Primer kit for detecting type 2 diabetes kidney disease related SNP (Single Nucleotide Polymorphism) site combination

Abstract

The invention discloses a mutation site combination for detecting susceptible genes of a type 2 diabetes kidney disease, which comprises eight SNP sites, application of primers for detecting the SNP sites in preparation of products for evaluating the risk of the type 2 diabetes kidney disease, and a primer kit for detecting the SNP site combination related to the type 2 diabetes kidney disease. According to the present invention, the importance of the pathogenesis relationship between the SNP site combination and the type 2 diabetes kidney disease is comprehensively evaluated by detecting the SNP site combination, the accuracy of the SNP site analysis is improved, and the provided kit provides the simple and effective auxiliary means for detecting the risk of the type 2 diabetes kidney disease; the method is suitable for prediction, prevention and individualized diagnosis and treatment of patients with the type 2 diabetes kidney disease.

Description

Technical Field

[0001] The present invention relates to the field of kits for disease susceptibility detection, and in particular to a primer kit for detecting a combination of SNP sites associated with type 2 diabetic nephropathy. Background Art

[0002] Diabetic kidney disease (DKD) is one of the most serious microvascular complications of diabetes. Its typical feature is the gradual increase in urinary albumin excretion rate, which eventually progresses to end-stage renal disease. It has become the most common cause of end-stage renal disease in developed countries such as Europe and the United States. In my country, the proportion of diabetic kidney disease in end-stage renal disease is also increasing, and it is one of the main causes of death in diabetic patients. According to the new version of IDF data, the number of diabetes patients in my country increased from 90 million to 140 million from 2011 to 2021. It is predicted that the total number of patients will increase to 175 million by 2045, of which 90% of diabetic patients are type 2 diabetes patients, and up to 20%-40% of these patients have DKD. DKD seriously affects the life and quality of life of patients, causing huge economic and social burdens.

[0003] At present, the diagnosis of type 2 diabetic nephropathy is mostly done by blood biochemistry, urine protein and other methods, which can only be detected in patients who are already ill, and it is difficult to warn and guide potential patients with type 2 diabetic nephropathy. Therefore, a method that can predict the risk of diabetic nephropathy is needed, so as to assist in the early diagnosis of diabetic nephropathy and reduce the risk of disease in susceptible people.

[0004] Existing research results suggest that the occurrence and progression of diabetic kidney disease is the result of the combined effects of genetic susceptibility and environmental factors, but each patient may have different susceptibility genes, and non-patient populations may also gather various genetic and environmental disease susceptibility factors to varying degrees; susceptibility genes can exist in both patient and non-patient populations, and the difference is only in frequency. Therefore, it is not easy to identify susceptibility genes for DKD.

[0005] In recent years, genetic studies have found more than 200 SNP sites that are closely related to type 2 diabetic nephropathy. The discovery of these SNP sites plays a certain role in predicting the risk of diabetic nephropathy, clarifying the pathogenesis of type 2 diabetic nephropathy, and exploring personalized treatment plans for type 2 diabetic nephropathy. However, the presence or absence of these SNP sites and the allele frequency vary among races and regions, indicating the existence of genetic heterogeneity in type 2 diabetic nephropathy. Moreover, diabetic nephropathy is a multi-gene genetic disease. The SNP sites found often do not consider the impact of multiple genetic sites on the risk of type 2 diabetic nephropathy, and the evaluation results are not comprehensive enough. At present, there is a lack of detection or methods for the combination of relevant SNP sites in the Chinese population to predict the risk of type 2 diabetic nephropathy.

[0006] Therefore, there is an urgent need to develop a detection method that can predict the risk of type 2 diabetic kidney disease in China. Summary of the invention

[0007] The purpose of the present invention is to provide a primer kit for detecting SNP site combinations associated with type 2 diabetic nephropathy, so as to solve the technical problem in the prior art that type 2 diabetic nephropathy is not easy to be predicted before the onset of the disease.

[0008] In order to solve the above technical problems, the present invention specifically provides the following technical solutions:

[0009] The present invention provides a mutation site combination for detecting a type 2 diabetic nephropathy susceptibility gene, comprising 8 SNP sites, wherein the SNP sites are: rs2504779 site on the CD164L2 gene; rs140936221 site on the ZNF717 gene; rs75405062 site on the CYP2F1 gene; rs75085872 site on the ZNF717 gene; rs112900131 site on the TAS2R19 gene; rs200904145 site on the HLA-DQA2 gene; rs199894662 site on the TAS2R31 gene; and rs35509911 site on the KIR2DL1 gene. The specific position and flanking sequence of each SNP site are shown in Table 1.

