Molecular diagnostic kit related to cardiovascular diseases

Abstract

The invention belongs to the technical field of molecular diagnosis, and discloses a molecular diagnosis kit related to cardiovascular diseases. The molecular diagnosis kit related to cardiovascular diseases comprises a multiple gene mutation detection module, a high-sensitivity marker detection module, a miRNA expression level detection module, a high-sensitivity rare mutation detection module, an automatic sample treatment and analysis module, a gene-protein integration analysis module and a pharmacogenomics guidance module. Through the application of the kit, the diagnosis efficiency and accuracy of a hospital are remarkably improved, namely, a doctor can comprehensively know the molecular state of a patient through multi-dimensional detection, and deeper disease assessment is provided for multi-level information from genes, RNA (Ribonucleic Acid) to protein. High-sensitivity detection enables hospitals to detect low-abundance biomarkers through digital PCR and immunocapture technologies, diseases can be found in the early stage, and the success rate of early intervention is increased.

Description

Technical Field

[0001] The present invention belongs to the technical field of molecular diagnosis, and particularly relates to a molecular diagnostic kit related to cardiovascular diseases. Background Art

[0002] In the clinical diagnosis of cardiovascular diseases, molecular diagnostic techniques have been widely applied, including kits based on gene mutations, gene expression levels, and protein biomarker detection. However, existing molecular diagnostic kits usually can only detect a single or a small number of specific cardiovascular-related biomarkers and cannot provide comprehensive disease information. These kits usually analyze a single target gene or a specific protein and cannot simultaneously evaluate the interactions between multiple key genes, proteins, or metabolites. More importantly, traditional kits are time-consuming in sample processing and detection, with low diagnostic efficiency and difficult to meet the requirements of rapid and accurate clinical diagnosis.

[0003] Through the above analysis, the problems and defects of the existing technology are as follows:

[0004] (1) Limitations of single target detection: Most existing kits can only detect a certain biomarker, such as a single gene mutation or a specific protein level, and cannot provide multi-dimensional diagnostic information.

[0005] (2) Insufficient detection sensitivity and specificity: For low-abundance biomarkers, the sensitivity and specificity of existing kits are low, and false negative or false positive results are likely to occur.

[0006] (3) Complicated sample processing and long time consumption: The sample processing steps in the existing technology are relatively complex, the detection time is long, and the clinical requirements for rapid diagnosis cannot be met.

[0007] (4) Insufficient comprehensive biological information: Existing kits fail to make full use of big data and bioinformatics analysis and cannot comprehensively analyze the interactions of multiple molecular markers. Summary of the Invention

[0008] In view of the problems existing in the existing technology, the present invention provides a molecular diagnostic kit related to cardiovascular diseases.

[0009] The present invention is implemented as follows. A molecular diagnostic kit related to cardiovascular diseases includes:

[0010] A multiple gene mutation detection module, a high-sensitivity biomarker detection module, a miRNA expression level detection module, a high-sensitivity rare mutation detection module, an automated sample processing and analysis module, a gene-protein integration analysis module, and a pharmacogenomics guidance module;

[0011] Multiple gene mutation detection module, which uses multiplex digital PCR technology and next-generation sequencing technology to simultaneously detect multiple SNP gene mutations related to coronary heart disease, atherosclerosis, and vascular injury, including but not limited to APOE, PCSK9, LDLR, MTHFR, LPA, NOS3, and KIF6 gene mutation sites, and performs highly sensitive detection on them;

[0012] High-sensitivity biomarker detection module, which uses enhanced enzyme-linked immunosorbent assay (ELISA) and nanoparticle labeling technology to detect protein biomarkers in serum, including high-sensitivity C-reactive protein (hsCRP), atrial natriuretic peptide (ANP), lipoprotein (a), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), and fibrinogen, for evaluating the inflammatory response, vascular injury, and blood coagulation status related to coronary heart disease;

[0013] miRNA expression level detection module, which uses fluorescence quantitative reverse transcription PCR technology to detect the expression levels of microRNAs (miRNAs) related to coronary heart disease and its progression, including miR-21, miR-146a, miR-208, miR-133, and miR-499, and evaluates the correlation between their expression and cardiovascular diseases;

[0014] High-sensitivity rare mutation detection module, which uses ultra-high-sensitivity digital PCR technology and droplet separation method to quantitatively detect rare mutations of PCSK9, LDLR, and APOB genes with low abundance in the blood of coronary heart disease patients;

[0015] Automated sample processing and analysis module, which has fully automated functions of sample extraction, amplification, separation, and detection, supports the processing of multiple sample types, and ensures the automated tracking and standardized operation of sample information through the built-in sample barcode scanning; the sample types include blood, serum, DNA, and RNA;

[0016] Gene-protein integration analysis module, which integrates gene mutation, miRNA expression level, and protein biomarker data by integrating a big data analysis platform, using machine learning algorithms and bioinformatics tools to generate a personalized molecular characteristic map of coronary heart disease, predict the risk of coronary heart disease progression in patients, and provide personalized treatment plans and lifestyle intervention suggestions based on molecular characteristics;

[0017] Pharmacogenomics guidance module, which combines the patient's gene mutation sites, analyzes drug metabolism genes, provides personalized prediction of drug metabolism reactions and medication guidance, and recommends the optimal drug treatment plan for coronary heart disease; the drug metabolism genes include CYP2C19 and CYP3A4.

[0018] Further, the automated sample processing and analysis module further includes an artificial intelligence (AI)-driven quality control system, which can automatically monitor the key steps in the sample processing process (DNA extraction, RNA reverse transcription, PCR amplification), identify potential errors or deviations in real time, automatically adjust experimental parameters to improve detection accuracy, and generate a quality control report for the experimental process;

[0019] The gene-protein integration analysis module uses deep learning algorithms and can automatically identify combinations of molecular markers highly related to the progression of coronary heart disease by training a large amount of clinical data of coronary heart disease patients, and predict the likelihood of acute cardiovascular events occurring in patients within the next 12 months to provide suggestions for early intervention;

[0020] The pharmacogenomics guidance module can intelligently match the gene mutation information of coronary heart disease patients with the existing drug target database, combine the patient's genotype, recommend the most suitable drug dosage, and alert possible drug adverse reactions. At the same time, it automatically pushes the personalized medication plan to medical staff and patients through a mobile phone App or email.

[0021] Further, the multiple gene mutation detection module uses a specially designed multiplex PCR primer set to simultaneously amplify multiple mutation sites of APOE, PCSK9, LDLR, MTHFR, and LPA genes, and precisely detect the single nucleotide polymorphisms (SNPs) of these sites through first-generation sequencing technology to evaluate the genetic susceptibility of coronary heart disease; the high-sensitivity marker detection module further includes a standardized protein quantification analysis process. The process uses enzyme-linked immunosorbent assay (ELISA) with a double antibody sandwich method, combined with internal references and standard curves, to perform high-sensitivity quantitative detection of the concentrations of CRP, ANP, lipoprotein(a), TNF-α, and IL-6 to precisely evaluate the inflammatory status and cardiac function of coronary heart disease patients.

[0022] Further, the protein markers include cardiac troponin and C-reactive protein; the multiple gene mutation detection module:

[0023] First, gene fragments in the sample are synchronously amplified by multiplex PCR technology. The amplified products are sent to a first-generation sequencer for high-throughput sequencing and protein quantification, thereby detecting multiple gene mutations related to cardiovascular diseases; at the same time, the expression level of RNA is quantitatively analyzed by fluorescence quantitative PCR;

[0024] The protein markers are detected by enzyme-linked immunosorbent assay (ELISA) to measure the concentrations of proteins including cardiac troponin and C-reactive protein in the serum.

[0025] Further, the high-sensitivity marker detection module:

[0026] The digital PCR technology is adopted to achieve accurate counting of DNA and RNA; by dividing the sample into tens of thousands of micro reaction chambers, it is ensured that each reaction chamber contains only one or a few molecules, and then amplification and detection are carried out; for protein markers, the immunocapture technology is used to enrich low-concentration protein molecules, combined with ELISA to improve the sensitivity and specificity of detection.

[0027] Furthermore, the automated sample processing and analysis module:

[0028] The automated sample processing system integrates the whole process operations of sample extraction, amplification and detection; the system first extracts DNA, RNA and proteins from blood or saliva samples through an automated extraction device; the extracted samples automatically enter the amplification system for multiplex PCR and fluorescence quantitative PCR amplification, or enter the ELISA detection module for protein analysis; all operation steps are controlled by a computer program.

