Composition, kit and application for detecting drug metabolism-related gene polymorphism

Abstract

The present invention relates to the field of biological detection, and specifically to the detection of gene polymorphisms associated with the metabolism of drugs for hypertension, hyperglycemia, and hyperlipidemia. The present invention provides a composition for detecting gene polymorphisms associated with the metabolism of drugs for hypertension, hyperglycemia, and hyperlipidemia, comprising a detection reagent for detecting SNP sites in the genes shown in Table 1. Using the composition of the present invention, 32 SNP sites in 18 genes associated with drugs for treating hypertension, hyperglycemia, and hyperlipidemia can be detected at one time. This allows for the development of different treatment plans tailored to individual genetic differences in patients with hyperglycemia and / or hypertension and / or hyperlipidemia, enabling the selection of appropriate drugs, achieving accurate typing and precise medication, thereby increasing drug efficacy and reducing adverse drug reactions.

Description

Technical Field

[0001] The present invention belongs to the field of biological detection, and in particular, relates to the detection of gene polymorphisms related to the metabolism of hypertension, hyperglycemia and hyperlipidemia drugs. Background Art

[0002] According to the 2019 IDF Global Diabetes Atlas, released by the International Diabetes Federation (IDF) in 2020, the number of people with diabetes in my country has reached 116.4 million, of which type 2 diabetes accounts for over 90%. Clinically, hyperglycemia is primarily controlled with hypoglycemic medications. However, the current "one-drug-for-one-thousand-patients" approach fails to effectively lower blood sugar and can exacerbate adverse reactions. Therefore, providing personalized treatment for patients with hyperglycemia is crucial.

[0003] Hypertension, one of the most important risk factors for cardiovascular and cerebrovascular disease, carries a high rate of disability and mortality, and is a serious epidemic. The low control rate of hypertension is due not only to low awareness and treatment rates, but also to factors such as inadequate dietary and lifestyle improvements, suboptimal drug treatment efficacy, numerous drug side effects, poor patient compliance, and a lack of personalized medication guidance.

[0004] Dyslipidemia (mainly hypercholesterolemia) is a major risk factor for cardiovascular disease. Hyperlipidemia refers to the concentration of blood lipid components such as plasma cholesterol, triglycerides (i.e. neutral fat), and total lipids (phospholipids, fatty acids) exceeding normal standards. Clinically, hyperlipidemia is often called hyperlipidemia and is a common disease. Clinical lipid-lowering measures mainly include diet therapy, lifestyle improvement, and the use of lipid-lowering drugs. The use of lipid-lowering drugs involves individual differences in lipid-lowering efficacy and tolerance, and a "tailor-made" approach is very important for individuals.

[0005] Currently, commonly used antihypertensive drugs in clinical practice are mainly divided into five categories: the renin angiotensin-aldosterone system (RAAS), adrenergic receptor β-blockers, calcium channel blockers (calcium ion antagonists), and diuretics. Glucose-lowering drugs are mainly divided into the following categories: insulin and its derivatives, sulfonylureas, biguanides, thiazolidinediones, α-glucosidase inhibitors, meglitinides, amylin, incretin hormone mimetics, dipeptidyl peptidase VI inhibitors, glucagon-like peptide receptor agonists, and sodium-glucose co-transporter inhibitors. Lipid-lowering drugs mainly include statins, which primarily lower serum total cholesterol and low-density lipoprotein (LDL) cholesterol; fibrates and niacin, which primarily lower serum triglycerides (TG); bile acid sequestrants; and cholesterol absorption inhibitors. A wide variety of drugs are available. Genetic variations in genes involved in drug metabolism, transport, and drug targets, as well as changes in their expression levels, can affect drug concentrations and sensitivity in vivo, leading to individual differences in drug response. Pharmacogenomics has become an important tool for guiding personalized clinical medication, assessing the risk of serious adverse drug reactions, and guiding new drug development and evaluation. Some new drugs are now available only for patients with specific genotypes. The US FDA has approved the addition of pharmacogenomic information to the drug labels of over 140 drugs, including 42 pharmacogenomic biomarkers. Molecular detection of drug-response-related genes and their expression products is a prerequisite for implementing personalized drug therapy.

