Optimization of warfarin dose by population-specific pharmacogenomic algorithm

Stability of Anticoagulation Following Acenocoumarin in Stroke Patients: Role of Pharmacogenomics and Acquired Factors

OBJECTIVE

Pharmacogenomics plays an important role in drug metabolism. A stable anticoagulation is important for primary and secondary prevention of cardioembolic stroke and cerebral venous sinus thrombosis (CVST). We report the role of cytochrome P450 ( CYP2C9*2/*3 ) and vitamin K epoxide reductase subunit 1 ( VKORC1 ) genotypes and acquired causes in maintaining stability of anticoagulation following acenocoumarin in cardioembolic stroke and CVST.

METHODS

The study comprised 157 individuals with cardioembolic stroke and CVST who were on acenocoumarin. Their comorbidities, comedication, and dietary habits were noted. Prothrombin time and international normalized ratio (INR) were measured during follow-up, and the coagulation status was categorized as stable (>50% occasions in therapeutic range) and unstable (>50% below and above therapeutic range). Genotyping of VKORC1 , CYP2C9*2 , and CYP2C9*3 was done by polymerase chain reaction-restriction fragment length polymorphism. Bleeding and embolic complications were noted. The predictors of unstable INR were evaluated using multivariate analysis.

RESULTS

INR was stable in 47.8% and unstable in 52.2% of patients. Patients with mutant genotypes required low dose of acenocoumarin. The predictors of unstable INR were metallic valve (odds ratio [OR] 4.07, 95% confidence interval [CI] 1.23-13.49, P = 0.02), use of digoxin (OR 0.031, 95% CI 0.13-0.74, P = 0.09), proton pump inhibitor (OR 0.23, 95% CI 0.06-0.91, P = 0.037), sodium valproate (OR 0.22, 95% CI 0.05-0.85, P = 0.029), and CYP2C9*2 genotype (OR 5.57, 95% CI 1.19-26.06, P = 0.02).

CONCLUSIONS

Variant genotypes of VKORC1 , CYP2C9*2 , and CYP2C9*3 required lower dose of acenocoumarin, and CYP2C9*2 was associated with unstable INR. Comedication is a modifiable risk factor that needs attention.

Validating two international warfarin pharmacogenetic dosing algorithms for estimating the maintenance dose for patients in Singapore

Predicting optimal warfarin dosing is difficult due to complex pharmacodynamics and pharmacokinetics, narrow therapeutic index and susceptibility to many factors.1 Genetic variations of the CYP2C9 and VKORC1 enzymes, occurring in different frequencies in different populations, play a significant role in determining warfarin dosing.1-4 Using pharmacogenetic dosing algorithms to predict warfarin doses may shorten the time to achieve target International Normalised Ratio (INR) and stable dose.2,5 The Clinical Pharmacogenetics Implementation Consortium Guidelines 2017 Update4 recommends the Gage (WarfarinDosing.org7) and International Warfarin Pharmacogenetics Consortium (IWPC)8 pharmacogenetic algorithms.

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.

Pharmacogenetic variants influence vitamin K anticoagulant dosing in patients with mechanical prosthetic heart valves

Background: Vitamin K antagonists (VKAs) are class I oral anticoagulants that are widely prescribed following surgical heart valve implantation. The objective of this study was to quantify the relative effects of VKORC1, CYP2C9 and CYP4F2 genotypes in predicting VKA dosing. Materials & methods: A total of 506 South Indian patients with mechanical prosthetic heart valves who were prescribed oral VKAs, such as warfarin or acenocoumarol, were genotyped. The discriminatory ability of mutant genotypes to predict dose categories and bleeding events was assessed using regression analysis. Results: The VKORC1 rs9923231, CYP2C9*3 and CYP4F2*3 mutant genotypes significantly influenced VKA-dose requirements and explained 27.47% of the observed dose variation. Conclusion: These results support pharmacogenetic screening for initial VKA dosing among South Indian patients with mechanical prosthetic heart valves.

Genetic and Nongenetic Determinants of Variable Warfarin Dose Requirements: A Report from North India

INTRODUCTION

Warfarin is widely used and will continue to be prescribed especially in developing countries due to its low cost. Given the huge patient load requiring anticoagulation, there is a need to develop strategies to optimize warfarin therapy for ensuring safe and effective anticoagulation. In the present work, we aimed at elucidating the association of genetic and nongenetic variables with warfarin dose requirement in patients attending the cardiovascular clinic in a tertiary care center of North India.

METHODS

This was a prospective study conducted over 1 year. Patient demographic and clinical details were captured in customized case record forms. Genotyping was done using the polymerase chain reaction-restriction fragment length polymorphism method. Pharmacogenetic influence of CYP2C9 (rs1799853 and rs1057910) and VKORC1 (rs9923231) variant alleles was studied. The association of genetic and nongenetic factors with warfarin dose was quantified using a stepwise multivariate linear regression model.

RESULTS

Two hundred and forty patients were screened. Data from 82 eligible patients were used for quantifying the association of genetic and nongenetic factors with warfarin dose. A descriptive model based on CYP2C9*3 (rs1057910) and VKORC1 (rs9923231) variant alleles and BMI was developed. The model explains nearly half of the interindividual variation in warfarin dose requirement.

CONCLUSION

The model explains nearly half of the interindividual variation in warfarin dose in patients with atrial fibrillation and or requiring valve replacement.

Pharmacogenetic determinants of warfarin in the Indian population

BACKGROUND

Several studies optimized the warfarin dose based on CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, CYP4F2 V433M. But, the information on the rare variants is lacking. In this study, we have explored the prevalence of common and rare pharmacogenetic determinants of warfarin and determined their damaging nature.

METHODS

We have analyzed 2000 healthy adults using the Infinium global screening array (GSA) for 15 pharmacogenetic determinants of warfarin. In addition, we have elucidated the impact of these variants on protein function, stability, dynamics, evolutionary preservation, and ligand binding propensity.

