A hypertension early warning model, product, computer readable storage medium and application thereof

Abstract

The application discloses a hypertension early warning model, product, computer readable storage medium and application thereof, and relates to the technical field of biomedical detection. The hypertension early warning or diagnosis marker comprises rs2106809, rs699, rs671 and rs1799983, and the hypertension risk early warning or diagnosis is carried out according to the genotype information of rs2106809, rs699, rs671 and rs1799983 of a sample. The application further constructs an early warning model capable of predicting hypertension. The early warning model can carry out the hypertension risk early warning or diagnosis based on the genotype information of rs2106809, rs699, rs671 and rs1799983. In addition, the early warning model can also combine the data of multiple dimensions such as genes, pulse and BMI, and has the characteristics of low cost, easy acquisition of indexes, comprehensive prediction ability, high accuracy of early warning or diagnosis results and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biomedical detection, in particular to a hypertension early warning model, a product, a computer readable storage medium and an application thereof. BACKGROUND

[0002] As a common chronic disease, hypertension has long been a focus of global health research. It is not only a major risk factor for cardiovascular and cerebrovascular diseases, but also has a direct correlation with many other serious health problems, such as kidney disease, retinopathy, and many metabolic diseases. Due to the complex pathogenesis of hypertension, which involves the interaction of multiple genetic and environmental factors, the study of its etiology has always been a hot spot in medical research.

[0003] In the field of hypertension research, Whole Genome Sequencing (WGS) technology has become a powerful tool for identifying genetic factors associated with the disease. This method not only covers the coding and non-coding regions of the entire genome, but also identifies rare and low-frequency variants, providing a new perspective for the genetic study of hypertension.

[0004] Recent studies using WGS technology have discovered several new genetic loci associated with hypertension. For example, a study by Ehret GB et al. published in the journal Nature Genetics identified new genetic loci CYP17A1 (located at 8q24.2) and NPR3-C5orf23 (located at 5q21.3) significantly associated with hypertension by whole genome sequencing of thousands of hypertension patients. The discovery of these loci not only increases our understanding of the genetic basis of hypertension, but also points to new disease mechanisms and potential therapeutic targets.

[0005] In addition, a study by Warren HR et al. published in Nature Communications analyzed a population of hypertension patients from different ethnic backgrounds using WGS technology and discovered multiple rare variants associated with hypertension, including variants in the PLCE1 (located at 10q23.33) and CACNA1D (located at 3p21.1) genes. These studies reveal the potential role of rare variants in the pathogenesis of hypertension and provide new clues for individualized treatment of hypertension.

[0006] These WGS-based studies not only demonstrate the great potential of high-throughput sequencing technology in the genetic study of complex diseases, but also provide valuable information about the genetic susceptibility of hypertension. By carefully analyzing these genetic loci and variants associated with hypertension, researchers can better understand the mechanisms of the disease and develop more precise prevention and treatment strategies, bringing hope to patients with hypertension.

[0007] Although some progress has been made in hypertension risk prediction technology, there are still some objective shortcomings and limitations:

[0008] (1) Risk assessment based on traditional biomarkers: These methods mainly rely on traditional biomarkers such as blood pressure measurement, blood lipid levels, and body mass index (BMI) to assess the risk of hypertension. Although these methods are widely used in clinical practice, they cannot fully reflect the individual's genetic susceptibility and are therefore limited in accuracy and early risk prediction.

[0009] (2) Genome-wide association study (GWAS): GWAS technology assesses risk by identifying common genetic variants (i.e., polymorphic sites) associated with the disease. However, this approach focuses primarily on frequently occurring genetic variants and may overlook the role of rare variants, which may have a significant impact on the risk of hypertension in some individuals.

[0010] (3) Gene panel-based testing: Gene panel testing assesses risk by analyzing a group of genes known to be associated with hypertension. Although this method is more accurate in detecting specific gene variants, it is limited in that it can only detect a small number of known gene variants associated with hypertension and may miss other unknown important genetic factors.

[0011] (4) Whole exome sequencing (WES): Although WES technology can detect genetic variations within coding regions, it is unable to detect variations in non-coding regions (such as regulatory sequences) that may affect disease risk. Therefore, its predictive ability may not be as comprehensive as whole genome sequencing.

[0012] In view of this, the present invention is proposed. Summary of the Invention

[0013] The purpose of the present invention is to provide a hypertension early warning model, product, computer-readable storage medium and its application to improve the comprehensiveness of prediction capabilities and thus improve the accuracy of early warning of hypertension.

[0014] The present invention is achieved in that:

[0015] In the first aspect, the present invention provides an application of a detection reagent for a hypertension warning or diagnostic marker in the preparation of a hypertension warning or diagnostic product, wherein the hypertension warning or diagnostic markers include rs2106809, rs699, rs671 and rs1799983, and hypertension risk warning or diagnosis is performed based on the genotype information of sample rs2106809, rs699, rs671 and rs1799983.