[0006] Studies have shown that the four major categories of antidiabetic drugs, sulfonylureas, biguanides, thiazolidinediones, and meglitinides, are closely related to genetic polymorphisms. Pharmacogenomic research may allow for precise treatment of some drugs. Dozens of genes have been found to be associated with diabetes drugs, including GLP1R, AQP2, ACE, GNB3, PAX4, NEUROD1, NOS1AP, SLC30A8, IGF2BP2, KCNQ1, TCF7L2, KCNJ11, KCNJ1, SLCO1B1, NPC1L1, ADRB1, REN, EDN1, IRS1, LPIN1, AGTR1, CYP2C9, G6PD, PPARA, SCNN1B, CDKAL1, C11orf65, and SLC4. 7A2, SLC22A1, SLC47A1, CAPN10, SP1FMO5, AMHR2, SLC2A2, ADIPOQ, etc., among which G6PD, CYP2C9, KCNJ11, SUR1, PPAR-γ, SLCO1B1, SLC22A1, SLC22A2, SLC47A1, etc. have been studied more and the evidence is more sufficient. Among them, FDA and HCSC have written the genomic information of some diabetes drugs into the drug instructions. For example, FDA and HCSC recommend that the detection gene of glibenclamide is G6PD.

[0007] Currently, there are dozens of genes related to the four major categories of hypertension drugs, including CYP2C9, CYP2D6, AGTR1, EDN1, ACE, ADRB1, ADRB2, CYP3A5, APOB, AGT, NPPA, etc. Among them, there are more related studies on CYP2C9, AGTR1, ACE, ADRB1, CYP3A5, NPPA, and CYP2D6, and the evidence is relatively sufficient. Among them, the FDA, EMA and HCSC have already written the genomic information of some hypertension drugs into the drug instructions, such as metoprolol.

[0008] Lipid-modifying drugs are primarily divided into two categories, statins and fibrates, based on their therapeutic effects on hyperlipidemia. Pharmacogenomic research on these drugs is also relatively mature. Currently, dozens of genes have been implicated in statins, including CYP2C9, APOE, CYP3A4, CYP3A5, LEPR, SLCO1B1, ABCB1, SCAP, ABCA1, and UGT1A3. APOE and SLCO1B1 have been extensively studied and supported by sufficient evidence. The FDA, PMDA, and HCSC have already incorporated genomic information into the drug labels for some lipid-lowering drugs, such as pravastatin, rosuvastatin, and atorvastatin.

[0009] Hyperglycemia, hyperlipidemia, and high cholesterol often coexist, with hypertension and diabetes, diabetes and hyperlipidemia, or all three presenting as a clustered phenomenon. More than half of diabetic patients have high blood sugar, but also hypertension and high cholesterol. Studies show that over 70% of diabetic patients have concurrent hyperlipidemia. Whether hypertensive patients develop diabetes or diabetes develops hypertension, the combined presence of hyperlipidemia significantly increases the risk of future cardiovascular and cerebrovascular disease. Therefore, there is a need for simultaneous testing of all three medication-related genes to provide clinical guidance for medication use. Summary of the Invention

[0010] In view of this, in the first aspect, based on the types of drugs commonly used in the clinical treatment of hypertension, hyperglycemia, and hyperlipidemia, and in combination with global authoritative pharmacogenomics databases, authoritative guidelines, and the latest reported research, SNP sites closely related to drug metabolism were selected. The present invention provides a composition for detecting genetic polymorphisms related to drug metabolism of hypertension, hyperglycemia, and hyperlipidemia, which includes a detection reagent for detecting SNP sites in the genes shown in Table 1.

[0011] Table 1

[0012]

[0013]

[0014] The composition of the present invention can be used to detect 32 SNP sites of 18 genes related to drugs for treating hypertension, hyperglycemia, and hyperlipidemia at one time, thereby detecting the corresponding genes, especially the polymorphisms of the corresponding genes at specific mutation sites. Different plans can be formulated for patients with hyperglycemia and / or hypertension and / or hyperlipidemia based on individual genetic differences, and appropriate drugs can be selected to achieve accurate typing and precise medication, thereby increasing drug efficacy and reducing adverse drug reactions.

[0015] In the present invention, "detection reagent" refers to a reagent for detecting SNP sites in a sample.

[0016] In some specific embodiments, the detection reagents include but are not limited to nucleic acid primers, sequencing Tag sequences, or capture chips.

[0017] In a specific embodiment, the nucleic acid primers are a primer combination including SEQ ID NOs: 1 to 52.

[0018] Furthermore, the detection reagent also includes an internal standard primer and an internal standard probe.

[0019] Furthermore, the above composition may also include other reagents, specifically, for example, various reagents required for pre-treatment or pre-processing of the sample, such as a sample release agent for extracting sample nucleic acid, a purification agent for purifying sample nucleic acid, etc.