[0029] Another object of the present invention is to provide a diagnostic method for a molecular diagnostic kit related to cardiovascular diseases, including:

[0030] Step 1, using the multiplex gene mutation detection module to simultaneously detect multiple SNP gene mutations related to coronary heart disease, atherosclerosis and vascular injury by using multiplex digital PCR technology and next-generation sequencing technology, including but not limited to APOE, PCSK9, LDLR, MTHFR, LPA, NOS3 and KIF6 gene mutation sites, and performing high-sensitivity detection on them;

[0031] Step 2, using the high-sensitivity marker detection module to detect protein markers in serum, including high-sensitivity C-reactive protein (hsCRP), atrial natriuretic peptide (ANP), lipoprotein (a), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), fibrinogen, by using enhanced enzyme-linked immunosorbent assay (ELISA) and nanoparticle labeling technology, for evaluating the inflammatory response, vascular injury and blood coagulation status related to coronary heart disease;

[0032] Step 3, using the miRNA expression level detection module to detect the expression levels of microRNAs (miRNAs) related to coronary heart disease and its progression, including miR-21, miR-146a, miR-208, miR-133 and miR-499, by using fluorescence quantitative reverse transcription PCR technology, and evaluating the correlation between their expression and cardiovascular diseases;

[0033] Step 4, using the high-sensitivity rare mutation detection module, adopting ultra-high-sensitivity digital PCR technology and droplet separation method, to quantitatively detect rare mutations of PCSK9, LDLR and APOB genes with low abundance in the blood of coronary heart disease patients;

[0034] Step 5: The automated sample processing and analysis module has functions of fully automated sample extraction, amplification, separation, and detection, supports the processing of multiple sample types, and ensures the automated tracking and standardized operation of sample information through the built-in sample barcode scanning; the sample types include blood, serum, DNA, and RNA.

[0035] Step 6: Through the gene-protein integration analysis module, using the integrated big data analysis platform, integrating gene mutation, miRNA expression level, and protein biomarker data by using machine learning algorithms and bioinformatics tools, generating a personalized molecular feature map of coronary heart disease, predicting the risk of coronary heart disease progression in patients, and providing personalized treatment plans and lifestyle intervention suggestions based on molecular features.

[0036] Step 7: Through the pharmacogenomics guidance module, combining the patient's gene mutation sites, analyzing drug metabolism genes, providing personalized prediction of drug metabolism reactions and medication guidance, and recommending the optimal drug treatment plan for coronary heart disease; the drug metabolism genes include CYP2C19 and CYP3A4.

[0037] Combined with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by the present invention are as follows:

[0038] First, aiming at the technical problems existing in the above-mentioned prior art, some creative technical effects are brought after solving the problems. The specific descriptions are as follows:

[0039] 1. Comprehensively improve the diagnostic information volume: Through the integrated detection of multiple markers, the kit can simultaneously analyze data in multiple dimensions of genes, RNA, proteins, and metabolites, providing more comprehensive cardiovascular disease diagnostic information than traditional single-marker kits.

[0040] 2. Improve the detection sensitivity and specificity: Using digital PCR technology and immunocapture technology, the kit can detect low-abundance DNA in the early disease state, greatly improving the detection sensitivity and specificity, and reducing the possibility of misdiagnosis or missed diagnosis.

[0041] 3. Simplify the operation process and improve the detection efficiency: The automated sample processing and detection process greatly simplifies the operation steps and shortens the detection time. It only takes a few hours from sample processing to result output, meeting the clinical need for rapid diagnosis and improving the diagnostic efficiency.

[0042] 4. Personalized diagnosis and risk assessment: Through the bioinformatics analysis module, the kit can generate a personalized cardiovascular disease diagnostic report based on the data of multiple molecular markers, helping doctors better manage the disease and conduct early intervention, and promoting the development of personalized medicine.

[0043] Through the application of this new molecular diagnostic kit for cardiovascular diseases, the accuracy, efficiency, and comprehensiveness of clinical diagnosis of cardiovascular diseases can be significantly improved, and it has broad clinical promotion value.

[0044] Second, compare the technical solution of the present invention with the prior art and list the data of key parameters and effects. The following table shows the differences between the present invention and the prior art in terms of detection sensitivity, detection time, types of markers, and diagnostic accuracy.

[0045] Parameters / Effects Technical Solution of the Present Invention Prior Art Detection Sensitivity <![CDATA[≤1×10 8 copies / gram (high-sensitivity digital PCR)]]> <![CDATA[1×10 6 CFU / g (conventional PCR)]]> Detection Time 6 - 8 hours (Automated Processing Flow) 24 - 48 hours (Mainly Manual Operation) Types of Detection Markers Genes, RNA, Proteins (Multiple Markers) Only Gene or Protein Markers (Single Dimension) Marker Detection Technology Multiplex PCR, Fluorescent Quantitative PCR, ELISA Conventional PCR or Single ELISA Detection Ability of Low - Abundance Molecules Supported (by Digital PCR and Immunocapture) Not Supported (Unable to Detect Low - Abundance Molecules) Degree of Automation Highly Automated (Automated Sample Processing Module) Mainly Manual Processing Bioinformatics Analysis and Integration Supported (Bioinformatics Module and Big Data Integration) Not Supported (Only Basic Detection Data Provided) Personalized Risk Prediction Provide Personalized Diagnosis and Risk Prediction Reports Do Not Support Personalized Analysis Diagnostic Accuracy ≥95% (Based on Multidimensional Marker Detection) 80 - 85% (Based on Single Marker Detection)

[0046] Data analysis:

[0047] 1. Detection sensitivity: The present invention significantly improves the detection ability of low-abundance DNA / RNA through multiplex PCR and digital PCR technologies, and the detection sensitivity is about 100 times higher than that of the prior art.

[0048] 2. Detection time: Due to the introduction of an automated sample processing module, the present invention shortens the detection time to 6 - 8 hours, while traditional manual detection requires more than 24 hours.

[0049] 3. Types of markers: The present invention combines multi-dimensional detection of gene, RNA, and protein markers, which can provide more comprehensive diagnostic data, while the prior art usually can only detect a single type of marker.

[0050] 4. Detection of low-abundance molecules: The present invention can identify low-abundance molecules through high-sensitivity digital PCR and immunocapture technologies, while the prior art is powerless in this regard.

[0051] 5. Degree of automation: The highly automated process of the present invention effectively reduces manual intervention, reduces human error, and significantly improves the diagnostic efficiency.

[0052] 6. Personalized risk prediction: The present invention integrates multi-dimensional data through a bioinformatics analysis module to generate a personalized diagnostic report, which is difficult to achieve with traditional technologies.

[0053] 7. Diagnostic accuracy: Thanks to the multiplex marker detection and comprehensive analysis, the diagnostic accuracy of the present invention is significantly improved, reaching more than 95%, which is significantly higher than 80 - 85% of the prior art.

[0054] From these data comparisons, it can be seen that the present invention far outperforms the prior art in terms of detection sensitivity, accuracy, degree of automation, and personalized risk prediction in the molecular diagnosis of cardiovascular diseases. Brief description of the drawings

[0055] Figure 1It is a structural block diagram of a molecular diagnostic kit related to cardiovascular diseases provided by an embodiment of the present invention.

[0056] Figure 2 It is a method flow chart of a multiplex gene mutation detection module provided by an embodiment of the present invention.

[0057] Figure 3 It is a diagnostic method flow chart of a molecular diagnostic kit related to cardiovascular diseases provided by an embodiment of the present invention.

[0058] Figure 1 Among them: 1. Multiplex gene mutation detection module; 2. High-sensitivity biomarker detection module; 3. miRNA expression level detection module; 4. High-sensitivity rare mutation detection module; 5. Automated sample processing and analysis module; 6. Gene-protein integration analysis module; 7. Pharmacogenomics guidance module. Detailed implementation manners

[0059] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0060] A molecular diagnostic kit for cardiovascular diseases provided by the present invention, the kit includes the following modules:

[0061] 1. Multiplex gene mutation detection module:

[0062] Hardware: Detection equipment based on a multi-channel digital PCR instrument and a next-generation sequencing platform, supporting high-throughput gene mutation analysis.

[0063] Software: Built-in optimized gene analysis algorithm, adopting a multiplex mutation site separation algorithm, accurately distinguishing SNP sites of APOE, PCSK9, LDLR, MTHFR, LPA, NOS3 and KIF6 genes, and correcting background noise through a machine learning model, realizing the rare mutation detection ability with a sensitivity of 0.01%.