[0016] In a second aspect, the present application provides a product for hypertension early warning or diagnosis, the product comprising the detection reagent of the hypertension early warning or diagnosis marker described above.

[0017] In a third aspect, the present application provides a model for hypertension risk early warning or diagnosis, the model using the following regression equation to calculate a risk score: risk score y = -0.11805319 * rs2106809 - 0.39629604 * rs699 + 0.02177215 * rs671 + 0.03985716 * rs1799983 - 0.1326726 * Pulse - 0.2147923 * BMI + 1.42201697.

[0018] The risk score has a value between 0 and 1; wherein the genotype information has a value between 0 and 1, and has a value of 0.5 when the gene locus is heterozygous, has a value of 1 when it is homozygous mutation, and has a value of 0 when it is wild type homozygous mutation.

[0019] The Pulse and BMI values in the model are the values of the Pulse and BMI values of the sample after standardization, and the values of Pulse and BMI after standardization are both between 0 and 1.

[0020] In a fourth aspect, the present application provides a device or system for hypertension risk early warning or diagnosis, the device or system comprising:

[0021] A data acquisition module for acquiring genotype information of a hypertension early warning or diagnosis marker in a sample of a subject to be tested; or acquiring genotype information of the hypertension early warning or diagnosis marker and pulse and body mass index described above;

[0022] An early warning module for providing the genotype information of the hypertension early warning or diagnosis marker obtained by the data acquisition module, or the genotype information, pulse and body mass index as input data to the trained early warning model, the early warning model being trained to early warn or diagnose the hypertension risk of the subject based on the genotype information of the hypertension early warning or diagnosis marker and the pulse and body mass index of the subject.

[0023] A result acquisition module for acquiring the output result of the early warning model in the early warning module to obtain the early warning result of the subject; the early warning logistic regression model; and the early warning model is the model for hypertension risk early warning or diagnosis described above.

[0024] In a fifth aspect, the present application provides a computer device, the computer device comprising a memory and a processor, the memory storing a program, and the processor implementing the following method when executing the program:

[0025] obtaining genotype information of a high blood pressure early warning or diagnosis marker in a sample of a subject to be tested; or obtaining the genotype information of the high blood pressure early warning or diagnosis marker, Pulse and BMI;

[0026] providing the obtained genotype information of the high blood pressure early warning or diagnosis marker, or the genotype information, Pulse and BMI as input data to the trained model, and the model is trained to early warn or diagnose the high blood pressure risk of the subject based on the genotype information of the high blood pressure early warning or diagnosis marker, Pulse and BMI of the subject;

[0027] obtaining an output result of the model to obtain an early warning result of the subject; the model is a logistic regression model.

[0028] In a sixth aspect, the present application provides a computer readable storage medium, which comprises a stored computer program; wherein the computer readable storage medium is controlled to implement the above method when the computer program is run.

[0029] The present application has the following beneficial effects:

[0030] The present application has screened and newly discovered biomarkers rs2106809, rs699, rs671 and rs1799983 that can be used to evaluate the risk of high blood pressure, and by detecting the genotype information of rs2106809, rs699, rs671 and rs1799983 in a sample, the sample is determined to have a high blood pressure risk or to have high blood pressure according to the genotype information.

[0031] The present application also constructs an early warning model capable of predicting high blood pressure, which can early warn or diagnose the risk of high blood pressure based on the genotype information of rs2106809, rs699, rs671 and rs1799983, and in addition, can also combine the data of multiple dimensions such as genes, pulse, BMI, etc., and has the characteristics of low cost, easy to obtain indicators, comprehensive prediction ability, high accuracy of early warning or diagnosis results, etc. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be considered as limiting the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0033] Figure 1 ROC curve graph of Example 2;

[0034] Figure 2ROC curve plot for marker rs2106809 detected by WGS detection primers for experimental example 1 (4 SNP loci);

[0035] Figure 3 ROC curve plot for marker rs699 detected by WGS detection primers;

[0036] Figure 4 ROC curve plot for marker rs671 detected by WGS detection primers;

[0037] Figure 5 ROC curve plot for marker rs1799983 detected by WGS detection primers;

[0038] Figure 6 ROC curve plot for marker rs2106809 detected by qPCR detection primers;

[0039] Figure 7 ROC curve plot for marker rs699 detected by qPCR detection primers;

[0040] Figure 8 ROC curve plot for marker rs671 detected by qPCR detection primers;

[0041] Figure 9 ROC curve plot for marker rs1799983 detected by qPCR detection primers.

[0042] Figure 10 ROC curve plot for marker rs1799983 detected by qPCR detection primers.DETAILED DESCRIPTION

[0043] Reference will now be made in detail to embodiments of the application, one or more examples of which are set forth below. Each example is provided as an explanation and not as a limitation of the application. Indeed, it will be apparent to one of ordinary skill in the art that numerous modifications and variations of the present application are possible in light of the above teachings. For example, features described or illustrated as part of one embodiment can be used with another embodiment to yield still a further embodiment.