[0020] In a specific embodiment, the components of the composition of the present invention are each present in a separate package.

[0021] In a particular embodiment, the components of the composition of the present invention are present in admixture.

[0022] In a second aspect, the present invention provides use of the above-mentioned composition in preparing a kit for detecting gene polymorphisms related to drug metabolism in hypertension, hyperglycemia, and hyperlipidemia.

[0023] In a third aspect, the present invention provides a kit for detecting gene polymorphisms related to drug metabolism of hypertension, hyperglycemia, and hyperlipidemia, wherein the kit comprises the composition as described above.

[0024] Furthermore, the kit also includes, but is not limited to, at least one of a reagent for extracting nucleic acid, a reagent for purifying nucleic acid, and a reagent for amplifying nucleic acid.

[0025] Furthermore, the reagent for purifying nucleic acid includes magnetic beads.

[0026] In a fourth aspect, the present invention provides a method for detecting gene polymorphisms related to drug metabolism in hypertension, hyperglycemia, and hyperlipidemia, comprising:

[0027] 1) Extracting or releasing nucleic acid from the sample to be tested;

[0028] 2) analyzing the nucleic acid obtained in step 1) using the above composition or kit;

[0029] 3) Obtain and analyze the results.

[0030] In some specific embodiments, step 2) comprises performing a first round of amplification on the nucleic acid.

[0031] In some specific embodiments, step 2) comprises purifying the nucleic acid.

[0032] In some specific embodiments, step 2) comprises performing a second round of amplification on the nucleic acid.

[0033] In a specific embodiment, step 2) includes performing a first round of amplification on the nucleic acid using the above composition, purifying the nucleic acid after the first round of amplification, and performing a second round of amplification on the purified nucleic acid.

[0034] The components of the second round of PCR reaction system are shown in Table 2 below:

[0035] Table 2

[0036]

[0037] In a specific embodiment, step 3) includes sequencing the amplified products and performing data analysis.

[0038] The specific analysis method is as follows:

[0039] 1) Perform primer matching query on the original fastq reads: retain the reads with primers found, filter the unmatched reads, and generate statistics.

[0040] 2) Use SOAPnuke (Version: 1.5.3) software to perform basic quality filtering on the split reads

[0041] 3) Use the alignment software bwa-mem2 (v2.0) to obtain the alignment information bam file of reads on the genome

[0042] 4) Alignment preprocessing and re-alignment

[0043] 5) Single nucleotide variant (SNV) calling

[0044] 6) Short insertion / deletion (InDels) mutation calling

[0045] 7) Summarize the genotypes of the target sites of all samples in the batch and output a summary table of genetic testing results

[0046] 8) Correlating the results obtained for each gene-related locus with information in the PharmGKB database, conventional analytical methods in the art and information in the PharmGKB database can be used to determine the efficacy of different types of hypoglycemic, hypotensive, and hypolipidemic drugs used by the subjects, thereby assisting in guiding clinicians in using these drugs to treat patients accordingly.

[0047] More specifically, the present invention provides a method for detecting gene polymorphisms related to drug metabolism of hypertension, hyperglycemia, and hyperlipidemia for non-detection purposes, comprising:

[0048] 1) Extracting or releasing nucleic acid from the sample to be tested;

[0049] 2) analyzing the nucleic acid obtained in step 1) using the above composition or kit;

[0050] 3) Obtain and analyze the results.

[0051] In some specific embodiments, step 2) comprises performing a first round of amplification on the nucleic acid.

[0052] In some specific embodiments, step 2) comprises purifying the nucleic acid.

[0053] In some specific embodiments, step 2) comprises performing a second round of amplification on the nucleic acid.

[0054] In a specific embodiment, step 2) includes performing a first round of amplification on the nucleic acid using the above composition, purifying the nucleic acid after the first round of amplification, and performing a second round of amplification on the purified nucleic acid. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Schematic diagram of the detection method of the present invention;

[0056] Figure 2 The number of sequencing reads of different primer pairs of the composition of the present invention and the comparative example;

[0057] Figure 3 It represents the uniformity between the primers of the composition of the present invention and the repeatability of the results. DETAILED DESCRIPTION

[0058] The present invention will be described in detail below in conjunction with specific embodiments and examples, and the advantages and various effects of the present invention will be more clearly presented. It should be understood by those skilled in the art that these specific embodiments and examples are for illustrating the present invention, rather than for limiting the present invention.

