Creating and validating a warfarin pharmacogenetic dosing algorithm for Colombian patients

Association between polymorphisms of the VKORC1 and CYP2C9 genes and warfarin maintenance dose in Peruvian patients

AIMS

The aim of this study was to investigate the association between VKORC1 and CYP2C9 genes polymorphisms and the maintenance dose of warfarin in Peruvian patients.

METHODS

An observational study was conducted on outpatients from the Hospital Grau ESSALUD in Lima, Peru. The participants were selected using nonprobabilistic convenience sampling. Inclusion criteria required patients to have been on anticoagulation therapy for >3 months, maintain stable doses of warfarin (consistent dose for at least 3 outpatient visits), and maintain an international normalized ratio within the therapeutic range of 2.5-3.5. DNA samples were obtained from peripheral blood for gene analysis.

RESULTS

Seventy patients (mean age of 69.6 ± 13.4 years, 45.7% female) were included in the study. The average weekly warfarin dose was 31.6 ± 15.2 mg. The genotypic frequencies of VKORC1 were as follows: 7.1% (95% confidence interval, 2.4-15.9) for AA; 44.3% (32.4-56.7) for GA; and 48.6% (36.4-60.8) for GG. No deviation from the Hardy-Weinberg equilibrium was observed in the variants studied (P = .56). The mean weekly warfarin doses for AA, GA and GG genotypes were 16.5 ± 2.9, 26.5 ± 9.5 and 37.9 ± 17.1 mg, respectively (P < .001). The genotypic frequencies of CYP2C9 were as follows: 82.8% (72.0-90.8) for CC (*1/*1); 4.3% (1.0-12.0) for CT (*1/*2); and 12.9% (6.1-23.0) for TT (*2/*2). We did not find a significant association between the CYP2C9 gene polymorphism and the dose of warfarin.

CONCLUSIONS

The AA genotype of the VKORC1 gene was associated with a lower maintenance dose of warfarin in Peruvian patients.

Development and validation wise assessment of genotype guided warfarin dosing algorithm in Indian population

OBJECTIVES

A study was conducted to develop and validate the warfarin pharmacogenetic dose optimization algorithm considering the clinical pharmacogenetic implementation consortium (CPIC) recommendations for the Asian ethnicity population.

METHODS

The present prospective observational study recruited warfarin-receiving patients. We collected a three ml blood sample for VKORC1, CYP2C9*2, CYP2C9*3, and CYP4F2 polymorphism assessment during the follow-up visits. Clinical history, sociodemographic and warfarin dose details were noted.

RESULTS

The study recruited 300 patients (250 in derivation and 50 in validation timed cohort) receiving warfarin therapy. The baseline characteristics were similar in both cohorts. BMI, presence of comorbidity, VKORC1, CYP2C9*2, and CYP2C9*3 were identified as covariates significantly affecting the warfarin weekly maintenance dose (p<0.001 for all) and the same were included in warfarin pharmacogenetic dose optimization algorithm building. The algorithm built-in the present study showed a good correlation with Gage (r=0.57, p<0.0001), and IWPC (r=0.51, p<0.0001) algorithms, widely accepted in western side of the globe. The receiver operating characteristic curve analysis showed a sensitivity of 73 %, a positive predictive value of 96 %, and a specificity of 89 %. The algorithm correctly identified the validation cohort's warfarin-sensitive, intermediate reacting, and resistant patient populations.

CONCLUSIONS

Validation and comparisons of the warfarin pharmacogenetic dose optimization algorithm have made it ready for the clinical trial assessment.

Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing

In genes related to drug pharmacokinetics, molecular variations determine interindividual variability in the therapeutic efficacy and adverse drug reactions. The assessment of single-nucleotide variants (SNVs) is used with growing frequency in pharmacogenetic practice, and recently, high-throughput genomic analyses obtained through next-generation sequencing (NGS) have been recognized as powerful tools to identify common, rare and novel variants. These genetic profiles remain underexplored in Latin-American populations, including Colombia. In this study, we investigated the variability of 35 genes included in the ADME core panel (absorption, distribution, metabolism, and excretion) by whole-exome sequencing (WES) of 509 unrelated Colombian individuals with no previous reports of adverse drug reactions. Rare variants were filtered according to the minor allele frequencies (MAF) <1% and potential deleterious consequences. The functional impact of novel and rare missense variants was assessed using an optimized framework for pharmacogenetic variants. Bioinformatic analyses included the identification of clinically validated variants described in PharmGKB and ClinVar databases. Ancestry from WES data was inferred using the R package EthSEQ v2.1.4. Allelic frequencies were compared to other populations reported in the public gnomAD database. Our analysis revealed that rare missense pharmacogenetic variants were 2.1 times more frequent than common variants with 121 variants predicted as potentially deleterious. Rare loss of function (LoF) variants were identified in 65.7% of evaluated genes. Regarding variants with clinical pharmacogenetic effect, our study revealed 89 sequence variations in 28 genes represented by missense (62%), synonymous (22.5%), splice site (11.2%), and indels (3.4%). In this group, ABCB1, ABCC2, CY2B6, CYP2D6, DPYD, NAT2, SLC22A1, and UGTB2B7, are the most polymorphic genes. NAT2, CYP2B6 and DPYD metabolizer phenotypes demonstrated the highest variability. Ancestry analysis indicated admixture in 73% of the population. Allelic frequencies exhibit significant differences with other Latin-American populations, highlighting the importance of pharmacogenomic studies in populations of different ethnicities. Altogether, our data revealed that rare variants are an important source of variability in pharmacogenes involved in the pharmacokinetics of drugs and likely account for the unexplained interindividual variability in drug response. These findings provide evidence of the utility of WES for pharmacogenomic testing and into clinical practice.

Ethnic Diversity and Warfarin Pharmacogenomics

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

Machine Learning for Prediction of Stable Warfarin Dose in US Latinos and Latin Americans

Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model’s ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients (n = 7,030), inclusion of additional predictor variables led to a small but significant improvement in prediction of dose relative to the IWPC algorithm (47.8 versus 46.7% in IWPC, p = 1.43 × 10⁻¹⁵). Nonlinear models using IWPC variables did not significantly improve prediction of dose over the linear IWPC algorithm. In ULLA patients alone (n = 1,734), IWPC performed similarly to all other linear and nonlinear pharmacogenetic algorithms. Our results reinforce the validity of IWPC in a large, ethnically diverse population and suggest that additional variables that capture warfarin dose variability may improve warfarin dose prediction algorithms.

Metabolizer phenotype prediction in different Peruvian ethnic groups through CYP2C9 polymorphisms

OBJECTIVES

The CYP2C9 gene have three common alleles, CYP2C9*1, CYP2C9*2 and CYP2C9*3, associated with different homozygous (*1/*1, *2/*2 and *3/*3) and heterozygous (*1/*2 and *1/*3) genotypes, which in turn are related to extensive (gEM), intermediate (gIM) and poor (gPM) metabolizers. Likewise, the inter-ethnic variability was intimately associated with different drug metabolism. Therefore, the aim of the present study was predict the metabolizer phenotypes in different Peruvian ethnic groups from lowland (<2,500 m) and highland (>2,500 m).

METHODS

TaqMan genotyping assays were performed in a group of 174 healthy unrelated Peruvian individuals.

RESULTS

In this study, the allelic comparison between the three eco-regions showed that the CYP2C9*1 was the most common in Andean (96.32%); the *2 was the most frequent in Coast (7.45%, p<0.05). Regarding the *3 was the most common in Amazonian (6.25%, p<0.05). In a corroborative manner, the gEM was the most common in Andean (94.74%), the gIM in Coast (17.02%) and gPM in Amazonian (6.25%) populations.

CONCLUSIONS

Our study provides a valuable source of information about to metabolizer phenotype drugs in different Peruvian ethnic groups. In this way, it could be established suitable genetic-dosage medicaments for various common diseases in these heterogenetic populations.

