Genetic markers or kits for predicting the risk of gestational diabetes

Abstract

The present invention discloses genetic markers or kits for predicting the risk of gestational diabetes. A genetic marker or a combination thereof for predicting the risk of gestational diabetes, characterized in that the genetic marker is selected from any one of the following human genomic SNP loci: rs1393210449, rs4566357, rs13059843, rs147522534, rs10830962, rs11188519, rs3769644, rs11642441. The detection reagents and kits prepared from the markers and combinations provided by the present invention have high accuracy in detecting gestational diabetes, can accurately reflect the risk of predicting the occurrence of GDM. The detection results are reliable, the detection process is easy to operate, and high-risk pregnant women are intervened and regulated in advance to reduce the possibility of their later development into gestational diabetes, thereby improving the health level of women and children.

Description

Technical Field

[0001] The present invention belongs to the field of biological detection, and relates to genetic markers or kits for predicting the risk of gestational diabetes mellitus. Background Art

[0002] Gestational diabetes mellitus (GDM) is a condition of abnormal glucose metabolism that first occurs or is detected during pregnancy, and is a common pregnancy complication. The incidence of GDM in Chinese women has reached as high as 24.24%. Although the symptoms of GDM usually subside after childbirth, it can cause short-term and long-term health damage to the mother and her children, including an increased risk of type 2 diabetes and cardiovascular diseases, etc.

[0003] Existing studies have mainly focused on the detection of real-time metabolic markers in amniotic fluid and plasma in the first trimester of pregnancy, and the detection of single-site or oligosite genetic susceptibility. For example: Searching for GDM-related data in the Chinese patent database, the kit for detecting the genetic susceptibility of gestational diabetes mellitus in patent (201910383683.6) involves a total of 2 SNP sites, namely rs290487 of the TCF7L2 gene and rs10830963 of the MTNR1B gene. These two sites come from a retrospective study of the Chinese pregnant population, with 335 and 110 cases enrolled respectively. The relevant research was carried out separately for the 2 sites, and the results were generated separately, and the combined detection power and sensitivity for the real world of GDM genetic susceptibility after combination are unknown.

[0004] Currently, the multi-gene SNP markers used to detect the risk of gestational diabetes mellitus, as described in patents such as (CN 101967511A), etc., the relevant multi-gene SNP sites are summarized from the results of previous domestic and foreign scientific articles, lacking data basis specific to the Chinese population.

[0005] Another patent (CN 114236123 A) included pregnant women samples at 16 - 20 weeks, recruited 54 GDM samples and 57 healthy controls for RNA sequencing analysis of gene expression, and obtained a combination of 5 mRNA molecules and 6 lncRNA molecule markers. This technical platform relies on NGS high-throughput sequencing, with a relatively high cost, has not been implemented on a large scale clinically, and lacks large-scale prospective genomic-level database detection from the Chinese population cohort. The existing technology lacks a kit that can be used to detect the genetic susceptibility of GDM to screen out susceptible high-risk populations in the first trimester of pregnancy in a timely manner and take preventive measures for GDM in advance. Summary of the Invention

[0006] The purpose of the present invention is to provide genetic markers for predicting the risk of gestational diabetes mellitus in view of the above deficiencies of the prior art.

[0007] Another object of the present invention is to provide the use of a reagent for detecting the genetic marker or its combination.

[0008] Another object of the present invention is to provide a reagent kit for predicting the risk of gestational diabetes mellitus.

[0009] The object of the present invention can be achieved by the following technical solutions:

[0010] A genetic marker or its combination for predicting the risk of gestational diabetes mellitus, characterized in that the genetic marker is selected from any one of the following human genome SNP loci: rs1393210449, rs4566357, rs13059843, rs147522534, rs10830962, rs11188519, rs3769644, rs11642441.