[0044] The practice of the present application will employ, unless otherwise indicated, conventional techniques of cell biology, molecular biology (including recombinant techniques), microbiology, biochemistry and immunology, which are within the skill of the art. Such techniques are explained fully in the literature, such as Molecular Cloning: A Laboratory Manual, Second Edition (Sambrook et al., 1989); Oligonucleotide Synthesis (M. J. Gait, ed., 1984); Animal Cell Culture (R. I. Freshney, ed., 1987); Methods in Enzymology (Academic Press, Inc.); Handbook of Experimental Immunology (D. M. Weir and C. C. Blackwell, eds.); Gene Transfer Vectors for Mammalian Cells (J. M. Miller and M. P. Calos, eds., 1987); Current Protocols in Molecular Biology (F. M. Ausubel et al., eds., 1987); PCR: The Polymerase Chain Reaction (Mullis et al., eds., 1994); and Current Protocols in Immunology (J. E. Coligan et al., eds., 1991), each of which is incorporated herein by reference.

[0045] In a first aspect, the present application provides a use of a detection reagent of a hypertension early warning or diagnosis marker in the preparation of a hypertension early warning or diagnosis product, the hypertension early warning or diagnosis marker comprising rs2106809, rs699, rs671 and rs1799983, and the early warning or diagnosis of hypertension risk is based on the genotype information of rs2106809, rs699, rs671 and rs1799983 of the sample.

[0046] By detecting the genotype of the marker, the risk of hypertension can be accurately warned and diagnosed, and the index is easy to obtain and has low detection cost.

[0047] The marker information of rs2106809 is as follows:

[0048] chrX: 15599938 - NG_012575.2: g.7221T>G - ACE2 - rs2106809;

[0049] Marker information of rs699 is as follows:

[0050] chr1: 230710048 - NG_008836.2: g.9543T>C - AGT - rs699;

[0051] Marker information of rs671 is as follows:

[0052] chr12: 111803962 - NP_000681.2: p.Glu504Lys - ALDH2 - rs671;

[0053] Marker information of rs1799983 is as follows:

[0054] chr7: 150999023 - NC_000007.14: g.150999023T>G - NOS3 - rs1799983.

[0055] Simultaneous detection of genotype information of rs2106809, rs699, rs671 and rs1799983 markers can obtain more comprehensive mutation information, so as to more accurately evaluate the risk of hypertension.

[0056] The method for early warning or diagnosis of hypertension risk is as follows: constructing a model for early warning or diagnosis of hypertension risk according to genotype information of rs2106809, rs699, rs671 and rs1799983 and hypertension risk; assigning genotype information of rs2106809, rs699, rs671 and rs1799983 of the sample to be tested, inputting the assignment into the model for early warning or diagnosis of hypertension risk, and early warning or diagnosing the sample according to the output result of the model for early warning or diagnosis of hypertension risk.

[0057] In a preferred embodiment of the application, the detection reagent is a reagent for detecting the genotype of the hypertension early warning or diagnosis marker in the sample by polymerase chain reaction, real-time fluorescent quantitative polymerase chain reaction, and / or nucleic acid mass spectrometry method.

[0058] In a preferred embodiment of the application, the detection reagent is a primer and / or a probe. For example, a detection primer or probe covering the above marker site is designed.

[0059] In a preferred embodiment of the application, the hypertension early warning or diagnosis product is at least one of a primer, a probe, a kit, a chip, a sequencing library, and a membrane strip.

[0060] Preferably, when the high blood pressure early warning or diagnosis product is a primer, the nucleotide sequence of the primer for detecting rs2106809 is shown as SEQ ID NO: 1-2; the SNP site of rs2106809 is: chrX: 15599938-NG_012575.2: g.7221T>G.

[0061]

[0062] The primer sequence for detecting rs699 is as follows: the nucleotide sequence of the primer pair is shown as SEQ ID NO: 3-4; the SNP site of rs699 is: chr1: 230710048-NG_008836.2: g.9543T>C.

[0063] The primer sequence for detecting rs699 is as follows:

[0064]

[0065] The primer sequence for detecting rs671 is as follows: the nucleotide sequence of the primer pair is shown as SEQ ID NO: 5-6; the marker information of rs671 is: chr12: 111803962-NP_000681.2: p.Glu504Lys.

[0066] The primer sequence for detecting rs671 is as follows:

[0067]

[0068] The primer sequence for detecting rs1799983 is as follows: the nucleotide sequence of the primer pair is shown as SEQ ID NO: 7-8; the SNP site of rs1799983 is: chr7: 150999023-NC_000007.14: g.150999023T>G.

[0069] The primer sequence for detecting rs1799983 is as follows:

[0070]

[0071] In a preferred embodiment of the application, when the high blood pressure early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs2106809 is shown as SEQ ID NO: 9;

[0072] When the high blood pressure early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs699 is shown as SEQ ID NO: 10;

[0073] When the hypertension early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs671 is shown as SEQ ID NO: 11.

