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WO2024032834A1 - Procédé de prédiction du diabète sucré gestationnel fondé sur le profil d'expression des miarn cardiovasculaires - Google Patents

Procédé de prédiction du diabète sucré gestationnel fondé sur le profil d'expression des miarn cardiovasculaires Download PDF

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WO2024032834A1
WO2024032834A1 PCT/CZ2023/050047 CZ2023050047W WO2024032834A1 WO 2024032834 A1 WO2024032834 A1 WO 2024032834A1 CZ 2023050047 W CZ2023050047 W CZ 2023050047W WO 2024032834 A1 WO2024032834 A1 WO 2024032834A1
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mir
mirnas
gdm
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pregnancy
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Ilona HROMADNIKOVA
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Genespector SRO
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Priority to JP2025506950A priority patent/JP2025526611A/ja
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
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    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
    • C12N15/00—Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
    • C12N15/09—Recombinant DNA-technology
    • C12N15/11—DNA or RNA fragments; Modified forms thereof; Non-coding nucleic acids having a biological activity
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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the invention relates to the field of analysis of non-coding nucleic acids and expression markers, specifically microRNAs (miRNAs), using molecular-biological methods, primarily quantitative polymerase chain reaction with reverse transcription (RT-qPCR), and their use in screening to predict the development of metabolic disorders in pregnancy.
  • miRNAs microRNAs
  • RT-qPCR quantitative polymerase chain reaction with reverse transcription
  • GDM Gestational diabetes mellitus
  • gestational diabetes is a metabolic disorder of the mother manifested by glucose intolerance, which appears during pregnancy and spontaneously resolves during the postpartum period.
  • GDM increases the risk of pregnancy complications in the mother, newborn morbidity, and also has long-term consequences for both the mother and the child in the form of the risk of developing other metabolic disorders, for example obesity or type 2 diabetes mellitus.
  • GDM is diagnosed through an oral glucose tolerance test, which is performed at the turn of the second and third trimester. However, this test only detects already developed GDM. Therefore, the effort of contemporary medicine is to predict this metabolic disorder in time and, ideally, to prevent its occurrence or at least to mitigate its course and effects by an early intervention.
  • these methods are primarily based on data about the mother and her clinical parameters, such as age, weight, height, race, amount of subcutaneous fat, blood pressure, family history of diabetes, smoking, physical activity, use of medications to promote ovulation, or the occurrence of GDM in previous pregnancies.
  • these data are only supplemented by a blood count and the determination of an incomplete set of biochemical markers, for example coagulation factors, indicators of glycolipid metabolism, serum glutamine, ethanolamine and 1,3-diphosphoglycerate in urine, the soluble form of the CD163 receptor, tumor necrosis factor ⁇ (TNF - ⁇ ), placental protein 13 (PP13), or pregnancy-associated plasma protein A (PAPP-A).
  • TNF - ⁇ tumor necrosis factor ⁇
  • PP13 placental protein 13
  • PAPP-A pregnancy-associated plasma protein A
  • the increased or decreased values of the levels of given miRNAs after experiencing a pregnancy metabolic disorder do not correspond in any way to their values before the onset of the disorder and are completely independent of them. Since the findings from the cited document are based on changes caused by experiencing this metabolic disorder, using these changes to predict the disorder before it occurs is not possible.
  • Goal of the present invention is to eliminate the drawbacks of the prior art by developing a method that can be easily implemented on a large scale even in a commonly equipped molecular-genetics laboratory and which is able to predict—already during the first trimester of pregnancy—in a robust manner and with high reliability the onset of gestational diabetes mellitus in the later stages of pregnancy, for which there is no possibility of prediction in current clinical practice, and to do so even with anonymous samples, i.e. , without the need to know the data about the mother and her clinical parameters.
  • the present invention is based on determining 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) by an RT-qPCR method in samples of whole peripheral venous blood taken from pregnant women during the standard first-trimester screening, i.e. , in the period of 10th to 13th gestational week.
  • This way it is possible to predict the onset of GDM with high probability and reliability.
  • By selecting suitable subsets from this group of miRNAs it is further possible to specify whether it is going to be a milder form requiring only dietary modifications, or a more severe form requiring therapeutic intervention in addition to dietary modifications, for example in the form of medication.
  • the method was developed based on analyses of selected samples from 4,187 women in the first trimester of pregnancy, statistical processing of the results of these analyses, and their comparison with the subsequent course of pregnancy in the monitored women.
  • 121 women developed GDM without any other pregnancy complication.
  • 101 women had a milder form of GDM requiring only dietary modifications and 20 women had a more severe form requiring therapeutic intervention in addition to dietary modifications.
  • the method according to the invention is carried out as follows. First, the collected blood is processed into a leukocyte lysate. The contained RNA is then extracted and short RNAs are subsequently isolated. Resulting purified solution is analyzed using a two-step RT-qPCR reaction in a device maintaining ideal temperature conditions for individual steps that are repeated cyclically in the presence of standard and sequence-specific chemicals, namely miRNA-specific stem-loop RT primers, miRNA-specific forward and reverse PCR primers, and miRNA-specific MGB probes. In each step, a fluorescence signal released from the probe is measured and the cycle is usually repeated 40–45 times in total.
  • RNA extraction from leukocyte lysate and RT-qPCR analysis are standards in current molecular diagnostic practice. The procedures are fast, simple to perform, and allow for easy automation. Therefore, this diagnostic method is suitable for implementation in most genetic laboratories and for wide use in clinical practice.
