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Genetic risk factors for restenosis after percutaneous coronary intervention in Kazakh population.

ABSTRACT: After coronary stenting, the risk of developing restenosis is from 20 to 35 %. The aim of the present study is to investigate the association of genetic variation in candidate genes in patients diagnosed with restenosis in the Kazakh population.Four hundred fifty-nine patients were recruited to the study; 91 patients were also diagnosed with diabetes and were excluded from the sampling. DNA was extracted with the salting-out method. The patients were genotyped for 53 single-nucleotide polymorphisms. Genotyping was performed on the QuantStudio 12K Flex (Life Technologies). Differences in distribution of BMI score among different genotype groups were compared by analysis of variance (ANOVA). Also, statistical analysis was performed using R and PLINK v.1.07. Haplotype frequencies and LD measures were estimated by using the software Haploview 4.2.A logistic regression analysis found a significant difference in restenosis rates for different genotypes. FGB (rs1800790) is significantly associated with restenosis after stenting (OR?=?2.924, P?=?2.3E-06, additive model) in the Kazakh population. CD14 (rs2569190) showed a significant association in the additive (OR?=?0.08033, P?=?2.11E-09) and dominant models (OR?=?0.05359, P?=?4.15E-11). NOS3 (rs1799983) was also highly associated with development of restenosis after stenting in additive (OR?=?20.05, P?=?2.74 E-12) and recessive models (OR?=?22.24, P?=?6.811E-10).Our results indicate that FGB (rs1800790), CD14 (rs2569190), and NOS3 (rs1799983) SNPs could be genetic markers for development of restenosis in Kazakh population. Adjustment for potential confounder factor BMI gave almost the same results.

SUBMITTER: Zholdybayeva EV

PROVIDER: S-EPMC4898353 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Genetic risk factors for restenosis after percutaneous coronary intervention in Kazakh population.

Zholdybayeva Elena V EV Talzhanov Yerkebulan A YA Aitkulova Akbota M AM Tarlykov Pavel V PV Kulmambetova Gulmira N GN Iskakova Aisha N AN Dzholdasbekova Aliya U AU Visternichan Olga A OA Taizhanova Dana Zh DZh Ramanculov Yerlan M YM

Human genomics 20160608 1

<h4>Background</h4>After coronary stenting, the risk of developing restenosis is from 20 to 35 %. The aim of the present study is to investigate the association of genetic variation in candidate genes in patients diagnosed with restenosis in the Kazakh population.<h4>Methods</h4>Four hundred fifty-nine patients were recruited to the study; 91 patients were also diagnosed with diabetes and were excluded from the sampling. DNA was extracted with the salting-out method. The patients were genotyped ...[more]

PMID: 27277665

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Project description:BackgroundThis study aimed to develop and validate a nomogram to predict probability of in-stent restenosis (ISR) in patients undergoing percutaneous coronary intervention (PCI).MethodsPatients undergoing PCI with drug-eluting stents between July 2009 and August 2011 were retrieved from a cohort study in a high-volume PCI center, and further randomly assigned to training and validation sets. The least absolute shrinkage and selection operator (LASSO) regression model was used to screen out significant features for construction of nomogram. Multivariable logistic regression analysis was applied to build a nomogram-based predicting model incorporating the variables selected in the LASSO regression model. The area under the curve (AUC) of the receiver operating characteristics (ROC), calibration plot and decision curve analysis (DCA) were performed to estimate the discrimination, calibration and utility of the nomogram model respectively.ResultsA total of 463 patients with DES implantation were enrolled and randomized in the development and validation sets. The predication nomogram was constructed with five risk factors including prior PCI, hyperglycemia, stents in left anterior descending artery (LAD), stent type, and absence of clopidogrel, which proved reliable for quantifying risks of ISR for patients with stent implantation. The AUC of development and validation set were 0.706 and 0.662, respectively, indicating that the prediction model displayed moderate discrimination capacity to predict restenosis. The high quality of calibration plots in both datasets demonstrated strong concordance performance of the nomogram model. Moreover, DCA showed that the nomogram was clinically useful when intervention was decided at the possibility threshold of 9%, indicating good utility for clinical decision-making.ConclusionsThe individualized prediction nomogram incorporating 5 commonly clinical and angiographic characteristics for patients undergoing PCI can be conveniently used to facilitate early identification and improved screening of patients at higher risk of ISR.

Dataset Information

Genetic risk factors for restenosis after percutaneous coronary intervention in Kazakh population.

Publications

Genetic risk factors for restenosis after percutaneous coronary intervention in Kazakh population.

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