[0074] When the hypertension early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs1799983 is shown as SEQ ID NO: 12.

[0075] In order to further improve the accuracy of the hypertension risk early warning, in the preferred embodiment of the application, the hypertension early warning or diagnosis marker further comprises pulse (Pulse) and body mass index (BMI). By comprehensively combining the genotype information and the Pulse and BMI multi-dimensional data, the accuracy of the hypertension risk early warning can be further improved. The above-mentioned various indexes are easy to obtain and low in cost.

[0076] The method for the hypertension risk early warning or diagnosis is as follows: constructing a hypertension risk early warning or diagnosis model according to the genotype information of rs2106809, rs699, rs671 and rs1799983, Pulse and BMI and the hypertension risk; assigning the genotype information of rs2106809, rs699, rs671 and rs1799983 of the sample to be tested, and assigning the Pulse and BMI of the sample to be tested; inputting the genotype information assignment, the Pulse and BMI assignment into the hypertension risk early warning or diagnosis model; and performing the hypertension risk early warning or diagnosis on the sample according to the output result of the hypertension risk early warning or diagnosis model.

[0077] In the preferred embodiment of the application, the model uses the following regression equation to calculate the risk score:

[0078] y = -0.11805319 * rs2106809 - 0.39629604 * rs699 + 0.02177215 * rs671 + 0.03985716 * rs1799983 - 0.1326726 * Pulse - 0.2147923 * BMI + 1.42201697; the risk score is valued between 0 and 1; wherein the genotype information assignment range is between 0 and 1, the value is 0.5 when the genotype is heterozygous, the value is 1 when the genotype is homozygous mutation, and the value is 0 when the genotype is wild type homozygous mutation;

[0079] The Pulse and BMI values in the model are the values after standardizing the Pulse and BMI values of the sample, and the values after standardizing the Pulse and BMI are both between 0 and 1.

[0080] In a preferred embodiment of the present invention, when the risk score is less than 0.33, it is low risk; when the risk score is between 0.33-0.85, it is medium risk; when the risk score is greater than 0.85, it is high risk.

[0081] In a second aspect, the present invention provides a product for early warning or diagnosis of hypertension, which includes a detection reagent for the above-mentioned hypertension early warning or diagnosis marker.

[0082] In a preferred embodiment of the present invention, the product is at least one of a primer, a probe, a kit, a chip, a sequencing library and a membrane strip.

[0083] The above products are primers; the primer sequences for detecting rs2106809 are as follows: the nucleotide sequences of the primer pair are shown in SEQ ID NO: 1-2; the SNP site of rs2106809 is: chrX: 15599938-NG_012575.2: g.7221T>G.

[0084]

[0085]

[0086] The primer sequences for detecting rs699 are as follows: the nucleotide sequences of the primer pair are shown in SEQ ID NOs: 3-4; the SNP site of rs699 is: chr1: 230710048-NG_008836.2: g.9543T>C.

[0087] The primer sequences for detecting rs699 are as follows:

[0088]

[0089] The primer sequences for detecting rs671 are as follows: the nucleotide sequences of the primer pairs are shown in SEQ ID NOs: 5-6; the marker information for rs671 is:

[0090] chr12:111803962-NP_000681.2:p.Glu504Lys.

[0091] The primer sequences for detecting rs671 are as follows:

[0092]

[0093] The primer sequence for detecting rs1799983 is as follows: the nucleotide sequence of the primer pair is shown in SEQ ID NO: 7-8; the SNP site of rs1799983 is: chr7: 150999023-NC_000007.14: g.150999023T>G.

[0094] The primer sequence for detecting rs1799983 is as follows:

[0095]

[0096] When the hypertension early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs2106809 is shown in SEQ ID NO: 9;

[0097] When the hypertension early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs699 is shown in SEQ ID NO: 10;

[0098] When the hypertension early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs671 is shown in SEQ ID NO: 11;

[0099] When the hypertension early warning or diagnosis product is a probe, the nucleotide sequence of the probe for detecting rs1799983 is shown in SEQ ID NO: 12.

[0100] When the product is a primer and / or a probe, the form of the product includes, but is not limited to, a freeze-dried powder, a liquid, etc. When the product is a kit, the kit further includes an amplification buffer, a solvent, a washing liquid (or a rinsing liquid), a developing liquid, a termination liquid, etc.

[0101] In a third aspect, the present application provides a model for early warning or diagnosis of hypertension risk, which calculates a risk score by using the following regression equation: risk score y = -0.11805319*rs2106809-0.39629604*rs699+0.02177215*rs671+0.03985716*rs1799983-0.1326726*Pulse-0.2147923*BMI+1.42201697;

[0102] The value of the risk score is between 0 and 1; wherein the value of the genotype information is between 0 and 1, the value is 0.5 when the gene locus is heterozygous, the value is 1 when it is homozygous mutation, and the value is 0 when it is wild type homozygous mutation;

[0103] The Pulse and BMI values in the model are the values of the Pulse and BMI values of the sample after standardization, and the values of Pulse and BMI after standardization are both between 0 and 1;

[0104] Preferably, when the risk score is less than 0.33, it is low risk, when the risk score is between 0.33-0.85, it is medium risk, and when the risk score is greater than 0.85, it is high risk.