RESULTS

The GSA Analysis has revealed that CYP4F2 V433M (MAF: 39.425%), VKORC1 -1639 G > A (MAF: 20.5%), CYP2C9*3 (MAF:9.925%), and CYP2C9*2 (MAF:4.575%) are common, while CYP2C9*14 (MAF: 1.475%), CYP2C9*4 (0.175%), CYP2C9*5 (0.125%), and CYP2C9*11 (0.125%) are rare. Position-specific evolutionary preservation (PSEP) analysis has revealed that CYP2C9*4 is possibly damaging, while CYP2C9*5, CYP2C9*11, and CYP2C9*14 are probably damaging. CYP2C9*4 has high thermolability (-10.14 kcal/mol). Among the rare CYP2C9 variants, CYP2C9*4 and CYP2C9*11 exert destabilizing effects and may have increased molecular flexibility, while CYP2C9*5 and CYP2C9*14 exert stabilizing effects and may have decreased molecular flexibility. DNase I footprint analysis has revealed the loss of the E-box consensus sequence due to VKORC1 -1639 G > A polymorphism.

CONCLUSION

CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A and CYP4F2 V433M are common; CYP2C9*4, CYP2C9*5, CYP2C9*11, and CYP2C9*14 variants are rare in Indian subjects. All the CYP2C9 variants are found to be damaging. DNase I footprint analysis provided the mechanistic rationale for the association of VKORC1 -1639 G > A with warfarin sensitivity.

Genetic polymorphisms and dosing of vitamin K antagonist in Indian patients after heart valve surgery

Purpose

Vitamin K antagonists (VKAs), such as warfarin and acenocoumarol, exert their anti-coagulant effect by inhibiting the subunit 1 of vitamin K epoxide reductase complex (VKORC1). CYP2C9 is a hepatic drug-metabolizing enzyme in the CYP450 superfamily and is the primary metabolizing enzyme of warfarin. Three single nucleotide polymorphisms, two in the CYP2C9 gene, namely CYP2C9*2 and CYP2C9*3, and one in the VKORC1 gene (c.- 1639G > A, rs9923231), have been identified to reduce VKA metabolism and enhance their anti-coagulation effect. The purpose of this study is to evaluate the prevalence of CYP2C9 and VKORC1 polymorphism in Indians receiving VKA-based anti-coagulation after valve surgery and to evaluate the usefulness of genetic information in managing VKA-based anti-coagulation.

Methods

In the current prospective observational study, 150 patients who underwent heart valve surgery and had stable INR were genotyped for VKORC1 (- 1639 G > A), CYP2C9*2, and CYP2C9*3. The VKA dosage was estimated from published algorithms and compared to the clinically stabilized dosage.

Results

Out of 150 patients, 101 (67.33%) were on warfarin and 49 (32.66%) were on acenocoumarol. Majority of the patients, the 83 in warfarin group and the 40 in acenocoumarol group, had a wild CYP2C9 diplotype. The rest had a mutant (CYP2C9*2 or CYP2C9*3) diplotype. Similarly, 67 patients in the warfarin group and 35 patients in the acenocoumarol group had wild type (G/G) of VKORC1 genotype. The rest had a mutant (G/A or A/A) VKORC1 genotype. In the warfarin group, based on the genotype, 51.5% of the patients were extensive or normal metabolizers, and 47.4% of the patients were intermediate metabolizers of VKAs. In the acenocoumarol group, 61.2% of the patients were extensive or normal metabolizers, and 38.8% of the patients were intermediate metabolizers. Individually, alleles of VKORC1 (- 1639 G > A), CYP2C9*2, and CYP2C9*3 had mean dosage reduction effect on VKA dosage, which co-related to the clinically stabilized dosages (P < 0.0001). Among the VKORC1 (- 1639 G > A) cohort, the reduction in warfarin mean weekly dosage was 13.48 mg as compared to the wild-type category (P < 0.0001) and similarly, the reduction in the mean weekly acenocoumarol dose was 6.07 mg (P < 0.03) as compared to the wild type after adjusting for age, gender, and body mass index.

Conclusion

Single nucleotide polymorphism in the CYP2C9 gene and in the VKORC1 gene is present in nearly 40% of Indian patients. VKORC1 (- 1639 G > A), CYP2C9*2, and CYP2C9*3 genotypes have significant dosage-lowering effects on VKA-based anti-coagulation therapy. The trend in estimated dosages of VKAs co-related to that of observed the clinically stabilized dosage in the cohort. The pharmacogenomic calculators used in this study tend to overestimate the VKA dosages as compared to clinical dosage due to the limitations in the algorithms and in our study. A new algorithm based on a larger dataset capturing the vast genetic variability across the Indian population and relevant clinical factors could provide better results.

Effect of CYP4F2, VKORC1, and CYP2C9 in Influencing Coumarin Dose: A Single-Patient Data Meta-Analysis in More Than 15,000 Individuals

The cytochrome P450 (CYP)4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at the individual patients level to capture the possible effect of ethnicity, gene-gene interaction, or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists of 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95% confidence interval (CI) 7-10%), with a higher effect in women, in patients taking acenocoumarol, and in white patients. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived.

Follow-up and management of valvular heart disease patients with prosthetic valve: a clinical practice guideline for Indian scenario

PURPOSE

Valvular heart disease (VHD) patients after prosthetic valve implantation are at risk of thromboembolic events. Follow-up care of patients with prosthetic valve has a paramount role in reducing the morbidity and mortality. Currently, in India, there is quintessential need to stream line the follow-up care of prosthetic valve patients. This mandates the development of a consensus guideline for the antithrombotic therapy in VHD patients post prosthetic valve implantation.

METHODS

A national level panel was constituted comprising 13 leading cardio care experts in India who thoroughly reviewed the up to date literature, formulated the recommendations, and developed the consensus document. Later on, extensive discussions were held on this draft and the recommendations in 8 regional meetings involving 79 additional experts from the cardio care in India, to arrive at a consensus. The final consensus document is developed relying on the available evidence and/or majority consensus from all the meetings.

RESULTS

The panel recommended vitamin K antagonist (VKA) therapy with individualized target international normalized ratio (INR) in VHD patients after prosthetic valve implantation. The panel opined that management of prosthetic valve complications should be personalized on the basis of type of complications. In addition, the panel recommends to distinguish individuals with various co-morbidities and attend them appropriately.

CONCLUSIONS

Anticoagulant therapy with VKA seems to be an effective option post prosthetic valve implantation in VHD patients. However, the role for non-VKA oral therapy in prosthetic valve patients and the safety and efficacy of novel oral anticoagulants in patients with bioprosthetic valve need to be studied extensively.

Value of VKORC1 (-1639G>A) rs9923231 genotyping in predicting warfarin dose: A replication study in South Indian population

OBJECTIVE

Warfarin is the most commonly prescribed oral anticoagulant, although having a narrow therapeutic index and wide interindividual variability. The aim of this study was to replicate the utility of VKORC1 (-1639G>A) rs9923231 genotyping in predicting the mean daily dose and to evaluate its ability to categorize warfarin-treated patients to high-, intermediate-, or low-dose categories in the South Indian population.