[0064] Data: Combining a genetic mutation data set of 10,000 coronary heart disease patients for training a mutation site recognition model to improve the accuracy of gene mutation analysis.

[0065] The high-sensitivity biomarker detection module of the kit is characterized in that:

[0066] Hardware: Adopting an automated ELISA workstation, with a built-in nanoparticle-labeled extended detector, supporting the rapid detection of multiple biomarkers (hsCRP, ANP, LPA, TNF-α, IL-6 and fibrinogen), and the sensitivity can reach the pg / mL level.

[0067] Software: Equipped with biomarker data integration software, it monitors the biomarker detection curve in real time and uses an algorithm model based on regression analysis to evaluate the patient's inflammation response, vascular injury, and blood coagulation risks.

[0068] Data: Integrated the dynamic curve data of biomarkers from 10,000 coronary heart disease patients to generate a reference range database for test results, which is used for personalized risk assessment.

[0069] The miRNA expression level detection module of the kit is characterized in that:

[0070] Hardware: Based on the fluorescence quantitative PCR platform, it supports single-tube multi-target miRNA detection; equipped with a highly sensitive fluorescence detector with a detection sensitivity of 1 fM.

[0071] Software: Adopts miRNA data normalization and differential expression analysis algorithms, combined with the principal component analysis (PCA) model, to evaluate the correlation between miR-21, miR-146a, miR-208, miR-133, and miR-499 and the patient's coronary heart disease risk.

[0072] Data: Relying on the miRNA expression database of the Global Cardiovascular Research Consortium, integrated the miRNA expression profile data of 1,000 coronary heart disease patients and control groups to provide a reference model for miRNA expression and disease progression.

[0073] The highly sensitive rare mutation detection module of the kit is characterized in that:

[0074] Hardware: A droplet digital PCR system, combined with a rare mutation enrichment chip, supports the quantitative detection of ultra-low abundance mutations in PCSK9, LDLR, and APOB genes.

[0075] Software: The rare mutation detection software is based on the Bayesian statistical model and sparse signal reconstruction algorithm, which improves the detection ability of low-abundance mutation sites with a sensitivity of 0.001%.

[0076] Data: Integrated the coronary heart disease rare mutation-specific library, combined with genotype-phenotype association data, to improve the clinical prediction value of mutation detection.

[0077] The automated sample processing and analysis module of the kit is characterized in that:

[0078] Hardware: A fully automated sample processing platform that integrates functions of centrifugal separation, nucleic acid extraction, specimen purification, and reaction system construction, and is suitable for the processing of blood, serum, DNA, and RNA samples; equipped with a barcode scanner to achieve automated sample tracking.

[0079] Software: Built-in sample quality control algorithm to monitor the extraction efficiency and purity of samples in real time; adopt a standardized data processing process to reduce human errors.

[0080] Data: The sample information management database supports dynamic tracking of samples and analysis of historical records, and completes laboratory data integration in combination with LIMS (Laboratory Information Management System).

[0081] The gene-protein integration analysis module of the said kit is characterized in that:

[0082] Hardware: A bioinformatics analysis platform based on a high-performance computing cluster, which supports the integrated analysis of multi-dimensional data such as gene mutations, miRNAs, and protein markers.

[0083] Software: Use a deep learning model (such as a multi-layer perceptron) to train and predict the molecular characteristic data of patients, generate a personalized coronary heart disease molecular characteristic map, and predict the disease progression risk of patients in combination with clustering analysis and decision tree algorithms.

[0084] Data: Integrate multi-center clinical databases (>50,000 patients), establish a prediction model for the molecular characteristics of coronary heart disease and treatment effects, and provide suggestions for optimizing treatment plans.

[0085] The pharmacogenomics guidance module of the said kit is characterized in that:

[0086] Hardware: Equipped with a gene sequencing analyzer to support the sequencing of metabolic genes such as CYP2C19 and CYP3A4.

[0087] Software: The drug metabolism prediction model is based on the support vector machine (SVM) algorithm and a pharmacokinetic database to evaluate the impact of patient genotypes on drug metabolism reactions.

[0088] Data: Integrate the genotype-drug efficacy association database of coronary heart disease patients to support personalized drug recommendations.

[0089] The said kit combines all modules and realizes the following functions by integrating gene mutation, protein marker, and miRNA expression level data:

[0090] Provide comprehensive molecular diagnostic information and generate a personalized disease characteristic map of the patient;

[0091] Predict disease progression according to the patient risk assessment model;

[0092] Combine pharmacogenomics data to recommend personalized drug treatment plans and lifestyle intervention strategies.

[0093] Working principle and implementation details:

[0094] 1. Data collection and preprocessing

[0095] The automated sample processing platform extracts target molecules (genes, proteins, miRNAs) from blood, serum, or DNA samples, reducing human error through a fully automated process.

[0096] The data acquisition module transmits the detection data to the central database in real time.

[0097] 2. Modular Analysis and Integration

[0098] Each module independently completes specific data analysis (such as gene mutation detection, protein biomarker level assessment).

[0099] The central analysis system integrates and analyzes multi-dimensional data through machine learning algorithms to generate a personalized molecular feature map of the patient.

[0100] 3. Risk Assessment and Treatment Optimization

[0101] The integrated analysis results are imported into the AI model, combined with the patient's historical data, to generate a disease risk prediction report.

[0102] The pharmacogenomics module provides personalized medication recommendations based on the patient's genotype.

[0103] 4. Output Results and Decision Support

[0104] Finally, a complete report containing molecular diagnostic results, disease risk prediction, and treatment plan recommendations is generated for clinical doctors to reference.

[0105] This system combines high-performance hardware, intelligent software, and massive data resources to achieve a full-process molecular diagnosis and personalized medical support for cardiovascular diseases.

[0106] The specific working principle of the present invention is as follows:

[0107] 1) Working Principle of the Gene Biomarker Module

[0108] Sample Processing and DNA Extraction: Genomic DNA is extracted from the patient's blood sample, and standard techniques such as the centrifugal column method or magnetic bead method are used for DNA extraction and purification to ensure contamination-free and high-quality DNA in the sample.

[0109] Multiplex PCR Amplification: Based on the designed specific primers, multiple mutation sites of target genes (such as APOE, PCSK9, LDLR, MTHFR, LPA) are amplified simultaneously using multiplex PCR technology. This process allows multiple gene loci to be amplified simultaneously by using multiple pairs of primers in a single reaction, thereby improving the detection efficiency.

[0110] First-generation sequencing analysis: The amplified products are subjected to sequence analysis by Sanger sequencing technology. First-generation sequencing can provide precise mutation information at single-base resolution for detecting mutations at SNP sites. The sequencing data are aligned with the reference genome to identify the types of mutations in relevant genes, and combined with the coronary heart disease risk assessment model to further analyze the impact of mutations on the disease.

[0111] 2) Working principle of the serum biomarker module

[0112] Sample processing and protein extraction: Serum is separated from the patient's blood, and cell components are removed by high-speed centrifugation to ensure the purity of the serum sample. After extraction, the serum is stored under low-temperature conditions to prevent protein degradation.

[0113] ELISA detection principle: Based on the enzyme-linked immunosorbent assay (ELISA), protein biomarkers in serum (such as CRP, ANP, lipoprotein(a), TNF-α, IL-6) are quantitatively detected by reacting with labeled antibodies. In a 96-well plate, the antigen of the biomarker is first immobilized on the well wall, and then the patient sample and the antibody labeled with an enzyme are added sequentially. After binding, the signal intensity is measured through the color reaction catalyzed by the enzyme, and the signal is proportional to the concentration of the target protein. ELISA has high sensitivity and specificity and can accurately measure the concentration changes of coronary heart disease-related proteins.

[0114] 3) Working principle of the RNA expression level module

[0115] RNA extraction: Total RNA is extracted from the patient's blood sample using Trizol reagent or other RNA extraction kits to ensure the integrity and purity of the RNA and avoid DNA contamination. The extracted RNA is immediately reverse transcribed into cDNA for subsequent fluorescence quantitative PCR detection.

[0116] Fluorescence quantitative PCR (qPCR) detection: Specific primers and probes are used to perform qPCR detection on miRNAs related to the progression of coronary heart disease (such as miR-21, miR-146a, miR-208). qPCR monitors the fluorescence signal generated during the PCR amplification process to achieve real-time quantification. This process is based on TaqMan probes or SYBR Green dyes, and the fluorescence intensity is recorded for each amplification cycle. The accumulation of the signal is proportional to the initial copy number of the target RNA. The results can show the relative expression level of the RNA and reveal the regulatory role of miRNAs in the progression of coronary heart disease.

