Use of col6a3 in diagnosing coronary artery ectasia

Abstract

This invention belongs to the field of biomedical technology, specifically disclosing the application of COL6A3 in the diagnosis of coronary artery dilatation. Through plasma proteomics analysis, this invention revealed that COL6A3 expression is significantly increased in the plasma of patients with coronary artery dilatation, making it a specific biomarker for the coronary artery dilatation phenotype. It demonstrates good efficacy in the diagnosis of coronary artery dilatation, and independent clinical sample validation sets further confirm that COL6A3 can serve as a biomarker for coronary artery dilatation, holding significant importance in the clinical diagnosis and auxiliary diagnosis of coronary artery dilatation. This invention provides a new approach to the diagnosis of coronary artery dilatation and has broad clinical application prospects.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to the application of COL6A3 in the diagnosis of coronary artery dilation. Background Technology

[0002] Coronary artery ectasia (CAE) is a rare cardiac anatomical abnormality, most classicly defined as an abnormally dilated coronary artery with a diameter exceeding 1.5 times the normal surrounding diameter. The etiology of CAE is not fully understood, but its pathological manifestations primarily involve the destruction of the medial structure of the coronary artery wall and the degradation of elastic fibers. Coronary artery disease (CAD) is the most common comorbidity of CAE. Based on whether CAE is accompanied by CAD, it can be classified into isolated CAE (iCAE) and mixed CAE (mCAE).

[0003] The diagnosis of coronary artery embolism (CAE) relies on imaging techniques, with coronary angiography being the recognized "gold standard." It can indicate the degree of dilation of the coronary artery lumen, meeting the criteria for CAE, with or without coronary atherosclerotic plaques, stenosis, or thrombosis. However, this method also has limitations: 1) Coronary angiography can only display information within the vessel lumen, making it difficult to provide information on structural abnormalities of the vessel wall; 2) When the dilated vessel is excessively large, inadequate contrast filling may affect the assessment. Intravascular ultrasound has the advantage of accurately measuring the size of dilated lesions, but its high cost is a limiting factor. Optical coherence tomography (OCT) has higher resolution, but its smaller scanning diameter limits its use in CAE diagnosis. Biomarkers are indicators used to measure normal biological processes, pathogenic abnormalities, and responses to exposure or intervention. They play a crucial role in accurate clinical assessment, including disease diagnosis and differentiation, prognosis, and selection of optimal interventions. Therefore, exploring biomarkers that specifically identify the "dilated" phenotype of CAE has become an important direction in the field of CAE diagnosis. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, the purpose of this invention is to provide a novel coronary artery dilation biomarker, COL6A3, for the diagnosis of coronary artery dilation.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of this invention provides the application of a reagent for detecting the expression level of COL6A3 in a sample in the preparation of products for diagnosing or assisting in the diagnosis of coronary artery dilation.

[0006] The term "expression level" as used in this invention generally refers to the amount of a biomarker in a biological sample. "Expression" generally refers to the process by which information (e.g., gene-encoded and / or epigenetic information) is transformed into structures present and functioning within the cell. Therefore, as used herein, "expression" can refer to transcription into a polynucleotide, translation into a polypeptide, polynucleotide, or polypeptide modification (e.g., post-translational modification of a polypeptide). Transcribed polynucleotide fragments, translated polypeptide fragments, polynucleotide fragments, or polypeptide modified fragments (e.g., post-translational modifications of a polypeptide) should also be considered as expressions, whether they originate from transcripts generated through alternative splicing or degraded transcripts, or from post-translational processing of polypeptides (e.g., through proteolysis).

[0007] In this invention, the term "biomarker" refers to a measurable indicator of an individual's biological state. Such biomarkers can be any substance in an individual, including but not limited to genes, proteins, metabolites, and microorganisms, as long as they are related to a specific biological state (e.g., disease) of the individual being examined. In this invention, a biomarker refers to a protein, and more specifically, the biomarker is COL6A3.