Whole-Exome Sequencing in Patients Affected by Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis Reveals New Variants Potentially Contributing to the Phenotype

Background

Adverse drug reactions (ADRs) are frequent occurring events that can essentially be defined as harmful or unpleasant symptoms secondary to the use of a medicinal product. ADRs involve a wide spectrum of clinical manifestations ranging from minor itching and rash to life-threatening reactions. Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare ADRs. SJS-TEN may be considered a polygenic pathology due to additive/epistatic effects caused by sequence variants in numerous genes. Next-generation sequencing (NGS) represents a potentially interesting exploration tool in such scenario as it facilitates the simultaneous analysis of large genomic regions and genes at affordable cost.

Methods

The present study has involved using whole-exome sequencing (WES) for the first time on SJS-TEN patients. It involved robust and innovative multistep bioinformatics analysis focusing on 313 candidate genes potentially participating in the disease’s aetiology, specific drugs’ metabolism and gene regulation.

Results

We identified combinations of frequently occurring and rare variants that may contribute to the disease’s pathogenesis. Depending on the specific drug being taken, different variants (and alleles) in NAT2, CYP2D8, CYP2B6, ABCC2, UGT2B7 and TCF3 were identified as coherent candidates representing potential future markers for SJS-TEN.

Conclusion

The present study proposed and has described (for the first time) a large-scale genomic analysis of patients affected by SJS-TEN. The genes and variants identified represent relevant candidates potentially participating in the disease’s pathogenesis. Corroborating that proposed by others, we found that complex combinations of frequently occurring and rare variants participating in particular drug metabolism molecular cascades could be associated with the phenotype. TCF3 TF may be considered a coherent candidate for SJS-TEN that should be analysed in new cohorts of patients having ADRs.

Evaluation of the impact of body mass index on venous thromboembolism risk factors

In this paper, we investigate the interaction impacts of body mass index (BMI) on the other important risk factors for venous thromboembolism (VTE), using deep venous thrombosis (DVT) patient data from the International Warfarin Pharmacogenetics Consortium (IWPC). We apply eight machine learning techniques, including naive Bayes classifier (NB), support vector machine (SVM), elastic net regression (ENET), logistic regression (LR), lasso regression (LAR), multivariate adaptive regression splines (MARS), boosted regression tree (BRT) and random forest model (RF). The RF method is selected as the best model for classification. Out of 33 features considered in this study, we identify 12 variables as relatively important risk factors for VTE. Finally, we examine the interaction impacts of BMI on these important VTE risk factors. We conclude that the impacts of risk factors on VTE incidence are varying across different BMI groups, and the variations are different for different risk factors. Therefore the interaction impacts of BMI on the other risk factors have to be taken into account in order to better understand the incidence of VTE.

Possible Genetic Determinants of Response to Phenytoin in a Group of Colombian Patients With Epilepsy

Background

Epilepsy is a serious health problem worldwide. Despite the introduction of new antiepileptic drugs (AEDs) almost 30% of these patients have drug-resistant forms of the disease (DRE), with a significant increase in morbi-mortality.

Objective

Our objective was to assess the impact of some genetic factors and its possible association with treatment response and adverse drug reactions (ADRs) to phenytoin in 67 adult Colombian patients with epilepsy.

Methods

We conducted an analytical, observational, prospective cohort study to screen four polymorphisms in pharmacogenes: CYP2C9*2-c.430C>T (rs1799853), CYP2C9*3-c.1075A>C (rs1057910), ABCB1-c.3435T>C (rs1045642), and SCN1A-IVS5-91G>A (rs3812718), and their association with treatment response. Patients were followed for 1 year to confirm the existence of DRE (non-response) and ADRs using an active pharmacovigilance approach, followed by a consensus in order to classify ADRs according to causality, preventability, intensity and their relation with phenytoin dose, the duration of treatment, and susceptibility factors (DoTS methodology).

Results

A little more than half of evaluated subjects (52.2%) were non-responding to phenytoin. Regarding the genotype-phenotype correlation there was no association between polymorphisms of SCN1A and ABCB1 and DRE (non-response) (p = 0.34), and neither with CYP2C9 polymorphisms and the occurrence of ADRs (p = 0.42). We only found an association between polymorphic alleles of CYP2C9 and vestibular-cerebellar ADRs (dizziness, ataxia, diplopia, and dysarthria) (p = 0.001). Alleles CYP2C9*2-c.430C>T and CYP2C9*3-c.1075A>C were identified as susceptibility factors to ADRs in 24% of patients.

