Method for predicting gestational diabetes mellitus based on cardiovascular miRNA expression profile

Abstract

A method of predicting both lighter and heavier forms of gestational diabetes mellitus. According to the method, a pregnant woman is screened to determine the expression profiles of two or more miRNAs in the whole peripheral venous blood collected during the period from the tenth week to the thirteenth week of pregnancy, and the two or more miRNAs are selected from the following groups: miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p and miR-574-3p.

Description

Technical Field

[0001] The present invention relates to the field of analysis of non-coding nucleic acids and expression markers, in particular microRNAs (miRNAs), using molecular biology methods, mainly reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and their use in screening to predict the development of metabolic disorders during pregnancy. Background Art

[0002] Gestational diabetes (GDM), also known as gestational diabetes, is a metabolic disorder of the mother, manifested as glucose intolerance, which develops during pregnancy and resolves spontaneously in the postpartum period. In the absence of appropriate prenatal care for diabetes in the form of dietary modification or, in more severe cases, targeted therapy, GDM increases the risk of maternal complications before pregnancy, neonatal morbidity, and also has long-term effects on both the mother and the child in the form of the risk of developing other metabolic disorders (e.g., obesity or type 2 diabetes). In clinical practice, GDM is diagnosed by an oral glucose tolerance test, which is performed alternately in the second and third trimesters of pregnancy. However, this test only detects GDM that has already developed. Therefore, contemporary medicine strives to predict this metabolic disorder in a timely manner and, ideally, prevent its occurrence or at least mitigate its course and impact through early intervention.

[0003] Methods for predicting the onset of maternal GMD during early pregnancy are known in the prior art, for example from the following literature: Syngelaki et al., Fetal. Diagn. Ther. (Fetal Diagnosis and Ther.) 2015, 38, pp. 14-21; Sweeting et al., Diabetes Res. Clin. Pract. (Diabetes Research and Clinical Practice) 2017, 127, pp. 44-50; Sweeting et al., Fetal Diagn. Ther. (Fetal Diagnosis and Ther.) 2019, 45, pp. 76-84; Wang et al., Diabetes Res. Clin. Pract. (Diabetes Research and Clinical Practice) 2018, 142, pp. 130-138; Sakurai et al., J. Diabetes Investig. (Journal of Diabetes Investigation) 2019, 10, pp. 513-520; Tenenbaum-Gavish et al., Placenta 2020, 101, pp. 80-89; Zheng et al., Front. Public Health (Frontiers of Public Health) 2022, 10, pp. 850-191; Zhang et al., Exp. Ther. Med. (Experimental and Ther. Medicine) 2020, 20, pp. 293-300; Cremona et al., Clin. Nutr. ESPEN (European Society for Clinical Nutrition and Metabolism) 2021, 45, pp. 312-321; Shaarbaf Eidgahi et al., BMC Pregnancy Childbirth (BMC Pregnancy and Childbirth) 2022, 22, p. 13. However, these methods are mainly based on data about the mother and her clinical parameters, such as age, weight, height, race, subcutaneous fat mass, blood pressure, family history of diabetes, smoking, physical activity, use of drugs to promote ovulation or the incidence of GDM in previous pregnancies. In the case of some of the above methods, these data are only supplemented by blood cell counts and determination of an incomplete set of biochemical markers, such as coagulation factors, indicators of glucose and lipid metabolism in urine, serum glutamine, ethanolamine and 1,3-bisphosphoglycerate, soluble forms of the CD163 receptor, tumor necrosis factor alpha (TNF-α), placental protein 13 (PP13) and pregnancy-associated plasma protein A (PAPP-A). The prediction of the risk of onset of GDM by these methods relies on the above data about the mother, which may often be incomplete, affected by the mother's current physical and psychological state or expressed inaccurately or even wrongly. Therefore, this degree of subjectivity represents a fundamental flaw of the prior art and seriously affects the accuracy of predictions under real clinical conditions.At the same time, without this information, it is simply impossible to make predictions using methods known in the prior art, as it is not possible to reliably analyze anonymous samples or to evaluate samples on a large scale in a laboratory. Another disadvantage of this state-of-the-art technology is the use of non-specific biochemical markers, whose values ​​can vary significantly within a population, further complicating the degree of reliability of the predictions.

[0004] Examples of changes in levels of selected circulating microRNAs (miRNAs) associated with the onset of GDM have been described in the scientific literature. Lamadrid-Romero et al. (Neurosci. Res. 2018, 130, pp. 8-22) described changes in miRNA levels associated with nervous system function in women with GDM in mid- and late pregnancy compared with early pregnancy values. However, these findings cannot be used to predict the onset of GDM. In some literature (Thamotharan et al., PLoS ONE (Public Library of Science One) 2022, 17(5), e0267564; Yoffe et al., Eur. J. Endocrinol. (European Journal of Endocrinology) 2019, 181, pp. 565-577; Légaré et al., BMJ Open Diabetes Res. Care (BMJ Open Diabetes Research and Care) 2022, 10, e002703; Cao et al., J. Obstet. Gynaecol. Res. (Journal of Obstetrics and Gynecology Research) 2017, 43, pp. 974-981; et al., Cells 2021, 10, p. 170; Zhao et al., PLoS One 2011, 6, e23925), describe dozens of miRNAs whose expression profiles are altered during early pregnancy in women who subsequently develop GDM, and these references mention the use of these findings to predict the likelihood of GDM onset. However, these references do not discuss the statistical significance of individual miRNAs, which is necessary to conclude which miRNAs are suitable for such predictions in clinical practice. In addition, the references described markers that circulate freely in serum or plasma or are part of plasma exosomes. Plasma exosome processing is a demanding process that is not suitable for wider use in clinical practice.

[0005] In the following document: Hromadnikova et al., Int. J. Mol. Sci. (International Journal of Molecular Sciences) 2020, 21, p. 2437, postpartum (i.e., after delivery) selected miRNA profiles of women who experienced GDM during pregnancy are described. However, since the observed changes in miRNA expression profiles are caused by metabolic disorders that develop only in late pregnancy, it is impossible to use the knowledge known from the cited literature to develop a method for predicting the onset of GDM in the early pregnancy period (i.e., during the 10th to 13th week of pregnancy). In other words, after experiencing a metabolic disorder during pregnancy, the increase or decrease in a given miRNA level does not correspond to its value before the onset of the disorder at all, and is completely independent of these values. Since the findings of the cited literature are based on changes caused by experiencing this metabolic disorder, it is impossible to use these changes to predict the disorder before the disorder occurs.

[0006] In some literature (Hromadnikova et al., Biomedicines 2022, 10, p. 256; Hromadnikova et al., Biomedicines 2022, 10, p. 718; Hromadnikova et al., Int. J. Mol. Sci. 2022, 23, p. 3951), methods are described for using selected cardiovascular miRNAs as biomarkers to predict pregnancy complications in the form of preeclampsia, fetal growth restriction, gestational hypertension, small fetal size for a given gestational age, and preterm birth (in the form of spontaneous preterm birth and rupture of amniotic membranes before preterm birth), as well as for detecting undiagnosed chronic hypertension. However, since the above complications are related to impaired placental function and abnormal activity of the maternal cardiovascular system, it is not possible to use in an obvious way what is known from the cited literature (i.e. using cardiovascular miRNAs) to develop a method for predicting the onset of GDM, which is a metabolic disorder rather than a complication related to placental function or the function of the maternal cardiovascular system.

[0007] The aim of the present invention is to eliminate the disadvantages of the prior art by developing a method which can be easily implemented on a large scale even in commonly equipped molecular genetics laboratories and which is able to predict already in the first trimester, in a robust manner and with high reliability, the onset of gestational diabetes mellitus in later pregnancy, which is not possible in current clinical practice and which can be done even with anonymous samples, i.e. without the need for knowing data about the mother and her clinical parameters. Summary of the invention

[0008] The present invention is based on the following: During standard early pregnancy screening, i.e., between the 10th and 13th weeks of pregnancy, the levels of 11 specific miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) are determined by RT-qPCR in whole peripheral venous blood samples collected from pregnant women. In this way, the onset of GDM can be predicted with high probability and high reliability. By selecting a suitable subset from this group of miRNAs, it is possible to further specify whether the GDM is a milder mode that only requires dietary regulation or a more severe form that requires therapeutic intervention in addition to dietary regulation, such as medication.

