APOB gene polymorphisms may affect the risk of minor or minimal bleeding complications in patients on warfarin maintaining therapeutic INR

Yee, Jeong; Kim, Woorim; Chang, Byung Chul; Chung, Jee Eun; Lee, Jun Young; Gwak, Hye Sun

doi:10.1038/s41431-019-0450-1

Cited by 6 publications

(6 citation statements)

References 32 publications

(29 reference statements)

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“…This is a retrospective analysis of prospectively collected blood samples. The details for study patients have already been described in previous papers [ 7 , 8 ]. Study patients were recruited from the previous study cohort, entitled the Ewha-Severance Treatment (EAST) Group of Warfarin.…”

Section: Methodsmentioning

confidence: 99%

“…The NNG, which represents the number of patients for preventing one additional bleeding complication, was calculated by the following equations [ 7 ]: Relative risk reduction (RRR) = (AOR − 1)/AOR; Absolute risk reduction (ARR) = RRR × Risk no genotyping ; NNG = 1/ARR, where Risk no genotyping was defined as the risk of higher incidence of bleeding complications without genotyping. To assess the cumulative effect of clinical factors and multiple SNPs on bleeding complications, the WRS was created based on variables that were included in each model in this study.…”

Section: Methodsmentioning

confidence: 99%

“…According to Pourgholi et al, CYP2C9 and NQO1 variants may affect bleeding complications [ 6 ]. Our previous research also identified several gene polymorphisms (e.g., APOB and GATA4 ), which can affect warfarin bleedings [ 7 , 8 ]. However, compared to pharmacogenomic studies for warfarin dose [ 9 ], previous studies have rarely assessed the genetic effects on bleeding complications during anticoagulation therapy.…”

Section: Introductionmentioning

confidence: 99%

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Gene Polymorphisms of the Renin-Angiotensin System and Bleeding Complications of Warfarin: Genetic-Based Machine Learning Models

et al. 2021

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Background: This study aimed to investigate the effects of genetic variants and haplotypes in the renin–angiotensin system (RAS) on the risk of warfarin-induced bleeding complications at therapeutic international normalized ratios (INRs). Methods: Four single nucleotide polymorphisms (SNPs) of AGT, two SNPs of REN, three SNPs of ACE, four SNPs of AGTR1, and one SNP of AGTR2, in addition to VKORC1 and CYP2C9 variants, were investigated. We utilized logistic regression and several machine learning methods for bleeding prediction. Results: The study included 142 patients, among whom 21 experienced bleeding complications. We identified a haplotype, H2 (TCG), carrying three SNPs of ACE (rs1800764, rs4341, and rs4353), which showed a significant relation with bleeding complications. After adjusting covariates, patients with H2/H2 experienced a 0.12-fold (95% CI 0.02–0.99) higher risk of bleeding complications than the others. In addition, G allele carriers of AGT rs5050 and A allele carriers of AGTR1 rs2640543 had 5.0- (95% CI 1.8–14.1) and 3.2-fold (95% CI 1.1–8.9) increased risk of bleeding complications compared with the TT genotype and GG genotype carriers, respectively. The AUROC values (mean, 95% CI) across 10 random iterations using five-fold cross-validated multivariate logistic regression, elastic net, random forest, support vector machine (SVM)–linear kernel, and SVM–radial kernel models were 0.732 (0.694–0.771), 0.741 (0.612–0.870), 0.723 (0.589–0.857), 0.673 (0.517–0.828), and 0.680 (0.528–0.832), respectively. The highest quartile group (≥75th percentile) of weighted risk score had approximately 12.0 times (95% CI 3.1–46.7) increased risk of bleeding, compared to the 25–75th percentile group, respectively. Conclusion: This study demonstrated that RAS-related polymorphisms, including the H2 haplotype of the ACE gene, could affect bleeding complications during warfarin treatment for patients with mechanical heart valves. Our results could be used to develop individually tailored intervention strategies to prevent warfarin-induced bleeding.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Gene Polymorphisms of the Renin-Angiotensin System and Bleeding Complications of Warfarin: Genetic-Based Machine Learning Models

et al. 2021

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“…The same variants are reported in PharmGKB, but only two have a significant association with warfarin. Variants rs1042034 and rs693 were studied in Korean patients under warfarin treatment and the risk of hemorrhage, but the T and G alleles, respectively, were not associated ( Yee et al, 2019 ). However, in the same study, the G allele in rs1367117 and the G allele in rs6789899 were associated with an increased risk of hemorrhage when using warfarin in people with heart valve replacement.…”