[0105] In a fourth aspect, the present application provides a device or system for high blood pressure risk warning or diagnosis, the device or system comprising:

[0106] a data acquisition module for acquiring genotype information of a high blood pressure warning or diagnosis marker in a sample of a subject to be tested; or acquiring genotype information of the high blood pressure warning or diagnosis marker and pulse and body mass index;

[0107] a warning module for providing the genotype information of the high blood pressure warning or diagnosis marker obtained by the data acquisition module, or the genotype information, pulse and body mass index as input data to a trained warning model, the warning model being trained to warn or diagnose the high blood pressure risk of the subject based on the genotype information of the high blood pressure warning or diagnosis marker and the pulse and body mass index of the subject;

[0108] a result acquisition module for acquiring the output result of the warning model in the warning module to obtain the warning result of the subject; the warning model is a logistic regression model; the warning model is the model for high blood pressure risk warning or diagnosis described above.

[0109] In a fifth aspect, the present application provides a computer device, the computer device comprising a memory and a processor, the memory storing a program, and the processor implementing the following method when executing the program:

[0110] acquiring genotype information of a high blood pressure warning or diagnosis marker in a sample of a subject to be tested; or acquiring genotype information of the high blood pressure warning or diagnosis marker and pulse and body mass index;

[0111] providing the genotype information of the high blood pressure warning or diagnosis marker obtained by the data acquisition module, or the genotype information, pulse and body mass index as input data to a trained warning model, the warning model being trained to warn or diagnose the high blood pressure risk of the subject based on the genotype information of the high blood pressure warning or diagnosis marker and the pulse and body mass index of the subject;

[0112] acquiring the output result of the warning model in the warning module to obtain the warning result of the subject; the warning model is a logistic regression model; the warning model is the model for high blood pressure risk warning or diagnosis described above.

[0113] Specifically, the computer device includes a memory, a processor, a bus and a communication interface, which are directly or indirectly electrically connected with each other to realize the transmission or interaction of data. For example, these elements can be electrically connected with each other through one or more buses or signal lines. The processor can process information and / or data related to target identification to execute one or more functions described in the present application.

[0114] The memory can be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) and the like.

[0115] The processor can be an integrated circuit chip with a signal processing capability. The processor can be a general purpose processor, including a central processing unit (CPU), a network processor (NP) and the like; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0116] In a sixth aspect, the present application provides a computer readable storage medium, which includes a stored computer program; wherein the computer readable storage medium realizes the above method when the computer program runs.

[0117] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below. If no specific conditions are specified in the embodiments, the conventional conditions or the conditions recommended by the manufacturers are adopted. If no manufacturer of the reagents or instruments is specified, the conventional products that can be purchased in the market are adopted.

[0118] The features and performances of the present application are further described in detail below in combination with examples.

[0119] Example 1 (marker screening)

[0120] This example provides a screening method for screening mutation sites associated with hypertension disease, and the specific steps are as follows:

[0121] 1. Extract DNA from peripheral blood samples (≥4 ml) of hypertension patients and normal controls from Baijia Medical Clinic;

[0122] 2. Collect the corresponding pulse (Pulse) and body mass index (BMI) of patients and controls;

[0123] 3. Ultrasonic fragmentation of DNA, end repair, 3' end A, adaptor ligation, and selection of fragments between 285-415 bp to prepare a whole genome library;

[0124] 4. Double-end sequencing with a high-throughput sequencer, read length 150 bp;

[0125] 5. After whole genome sequencing, conventional filtering analysis is performed, and hg38, dbSNP (v147) is used as the reference genome version for screening filtering criteria;

[0126] 6. Then, respectively taking the mutated gene (a) and the mutated site (b) as biomarkers, the number of samples with gene mutations in the case group and the control group is counted and the OR value is calculated, OR>1, P<0.01. It is found that multiple mutation sites are statistically associated with hypertension;

[0127] 7. Through annotation analysis of gene function and related pathways and literature retrieval data, the sequencing results are deeply analyzed, and from 52 sites (see Table 1 for details) 4 mutation sites related to hypertension are finally screened out: rs2106809, rs699, rs671 and rs1799983.

[0128] Table 1 RS site information

[0129]

[0130]

[0131] This example further combines whole genome data, pulse (Pulse), body mass index (BMI) data information in patients and control groups, and the inventors construct a model for early risk warning of hypertension. The specific model construction process is as follows.

[0132] 1) Single nucleotide polymorphism (SNP) selection

[0133] Selection of SNPs: 52 sites related to hypertension were found in the literature, and bioinformatics methods including pathway analysis and gene ontology (GO) analysis were used to predict and evaluate the biological function of the sites and their potential association with hypertension. Four mutation sites related to hypertension were selected from them: rs2106809, rs699, rs671, and rs1799983.