[0009] Although the association between changes in the levels of the above-mentioned miRNAs and the experience of GDM or the prediction of pregnancy complications related to abnormalities in the functioning of the placenta and maternal cardiovascular system has been proposed in the scientific literature and is therefore known from the prior art, the use of these miRNAs for the prediction of GDM is not obvious or can be easily inferred from this literature due to the large number of miRNAs described, their specific association with the cardiovascular system rather than metabolism, the high variability in the possible changes in expression levels, and the fact that a specific subset of 11 markers had to be non-obvious selected from these markers.

[0010] The method was developed based on the analysis of a selected sample of 4,187 women in early pregnancy, the statistical treatment of the results of these analyses, and the comparison of these results with the subsequent course of pregnancy of the monitored women. Of these women, 3,028 had known complete health status throughout pregnancy, including all complications and the course of delivery. Of these 3,028 women, 121 women developed GDM without any other complications of pregnancy. Of these 121 women, 101 women had a milder form of GDM that only required dietary modification, while 20 women had a more severe form that required therapeutic intervention in addition to dietary modification.

[0011] The implementation of the method according to the present invention is as follows. First, the collected blood is processed into leukocyte lysate. Then, the RNA contained is extracted and short RNA is subsequently separated. The purified solution obtained is analyzed using a two-step RT-qPCR reaction in a device, which maintains ideal temperature conditions for each step of cyclic repetition in the presence of standard and sequence-specific chemicals, i.e., miRNA-specific stem-loop RT primers, miRNA-specific forward and reverse PCR primers, and miRNA-specific MGB probes. In each step, the fluorescent signal released from the probe is measured, and the cycle is usually repeated 40 to 45 times in total. After the program is completed, the Ct value is read in each channel, and the result corresponds to the original number of monitored nucleic acid molecules. Extracting RNA from leukocyte lysate and RT-qPCR analysis are standard operations for current molecular diagnostic practices. These procedures are fast, easy to perform, and easy to automate. Therefore, this diagnostic method is suitable for implementation in most genetic laboratories and is suitable for widespread use in clinical practice.

[0012] Based on the sample of the women in physiological pregnancy without complications, the normal distribution of the expression of selected RNA is determined. Subsequently, the miRNA levels in the samples obtained by the women who developed GDM during pregnancy are compared, and Kruskal-Wallis test and Mann-Whitney test are used to statistically process the results. Based on the results, a group of 11 kinds of miRNA (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) of specificity are selected. These miRNAs are all upregulated before the onset of GDM, and it is determined that their levels can predict GDM with sufficiently high sensitivity and sufficiently low false positive rate. A generally accepted value is a 10% false positive rate. Of this set of 11 miRNAs, the determination of 8 specific miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) allowed specification of whether the GDM would become a milder form requiring only dietary regulation, and the determination of 3 specific miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) allowed specification of whether the GMD would become a more severe form requiring therapeutic intervention in addition to dietary regulation.

[0013] As can be seen from the results presented below, this method enables effective prediction of GDM based solely on the analysis results of the miRNA profile in peripheral venous blood, i.e., without the need for additional clinical examinations of women or knowledge of their medical history. Therefore, the method is highly objective, cannot be distorted by false or erroneous data, and at the same time, enables large-scale testing of samples (including sample evaluation) while maintaining the anonymity of the patients. Nevertheless, the method also allows for combination with maternal clinical characteristics, which further increases the probability of successful prediction.

[0014] Gestational diabetes mellitus (GDM)

[0015] In women who develop GDM during pregnancy, the most suitable method for prediction was to monitor the upregulation of the following 11 miRNAs in whole peripheral venous blood collected in early pregnancy: miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p. Using this method, 47.9% of cases can be predicted with a 10% false positive rate (FPR) without any additional clinical examination of the women or their medical history. By combining these 11 miRNAs with 3 basic maternal clinical characteristics (age in early pregnancy, body mass index (BMI) in early pregnancy, and assisted reproductive methods for infertility treatment), 69.2% of cases can be predicted with a 10% FPR. By combining the 11 selected miRNAs with seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using an established prediction routine algorithm method in an obstetrics and gynecology database computer application, and incidence of grade 1 diabetes in close relatives), 72.5% of cases could be predicted with a 10% FPR.