Section: Discussionmentioning

confidence: 99%

Frequencies of variants in genes associated with dyslipidemias identified in Costa Rican genomes

et al. 2023

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Dyslipidemias are risk factors in diseases of significant importance to public health, such as atherosclerosis, a condition that contributes to the development of cardiovascular disease. Unhealthy lifestyles, the pre-existence of diseases, and the accumulation of genetic variants in some loci contribute to the development of dyslipidemia. The genetic causality behind these diseases has been studied primarily on populations with extensive European ancestry. Only some studies have explored this topic in Costa Rica, and none have focused on identifying variants that can alter blood lipid levels and quantifying their frequency. To fill this gap, this study focused on identifying variants in 69 genes involved in lipid metabolism using genomes from two studies in Costa Rica. We contrasted the allelic frequencies with those of groups reported in the 1000 Genomes Project and gnomAD and identified potential variants that could influence the development of dyslipidemias. In total, we detected 2,600 variants in the evaluated regions. However, after various filtering steps, we obtained 18 variants that have the potential to alter the function of 16 genes, nine variants have pharmacogenomic or protective implications, eight have high risk in Variant Effect Predictor, and eight were found in other Latin American genetic studies of lipid alterations and the development of dyslipidemia. Some of these variants have been linked to changes in blood lipid levels in other global studies and databases. In future studies, we propose to confirm at least 40 variants of interest from 23 genes in a larger cohort from Costa Rica and Latin American populations to determine their relevance regarding the genetic burden for dyslipidemia. Additionally, more complex studies should arise that include diverse clinical, environmental, and genetic data from patients and controls and functional validation of the variants.

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“…In recent years, a number of genetic association studies have suggested that there are multiple genetic risk factors for ischemic stroke, and multiple risk loci were found to affect the susceptibility to ischemic stroke. Cacabelos et al (2018) and Yee et al (2019) showed that the C7673T polymorphism of APOB gene was significantly associated with the risk of ischemic stroke. Chen et al (2019), Nordestgaard et al (2018) confirmed that the polymorphism of ϵ 2,ϵ3,ϵ4 of APOE gene was associated with ischemic stroke.…”

Section: Introductionmentioning

confidence: 99%

Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

et al. 2020

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Stroke ranks the second leading cause of death among people over the age of 60 in the world. Stroke is widely regarded as a complex disease that is affected by genetic and environmental factors. Evidence from twin and family studies suggests that genetic factors may play an important role in its pathogenesis. Therefore, research on the genetic association of susceptibility genes can help understand the mechanism of stroke. Genome-wide association study (GWAS) has found a large number of stroke-related loci, but their mechanism is unknown. In order to explore the function of single-nucleotide polymorphisms (SNPs) at the molecular level, in this paper, we integrated 8 GWAS datasets with brain expression quantitative trait loci (eQTL) dataset to identify SNPs and genes which are related to four types of stroke (ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke). Thirty-eight SNPs which can affect 14 genes expression are found to be associated with stroke. Among these 14 genes, 10 genes expression are associated with ischemic stroke, one gene for large artery stroke, six genes for cardioembolic stroke and eight genes for small vessel stroke. To explore the effects of environmental factors on stroke, we identified methylation susceptibility loci associated with stroke using methylation quantitative trait loci (MQTL). Thirty-one of these 38 SNPs are at greater risk of methylation and can significantly change gene expression level. Overall, the genetic pathogenesis of stroke is explored from locus to gene, gene to gene expression and gene expression to phenotype.

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APOB gene polymorphisms may affect the risk of minor or minimal bleeding complications in patients on warfarin maintaining therapeutic INR

Cited by 6 publications

References 32 publications

Gene Polymorphisms of the Renin-Angiotensin System and Bleeding Complications of Warfarin: Genetic-Based Machine Learning Models

Gene Polymorphisms of the Renin-Angiotensin System and Bleeding Complications of Warfarin: Genetic-Based Machine Learning Models

Frequencies of variants in genes associated with dyslipidemias identified in Costa Rican genomes

Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

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