Genetic Predictors for Cardioembolic Stroke in Patients With Atrial Fibrillation

Шульман, В. А.; Аксютина, Н. В.; Никулина, С. Ю.; Назаров, Б. В.; Дудкина, К. В.; Максимов, В. Н.; Козлов, В. В.; Котловский, М. Ю.; Синяпко, С. Ф.; Платунова, И. М.

doi:10.15829/1560-4071-2014-10-29-33

Cited by 2 publications

(1 citation statement)

References 5 publications

(11 reference statements)

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“…(9,10) However, over the past decade a number of studies have discussed the genetic risk factors for IS development in patients with AF. (11)(12)(13)(14)(15) Mainly, the objects of the study were the genes of the hemostasis system, but more generally, the objects of study were the genes of the hemostatic system. Several polymorphisms of platelet membrane glycoprotein have been identified as potential risk factors for cardiovascular disease.…”

Section: Introductionmentioning

confidence: 99%

A Multiple Logistic Regression Model as an Additional Mathematical Method for Predicting the Development of Ischemic Stroke in Patients with Atrial Fibrillation

Aksyutina¹,

Шульман²,

Никулина³

et al. 2018

IJBM

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Prevention of thromboembolic complications in cases of atrial fibrillation (AF) and, above all, ischemic stroke (IS), represents a key problem of modern cardiology. The aim of the present study was to assess the feasibility of Multiple Logistic Regression Analysis in predicting the occurrence of IS in AF patients with the predictor genotypes of the FGB, GPIα, and GPIβα genes, in order to implement an approach to primary prevention and personalized treatment. Methods and Results: We examined 43 patients with atrial fibrillation and IS in their histories and 78 patients with AF without IS. A total of 188 persons without AF were included in the control group. The present study showed that the homozygote minor allele genotype (AA) of the FGB-455G/A SNP, the minor allele CT and TT genotypes of the GPIa 807C/T SNP, and the-5C/-5C and-5C/-5T genotypes of the GPIβα-5T/C polymorphism can be studied as genetic predictors of IS in AF patients. Logistic regression analysis was used to predict the development of IS in AF patients, depending on the presence of pathological genotypes of the FGB, GPIα, and GPIβα genes. The percentage of correct predictions for the absence of IS using this model was 99.5%. The development of IS was correctly predicted in 7.0% of cases. The overall percentage of correct predictions was 82.3%. Conclusion: The obtained logistic regression model is recommended as an additional method for assessing the risk of IS in young patients with lone AF.

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Section: Introductionmentioning

confidence: 99%

A Multiple Logistic Regression Model as an Additional Mathematical Method for Predicting the Development of Ischemic Stroke in Patients with Atrial Fibrillation

Aksyutina¹,

Шульман²,

Никулина³

et al. 2018

IJBM

View full text Add to dashboard Cite

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Gene polymorphism in blood coagulation system and folate cycle affecting heart condition in patients with hemorrhagic fever and renal syndrome

Manakhov

Sarksyan

Sufiyanov

et al. 2022

Russian Journal of Infection and Immunity

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Abstract. One of the typical manifestations of hemorrhagic fever with renal syndrome (HFRS) is a damage to the cardiovascular system. The most promising direction of studying the causes of cardiac complications in HFRS should be considered the genetic patient characteristics, particularly taking into account the disease pathogenesis, study of polymorphism of the genes in the blood coagulation system and the folate cycle. The aim of the study was to find out an effect of polymorphism of the blood coagulation system and folate cycle genes on heart damage in hemorrhagic fever with renal syndrome. A case-control study was conducted by enrolling 19 patients in the 2019 summer-autumn period at the Republican clinical infectious disease hospital in the city of Izhevsk. The study of polymorphism of the blood coagulation system and folate cycle genes was performed by using a set of reagents "Realbest-Genetics Hemostasis (12)" on the "CFX96" amplifier (Bio-Rad, USA). DNA was extracted from peripheral blood leukocytes with reagents "Realbest Extraction 100". Transthoracic echocardiography was performed on a Vivid 7 Dimension ultrasound scanner (GE Healthcare, USA) with a matrix sector sensor M4S with a phased array at scanning frequency of 1.5-4.3 MHz. The group parameters were calculated and depicted as median and interquartile range (ME [Q25;Q75]). Comparison of such parameters was carried out by using the Mann-Whitney criterion. Comparison of the frequency distribution for genotypes and alleles in the study groups was carried out using the criterion χ2. The association of alleles/genotypes with a predisposition to detectable changes was assessed by the risk ratio (OR) additionally calculating 95% confidence interval (CI) . The p≤0.05 was considered as statistically significant. During the study, 7 patients were found to have floating echoes on the aortic valve in the outlet of the left ventricle - signs of thrombotic endocarditis. In the group of patients with signs of thrombotic endocarditis, there was revealed a higher frequency of the allele A for the F7:10976 G/A gene compared to patients lacking signs of thrombotic endocarditis (p=0.0357). All study patients had a normal left ventricular ejection fraction (more than 50%), but during the speckle-tracking study assessing the index of averaged peak longitudinal contractility (GLPS AVG), 11 patients with impaired myocardial contractility were identified. In patients with decreased GLPS AVG, the genograde G/G of the FGB:-455 G/A gene was detected more often compared to patients with preserved myocardial contractility (p=0.0397). In 8 patients, signs of grade 1 diastolic left ventricular dysfunction were revealed, the prognostic importance of the gene polymorphism related to the blood coagulation system and folate cycle in developing this complication has not been determined.

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Genetic Predictors for Cardioembolic Stroke in Patients With Atrial Fibrillation

Cited by 2 publications

References 5 publications

A Multiple Logistic Regression Model as an Additional Mathematical Method for Predicting the Development of Ischemic Stroke in Patients with Atrial Fibrillation

A Multiple Logistic Regression Model as an Additional Mathematical Method for Predicting the Development of Ischemic Stroke in Patients with Atrial Fibrillation

Gene polymorphism in blood coagulation system and folate cycle affecting heart condition in patients with hemorrhagic fever and renal syndrome

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