[0059] Example 1: Primers used in the present invention

[0060] Table 3 shows the primer pairs used in the present invention.

[0061] Table 3

[0062]

[0063] Example 2: Method of using the composition of the present invention

[0064] The specific process is as follows Figure 1 shown.

[0065] 1. Determination of genes and detection sites

[0066] Based on drug characteristics, drugs enter the human body and exert their effects through absorption, transport, metabolism, effects, and clearance. Patients with different genotypes may exhibit individual differences in drug responsiveness to drugs used to treat hypertension, hyperglycemia, and hyperlipidemia. A total of 18 genes and 32 single-nucleotide polymorphisms (SNPs) have been identified as being associated with these drugs. The associated genes and SNPs are shown in Table 1.

[0067] 2. Primer design and synthesis

[0068] Based on the above-screened genes and SNP sites, primer combinations for genes related to drugs for treating hypertension, hyperglycemia, and hyperlipidemia were designed and optimized. The corresponding multiple primer combinations include 26 pairs, as shown in Table 3.

[0069] 3. Sample processing

[0070] Extract DNA using a commercial nucleic acid extraction kit (such as the Tiangen Whole Blood Genomic DNA Extraction Kit).

[0071] 4. Targeted Multiplex Amplification

[0072] In the first round of PCR, DNA samples were extracted from the subjects as templates. 26 pairs of specific primers were used to perform multiplex amplification in a single tube to obtain a half-library of gene polymorphisms related to hypertension, hyperglycemia, and hyperlipidemia drug metabolism. The multiplex PCR amplification used a 25 μL reaction system containing the following components:

[0073]

[0074] The total volume of the polymerase mix and primer mix was 7.75 μL. The amount of DNA template was controlled between 5 and 200 ng, and the volume was determined based on the actual concentration. Ultrapure water was then added to a total volume of 25 μL. The polymerase mix contained dNTPs, FastStart High Fidelity Enzyme hot-start enzyme, and the required buffer system. The multiplex PCR amplification program was as follows: 95°C, 10 m; 95°C, 30 s; 60°C, 1.5 m; 72°C, 4 m, 20 cycles; 72°C, 4 m.

[0075] 5. Semi-library purification

[0076] The half library was purified using 1.5X magnetic beads (37.5 μL) and eluted with 20 μL ddH 2 O.

[0077] 6. Second round of PCR

[0078] 6.1 Second round of PCR: Take 10 μL of the purified half library for the second round of PCR amplification reaction. The components of the amplification reaction system are as follows:

[0079]

[0080]

[0081] The Pfx DNA polymerase in the above reaction system is a common commercial product, and the PCR reaction conditions are: 94°C, 2m pre-denaturation; 94°C, 15s denaturation, 60°C, 30s annealing, 72°C, 30s extension, 13 cycles; 72°C, 2m extension.

[0082] 6.2 Purify the amplified product using 1.0x magnetic beads (25 μL) and elute with 22 μL ddH2O to obtain a high-throughput sequencing library of gene polymorphisms related to hypertension, hyperglycemia, and hyperlipidemia drug metabolism.

[0083] 7. Sequencing on the sequencer

[0084] This example uses the Illumina NextSeq 500 sequencer with a 75-cycle sequencing kit for sequencing.

[0085] 8. Data Analysis

[0086] After the sequencing data is downloaded, bioinformatics analysis is performed on the data to detect the genotype of the target site. The specific steps are as follows:

[0087] 8.1. Primer matching query for raw FastQ reads: For single-end sequencing (SE) sequencing, primer matching is performed for each read starting several bases, allowing for zero (default) base mismatches. For paired-end sequencing (PE) sequencing, primer matching is performed for each read starting and ending several bases, allowing for zero base mismatches. Reads with primers found are retained, unmatched reads are filtered, and statistics are generated.

[0088] 8.2. Use SOAPnuke (Version: 1.5.3) software to perform basic quality filtering on the split reads: filter out reads with a base ratio greater than 30% and a quality value lower than 20, and filter out reads with an N ratio greater than 4% to obtain clean reads.

[0089] 8.3. Alignment: Use the alignment software bwa-mem2 (v2.0) to align the clean reads to the human reference genome GRCh37 and obtain a bam file containing the alignment information of the reads on the genome.

[0090] 8.4. Alignment preprocessing and realignment: This includes using in-house scripts to filter BAM results (removing reads from multiple alignment positions), using PicardTools (v1.92) to sort BAM genomic positions, using GATK to realign BAM, and using samtools (v1.9) to merge BAM files from different lanes of the same library sample.