[0008] In this invention, diagnosis refers to the discovery, judgment, or recognition of an individual's health status or condition based on one or more symptoms, data, or other information related to the individual. An individual's health status can be diagnosed as healthy / normal (i.e., without disease or ailment), or as unhealthy / abnormal (i.e., with disease or ailment), or as a specific degree of disease severity or progression. The term diagnosis includes the early detection of a disease / symptom associated with a specific disease or ailment; the characteristics or classification of the disease; the discovery of disease progression, cure, or recurrence; and the discovery of an individual's response to the disease after treatment or intervention.

[0009] Furthermore, the reagents for detecting the expression level of COL6A3 in the sample include reagents for detecting the expression level of the COL6A3 gene and / or reagents for detecting the expression level of the COL6A3 protein.

[0010] Furthermore, the reagents include those for detecting the presence, absence, and / or expression level of the COL6A3 gene, fragments, and protein in a sample via PCR reaction, RT-PCR derivatization reaction, 3SR amplification, LCR, SDA, NASBA, TMA, SYBR Green, TaqMan probes, molecular beacons, two-hybrid probes, composite probes, ISH, microarrays, Southern blotting, Northern blotting, multianalyte assays, enzyme-linked immunosorbent assays, radioimmunoassays, immunofluorescence assays, enzyme immunoassays, immunoprecipitation assays, chemiluminescence assays, immunohistochemistry assays, dot blot assays, or narrow-line blot assays.

[0011] In this invention, the term "reagent" includes compounds that induce desired pharmacological and / or physiological effects. The term also covers pharmaceutically acceptable and pharmacologically active components of those compounds specifically mentioned herein, including but not limited to salts, esters, amides, prodrugs, active metabolites, analogs, etc. When using the above term, it should be understood that this includes the active agent itself, as well as pharmaceutically acceptable and pharmacologically active salts, esters, amides, prodrugs, metabolites, analogs, etc. The term "reagent" should not be interpreted narrowly but should be extended to small molecules, protein molecules such as peptides, polypeptides, and proteins, and compositions comprising them, as well as genetic molecules such as RNA, DNA, their analogues and chemical analogs, and cellular agents.

[0012] In this invention, the term "sample" as used refers to a composition obtained from or derived from a subject that contains cells and / or other molecular entities to be characterized and / or identified based on, for example, physical, biochemical, chemical, and / or physiological characteristics. For example, a sample refers to any sample derived from a subject that is expected or known to contain cells and / or molecular entities to be characterized. Samples include, but are not limited to, tissue samples, primary or cultured cells or cell lines, cell cultures, cell supernatants, cell lysates, platelets, serum, plasma, vitreous fluid, lymph, synovial fluid, follicular fluid, semen, pancreatic juice, amniotic fluid, milk, whole blood, blood-derived cells, urine, cerebrospinal fluid, saliva, sputum, tears, sweat, mucus, tissue culture fluid, tissue extracts, homogenized tissue, cell extracts, and combinations thereof.

[0013] Furthermore, the sample includes at least one of cells, tissues, or body fluids.

[0014] Furthermore, the body fluids include at least one of blood, lymph, urine, sweat, bile, interstitial fluid, cerebrospinal fluid, or breast milk.

[0015] Furthermore, the blood is selected from at least one of whole blood, plasma, or serum.

[0016] Furthermore, the sample was plasma.

[0017] In some embodiments, the subject refers to an individual or animal that suffers from or may suffer from the CAE or CAE-related diseases described in this invention, or it may refer to an individual or animal used for a specific purpose, such as scientific research. Specifically, the individual may be an animal, particularly a mammal, such as a human, pig, dog, cat, cow, sheep, horse, mouse, rat, rabbit, guinea pig, monkey, etc. More specifically, the individual described in this invention is a human.

[0018] In this invention, verification using real clinical samples collected by this invention revealed that COL6A3 is specifically elevated in CAE patients, demonstrating good diagnostic efficacy for CAE patients. This diagnostic efficacy is verified using receiver operating characteristic (ROC) curves, and the measurement of the area under the curve (AUC) helps to compare the accuracy of classifiers across the overall data range.

