A kit for predicting the risk of gestational diabetes

Abstract

The present invention discloses a biomarker for predicting the risk of gestational diabetes and a detection kit. Based on the Chinese Birth Cohort Study on Environment and Genetic Factors, through a nested case-control study, the present invention analyzes mitochondrial genome sequencing data, successfully screens out mitochondrial gene variations associated with gestational diabetes, and designs a kit that can be used for predicting the risk of gestational diabetes, providing a new genetic biomarker for the early diagnosis and treatment of gestational diabetes, and laying a foundation for guiding the early diagnosis of gestational diabetes and establishing an individualized medical prevention and treatment plan.

Description

Technical Field

[0001] The present invention belongs to the field of biological detection and relates to a kit 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. GDM is a metabolic disease characterized by insulin resistance and pancreatic islet β-cell dysfunction. Mitochondria, as the main energy-providing organelles of cells, are involved in maintaining normal cellular metabolic balance. Therefore, mitochondrial function affects normal energy metabolism and ATP supply within cells and may lead to the occurrence of metabolic diseases. Mitochondria have a genetic system independent of the nuclear genome - mitochondrial DNA (mtDNA). Any quantitative or qualitative defects in mitochondrial DNA may determine changes in mitochondrial function and have a negative impact on cellular bioenergy. Previous studies have confirmed that mtDNA variations are associated with the development of GDM.

[0003] There is insufficient research on the correlation between GDM and mitochondrial variations, the research sample size is small, and there is a lack of analysis of the entire mitochondrial genome. A patent (CN 112143803 A) included pregnant women at 24 - 28 weeks, including 204 pregnant women with gestational diabetes mellitus and 220 normal pregnant women, and sequenced and analyzed the 16189 site in the D-loop region. This technology lacks large-scale prospective whole mitochondrial genome-level detection data from a Chinese population cohort. Based on this, screening genetic markers related to GDM from the entire mitochondrial genome is of profound significance for determining the relationship between mitochondrial genes and the risk of GDM in Chinese Han female population, further revealing the pathogenesis of GDM, and establishing an early diagnosis and personalized intervention plan for GDM. Summary of the Invention

[0004] The object of the present invention is to provide mitochondrial gene variation markers for predicting the risk of gestational diabetes mellitus in view of the above deficiencies of the prior art.

[0005] Another object of the present invention is to provide the application of a reagent for detecting the marker.

[0006] Another object of the present invention is to provide a kit for predicting the risk of gestational diabetes mellitus.

[0007] The object of the present invention can be achieved by the following technical solutions:

[0008] Mitochondrial gene variant markers for predicting the risk of gestational diabetes, selected from any one or more of the following gene variant sites: m.73A>G, m.185G>A, m.16051A>G, m.16092T>A, m.16291C>T in the D-loop region of the mitochondrial genome, and m.6228C>T in the COX1 gene.

[0009] Use of a reagent for detecting the mitochondrial gene variant sites described in the present invention in the preparation of a reagent for predicting the risk of gestational diabetes.

[0010] As a preference of the present invention, use of a reagent for detecting any one or more of the mitochondrial gene variant sites of m.16092T>A, m.16291C>T and m.6228C>T in the preparation of a reagent for predicting an increased risk of onset of gestational diabetes.

[0011] As a preference of the present invention, use of a reagent for detecting any one or more of the mitochondrial gene variant sites of m.73A>G, m.185G>A and m.16051A>G in the preparation of a reagent for predicting a decreased risk of onset of gestational diabetes.

[0012] As a preference of the present invention, the reagent for detecting the mitochondrial gene variant sites is a specific amplification PCR primer and sequencing primer for detecting these gene variant sites or a gene sequencing reagent.

[0013] A reagent kit for predicting the risk of gestational diabetes, comprising a reagent for detecting the gene variant sites described in the present invention.

[0014] As a preference of the present invention, the reagent for detecting the mitochondrial gene variant sites described in the present invention is a specific PCR amplification primer and sequencing primer for detecting these gene variant sites.

[0015] As a preference of the present invention, the reagent kit for predicting the risk of gestational diabetes comprises a reagent for detecting any one or more of the mitochondrial gene variant sites of m.16092T>A, m.16291C>T and m.6228C>T.

[0016] As another preference of the present invention, the reagent kit for predicting the risk of gestational diabetes comprises a reagent for detecting any one or more of the mitochondrial gene variant sites of m.73A>G, m.185G>A and m.16051A>G.

[0017] The screening method of the genetic marker for predicting the risk of gestational diabetes in the present invention comprises the following steps:

[0018] 1) A nested case-control study was established based on the China Environment and Genetics in Nongenetic Diseases (CHINESE) Birth Cohort, and the general clinical data of the subjects were collected.

[0019] 2) Blood samples were collected from the subjects in early pregnancy.

[0020] 3) DNA was extracted from the blood samples of the subjects in early pregnancy.

[0021] 4) The extracted DNA samples were sequenced for the mitochondrial genome to obtain sequencing data.