[0011] Table 1: Nucleic acid sequence table of SNP polymorphic loci of each related gene of GDM;

[0012]

[0013]

[0014] Table 2. Design of SNP detection primer pairs according to SNP loci and flanking sequences

[0015]

[0016] Use of a reagent for detecting the genetic marker or its combination in the preparation of a reagent for predicting the risk of gestational diabetes mellitus.

[0017] As a preferred embodiment of the present invention, the reagent for detecting the genetic marker or its combination includes, but is not limited to, one or more of a DNA microarray or chip for detecting the genetic marker or its combination, specific PCR primers and / or probes, and targeted high-throughput sequencing reagents.

[0018] As a further preference of the present invention, the specific PCR primers for detecting rs1393210449 are as shown in SEQ ID NO.1 / SEQ ID NO.2, the specific PCR primers for detecting rs4566357 are as shown in SEQ ID NO.3 / SEQ ID NO.4, the specific PCR primers for detecting rs13059843 are as shown in SEQ ID NO.5 / SEQ ID NO.6, the specific PCR primers for detecting rs147522534 are as shown in SEQ ID NO.7 / SEQ ID NO.8, the specific PCR primers for detecting rs10830962 are as shown in SEQ ID NO.9 / SEQ ID NO.10, the specific PCR primers for detecting rs11188519 are as shown in SEQ ID NO.11 / SEQ ID NO.12, the specific PCR primers for detecting rs3769644 are as shown in SEQ ID NO.13 / SEQ ID NO.14, and the specific PCR primers for detecting rs11642441 are as shown in SEQ ID NO.15 / SEQ ID NO.16.

[0019] A reagent kit for predicting the risk of gestational diabetes mellitus, comprising reagents for detecting the genetic markers or their combinations as described above. The detection samples of the reagent kit include one or more of whole blood, oral exfoliated cells, saliva, urine, and amniotic fluid.

[0020] As a preference of the present invention, the reagents for detecting the genetic markers or their combinations include, but are not limited to, one or more of DNA microarrays or chips, specific PCR primers or probes, and targeted high-throughput sequencing reagents for detecting the genetic markers or their combinations as described above.

[0021] As a preference of the present invention, the reagent for detecting the genetic markers or their combinations is a specific PCR primer for detecting the SNP locus.

[0022] As a preference of the present invention, the specific PCR primers for detecting rs1393210449 are shown as SEQ ID NO.1 / SEQ ID NO.2, the specific PCR primers for detecting rs4566357 are shown as SEQ ID NO.3 / SEQ ID NO.4, the specific PCR primers for detecting rs13059843 are shown as SEQ ID NO.5 / SEQ ID NO.6, the specific PCR primers for detecting rs147522534 are shown as SEQ ID NO.7 / SEQ ID NO.8, the specific PCR primers for detecting rs10830962 are shown as SEQ ID NO.9 / SEQ ID NO.10, the specific PCR primers for detecting rs11188519 are shown as SEQ ID NO.11 / SEQ ID NO.12, the specific PCR primers for detecting rs3769644 are shown as SEQ ID NO.13 / SEQ ID NO.14, and the specific PCR primers for detecting rs11642441 are shown as SEQ ID NO.15 / SEQ ID NO.16.

[0023] Compared with the prior research technologies, the solution of the present invention solves the following problems:

[0024] Based on the National Key Research and Development Program - Research on the Effects of Environmental and Behavioral Factors on Embryonic Development and Pregnancy Based on Internal and External Exposure Monitoring, the Chinese Environmental and Genetic Factors Birth Cohort is established. On this basis, a nested case-control study on the effects of gene-environment interaction on embryonic development and pregnancy is carried out to screen and identify the susceptibility genes and gene-environment interactions related to diseases affecting embryonic development and pregnancy, and to establish a comprehensive disease risk prediction model.

[0025] The present invention identifies the risk of having gestational diabetes or related diseases by using a risk prediction model for gestational diabetes or related diseases, and the prediction model is comprehensively calculated by using various statistical methods based on the P value of the difference between groups and the odds ratio (OR) of the biomarker combination in the biological samples from pregnant women with diagnosed gestational diabetes or related diseases and healthy control pregnant women.