[0016] Milder forms of GDM require only dietary modification.

[0017] In women who develop milder forms of GDM during pregnancy, the best predictor was found to be monitoring the upregulation of the following eight miRNAs in whole peripheral venous blood collected in early pregnancy: miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p. Using this approach, 34.7% of cases could be predicted with a 10% FPR without any additional clinical examination of the woman or her medical history. By combining these eight miRNAs with three basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, and assisted reproductive methods for infertility), 50.5% of cases could be predicted with a 10% FPR. By combining the eight selected miRNAs with seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using an established prediction routine algorithm method in an obstetrics and gynecology database computer application, and incidence of grade 1 diabetes in close relatives), 56.4% of cases could be predicted with a 10% FPR.

[0018] More severe forms of GDM require therapeutic intervention in addition to dietary modification.

[0019] In women who develop a more severe form of GDM during pregnancy, it was shown that the most suitable for prediction was to monitor the upregulation of the following 3 miRNAs in whole peripheral venous blood collected in early pregnancy: miR-20a-5p, miR-20b-5p, miR-195-5p. In these cases, no significant upregulation was observed for miR-1-3p, miR-100-5p, miR-125b-5p, miR-499a-5p, miR-574-3p, as these were only significantly upregulated in milder forms of GDM. Using this method, 30.0% of cases can be predicted with a 10% FPR without any additional clinical examination of the women or understanding their medical history. By combining these 3 miRNAs with 3 basic clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility treatment), 79.0% of cases can be predicted with a 10% FPR. By combining the three selected miRNAs with seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using an established prediction routine algorithm method in an obstetrics and gynecology database computer application, and incidence of grade 1 diabetes in close relatives), 89.5% of cases could be predicted with a 10% FPR. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The ROC (receiver operating characteristic) curve obtained from the statistical analysis of the up-regulation of 11 selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) for the prediction of GDM is depicted.

[0021] Figure 2 ROC curves obtained by statistical analysis of the upregulation of 11 selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, and miR-574-3p) combined with three basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, and assisted reproductive methods for infertility) were depicted for the prediction of GDM.

[0022] Figure 3 ROC curves obtained by statistical analysis of upregulation of 11 selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) combined with 7 basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, treatment of infertility with assisted reproductive methods, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using an established prediction routine algorithm method in an obstetrics and gynecology database computer application, and incidence of grade 1 consanguineous diabetes mellitus) were depicted for the prediction of GDM.

[0023] Figure 4 ROC curves obtained from statistical analysis of upregulation of eight selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) are depicted for predicting milder forms of GDM that only require dietary modulation.

[0024] Figure 5 ROC curves obtained by statistical analysis of the upregulation of eight selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) in combination with three basic maternal clinical characteristics (age at early pregnancy, BMI at early pregnancy, assisted reproductive methods for infertility treatment) are depicted for the prediction of milder forms of GDM that only require dietary modification.

[0025] Figure 6ROC curves obtained by statistical analysis of upregulation of eight selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) in combination with seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, treatment of infertility with assisted reproductive methods, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using an established prediction routine algorithm method in an obstetrics and gynecology database computer application, and incidence of grade 1 consanguineous diabetes mellitus) are depicted for the prediction of milder forms of GDM requiring only dietary modification.

[0026] Figure 7 ROC curves obtained from statistical analysis of upregulation of 3 selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) are depicted for predicting more severe forms of GDM requiring therapeutic intervention in addition to dietary modification.

[0027] Figure 8 ROC curves obtained by statistical analysis of upregulation of 3 selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) in combination with 3 basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility treatment) are depicted for prediction of more severe forms of GDM requiring therapeutic intervention in addition to dietary modification.

