Predicting the Development of Great Obstetric Syndromes Based on Multilocus Genetic Analysis: Results of a Retrospective Comparative Cohort Study

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Abstract

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, IL1β, 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 + IL1β G+3953A GA, PAI1-657 5G/4G 5G4G + IL1β G+3953A AA, PAI1-657 5G/4G 4G4G + IL1β 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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About the authors

Elena V. Kudryavtseva

Ural state medical universiry

Author for correspondence.
Email: elenavladpopova@yandex.ru
ORCID iD: 0000-0003-2797-1926
SPIN-code: 7232-3743
Scopus Author ID: 57211989398

MD, PhD, Assistant Professor, Department of obstetrics and Gynecology 

Russian Federation, 620024, Ekatetinburg, Repina str., 3

Vladislav V. Kovalev

Ural state medical university

Email: vvlovalev55@gmail.com
ORCID iD: 0000-0001-8640-8418
SPIN-code: 2061-0704
Scopus Author ID: 56204175600

DM, PhD, Professor, Head of the Department, Department of Obstetrics and Gynecology, Transfusiology

Russian Federation, 620024, Ekaterinburg, Repina str., 3

Igor I. Baranov

Nationa Medical Research Center Obsterics, Gynecology and Perinatology the name of Academician V.I. Kulakov

Email: i_baranov@oparina4.ru
ORCID iD: 0000-0002-9813-2823
SPIN-code: 4224-0437
Scopus Author ID: 57191908565

PhD, MD, Professor

Russian Federation, 4, Oparina str., Moscow, 117198

Igor V. Ugarov

xGen Cybernetics LLC

Email: iugarov@yandex.ru
ORCID iD: 0000-0001-6149-2721
SPIN-code: 6502-1953

MD, PhD, General manager

Russian Federation, Moscow

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Supplementary files

Supplementary Files
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1. Fig. 1. Genetic networks associated with pregnancy complications

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2. Fig. 2. GOS RISK computer program interface

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3. Fig. 3. ROC-curve model for predicting major obstetric syndromes using the GOS RISK program

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