[0026] Beneficial effects:

[0027] Genetic factors are related to the etiology of GDM, but there are very limited reports on the systematic study of the relationship between genetic factors and GDM. Currently, there are only 6 reports on genome-wide association studies of GDM included in the GWAS Catalog database. The research of the present invention determines the risk factors and mechanisms at the genetic level of GDM in the Chinese population through multi-regional population cohort genomics research. The clinical information corresponding to 1728 qualified sequencing data was strictly screened (GDM group: clinically diagnosed only with GDM, without other pregnancy-related diseases such as preeclampsia and hypothyroidism; control group: clinically diagnosed without any pregnancy-related diseases), and a total of 1610 pieces of data were obtained, including 733 cases of GDM and 877 controls. The included samples have good homogeneity and are more conducive to controlling selection bias.

[0028] Based on the whole exome sequencing technology, the present invention successfully screened 8 single nucleotide polymorphism variations related to gestational diabetes by using nested case-control association analysis, providing important genetic markers for predicting the risk of gestational diabetes and providing evidence in the genetic direction for the early prevention of gestational diabetes.

[0029] The biological samples required for the present invention are from blood. Blood samples are the most easily obtained in clinical practice, have good stability and representativeness, and the results are reliable. In addition, blood tests in the first trimester of pregnancy are routine items for antenatal examinations, so the present invention will not increase the number of examinations for pregnant women additionally, and the compliance of the subjects is high, which is conducive to clinical promotion.

[0030] The present invention uses various analysis methods such as chi-square test, Fisher test, and logistic regression to perform association analysis on the sequencing results, and considers age and BMI information variables. Compared with previous studies on single loci or special gene regions, it can provide more information in the genetic direction for the diagnosis of gestational diabetes.

[0031] The kit of the present invention for detecting GDM-susceptible populations constructs a gene locus system for screening high-risk populations with polymorphisms of various genes related to GDM, can quickly and accurately detect various relevant SNPs of GDM in clinical samples, has a large throughput and high sensitivity, and is of great significance for the clinical diagnosis of GDM and the early screening and early prevention and intervention of high-risk populations, and can be widely used for the efficient screening of GDM high-risk populations in clinical practice.

[0032] The detection reagents and kits prepared from the markers and their combinations provided by the present invention have high accuracy in detecting gestational diabetes, can accurately reflect and predict the situation of GDM. The detection results are reliable, the detection process is easy to operate, and high-risk pregnant women are intervened and regulated in advance to reduce the possibility of their later development into gestational diabetes and thus improve their health level. Detailed implementation mode

[0033] Example 1

[0034] The screening method of genetic markers for predicting the risk of gestational diabetes mellitus in the present invention comprises the following steps:

[0035] 1) Based on a nested case-control study established from the China Environment and Genetics in Nongenetic Diseases (CEGS) Birth Cohort, the clinical information corresponding to 1,728 qualified sequencing data was strictly screened (GDM group: clinically diagnosed only with GDM, without other pregnancy-related diseases such as preeclampsia and hypothyroidism; control group: clinically diagnosed without any pregnancy-related diseases), and a total of 1,610 data were obtained, including 733 cases of GDM and 877 controls; general clinical data of the subjects were collected;

[0036] 2) The subjects completed an oral glucose tolerance test (OGTT) at 24-28 weeks of pregnancy. GDM was diagnosed according to the criteria of the International Association of Diabetes and Pregnancy Study Groups (IADPSG): fasting ≥ 5.1 mmol / L, 1 hour after glucose load ≥ 10.0 mmol / L, 2 hours after glucose load ≥ 8.5 mmol / L. Meeting one or more of these blood glucose values equal to or greater than the above levels was diagnosed as GDM;