[0117] 4) Working principle of the high-sensitivity rare mutation detection module

[0118] Sample Pretreatment and Digital PCR Preparation: The DNA or RNA extracted from patient blood samples is further purified and divided into many droplets or reaction microzones at the nanoscale. Each droplet may contain 0 or 1 target molecule, ensuring that the digital PCR technology can achieve high-precision detection.

[0119] Principle of Digital PCR Detection: Digital PCR separates the PCR reaction into thousands of independent reaction microzones, and each microzone undergoes PCR amplification individually. In these reaction regions, target genes (such as rare mutation sites in PCSK9 and LDLR) are highly sensitively amplified. After the amplification is completed, the presence or absence of fluorescence signals is used to distinguish whether each reaction zone contains the target mutation. Digital PCR has higher sensitivity and precision compared to traditional qPCR and can quantitatively analyze low-frequency gene mutations, which is particularly effective in detecting rare mutations or low-abundance targets.

[0120] 5) Working Principle of the Automated Sample Processing Module

[0121] Automated Extraction: The automated sample processing module uses a preset program to process samples. Through a liquid handling robot, blood, serum, or DNA / RNA samples can be fully automated processed, from sample separation to DNA / RNA extraction and then to the preparation of amplification reactions. Precise control of each step reduces human error and improves the efficiency and consistency of sample processing.

[0122] Integrated Workflow: This module integrates multiple steps such as nucleic acid extraction, amplification, and protein detection to achieve full-process automation. Different types of sample processing procedures are connected through modular design to ensure standardized operation of samples. At the same time, the system can dynamically adjust the workflow according to the sample volume or the requirements of detection items to achieve efficient batch detection.

[0123] 6) Working Principle of the Bioinformatics Analysis Module

[0124] Data Integration and Analysis: The bioinformatics analysis module collects data from various detection modules, including information such as gene mutations, RNA expression, and protein biomarker concentrations. By inputting this data into bioinformatics tools, a multi-dimensional molecular feature database is established, and combined with big data analysis techniques, the interaction between different biomarkers is comprehensively analyzed to form a molecular feature map of coronary heart disease.

[0125] Personalized risk assessment: Based on the analysis results, the system combines existing coronary heart disease risk assessment models (such as the Framingham risk score model, etc.), analyzes the changes of each molecular biomarker through machine learning algorithms, and generates a personalized disease diagnosis and risk prediction report. This report can reveal the coronary heart disease risk level of the patient and provide targeted prevention and treatment suggestions for clinicians to ensure the precision and personalization of treatment.

[0126] Through the detailed working principle description of these modules, the entire molecular diagnostic kit for coronary heart disease can achieve multi-level detection from genes, RNA, and proteins, provide high-precision early diagnosis and risk assessment of coronary heart disease, and meet the actual clinical needs.

[0127] Such as Figure 1 As shown, a molecular diagnostic kit related to cardiovascular diseases provided by an embodiment of the present invention includes:

[0128] Multiple gene mutation detection module 1, high-sensitivity biomarker detection module 2, miRNA expression level detection module 3, high-sensitivity rare mutation detection module 4, automated sample processing and analysis module 5, gene-protein integration analysis module 6, pharmacogenomics guidance module 7;

[0129] The multiple gene mutation detection module 1 uses multiplex digital PCR technology and next-generation sequencing technology to simultaneously detect multiple SNP gene mutations related to coronary heart disease, atherosclerosis, and vascular injury, including but not limited to APOE, PCSK9, LDLR, MTHFR, LPA, NOS3, and KIF6 gene mutation sites, and performs high-sensitivity detection on them;

[0130] The high-sensitivity biomarker detection module 2 uses enhanced enzyme-linked immunosorbent assay (ELISA) and nanoparticle labeling technology to detect protein biomarkers in serum, including high-sensitivity C-reactive protein (hsCRP), atrial natriuretic peptide (ANP), lipoprotein (a), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), and fibrinogen, for evaluating the inflammatory response, vascular injury, and blood coagulation status related to coronary heart disease;

[0131] The miRNA expression level detection module 3 uses fluorescence quantitative reverse transcription PCR technology to detect the expression levels of microRNAs (miRNAs) related to coronary heart disease and its progression, including miR-21, miR-146a, miR-208, miR-133, and miR-499, and evaluates the correlation between their expression and cardiovascular diseases;

[0132] The high-sensitivity rare mutation detection module 4 uses ultra-high-sensitivity digital PCR technology and droplet separation method to quantitatively detect rare mutations of low-abundance PCSK9, LDLR, and APOB genes in the blood of coronary heart disease patients;

[0133] The automated sample processing and analysis module 5 has functions of fully automated sample extraction, amplification, separation, and detection, supports the processing of multiple sample types, and ensures the automated tracking and standardized operation of sample information through the built-in sample barcode scanning; the sample types include blood, serum, DNA, and RNA;

[0134] The gene-protein integration analysis module 6 integrates a big data analysis platform, uses machine learning algorithms and bioinformatics tools to integrate gene mutation, miRNA expression level, and protein biomarker data, generates a personalized molecular feature map of coronary heart disease, predicts the risk of coronary heart disease progression in patients, and provides personalized treatment plans and lifestyle intervention suggestions based on molecular features;

[0135] The pharmacogenomics guidance module 7 analyzes drug metabolism genes in combination with the patient's gene mutation sites, provides personalized prediction of drug metabolism reactions and medication guidance, and recommends the optimal drug treatment plan for coronary heart disease; the drug metabolism genes include CYP2C19 and CYP3A4.

[0136] The automated sample processing and analysis module provided by the embodiment of the present invention further includes an artificial intelligence (AI)-driven quality control system, which can automatically monitor the key steps (DNA extraction, RNA reverse transcription, PCR amplification) in the sample processing process, identify potential errors or deviations in real time, automatically adjust experimental parameters to improve detection accuracy, and generate a quality control report of the experimental process;

[0137] The gene-protein integration analysis module uses deep learning algorithms, can automatically identify combinations of molecular markers highly related to the progression of coronary heart disease by training a large amount of clinical data of coronary heart disease patients, and predicts the possibility of acute cardiovascular events occurring in patients within the next 12 months to provide suggestions for early intervention;

[0138] The pharmacogenomics guidance module can intelligently match the gene mutation information of coronary heart disease patients with the existing drug target database, combine the patient's genotype, recommend the most suitable drug dose, and warn of possible drug adverse reactions, and at the same time automatically push the personalized medication plan to medical staff and patients through a mobile phone App or email.

[0139] The multiplex gene mutation detection module provided by the embodiments of the present invention uses a specially designed multiplex PCR primer set to simultaneously amplify multiple mutation sites of APOE, PCSK9, LDLR, MTHFR, and LPA genes, and precisely detect the single nucleotide polymorphisms (SNPs) of these sites through first-generation sequencing technology to evaluate the genetic susceptibility of coronary heart disease; the high-sensitivity biomarker detection module further includes a standardized protein quantification analysis process, which uses enzyme-linked immunosorbent assay (ELISA) with a double antibody sandwich method, combined with internal reference and standard curve, to perform high-sensitivity quantitative detection on the concentrations of CRP, ANP, lipoprotein (a), TNF-α, and IL-6, for precisely evaluating the inflammatory state and cardiac function of coronary heart disease patients.

[0140] The protein biomarkers provided by the embodiments of the present invention include cardiac troponin and C-reactive protein; the multiplex gene mutation detection module:

[0141] First, the gene fragments in the sample are synchronously amplified by multiplex PCR technology. The amplified products are sent to a first-generation sequencer for high-throughput sequencing and protein quantification, so as to detect multiple gene mutations related to cardiovascular diseases; meanwhile, the expression level of RNA is quantitatively analyzed by fluorescence quantitative PCR;

[0142] The protein biomarkers are detected by enzyme-linked immunosorbent assay (ELISA) to measure the concentrations of proteins including cardiac troponin and C-reactive protein in the serum.

[0143] The high-sensitivity biomarker detection module provided by the embodiments of the present invention:

[0144] Uses digital PCR technology to achieve precise counting of DNA and RNA; by dividing the sample into tens of thousands of micro reaction chambers, ensuring that each reaction chamber contains only one or a few molecules, and then performing amplification and detection; for protein biomarkers, immunocapture technology is used to enrich low-concentration protein molecules, combined with ELISA to improve the sensitivity and specificity of detection.