[0010] The present invention provides a primer and a primer combination for detecting a type 2 diabetic nephropathy susceptibility gene, wherein the primer and the primer combination are used to amplify a mutation site in the aforementioned mutation site combination.

[0011] As a preferred embodiment of the present invention, the primers are specifically (see Table 2):

[0012] The rs2504779 site is: an amplification product obtained by PCR amplification using primer pair 1 with human genomic DNA as a template; the nucleotide of the site is C or T;

[0013] The rs140936221 site is: an amplification product obtained by PCR amplification using primer pair 2 with human genomic DNA as a template; the nucleotide of the site is C or T;

[0014] The rs75405062 site is: an amplification product obtained by PCR amplification using primer pair 3 with human genomic DNA as a template; the nucleotide of the site is G or C;

[0015] The rs75085872 site is: an amplification product obtained by PCR amplification using primer pair 4 with human genomic DNA as a template; the nucleotide of the site is T or C;

[0016] The rs112900131 site is: an amplification product obtained by PCR amplification using primer pair 5 with human genomic DNA as a template; the nucleotide of the site is A or G;

[0017] The rs200904145 site is: an amplification product obtained by PCR amplification using primer pair 6 with human genomic DNA as a template; the nucleotide of the site is A or G;

[0018] The rs199894662 site is: an amplification product obtained by PCR amplification using primer pair 7 with human genomic DNA as a template; the nucleotide of the site is G or A;

[0019] The rs35509911 site is: an amplification product obtained by PCR amplification using primer pair 8 with human genomic DNA as a template; the nucleotide of the site is G or C.

[0020] The present invention provides an application of a primer for detecting a SNP site in preparing a product for assessing the risk of type 2 diabetic nephropathy.

[0021] The present invention provides a primer kit for detecting a combination of SNP sites associated with type 2 diabetic nephropathy, comprising the following 8 primer pairs or primer pair combinations:

[0022] Primer pair for amplifying SNP site rs2504779;

[0023] Primer pair for amplifying SNP site rs140936221;

[0024] Primer pair for amplifying SNP site rs75405062;

[0025] Primer pair for amplifying SNP site rs75085872;

[0026] Primer pair for amplifying SNP site rs112900131;

[0027] Primer pair for amplifying SNP site rs200904145;

[0028] Primer pair for amplifying SNP site rs199894662;

[0029] Primer pair for amplifying SNP site rs35509911.

[0030] As a preferred embodiment of the present invention, the nucleotide sequence of the primer pair for amplifying the SNP site rs2504779 is shown in SEQ ID NO.1-2;

[0031] The nucleotide sequence of the primer pair for amplifying the SNP site rs140936221 is shown in SEQ ID NOs. 3 to 4;

[0032] The nucleotide sequences of the primer pairs for amplifying the SNP site rs75405062 are shown in SEQ ID NOs. 5 to 6;

[0033] The nucleotide sequences of the primer pairs for amplifying the SNP site rs75085872 are shown in SEQ ID NOs. 7 to 8;

[0034] The nucleotide sequences of the primer pairs for amplifying the SNP site rs112900131 are shown in SEQ ID NOs. 9 to 10;

[0035] The nucleotide sequences of the primer pairs for amplifying the SNP site rs200904145 are shown in SEQ ID NOs. 11 to 12;

[0036] The nucleotide sequence of the primer pair for amplifying the SNP site rs199894662 is shown in SEQ ID NOs. 13 to 14;

[0037] The nucleotide sequences of the primer pairs for amplifying the SNP site rs35509911 are shown in SEQ ID NOs. 15-16.

[0038] As a preferred embodiment of the present invention, it also includes a DNA extraction kit, reagents for PCR reaction and a sequencer.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention uses whole exome sequencing and further performs data analysis, and uses statistics and machine learning algorithms to screen out SNP sites that are highly correlated with type 2 diabetic nephropathy in the Chinese population. The SNP markers enrich and improve the relevant information of the genetic sites of type 2 diabetic nephropathy in the Chinese population, and construct a prediction model through Logistic regression analysis, so as to facilitate the prediction of the susceptibility of type 2 diabetic nephropathy in the individual to be tested. The model is suitable for the prediction, prevention, and individualized diagnosis and treatment of type 2 diabetic nephropathy patients in China, and provides a simple and effective auxiliary means for detecting the risk of type 2 diabetic nephropathy.

[0041] There is a connection between the multiple potential pathogenic sites disclosed in the present invention. By using a combination of SNP sites to comprehensively evaluate the importance of their relationship with the onset of type 2 diabetic nephropathy, the results are more accurate than the analysis of a single SNP site.

[0042] The present invention provides an application of primers for detecting SNP sites in the preparation of a product for assessing the risk of type 2 diabetic nephropathy, comprising a primer kit for detecting a combination of SNP sites associated with type 2 diabetic nephropathy, and judging the risk of type 2 diabetic nephropathy according to the genotypes of 8 SNP sites, which is easy to interpret and has high detection accuracy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0044] Figure 1 The present invention provides an importance chart of the 8 SNP sites that are important for the prediction performance of type 2 diabetic nephropathy in Example 1.

[0045] Figure 2 The present invention provides an ROC curve of the type 2 diabetic nephropathy risk prediction model constructed based on 8 SNPs in Example 1 in the type 2 diabetic nephropathy case-control group.

[0046] Figure 3 The present invention provides a schematic diagram of a detection kit for predicting the risk of developing type 2 diabetic nephropathy.

[0047] Figure 4 The present invention provides a ROC curve drawn using the prediction model for the validation set data in Example 2. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In order to enable the detection of relevant SNP site combinations for the Chinese population or use the method to predict the risk of type 2 diabetic nephropathy, the present invention provides a method for screening SNP markers and its use in preparing a product for assessing the risk of type 2 diabetic nephropathy.

[0050] The steps include:

[0051] (1) Establish a sample library and database with unified standards: Collect standard blood samples using standard operating procedures, collect complete demographic and clinical data, select type 2 diabetes and type 2 diabetic nephropathy cases that meet the standards, and extract genomic DNA.

[0052] (2) Whole exome sequencing and data analysis: To perform whole exome sequencing, specific probes are first designed for the target region, and then the target region of genomic DNA is captured through liquid phase chip hybridization, and then sequenced using a high-throughput sequencer.

[0053] After the data is downloaded, the image files obtained by sequencing are converted into FASTQ format files used for analysis, and the data quality is filtered. The high-quality reads obtained after filtering are compared with the human reference genome sequence (GRCh38), and finally the data results are subjected to variant detection, annotation, and harmful variant filtering.

[0054] (3) Screening out SNP sites associated with type 2 diabetic nephropathy: Calculate the gene frequency of each SNP mutation site in the type 2 diabetes and type 2 diabetic nephropathy groups, perform a chi-square test between the two groups, and screen 66 SNPs with a p-value less than 0.05.

[0055] (4) The above 66 SNPs were used as the input SNPs of the model, and the XGBoost model was used to further simplify the SNPs, and 25 SNP site combinations that were more important for the prediction performance of the model were screened out. Recursive Feature Elimination (RFE) was further combined with the XGB model to simplify the features, and the 8 SNP site combinations that were most important for predicting DKD were screened out.

[0056] (5) A prediction model was constructed through logistic regression analysis. Further analysis showed that the eight SNP combinations can be used for auxiliary diagnosis of type 2 diabetic nephropathy. The AUC of the prediction model was 0.859, the sensitivity was 0.809, and the specificity was 0.833.

[0057] (6) Prepare a SNP marker kit associated with the risk of type 2 diabetic nephropathy, comprising primers for the above 8 SNPs in the DNA of the subject's blood sample and other detection reagents. Specifically, the combination of this SNP, or the related diagnostic kit composed of the specific primers of these 8 SNPs is helpful for the auxiliary diagnosis of type 2 diabetic nephropathy.

[0058] The present invention performs whole exome sequencing on peripheral blood DNA of patients with type 2 diabetic nephropathy and patients with simple type 2 diabetes, screens out SNP sites with statistical differences between the two groups of patients, and further streamlines SNPs through the XGBoost model to screen out the SNP site combination that is most important for the predictive performance of type 2 diabetic nephropathy.

[0059] The present invention specifically provides SNP markers associated with the risk of type 2 diabetic nephropathy. The 25 SNP markers preliminarily screened out are: rs2504779 on the CD164L2 gene; rs140936221 on the ZNF717 gene; rs75405062 on the CYP2F1 gene; rs75085872 on the ZNF717 gene; rs112900131 on the TAS2R19 gene; rs200904145 on the HLA-DQA2 gene; rs199894662 on the TAS2R31 gene; rs35509911 on the KIR2DL1 gene; rs145349678 on the PDLIM2 gene; rs61745597 on the ZGRF1 gene; rs55638653 on the MUC21 gene; and rs145349678 on the PDLIM2 gene. rs76264750 on the C3 gene; rs63750447 on the MLH1 gene; rs79238130 on the CYP2F1 gene; rs145373249 on the ACR gene; rs143011384 on the RABL6 gene; rs118110471 on the SEC23IP gene; rs77067369 on the SSC4D gene; rs74425496 on the COL6A3 gene; rs3750674 on the ADARB2 gene; rs76524550 on the IQCF6 gene; rs79826323 on the FAM208B gene; rs116911833 on the TRIM7 gene; rs76861216 on the PABPC3 gene; rs76187047 on the ZGRF1 gene. The first 8 of them are the 8 most important loci for predicting DKD that were further screened.

[0060] The specific location and flanking sequences of each SNP site are shown in Table 1.

[0061] Table 1

[0062]

[0063]

[0064] How to obtain the SNP site combination is described in detail through examples.

[0065] Unless otherwise specified, the experimental methods used in the following examples are all conventional methods.

[0066] Unless otherwise specified, the materials and reagents used in the following examples can be obtained from commercial sources.

[0067] The specific embodiments of the present invention are described in detail below, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0068] The specific embodiments are as follows:

[0069] Embodiment 1:

[0070] 1. Selection of research subjects:

[0071] The selected research subjects were patients visiting the First Affiliated Hospital of Wannan Medical College. The research subjects were divided into type 2 diabetes group and type 2 diabetic nephropathy group.

[0072] The criteria for the type 2 diabetes group are to meet the diagnostic criteria for diabetes and exclude other types of diabetes, gestational diabetes, or special types of diabetes, with a history of diabetes for more than 10 years, urine microalbumin / urine creatinine <30 mg / g, and normal glomerular filtration rate;

[0073] The criteria for the type 2 diabetic nephropathy group were that the patients met the diagnostic criteria for diabetes and excluded other types of diabetes mellitus / gestational diabetes / special types of diabetes, had at least 2 urine protein+ or urine microalbumin / urine creatinine ≥ 300 mg / g, and excluded kidney disease caused by other reasons. A total of 60 patients with type 2 diabetes and 68 patients with type 2 diabetic nephropathy who met the criteria were used in this study.

[0074] 2. Extract peripheral venous blood according to conventional methods, further extract genomic DNA, and test the extracted DNA samples.

[0075] 3. After the extracted DNA samples are qualified, they are broken into about 180bp-280bp using a Covaris ultrasonic crusher, and the ends of the fragments are repaired and connectors are added to construct a DNA library. Before capture, the library is amplified by ligation-mediated PCR (LM-PCR) and the concentration of each sample is calculated to facilitate equal capture.

[0076] The amplified sample is hybridized with the biotin-labeled probe to form an exon region and probe complex. The complex obtained in the previous step is adsorbed by streptavidin-modified nanomagnetic beads, the beads are washed to remove the unbound sequences, and then the captured exon sequences are eluted. The captured sample is amplified again by LM-PCR. The relative enrichment multiple of the target region is estimated by qPCR, and the preparation for sequencing can be carried out after the quality control requirements are met. After the quality control is qualified, cluster preparation is carried out, and double-end sequencing is performed using the HiSeq sequencing platform.

[0077] 4. After the data is downloaded, the image files obtained by sequencing are first converted into FASTQ format files used for analysis. Before further analysis, the data quality needs to be filtered to remove sequences containing adapters and sequences containing too many "N" bases and low-quality bases. "N" bases refer to bases that cannot be read by the instrument. The high-quality reads obtained after filtering are compared with the human reference genome sequence (GRCh38). The software used for the comparison is BWA mem, and the redundant sequences in the result file are removed. A comprehensive evaluation is made on the data sequencing coverage area and sequencing data coverage depth.

[0078] 5. Use the variation detection tool to detect and filter the data. The software used for variation detection is GATK, and the filtering parameters are as follows: Application of GATK Quality Filters, variant keptif: (1) QualityDepth(QD)>2; (2) VQSLOD>0(Based on variants present in the HapMap(v3.3), 1000Genomes(Omni2.5 and Gold Standard Indels b37), and dbSNP144 databases); (3) Mapping Quality(MQ)>40; (4) Fisher test of strand bias(FS)<60; (5) MQRankSum>-12.5; (6) ReadPosRankSum>-8; (7) Genotype Quality(GQ)>5; (8) PolymorphismLikelihood(PL)value difference<30; (9) HaplotypeScore<13; finally, high-quality variation results were obtained.

[0079] 6. Results Notes:

[0080] ANNOVAR software was used to annotate the variant results. Generally speaking, there is one SNP site for every 1000 bases in the human genome, and most of them are common sites with a minor allele frequency (MAF) > 5%. These common SNPs are generally not the main pathogenic sites. SNPs in exonic and splicing regions were filtered again. The filtering parameters were as follows: Variant kept if: (1) Variants in Exons or Splice Sites as annotated using ANNOVAR; (2) Nonsynonymous_SNV; .; frameshift_insertion; frameshft_deletion; frameshift_

[0081] block_substitution; stopgain; stoploss; (3) Variants with a Minor AlleleFrequency < 5% as reported in available databases (1000Genomes and ESP6500 from NHLBI and ExAc); (4) SIFT ≤ 0.05; harmful variants that may cause changes in protein function are obtained.

[0082] 7. Calculate the gene frequency of each SNP mutation site in the type 2 diabetes and type 2 diabetic nephropathy groups, perform a chi-square test on the gene frequency of the mutation sites in the two groups, and screen 66 SNP sites with a p-value less than 0.05.

[0083] 8. The above 66 SNPs were used as the input SNPs of the model, and then the XGBoost model was used to further refine the SNPs, and the data set was randomly divided into a training set (75%) and a validation set (25%). First, the Bayesian optimizer was used to find the best parameters of an XGB model, and then the parameters were used to train the XGB model, and then the validation set was used to validate it, and the importance of each SNP was obtained from the results. It was found that 25 SNPs were important for the prediction performance of the model (see Table 1).

[0084] 9. We further simplified the features by combining Recursive Feature Elimination (RFE) with the XGB model. After multiple iterations, we found the 8 most important SNP loci combinations. The importance of the 8 SNP loci is shown in Figure 1 .

[0085] 10. In order to further evaluate the effect of the combination of these 8 SNP sites in predicting type 2 diabetic nephropathy, we constructed a prediction model through logistic regression analysis.

[0086] Prediction formula:

[0087] P=1 / (1+e^-(4.106-0.598*rs2504779+1.079*rs140936221+1.000*rs75405062-0.975*rs75 085872-2.293*rs112900131-1.930*rs200904145-0.677*rs199894662-1.069*rs35509911))

[0088] Among them, P represents the evaluation parameter of type 2 diabetic nephropathy susceptibility, rs# represents the genotype of each SNP site, and the value may be 0, 1 or 2. If the genotype is wild type, the value is 0; if the genotype is heterozygous mutation, the value is 1; if the genotype is pure and mutation, the value is 2. According to the above rules, the data value is substituted into the formula to calculate P, and the result value of P is constrained between 0 and 1.

[0089] According to the calculation results, in practical application, the qualitative overall assessment is: the Youden index of the regression model is 0.642, and the corresponding optimal diagnostic critical value is 0.57. Therefore, when the P value is less than or equal to 0.57, it is judged as not susceptible; when the P value is greater than 0.57, it is judged as susceptible.

[0090] ROC was drawn to evaluate the sensitivity and specificity of auxiliary diagnosis, and then to evaluate the ability of these SNPs to judge the onset of type 2 diabetic nephropathy. The AUC under this model was 0.859, the sensitivity was 0.809, and the specificity was 0.833. Figure 2 .

[0091] The SNP markers provided by the present invention enrich and improve the information related to the genetic loci of type 2 diabetic nephropathy in the Chinese population, and are suitable for the prediction, prevention, and individualized diagnosis and treatment of type 2 diabetic nephropathy patients in China. Considering the connection between multiple potential pathogenic sites, the present invention uses a combination of SNP sites to comprehensively evaluate the importance of their relationship with the onset of type 2 diabetic nephropathy, which is more accurate than the analysis results of a single SNP site.

[0092] In addition, the present invention also provides a primer and a primer combination for detecting a type 2 diabetic nephropathy susceptibility gene, wherein the primer and the primer combination are used to amplify the mutation site in the aforementioned mutation site combination.

[0093] The present invention provides an application of primers for detecting SNP sites in preparing a product for assessing the risk of type 2 diabetic nephropathy, including a primer kit for detecting a combination of SNP sites associated with type 2 diabetic nephropathy.

[0094] The primer kit includes amplification primers and amplification primer combinations. The primers are specifically shown in Table 2, which contains 8 primer pairs.

[0095] Table 2

[0096]

[0097] Among them, the nucleotide sequence of the primer pair for amplifying the SNP site rs2504779 is shown in SEQ ID NOs.1-2; the nucleotide sequence of the primer pair for amplifying the SNP site rs140936221 is shown in SEQ ID NOs.3-4; the nucleotide sequence of the primer pair for amplifying the SNP site rs75405062 is shown in SEQ ID NOs.5-6; the nucleotide sequence of the primer pair for amplifying the SNP site rs75085872 is shown in SEQ ID NOs.7-8; the nucleotide sequence of the primer pair for amplifying the SNP site rs112900131 is shown in SEQ ID NOs.9-10; the nucleotide sequence of the primer pair for amplifying the SNP site rs200904145 is shown in SEQ ID NOs.11-12; the nucleotide sequence of the primer pair for amplifying the SNP site rs199894662 is shown in SEQ ID NO.13-14; the nucleotide sequence of the primer pair for amplifying the SNP site rs35509911 is shown in SEQ ID NO.15-16.

[0098] The two nucleotide sequences in the primer pair refer to the upstream primer and the downstream primer respectively.

[0099] SEQ ID NO. 1 to 16 are all artificial sequences.

[0100] The present invention also provides a SNP marker kit associated with the risk of type 2 diabetic nephropathy, the kit containing the amplification primer combination for detecting the SNP marker as described above.

[0101] The kit is used to evaluate the importance of the relationship between SNP site combination and the onset of type 2 diabetic nephropathy by detecting SNP site combination, which is more accurate than the analysis result of a single SNP site. It should be noted that there is no particular limitation on the method of obtaining SNP site information based on amplification product and sequencing, and any method known in the art for obtaining SNP site information, such as PCR-RFLP method, TaqMan probe method, SNaPshot, LDR-PCR sequencing typing technology, flight mass spectrometry, etc., are all within the scope of protection of the present invention.

[0102] The preparation and operation procedures of the SNP marker kit are described in detail below.

[0103] The production and operation process of the SNP kit is based on PCR and sequencing technology. The kit consists of 8 small boxes, each of which corresponds to one SNP site in the 8-SNP site model for genotyping.

[0104] The kit contains a DNA extraction kit, a batch of SNP amplification primers and common reagents required for the corresponding PCR technology, such as: 2xTaq PCR Master Mix, ultrapure water, etc. These common reagents are well known to those skilled in the art (such as Figure 3 ).

[0105] The specific steps are as follows:

[0106] (1) Collect peripheral blood from the subject;

[0107] (2) Extraction of peripheral blood genomic DNA;

[0108] (3) PCR amplification of specific DNA fragments;

[0109] (4) sequencing the amplified product;

[0110] (5) Analyze the sequencing results and obtain the genotypes of the 8 SNP sites;

[0111] (6) Calculate the risk of type 2 diabetic kidney disease based on the genotypes of the eight SNP loci;

[0112] (7) Actively manage and prevent people at high risk of type 2 diabetic kidney disease.

[0113] Unless otherwise specified, the experimental methods used in the following examples are all conventional methods.

[0114] Unless otherwise specified, the materials and reagents used in the following examples can be obtained from commercial sources.

[0115] The specific embodiments of the present invention are described in detail below, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0116] The specific embodiments are as follows:

[0117] Embodiment 2:

[0118] The application of the SNP site provided by the present invention and the reagents used in the detection kit can all be purchased from the market. The primer sequence is synthesized by the company.

[0119] 1. Collect 2 ml of venous blood from the patient using a blood routine vacuum blood collection tube;

[0120] 2. Use TIANGEN's blood genomic DNA extraction kit to extract DNA (refer to the instructions for detailed steps).

[0121] 3. Configure the PCR reaction system, the detection system of 8 SNP sites, a total of 8 tubes, the reaction preparation is as follows: DNA template 1ul, upstream primer 1ul, downstream primer 1ul, 2xTaq PCR Master Mix 12.5ul, ultrapure water 9.5ul, according to the above reagent volumes to prepare 25ul of the reaction system. Place it on the PCR instrument, set the PCR parameters, and perform the PCR reaction.

[0122] 4. After purifying the PCR product obtained in the above step, the sequencing reaction, electrophoresis separation, data analysis and other steps are performed using an ABI 3500 sequencer to obtain the sequencing results.

[0123] 5. Use SnapGene software to compare the sequencing results and obtain the genotypes of the corresponding 8 SNP sites. For example, the SNP site typing results of a patient with type 2 diabetes are shown in Table 3.

[0124] 6. Assess the patient's risk of diabetic kidney disease based on the genotypes of 8 SNP loci.

[0125] Calculated by the formula:

[0126] P=1 / (1+e^-(4.106-0.598*2+1.079*1+1.000*1-0.975*0-2.293*1-1.930*05-0.677*1-1.069*0)), P=0.883, P>0.5, so the patient is at high risk of type 2 diabetic kidney disease.

[0127] Table 3

[0128]

[0129]

[0130] 7. Overall performance analysis of the prediction model: 30 patients with type 2 diabetes and 30 patients with type 2 diabetic nephropathy were selected as the validation set. The ROC curve was drawn using the above prediction model. The analysis showed that the AUC area of ​​the prediction model was 0.794. Figure 4 shown.

[0131] It can be seen that the detection kit and the above formula can be used to predict type 2 diabetic kidney disease with high accuracy, which is more accurate than the analysis results of a single SNP site and has practical application value.

[0132] The present invention is used to detect the SNP site combination associated with type 2 diabetic nephropathy, enriches and improves the information related to the genetic sites of type 2 diabetic nephropathy in the Chinese population, is suitable for the prediction, prevention, and individualized diagnosis and treatment of type 2 diabetic nephropathy patients in China, and provides an amplification primer kit for the SNP site combination associated with type 2 diabetic nephropathy, which is more accurate than the analysis results of a single SNP site.

[0133] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. Use of primers for detecting SNP sites in the preparation of products for assessing the risk of type 2 diabetic nephropathy, characterized in that: The SNP sites are: rs2504779 on the human CD164L2 gene; rs140936221 site on the human ZNF717 gene; rs75405062 on the human CYP2F1 gene; The rs75085872 site on the human ZNF717 gene; rs112900131 site on the human TAS2R19 gene; rs200904145 on the human HLA-DQA2 gene; rs199894662 on the human TAS2R31 gene; The rs35509911 site on the human KIR2DL1 gene.

2. A primer kit for detecting SNP site combinations associated with type 2 diabetic nephropathy, characterized in that: Includes the following 8 primer pairs or primer pair combinations: Primer pair for amplifying SNP site rs2504779; Primer pair for amplifying SNP site rs140936221; Primer pair for amplifying SNP site rs75405062; Primer pair for amplifying SNP site rs75085872; Primer pair for amplifying SNP site rs112900131; Primer pair for amplifying SNP site rs200904145; Primer pair for amplifying SNP site rs199894662; Primer pair for amplifying SNP site rs35509911.

3. A primer kit for detecting SNP site combinations associated with type 2 diabetic nephropathy according to claim 2, characterized in that: The nucleotide sequences of the primer pairs for amplifying the SNP site rs2504779 are shown in SEQ ID NOs. 1 to 2; The nucleotide sequence of the primer pair for amplifying the SNP site rs140936221 is shown in SEQ ID NOs. 3 to 4; The nucleotide sequences of the primer pairs for amplifying the SNP site rs75405062 are shown in SEQ ID NOs. 5 to 6; The nucleotide sequences of the primer pairs for amplifying the SNP site rs75085872 are shown in SEQ ID NOs. 7 to 8; The nucleotide sequences of the primer pairs for amplifying the SNP site rs112900131 are shown in SEQ ID NOs. 9 to 10; The nucleotide sequences of the primer pairs for amplifying the SNP site rs200904145 are shown in SEQ ID NOs. 11 to 12; The nucleotide sequences of the primer pairs for amplifying the SNP site rs199894662 are shown in SEQ ID NOs. 13 to 14; The nucleotide sequences of the primer pairs for amplifying the SNP site rs35509911 are shown in SEQ ID NOs. 15-16.

4. A primer kit for detecting SNP site combinations associated with type 2 diabetic nephropathy according to claim 2, characterized in that: It also includes a DNA extraction kit, reagents for PCR reactions, and a sequencer.

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