[0037] 3) Blood samples of the subjects in the first trimester of pregnancy were collected;

[0038] 4) Blood DNA of the subjects in the first trimester of pregnancy was extracted;

[0039] 5) Whole exome sequencing was performed on the extracted DNA samples to obtain sequencing data;

[0040] 6) Chi-square test (multiple hypothesis testing correction), Fisher test and logistic model were used for association analysis; in the logistic analysis, P value correction was performed for age and BMI; secondary data quality control was performed using PCA, Hail and Plink, etc.; Hardy-Weinberg equilibrium test was performed;

[0041] 7) Take the intersection of the associated genes discovered by the above three analyses, and a total of 12 common genes corresponding to 16 loci are obtained: mainly MUC5AC (rs1393210449), COL4A4 (rs4566357, rs3769644), ACAP2 (rs13059843, rs147522534, rs57063250), MTNR1B (rs10830962), C10orf131 (rs11188519), SMG1 (rs11642441), PPP2CB (chr8:30651340), SERPINI1 (rs3811683), MUC16 (rs75101943), FCRL6 (rs11586456), ADAMTS7 (rs7495616), DMRTA1 (rs10811660, rs10811661); among them, MTNR1B (rs10830962) and DMRTA1 (rs10811660, rs10811661) are genetic association genes reported in the genomics research of GDM, indicating that our data analysis is relatively reliable. Retrieve and review the literature knowledge through multiple databases, and analyze the potential functions of related genes. The results are as follows (Table 3);

[0042] Table 3 List of GDM Genetic Candidate Loci (Top 16)

[0043]

[0044]

[0045] The most significantly associated locus with GDM is rs1393210449, and its corresponding gene is MUC5AC, which can compile an extracellular matrix structure - mucin and is a biomarker for various diseases such as Sjogren's syndrome, biliary tract diseases, cystic fibrosis, eye diseases, and pancreatic cancer. Insulin can promote its expression through the PI3K - AKT signaling pathway. MUC5AC is closely related to the O - linked glycosylation of mucin and protein and vitamin metabolism, and is involved in phosphatidylinositol - mediated signal transduction; it is the first genetic gene discovered to be related to GDM.

[0046] Previously reported, the rs4566357 locus is significantly associated with coronary heart disease, birth weight, etc. We first discovered its close association with GDM. The corresponding gene is COL4A4, which encodes one of the six subunits of type IV collagen and is a major structural component of the basement membrane. Mutations in this gene are related to autosomal recessive type II Alport syndrome (hereditary glomerulopathy) and familial benign hematuria (thin basement membrane disease).

[0047] The third GDM-related associated gene discovered in this study is ACAP2, which encodes the β-centaurin protein, plays a role in processes related to actin filaments, activates GTPase when binding to Rab35, participates in ADP-ribosylation factor 6 (Arf6) signaling, and may be related to the functions of immune cells. There have been no reports related to GDM so far, and its role in GDM remains to be further studied.

[0048] C10orf131, also known as CC2D2B (Coiled-Coil And C2 Domain Containing 2B), is located in the transition zone of cilia (the part where the base of the cilium connects to the cell body) and is predicted to participate in the assembly of non-motile cilia. Cilia are highly conserved organelles in cells, protruding from the cell surface and serving as the "signal antennas" of cells, responsible for sensing and transmitting extracellular physical, chemical, and biological signal stimuli. Cilia are involved in regulating various life activities of cells, and abnormalities in their structure and function can cause a series of human diseases such as congenital heart disease, obesity, and reproductive abnormalities.

[0049] MTNR1B encodes the melatonin receptor (Melatonin Receptor 1B) and is a member of the G protein-coupled receptor family. Melatonin receptors are present in many parts of the human body, including the brain, retina, cardiovascular system, liver, kidney, spleen, and intestine. The correlation of this gene with T2D and GDM has been confirmed by multiple studies, but the specific mechanism of action still needs to be explored more deeply. It may be closely related to the cyclic changes in the activity of melatonin in the body.