[0019] In some implementations, the ROC curve is a graph of the test's true positive rate (sensitivity) versus the test's false positive rate (100% - specificity). It is useful for depicting the performance of a specific characteristic when distinguishing between two populations. Typically, characteristic data are selected across the entire population in ascending order based on the values ​​of a single characteristic. Then, for each value of that characteristic, the true positive and false positive rates of the data are calculated. The true positive rate is determined by counting the number of cases with values ​​higher than that characteristic and dividing by the total number of cases. The false positive rate is determined by counting the number of controls with values ​​higher than that characteristic and dividing by the total number of controls. While this definition refers to cases where the characteristic is higher in cases compared to controls, it also applies to cases where the characteristic is lower in cases compared to controls (in which case samples with values ​​lower than that characteristic are counted). ROC curves can be generated with respect to individual characteristics and can also be generated with respect to other individual outputs; for example, combinations of two or more characteristics can be mathematically combined (e.g., addition, subtraction, multiplication, etc.) to provide individual sum values ​​that can be plotted on the ROC curve. Furthermore, any combination of multiple features derived from individual output values ​​can be plotted on a ROC curve.

[0020] A second aspect of the present invention provides a product for diagnosing and assisting in the diagnosis of coronary artery dilatation, the product comprising a reagent for detecting the expression level of COL6A3 in a sample.

[0021] Furthermore, the product includes at least one of a reagent kit, a chip, a test strip, or a high-throughput sequencing platform.

[0022] In some embodiments, the kit further includes one or more substances from the group consisting of: containers, positive controls, negative controls, buffers, preservatives, and protein stabilizers. The components of the kit may be packaged in an aqueous medium or in a lyophilized form. Suitable containers in the kit typically include at least one vial, test tube, long-necked flask, PET bottle, syringe, or other container for holding one component, and preferably, can be appropriately aliquoted. When more than one component is present in the kit, the kit will typically also include a second, third, or other additional container in which the additional components are separately placed. However, different combinations of components may be contained in a single vial. The kit of the present invention typically also includes a container for containing the reactants, sealed for commercial sale. Such a container may include injection-molded or blow-molded plastic containers in which the desired vials can be retained. The kit may also include instructions for use, describing how to use the kit for detection and how to use the test results to assess tumor development and select treatment regimens.

[0023] In some embodiments, the chip includes a gene chip and a protein chip; the gene chip includes a solid support and oligonucleotide probes ordered immobilized on the solid support, the oligonucleotide probes specifically corresponding to part or all of the sequence described in COL6A3. The protein chip includes a solid support and specific antibodies or ligands for the protein encoded by COL6A3 immobilized on the solid support. The solid support can be made of various commonly used materials in the chip field, such as plastic products, microparticles, membrane carriers, etc.

[0024] In some implementations, the solid support may be made of various commonly used materials in the field of gene chips, including but not limited to: nylon membranes, glass or silicon slides modified with active groups (e.g., aldehydes, aminos, etc.), unmodified glass slides, plastic sheets, etc.

[0025] The third aspect of this invention provides the application of COL6A3 in constructing a diagnostic model for coronary artery dilation.

[0026] The fourth aspect of the present invention provides a method for constructing a diagnostic model for coronary artery dilatation, the method comprising acquiring COL6A3 expression level data in a sample and inputting the data into a machine learning algorithm to construct a diagnostic model.

[0027] Furthermore, the diagnostic model obtains results using the following criteria: when the COL6A3 expression level is higher than the optimal cutoff value, the subject is classified as having a risk of coronary artery dilation; when the COL6A3 expression level is lower than the optimal cutoff value, the subject is classified as not having a risk of coronary artery dilation. In this invention, the term "optimal cutoff value" refers to a value that is statistically relevant to a specific outcome when compared with the analysis results. In a preferred embodiment, the optimal cutoff value is determined based on statistical conclusions from studies comparing CAE patients and control groups. Studies from the literature and the experience of users of the methods described herein can also be used to generate or adjust the optimal cutoff value. The optimal cutoff value can also be determined by considering the patient's genetic background, clinical characteristics, work environment, and other relevant factors and outcomes.