[0022] 5) By means of regression analysis, the relationship between mitochondrial gene mutations and the risk of gestational diabetes mellitus was determined, and genetic markers for predicting the risk of gestational diabetes mellitus were obtained.

[0023] Compared with previous research techniques, the method of this study solves the following problems:

[0024] 1. Establishing a large-scale prospective cohort and conducting follow-up on population exposure factors and health outcomes. Using a prospective cohort study is the optimal study design type that can simultaneously study the associations between multiple risk factors and multiple health outcomes.

[0025] 2. Establishing a nested case-control study based on the above-mentioned prospective cohort.

[0026] 3. Selecting biological samples of cases and controls with sufficient statistical power from the cohort population, and through whole mitochondrial genome sequencing studies, combined with logistic regression analysis, screening for mitochondrial DNA mutations significantly associated with the occurrence of GDM outcome events.

[0027] It should be noted that the design of specific amplification primers and sequencing primer pairs in the present invention can be easily completed by those skilled in the art. The primer pairs can be synthesized using conventional synthesis techniques. Those skilled in the art can understand that the primer pairs of the present invention are not limited to the following, and all primer pairs that can be used for PCR detection of the mtDNA loci described in the present invention for evaluating the risk of gestational diabetes mellitus in pregnant women are within the scope of the present invention. The mtDNA mutations related to GDM in the present invention are as follows (Table 1):

[0028] Table 1. Sequence list of mtDNA mutations related to GDM

[0029]

[0030]

[0031] The sequences of the specific amplification primer pairs for the mtDNA mutations related to GDM in the present invention are as follows (Table 2):

[0032] Table 2. Design of specific amplification primer pairs according to mtDNA loci

[0033]

[0034] The sequencing primer pairs for mtDNA loci related to GDM in the present invention are as follows (Table 3):

[0035] Table 3. Design of sequencing primer pairs based on mtDNA loci

[0036]

[0037] Beneficial effects:

[0038] 1. The present invention is based on a prospective nested case-control design, which is derived from a natural pregnancy cohort study in China - the China Environment and Genetics in Children Study. The included samples have good homogeneity, which is more conducive to controlling selection bias.

[0039] 2. This design has a sufficient sample size (including 701 cases and 859 controls), and the statistical power is relatively high.

[0040] 3. The present invention uses mitochondrial whole-genome sequencing technology to detect mitochondrial genome variations in early pregnancy blood. This sequencing method has high sensitivity and specificity, and is suitable for obtaining and analyzing large-sample, high-throughput sequencing data.

[0041] 3. The biological samples required by 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. Therefore, 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.

[0042] 4. The present invention is a genetic marker for predicting the risk of gestational diabetes mellitus proposed based on the analysis of the entire mitochondrial genome variation. Compared with previous studies targeting single loci or special gene regions, it can provide more information on the mitochondrial gene direction for the diagnosis of gestational diabetes mellitus. Specific embodiments

[0043] The present invention will be further described below in conjunction with specific preferred embodiments. However, the implementation manners of the present invention are not limited thereto.

[0044] Step 1. Patient enrollment

[0045] A nested case-control study was conducted based on the Chinese natural pregnancy population cohort established between 2018 and 2022. All pregnant women were included in the cohort study at their first antenatal examination and screened for GDM at 24-28 weeks of gestation. All selected subjects gave informed consent and signed a written informed consent form. This project was approved by the Ethics Committee of the School of Medicine, Nanjing University.

[0046] In this nested case-control study, a total of 1,560 Han Chinese women were finally selected, including 701 cases with GDM during follow-up and 859 healthy controls during the same period. All subjects in this study met the following inclusion criteria: 1) Natural conception; 2) 20 ≤ age ≤ 45 years old; 3) Gestational age at delivery ≥ 28 weeks. Exclusion criteria: 1) Suffering from severe chronic diseases and infectious diseases (such as cancer, chronic cardio-cerebrovascular diseases); 2) History of chemotherapy or radiation exposure; 3) Previous history of diabetes or insulin treatment.

[0047] 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 blood glucose values equal to or greater than the above levels was diagnosed as GDM.

[0048] As shown in the clinical data in Table 4, compared with the control group, GDM women were older (30.56 ± 3.92 vs. 30.06 ± 3.64, P = 0.009) and heavier (22.46 ± 4.36 vs. 21.23 ± 3.05, P < 0.001).

[0049] Table 4. Comparison of clinical data between the two groups

[0050]

[0051]

[0052] Note: BMI: body mass index, the data are expressed as mean ± standard deviation (mean ± SD).

[0053] Step 2. Peripheral blood DNA extraction

[0054] All subjects collected 2 ml of peripheral venous blood in an EDTA anticoagulant blood collection tube in a fasting state after 8-12 hours of fasting in the early pregnancy. After thorough mixing, the total DNA in the peripheral blood was extracted using the HiPure Blood DNA Midi Kit I kit (Magen, Beijing, China). It was stored at -20°C.