[0050] The full name of SMG1 is SMG1 Nonsense Mediated MRNA Decay Associated PI3K Related Kinase. This gene encodes a protein that participates in nonsense-mediated mRNA decay (NMD) and is part of the mRNA surveillance complex. This protein has serine / threonine protein kinase activity and is thought to play a role in NMD by phosphorylating nonsense transcript regulatory protein 1. It is related to the occurrence of tumor metastasis, liver cancer, pancreatic cancer, etc.

[0051] PPP2CB full name is Protein Phosphatase 2 Catalytic Subunit Beta. This gene encodes a beta isoform of the phosphatase 2 catalytic subunit, negatively regulates cell growth and division, is related to the MyD88 dependent cascade initiated on endosome and CTNNB1 S33 mutants aren't phosphorylated pathway, and inhibits PMA / ionomycin-induced T cell activation by negatively regulating the PI3K / Akt signal.

[0052] The rs3811683 locus is located in the promoter region of the SERPINI1 gene. SERPINI1 encodes neuroserpin, which is a member of the serine superfamily of serine protease inhibitors. This protein is mainly secreted by axons in the brain and first reacts with tissue-type plasminogen activator. It is thought to play a role in regulating axon growth and the development of synaptic plasticity and is related to the development and maintenance of the nervous system.

[0053] MUC16 also encodes a mucin that is present on the apical surface of epithelial cells and plays an important role in forming a protective mucus barrier to protect the body from pathogens. Recent studies have shown that in the gene network analysis of placental transcriptome sequencing in mice with gestational diabetes mellitus induced by a high-fat diet during pregnancy, this gene was found to be a core gene involved in GDM in placental tissue.

[0054] FCRL6 (Fc Receptor-Like Protein 7), located on the outer side of the plasma membrane, is involved in the cell surface receptor signaling pathway and is related to the regulation of CTL effector function in various immune diseases. Recent studies have shown that the methylation level of the CpG island in the corresponding region of this gene is closely related to fasting blood glucose.

[0055] 8) Add age and BMI information as covariates, include them in the analysis, and perform P-value correction to obtain 8 significantly associated loci, mainly gene loci related to glucose metabolism. Sort the loci according to the P-value (Table 4):

[0056] Table 4 Genetic loci significantly associated with GDM and pathogenic risks (adjusted for age and BMI)

[0057]

Claims

1. Use of a reagent for detecting a genetic marker combination for auxiliary prediction of the risk of gestational diabetes mellitus in the preparation of a reagent for auxiliary prediction of the risk of gestational diabetes mellitus, wherein the genetic marker combination for auxiliary prediction of the risk of gestational diabetes mellitus consists of the following genetic markers; rs1393210449 , rs4566357, rs13059843, rs147522534, rs11188519, rs3769644, rs11642441.

2. The application according to claim 1, wherein the reagent for detecting the genetic marker combination for the auxiliary prediction of the risk of gestational diabetes is selected from one or more of a DNA microarray or chip for detecting the genetic marker combination, specific PCR primers or probes, and targeted high-throughput sequencing reagents.

3. The application according to claim 2, wherein Detection rs1393210449 The specific PCR primers for detecting rs4566357 are shown as SEQ ID NO.1 / SEQ ID NO.

2. The specific PCR primers for detecting rs13059843 are shown as SEQ ID NO.3 / SEQ ID NO.

4. The specific PCR primers for detecting rs147522534 are shown as SEQ ID NO.5 / SEQ ID NO.

6. The specific PCR primers for detecting rs11188519 are shown as SEQ ID NO.7 / SEQ ID NO.

8. The specific PCR primers for detecting rs3769644 are shown as SEQ ID NO.11 / SEQ ID NO.

12. The specific PCR primers for detecting rs11642441 are shown as SEQ ID NO.13 / SEQ ID NO.14.

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