[0028] In some implementations, the methods for constructing the diagnostic model are known to those skilled in the art and can be implemented and realized in different ways, linking biomarker expression levels to a certain probability or risk. Preferably, the measured concentrations of the biomarker and one or more other biomarkers are mathematically combined, and the combined value is associated with the fundamental question of whether or not one has a disease or is suspected of having a disease. The measured biomarker values ​​can be combined using any suitable existing technical mathematical method, and a predictive model can be constructed using machine learning algorithms.

[0029] Furthermore, the machine learning algorithm includes algorithmic models developed using various development tools.

[0030] Furthermore, the development tools include at least one of TensorFlow, Scikit-Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, or Spell.

[0031] Furthermore, the algorithm model includes at least one of the following: linear regression model, logistic regression model, Lasso regression model, Ridge regression model, linear discriminant analysis model, nearest neighbor model, decision tree model, perceptron model, neural network model, support vector machine model, Naive Bayes model, AdaBoost model, GBDT model, XGBoost model, LightGBM model, CatBoost model, or random forest model.

[0032] The fifth aspect of the present invention provides a system for diagnosing and assisting in the diagnosis of coronary artery dilatation, the system comprising a processor, an input module, and an output module.

[0033] The input module is used to input COL6A3 level data in the subject sample; the processor is used to perform logical operations on the input information using bioinformatics methods, and the processor contains a computer-readable medium storing instructions, which, when executed by the processor, execute the method for constructing the diagnostic model described in the fourth aspect of the present invention on the input COL6A3 level; the output module is used to output the classification result of whether the subject has or is suspected of having coronary artery dilatation.

[0034] In this invention, the term "system" refers to different tools that are effectively connected to each other. These tools may be implemented in a single device or may be physically separate devices that are effectively connected to each other.

[0035] In this invention, the term "module" refers to a combination of software and / or hardware that can perform a predetermined function. Implementations of hardware, software, or a combination of hardware and software are conceivable.

[0036] The sixth aspect of the present invention provides a device / apparatus for diagnosing and assisting in the diagnosis of coronary artery dilatation, the device / apparatus including a memory and a processor; the memory is used to store program instructions, and the processor is used to call the program instructions, and when the program instructions are executed, the system for diagnosing and assisting in the diagnosis of coronary artery dilatation described in the fifth aspect of the present invention is implemented.

[0037] In this invention, the device is a method for distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they can be replaced by other expressions. Those skilled in the art will know that this invention can be implemented as a device, method, or computer program product. Therefore, the disclosure of this invention can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of software and hardware. Furthermore, in some specific embodiments, this invention can also be implemented as a computer program product in one or more computer-readable storage media containing computer-readable program code.

[0038] The term "device" as used in this invention is not limited to one or a specific number of physical objects. As used herein, a device can be any medical or electronic component having multiple parts that can implement at least some portions of this disclosure. Although the term "device" is used in the following description and examples to describe certain aspects of this disclosure, the term "device" is not limited to a particular configuration, type, or number of objects.

[0039] The seventh aspect of the present invention provides a computer-readable storage medium for diagnosing and assisting in the diagnosis of coronary artery dilatation, wherein the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the functions of the system for diagnosing and assisting in the diagnosis of coronary artery dilatation described in the sixth aspect of the present invention.

