CN114427002B - Kit for evaluating risk of type 1 diabetes based on 22 SNP susceptibility sites - Google Patents
Kit for evaluating risk of type 1 diabetes based on 22 SNP susceptibility sites Download PDFInfo
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Abstract
The invention discloses 22 SNP markers related to auxiliary diagnosis of risk of type 1 diabetes mellitus, and develops an auxiliary diagnosis kit for type 1 diabetes mellitus, which is convenient for clinical application, and provides data support for finding novel small molecular drugs with potential therapeutic value.
Description
Technical Field
The invention belongs to the technical field of biological detection, and relates to a kit for evaluating the risk of type 1 diabetes based on 22 SNP loci.
Background
1. Type diabetes is a T cell mediated autoimmune disease characterized by the selective destruction of pancreatic beta cells. 1. The risk of onset of type diabetes is mainly composed of two parts, genetic and environmental. Wherein the genetic impact is estimated to be between 65% and 88%, and the risk of developing T1D is affected by a combination of genetic variations at multiple sites in the genome. Over the past few decades, extensive genetic studies have described more than 50 genetic loci that affect T1D susceptibility. One way to find genetic predictors for T1D, to convert genetic data into disease susceptibility predictors is to add the risk effects of loci to a Polygenic Risk Score (PRS). All common variations in the genome can explain a higher proportion of genetic effects in many complex traits than if only a small proportion of significant Single Nucleotide Polymorphisms (SNPs) were based. The use of PRS helps to screen out people at risk of developing disease while preventing the increase in morbidity and mortality associated with diabetes.
In recent years, there have been several research teams abroad that have formulated PRS for T1D. In linkage and whole genome association studies (GWAS) of genes including INS, PTPN22, CTLA-4, and IL2RA, non-HLAT 1D risk variants common in more than 60 genomes have been identified. Genetic prediction of T1D has evolved from the use of HLA alleles alone to the addition of non-HLA variants. 2014. In the years, winkler et al developed a multiple logistic regression model to estimate PRS, including 40 non-HLA gene SNPs, significantly improving risk scores. The team of Oram adjusted the log-additive PRS model to distinguish T1D patients from the control group. They applied T1D-PRSs for 30 SNPs to a panel of T1D populations. They found that T1D-PRS has a high discrimination capability, with an area under the curve of 0.88. However, most of the foreign research is performed in caucasian population, and the prediction model they design is not fully applicable to chinese population.
In addition to the prediction of risk of developing type 1 diabetes (T1D), genetic Risk Scores (GRS) have been widely used in recent years for diagnosis and differential diagnosis of type 1 diabetes, as well as for the identification of type 1D and type 2 diabetes, monogenic diabetes. The existing method for evaluating the T1D disease risk has the defects that firstly, when the T1D disease risk is evaluated through GRS, the influence of a plurality of genetic loci on the T1D disease risk is not comprehensively considered, and the evaluation result is not comprehensive enough. Secondly, the model is mostly derived from European Caucasian populations, and the same prediction efficiency cannot be achieved when the model is applied to Chinese populations due to the difference of susceptibility genes among species. Third, most of the current genetic risk prediction models are based on existing data, so that the problems of external verification are faced.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person of ordinary skill in the art.
Disclosure of Invention
The first object of the invention is to screen SNP with high specificity and sensitivity highly related to type 1 diabetes in Chinese population, the second object of the invention is to provide SNP marker related to auxiliary diagnosis of type 1 diabetes and application thereof, and the third object of the invention is to provide the SNP marker which can be used as molecular marker for auxiliary diagnosis application of type 1 diabetes.
In order to achieve the above purpose, the team searches a group of SNP with high specificity and sensitivity highly related to type 1 diabetes by detecting single nucleotide polymorphism in the peripheral blood DNA of type 1 diabetes patients and healthy controls matched with the patients, and develops an auxiliary diagnosis kit for type 1 diabetes, which is convenient for clinical application, provides data support for screening and diagnosis of type 1 diabetes, and provides data support for finding novel small molecular drugs with potential therapeutic value.
A SNP marker associated with the risk-assisted diagnosis of type 1 diabetes mellitus, characterized in that: the SNP markers are: the rs2816313 site near RGS1 gene has the sequence ACCCTTTGAGCTGAGTCTGGAGCCAGAGCT [ G/A ] CCAGGATGCAGACAGCAGTGTCCTGAGGCT; the rs12712067 locus near the AFF3 gene has a sequence of TCCCCATTGAGCAAAGGGACAGCTAAGGTG [ G/T ] TAGTGGGTGAGGGAGTACTGGTTAGAACTG; the rs4849135 locus on the ACOXL gene has a sequence of ACTTTATTACCAAGGATGGGAGGAAGAGGG [ T/G ] TTGGGCCAACAACTGGAAATCTTGCTACAC; the sequence of the site rs2111485 near the IFIH1 gene is CACCAGCATGGGGTCATAAATATAAAGCCT [ A/G ] GAAGGGTGGAATTTCCCTGAGGAAGAAGAA; the rs7582694 locus on STAT4 gene has the sequence of CACACCAAATTCATGAAGGGATGACACATA [ C/G ] AGTATGCAACCTATGCATGTTTGCTTGTTC; the rs3087243 locus near CTLA4 gene has the sequence of TGATTTCTTCACCACTATTTGGGATATAAC [ G/A ] TGGGTTAACACAGACATAGCAGTCCTTTAT; the rs62405743 site near RING1 gene has sequence CCAGCACTTTGGGAGGCTAAGGCCAATGGG [ T/C ] TACTTGAGGCCAGGAGTTCGAAACCAGCCT; the rs9294458 locus on the BACH2 gene has the sequence of GCAAACATGGTGAAACCCCATCTCTACTAA [ G/C ] ATTACAAAAATTAGCTGGGCATGGTGGCAT; the rs2179781 locus on AHI1 gene has sequence CCAGGACAGAGAAGTGAAGGATTTGGAAGA [ C/A ] AACACTGTAACTGTTAAAGAAAAATTTCTA; the rs735048 locus on GRB10 gene has sequence CCCAGACAAGAGACTGGAACTCAGTTCAAT [ A/G ] GGACGTTTCCCAAAGCGGCTAGGAGCTGAT; the rs4355801 locus near the TNFRSF11B gene has the sequence of AGCAGTAAACAGGTGTACAGGTCTCAATAA [ A/G ] TGGGTGGTAGGTGTCAGGGAAAGTCAGCTG; the rs1574285 locus on the GLIS3 gene has a sequence of ACACACACACACACAGGAATGCACTTTGCA [ G/T ] GATTGCAAAGCTAGCTCTTTACCTTCCAAG; the rs3802604 locus on the GATA3 gene has a sequence of CCTGCATGTTCAGTACATGAAAGTAGGCAG [ G/A ] AGGGAGAGGGAGGCAGGCTAGCTGGTGGAG; the rs2018705 locus on the RNLS gene has the sequence of TTAGTTCATTCTCACACTGCTATTAAGAAC [ T/A ] TCCCTGAGACTGGGTAATTTATAAAGAAAA; the rs3842752 locus near INS gene has sequence GCAGGAGGCGGCGGGTGTGGGGCTGCCTGC [ G/A ] GGCTGCGTCTAGTTGCAGTAGTTCTCCAGC; the locus rs17378105 of SLC1A2 gene has the sequence of AGGAGATCCACGTAAGCATTGGCTAAGAGC [ G/C ] TGAAGTCCGGATACCAGCCTGGATGACACT; the rs34415530 locus near the RPS26 gene has the sequence of ATTTTTTCTTCAATAATAAATTAACCTTAG [ C/T ] TTACTGTAACTTTTTTTTTCTTTCTTTTTT; the rs927292 locus on the ZFP36L1 gene has a sequence of ACTGGCTGACAAGCAACATGTTTTAAGGAG [ C/G ] CCCCCATTAAATCCTTACTCGCGGGACTCT; the rs4900384 locus near the VRK1 gene has the sequence of TAGGACACTTCTGTTTTAATCTCATGGACC [ A/G ] GAATGTAGTCACATAACCACATCCAGCTGT; the rs12928537 locus near IL2RA gene has the sequence of TTCCTTCTTTACCTGAATCATTAATGGCAA [ G/A ] GAGCACCGACACAGAACTGAGTTCAGGGCT; the rs8066541 locus near the SMARCE1 gene has the sequence of CAGGCTGGTCTTGAACTTCTGAACACAAGC [ G/A ] ATCCTCCTGCCTTGGCCTCCCAAAGTGCTG; the rs193477 locus on the HORMAD2 gene is the combination of AATGCCTGTAGTCCTAGCTACTTGTGAGGC [ C/T ] GAGGGAGGAGAATCGCTTGAGCCCAGGAGT.
Complex diseases reported by European populations were evaluated for cumulative locus risk (PRS) and were less predictive in other ethnic populations (Nat Genet.2019; 51 (4): 584-591;Am J Hum Genet. 2017; 100 (4): 635-649), PRS including European type 1 diabetes susceptibility sites, and were not significantly predictive in eastern Asian populations (Am J HumGlunet.2022; 109 (1): 12-23). Through the prior-stage GWAS data of the Chinese T1D crowd, only about 1/3 of the T1D susceptibility loci of the European crowd are related to susceptibility in the Chinese crowd, and each locus effect value has a certain difference with the European crowd. These indicate the importance of selecting the relevant sites of the Chinese crowd and the corresponding effect values on the T1D prediction of the Chinese crowd. The three new sites (rs 2179781, rs10117059 and rs 7184802) which are found in addition are critical to the effect of the T1D risk diagnosis kit, the AUC value of the ROC curve is obviously reduced from 0.809 to 0.696 by removing the three sites, and thus, a good prediction effect is not achieved.
Based on the T1D risk susceptibility of 22 SNP loci in the cross-race GWAS susceptibility loci, the team develops a T1DM risk prediction model suitable for the Chinese population, and the area under an AUC curve reaches 0.809.PRS is used as a new diagnostic tool, and the application of the PRS in the aspects of prediction, diagnosis, differential diagnosis, disease progress and the like of T1DM, especially T1DM of Chinese population is worthy of further research and development. The multigenic risk score (Polygenic risk score, PRS) considers each SNP in the form of a subvariant, i.e. applies a co-dominant model in the genetic model. Based on SNP loci screened by GWAS, designing a corresponding algorithm, synthesizing the pathogenic contribution rate of the loci, and establishing a proper scoring prediction model. The method has the advantages that the connection among a plurality of potential pathogenic sites is considered, and the data of a big database such as Biobank is used for testing, so that the prediction accuracy is greatly improved finally.
A primer combination for amplifying the SNP markers described above, the primer combination comprising specific amplification primers, the primers specifically being:
the rs2816313 locus is: using human genome DNA as a template, and adopting a primer pair 1 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or A;
the rs12712067 locus is: using human genome DNA as a template, and adopting a primer pair 2 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or T;
the rs4849135 locus is: using human genome DNA as a template, and adopting a primer pair 3 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is T or G;
the rs2111485 locus is: using human genome DNA as a template, and adopting a primer pair 4 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is A or G;
the rs7582694 locus is: using human genome DNA as a template, and adopting a primer pair 5 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is C or G;
the rs3087243 locus is: using human genome DNA as a template, and adopting a primer pair 6 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or A;
the rs62405743 locus is: using human genome DNA as a template, and adopting a primer pair 7 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is T or C;
the rs9294458 locus is: using human genome DNA as a template, and adopting a primer pair 8 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or A;
the rs2179781 locus is: using human genome DNA as a template, and adopting a primer pair 9 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is C or A;
the rs735048 locus is: using human genome DNA as a template, and adopting a primer pair 10 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is A or C;
the rs4355801 locus is: using human genome DNA as a template, and adopting a primer pair 11 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is A or G;
the rs1574285 locus is: using human genome DNA as a template, and adopting a primer pair 12 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or T;
the rs3802604 locus is: using human genome DNA as a template, and adopting a primer pair 13 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or T;
the rs2018705 locus is: using human genome DNA as a template, and adopting a primer pair 14 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is T or G;
the rs3842752 locus is: using human genome DNA as a template, and adopting a primer pair 15 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or A;
the rs17378105 locus is: using human genome DNA as a template, and adopting a primer pair 16 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or C;
the rs34415530 locus is: using human genome DNA as a template, and adopting a primer pair 17 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is C or T;
the rs927292 locus is: using human genome DNA as a template, and adopting a primer pair 18 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is C or G;
the rs4900384 locus is: using human genome DNA as a template, and adopting a primer pair 19 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is A or G;
the rs12928537 locus is: using human genome DNA as a template, and adopting a primer pair 20 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or A;
the rs8066541 locus is: using human genome DNA as a template, and adopting a primer pair 21 to carry out PCR amplification to obtain an amplification product; the nucleotide of the locus is G or A;
the rs193477 locus is: using human genome DNA as a template, and adopting a primer pair 22 to carry out PCR amplification to obtain an amplification product; the nucleotide of the site is C or T.
The use of the primer combination described above for the preparation of a type 1 diabetes mellitus risk auxiliary diagnostic kit.
A type 1 diabetes risk-assisted diagnosis-related SNP marker kit comprising a specific amplification primer combination for detection of a SNP marker as described hereinbefore.
Preferably, in the above technical scheme, the kit further comprises enzymes and reagents for PCR reaction.
Compared with the prior art, the invention has the following beneficial effects:
the SNP marker provided by the invention is used as a marker for assisting in judging type 1 diabetes, and has the advantages that:
(1) In consideration of the connection among a plurality of potential pathogenic sites, the data of a big database such as Biobank and the like is used for testing, and finally, the prediction accuracy is greatly improved.
(2) The related information of the type 1 diabetes genetic locus of Chinese people is enriched and perfected.
(3) The diagnosis of the type 1 diabetes mellitus can be more convenient and easy to implement by the kit prepared by the SNP spectrum related to the type 1 diabetes mellitus. Lays a foundation for clinicians to quickly and accurately master the disease condition of patients, evaluates the clinical treatment effect, and provides help for finding novel small molecule drug targets with potential treatment value.
Drawings
Fig. 1, ROC curves in a type 1 diabetes case control group based on PRS of 22 SNPs, with auc=0.809.
Figure 2, differentiation of PRS based on 22 SNPs in the type 1 diabetes case control group, P values <0.0001 before both groups.
Detailed Description
The following detailed description of specific embodiments of the invention is, but it should be understood that the invention is not limited to specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the term "comprise" or variations thereof such as "comprises" or "comprising", etc. will be understood to include the stated element or component without excluding other elements or components.
The technical scheme for solving the problems comprises the following steps: (1) establishing a unified standard specimen library and database: standard-compliant blood samples were collected with standard procedures (SOP) and the system collected complete demographic and clinical data. (2) genotype detection: and selecting type 1 diabetes cases and healthy controls matched with the ages and sexes of the type 1 diabetes cases, and finding out SNP related to the type 1 diabetes in the whole genome range by utilizing a high-density SNP chip. (3) development of type 1 diabetes auxiliary diagnostic kit: SNP development auxiliary diagnosis kit according to SNP with significant difference of genotype distribution frequency in type 1 diabetes cases and healthy controls. The inventors collected standard-compliant blood samples with standard procedure (SOP), collected complete demographic, clinical data, etc. by the system, and performed full genome scans using a humanniz onghua-8 loadchip.
In particular, the experimental method studied mainly comprises the following parts:
1. selection of study samples
(1) Clinically definite type 1 diabetes mellitus and normal non-diabetes mellitus patients with normal blood sugar;
(2) Healthy controls matched to case age, sex;
the study was conducted using a total of 1257 normal and 1005 type 1 diabetic samples that meet the criteria.
2. Extracting peripheral blood genome DNA, and operating according to a conventional method. Usually can obtain 20-50 ng/mu l DNA with purity
(ratio of ultraviolet 260OD to 280 OD) is 1.6-2.0. 3. HumanOmni ZhONgHua 8BeadChip chip detection
(1) Taking a whole genome DNA sample of a subject;
(2) Performing genome-wide scanning on a HumanOmni ZhONgHua-8BeadChip chip;
(3) Differences in the distribution of genotypes in 1005 of type 1 diabetes versus 1257 of euglycemic control populations were detected and compared.
4. Statistical analysis method
Differences in distribution among groups of study subjects, such as demographic characteristics, are compared using chi-square test (for classification variables) or student t-test (for continuity variables). And performing association analysis by using an additive model in logistic regression analysis.
To further investigate the effect of the combined index of 22 SNPs for early diagnosis, we constructed a mathematical formula that comprehensively considers the positive association and the strength of the association of each SNP with T1D pathogenesis. Specifically, we score three genotypes of each SNP, protect homozygous = "0", heterozygote = "1", dangerous homozygous = "2", and determine a dangerous score for each subject by comprehensively considering the situation of each SNP with the regression coefficient under the additive model at the time of single SNP analysis as the weight. The risk score was calculated as follows: risk score = (score of 0.xx×rsxxx) +. . . . . The risk score coefficient obtained and the threshold value were directly applied to 2262 samples of the whole genome correlation study. ( Taking rs3802604 as an example: 0.295 Regression coefficients for rsxxxx; scoring rs3802604, protecting homozygosity= "0", heterozygosity= "1", dangerous homozygosity= "2", genotype of a certain SNP is determined by instrument detection result; the total score of a sample is the sum of the individual scores of the SNPs, and the genotype of a single SNP is only one intermediate process of calculating the score, and a specific cause is not required to be known. )
Statistical analysis was done by specialized statistical analysis software (snpetet v 2.5). The P-value for the statistical significance level was set to 0.01 and all statistical tests were double-sided.
5. Diagnostic kit preparation method
And (3) determining SNP with obvious difference between genotype distribution frequency in the type 1 diabetes case and the healthy control after carrying out whole genome scanning and single SNP detection by using a HumanOmni ZhONgHua-8BeadChip chip, and taking the SNP as an index of type 1 diabetes diagnosis. Finally, the screened SNP related to the onset of type 1 diabetes constitutes an auxiliary diagnosis kit. Diagnosis of
The reagents may include specific primers for these SNPs, taq enzyme, dNTP, etc.
The invention is further illustrated below:
of the 1005 eligible type 1 diabetes cases and 1257 healthy controls described above, the two groups were age-balanced. We performed whole genome scans of both groups of people using the HumanOmni ZhONgHua-8BeadChip chip to obtain relevant results. According to the HumanOmni ZhONgHua-8BeadChip chip test, the SNPs in which the difference in genotype distribution frequency was detected in the "type 1 diabetes case" group and the "healthy control" group according to the present invention include: the rs2816313 site near RGS1 gene has the sequence ACCCTTTGAGCTGAGTCTGGAGCCAGAGCT [ G/A ] CCAGGATGCAGACAGCAGTGTCCTGAGGCT; the rs12712067 locus near the AFF3 gene has a sequence of TCCCCATTGAGCAAAGGGACAGCTAAGGTG [ G/T ] TAGTGGGTGAGGGAGTACTGGTTAGAACTG; the rs4849135 locus on the ACOXL gene has a sequence of ACTTTATTACCAAGGATGGGAGGAAGAGGG [ T/G ] TTGGGCCAACAACTGGAAATCTTGCTACAC; the sequence of the site rs2111485 near the IFIH1 gene is CACCAGCATGGGGTCATAAATATAAAGCCT [ A/G ] GAAGGGTGGAATTTCCCTGAGGAAGAAGAA; the rs7582694 locus on STAT4 gene has the sequence of CACACCAAATTCATGAAGGGATGACACATA [ C/G ] AGTATGCAACCTATGCATGTTTGCTTGTTC; the rs3087243 locus near CTLA4 gene has the sequence of TGATTTCTTCACCACTATTTGGGATATAAC [ G/A ] TGGGTTAACACAGACATAGCAGTCCTTTAT; the rs62405743 site near RING1 gene has sequence CCAGCACTTTGGGAGGCTAAGGCCAATGGG [ T/C ] TACTTGAGGCCAGGAGTTCGAAACCAGCCT; the rs9294458 locus on the BACH2 gene has the sequence of GCAAACATGGTGAAACCCCATCTCTACTAA [ G/C ] ATTACAAAAATTAGCTGGGCATGGTGGCAT; the rs2179781 locus on AHI1 gene has sequence CCAGGACAGAGAAGTGAAGGATTTGGAAGA [ C/A ] AACACTGTAACTGTTAAAGAAAAATTTCTA; the rs735048 locus on GRB10 gene has sequence CCCAGACAAGAGACTGGAACTCAGTTCAAT [ A/G ] GGACGTTTCCCAAAGCGGCTAGGAGCTGAT; the rs4355801 locus near the TNFRSF11B gene has the sequence of AGCAGTAAACAGGTGTACAGGTCTCAATAA [ A/G ] TGGGTGGTAGGTGTCAGGGAAAGTCAGCTG; the rs1574285 locus on the GLIS3 gene has a sequence of ACACACACACACACAGGAATGCACTTTGCA [ G/T ] GATTGCAAAGCTAGCTCTTTACCTTCCAAG; the rs3802604 locus on the GATA3 gene has a sequence of CCTGCATGTTCAGTACATGAAAGTAGGCAG [ G/A ] AGGGAGAGGGAGGCAGGCTAGCTGGTGGAG; the rs2018705 locus on the RNLS gene has the sequence of TTAGTTCATTCTCACACTGCTATTAAGAAC [ T/A ] TCCCTGAGACTGGGTAATTTATAAAGAAAA; the rs3842752 locus near INS gene has sequence GCAGGAGGCGGCGGGTGTGGGGCTGCCTGC [ G/A ] GGCTGCGTCTAGTTGCAGTAGTTCTCCAGC; the locus rs17378105 of SLC1A2 gene has the sequence of AGGAGATCCACGTAAGCATTGGCTAAGAGC [ G/C ] TGAAGTCCGGATACCAGCCTGGATGACACT; the rs34415530 locus near the RPS26 gene has the sequence of ATTTTTTCTTCAATAATAAATTAACCTTAG [ C/T ] TTACTGTAACTTTTTTTTTCTTTCTTTTTT; the rs927292 locus on the ZFP36L1 gene has a sequence of ACTGGCTGACAAGCAACATGTTTTAAGGAG [ C/G ] CCCCCATTAAATCCTTACTCGCGGGACTCT; the rs4900384 locus near the VRK1 gene has the sequence of TAGGACACTTCTGTTTTAATCTCATGGACC [ A/G ] GAATGTAGTCACATAACCACATCCAGCTGT; the rs12928537 locus near IL2RA gene has the sequence of TTCCTTCTTTACCTGAATCATTAATGGCAA [ G/A ] GAGCACCGACACAGAACTGAGTTCAGGGCT; the rs8066541 locus near the SMARCE1 gene has the sequence of CAGGCTGGTCTTGAACTTCTGAACACAAGC [ G/A ] ATCCTCCTGCCTTGGCCTCCCAAAGTGCTG; the rs193477 locus on the HORMAD2 gene is the combination of AATGCCTGTAGTCCTAGCTACTTGTGAGGC [ C/T ] GAGGGAGGAGAATCGCTTGAGCCCAGGAGT. The analysis result of the multi-factor Logistic regression statistical method shows that the 22 SNPs are obviously related to the onset of type 1 diabetes.
Further analysis of the effect of these 22 SNP combinations on type 1 diabetes diagnosis revealed that the combinations could well distinguish cases from controls, as shown in figure 2.
According to the experimental results, a kit for auxiliary diagnosis of type 1 diabetes is prepared, and comprises specific primers for determining the SNP in DNA of a blood sample of a subject and other detection reagents. Specifically, the combination of the SNP or the relevant diagnosis kit formed by the specific primers of the 22 SNP is beneficial to the auxiliary diagnosis of the type 1 diabetes, and provides support for a clinician to quickly and accurately grasp the disease state and the disease severity of a patient and timely take more personalized control schemes.
1. Sample collection and sample data sorting
1. Selection of study samples: (1) clinically definite type 1 diabetes; (2) Healthy controls matched with the age and sex of the cases, and the system collects the demographics, clinical data and the like of the samples.
2. Whole genome scanning of SNPs in peripheral blood DNA
Of 1005 type 1 diabetics and 1257 healthy controls, the two groups were age, sex matched. And detecting the two groups of people through a HumanOmni ZhONgHua-8BeadChip chip to obtain a related result. The method comprises the following specific steps:
1. the hemolysis reagent was added to the white blood cells stored in the 2ml cryopreservation tube and mixed upside down.
2. Removing red blood cells: the tube was filled to 4ml with hemolysis reagent, mixed upside down, 4000r,10min and the supernatant discarded. To the precipitate was added 4ml of a hemolysis reagent, and the mixture was again washed once again with inversion, 4000r,10min, and the supernatant was discarded.
3. Extracting DNA: to the precipitate, 1ml of extract (122.5 ml of 0.2M sodium chloride, 14.4ml of 0.5M ethylenediamine tetraacetic acid, 15ml of 10% sodium dodecyl sulfate, 148.1. 148.1 ml double distilled water, the same applies below) and 8. Mu.l of proteinase K were added, and the mixture was thoroughly mixed by shaking on a shaker, and water-bath was carried out at 37℃overnight.
4. Protein removal: 1ml of saturated phenol was added and thoroughly mixed (hand-shake 15 min), centrifuged at 4000rpm for 10min, and the supernatant was transferred to a new 5ml centrifuge tube. Adding the mixture of chloroform and isoamyl alcohol into the supernatant, mixing thoroughly (shaking for 15 min), and taking the supernatant at 4000r for 10min.
5. DNA precipitation: adding 60 μl of sodium acetate into the supernatant, adding ice absolute ethyl alcohol with the same volume as the supernatant, and slightly shaking up and down to obtain white flocculent precipitate, 12000r, and 10min.
6. DNA washing: 1ml of ice absolute ethanol was added to the precipitate, 12000r was added for 10min, and the supernatant was discarded and dried.
7. Measuring the concentration: generally, 20-50ng/μl DNA can be obtained, and the purity (the ratio of ultraviolet 260OD to 280 OD) is 1.6-1.8.
8. Whole genome scanning was performed: full genome scans were performed on a HumanOmni ZhONgHua-8BeadChip chip.
9. Data analysis and processing: SNPs found in the "type 1 diabetes case" group and the "healthy control" group with significant differences in genotype distribution frequency were listed above, and the results are shown in table 1.
3. According to the results, the genotype distribution frequencies of two groups of samples (the 'type 1 diabetes case group' and the 'healthy control group') are compared, positive associated SNPs are selected, a single SNP regression coefficient in a whole genome scanning sample is taken as a weight, a risk score is further obtained, ROC is drawn to evaluate the predicted sensitivity and specificity, and the judgment capability of the SNPs on the type 1 diabetes onset is further evaluated. Joint analysis of 22 SNP markers found that these 22 SNPs separated the healthy control group from the group of type 1 diabetes cases with an AUC of 0.809, sensitivity at the best critical point (PRS value 10.58) was 0.724, specificity: 0.641. thus, we demonstrate that the rs2816313 locus near the RGS1 gene is employed; rs12712067 locus near AFF3 gene; an rs4849135 locus on the ACOXL gene; an rs2111485 site near the IFIH1 gene; the rs7582694 locus on the STAT4 gene; the rs3087243 site near the CTLA4 gene; the rs62405743 locus near the RING1 gene; an rs9294458 locus on the BACH2 gene; an rs2179781 locus on the AHI1 gene; the rs735048 locus on the GRB10 gene; an rs4355801 site near the TNFRSF11B gene; the rs1574285 locus on the GLIS3 gene; an rs3802604 locus on the GATA3 gene; an rs2018705 site on the RNLS gene; rs3842752 locus near INS gene; locus rs17378105 on SLC1A2 gene; the rs34415530 locus near the RPS26 gene; the rs927292 locus on the ZFP36L1 gene; rs4900384 locus near VRK1 gene; rs12928537 locus near IL2RA gene; rs8066541 locus near SMARCE1 gene; the combination of the rs193477 locus on the HORMAD2 gene is able to distinguish well between healthy controls and type 1 diabetics.
4. Preparation of SNP kit for auxiliary diagnosis of type 1 diabetes
The preparation and operation flow of the SNP kit are based on the HumanOmni ZhONgHua-8BeadChip chip detection and Sequenom MassARRAY genotyping technology. The kit contains a batch of SNP specific amplification primers and the usual reagents required for the corresponding PCR technique, such as: dNTPs, mgCl2, double distilled water, fluorescent probes, taq enzyme, etc., which are commonly used reagents are well known to those skilled in the art, and standards and controls (such as genotyping standards and blank controls, etc.) may be used. The kit has the value that only peripheral blood is needed without other tissue samples, SNP is detected by the simplest and specific primers, and the type 1 diabetes is judged in an auxiliary way by the SNP spectrum, so that the kit is stable, convenient and accurate to detect, and the sensitivity and the specificity of disease diagnosis are greatly improved, and therefore, the kit is put into practice, and can help to guide diagnosis and more effective individuation treatment.
TABLE 1, 22 SNP locus related primer sequences of type 1 diabetes susceptibility genes
The foregoing descriptions of specific exemplary embodiments of the present invention are presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain the specific principles of the invention and its practical application to thereby enable one skilled in the art to make and utilize the invention in various exemplary embodiments and with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.
Sequence listing
<110> Jiangsu province people's hospital (first affiliated hospital of Nanjing medical university)
<120> kit for assessing risk of developing type 1 diabetes based on 22 SNP loci
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<170> SIPOSequenceListing 1.0
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gagacatgcg tatgggaatc 20
<210> 2
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 2
cagcctggtt gggaattatg 20
<210> 3
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 3
cagccctagc tgtatctaag 20
<210> 4
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 4
ttttgtgggc ttggccaagg 20
<210> 5
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 5
ctgagatggt tgggactaag 20
<210> 6
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 6
gctttagcag ctgactttcc 20
<210> 7
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 7
cttggaaggt atccatcctc 20
<210> 8
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 8
cctgtgttaa acagcatgcc 20
<210> 9
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 9
tagagtccgg atgcggttag 20
<210> 10
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 10
tttgactcca ccagctagcc 20
<210> 11
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 11
tattccatct ctctcggtgc 20
<210> 12
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 12
gtggaacaat gctgtaccag 20
<210> 13
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 13
atcaactcag gccaggcata 20
<210> 14
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 14
tggccaggct ggtttcgaac 20
<210> 15
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 15
gtcccgcgag taaggattta 20
<210> 16
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 16
ttaaaccgca gtcctggaac 20
<210> 17
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 17
ttaaaccgca gtcctggaac 20
<210> 18
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 18
cttgagctgg gagtgtcatc 20
<210> 19
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 19
tctctcctga tgtcccttag 20
<210> 20
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 20
tggcaatact cctggctaag 20
<210> 21
<211> 26
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 21
ccaatagtct aatagcaagg gatatg 26
<210> 22
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 22
gccatttgga actgtgagtc 20
<210> 23
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 23
cacaccaaat tcatgaaggg 20
<210> 24
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 24
ataatcagga gagaggagtc 20
<210> 25
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 25
accttatcag ctcctagccg 20
<210> 26
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 26
ggcccgcatc aattaattcc 20
<210> 27
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 27
cctccatgca aatatatgcg 20
<210> 28
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 28
ggcagatact tggaaggtaa 20
<210> 29
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 29
cttcttcctc agggaaattc 20
<210> 30
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 30
ctagactacc agtctaaggc 20
<210> 31
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 31
gtgacaagag taagaccctg 20
<210> 32
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 32
ccgtgctcag caaatttgtt 20
<210> 33
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 33
aaatagagac agggtcttgc 20
<210> 34
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 34
ttaaggccaa gtctcagcac 20
<210> 35
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 35
acgtgtagca agatttccag 20
<210> 36
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 36
ttgggttagt tagtggctcc 20
<210> 37
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 37
aatcatagct cactgcaggg 20
<210> 38
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 38
agccaggcat ggtggtgaat 20
<210> 39
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 39
caagccagga cagagaagtg 20
<210> 40
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 40
tgaactggtt tgggggtaag 20
<210> 41
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 41
catccccggg agttaattag 20
<210> 42
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 42
ttccttccct gccctattat 20
<210> 43
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 43
caccatgccc agctaatttt 20
<210> 44
<211> 20
<212> DNA
<213> Artificial sequence (Artificial Sequence)
<400> 44
gcaggcagat cacttgaggt 20
Claims (4)
1. A primer set for amplifying SNP markers, characterized by: the nucleotide sequence of the primer combination is shown as SEQ ID NO.1-44, and the SNP marker consists of a site rs2816313, a site rs12712067, a site rs4849135, a site rs2111485, a site rs7582694, a site rs3087243, a site rs62405743, a site rs9294458, a site rs2179781, a site rs735048, a site rs4355801, a site rs1574285, a site rs3802604, a site rs2018705, a site rs3842752, a site rs17378105, a site rs34415530, a site rs927292, a site rs4900384, a site rs12928537, a site rs8066541 and a site rs 193477.
2. Use of the primer combination of claim 1 for the preparation of a type 1 diabetes mellitus risk auxiliary diagnostic kit.
3. A detection kit for SNP markers related to auxiliary diagnosis of risk of type 1 diabetes mellitus, which is characterized in that: the kit comprising the primer combination for amplifying a SNP marker according to claim 1.
4. A test kit according to claim 3, wherein: the kit also comprises enzymes and reagents for PCR reaction.
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| CN107271532A (en) * | 2017-06-28 | 2017-10-20 | 青梧桐（吉林省）生物科技有限公司 | Distinguish the SNP marks and kit of 1 type and diabetes B |
| WO2019002364A1 (en) * | 2017-06-28 | 2019-01-03 | Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH) | Method for determining the risk to develop type 1 diabetes |
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| WO2008112898A2 (en) * | 2007-03-13 | 2008-09-18 | The Children's Hospital Of Philadelphia | Genetic alterations on chromosome 12 and methods of use thereof for the diagnosis and treatment of type 1 diabetes |
| AU2009246134B2 (en) * | 2008-05-16 | 2016-03-03 | The Children's Hospital Of Philadelphia | Genetic alterations on chromosomes 21q, 6q and 15q and methods of use thereof for the diagnosis and treatment of type I diabetes |
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| CN107271532A (en) * | 2017-06-28 | 2017-10-20 | 青梧桐（吉林省）生物科技有限公司 | Distinguish the SNP marks and kit of 1 type and diabetes B |
| WO2019002364A1 (en) * | 2017-06-28 | 2019-01-03 | Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH) | Method for determining the risk to develop type 1 diabetes |
| CN111065749A (en) * | 2017-06-28 | 2020-04-24 | 德国亥姆霍兹慕尼黑中心健康与环境研究中心（有限公司） | Method for determining the risk of developing type 1diabetes |
Non-Patent Citations (3)
| Title |
|---|
| 1型糖尿病易感基因研究进展;蔡庸昭;李才锐;孙曙光;;世界最新医学信息文摘;15(86);28-30 * |
| PTPN22、CTLA-4基因多态性与1型糖尿病发病的关联研究;陈秀丽;江苏省第十三次儿科学学术会议论文集;188-189 * |
| Reduced GLP-1 response to a meal is associated with the CTLA4 rs3087243 G/Ggenotype;ANDRÁS ZÓKA等;Centr Eur J Immunol;第44卷(第3期);299-306 * |
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