  • miRNAs The normal distribution of expression of selected miRNAs was determined based on a sample of women who had a physiological pregnancy without complications. These levels were subsequently compared with miRNA levels in samples obtained from women who developed GDM during pregnancy, and the results were statistically processed using the Kruskal–Wallis test and the Mann–Whitney test. Based on the results, a specific set of 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) was selected.
  • miRNAs are all up-regulated before the onset of GDM and determination of their levels enables a prediction of GDM with a sufficiently high sensitivity at a sufficiently low rate of false positives. A generally accepted value is 10% false positive rate.
  • determination of 8 specific miRNAs allows to specify whether it is going to be a milder form requiring only dietary modifications and determination of 3 specific miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) allows to specify whether it is going to be a more severe form requiring therapeutic intervention in addition to dietary modifications.
  • the method makes it possible to effectively predict GDM based solely on the results of analysis of a miRNA profile in peripheral venous blood, i.e. , without the need for additional clinical examination of women or knowledge of their medical history.
  • the method is highly objective without the possibility of its distortion by false or erroneous data, and at the same time enables the testing of samples on a large scale, including their evaluation, while preserving the anonymity of the patients.
  • the method also allows a combination with the clinical characteristics of the mother, which increases the probability of a successful prediction even further.
  • GDM Gestational diabetes mellitus
  • ROC Receiveiver Operating Characteristic
  • ROC 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) in a combination with three basic clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods) for prediction of GDM.
  • ROC 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) in a combination with seven clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods, maternal history of miscarriage, presence of thrombophilic gene mutations, positive result of first-trimester prenatal screening for early preeclampsia and spontaneous preterm birth before the 34th week of gestation and fetal growth restriction before the 37th week of gestation using an established method of a predictive routine algorithm within a computer application for obstetrics and gynecology databases, the incidence of diabetes mellitus in close first-degree relatives) for prediction of GDM.
  • ROC curve obtained from the statistical analysis of the up-regulation 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) for prediction of a milder form of GDM requiring only dietary modifications.
  • ROC curve obtained from the statistical analysis of the up-regulation 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) in a combination with three basic clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods) for prediction of a milder form of GDM requiring only dietary modifications.
  • ROC curve obtained from the statistical analysis of the up-regulation 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) in a combination with seven clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods, maternal history of miscarriage, presence of thrombophilic gene mutations, positive result of first-trimester prenatal screening for early preeclampsia and spontaneous preterm birth before the 34th week of gestation and fetal growth restriction before the 37th week of gestation using an established method of a predictive routine algorithm within a computer application for obstetrics and gynecology databases, the incidence of diabetes mellitus in close first-degree relatives) for prediction of a milder form of GDM requiring only dietary modifications.
  • ROC curve obtained from the statistical analysis of the up-regulation of 3 selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) for prediction of a more severe form of GDM requiring therapeutic intervention in addition to dietary modifications.
  • ROC curve obtained from the statistical analysis of the up-regulation of 3 selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) in a combination with three basic clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods) for prediction of a more severe form of GDM requiring therapeutic intervention in addition to dietary modifications.
  • ROC curve obtained from the statistical analysis of the up-regulation of 3 selected miRNAs (miR-20a-5p, miR-20b-5p, miR-195-5p) in a combination with seven clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods, maternal history of miscarriage, presence of thrombophilic gene mutations, positive result of first-trimester prenatal screening for early preeclampsia and spontaneous preterm birth before the 34th week of gestation and fetal growth restriction before the 37th week of gestation using an established method of a predictive routine algorithm within a computer application for obstetrics and gynecology databases, the incidence of diabetes mellitus in close first-degree relatives) for prediction of a more severe form of GDM requiring therapeutic intervention in addition to dietary modifications.
  • Example 1 describes a general implementation of RT-qPCR analysis determining the amount of miRNA in a tested sample of whole peripheral venous blood and in a reference sample normalized to a simultaneously determined amount of selected endogenous controls (RNU58A a RNU38B).
  • RNA isolation is performed from thawed leukocyte lysate using a mixture of acidic phenol and chloroform. Long RNAs are further removed from the obtained RNA and short RNAs are concentrated using a column with a glass fiber filter and ethanol of different concentrations in the individual isolation steps.
  • the isolated RNA containing short RNAs is directly used as a template in a two-step RT-qPCR reaction. Reverse transcription takes place under the following conditions: 30 min at 16 °C, 30 min at 42 °C, and 5 min at 85 °C. This is followed by a polymerase chain reaction under the following conditions: 50 °C for 2 min, 95 °C for 10 min, then cycling at 95 °C for 15 s and 60 °C for 1 min.
  • the fluorescence is measured in the FAM and ROX channels (passive reference for fluorescence normalization). The cycling is repeated a total of 40 to 45 times.
  • C t values in the individual channels are read. Within one sample, the C t value in the FAM channel is obtained for the measured miRNA or for the short RNA serving as an endogenous control. These values correspond to the expression of individual genes in the biological sample.