MATERIALS AND METHODS

A cohort of 222 warfarin-treated patients was genotyped using restriction fragment length polymorphism method. The influence of the rs9923231 polymorphism on the variations in the mean daily dose was compared using one-way analysis of variance and linear regression analysis. Discriminatory ability of the rs9923231 polymorphism to group the patients into ordered dose categories was assessed by estimating the proportional odds ratios using the ordered logit regression analysis.

RESULTS

The frequency of AA genotype and A allele in the study sample was found to be 1.8% and 9.23%, respectively, which was similar to reports from other South Indian populations. The mean daily dose required to achieve the optimum international normalized ratio was significantly lower in AA homozygous genotype carriers (3.99 ± 1.67 mg/day) and GA heterozygous (4.26 ± 1.57 mg/day) compared to the GG genotype carriers (5.51 ± 2.13 mg/day), p = 0.003. The A allele carriers (GA+AA genotypes) had a 3.23 higher odds of being grouped as a low-dose requiring category compared to non-carriers (95% CI 1.49-6.98, p = 0.003).

CONCLUSIONS

These preliminary results strongly support the use of VKORC1 (-1639G>A) rs9923231 polymorphism for genetically guided initial warfarin dosing in South Indian patients with heart valve replacements.

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (LR) models were used to predict the bioavailability of tacrolimus and risk for post-transplant diabetes, respectively. The five-fold cross-validation of ANN model showed good correlation with the experimental data of bioavailability (r2 = 0.93-0.96). Younger age, male gender, optimal body mass index were shown to exhibit lower bioavailability of tacrolimus. ABCB1 1236 C>T and 2677G>T/A showed inverse association while CYP3A5*3 showed a positive association with the bioavailability of tacrolimus. Gender bias was observed in the association with ABCB1 3435 C>T polymorphism. CYP3A5*3 was shown to interact synergistically in increasing the bioavailability in combination with ABCB1 1236 TT or 2677GG genotypes. LR model showed an independent association of ABCB1 2677 G>T/A with post transplant diabetes (OR: 4.83, 95% CI: 1.22-19.03). Multifactor dimensionality reduction analysis (MDR) revealed that synergistic interactions between CYP3A5*3 and ABCB1 2677 G>T/A as the determinants of risk for post-transplant diabetes. To conclude, the ANN and MDR models explore both individual and synergistic effects of variables in modulating the bioavailability of tacrolimus and risk for post-transplant diabetes.

Warfarin Dosing Algorithms Underpredict Dose Requirements in Patients Requiring ≥7 mg Daily: A Systematic Review and Meta-analysis

There is preliminary evidence to suggest that some published warfarin dosing algorithms produce biased maintenance dose predictions in patients who require higher than average doses. We conducted a meta-analysis of warfarin dosing algorithms to determine if there exists a systematic under- or overprediction of dose requirements for patients requiring ≥7 mg/day across published algorithms. Medline and Embase databases were searched up to September 2015. We quantified the proportion of over- and underpredicted doses in patients whose observed maintenance dose was ≥7 mg/day. The meta-analysis included 47 evaluations of 22 different warfarin dosing algorithms from 16 studies. The meta-analysis included data from 1,492 patients who required warfarin doses of ≥7 mg/day. All 22 algorithms were found to underpredict warfarin dosing requirements in patients who required ≥7 mg/day by an average of 2.3 mg/day with a pooled estimate of underpredicted doses of 92.3% (95% confidence interval 90.3-94.1, I² = 24%).

Evaluation of a pharmacogenetic-based warfarin dosing algorithm in patients with low time in therapeutic range - study protocol for a randomized controlled trial

Background

Time in therapeutic range (TTR) is a measurement of quality of warfarin therapy and lower TTR values (<50%) are associated with greater risk of thromboembolic and bleeding events. Recently, we developed a pharmacogenetic-based warfarin dosing algorithm specifically calibrated for a Brazilian patient sample. The aims of this study are: to evaluate the impact of a genetic-based algorithm, compared to traditional anticoagulation, in the time to achieve the therapeutic target and in TTR percentage; and to assess the cost-effectiveness of genotype-guided warfarin dosing in a specific cohort of patients with low TTR (<50%) from a tertiary cardiovascular hospital.

Methods/design

This study is a randomized controlled trial in patients (n = 300) with atrial fibrillation with TTR < 50%, based on the last three INR values. At the first consultation, patients will be randomized into two groups: TA group (traditional anticoagulation) and PA group (pharmacogenetic anticoagulation). For the first group, the physician will adjust the dose according to current INR value and, for the second group, a pharmacogenetic algorithm will be used. At the second, third, fourth and fifth consultations (with an interval of 7 days each) INR will be measured and, if necessary, the dose will be adjusted based on guidelines. Afterwards, patients who are INR stable will begin measuring their INR in 30 day intervals; if the patient’s INR is not stable, the patient will return in 7 days for a new measurement of the INR. Outcomes measures will include the time to achieve the therapeutic target and the percentage of TTR at 4 and 12 weeks. In addition, as a secondary end-point, pharmacoeconomic analysis will be carried out. Ethical approval was granted by the Ethics Committee for Medical Research on Human Beings of the Clinical Hospital of the University of São Paulo Medical School.

Discussion

This randomized study will include patients with low TTR and it will evaluate whether a population-specific genetic algorithm might be more effective than traditional anticoagulation for a selected group of poorly anticoagulated patients.

Trial registration

ClinicalTrials.gov, NCT02592980. Registered on 29 October 2015.

Frequency of Common CYP2C9 Polymorphisms and Their Impact on Warfarin Dose Requirement in Pakistani Population

Polymorphisms in cytochrome P450 (CYP) 2C9 (CYP2C9) gene result in interindividual variability in warfarin dose requirement. There is a need for characterization of genotype frequency distribution in different populations for construction of customized dosing algorithms to enhance the efficacy and reduce the toxicity of warfarin therapy. This study was carried out in Pakistani population to evaluate the contribution of common CYP2C9 polymorphisms to warfarin therapy. A total of 550 stable patients taking warfarin were enrolled after medical history, physical examination, and laboratory investigations. Single blood sample was collected after informed consent. Genomic DNA was extracted, and genotype analysis for CYP2C9*2 and CYP2C9*3 polymorphisms was done by polymerase chain reaction-restriction fragment length polymorphism assay. A number of samples were also analyzed by direct DNA sequencing for validation of the results. Data were analyzed using SPSS version 20. Genotype frequency distribution of CYP2C9*2 and CYP2C9*3 was found to be different from other populations. Of these 2 polymorphisms, CYP2C9*2 did not demonstrate significant effect on warfarin dose requirement, whereas CYP2C9*3 did show significant effect ( P value = .012). It is concluded that there is a need to study genotype frequency distribution and their effect on warfarin dose variability among different populations due to diversity in outcome.

