Background. Great obstetric syndromes are pathological conditions, related to the level of maternal, perinatal and infant morbidity and mortality. There is a genetic component in the development of pregnancy complications, as evidenced by numerous clinical observations and research results. Purpose to study the frequency characteristics of the occurrence of polymorphic variants of various genes and their combinations in patients who underwent pregnancy complicated by great obstetric syndromes in comparison with women whose pregnancy proceeded without complications and successfully ended with the birth of a live full-term baby. Methods. A retrospective comparative cohort study was conducted. Molecular genetic research was carried out in 391 women: 279 women who underwent one of the verified clinical forms related to great obstetric syndromes (main group), 112 women were included in the control group. 37 polymorphisms in 33 genes were studied (FGB, F2, F5, F7, F13, GPIa, GPIIIa, GPVI, PROC, PAI1, PLAT, MTHFR, MTHFD, MTRR, MTR, SLC19A1, CBS, NOS3, END1, ACE, ADD1, AGT , CYP11B2, GSTM, GSTT, GSTP1, MnSOD, GPX1, IL1, TNF-a, ESR1, ESR2, PGR). Results. The most significant polymorphisms and their combinations were identified. In the main group, the following combinations were more common: ACE Alu I/D ID + AGT А704G GG, AGT А704G GG + MTRR A66G AG, F7 G10976A GG + AGT А704G GG, F7 G10976A GG + F13 G103A GG, F7 G10976A GG + GPIa С807T CC, F7 G10976A GG + MTHFR C677T CC, CYP11B2 G-344A GA + IL1 G+3953A GA, PAI1-657 5G/4G 5G4G + IL1 G+3953A AA, PAI1-657 5G/4G 4G4G + IL1 G+3953A AA, in control group AGT A704G AA + MTRR A66G AG, AGT A704G AG + MTRR A66G AG (the differences are statistically significant). To simplify the practical application of the analysis for genetic polymorphisms, a computer program named GOS RISK was created to assess the risk of pregnancy complications. The sensitivity and specificity were 70.8% and 78.8%, the efficiency of the method 74.8%. Conclusion. Analysis of individual polymorphic variants of genes indicates their role in the discussed pathology. Creation of computer programs based on multilocus genome analysis increases the predictive value of molecular genetic studies.
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