[0028] Fig. 9 ROC curves obtained by statistical analysis of upregulation of three selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) in combination with seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using an established prediction routine algorithm method in an obstetrics and gynecology database computer application, and incidence of grade 1 consanguineous diabetes mellitus) are depicted for the prediction of milder forms of GDM that only require dietary modification. DETAILED DESCRIPTION

[0029] Example 1

[0030] Example 1 describes the general implementation of an RT-qPCR analysis that determines miRNA amounts in whole peripheral venous blood test samples as well as reference samples, with these amounts normalized to the amounts of selected endogenous controls (RNU58A and RNU38B) determined simultaneously.

[0031] RNA isolation was performed from thawed leukocyte lysate using a mixture of acidic phenol and chloroform. In each isolation step, long RNA was further removed from the obtained RNA, and short RNA was concentrated using a chromatographic column containing a glass fiber filter and different concentrations of ethanol. The isolated RNA containing short RNA was directly used as a template for a two-step RT-qPCR reaction. Reverse transcription was performed under the following conditions: 30 minutes at 16°C, 30 minutes at 42°C, and 5 minutes at 85°C. The polymerase chain reaction was then performed under the following conditions: 2 minutes at 50°C, 10 minutes at 95°C, followed by a cycle at 95°C for 15 seconds and a cycle at 60°C for 1 minute. After each cycle, fluorescence was measured in the FAM and ROX channels (fluorescence normalized passive reference). The cycle was repeated a total of 40 to 45 times. After the program is completed, the C in each channel will be read. t In one sample, the C value obtained in the FAM channel is t The values ​​are for the measured miRNAs or for short RNAs as endogenous controls. These values ​​correspond to the expression of individual genes in the biological sample. T The C value of the endogenous control was subtracted from the t The values ​​(geometric mean of RNU58A and RNU38B) were used to obtain normalized expression values. For relative quantification, the expression of all investigated RNAs and endogenous controls was also determined simultaneously in a reference sample, which was used for all performed analyses.

[0032] Example 2

[0033] Example 2 describes a general implementation of statistical analysis of data describing levels of selected miRNAs.

[0034] Since the data according to the Shapiro–Wilk test were non-normally distributed, nonparametric tests were used to evaluate the experimental data. The gene expression of miRNAs between the groups was compared using the Mann–Whitney test, and in the case of more than 2 comparison groups, the Kruskal–Wallis test was used, followed by post hoc analysis. The level of statistical significance was determined based on the corrected p-value after application of the Benjamini-Hochberg correction. ROC (receiver operating characteristic) curves were also constructed for the corresponding miRNAs. The area under the curve, the sensitivity and specificity of individual miRNAs, and the optimal cutoff value (the so-called standard) were evaluated. In addition, the optimal cutoff value and sensitivity of a given miRNA biomarker were determined with a specificity of 90.0%, which corresponds to information about the percentage of women with increased or decreased expression of a specific miRNA at a false positive rate (FPR) of 10.0%. In addition, a combined statistical analysis in the form of logistic regression and ROC analysis was performed in order to select the best combination of biomarkers for a given situation. The application provides the following parameters: area under the curve, sensitivity, specificity, optimal cut-off value, and sensitivity of a given miRNA biomarker combination at 90.0% specificity.

[0035] Example 3

[0036] Example 3 describes the collection and selection of a suitable set of biological samples for developing a method for predicting pregnancy complications using cardiovascular miRNAs as biomarkers.

[0037] 200 μL of whole peripheral venous blood was collected from 4,187 women between the 10th and 13th weeks of pregnancy. Cell lysates of leukocytes were prepared by removing red blood cells and then stored frozen at -80°C. Samples were selected exclusively from women whose complete health status throughout pregnancy, including all complications and delivery course, was known after delivery of the patients. Using established methods, 80 patients who experienced a physiological pregnancy course and had a negative result of first trimester prenatal screening were selected as a control group using a routine prediction algorithm in a computer application of obstetrics and gynecology database. For the study of GDM prediction, 121 patients diagnosed with GDM during pregnancy were selected. Blood samples of these selected patients were analyzed according to the procedure described in Example 1, and the levels of the selected 11 miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. For the prediction of GDM with sufficient reliability described in Examples 4 to 12, more than half of the appropriate miRNAs shown in a single example were used each time. The highest reliability was achieved by using all the appropriate miRNAs shown in a single example.