Artificial neural network-based pharmacogenomic algorithm for warfarin dose optimization

AIM

To develop more precise pharmacogenomic algorithm for prediction of safe and effective dose of warfarin.

MATERIALS & METHODS

An artificial neural network (ANN) algorithm was developed by using age, gender, BMI, plasma vitamin K levels, thyroid status and ten genetic variables as the inputs and therapeutic warfarin dose as the output. Hyperbolic tangent function was used to build an ANN architecture.

RESULTS

This model explained 93.5% variability in warfarin dosing and predicted warfarin dose accurately in 74.5% patients whose international normalized ratio (INR) was less than 2.0 and in 83.3% patients whose INR was more than 3.5. This algorithm reduced the out-of-range INRs (odds ratio [OR]: 0.49; 95% CI: 0.30-0.79; p = 0.003), the rate of adverse drug reactions (OR: 0.00; 95% CI: 0.00-1.21; p = 0.06) and time to reach first therapeutic INR (OR: 6.73; 95% CI: 2.17-22.31; p < 0.0001). This algorithm was found to be applicable in both euthyroid and hypothyroid status. S-warfarin/7-hydroxywarfarin ratio was found to increase in subjects with CYP2C9*2 and CYP2C9*3 justifying the warfarin sensitivity attributed to these variants.

CONCLUSION

An application of ANN for warfarin dosing improves predictability and provides safe and effective dosing.

Determination of genotypes using a fully automated molecular detection system

CONTEXT

Although the value of pharmacogenomics to improve patient outcomes has become increasingly clear, adoption in medical practice has been slow, which can be attributed to several factors, including complicated and expensive testing procedures and required equipment, lack of training by private practice physicians, and reluctance of both private and commercial payers to reimburse for such testing.

OBJECTIVES

To evaluate a fully automated molecular detection system for human genotyping assays, starting with anticoagulated whole blood samples, and to perform all sample preparation, assay, and analysis steps automatically with actionable results reported by the system's software.

DESIGN

The genotypes of 254 random individuals were determined by performing bidirectional DNA sequencing, and that information was used to statistically train the imaging software of the automated molecular detection system to distinguish the 3 possible genotypes (ie, homozygous wild type, heterozygous, and homozygous mutant) at each of 3 different loci (CYP2C9*2, CYP2C9*3, and VKORC1).

RESULTS

The resulting software algorithm was able to correctly identify the genotypes of all 254 individuals (100%) evaluated without any further user analysis.

CONCLUSIONS

The EncompassMDx workstation (Rheonix, Inc, Ithaca, New York) is a molecular detection system that can automatically determine the genotypes of individuals in an unattended manner. Considerably less technical expertise was required to achieve results identical to those obtained using more complex, time-consuming, and expensive bidirectional DNA sequencing. This optimized system may dramatically simplify and reduce the costs of pharmacogenomics testing, thus leading to more-widespread use.

Mechanistic insights into the effect of CYP2C9*2 and CYP2C9*3 variants on the 7-hydroxylation of warfarin

AIM

To evaluate the impact of CYP2C9*2 and CYP2C9*3 variants on binding and hydroxylation of warfarin.

MATERIALS & METHODS

Multiple linear regression model of warfarin pharmacokinetics was developed from the dataset of patients (n = 199). Pymol based in silico models were developed for the genetic variants.

RESULTS

CYP2C9*2 and CYP2C9*3 variants exhibited high warfarin/7-hydroxywarfarin (multiple linear regression model), dose-dependent disruption of hydrogen bonds with warfarin, dose-dependent increase in the distance between C7 of S-warfarin and Fe-O of CYP2C9, dose-dependent decrease in the glide scores (in silico).

CONCLUSION

CYP2C9*2 and CYP2C9*3 variants result in disruption of hydrogen bonding interactions with warfarin and longer distance between C7 and Fe-O thus impairing warfarin 7-hydroxylation due to lower binding affinity of warfarin. Original submitted 7 May 2014; Revision submitted 30 October 2014.

Analysis of pharmacogenomic variants associated with population differentiation

In the present study, we systematically investigated population differentiation of drug-related (DR) genes in order to identify common genetic features underlying population-specific responses to drugs. To do so, we used the International HapMap project release 27 Data and Pharmacogenomics Knowledge Base (PharmGKB) database. First, we compared four measures for assessing population differentiation: the chi-square test, the analysis of variance (ANOVA) F-test, Fst, and Nearest Shrunken Centroid Method (NSCM). Fst showed high sensitivity with stable specificity among varying sample sizes; thus, we selected Fst for determining population differentiation. Second, we divided DR genes from PharmGKB into two groups based on the degree of population differentiation as assessed by Fst: genes with a high level of differentiation (HD gene group) and genes with a low level of differentiation (LD gene group). Last, we conducted a gene ontology (GO) analysis and pathway analysis. Using all genes in the human genome as the background, the GO analysis and pathway analysis of the HD genes identified terms related to cell communication. "Cell communication" and "cell-cell signaling" had the lowest Benjamini-Hochberg's q-values (0.0002 and 0.0006, respectively), and "drug binding" was highly enriched (16.51) despite its relatively high q-value (0.0142). Among the 17 genes related to cell communication identified in the HD gene group, five genes (STX4, PPARD, DCK, GRIK4, and DRD3) contained single nucleotide polymorphisms with Fst values greater than 0.5. Specifically, the Fst values for rs10871454, rs6922548, rs3775289, rs1954787, and rs167771 were 0.682, 0.620, 0.573, 0.531, and 0.510, respectively. In the analysis using DR genes as the background, the HD gene group contained six significant terms. Five were related to reproduction, and one was "Wnt signaling pathway," which has been implicated in cancer. Our analysis suggests that the HD gene group from PharmGKB is associated with cell communication and drug binding.