[0040] In some embodiments, any combination of one or more computer-readable media may be employed. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. In this invention, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. More specific examples of computer-readable storage media in some embodiments include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0041] Advantages and beneficial effects of the present invention: This invention, through plasma proteomics analysis, revealed a significant increase in the expression level of COL6A3 in the plasma of patients with coronary artery dilation. COL6A3 is a specific biomarker for the "dilation" phenotype and exhibits good efficacy in the diagnosis of coronary artery dilation. Further validation using an independent clinical sample set confirmed that COL6A3 can serve as a biomarker for coronary artery dilation, holding significant importance in the clinical diagnosis and auxiliary diagnosis of coronary artery dilation. This invention provides a new approach to the diagnosis of coronary artery dilation and has broad clinical application prospects. Attached Figure Description

[0042] Figure 1 The results validate the efficacy of COL6A3 in diagnosing CAE, among which, Figure 1 A is to discover changes in the expression level of COL6A3 in the set. Figure 1 B represents the ROC curve for the COL6A3 set. Figure 1 C represents the changes in COL6A3 expression levels in the validation set. Figure 1 D represents the ROC curve of COL6A3 in the validation set. Detailed Implementation

[0043] The present invention is further illustrated below with reference to specific embodiments. These embodiments are for illustrative purposes only and should not be construed as limiting the invention. Those skilled in the art will understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the invention. The scope of the invention is defined by the claims and their equivalents. Experimental methods in the following embodiments that do not specify specific conditions are generally performed under conventional conditions or according to the manufacturer's recommendations. Reagents or instruments used that do not specify the manufacturer are all commercially available conventional products.

[0044] Example 1: Validation of the efficacy of COL6A3 in diagnosing coronary artery dilatation I. Experimental Methods 1. Sample: The discovery cohort recruited at Peking Union Medical College Hospital (PUMCH) included 12 patients with coronary artery dilatation (CAE) and 12 age- and sex-matched controls. The CAE group consisted of 3 cases of involuntary coronary artery ectasia (iCAE) and 9 cases of mCAE, matched 1:1 with 3 healthy controls (HC) and 9 patients with isolated coronary artery ectasia (CAD), respectively. Since CAE patients often have concurrent CAD, and mCAE was present in the patient population of this invention, to avoid the influence of the stenosis phenotype on biomarker screening, the CAD population was used as a confounding correction for the stenosis phenotype to ensure the screening of biomarkers specific to the "dilatation" phenotype.

[0045] The independent validation cohort, also from Peking Union Medical College Hospital (PUMCH), included 60 CAE patients (15 with iCAE and 45 with mCAE) and 60 matched controls (15 healthy volunteers and 45 with CAD alone), from whom plasma samples were collected.

[0046] The inclusion criteria for iCAE are: the diameter of the dilated coronary artery lumen confirmed by coronary angiography is ≥ 1.5 times that of the adjacent normal segment. The exclusion criteria are: (1) severe coronary artery disease requiring coronary artery bypass grafting; (2) other organic heart diseases, such as severe cardiomyopathy, valvular heart disease and pulmonary heart disease; (3) severe arrhythmia; (4) severe liver failure (Child-Pugh B or worse); (5) severe renal failure (eGFR < 30 ml / min / m2); (6) severe chronic obstructive pulmonary disease (Grade 3 or above, FEV1% pred < 50%); (7) severe anemia (Hb < 60 g / L); (8) malignant tumors and others.

[0047] The inclusion criteria for mCAE are: meeting the diagnostic criteria for dilation and having severe stenosis (stenosis degree >50%) in the main coronary artery or having significant plaque.

[0048] The inclusion criteria for CAD are: imaging showing that the stenosis of the lumen of at least one major coronary artery is >50%, and there is no dilation or change in the diameter and shape of the vessel.

[0049] The inclusion criteria for HC were: age and sex matched with the corresponding patient group, CAG or CTA showing no significant stenosis or dilation of the coronary arteries, and no history of angina or myocardial infarction.