[0055] Step 3. Mitochondrial gene sequencing

[0056] After quality control of the DNA samples, library construction for sequencing was performed. Library construction and capture were carried out using Liquid-phase chip, which can efficiently enrich the mitochondrial DNA region. After library quality inspection, high-throughput and high-depth sequencing are performed using the BGI platform to obtain raw sequencing data (raw reads). The raw data is filtered using Fastp according to the filtering criteria, and clean reads are obtained after removing low-quality data. The clean reads of each sample are aligned with the revised Cambridge reference sequence (rCRS, NC_012920.1) using the BWA software, duplicates are removed, and the quality of the sample library is evaluated through indicators such as the average library length, alignment rate, coverage rate, capture rate, sequencing depth, and uniformity. The preliminary results of the BWA software are corrected using the standard procedure of Genome Analysis Tookit (GATK), and the SNV / INDEL of each sample is detected using the GATK Haplotype Caller software and filtered according to the recommended screening scheme of the software. All SNV / INDEL sites obtained are annotated using ANNOVAR to determine the gene information, functional information, population frequency information, etc. of the sites.

[0057] Step 4. Statistical analysis

[0058] Statistical analysis is performed using SPSS 26.0 software, and a P value < 0.05 is considered to indicate a statistically significant difference. The association between mtDNA variation and gestational diabetes is analyzed through binary logistic regression, and the age and BMI data are corrected to screen for differential sites, and the OR value and 95% confidence interval are given.

[0059] Step 5. Result summary

[0060] From the statistical analysis, (as shown in Table 5), a total of 6 mtDNA variations related to gestational diabetes were screened through logistic regression analysis. The frequencies of m.16092T>A and m.16291C>T in the D-loop region and m.6228C>T located in the COX1 gene were significantly higher in the case group than in the control group, and may be related to an increased risk of gestational diabetes (OR > 1, P < 0.05). After correcting for age and BMI, the risk of gestational diabetes in carriers of the m.16092T>A variation was 8.99 times that of non-carriers; the risk of gestational diabetes in carriers of the m.16291C>T variation was 2.39 times that of non-carriers; and the risk of gestational diabetes in carriers of m.6228C>T was 8.69 times that of non-carriers.

[0061] The frequencies of m.73A>G, m.185G>A, and m.16051A>G in the D-loop region were lower in the case group than in the control group, which may reduce the risk of gestational diabetes mellitus (OR<1, P<0.05). After adjusting for age and BMI, the risk of gestational diabetes mellitus in carriers of m.73A>G was 0.49 times that of non-carriers, the risk of gestational diabetes mellitus in carriers of m.185G>A was 0.40 times that of non-carriers, and the risk of gestational diabetes mellitus in carriers of the m.16051A>G variant was 0.23 times that of non-carriers.

[0062] In summary, the results showed that the above 6 mtDNA variants could be potential genetic markers for predicting the risk of gestational diabetes mellitus. Predicting the risk of gestational diabetes mellitus for early diagnosis and artificial intervention helps reduce the damage of gestational diabetes mellitus to pregnant women and their offspring.

[0063] Table 5. mtDNA variants significantly associated with GDM

[0064]

[0065] Note: Data are shown as percentages. P<0.05 is statistically significant, calculated by logistic regression. Adjusted P value, logistic regression adjusted for age and BMI; 95% CI, 95% confidence interval.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are within the protection scope of the present invention.

Claims

1. Use of a reagent for detecting mitochondrial gene variant markers in the preparation of a reagent for predicting the risk of gestational diabetes, wherein the mitochondrial gene variant markers consist of the following gene variant sites Comprising: m.73A>G, m.185G>A, m.16051A>G, m.16092T>A, m.16291C>T located in the D-loop region, and COX1 m.6228C>T in the 2. The use according to claim 1, Characterized in that Use of a reagent for detecting mitochondrial gene variant sites m.16092T>A, m.16291C>T and m.6228C>T in the preparation of a reagent for predicting an increased risk of gestational diabetes.

3. The use according to claim 1, Characterized in that Use of a reagent for detecting mitochondrial gene variant sites m.73A>G, m.185G>A and m.16051A>G in the preparation of a reagent for predicting a decreased risk of gestational diabetes.

4. The use according to any one of claims 1-3, Characterized in that The reagent for detecting mitochondrial gene variant markers is a specific PCR amplification primer and sequencing primer for detecting these gene variant sites.

5. A reagent kit for predicting the risk of gestational diabetes, Characterized in that A reagent for detecting mitochondrial gene mutation markers, wherein the mitochondrial gene mutation markers consist of the following gene mutation sites: m.73A>G, m.185G>A, m.16051A>G, m.16092T>A, m.16291C>T located in the D-loop region, and COX1 m.6228C>T located in the 6. The reagent kit for predicting the risk of gestational diabetes according to claim 5, Characterized in that The reagent for detecting mitochondrial gene variant markers is a specific PCR amplification primer and sequencing primer for detecting these mitochondrial gene variant sites.

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