Pharmacogenetic-guided dosing of coumarin anticoagulants: algorithms for warfarin, acenocoumarol and phenprocoumon

Coumarin derivatives, such as warfarin, acenocoumarol and phenprocoumon are frequently prescribed oral anticoagulants to treat and prevent thromboembolism. Because there is a large inter-individual and intra-individual variability in dose-response and a small therapeutic window, treatment with coumarin derivatives is challenging. Certain polymorphisms in CYP2C9 and VKORC1 are associated with lower dose requirements and a higher risk of bleeding. In this review we describe the use of different coumarin derivatives, pharmacokinetic characteristics of these drugs and differences amongst the coumarins. We also describe the current clinical challenges and the role of pharmacogenetic factors. These genetic factors are used to develop dosing algorithms and can be used to predict the right coumarin dose. The effectiveness of this new dosing strategy is currently being investigated in clinical trials.

CYP2C9*3 polymorphism presenting as lethal subdural hematoma with low-dose warfarin

Warfarin is the most common and cheap oral anticoagulant currently used in clinical practice. A high inter-individual variation is seen in the response to warfarin. Recently, pharmacogenetics has gained importance in managing patients on warfarin, both in predicting the optimum required dose as well as in decreasing the risk of bleeding. This case report is a description of a 49-year-old patient who had a lethal subdural hematoma with low-dose warfarin. He was subsequently found to have CYP2C9 gene polymorphism (*1/*3). This case report stresses the importance of pre-prescription assessment of genetic analysis for those initiated on warfarin.

Effect of CYP2C9 and VKORC1 genetic variations on warfarin dose requirements in Indian patients

BACKGROUND

Warfarin, an oral anticoagulant is used in patients who are at increased risk of developing blood clots. The management of warfarin therapy is challenging because it shows large inter and intra individual variability in patient response due to factors like age, gender, diet, concurrent drug interactions and variations in CYP2C9 and VKORC1 genes. Studies implicate that polymorphisms in VKORC1 and CYP2C9 genes are associated with reduced doses of warfarin. The aim of our current study was to characterize the effects of VKORC1 and CYP2C9 gene variations that contribute to variability in warfarin dosing in Indian patients.

METHODS

Genomic DNA was extracted from 103 patients undergoing warfarin therapy. Their mean daily warfarin dose, INR and demographics were recorded and genotyping of VKORC1 and CYP2C9 gene was performed by PCR-RFLP method.

RESULTS

Individuals with wild type genotypes required highest mean warfarin dosage of 4.72 mg/day while VKORC1 variants required 3.6 mg/day to maintain their therapeutic INR. CYP2C9*2 genotype was not found to affect the warfarin maintenance dosages. The odds ratio for developing supra therapeutic INR in patients carrying VKORC1 variant allele when compared to wild types was 13.96 (95% CI; 4.85 - 44.65. Other factors affecting warfarin dosages were age and weight.

CONCLUSION

Inclusion of pharmacogenetic data along with clinical parameters would help better predict warfarin doses in Indian patients.

Methodological issues in the development of a pharmacogenomic algorithm for warfarin dosing: comparison of two regression approaches

Aim: To ascertain whether multiple polynomial regression (MPR) has any advantage over multiple linear regression (MLR) in developing pharmacogenomic algorithms. Materials & methods: Two pharmacogenomic algorithms were developed based on MPR and MLR models from a warfarin pharmacogenomic data set (derivation cohort [n = 125] and validation cohort [n = 115]). Results: The MPR model showed better correlation with therapeutic dose (r = 0.62 vs 0.52); better diagnostic utility in distinguishing the warfarin-sensitive and warfarin-resistant patients (area under the receiver operating characteristic curves: 0.89 vs 0.81); and lower rate of underestimation (13.9 vs 20%) compared with the MLR model. Rate of overestimation was higher in the MPR than the MLR (10 vs 6.7%) model. Conclusion: The MPR approach has advantages over the MLR approach in predicting accurate and safe dose.

Original submitted 12 December 2013; Revision submitted 24 March 2014

The VKORC1 Asp36Tyr variant and VKORC1 haplotype diversity in Ashkenazi and Ethiopian populations

The vitamin K epoxide reductase (VKORC1) is a key enzyme in the vitamin K cycle impacting various biological processes. VKORC1 genetic variability has been extensively studied in the context of warfarin pharmacogenetics revealing different distributions of VKORC1 haplotypes in various populations. We previously identified the VKORC1 Asp36Tyr mutation that was associated with warfarin resistance and with distinctive ethnic distribution. In this study, we performed haplotype analysis using Asp36Tyr and seven other VKORC1 markers in Ashkenazi and Ethiopian-Jewish and non-Jewish individuals. The VKORC1 variability was represented by nine haplotypes (V1-V9) that could be grouped into two distinct clusters (V1-V3 and V4-V9) with intra-cluster difference limited to two nucleotide changes. Phylogeny analysis suggested that these haplotypes could have developed from an ancestral variant, the common V8 haplotype (40 % in all population samples), after ten single mutation events. Asp36Tyr was exclusive to the V5 haplotype of the second cluster. Two haplotypes V5 and V4, distinguished only by Asp36Tyr, were prevalent in both Ethiopian population samples. The V2 haplotype, belonging to the first cluster, was the second most prevalent haplotype in the Ashkenazi population sample (15.8 %) but relatively uncommon in the Ethiopian origin (4.5-4.7 %). We discuss the genetic diversity among studied populations and its potential impact on warfarin-dose management in certain populations of African and European origin.

Inter and intra ethnic variation of vitamin K epoxide reductase complex and cytochrome P450 4F2 genetic polymorphisms and their prevalence in South Indian population

BACKGROUND:

Genetic variation in the vitamin K epoxide reductase complex (VKORC1) and cytochrome P450 4F2 (CYP4F2) genes were found to be strongly associated with the oral anticoagulant (OA) dose requirement. The distribution of genetic variation in these two genes was found to show large inter- and intra-ethnic difference.

MATERIALS AND METHODS:

A total of 470 unrelated, healthy volunteers of South Indians of either sex (age: 18-60 years) were enrolled for the study. A 5 ml of venous blood was collected and the genomic deoxyribonucleic acid (DNA) was extracted by using phenol-chloroform extraction method. Real-time quantitative polymerase chain reaction (RT-PCR) method was used for genotyping.