[0091] 8.5. Single Nucleotide Variant (SNV) Calling: We used samtools to generate a mpileup file from the final BAM, and used in-house scripts to perform genotype calling for the target loci. The general principle is to scan the base types at each locus to obtain a base distribution table, which is then filtered using a filter.

[0092] 8.6. Calling Short Insertions / Deletions (InDels): By constructing a base motif surrounding the target indel genotype and counting the number of motifs with different genotypes, the wild-type / mutant indel is determined. For motifs with amplification advantages, preliminary testing is performed to determine the cut-off value for the ratio of dominant to non-dominant amplification types.

[0093] 8.7. Summarize the genotypes of the target loci of all samples in the batch and output a summary table.

[0094] Example 3, clinical test results of the composition of the present invention

[0095] The patient, surnamed Guo, was a patient with hypertension. Prior to testing, he had been taking losartan, which had shown unsatisfactory results in lowering his blood pressure. The primer set and / or kit of the present invention were used to perform relevant gene testing on Guo. The test results, interpretation of the results, and medication recommendations are shown in Table 4. Drug efficacy analysis indicated that the patient needed to increase the losartan dosage to enhance the antihypertensive effect. The attending physician subsequently adjusted the dosage, and after one month of treatment, his blood pressure stabilized.

[0096] At the same time, if the subject Guo in this case subsequently develops symptoms of hyperglycemia and hyperlipidemia, he or she can reasonably choose drugs for relevant treatment based on the medication instructions for hyperglycemia and hyperlipidemia in Table 4.

[0097] Table 4 Guo's test results, result interpretation and medication recommendations

[0098]

[0099]

[0100]

[0101] Example 4: Clinical test results of the composition of the present invention

[0102] The patient, surnamed Jiang, was a diabetic. Prior to testing, metformin had shown suboptimal blood sugar reduction. The primer set and / or kit of the present invention were used to perform relevant genetic testing on Jiang. The test results, interpretation of the results, and medication recommendations are shown in Table 5. Drug efficacy analysis predicted that sulfonylureas and meglitinides would be effective, while metformin would be less effective and more likely to cause side effects. Following the doctor's advice, Jiang opted for troglitazone for blood sugar reduction, which stabilized blood sugar control for three months.

[0103] At the same time, if the subject Jiang in this case subsequently develops symptoms of combined hypertension and hyperlipidemia, he or she can reasonably choose drugs for relevant treatment based on the medication instructions for hypertension and hyperlipidemia in Table 3.

[0104] Table 5 Jiang's test results, result interpretation and medication recommendations

[0105]

[0106]

[0107]

[0108] Example 5: Clinical test results of the composition of the present invention

[0109] The patient, Mr. Peng, had high blood lipids and was taking simvastatin before the test, but the lipid-lowering effect was unsatisfactory. The primer set and / or kit of the present invention were used to perform relevant gene testing on Mr. Peng. The test results, result interpretation, and medication recommendations are shown in Table 6. The drug efficacy analysis predicted that the patient needed to increase the simvastatin dosage to enhance the lipid-lowering effect. The attending physician subsequently adjusted the dosage, and after one month of treatment, the patient's blood lipids stabilized.

[0110] At the same time, if the subject Jiang in this case subsequently develops symptoms of combined hypertension and hyperglycemia, he or she can reasonably choose drugs for relevant treatment based on the medication instructions for hypertension and hyperglycemia in Table 3.

[0111] Table 6 Peng's test results, result interpretation and medication recommendations

[0112]

[0113]

[0114]

[0115] Comparative Example 1

[0116] The tester, Li, is a diabetic patient. He was tested using a gene detection kit for hyperglycemia-related drugs. The test results are shown in Table 7. The results show that the patient had a good effect using sulfonylurea hypoglycemic drugs (glibenclamide, glipizide, gliclazide, gliquidone, glimepiride, tolbutamide, chlorpropamide), while the biguanide drugs (metformin, buformin) had a poor effect. Chlormeglitinide drugs (repaglinide, nateglinide) are prone to toxic and side effects and need to be used in reduced doses. Thiazolidinediones (troglitazone, rosiglitazone, pioglitazone) have increased drug sensitivity and enhanced hypoglycemic effects, but also increased toxic and side effects. It is recommended to reduce the dosage of the drug or change the medicine. Based on the above test results, the doctor recommended that Li use glimepiride to lower blood sugar. Li developed hemolytic symptoms after using it, and the symptoms disappeared after he stopped using it. The results of subsequent testing using the primer set and / or kit of the present invention are shown in Table 8. These results indicate that the patient has a G6PD gene mutation, indicating glucose-6-phosphate dehydrogenase (G6PD) deficiency. Sulfonylureas are associated with a high risk of hemolysis. Non-sulfonylurea medications should be considered for diabetic patients with G6PD deficiency. Based on the results of this genetic test, a low dose of repaglinide was administered, and the patient's blood sugar was stabilized.