[0134] 2) Feature selection

[0135] The SNP site data and Pulse and BMI were standardized, where the SNP site was divided into wild type, heterozygous type and homozygous mutant type according to the site state, and was assigned a value of 0, 0.5 and 1 respectively.

[0136] 3) Data standardization

[0137] BMI and Pulse were standardized by the min-max method to standardize their numerical values to 0-1.

[0138] 4) Model training

[0139] A logistic regression model was constructed, and the model performance was evaluated in subsequent examples.

[0140] The model uses the following regression equation to calculate the risk score: risk score y = -0.11805319*rs2106809 - 0.39629604*rs699 + 0.02177215*rs671 + 0.03985716*rs1799983 - 0.1326726*Pulse - 0.2147923*BMI + 1.42201697;

[0141] The risk score is between 0 and 1; the genotype information is assigned a value between 0 and 1, with a value of 0.5 when the gene site is heterozygous, a value of 1 when it is homozygous mutant, and a value of 0 when it is wild type homozygous mutant;

[0142] The Pulse and BMI values in the model are the standardized values of the Pulse and BMI values of the samples, and the standardized values of Pulse and BMI are both between 0 and 1;

[0143] When the risk score is less than 0.33, it is low risk, when the risk score is between 0.33 and 0.85, it is medium risk, and when the risk score is greater than 0.85, it is high risk.

[0144] Example 2 (marker independent verification)

[0145] The embodiment provides a method for early risk warning of hypertension based on four markers (rs2106809, rs699, rs671 and rs1799983) and pulse (Pulse), body mass index (BMI), and specifically the prediction method is as follows:

[0146] Take 336 blood samples (from Baijia Medical Clinic), extract the genome, perform whole genome sequencing, use Sentieon to analyze the variations, obtain the GVCF file of all variation sites of each sample, and obtain the pulse (Pulse), body mass index (BMI) of the 336 samples. The Pulse and BMI are subjected to data Min-Max method standardization processing, and the results after standardization of Pulse and BMI are between 0 and 1.

[0147] The four markers, pulse, and body mass index of the above-mentioned 336 samples are analyzed, and are substituted into the model of the above-mentioned embodiment 1 to perform hypertension risk scoring. According to the guidelines of the World Health Organization (WHO) and the International Hypertension Society (ISH), hypertension is usually defined as systolic pressure (upper pressure) ≥ 140 mmHg and / or diastolic pressure (lower pressure) ≥ 90 mmHg, which is the gold standard for judging hypertension, and is used as the gold standard for true positive diagnosis or early warning. ROC curve is made.

[0148] The interval range of AUC usually refers to the uncertainty of the model prediction, which is estimated by a statistical method (bootstrapping). This involves multiple resampling of the original data set, and after each resampling, the model is retrained using the same model parameter settings, and the AUC value of each time is calculated. Through the distribution of these AUC values, an interval estimate can be obtained, which is usually a 95% confidence interval. Therefore, through the analysis of the confidence interval of AUC, the accuracy of early risk warning of hypertension can be more accurately evaluated.

[0149] ROC curve reference Figure 1 As shown in the results, the sensitivity confidence interval is (0.8076812686575603, 0.9125271624034546) when alpha=0.95;

[0150] The specificity confidence interval is (0.7988037378601484, 0.8799988929102641) when alpha=0.95; therefore, it has high accuracy for early risk warning of hypertension.

[0151] The following compares the performance of the integration of the four rs sites based on WGS and the integration of the four rs sites based on qPCR for early risk warning of hypertension through experimental examples and comparative examples.

[0152] Comparative Example 1

[0153] This comparative example provides early risk warning of hypertension based on single site of rs2106809, rs699, rs671 and rs1799983, specifically the prediction method is as follows:

[0154] (1) Extract the information of rs2106809, rs699, rs671 and rs1799983 sites of all blood samples in Example 2;

[0155] (2) Assign values to the state of the site, with wild type value of 0, heterozygous value of 0.5, and homozygous value of 1;

[0156] (3) Draw the ROC curve using the results after assignment to evaluate the classification effect of a single site; other steps are the same as Example 2.

[0157] The ROC curve of a single site is shown in Figure 3 , Figure 4 , Figure 5 and Figure 6 , and the results show that the performance of a single site based on WGS is poorer compared with the early warning method of four sites, pulse (Pulse) and body mass index (BMI) in Example 2.

[0158] Experimental Example 1

[0159] This example provides a method for early risk warning of hypertension based on four markers (rs2106809, rs699, rs671 and rs1799983), specifically the prediction method is as follows:

[0160] 1) Extract the information of the above four markers of all blood samples in Example 2;

[0161] 2) Assign values to each site according to the heterozygous or homozygous state of the site, with heterozygous site value of 0.5, homozygous site value of 1, and wild type value of 0;

[0162] 3) Use the data after sorting to construct a Logstic regression model, and the model formula is as follows: y = -0.2607 * rs2106809 - 0.8757 * rs699 + 0.0481 * rs671 + 0.0881 * rs1799983, and evaluate the model performance, and the model performance is shown in Figure 2 .