RESULTS:

The variant allele frequencies of VKORC1 rs2359612 (T), rs8050894 (C), rs9934438 (T) and rs9923231 (A) were found to be 11.0%, 11.8%, 11.7% and 12.0%, respectively. The variant allele VKORC1 rs7294 was (80.1%) more frequent and the variant allele CYP4F2 * 3 was found to be 41.8% in South Indians. The allele, genotype and haplotype frequencies of VKORC1 and CYP4F2 gene were distinct from other compared HapMap populations (P < 0.0001).

CONCLUSION:

The findings of our study provide the basic genetic information for further pharmacogenetic based investigation of OA therapy in the population.

Warfarin anticoagulant therapy: a Southern Italy pharmacogenetics-based dosing model

Background and Aim

Warfarin is the most frequently prescribed anticoagulant worldwide. However, warfarin therapy is associated with a high risk of bleeding and thromboembolic events because of a large interindividual dose-response variability. We investigated the effect of genetic and non genetic factors on warfarin dosage in a South Italian population in the attempt to setup an algorithm easily applicable in the clinical practice.

Materials and Methods

A total of 266 patients from Southern Italy affected by cardiovascular diseases were enrolled and their clinical and anamnestic data recorded. All patients were genotyped for CYP2C9*2,*3, CYP4F2*3, VKORC1 -1639 G>A by the TaqMan assay and for variants VKORC1 1173 C>T and VKORC1 3730 G>A by denaturing high performance liquid chromatography and direct sequencing. The effect of genetic and not genetic factors on warfarin dose variability was tested by multiple linear regression analysis, and an algorithm based on our data was established and then validated by the Jackknife procedure.

Results

Warfarin dose variability was influenced, in decreasing order, by VKORC1-1639 G>A (29.7%), CYP2C9*3 (11.8%), age (8.5%), CYP2C9*2 (3.5%), gender (2.0%) and lastly CYP4F2*3 (1.7%); VKORC1 1173 C>T and VKORC1 3730 G>A exerted a slight effect (<1% each). Taken together, these factors accounted for 58.4% of the warfarin dose variability in our population. Data obtained with our algorithm significantly correlated with those predicted by the two online algorithms: Warfarin dosing and Pharmgkb (p<0.001; R² = 0.805 and p<0.001; R² = 0.773, respectively).

Conclusions

Our algorithm, which is based on six polymorphisms, age and gender, is user-friendly and its application in clinical practice could improve the personalized management of patients undergoing warfarin therapy.

Drug-nutrient interactions

Drug-nutrient interactions are defined as physical, chemical, physiologic, or pathophysiologic relationships between a drug and a nutrient. The causes of most clinically significant drug-nutrient interactions are usually multifactorial. Failure to identify and properly manage drug-nutrient interactions can lead to very serious consequences and have a negative impact on patient outcomes. Nevertheless, with thorough review and assessment of the patient's history and treatment regimens and a carefully executed management strategy, adverse events associated with drug-nutrient interactions can be prevented. Based on the physiologic sequence of events after a drug or a nutrient has entered the body and the mechanism of interactions, drug-nutrient interactions can be categorized into 4 main types. Each type of interaction can be managed using similar strategies. The existing data that guide the clinical management of most drug-nutrient interactions are mostly anecdotal experience, uncontrolled observations, and opinions, whereas the science in understanding the mechanism of drug-nutrient interactions remains limited. The challenge for researchers and clinicians is to increase both basic and higher level clinical research in this field to bridge the gap between the science and practice. The research should aim to establish a better understanding of the function, regulation, and substrate specificity of the nutrient-related enzymes and transport proteins present in the gastrointestinal tract, as well as assess how the incidence and management of drug-nutrient interactions can be affected by sex, ethnicity, environmental factors, and genetic polymorphisms. This knowledge can help us develop a true personalized medicine approach in the prevention and management of drug-nutrient interactions.

Genetic variation and haplotype structure of the gene Vitamin K epoxide reductase complex, subunit 1 in the Tamilian population

OBJECTIVE

To study the genetic variation and haplotype structure of Vitamin K epoxide reductase complex, subunit 1 (VKORC1) gene in the Tamilian population.

MATERIALS AND METHODS

The study was performed on 210 unrelated, healthy volunteers of the Tamilian population, of either sex between the age group of 18-60 years. Five ml of venous blood sample was collected using sodium ethylene diamine tetra acetic acid (EDTA) as anticoagulant. DNA was extracted using phenol-chloroform extraction method. Eight single nucleotide polymorphisms (SNPs) VKORC1 rs9923231 (G), rs7196161 (T), rs2884737 (T), rs17708472 (C), rs9934438 (C), rs8050894 (G), rs23596121 (C), and rs7294 (A) were studied using real-time quantitative Polymerase Chain Reaction (qPCR) method and they were included for constructing five-major haplotype blocks of VKORC1 gene.

RESULTS

The major alleles of VKORC1 rs9923231 (G), rs7196161 (T), rs2884737 (T), rs17708472 (C), rs9934438 (C), rs8050894 (G), and rs23596121 (C), were found to be at frequencies of 90.0%, 89.2%, 90.9%, 94.1%, 90.7%, 89.5% and 91.2%, respectively. The variant allele of VKORC1 rs7294 (A) was more frequent (83.6%) in the Tamilian population. The frequencies of haplotypes HAP1 (GTTCCGCA), HAP2 (ACGCTCTG), HAP3 (GTTTCGCG), HAP4 (GTTCCGCG) and HAP5 (GCTCCCCG) were found to be 80.0%, 7.4%, 4.7%, 1.5% and 1.1%, respectively.

CONCLUSION

In the present study the allele- frequency distributions, genotype and haplotype frequencies of the VKORC1 gene was considered. The findings of this study provide the genetic information required for learning the association of VKORC1 genetic variation and oral anticoagulant dose variability among patients receiving oral anticoagulants in the Tamilian population.

Allele frequency distribution of CYP2C9 2 and CYP2C9 3 polymorphisms in six Mexican populations

Allele frequency differences of functional CYP2C9 polymorphisms are responsible for some of the variation in drug response observed in human populations. The most relevant CYP2C9 functional variants are CYP2C9*2 (rs1799853) and CYP2C9 3 (rs1057910). These polymorphisms show variation in allele frequencies among different population groups. The present study aimed to analyze these polymorphisms in 947 Mexican-Mestizo from Mexico City and 483 individuals from five indigenous Mexican populations: Nahua, Teenek, Tarahumara, Purepecha and Huichol. The CYP2C9*2 allele frequencies in the Mestizo, Nahua and Teenek populations were 0.051, 0.007 and 0.005, respectively. As for CYP2C9 3, the allelic frequencies in the Mestizo, Nahua and Teenek populations were 0.04, 0.005 and 0.005, respectively. The CYP2C9 2 and CYP2C9 3 alleles were not observed in the Tarahumara, Purepecha and Huichol populations. These findings are in agreement with previous studies reporting very low allele frequencies for these polymorphisms in American Indigenous populations.