[0038] Example 4

[0039] Example 4 describes the successful prediction of GDM in selected patient samples using selected miRNA markers.

[0040] 121 monitored patients developed GDM during pregnancy. According to the procedure described in Example 1, blood samples of these selected patients were analyzed and the levels of selected 11 miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. In 121 patients, 58 of these selected miRNA biomarkers were observed to be upregulated, and the upregulated levels exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to 47.9% of cases successfully predicted. Statistical analysis of the obtained data provides the following values: specificity, sensitivity, 95% CI and criteria:

[0041]

[0042] Example 5

[0043] Example 5 describes the successful prediction of GDM in selected patient samples using selected miRNA markers and basic maternal clinical characteristics.

[0044] 121 monitored patients developed GDM during pregnancy. Blood samples of these selected patients were analyzed according to the procedure described in Example 1, and the levels of 11 selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. Upregulation of these selected miRNA biomarkers and values ​​of 3 basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility) were observed in 84 of the 121 patients, and their levels exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to a successful prediction of 69.4% of cases. Statistical analysis of the data obtained provided values ​​for: specificity, sensitivity, 95% CI, and criteria:

[0045]

[0046] Example 6

[0047] Example 6 describes the successful prediction of GDM in selected patient samples using selected miRNA markers and maternal clinical characteristics.

[0048] 121 monitored patients developed GDM during pregnancy. Blood samples from these selected patients were analyzed according to the procedure described in Example 1, and the levels of selected 11 miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. Upregulation of these selected miRNA biomarkers and values ​​of seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, treatment of infertility with assisted reproductive methods, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using established prediction routine algorithm methods in the obstetrics and gynecology database computer application, and incidence of diabetes mellitus grade 1 in close relatives) were observed in 88 of the 121 patients, with levels exceeding the minimum value determined by statistical analysis for 10% FPR, which corresponds to a successful prediction of 72.7% of cases. Statistical analysis of the obtained data provided values ​​for: specificity, sensitivity, 95% CI and criteria:

[0049]

[0050]

[0051] Example 7

[0052] Example 7 describes the successful prediction of milder forms of GDM requiring only dietary modification in selected patient samples using selected miRNA markers.

[0053] 101 monitored patients developed a milder form of GDM during pregnancy that only required dietary regulation. According to the procedure described in Example 1, blood samples of these selected patients were analyzed and the levels of 8 selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. In 101 patients, 35 were observed to have upregulated these selected miRNA biomarkers, and the upregulated levels exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to 34.7% of cases that were successfully predicted. Statistical analysis of the data obtained provides the following values: specificity, sensitivity, 95% CI and criteria:

[0054]

[0055] Example 8

[0056] Example 8 describes the successful prediction of milder forms of GDM requiring only dietary modification in selected patient samples using selected miRNA markers and basic maternal clinical characteristics.

[0057] 101 monitored patients developed a milder form of GDM during pregnancy that only required dietary regulation. According to the procedure described in Example 1, blood samples of these selected patients were analyzed and the levels of 8 selected miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. In 101 patients, 51 patients observed that these selected miRNA biomarkers were upregulated and the values ​​of 3 basic clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility treatment) exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to the successful prediction of 50.5% of cases. The statistical analysis of the obtained data provides the following values: specificity, sensitivity, 95% CI and standard:

[0058] Example 9

[0059] Example 9 describes the successful prediction of milder forms of GDM requiring only dietary modification in selected patient samples using selected miRNA markers and maternal clinical characteristics.