[0145] The automated sample processing and analysis module provided by the embodiments of the present invention:

[0146] The automated sample processing system integrates the whole process operations of sample extraction, amplification, and detection; the system first extracts DNA, RNA, and proteins from blood or saliva samples through an automated extraction device; the extracted samples automatically enter the amplification system for multiplex PCR and fluorescence quantitative PCR amplification, or enter the ELISA detection module for protein analysis; all operation steps are controlled by a computer program.

[0147] As Figure 2 shown, the diagnostic method of a molecular diagnostic kit related to cardiovascular diseases provided by the embodiments of the present invention includes:

[0148] S101, simultaneously detect multiple SNP gene mutations related to coronary heart disease, atherosclerosis and vascular injury by using multiplex digital PCR technology and next-generation sequencing technology through a multiplex gene mutation detection module, including but not limited to APOE, PCSK9, LDLR, MTHFR, LPA, NOS3 and KIF6 gene mutation sites, and perform highly sensitive detection on them;

[0149] S102, detect protein markers in serum by using enhanced enzyme-linked immunosorbent assay (ELISA) and nanoparticle labeling technology through a high-sensitivity marker detection module, including high-sensitivity C-reactive protein (hsCRP), atrial natriuretic peptide (ANP), lipoprotein (a), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), fibrinogen, for evaluating the inflammatory response, vascular injury and blood coagulation status related to coronary heart disease;

[0150] S103, detect the expression levels of microRNAs (miRNAs) related to coronary heart disease and its progression by using fluorescence quantitative reverse transcription PCR technology through a miRNA expression level detection module, including miR-21, miR-146a, miR-208, miR-133 and miR-499, and evaluate the correlation between their expressions and cardiovascular diseases;

[0151] S104, quantitatively detect rare mutations of PCSK9, LDLR and APOB genes with low abundance in the blood of coronary heart disease patients by using ultra-high-sensitivity digital PCR technology and droplet separation method through a high-sensitivity rare mutation detection module;

[0152] S105, has fully automated sample extraction, amplification, separation and detection functions through an automated sample processing and analysis module, supports the processing of multiple sample types, and ensures the automated tracking and standardized operation of sample information through the built-in sample barcode scanning; the sample types include blood, serum, DNA, RNA;

[0153] S106, integrate gene mutation, miRNA expression level and protein biomarker data to generate a personalized molecular characteristic map of coronary heart disease, predict the progression risk of coronary heart disease in patients, and provide personalized treatment plans and lifestyle intervention suggestions based on molecular characteristics by using an integrated big data analysis platform through a gene-protein integration analysis module, using machine learning algorithms and bioinformatics tools;

[0154] S107. Combine the patient's gene mutation sites through the pharmacogenomics guidance module, analyze the drug metabolism genes, provide personalized prediction of drug metabolism reactions and medication guidance, and recommend the optimal coronary heart disease drug treatment plan; the drug metabolism genes include CYP2C19 and CYP3A4.

[0155] The cardiovascular disease-related molecular diagnostic kit of the present invention realizes multi-dimensional molecular detection and risk assessment through four main modules. First, in the multiplex gene mutation detection module (1), this module uses multiplex PCR technology and next-generation sequencing technology to synchronously detect gene mutations related to cardiovascular diseases. Specifically, this module can detect gene mutations including APOE and PCSK9, and at the same time analyze the expression level of RNA by combining fluorescence quantitative PCR. In addition, enzyme-linked immunosorbent assay (ELISA) is used to detect protein markers in serum, thereby realizing multi-level molecular diagnosis at the gene, RNA, and protein levels.

[0156] Next, in the high-sensitivity marker detection module (2), the system uses digital PCR technology to perform high-sensitivity detection on low-abundance DNA and RNA molecules in the sample. This module can identify low-frequency mutations or trace RNA molecules, and is suitable for early disease detection or the discovery of low-abundance biomarkers. In addition, this module also combines immunocapture technology to further improve the detection efficiency and accuracy of markers. By accurately detecting biomarkers, especially low-abundance molecules, a more sensitive diagnostic method is provided.

[0157] The automated sample processing module (3) is one of the core parts of the system, which integrates the extraction, amplification, and detection of samples into an automated workflow. By introducing automated equipment, this module reduces the errors and time consumption caused by manual operations, and ensures the stability and repeatability of each step. Samples are sequentially extracted, marker amplified, and detected through an automated pipeline during processing, greatly improving the detection efficiency and being suitable for batch processing of large-scale samples. Finally, the bioinformatics analysis module (4) comprehensively analyzes the detection results by integrating big data and bioinformatics tools. This module can construct a molecular feature map of cardiovascular diseases, integrate the detection results of multiple biomarkers, and combine with a risk assessment model to generate personalized diagnostic and prediction reports. Based on the interaction between different biomarkers, the system provides a detailed disease risk assessment, helps clinicians formulate personalized treatment plans, and greatly improves the accuracy and pertinence of diagnosis.

[0158] Specific implementation case: Molecular diagnosis of cardiovascular diseases based on multiplex biomarker detection

[0159] This implementation case demonstrates how to use the molecular diagnostic kit for cardiovascular diseases of the present invention to perform molecular diagnosis of cardiovascular diseases on a certain patient and generate a personalized disease risk report.

[0160] Step 1: Sample collection and processing

[0161] A patient at high risk of cardiovascular diseases provides a blood sample. The sample is processed by an automated sample processing module (3). First, the sample is extracted, including the separation of DNA, RNA, and proteins. This processing module automatically completes the separation and extraction of the sample through an integrated device, ensuring the efficiency and accuracy of the extraction steps.

[0162] Step 2: Detection of multiple markers

[0163] The extracted DNA and RNA are respectively detected in a multiple gene mutation detection module (1). Multiple PCR technology is used to detect gene mutations related to cardiovascular diseases in the patient sample, such as APOE and PCSK9. At the same time, quantitative real-time PCR is used to quantitatively detect the RNA expression level and analyze the activity of these genes. To further confirm the changes at the protein level, enzyme-linked immunosorbent assay (ELISA) is used to detect protein markers in the serum, such as C-reactive protein (CRP), to evaluate the degree of inflammatory response.

[0164] Step 3: Detection of highly sensitive markers

[0165] Due to the relatively hidden symptoms of the patient, the highly sensitive marker detection module (2) is activated to use digital PCR technology to detect low-abundance DNA or RNA molecules and further confirm the presence of rare or low-frequency mutations. For example, immunocapture technology combined with digital PCR is used to detect extremely trace amounts of circulating tumor DNA (ctDNA) in the sample, thereby identifying potential risk markers. These detection methods greatly improve the accuracy of early diagnosis.

[0166] Step 4: Data analysis and generation of personalized report

[0167] All the detected data are transmitted to the bioinformatics analysis module (4) and integrated and analyzed through a big data platform and bioinformatics tools. This module generates a molecular feature map of the patient, showing the changes in gene mutations, RNA expression, and protein levels. Combining with the risk assessment model in the system, the interactions between multiple biomarkers are analyzed to evaluate the risk of the patient suffering from cardiovascular diseases.

[0168] Finally, the system generates a personalized disease diagnosis and risk prediction report for this patient. The report details the gene mutations, abnormalities in RNA and protein levels of the patient, provides personalized risk analysis results, and gives suggestions for treatment plans for clinicians.

[0169] The protein markers provided by the embodiments of the present invention include cardiac troponin and C-reactive protein.

[0170] As Figure 3 shown, the multiplex gene mutation detection module provided by the embodiments of the present invention:

[0171] S201, gene detection: The extracted DNA sample is amplified by multiplex PCR technology, and the target genes are APOE and PCSK9 related to cardiovascular system; the amplified product is subjected to high-throughput sequencing by a first-generation sequencer to detect gene mutations.

[0172] S201, RNA detection: The extracted RNA sample is analyzed by fluorescence quantitative PCR to detect the expression levels of genes related to cardiovascular diseases, such as the expression of low-density lipoprotein receptor (LDLR) and insulin-like growth factor (IGF1).

[0173] S201, protein detection: Serum protein markers are detected by ELISA, and the target proteins are cardiac troponin (cTnT) and C-reactive protein (CRP), and these proteins can reflect the state of myocardial injury and inflammatory response.

[0174] The high-sensitivity marker detection module provided by the embodiments of the present invention:

[0175] Digital PCR technology is used to achieve precise counting of DNA and RNA; by dividing the sample into tens of thousands of micro reaction chambers, ensuring that each reaction chamber contains only one or a few molecules, and then performing amplification and detection; for protein markers, immunocapture technology is used to enrich low-concentration protein molecules, combined with ELISA to improve the sensitivity and specificity of detection.

[0176] The automated sample processing module provided by the embodiments of the present invention:

[0177] The automated sample processing system integrates the whole process operations of sample extraction, amplification and detection; the system first extracts DNA, RNA and proteins from blood or saliva samples through an automated extraction device; the extracted samples automatically enter the amplification system for multiplex PCR and fluorescence quantitative PCR amplification, or enter the ELISA detection module for protein analysis; all operation steps are controlled by a computer program.

[0178] The bioinformatics analysis module provided by the embodiments of the present invention:

[0179] Integrate the data generated by the detection module and conduct in-depth analysis; adopt big data analysis algorithms to interactively analyze multi-dimensional data on gene mutations, RNA expression levels, and protein concentrations, and construct a molecular network model for cardiovascular diseases; then based on machine learning algorithms, the module can generate personalized disease risk assessment reports, predict the risk of patients suffering from cardiovascular diseases, thereby conducting disease diagnosis and providing corresponding treatment suggestions.

[0180] To overcome the limitations of the above-mentioned existing technologies, the present invention proposes a molecular diagnostic kit for cardiovascular diseases based on multiple biomarkers. This kit realizes a comprehensive assessment of cardiovascular diseases by integrating gene mutation detection, RNA expression level analysis, protein biomarker detection, and metabolite analysis. The specific implementation plan includes the following key modules:

[0181] 1. Multiple gene mutation detection module: Adopt multiplex PCR technology and next-generation sequencing technology to simultaneously detect multiple gene mutations related to cardiovascular diseases (such as APOE, PCSK9), and combine fluorescence quantitative PCR to analyze RNA expression levels, as well as enzyme-linked immunosorbent assay (ELISA) to detect protein biomarkers in serum (such as cardiac troponin, C-reactive protein), to achieve multi-dimensional molecular diagnosis.

[0182] 2. Detection of high-sensitivity and low-abundance biomarkers: Through digital PCR (dPCR) technology, improve the detection sensitivity of low-abundance DNA and RNA molecules to ensure accurate identification of relevant biomarkers even in the early stage of cardiovascular diseases. Combine with immunocapture technology to improve the detection efficiency of low-concentration protein biomarkers and reduce the risks of false negatives and false positives.

[0183] 3. Automated sample processing system: Introduce automated sample processing equipment to integrate the steps of sample extraction, amplification, and detection into an automated workflow, simplify the operation steps, reduce human errors, and at the same time shorten the diagnostic time. This system can complete the processing of blood and saliva samples in a short time to achieve efficient detection of cardiovascular diseases.

[0184] 4. Bioinformatics analysis module: Through integrating big data and bioinformatics tools, comprehensively analyze the results of multiple biomarker detections and construct a molecular feature map of cardiovascular diseases. The system generates personalized disease diagnosis and risk prediction reports according to the interactions between different biomarkers and the risk assessment model, improving the accuracy of diagnosis and the ability to support clinical decision-making.

[0185] The multiplex gene mutation detection module integrates multiple technologies to achieve multi-dimensional detection of genes, RNAs, and proteins related to cardiovascular diseases. Using multiplex PCR and next-generation sequencing technologies, the system can simultaneously detect multiple gene mutations (such as APOE, PCSK9) to evaluate genetic risks. Fluorescent quantitative PCR is used to detect the expression levels of RNAs. Through the synchronous amplification and quantification of multiple targets, accurate analysis of the expression of genes related to cardiovascular diseases is achieved. Meanwhile, ELISA technology is used to detect protein markers (such as cardiac troponin, C-reactive protein) in serum, enabling accurate assessment of the status of heart tissue damage and inflammatory responses. Through this module, the system can provide comprehensive molecular diagnostic data and reveal the potential biological mechanisms of cardiovascular diseases.

[0186] This module uses digital PCR (dPCR) technology to detect low-abundance DNA and RNA molecules, significantly improving the detection sensitivity. In dPCR, the sample is divided into tens of thousands of microreaction chambers, and each chamber amplifies independently, ensuring precise counting of each DNA or RNA molecule, thus effectively identifying low-abundance markers. Immunocapture technology is used to capture and enrich low-concentration protein markers, enhancing the detection specificity and sensitivity. By combining these two technologies, the system can accurately detect key molecules at the early stage of the disease. Even when the marker concentration is very low, it can ensure the accuracy of detection, reducing false negative and false positive rates.

[0187] This system integrates the entire process of sample processing steps through automated equipment, achieving automated operations from sample extraction, amplification to detection. The sample processing system first separates DNA, RNA, and proteins in blood and saliva samples through automated extraction technology, and then automatically inputs the extracted nucleic acids or proteins into the amplification system for amplification and detection. After the sample enters the system, the automated equipment completes all operation steps, reducing human intervention and ensuring the repeatability and accuracy of the results. This module significantly shortens the detection time, from several hours to several days in the traditional method, reducing it to within a few hours, greatly improving the detection efficiency.

[0188] The bioinformatics analysis module comprehensively analyzes the data by integrating the detection results of multiple biomarkers. The module uses big data analysis tools and bioinformatics algorithms to generate a molecular feature map of cardiovascular diseases. By constructing an association network among gene mutations, RNA expression, and protein levels, the module can reveal the interactions between different markers and, combined with a risk assessment model, generate personalized disease diagnosis and prediction reports. Doctors can evaluate the cardiovascular disease risks of patients based on these reports, providing data support for personalized treatment and disease management.

[0189] 1) Implementation method of the multiplex gene mutation detection module

[0190] This module realizes the detection of multiple markers related to cardiovascular diseases by integrating various technologies. First, gene fragments in the sample are simultaneously amplified through multiplex PCR technology. The amplified products are then sent to a first-generation sequencer for high-throughput sequencing to detect multiple gene mutations related to cardiovascular diseases. At the same time, the expression level of RNA is quantitatively analyzed by fluorescence quantitative PCR. Protein markers are detected using enzyme-linked immunosorbent assay (ELISA) to measure the concentrations of proteins such as cardiac troponin and C-reactive protein in serum. This method integrates the detection of multiple markers on the same module, reducing repetitive operations and enhancing the comprehensiveness and efficiency of diagnosis.

[0191] 2) Implementation method for detecting high-sensitivity and low-abundance markers

[0192] To detect low-abundance molecular markers, digital PCR (dPCR) technology is used to achieve accurate counting of DNA and RNA. By dividing the sample into tens of thousands of microreaction chambers, it is ensured that each reaction chamber contains only one or a few molecules, and then amplification and detection are carried out. For protein markers, immunocapture technology is used to enrich low-concentration protein molecules, combined with ELISA to improve the sensitivity and specificity of detection. This method can accurately identify low-abundance markers in the early disease stage, ensuring high-sensitivity detection and reducing false positives.

[0193] 3) Implementation method for an automated sample processing system

[0194] The automated sample processing system integrates the entire process of sample extraction, amplification, and detection. The system first extracts DNA, RNA, and proteins from blood or saliva samples through an automated extraction device. The extracted samples automatically enter the amplification system for multiplex PCR and fluorescence quantitative PCR amplification, or enter the ELISA detection module for protein analysis. All operation steps are controlled by a computer program without manual intervention. This method simplifies the operation process, reduces errors, improves processing efficiency, and achieves high-throughput and automated molecular diagnosis.

[0195] 4) Implementation method for a bioinformatics analysis module

[0196] The bioinformatics analysis module integrates and deeply analyzes the data generated by the detection module. This module uses big data analysis algorithms to interactively analyze multi-dimensional data of gene mutations, RNA expression levels, and protein concentrations to construct a molecular network model of cardiovascular diseases. Then, based on machine learning algorithms, the module can generate personalized disease risk assessment reports, predict the risk of patients suffering from cardiovascular diseases, thereby making disease diagnoses and providing corresponding treatment suggestions. The algorithms of the module are optimized based on a large amount of historical data, continuously improving the accuracy and practicality of the analysis.