[0163] 4) Draw the ROC curve using the results after assignment to evaluate the classification effect of four SNP sites; other steps are the same as Example 2.

[0164] The ROC curve is shown in Figure 2As shown, the results show that compared with the early warning method of four sites, pulse (Pulse) and body mass index (BMI) in Example 2, the accuracy of assessing hypertension using only four markers is relatively poor.

[0165] Experimental Example 2

[0166] This example provides a qPCR method for early risk warning of hypertension based on four markers (rs2106809, rs699, rs671, and rs1799983). Primers and probes were designed for the four markers, and qPCR amplification was performed on the four markers in the 336 samples. ROC curves were generated based on the amplified ΔCt values.

[0167] The single-point ROC curve is as follows Figure 7 、 Figure 8 、 Figure 9 and Figure 10 As shown, the results showed that compared with the early warning method of four sites, pulse (Pulse) and body mass index (BMI) in Example 2, the performance of a single site based on qPCR was poor.

[0168] The primer probe sequences are as follows:

[0169]

[0170] Prepare the qPCR reaction system as follows:

[0171] Component Final concentration 10X Taq enzyme buffer 1× Taq enzyme 2U dNTPs 200 μΜ Marker primer pair 0.2 μΜ Marker probe 200 nM ACTB primer pair 0.2 μΜ ACTB probe 200 nM Template DNA 5 ng Supplemented nuclease-free water to 50 μL

[0172] Perform qPCR reactions according to the following table:

[0173]

[0174] The ROC curves for detecting rs2106809, rs699, rs671 and rs1799983 were respectively Figure 7 、 Figure 8 、 Figure 9 and Figure 10 The results showed that the accuracy of single loci of rs2106809, rs699, rs671 and rs1799983 in assessing hypertension was poor.

[0175] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. Use of a detection reagent for a hypertension warning or diagnostic marker in the preparation of a hypertension warning or diagnostic product, characterized in that: The hypertension warning or diagnostic markers include rs2106809, rs699, rs671 and rs1799983. The hypertension risk warning or diagnosis is performed based on the genotype information of the samples rs2106809, rs699, rs671 and rs1799983. The SNP site of the rs2106809 is: chrX:15599938-NG_012575.2:g.7221T>G, the rs69 The SNP site of 9 is: chr1:230710048-NG_008836.2:g.9543T>C; the marker information of rs671 is: chr12:111803962-NP_000681.2:p.Glu504Lys; the SNP site of rs1799983 is: chr7:150999023-NC_000007.14:g.150999023T>G; The detection reagent is a primer-probe combination.

2. The use according to claim 1, characterized in that The method for hypertension risk warning or diagnosis is as follows: constructing a hypertension risk warning or diagnosis model based on the genotype information of rs2106809, rs699, rs671 and rs1799983 and hypertension risk; assigning values ​​to the genotype information of rs2106809, rs699, rs671 and rs1799983 of the test sample, inputting the assigned values ​​into the hypertension risk warning or diagnosis model, and performing hypertension risk warning or diagnosis on the sample according to the output result of the hypertension risk warning or diagnosis model.

3. The use according to claim 1 or 2, characterized in that The detection reagent is a reagent for detecting the genotype of the hypertension warning or diagnostic marker in a sample by polymerase chain reaction, real-time fluorescence quantitative polymerase chain reaction, and / or nucleic acid mass spectrometry.

4. The use according to claim 3, characterized in that The hypertension warning or diagnosis product is at least one of a kit, a chip, a sequencing library, and a membrane strip; The nucleotide sequences of the primers for detecting rs2106809 are shown in SEQ ID NOs: 1-2; The nucleotide sequences of the primers for detecting rs699 are shown in SEQ ID NOs: 3-4; The nucleotide sequences of the primers for detecting rs671 are shown in SEQ ID NOs: 5-6; The nucleotide sequences of the primers for detecting rs1799983 are shown in SEQ ID NOs: 7-8; The nucleotide sequence of the probe for detecting rs2106809 is shown in SEQ ID NO: 9; The nucleotide sequence of the probe for detecting rs699 is shown in SEQ ID NO: 10; The nucleotide sequence of the probe for detecting rs671 is shown in SEQ ID NO: 11; The nucleotide sequence of the probe for detecting rs1799983 is shown in SEQ ID NO:

12.

5. The use according to claim 1, characterized in that The hypertension warning or diagnostic markers also include pulse and body mass index (BMI). The method for hypertension risk warning or diagnosis is as follows: constructing a hypertension risk warning or diagnosis model based on the genotype information of rs2106809, rs699, rs671 and rs1799983, pulse and body mass index (BMI) and hypertension risk; assigning values ​​to the genotype information of rs2106809, rs699, rs671 and rs1799983 of the test sample, and assigning values ​​to the pulse and BMI of the test sample, inputting the assigned genotype information, pulse and BMI into the hypertension risk warning or diagnosis model, and performing hypertension risk warning or diagnosis on the sample according to the output results of the hypertension risk warning or diagnosis model.

