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With the aim to determine specific genetic characteristics of the population of Moscow region, we determined allele frequencies of 48 polymorphic loci (SNP) associated with the increased risk of ischemic stroke development. The genotype frequency distribution for all the SNPs corresponds to Hardy–Weinberg equilibrium. Comparison of the allele frequencies with those obtained for Caucasian populations from the databases dbSNP and 1000 Genomes Project revealed significant differences for two SNPs (rs556621 and rs556512) and seven SNPs (rs556621, rs556512, rs1801133, rs1799983, rs5918, rs328, and rs2398162), respectively. The revealed genetic features of the population make it possible to increase the accuracy and reliability of the individual genetic risk assessment of development for multifactorial diseases in the examined population.

One of the prevalent genetic causes of idiopathic male sterility is related to micro-deletions in AZF locus located in Y-chromosome. In total population, rate of such micro-deletions makes up to 1:4000. however, in infertile males their rate varies from 2% to 10%. In AZF locus three subregions are distinguished: AZFa, AZFb and AZFc. The loss of one or several subregions can result in disorder of spermatogenesis of various degree - from decreasing of its activity to Sertoli-cell syndrome manifested by azoospermia or oligospermia of severe degree. Therefore, implementation of genetic testing for presence of micro-deletions in AZF locus is a necessary test in case of prognosis of male sterility and its treatment. The purpose of study is to develop and test a diagnostic system of detection of micro-deletions in subregions of AZF locus using multiplex polymerase chain reaction in real-time. As a reference method a technique was implemented described in guidelines of the European Academy of Andrology conjointly with European Molecular Genetics Quality Network. The technique testing specified analysis of 33 samples of DNA separated from blood of males with azoospermia and oligospermia of severe degree. No discordant results were received as compared with reference method. In 27 DNA samples the deletions were detected in AZF locus: 4 AZFa deletions (15%), 2 AZFb deletions (7%), 17 AZFc deletions (63%) and 6 combined deletions of AZFb+candи AZFa+b+с (22%). The proposed technique permits detect micro-deletions of subregions of AZF locus.

To study genetic characteristics of the population of the Moscow region and analyze the association of rs1801133 and rs1801131 of MTHFR with the risk of ischemic stroke (IS).A sample of 170 and 115 patients with atherothrombotic and cardioembolic subtypes of IS and 360 residents of the Moscow region without IS were examined. MTHFR alleles were determined by a multiplex real-time polymerase chain reaction.No association between the frequencies of MTHFR alleles and the risk of ischemic stroke was found. The comparison of allele frequencies with those in Caucasian populations published in the dbSNP (NCBI) and 1000 Genomes Project databases revealed significant differences for rs1801133 from the EUR 1000 Genomes Project. The allele frequency data for MTHFR could increase the accuracy and reliability of the individual risk calculation for multifactorial diseases in the Russian population.Цель исследования. Изучение генетических особенностей населения московского региона и анализ влияния аллелей и генотипов полиморфных локусов rs1801133 и rs1801131 гена MTHFR на риск развития ишемического инсульта (ИИ). Материал и методы. Обследовано 170 и 115 пациентов с атеротромботическим и кардиоэмболическим подтипами ИИ соответственно и 360 жителей московского региона без признаков острого нарушения мозгового кровообращения на момент участия в исследовании. Аллели гена MTHFR определяли методом мультиплексной ПЦР в реальном времени. Результаты и заключение. В исследованной выборке не обнаружено ассоциации полиморфных локусов гена MTHFR с риском развития ишемического инсульта. При сопоставлении частот аллелей в популяционном контроле с частотами, представленными для популяции европеоидов в базах данных dbSNP и 1000 Genomes Project, выявлены статистически значимые различия для rs1801133 в сравнении с выборкой EUR 1000 Genomes Project. Описанные генетические особенности могут быть использованы для повышения точности и надежности расчета индивидуального генетического риска развития других патологических состояний, связанных с нарушением обмена фолатов в наблюдаемой популяции.

To develop a method of the complex assessment of genetic risk for ischemic stroke (IS) and evaluate its effectiveness.Genotyping of 182 patients with atherothrombotic and cardioembolic subtypes of IS and 360 healthy individuals of 48 single nucleotide polymorphic loci (SNP) associated with the risk of II and its subtypes was performed.In each group of SNPs, composite indicators of genetic risk of IS in groups of patients and healthy controls were identified. Differences between the calculated values of the genetic risk in these groups were significant (p0,05). The quality of the binary classification validated by ROC-analysis confirmed the predictive potential of the proposed method of risk calculation for determining the genetic predisposition to the development of IS.Цель исследования. Разработка методики комплексной оценки генетически обусловленного риска развития ишемического инсульта (ИИ) и оценка ее эффективности. Материал и методы. Проведено генотипирование 182 больных с атеротромботическим и кардиоэмболическим подтипами ИИ (группа больнах) и 360 здоровых (контрольная группа) по 48 однонуклеотидным полиморфным локусам (SNP), ассоциированным с риском развития ИИ и его подтипов. Результаты и заключение. Для каждой группы SNP в соответствии с предложенной моделью определены комплексные показатели генетического риска развития ИИ в группе больных и контрольной группе. Различия между группой больных и контрольной группой по показателям генетического риска определены как статистически значимые (p0,05). Качество бинарной классификации, проверенное ROC-анализом, подтверждает прогностический потенциал использования предложенной модели расчета риска для определения генетической предрасположенности к развитию ИИ.