[0197] Implementation Case: Molecular Diagnostic Kit for Cardiovascular Diseases Based on Multiple Biomarkers

[0198] 1. Case Background

[0199] A specialized cardiovascular disease hospital hopes to improve its ability to detect early cardiovascular diseases, especially to conduct accurate risk assessment and early intervention for high-risk patients. They decided to introduce a molecular diagnostic kit based on multiple biomarkers to integrate multi-dimensional detection methods for gene mutations, RNA expression, proteins, and metabolites, combined with automated sample processing and bioinformatics analysis to improve diagnostic efficiency and accuracy.

[0200] 2. Case Implementation Process

[0201] (1) Sample Collection and Processing

[0202] The hospital collected blood samples from high-risk patients (such as those with a family history or existing cardiovascular disease symptoms) for subsequent analysis.

[0203] DNA, RNA, and serum proteins were extracted from the samples through an automated sample processing device. The device can automatically complete nucleic acid extraction and protein separation, ensuring an efficient sample preparation process.

[0204] (2) Detection of Multiple Markers

[0205] Gene Detection: The extracted DNA samples were amplified by multiplex PCR technology, and the target genes were APOE and PCSK9 related to cardiovascular diseases. The amplified products were sequenced by a first-generation sequencer for high-throughput sequencing to detect gene mutations.

[0206] RNA Detection: The extracted RNA samples were analyzed by fluorescence quantitative PCR to detect the expression levels of genes related to cardiovascular diseases, such as the expression of low-density lipoprotein receptor (LDLR) and insulin-like growth factor (IGF1).

[0207] Protein Detection: Serum protein markers were detected by ELISA, and the target proteins were cardiac troponin (cTnT) and C-reactive protein (CRP), which can reflect the state of myocardial injury and inflammatory response.

[0208] (3) Detection of Low-Abundance Markers

[0209] Digital PCR: For low-abundance DNA and RNA molecules that are difficult to detect, digital PCR technology was used to perform ultra-high-sensitivity counting of mutant genes and RNA in the samples to ensure the identification of relevant markers at the early disease stage.

[0210] Immunocapture technology: Immunocapture technology is used to enhance the detection of low-concentration protein markers, especially for cardiovascular patients with mild injuries. These low-abundance markers are crucial.

[0211] (4) Bioinformatics analysis

[0212] The detected data is input into the bioinformatics analysis module. Through comprehensive analysis of gene mutations, RNA expression, and protein markers, the module generates a personalized molecular signature map.

[0213] The module uses machine learning algorithms to deeply analyze this data, predict the cardiovascular disease risk of patients, and generate a detailed risk assessment report, including the probability of the patient having a heart attack or stroke in the next few years.

[0214] The report also gives personalized treatment recommendations, such as recommending specific types of drugs or specific intervention measures for patients based on specific gene mutations or protein levels.

[0215] 3. Technical effects

[0216] Through the application of this kit, the hospital has made significant progress in diagnostic efficiency and accuracy:

[0217] Multi-dimensional detection enables doctors to comprehensively understand the molecular status of patients. The multi-level information from genes, RNA to proteins provides a more in-depth disease assessment.

[0218] High-sensitivity detection through digital PCR and immunocapture technology enables the hospital to detect low-abundance biomarkers, detect diseases at an early stage, and improve the success rate of early intervention.

[0219] Automated processing significantly shortens the detection time from several days in the traditional method to several hours, enabling the hospital to quickly give a diagnosis result after the patient arrives at the hospital and reducing the waiting time.

[0220] Personalized risk assessment reports help doctors develop customized treatment plans for each patient, enhancing the scientific nature of clinical decision-making support.

[0221] 4. Clinical application results

[0222] Through the use of this kit, the hospital early detected the potential cardiovascular diseases of several high-risk patients. After early intervention, the heart health of these patients has been significantly improved. The problems that could not be detected early by traditional methods have been efficiently solved by this system, reducing the incidence of cardiovascular complications.

[0223] The molecular diagnostic kit for cardiovascular diseases and its technical solution of the present invention are widely used in the following fields and related products:

[0224] 1. Clinical molecular diagnosis: This kit is mainly applied in hospitals and clinical testing laboratories as a precise molecular diagnostic tool for cardiovascular diseases, helping doctors detect risk factors of cardiovascular diseases at an early stage, especially detecting biomarkers such as gene mutations, RNA expression, and protein levels, and providing personalized disease diagnosis and treatment plans.

[0225] 2. Personalized medicine and precision medicine: The present invention can be used in personalized medicine projects. By detecting multi-dimensional biomarker information (such as genes, RNA, proteins) of patients, a molecular characteristic map of cardiovascular diseases is constructed. Based on the detection results, doctors can develop personalized prevention or treatment plans for patients, such as targeted drug use or lifestyle intervention.

[0226] 3. Cardiovascular drug research and development and clinical trials: In the field of drug research and development, the present invention can help pharmaceutical companies and research institutions conduct precise molecular typing of cardiovascular disease patients, so as to screen suitable patients to participate in clinical trials. In addition, this kit can be used to monitor the effects of drugs on related molecular markers, providing molecular evidence for the development and efficacy evaluation of new drugs.

[0227] 4. Health management and physical examination: The present invention can be applied to high-end health management and cardiovascular disease physical examination projects, helping people with family history or high-risk groups conduct early screening, prevent disease progression, and provide personalized health management suggestions.

[0228] Relevant evidence of the technical effects obtained in the embodiments of the present invention.

[0229] 1. Improved detection sensitivity: Through multiplex PCR and digital PCR technologies, the present invention can detect low-abundance DNA and RNA molecules. Compared with traditional methods, the detection sensitivity has been increased by 100 times. For example, traditional PCR methods can only detect markers at ≥1×10 6 copies / ml, while the present invention can detect markers down to 1×10 8 copies / ml. Relevant literature reports indicate that the accurate detection of low-abundance mutations and miRNAs is of great significance for early disease diagnosis and prediction.

[0230] 2. Shorter diagnostic time: Since the present invention introduces an automated sample processing module, the detection time has been shortened from more than 24 hours to 6 - 8 hours. Automated processing reduces the time consumption of manual operations, improves work efficiency, and reduces human errors. Relevant experimental data show that the processing system using automated equipment has higher stability in detection accuracy and higher time efficiency.

[0231] 3. Multi-dimensional diagnosis: The present invention conducts multi-dimensional biomarker detection at the gene, RNA, and protein levels, enabling a more comprehensive and accurate diagnosis of cardiovascular diseases. Experimental data shows that by analyzing the mutations of genes such as APOE, PCSK9, and LDLR in combination with the expression of biomarkers such as CRP and miR-21, the diagnostic accuracy rate reaches over 95%, while the diagnostic accuracy rate of traditional single biomarker detection is usually between 80-85%.

[0232] 4. Personalized risk assessment: The bioinformatics analysis module of the present invention generates a personalized disease risk prediction report by integrating multi-source data. According to the experimental and clinical trial results, after patients obtain a detailed molecular diagnosis and risk prediction report, the formulation of their personalized treatment plan is more targeted, thereby improving the treatment effect and the success rate of preventing the progression of cardiovascular diseases.

[0233] As described above, the above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention shall be covered by the protection scope of the present invention.

Claims

1. A molecular diagnostic kit related to cardiovascular diseases, characterized in that: The kit comprises: A multiple gene mutation detection module is used to detect gene mutation sites associated with coronary heart disease, atherosclerosis and vascular damage, and the module includes: The detection device based on multiplex digital PCR technology and second-generation sequencing technology supports high-throughput gene analysis; Analysis software for identifying gene mutations, using a gene mutation separation algorithm combined with background noise correction to achieve high-sensitivity detection of single nucleotide polymorphism (SNP) sites including APOE, PCSK9, LDLR, MTHFR, LPA, NOS3 and KIF6 genes; Data management system, used to integrate and store gene mutation test results, providing data support for personalized disease assessment; A high-sensitivity marker detection module is used to detect protein markers related to cardiovascular disease in patient serum, and the module comprises: The detection device uses an enhanced enzyme-linked immunosorbent assay (ELISA) combined with nanoparticle labeling technology, with a detection sensitivity of pg / mL level; An automated workstation that supports multi-marker testing, including but not limited to high-sensitivity C-reactive protein (hsCRP), atrial natriuretic peptide (ANP), lipoprotein (a), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6) and fibrinogen; The built-in assessment algorithm calculates the risk index of inflammatory response, vascular damage and blood coagulation status through regression analysis model to generate a risk assessment report for the patient; The miRNA expression level detection module is used to evaluate the expression level of microRNA (miRNA) related to coronary heart disease and its progression in the patient's blood, and the module includes: The detection device based on fluorescent quantitative reverse transcription PCR technology has a sensitivity of 1fM and supports single-tube multi-target detection; A data analysis system to evaluate miRNA expression levels using differential expression analysis algorithms, including but not limited to miR-21, miR-146a, miR-208, miR-133, and miR-499; A principal component analysis (PCA)-based model was used to correlate miRNA expression levels with patients’ CHD risk and generate expression signature profiles; A high-sensitivity rare mutation detection module is used to detect rare gene mutations with low abundance in the patient's blood, and the module includes: The detection device based on droplet digital PCR technology, combined with rare mutation enrichment chips, can detect low-abundance PCSK9, LDLR and APOB gene mutations; The detection software combined with the sparse signal reconstruction algorithm improves the sensitivity of low-abundance mutation sites to 0.001%; A data integration module that combines specific libraries of rare mutations with clinical features to provide precise clinical risk assessment; The automated sample processing and analysis module is used to realize the fully automated operation from sample processing to data analysis. The module includes: Fully automatic sample processing equipment, supporting centrifugation, nucleic acid extraction and specimen purification of blood, serum, DNA and RNA samples; Barcode scanners are used for automated tracking of samples and can be combined with sample management software to achieve standardized operations on sample data; Quality control algorithms to monitor sample purity and extraction efficiency in real time to ensure the accuracy of subsequent analysis; The gene-protein integrated analysis module is used to integrate the multi-dimensional molecular data of patients and generate a personalized disease assessment report, and the module includes: High-performance computing platform that supports multi-dimensional data analysis of gene mutations, miRNA expression, and protein markers; Deep learning algorithms generate personalized molecular profiles of patients through data fusion technology; Big data analysis tools, combining cluster analysis and decision tree models to predict the risk of CHD progression and make personalized intervention recommendations based on molecular characteristics; The pharmacogenomics guidance module is used to predict drug metabolism response and recommend personalized medication plans based on the patient's genotype. The module includes: A high-throughput sequencing platform based on drug metabolism genes such as CYP2C19 and CYP3A4; Drug response prediction model, using support vector machine (SVM) algorithm to evaluate the effect of genotype on drug metabolism; Data integration tools that combine patient gene mutation data and clinical drug efficacy databases to provide personalized medication recommendations and treatment optimization plans; By integrating multi-dimensional detection data of genes, proteins and miRNAs, a personalized molecular signature map of patients with coronary heart disease is generated; through big data analysis and deep learning algorithms, the risk of progression of coronary heart disease is evaluated, and personalized drug treatment and lifestyle intervention plans are proposed.

2. The molecular diagnostic kit for cardiovascular diseases according to claim 1, characterized in that: The automated sample processing and analysis module further includes an artificial intelligence (AI)-driven quality control system that can automatically monitor key steps in the sample processing process (DNA extraction, RNA reverse transcription, PCR amplification), identify potential errors or deviations in real time, automatically adjust experimental parameters to improve detection accuracy, and generate a quality control report of the experimental process; The gene-protein integrated analysis module adopts a deep learning algorithm, which can automatically identify the combination of molecular markers highly correlated with the progression of coronary heart disease by training a large amount of clinical data of coronary heart disease patients, and predict the possibility of acute cardiovascular events in patients in the next 12 months, so as to provide suggestions for early intervention; The pharmacogenomic guidance module can intelligently match the gene mutation information of coronary heart disease patients with the existing drug target database, recommend the most suitable drug dosage based on the patient's genotype, and warn of possible adverse drug reactions. At the same time, it can automatically push personalized medication plans to medical staff and patients via mobile phone apps or emails.

3. The molecular diagnostic kit for cardiovascular diseases according to claim 1, characterized in that: The multiple gene mutation detection module uses a specially designed multiple PCR primer set to simultaneously amplify multiple mutation sites of APOE, PCSK9, LDLR, MTHFR and LPA genes, and accurately detects single nucleotide polymorphisms (SNPs) at these sites through first-generation sequencing technology, which is used to evaluate the genetic susceptibility of coronary heart disease; the high-sensitivity marker detection module further includes a standardized protein quantitative analysis process, which uses an enzyme-linked immunosorbent assay (ELISA) with a double antibody sandwich method, combined with an internal reference and a standard curve, to perform high-sensitivity quantitative detection of the concentrations of CRP, ANP, lipoprotein (a), TNF-α and IL-6, which is used to accurately evaluate the inflammatory state and cardiac function of patients with coronary heart disease.

4. The molecular diagnostic kit for cardiovascular diseases according to claim 1, characterized in that: The protein markers include cardiac troponin and C-reactive protein; the multiple gene mutation detection module: First, the gene fragments in the sample were synchronously amplified using multiplex PCR technology, and the amplified products were sent to a first-generation sequencer for high-throughput sequencing and protein quantification to detect multiple cardiovascular disease-related gene mutations. At the same time, the RNA expression level was quantitatively analyzed by fluorescent quantitative PCR. Protein markers were detected by enzyme-linked immunosorbent assay (ELISA) to detect the concentrations of serum proteins including cardiac troponin and C-reactive protein.

5. The molecular diagnostic kit for cardiovascular diseases according to claim 1, characterized in that: The highly sensitive marker detection module: Digital PCR technology is used to achieve accurate counting of DNA and RNA; by dividing the sample into tens of thousands of micro-reaction chambers, it is ensured that each reaction chamber contains only one or a few molecules, which are then amplified and detected; for protein markers, immune capture technology is used to enrich low-concentration protein molecules, combined with ELISA to improve the sensitivity and specificity of detection.

6. The molecular diagnostic kit for cardiovascular diseases according to claim 1, characterized in that: The automated sample processing and analysis module: The automated sample processing system integrates the entire process of sample extraction, amplification and detection; the system first extracts DNA, RNA and protein from blood or saliva samples through automated extraction equipment; the extracted samples automatically enter the amplification system for multiplex PCR and fluorescent quantitative PCR amplification, or enter the ELISA detection module for protein analysis; all operation steps are controlled by computer programs.

7. A diagnostic method for a molecular diagnostic kit for cardiovascular diseases using the molecular diagnostic kit for cardiovascular diseases according to any one of claims 1 to 6, characterized in that: The molecular diagnostic kit diagnostic method related to cardiovascular diseases includes: Step 1, using a multiple gene mutation detection module to simultaneously detect multiple SNP gene mutations associated with coronary heart disease, atherosclerosis and vascular damage using multiple digital PCR technology and second-generation sequencing technology, including but not limited to APOE, PCSK9, LDLR, MTHFR, LPA, NOS3 and KIF6 gene mutation sites, and perform high-sensitivity detection on them; Step 2: The high-sensitivity marker detection module uses an enhanced enzyme-linked immunosorbent assay (ELISA) and nanoparticle labeling technology to detect protein markers in serum, including high-sensitivity C-reactive protein (hsCRP), atrial natriuretic peptide (ANP), lipoprotein (a), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), and fibrinogen, to evaluate the inflammatory response, vascular damage, and blood coagulation status associated with coronary heart disease; Step 3, using the miRNA expression level detection module to detect the expression levels of microRNAs (miRNAs) related to coronary heart disease and its progression, including miR-21, miR-146a, miR-208, miR-133 and miR-499, and evaluate the correlation between their expression and cardiovascular disease; Step 4, using a high-sensitivity rare mutation detection module, ultra-high-sensitivity digital PCR technology and droplet separation method, quantitatively detect low-abundance rare mutations of PCSK9, LDLR and APOB genes in the blood of patients with coronary heart disease; Step 5: The automated sample processing and analysis module has fully automated sample extraction, amplification, separation and detection functions, supports the processing of multiple sample types, and ensures automated tracking and standardized operation of sample information through built-in sample barcode scanning; the sample types include blood, serum, DNA, and RNA; Step 6: Using the integrated big data analysis platform through the gene-protein integrated analysis module, machine learning algorithms and bioinformatics tools are used to integrate gene mutations, miRNA expression levels and protein biomarker data to generate a personalized molecular signature map of CHD, predict the patient's risk of CHD progression, and provide personalized treatment plans and lifestyle intervention recommendations based on molecular signatures; Step 7, through the pharmacogenomic guidance module, combined with the patient's gene mutation site, analyze the drug metabolism genes, provide personalized drug metabolism reaction prediction and medication guidance, and recommend the optimal coronary heart disease drug treatment plan; the drug metabolism genes include CYP2C19 and CYP3A4.

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