6. The use according to claim 5, characterized in that The model uses the following regression equation to calculate the risk score: y=-0.11805319*rs2106809-0.39629604*rs699+0.02177215*rs671+0.03985716*rs1799983-0.1326726*Pulse-0.2147923*BMI+1.42201697; the risk score value is between 0 and 1; the genotype information is assigned a value between 0 and 1, with a value of 0.5 when the gene locus is heterozygous, a value of 1 when homozygous, and a value of 0 when wild type; The Pulse and BMI values ​​in the model are the values ​​obtained by standardizing the Pulse and BMI values ​​of the sample, and the values ​​after standardization of Pulse and BMI are both between 0 and 1.

7. The use according to claim 6, characterized in that When the risk score is less than 0.33, it is low risk; when the risk score is between 0.33-0.85, it is medium risk; when the risk score is greater than 0.85, it is high risk.

8. A product for early warning or diagnosis of hypertension, characterized in that: The product comprises a detection reagent for a hypertension warning or diagnostic marker as described in any one of claims 1 to 7, wherein the detection reagent is a primer-probe combination.

9. The product for early warning or diagnosis of hypertension according to claim 8, characterized in that: The product is a test kit; The nucleotide sequences of the primers for detecting rs2106809 are shown in SEQ ID NOs: 1-2; the SNP site of rs2106809 is: chrX:15599938-NG_012575.2:g.7221T>G; The nucleotide sequences of the primers for detecting rs699 are shown in SEQ ID NOs: 3-4; the SNP site of rs699 is: chr1:230710048-NG_008836.2:g.9543T>C; The nucleotide sequences of the primers for detecting rs671 are shown in SEQ ID NOs: 5-6; the marker information of rs671 is: chr12: 111803962-NP_000681.2: p.Glu504Lys; The nucleotide sequences of the primers for detecting rs1799983 are shown in SEQ ID NOs: 7-8; the SNP site of rs1799983 is: chr7: 150999023-NC_000007.14: g.150999023T>G.

10. The product for early warning or diagnosis of hypertension according to claim 9, characterized in that: The nucleotide sequence of the probe for detecting rs2106809 is shown in SEQ ID NO: 9; The nucleotide sequence of the probe for detecting rs699 is shown in SEQ ID NO: 10; The nucleotide sequence of the probe for detecting rs671 is shown in SEQ ID NO: 11; The nucleotide sequence of the probe for detecting rs1799983 is shown in SEQ ID NO:

12.

11. A model for early warning or diagnosis of hypertension risk, characterized in that: The model uses the following regression equation to calculate the risk score: y=-0.11805319*rs2106809-0.39629604*rs699+0.02177215*rs671+0.03985716*rs1799983-0.1326726*Pulse-0.2147923*BMI+1.42201697; the SNP site of rs2106809 is: chrX:15599938-NG_012575 .2:g.7221T>G, the SNP site of rs699 is: chr1:230710048-NG_008836.2:g.9543T>C; the marker information of rs671 is: chr12:111803962-NP_000681.2:p.Glu504Lys; the SNP site of rs1799983 is: chr7:150999023-NC_000007.14:g.150999023T>G; The risk score is between 0 and 1. The genotype information is assigned a value between 0 and 1, with a value of 0.5 when the gene locus is heterozygous, a value of 1 when the gene locus is homozygous, and a value of 0 when the gene locus is wild type. The Pulse and BMI values ​​in the model are the values ​​obtained by standardizing the Pulse and BMI values ​​of the sample, and the values ​​after standardization of Pulse and BMI are both between 0 and 1.

12. The hypertension risk warning or diagnosis model according to claim 11, characterized in that: When the risk score is less than 0.33, it is low risk; when the risk score is between 0.33-0.85, it is medium risk; when the risk score is greater than 0.85, it is high risk.

13. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a program, and the processor implements the following method when executing the program: Obtaining genotype information of the hypertension warning or diagnostic marker described in any one of claims 1 to 7 from a sample of a test subject; or obtaining genotype information, Pulse, and BMI of the hypertension warning or diagnostic marker described in any one of claims 1 to 7; The genotype information of hypertension warning or diagnostic markers will be obtained; or; providing genotype information, Pulse and BMI as input data to a trained model, wherein the model is trained to provide early warning or diagnosis of hypertension risk for the subject based on the genotype information, Pulse and BMI of the subject's hypertension early warning or diagnostic markers; Obtaining the output of the model to obtain a warning result for the subject; The model is a logistic regression model.

14. The computer device according to claim 13, wherein: The model is the model for early warning or diagnosis of hypertension risk according to any one of claims 11-12.

15. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program; wherein, when the computer program is executed, the computer-readable storage medium is controlled to implement the method described in claim 13.

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