[0050] 2. LC-MS / MS plasma proteomics analysis of the cohort: Plasma samples were centrifuged at 12,000 g for 10 minutes at 4 °C to remove cell debris. The supernatant was transferred to a new centrifuge tube, and protein concentration was quantified using a BCA kit. 51.25 mg of plasma was incubated with magnetic nanomaterials (PTM-00F13303, PTM Biotechnology) at 1200 rpm and 37 °C for 1 hour. After incubation, the magnetic beads were washed three times with washing buffer, and then 70 μL of enzyme digestion buffer was added to each bead, and the mixture was treated at 95 °C for 10 minutes. After cooling to room temperature, trypsin was added to a final concentration of 20 ng / μL, and digestion was performed overnight at 37 °C. Then, dithiothreitol (DTT) was added to a final concentration of 5 mM, and reduction was performed at 56 °C for 30 minutes. Finally, iodoacetamide (IAM) was added to a final concentration of 11 mM, and the mixture was incubated at room temperature in the dark for 15 minutes. The solution was then desalted using the method described in the C18 Zip Tips manual, lyophilized to obtain lyophilized powder, redissolved using mobile phase A to obtain the test solution, and separated using a Vanquish NeoUPLC system (ThermoFisher Scientific).

[0051] Protein separation was performed using a self-made reversed-phase column (15 cm × 100 μm inner diameter) via trypsin peptides. The liquid phase conditions were as follows: the mobile phase consisted of an aqueous solution containing 0.1% formic acid (mobile phase A) and an aqueous solution containing 0.1% formic acid and 80% acetonitrile (mobile phase B), with a flow rate of 300 nL / min; the elution program was gradient elution, as detailed in Table 1 below.

[0052] Table 1 After separation by an ultra-high performance liquid chromatography system, the sample was injected into an NSI ion source for ionization. The eluted peptides were then analyzed by an Orbitrap Astral mass spectrometer (electrospray voltage: 1.9 kV) to obtain full-range mass spectrometry (scanning range 380-980 m / z, scan resolution 240,000) and MS / MS (scanning range fixed start point 150 m / z, scan resolution 80,000, NCE 25%) results.

[0053] 3. ELISA Experiments for Validation Cohort: The concentration of COL6A3 protein in plasma was measured using a commercial ELISA kit (ELK3613) from ELK Biotechnology. Standards and plasma samples were aliquoted into antibody-pre-coated microplates for primary incubation. After washing, biotin-conjugated detection antibody and HRP-conjugated avidin were added sequentially. Enzyme activity was demonstrated by incubation with TMB substrate at 37°C, followed by neutralization with acidic stop solution. The optical density was measured at 450 nm.

[0054] II. Experimental Results The efficacy validation results of COL6A3 in diagnosing CAE are as follows: Figure 1 As shown; where, Figure 1 A is to discover changes in the expression level of COL6A3 in the set. Figure 1 B represents the ROC curve for the COL6A3 set. Figure 1 C represents the changes in COL6A3 expression levels in the validation set. Figure 1 D represents the ROC curve of COL6A3 in the validation set.

[0055] The results showed that the expression level of COL6A3 did not differ significantly between healthy individuals and those with simple CAD, but it was significantly elevated in the CAE patient group. Figure 1 A, C), implying that COL6A3 may be a potential "expanded" phenotype-specific biomarker. ROC curve validation confirmed that COL6A3 can effectively diagnose CAE patients, finding an AUC value of 0.856 in the cohort (…). Figure 1 B).

[0056] This invention further utilizes real-world clinical data from an independent validation cohort to determine the optimal diagnostic cutoff value as 91.3333 pg / mL using the maximum Youden Index. When the concentration of COL6A3 in a subject's sample is detected to be higher than or equal to 91.3333 pg / mL, it indicates a high risk of coronary artery dilation. Calculations show that, at this cutoff value, the sensitivity of using COL6A3 as a single biomarker to diagnose coronary artery dilation reaches 81.7%, the specificity reaches 65.0%, and the AUC is 0.796, fully demonstrating the independent clinical diagnostic efficacy and translational value of COL6A3. Figure 1 D).

[0057] The above results demonstrate that COL6A3 is a specific biomarker for the "expansion" phenotype in CAE patients and can be used for the clinical diagnosis of CAE patients with good sensitivity and specificity.