VKORC1 Asp36Tyr geographic distribution and its impact on warfarin dose requirements in Egyptians

The VKORC1 Asp36Tyr single nucleotide polymorphism (SNP) is one of the most promising predictors of high warfarin dose, but data on its population prevalence is incomplete. We determined the frequency of this SNP in participants from seven countries on four continents and investigated its effect on warfarin dose requirement. One thousand samples were analysed to define the population prevalence of this SNP. Those samples included individuals from Egypt, Ghana, Sudan, Kenya, Saudi Arabia, Peru and African Americans from the United States. A total of 206 Egyptian samples were then used to investigate the effect of this SNP on warfarin dose requirements. This SNP was most frequent among Kenyans and Sudanese, with a minor allele frequency (MAF) of 6% followed by Saudi Arabians and Egyptians with a MAF of 3% and 2.5%, respectively. It was not detected in West Africans, based on our data from Ghana, and a large cohort of African Americans. Egyptian carriers of the VKORC1 Tyr36 showed higher warfarin dose requirement (57.1 ± 29.4 mg/week) than those with the Asp36Asp genotype (35.8 ± 16.6 mg/week; p=0.03). In linear regression analysis, this SNP had the greatest effect size among the genetic factors (16.6 mg/week increase in dose per allele), and improved the warfarin dose variability explained in Egyptians (model R2 from 31% to 36.5%). The warfarin resistant VKORC1 Asp36Tyr appears to be confined to north-eastern Africa and nearby Middle-Eastern populations, but in those populations where it is present, it has a significant influence on warfarin dose requirement and the percent of warfarin dose variability that can be explained.

Eicosanoids in metabolic syndrome

Chronic persistent inflammation plays a significant role in disease pathology of cancer, cardiovascular disease, and metabolic syndrome (MetS). MetS is a constellation of diseases that include obesity, diabetes, hypertension, dyslipidemia, hypertriglyceridemia, and hypercholesterolemia. Nonalcoholic fatty liver disease (NAFLD) is associated with many of the MetS diseases. These metabolic derangements trigger a persistent inflammatory cascade, which includes production of lipid autacoids (eicosanoids) that recruit immune cells to the site of injury and subsequent expression of cytokines and chemokines that amplify the inflammatory response. In acute inflammation, the transcellular synthesis of antiinflammatory eicosanoids resolve inflammation, while persistent activation of the autacoid-cytokine-chemokine cascade in metabolic disease leads to chronic inflammation and accompanying tissue pathology. Many drugs targeting the eicosanoid pathways have been shown to be effective in the treatment of MetS, suggesting a common linkage between inflammation, MetS and drug metabolism. The cross-talk between inflammation and MetS seems apparent because of the growing evidence linking immune cell activation and metabolic disorders such as insulin resistance, dyslipidemia, and hypertriglyceridemia. Thus modulation of lipid metabolism through either dietary adjustment or selective drugs may become a new paradigm in the treatment of metabolic disorders. This review focuses on the mechanisms linking eicosanoid metabolism to persistent inflammation and altered lipid and carbohydrate metabolism in MetS.

Effect of genetic variants, especially CYP2C9 and VKORC1, on the pharmacology of warfarin

The genes encoding the cytochrome P450 2C9 enzyme (CYP2C9) and vitamin K-epoxide reductase complex unit 1 (VKORC1) are major determinants of anticoagulant response to warfarin. Together with patient demographics and clinical information, they account for approximately one-half of the warfarin dose variance in individuals of European descent. Recent prospective and randomized controlled trial data support pharmacogenetic guidance with their use in warfarin dose initiation and titration. Benefits from pharmacogenetics-guided warfarin dosing have been reported to extend beyond the period of initial dosing, with supportive data indicating benefits to at least 3 months. The genetic effects of VKORC1 and CYP2C9 in African and Asian populations are concordant with those in individuals of European ancestry; however, frequency distribution of allelic variants can vary considerably between major populations. Future randomized controlled trials in multiethnic settings using population-specific dosing algorithms will allow us to further ascertain the generalizability and cost-effectiveness of pharmacogenetics-guided warfarin therapy. Additional genome-wide association studies may help us to improve and refine dosing algorithms and potentially identify novel biological pathways.

CYP2C9 and VKORC1 polymorphisms influence warfarin dose variability in patients on long-term anticoagulation

OBJECTIVES

The main aim of this study was to determine whether CYP2C9 and VKORC1 polymorphisms influence warfarin dose variability during initial dose-finding phase and during maintenance treatment after 360 days.

METHODS

Two hundred and six consecutive patients who were beginning warfarin therapy were selected. They were assessed for general and clinical characteristics; prescribed warfarin dose; response to therapy on days 7-10, 30, 60, 180, and 360; adverse events; and CYP2C9 2, 3, 5, 6, 8, 11, and VKORC1 1639G >A assays.

RESULTS

During the first 30 days of anticoagulation, the relative variability of warfarin dose was significantly associated with CYP2C9*2 and CYP2C9*3 polymorphisms (p = 0.02) and with VKORC1 1639G >A genotypes (p = 0.04). Warfarin variability was also statistically different according to predicted metabolic phenotype and to VKORC1 genotypes after 360 days of treatment, and in the phase between 180 and 360 days (long-term dose variability). Both CYP2C9 and VKORC1 polymorphisms were associated with the international normalized ratio (INR) made between 7 and 10 days/initial dose ratio, adjusted for covariates (p < 0.01 and p = 0.02, respectively). Patients carrying VKORC1 and CYP2C9 variants presented lower required dose (at the end of follow-up of 360 days) compared to patients carrying wild-type genotypes (p = 0.04 and p = 0.03, respectively).

CONCLUSIONS

Genetic information on CYP2C9 and VKORC1 is important both for the initial dose-finding phase and during maintenance treatment with warfarin.