  • the normalized expression value is obtained by subtracting the C t value of the endogenous control (geometric mean of RNU58A and RNU38B) from the C t value of the miRNA in the assayed sample. For relative quantification, the expression of all studied miRNAs and endogenous controls is determined simultaneously also in a reference sample, which is used in all performed analyses.
  • Example 2 describes a general implementation of statistical analysis of data describing the level of selected miRNAs.
  • ROC Receiveiver Operating Characteristic
  • the optimal cut-off value and sensitivity of a given miRNA biomarker is determined at 90.0% specificity, which corresponds to information about the percentage of women with increased or decreased expression of a specific miRNA at 10.0% false positive rate (FPR). Furthermore, a combined statistical analysis in the form of logistic regression and ROC analysis is performed in order to select the optimal combination of miRNA biomarkers for the given situation. This application provides the following parameters: area under the curve, sensitivity, specificity, optimal cut-off value, and sensitivity of a given combination of miRNA biomarkers at 90.0% specificity.
  • Example 3 describes a collection and selection of a suitable set of biological samples for the development of a method for predicting pregnancy complications using cardiovascular miRNAs as biomarkers.
  • Blood samples of these selected patients are analyzed following the procedure described in Example 1 and 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) are determined.
  • 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.
  • Example 4 describes a successful prediction of GDM using selected miRNA markers in a selected sample of patients.
  • 121 monitored patients develop GDM during pregnancy. Blood samples of these selected patients are analyzed following the procedure described in Example 1 and 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) are determined. Up-regulation of these selected miRNA biomarkers, whose levels exceed the minimum values determined by a statistical analysis for a 10% FPR, is observed in 58 of 121 patients, which corresponds to a successful prediction in 47.9% of cases.
  • 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,
  • Example 5 describes a successful prediction of GDM using selected miRNA markers and basic clinical characteristics of the mother in a selected sample of patients.
  • Example 6 describes a successful prediction of GDM using selected miRNA markers and clinical characteristics of the mother in a selected sample of patients.
  • Up-regulation of these selected miRNA biomarkers and values of seven clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods, maternal history of miscarriage, presence of thrombophilic gene mutations, positive result of first-trimester prenatal screening for early preeclampsia and spontaneous preterm birth before the 34th week of gestation and fetal growth restriction before the 37th week of gestation using an established method of a predictive routine algorithm within a computer application for obstetrics and gynecology databases, the incidence of diabetes mellitus in close first-degree relatives), whose levels exceed the minimum values determined by a statistical analysis for a 10% FPR, is observed in 88 of 121 patients, which corresponds to a successful prediction in 72.7% of cases.
  • Example 7 describes a successful prediction of a milder form of GDM requiring only dietary modifications using selected miRNA markers in a selected sample of patients.
  • 101 monitored patients develop a milder form of GDM requiring only dietary modifications during pregnancy.
  • Blood samples of these selected patients are analyzed following the procedure described in Example 1 and 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) are determined.
  • Up-regulation of these selected miRNA biomarkers whose levels exceed the minimum values determined by a statistical analysis for a 10% FPR, is observed in 35 of 101 patients, which corresponds to a successful prediction in 34.7% of cases.
  • Example 8 describes a successful prediction of a milder form of GDM requiring only dietary modifications using selected miRNA markers and basic clinical characteristics of the mother in a selected sample of patients.
  • Example 9 describes a successful prediction of a milder form of GDM requiring only dietary modifications using selected miRNA markers and clinical characteristics of the mother in a selected sample of patients.
  • Up-regulation of these selected miRNA biomarkers and values of seven clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods, maternal history of miscarriage, presence of thrombophilic gene mutations, positive result of first-trimester prenatal screening for early preeclampsia and spontaneous preterm birth before the 34th week of gestation and fetal growth restriction before the 37th week of gestation using an established method of a predictive routine algorithm within a computer application for obstetrics and gynecology databases, the incidence of diabetes mellitus in close first-degree relatives), whose levels exceed the minimum values determined by a statistical analysis for a 10% FPR, is observed in 57 of 101 patients, which corresponds to a successful prediction in 56.4% of cases.
  • Example 10 describes a successful prediction of a more severe form of GDM requiring therapeutic intervention in addition to dietary modifications using selected miRNA markers in a selected sample of patients.
  • Example 11 describes a successful prediction of a more severe form of GDM requiring therapeutic intervention in addition to dietary modifications using selected miRNA markers and basic clinical characteristics of the mother in a selected sample of patients.
  • Example 12 describes a successful prediction of a more severe form of GDM requiring therapeutic intervention in addition to dietary modifications using selected miRNA markers and clinical characteristics of the mother in a selected sample of patients.
  • Up-regulation of these selected miRNA biomarkers and values of seven clinical characteristics of the mother (age in early pregnancy, BMI in early pregnancy, infertility treatment with assisted reproduction methods, maternal history of miscarriage, presence of thrombophilic gene mutations, positive result of first-trimester prenatal screening for early preeclampsia and spontaneous preterm birth before the 34th week of gestation and fetal growth restriction before the 37th week of gestation using an established method of a predictive routine algorithm within a computer application for obstetrics and gynecology databases, the incidence of diabetes mellitus in close first-degree relatives), whose levels exceed the minimum values determined by a statistical analysis for a 10% FPR, is observed in 18 of 20 patients, which corresponds to a successful prediction in 90.0% of cases.