Conclusions

Decreased function alleles of CYP2C9 were highly predictive of vestibular-cerebellar ADRs to phenytoin in our study (p = 0.001). However, the genetic variants CYP2C9*2-c.430C>T, CYP2C9*3-c.1075A>C, ABCB1-c.3435T>C, and SCN1A-IVS5-91G>A, were not associated with treatment response in our study.

Functionally Significant Coumarin-Related Variant Alleles and Time to Therapeutic Range in Chilean Cardiovascular Patients

Despite the development of new oral agents over the last decade, vitamin K antagonists (VKAs) remain the most widely used anticoagulants for treating and preventing thromboembolism worldwide. In Chile, the Ministry of Health indicates that acenocoumarol should be used in preference to any other coumarin. Complications of inappropriate dosing are among the most frequently reported adverse events associated with this medication. It is well known that polymorphisms in pharmacokinetic and pharmacodynamic proteins related to coumarins (especially warfarin) influence response to these drugs. This work analyzed the impact of CYP2C19*2 (rs4244285), CYP1A2*1F (rs762551), GGCx (rs11676382), CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), CYP4F2 (rs2108622), VKORC1 (rs9923231), VKORC1 (rs7294), CYP3A4*1B (rs2740574), and ABCB1 (rs1045642) polymorphisms on time to therapeutic range for oral anticoagulants in 304 Chilean patients. CYP2C9*3 polymorphisms were associated with time to therapeutic range for acenocoumarol in Chilean patients, and the CYP4F2 TT genotype, MDR1 A allele, CYP1A2 A allele, and CYP3A4T allele are promising variants that merit further analysis. The presence of polymorphisms explained only 4.1% of time to therapeutic range for acenocoumarol in a multivariate linear model. These results improve our understanding of the basis of ethnic variations in drug metabolism and response to oral anticoagulant therapy. We hope that these findings will contribute to developing an algorithm for VKA dose adjustment in the Chilean population in the near future, decreasing the frequency of stroke, systemic embolism, and bleeding-related adverse events.

A Pharmacogenetically Guided Acenocoumarol Dosing Algorithm for Chilean Patients: A Discovery Cohort Study

BACKGROUND

Vitamin K antagonists (VKA) are used as prophylaxis for thromboembolic events in patients with cardiovascular diseases. The most common VKA are warfarin and acenocoumarol. These drugs have a narrow therapeutic margin and high inter-individual response variability due to clinical and pharmacogenetic variables.

OBJECTIVE

The authors aim to develop an algorithm comprised of clinical and genetic factors to explain the variability in the therapeutic dose of acenocoumarol among Chilean patients.

METHODOLOGY

DNA was obtained from 304 patients as a discovery cohort with an international normalized ratio (INR) range of 2.0-3.0. The non-genetic (demographic and clinical) variables were also recorded. Genotype analyses were performed using real-time PCR for VKORC1 (rs9923231), VKORC1 (rs7294), GGCx (rs11676382), CYP4F2 (rs2108622), ABCB1 (rs1045642), CYP2C9*2 (rs1799853), ApoE (rs429358), and CYP2C9*3 (rs1057910).

RESULTS

The clinical variables that significantly influenced the weekly therapeutic dose of VKA were age, sex, body mass index (BMI), and initial INR, collectively accounting for 19% of the variability, and the genetic variables with a significant impact were VKORC1 (rs9923231), CYP2C9*2 (rs1799853), and CYP2C9*3 (rs1057910), explaining for another 37% of the variability.

CONCLUSION

We developed an algorithm that explains 49.99% of the variability in therapeutic VKA dosage in the Chilean population studied. Factors that significantly affected the dosage included VKORC1, CYP2C9*2, and CYP2C9*3 polymorphisms, as well as age, sex, BMI, and initial INR.