 endogenous metabolites showed significant changes in the AS group, with all 22 metabolites showing a decrease in relative levels. Compared to the Sham group, 5 endogenous metabolites showed significant changes in the AMI group, with all 5 metabolites showing a decrease in relative levels. Compared to the Sham group, 39 endogenous metabolites showed significant changes in the SCAD group, with 10 metabolites showing an increase in relative levels and 29 metabolites showing a decrease in relative levels. Detailed information on the differentially expressed metabolites is shown in Table 4.

[0099] Table 4. Identification table of differentially expressed metabolites in serum samples from different groups based on UPLC-MS technology.

[0100]

[0101]

[0102]

[0103] Note: In the table, "↑" and "↓" indicate upregulation and downregulation of metabolites in serum samples, respectively.

[0104] 2.5 Pathway enrichment analysis of serum differential metabolites

[0105] Metabolytic pathway analysis was performed on differentially expressed metabolites among different groups using MetaboAnalyst 5.0. The results are as follows: Figure 11 As shown.

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

[0107] The main metabolic pathways involved in differentially metabolites associated with AMI are: (a) histidine metabolism; and (b) alanine, aspartic acid, and glutamate metabolism.

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

[0109] Example 3: Screening and Validation of Potential Diagnostic Biomarkers

[0110] 3.1 Screening of potential diagnostic biomarkers

[0111] ROC curve analysis was performed on the selected differential metabolites to evaluate their potential as diagnostic biomarkers for sudden coronary death. The results are shown in Table 5.

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

[0113]

[0114]

[0115]

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

[0117] 3.2 Validation of potential diagnostic biomarkers

[0118] Forty-eight autopsy cases were collected from four independent centers: Shanxi Medical University Forensic Science Center, Inner Mongolia Medical University Forensic Science Center, Southern Medical University Forensic Science Center, and Shanxi Dian Farun Forensic Science Institute. The cause of death in each case was determined by at least two forensic pathology experts. The samples were divided into the following four groups:

[0119] ① Sudden death group of coronary atherosclerotic heart disease (n=12): patients with coronary atherosclerosis, with stenosis of grade III or above in one or more coronary arteries, and old / new myocardial infarction foci or myocardial fibrosis changes can be seen;

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

[0121] ③ Group with coronary atherosclerosis but died from other causes of death (n=12): Those with coronary atherosclerosis but mild stenosis (grade I-II) that was not enough to cause death, with no obvious pathological changes in the myocardium, died from craniocerebral injury or hemorrhagic shock, and strictly excluded from having other heart diseases or fatal diseases before death.

[0122] ④ Control group (n=12): Includes those who died from traumatic brain injury, hemorrhagic shock, freezing, and burning, strictly excluding those who had coronary heart disease, heart disease, or other fatal diseases before death. Specific information for each group is shown in Table 6.

[0123] Table 6. Statistical Information on Human Autopsy Cases

[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 Corpse 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 serum samples from each group was detected by ELISA, and the diagnostic efficacy was evaluated by ROC curve. The diagnostic efficacy of each biomarker was good, and it could clearly distinguish the control group from those who died suddenly from coronary atherosclerotic heart disease, sudden death from acute myocardial ischemia, and those who died from other causes despite having coronary atherosclerosis. Figure 12 The validated criteria for using various biomarkers to diagnose sudden coronary death were as follows: ascorbic acid expression level >35.50 μg / mL, docosahexaenoic acid expression level >155.74 pg / mL, carnitine expression level >343.35 ng / mL, and glutamine expression level >35.50 μg / mL.

[0127] <172.17 μmol / L or leucine expression level <44.12 μmol / L.

[0128] The above detailed description is a specific illustration of one feasible embodiment of the present invention, and this embodiment is not intended to limit the patent scope of the present invention. It should be noted that all equivalent implementations or modifications made without departing from the present invention should be included within the scope of the technical solution of the present invention. Therefore, the protection scope of the present invention should be determined by the appended claims.

Claims

1. A combination of biomarkers specific to sudden coronary death, characterized in that, The biomarker combination consists of ascorbic acid, docosahexaenoic acid, carnitine, glutamine, and leucine.

2. The application of the biomarker combination of claim 1 in the preparation of forensic diagnostic products for sudden coronary artery death.

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

4. The application according to claim 3, characterized in that, The criteria for determining sudden coronary death are as follows: 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 leucine expression level <44.12 μmol / L.

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

6. The application according to claim 5, characterized in that, The coronary sudden death mentioned above includes: sudden death from coronary atherosclerotic heart disease and sudden death from acute myocardial ischemia; other causes of death include: death from severe traumatic brain injury, death from hemorrhagic shock, death from freezing, and death from burning.

7. The application according to claim 3, characterized in that, The samples to be tested include: blood.

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

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

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

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