[0117] Table 7 Li's test results, result interpretation and medication recommendations

[0118]

[0119]

[0120] Table 8 Li's test results using the primer set and / or kit of the present invention, result interpretation, and medication recommendations

[0121]

[0122]

[0123]

[0124] Comparative Example 2

[0125] The subject, Xiao, had hyperlipidemia. Testing for SLCO1B1 gene-related loci revealed a low risk of rhabdomyolysis or myopathy with statin therapy, suggesting that conventional statin doses could be used to lower blood lipids. Consequently, the subject began treatment with simvastatin, but his blood lipids remained elevated. Subsequently, testing using the primer set and / or kit of the present invention revealed a poor statin response to APOE E4 / E4. Further statin therapy was recommended, necessitating an increased statin dose if continued. The simvastatin dosage was adjusted based on the genetic test results, achieving stable control of the patient's blood lipids.

[0126] Table 9 Xiao's test results, result interpretation and medication recommendations

[0127]

[0128] Table 10 Detection results, result interpretation, and medication recommendations for Xiao using the primer set and / or kit of the present invention

[0129]

[0130]

[0131]

[0132] Comparative Example 3

[0133] After determining the gene detection site, primers were designed and optimized for the corresponding site. The following primer pairs were designed and screened for optimization, as shown in Table 11. 18 samples were selected for amplification and sequencing analysis, and the results showed that the SEQ15+SEQ16 primer pair was superior to SEQ15-bk+SEQ16-bk, SEQ17+SEQ18 was superior to SEQ17-bk+SEQ18-bk, and SEQ19+SEQ20 was superior to SEQ19-bk+SEQ20-bk. The specific primer pair sequencing read counts are as follows, as shown in Tables 12 and Figure 2 .

[0134] After optimization, 26 primer pairs were finally selected and 10 samples were selected to verify the uniformity between primers and the repeatability of the results. The results showed good results. The specific results are shown in Table 13 and Figure 3 .

[0135] Table 11 Primer pairs

[0136]

[0137] Table 12 Number of sequencing reads for primer pairs

[0138]

[0139]

[0140] Table 13 Uniformity between primers and reproducibility of results

[0141]

[0142]

Claims

1. A composition for detecting gene polymorphisms related to hypertension, hyperglycemia, and hyperlipidemia drug metabolism, comprising a detection reagent for detecting SNP sites of the following genes: in, The detection reagent is a nucleic acid primer, and the nucleic acid primer is a primer combination shown in SEQ ID NO: 1 to 52.

2. The composition according to claim 1, characterized in that The nucleic acid primers also include internal standard primers and internal standard probes.

3. The composition according to claim 2, characterized in that The components of the composition are present in admixture.

4. Use of the composition according to any one of claims 1 to 3 in the preparation of a kit for detecting gene polymorphisms related to drug metabolism in hypertension, hyperglycemia and hyperlipidemia.

5. A kit for detecting gene polymorphisms related to drug metabolism in hypertension, hyperglycemia, and hyperlipidemia, comprising the composition according to any one of claims 1 to 3.

6. The kit according to claim 5, characterized in that The kit further comprises at least one of a reagent for extracting nucleic acid, a reagent for purifying nucleic acid, and a reagent for amplifying nucleic acid.

7. Use of a composition for preparing a reagent for detecting gene polymorphisms related to drug metabolism in hypertension, hyperglycemia, and hyperlipidemia, wherein the detection comprises: 1) Extracting or releasing nucleic acid from the sample to be tested; 2) analyzing the nucleic acid obtained in step 1) using the composition according to any one of claims 1 to 3 or the kit according to claim 5 or 6; 3) Obtain and analyze the results.

8. The use according to claim 7, characterized in that The step 2) comprises performing a first round of amplification on the nucleic acid using the composition according to any one of claims 1 to 3, purifying the nucleic acid after the first round of amplification, and performing a second round of amplification on the purified nucleic acid.

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