[0060] 101 monitored patients developed a milder form of GDM during pregnancy that only required dietary modification. Blood samples from these selected patients were analyzed according to the procedure described in Example 1, and the levels of selected 8 miRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, miR-574-3p) were determined. Upregulation of these selected miRNA biomarkers and values ​​of seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, treatment of infertility with assisted reproductive methods, history of maternal miscarriage, presence of thrombophilic gene mutations, positive results of early-onset preeclampsia screening and spontaneous preterm birth before 34 weeks of gestation and fetal growth restriction before 37 weeks of gestation performed using established prediction routine algorithm methods in the obstetrics and gynecology database computer application, and incidence of diabetes mellitus grade 1 in close relatives) were observed in 57 of 101 patients, with levels exceeding the minimum value determined by statistical analysis for 10% FPR, which corresponds to a successful prediction of 56.4% of cases. Statistical analysis of the obtained data provided values ​​for: specificity, sensitivity, 95% CI and criteria:

[0061]

[0062] Example 10

[0063] Example 10 describes the use of selected miRNA markers in selected patient samples to successfully predict more severe forms of GDM that require therapeutic intervention in addition to dietary modification.

[0064] 20 monitored patients developed a more severe form of GDM during pregnancy that required therapeutic intervention in addition to dietary regulation. According to the procedure described in Example 1, blood samples of these selected patients were analyzed and the levels of 3 selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) were determined. In 6 of the 20 patients, these selected miRNA biomarkers were observed to be upregulated, and the upregulated levels exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to a successful prediction of 30.0% of cases. Statistical analysis of the data obtained provides the following values: specificity, sensitivity, 95% CI and criteria:

[0065]

[0066]

[0067] Embodiment 11

[0068] Example 11 describes the successful prediction of more severe forms of GDM requiring therapeutic intervention in addition to dietary modification in selected patient samples using selected miRNA markers and basic maternal clinical characteristics.

[0069] 20 monitored patients developed a heavier form of GDM during pregnancy that required therapeutic intervention in addition to dietary regulation. According to the procedure described in Example 1, blood samples of these selected patients were analyzed and the levels of the selected 3 miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) were determined. In 16 of the 20 patients, the values ​​of these selected miRNA biomarkers were observed to be upregulated and the 3 basic clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility treatment) exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to a successful prediction of 80.0% of the cases. The statistical analysis of the data obtained provides the following values: specificity, sensitivity, 95% CI and standard:

[0070]

[0071]

[0072] Example 12

[0073] Example 12 describes the successful prediction of more severe forms of GDM requiring therapeutic intervention in addition to dietary modification in selected patient samples using selected miRNA markers and maternal clinical characteristics.

[0074] Twenty monitored patients developed a more severe form of GDM during pregnancy that required therapeutic intervention in addition to dietary modification. Blood samples from these selected patients were analyzed according to the procedure described in Example 1, and the levels of the selected three miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) were determined. Upregulation of these selected miRNA biomarkers and values ​​of seven basic maternal clinical characteristics (age in early pregnancy, BMI in early pregnancy, assisted reproductive methods for infertility, maternal history of miscarriage, presence of pro-thrombotic gene mutations, early pregnancy early-onset preeclampsia screening and positive results for spontaneous preterm birth before 34 weeks of pregnancy and fetal growth restriction before 37 weeks of pregnancy using established prediction routine algorithm methods in the obstetrics and gynecology database computer application, and the incidence of diabetes in first-degree relatives) were observed in 18 of the 20 patients, and their levels exceeded the minimum value determined by statistical analysis for 10% FPR, which corresponds to a successful prediction of 90.0% of cases. Statistical analysis of the data obtained provided values ​​for: specificity, sensitivity, 95% CI, and criteria:

[0075]

[0076] Industrial Applicability

[0077] The method for predicting gestational diabetes based on cardiovascular miRNA expression profiles has industrial applicability through laboratory analysis of biomaterial samples collected in clinical practice of obstetrics and gynecology.

Claims

1. A method for predicting gestational diabetes, characterized in that: Pregnant women are screened to determine the expression profile of two or more miRNAs in whole peripheral venous blood collected between the 10th and 13th weeks of pregnancy, and the two or more miRNAs are selected from the following group: miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, miR-574-3p.

2. The method according to claim 1, characterized in that The miRNAs screened for predicting milder forms of gestational diabetes were miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, and miR-574-3p.

3. The method according to claim 1, characterized in that The miRNAs screened for predicting more severe forms of gestational diabetes were miR-20a-5p, miR-20b-5p, and miR-195-5p.

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