[0058] The above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the protection and disclosure scope of the present invention.

Claims

1. Application of reagents for detecting COL6A3 expression levels in samples in the preparation of diagnostic or auxiliary diagnostic products for coronary artery dilation.

2. The application according to claim 1, characterized in that, The reagents used to detect the expression level of COL6A3 in the sample include reagents for detecting the expression level of the COL6A3 gene and / or reagents for detecting the expression level of the COL6A3 protein. Preferably, the reagents include those for detecting the presence, absence, and / or expression level of the COL6A3 gene, fragments, and protein in a sample via PCR reaction, RT-PCR derivatization reaction, 3SR amplification, LCR, SDA, NASBA, TMA, SYBR Green, TaqMan probes, molecular beacons, two-hybrid probes, composite probes, ISH, microarrays, Southern blotting, Northern blotting, multianalyte assays, enzyme-linked immunosorbent assays, radioimmunoassays, immunofluorescence assays, enzyme immunoassays, immunoprecipitation assays, chemiluminescence assays, immunohistochemistry assays, dot blot assays, or narrow-line blot assays.

3. The application according to claim 1, characterized in that, The sample includes at least one of cells, tissues, or body fluids; Preferably, the body fluid includes at least one of blood, lymph, urine, sweat, bile, interstitial fluid, cerebrospinal fluid, or breast milk; Preferably, the blood includes at least one of whole blood, plasma, or serum; Preferably, the sample is plasma.

4. A product for diagnosing and assisting in the diagnosis of coronary artery dilatation, characterized in that, The product includes reagents for detecting the expression level of COL6A3 in samples; Preferably, the product includes at least one of a reagent kit, a chip, a test strip, or a high-throughput sequencing platform.

5. Application of COL6A3 in constructing a diagnostic model for coronary artery dilatation.

6. A method for constructing a diagnostic model for coronary artery dilatation, characterized in that, The method includes obtaining COL6A3 expression level data in ex vivo samples and inputting the data into a machine learning algorithm to construct the diagnostic model. Preferably, the diagnostic model obtains results using the following criteria: when the COL6A3 expression level is higher than the optimal cutoff value, the subject is classified as having a risk of coronary artery dilation; when the COL6A3 expression level is lower than the optimal cutoff value, the subject is classified as not having a risk of coronary artery dilation.

7. The method according to claim 6, characterized in that, The machine learning algorithms include algorithm models developed using various development tools; Preferably, the development tools include at least one of TensorFlow, Scikit-Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, or Spell; Preferably, the algorithm model includes at least one of the following: linear regression model, logistic regression model, Lasso regression model, Ridge regression model, linear discriminant analysis model, nearest neighbor model, decision tree model, perceptron model, neural network model, support vector machine model, Naive Bayes model, AdaBoost model, GBDT model, XGBoost model, LightGBM model, CatBoost model, or random forest model.

8. A system for diagnosing and assisting in the diagnosis of coronary artery dilatation, characterized in that, The system includes a processor, an input module, and an output module; The input module is used to input COL6A3 level data in the subject sample; the processor is used to perform logical operations on the input information using bioinformatics methods, and the processor contains a computer-readable medium storing instructions, which, when executed by the processor, execute the method for constructing the diagnostic model according to claim 7 on the input COL6A3 level; the output module is used to output the classification result of whether the subject has or is suspected of having coronary artery dilatation.

9. A device / apparatus for diagnosing and assisting in the diagnosis of coronary artery dilatation, characterized in that, The device / apparatus includes a memory and a processor; the memory is used to store program instructions, and the processor is used to call the program instructions. When the program instructions are executed, the system for diagnosing and assisting in the diagnosis of coronary artery dilatation as described in claim 8 is implemented.

10. A computer-readable storage medium for diagnosing and assisting in the diagnosis of coronary artery dilatation, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the functions of the system for diagnosing and assisting in the diagnosis of coronary artery dilatation as described in claim 8.

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