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Abstract

Procédé de prédiction du diabète sucré gestationnel, tant dans sa forme légère que dans sa forme plus grave. Les femmes enceintes sont soumises à un dépistage pour déterminer le profil d'expression d'au moins deux miARN dans le sang veineux périphérique total prélevé entre la 10e et la 13e semaine de gestation, ces deux ou plusieurs miARN sont choisis dans le groupe constitué par 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 et miR-574-3p.
PCT/CZ2023/050047 2022-08-12 2023-08-03 Procédé de prédiction du diabète sucré gestationnel fondé sur le profil d'expression des miarn cardiovasculaires Ceased WO2024032834A1 (fr)

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EP23754700.5A EP4569136A1 (fr) 2022-08-12 2023-08-03 Procédé de prédiction du diabète sucré gestationnel fondé sur le profil d'expression des miarn cardiovasculaires
CN202380060753.9A CN119866380A (zh) 2022-08-12 2023-08-03 基于心血管miRNA表达谱预测妊娠期糖尿病的方法
JP2025506950A JP2025526611A (ja) 2022-08-12 2023-08-03 心血管ｍｉＲＮＡの発現プロファイルに基づく妊娠糖尿病の予測方法

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CZ2022-335A CZ2022335A3 (cs) 2022-08-12 2022-08-12 Způsob predikce gestačního diabetu mellitus dle expresního profilu kardiovaskulárních miRNA

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