Effect of the VKORC1 D36Y variant on warfarin dose requirement and pharmacogenetic dose prediction

Pharmacogenetic dosing algorithms help predict warfarin maintenance doses, but their predictive performance differs in different populations, possibly due to unsuspected population-specific genetic variants. The objectives of this study were to quantify the effect of the VKORC1 D36Y variant (a marker of warfarin resistance previously described in 4% of Ashkenazi Jews) on warfarin maintenance doses and to examine how this variant affects the performance of the International Warfarin Pharmacogenetic Consortium (IWPC) dose prediction model. In 210 Israeli patients on chronic warfarin therapy recruited at a tertiary care centre, we applied the IWPC model and then added D36Y genotype as covariate to the model (IWPC+D36Y) and compared predicted with actual doses. Median weekly warfarin dose was 35 mg (interquartile range [IQR], 24.5 to 52.5 mg). Among 16 heterozygous D36Y carriers (minor allele frequency = 3.8%), warfarin weekly dose was increased by a median of 43.7 mg (IQR, 40.5 to 47.2 mg) compared to non-carriers after adjustment for all IWPC parameters, a greater than two-fold dose increase. The IWPC model performed suboptimally (coefficient of determination R²=27.0%; mean absolute error (MAE), 14.4 ± 16.2 mg/week). Accounting for D36Y genotype using the IWPC+D36Y model resulted in a significantly better model performance (R²=47.2%, MAE=12.6 ± 12.4 mg/week). In conclusion, even at low frequencies, variants with a strong impact on warfarin dose may greatly decrease the performance of a commonly used dose prediction model. Unexpected discrepancies of the performance of universal prediction models in subpopulations should prompt searching for unsuspected confounders, including rare genetic variants.

CYP2C9 and VKORC1 polymorphisms are differently distributed in the Brazilian population according to self-declared ethnicity or genetic ancestry

BACKGROUND

Warfarin-dosing pharmacogenetic algorithms have presented different performances across ethnicities, and the impact in admixed populations is not fully known.

AIMS

To evaluate the CYP2C9 and VKORC1 polymorphisms and warfarin-predicted metabolic phenotypes according to both self-declared ethnicity and genetic ancestry in a Brazilian general population plus Amerindian groups.

METHODS

Two hundred twenty-two Amerindians (Tupinikin and Guarani) were enrolled and 1038 individuals from the Brazilian general population who were self-declared as White, Intermediate (Brown, Pardo in Portuguese), or Black. Samples of 274 Brazilian subjects from Sao Paulo were analyzed for genetic ancestry using an Affymetrix 6.0(®) genotyping platform. The CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), and VKORC1 g.-1639G>A (rs9923231) polymorphisms were genotyped in all studied individuals.

RESULTS

The allelic frequency for the VKORC1 polymorphism was differently distributed according to self-declared ethnicity: White (50.5%), Intermediate (46.0%), Black (39.3%), Tupinikin (40.1%), and Guarani (37.3%) (p<0.001), respectively. The frequency of intermediate plus poor metabolizers (IM+PM) was higher in White (28.3%) than in Intermediate (22.7%), Black (20.5%), Tupinikin (12.9%), and Guarani (5.3%), (p<0.001). For the samples with determined ancestry, subjects carrying the GG genotype for the VKORC1 had higher African ancestry and lower European ancestry (0.14±0.02 and 0.62±0.02) than in subjects carrying AA (0.05±0.01 and 0.73±0.03) (p=0.009 and 0.03, respectively). Subjects classified as IM+PM had lower African ancestry (0.08±0.01) than extensive metabolizers (0.12±0.01) (p=0.02).

CONCLUSIONS

The CYP2C9 and VKORC1 polymorphisms are differently distributed according to self-declared ethnicity or genetic ancestry in the Brazilian general population plus Amerindians. This information is an initial step toward clinical pharmacogenetic implementation, and it could be very useful in strategic planning aiming at an individual therapeutic approach and an adverse drug effect profile prediction in an admixed population.

Pharmacogenetic aspects of coumarinic oral anticoagulant therapies

Coumarinic oral-anticoagulants (COAs) are commonly used for treatment of thromboembolic events. However, these medications have a narrow therapeutic range and there are large inter-individual variations in drug response. This is especially important in the initial phases of oral-anticoagulant therapy. Recent advancements in pharmacogenetics have established that clinical outcomes in oral-anticoagulant therapy are affected by genetic factors. The allelic variants of genes like cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) are closely associated with maintenance dose of oral anti-coagulants. In addition, GGCX (Gamma-glutamyl carboxylase) polymorphism at position 12970 (rs11676382), CYP4F2 (rs2108622; V433M; 1347 C > T) and Apolipoprotein E (APOE) variants have been shown to explain a small but significant influence on dose requirements. There are large differences in the frequencies of these polymorphisms between different world populations which are also related to the requirements of oral anticoagulants. However, the final drug dosage in an individual is determined by complex sets of genetic and environmental factors and several dosing algorithms which combine clinical and genetic parameters to predict therapeutic COA doses have also been developed. The algorithm based dose prediction shows the importance of pharmacogenetic testing in patients undergoing oral anticoagulant therapies.

Therapeutic dosing of acenocoumarol: proposal of a population specific pharmacogenetic dosing algorithm and its validation in north Indians

Objectives

To develop a population specific pharmacogenetic acenocoumarol dosing algorithm for north Indian patients and show its efficiency in dosage prediction.

Methods

Multiple and linear stepwise regression analyses were used to include age, sex, height, weight, body surface area, smoking status, VKORC1 -1639 G>A, CYP4F2 1347 G>A, CYP2C9*2,*3 and GGCX 12970 C>G polymorphisms as variables to generate dosing algorithms. The new dosing models were compared with already reported algorithms and also with the clinical data for various performance measures. Odds ratios for association of genotypes with drug sensitive and resistant groups were calculated.

Results

The pharmacogenetic dosing algorithm generated by multiple regression analysis explains 41.4% (p-value <0.001) of dosage variation. Validation of the new algorithm showed its predictive ability to be better than the already established algorithms based on similar variables. Its validity in our population is reflected by increased sensitivity, specificity, accuracy and decreased rates of over- and under- estimation in comparison to clinical data. The VKORC1-1639 G>A polymorphism was found to be strongly associated with acenocoumarol sensitivity according to recessive model.

Conclusions

We have proposed an efficient north India specific pharmacogenetic acenocoumarol dosing algorithm which might become a baseline for personalised medicine approach for treatment of patients in future.

Bioinformatics and variability in drug response: a protein structural perspective

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk-benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein-drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein-drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants.