Pharmacogenetic Algorithms Research Articles

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.

Optimisation of warfarin-dosing algorithms for Han Chinese patients with CYP2C9*13 variants.

Existing pharmacogenetic algorithms cannot fully explain warfarin dose variability in allpatients. CYP2C9*13 is an important allelic variant in the Han Chinese population. However, adjustment of warfarin dosing in CYP2C9*13 variant carriers remains unclear. To the best of our knowledge, this study is the first to assess the effects of adjusting warfarin dosages in Han Chinese patients harbouring CYP2C9*13 variants. In total, 971 warfarin-treated Han Chinese patients with atrial fibrillation were enrolled in this study. Clinical data were collected, and CYP2C9*2, *3, *13 and VKORC1-1639 G > A variants were genotyped. We quantitatively analysed the effect of CYP2C9*13 on warfarin maintenance dose and provided multiplicative adjustments for CYP2C9*13 using validated pharmacogenetic algorithms. Approximately 0.6% of the Han Chinese population carried CYP2C9*13 variant, and the genotype frequency was between those of CYP2C9*2 and CYP2C9*3. The warfarin maintenance doses were significantly reduced in CYP2C9*13 carriers. When CYP2C9*13 variants were not considered, the pharmacogenetic algorithms overestimated warfarin maintenance doses by 1.03-1.16mg/d on average. The actual warfarin dose in CYP2C9*13 variant carriers was approximately 40% lower than the algorithm-predicted dose. Adjusting the warfarin-dosing algorithm according to the CYP2C9*13 allele could reduce the dose prediction error. Our study showed that the algorithm-predicted doses should be lowered for CYP2C9*13 carriers. Inclusion of the CYP2C9*13 variant in the warfarin-dosing algorithm tends to predict the warfarin maintenance dose more accurately and improves the efficacy and safety of warfarin administration in Han Chinese patients.

Warfarin Dosing in Patients With CYP2C9*5 Variant Alleles.

Pharmacogenetic dosing improves the accuracy of warfarin dosing, but current pharmacogenetic dosing algorithms are less accurate in populations of African ancestry. The cytochrome P450 2C9*5 (CYP2C9*5) allele is found almost exclusively in populations of African ancestry, and in vitro studies suggest CYP2C9*5 is associated with reduced clearance of warfarin. The clinical relevance of this single-nucleotide variation (SNV) (formerly SNP) is uncertain. In this multicentered study of 2,298 patients (49% female, 35% Black) taking warfarin, we quantified the association between the CYP2C9*5 allele and warfarin requirements. The CYP2C9*5 SNV was present in 2.3% of Black and 0.07% of White patients. Without taking CYP2C9*5 into account, pharmacogenetic algorithms that include other SNVs overestimated the warfarin dose by 30% (95% confidence interval (19-40%), P<0.001), an average of 1.87mg/day (SD 1.64) in heterozygotes (P<0.001). Noncarriers required a slightly (0.23mg/day, SD 2.09) higher than predicted dose. Genotyping for CYP2C9*5 corrected the potential overdose and halved overall dosing error in heterozygotes. Patients carrying CYP2C9*5 require a clinically relevant reduction in warfarin dose. Given the potential to improve the accuracy and safety of warfarin dosing in populations of African ancestry, we have incorporated this SNV into a nonprofit website to assist warfarin initiation (www.WarfarinDosing.org).

Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management

Warfarin is commonly used in thromboembolic conditions. Warfarin interruption represents a significant challenge in pre-operative warfarin management as it is associated with major consequences. Genetics polymorphism demonstrated to be a significant predictor of the required days of warfarin interruption. This study sought to assess the economic benefit of implementing a pharmacogenetic-guided approach in the preprocedural warfarin management. From the hospital's perspective, a cost-benefit analysis was conducted based on a 1-year decision-analytic follow-up model of the economic implications of using a pharmacogenetic algorithm vs standard of care in pre-operative warfarin management in the Hamad Medical Corporation, Qatar. The benefit of the interventional algorithm was based on estimated reduction in the probabilities of clinical events and their cost, added to the avoided cost because of canceled procedures. The cost of the algorithm was the cost of the genotyping assay. The model event probability inputs were extracted from major literature clinical trials, and the setting-specifc and cost inputs were locally obtained. The model was based on a multivariate analysis at its base case. As per 10.3% prevalence of genetic variants, 82% bridging, and a calculated 20% optimization in the preparative period of warfarin management, the benefit to cost ratio was 4.0 in favor genotype-guided approach. This positive benefit to cost ratio was maintained in 100% of the simulated study cases. Sensitivity analyses confirmed the robustness and generalizability of the study conclusion. A pharmacogenetic- guided pre-operative warfarin interruption management is a cost-beneficial approach in the Qatari practice.

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.

Acenocoumarol Pharmacogenetic Dosing Algorithm versus Usual Care in Patients with Venous Thromboembolism: A Randomised Clinical Trial.

Patients with venous thromboembolism (VTE) require immediate treatment with anticoagulants such as acenocoumarol. This multicentre randomised clinical trial evaluated the effectiveness of a dosing pharmacogenetic algorithm versus a standard-of-care dose adjustment at the beginning of acenocoumarol treatment. We included 144 patients with VTE. On the day of recruitment, a blood sample was obtained for genotyping (CYP2C9*2, CYP2C9*3, VKORC1, CYP4F2, APOE). Dose adjustment was performed on day 3 or 4 after the start of treatment according to the assigned group and the follow-up was at 12 weeks. The principal variable was the percentage of patients with an international normalised ratio (INR) within the therapeutic range on day 7. Thirty-four (47.2%) patients had an INR within the therapeutic range at day 7 after the start of treatment in the genotype-guided group compared with 14 (21.9%) in the control group (p = 0.0023). There were no significant differences in the time to achieve a stable INR, the number of INRs within the range in the first 6 weeks and at the end of study. Our results suggest the use of a pharmacogenetic algorithm for patients with VTE could be useful in achieving target INR control in the first days of treatment.

Combining Clinical and Genetic Factors to Predict Tacrolimus Levels in Pediatric Solid Organ Transplants: Problem Solved?

Combining Clinical and Genetic Factors to Predict Tacrolimus Levels in Pediatric Solid Organ Transplants: Problem Solved?

Pharmacogenetic algorithm for predicting daily dose of warfarin in Caucasian patients of Czech origin

Abstract Objectives Warfarin use is limited by a low therapeutic index and significant interindividual variability of the daily dose. The most important factor predicting daily warfarin dose is individual genotype, polymorphisms of genes CYP2C9 (warfarin metabolism) and VKORC1 (sensitivity for warfarin). Algorithms using clinical and genetic variables could predict the daily dose before the initiation of therapy. The aim of this study was to develop and validate an algorithm for the prediction of warfarin daily dose in Czech patients. Methods Detailed clinical data of patients with known and stable warfarin daily dose were collected. All patients were genotyped for polymorphisms in genes CYP2C9 and VKORC1. Results Included patients were divided into derivation (n=175) and validation (n=223) cohorts. The final algorithm includes the following variables: Age, height, weight, treatment with amiodarone and presence of variant alleles of genes CYP2C9 and VKORC1. The adjusted coefficient of determination is 72.4% in the derivation and 62.3% in the validation cohort (p&lt;0.001). Conclusions Our validated algorithm for warfarin daily dose prediction in our Czech cohort had higher precision than other currently published algorithms. Pharmacogenetics of warfarin has the potential in the clinical practice in specialized centers.

Pharmacogenetic algorithm for predicting daily dose of warfarin in Caucasian patients of Czech origin.

Warfarin use is limited by a low therapeutic index and significant interindividual variability of the daily dose. The most important factor predicting daily warfarin dose is individual genotype, polymorphisms of genes CYP2C9 (warfarin metabolism) and VKORC1 (sensitivity for warfarin). Algorithms using clinical and genetic variables could predict the daily dose before the initiation of therapy. The aim of this study was to develop and validate an algorithm for the prediction of warfarin daily dose in Czech patients. Detailed clinical data of patients with known and stable warfarin daily dose were collected. All patients were genotyped for polymorphisms in genes CYP2C9 and VKORC1. Included patients were divided into derivation (n=175) and validation (n=223) cohorts. The final algorithm includes the following variables: Age, height, weight, treatment with amiodarone and presence of variant alleles of genes CYP2C9 and VKORC1. The adjusted coefficient of determination is 72.4% in the derivation and 62.3% in the validation cohort (p<0.001). Our validated algorithm for warfarin daily dose prediction in our Czech cohort had higher precision than other currently published algorithms. Pharmacogenetics of warfarin has the potential in the clinical practice in specialized centers.

Randomised multicentre clinical trial to evaluate voriconazole pre-emptive genotyping strategy in patients with risk of aspergillosis: vorigenipharm study protocol

IntroductionInvasive aspergillosis is the most important cause of morbidity and mortality in patients with haematological diseases. At present, voriconazole is the first-line treatment for invasive fungal disease. The pharmacokinetic interindividual...

Имплементация системы поддержки принятия решений персонализации режима дозирования бромдигидрохлорфенилбензодиазепина у пациентов с синдромом отмены алкоголя, основанной на фармакогенетических биомаркерах

Введение: Имплементация систем поддержки принятия решений, способных формировать рекомендации по выбору лекарствен- ного средства и его дозы в соответствии с результатами фармакогенетического тестирования, является актуальной задачей, так как решение ее позволит повысить эффективность терапии и снизить риск развития нежелательных лекарственных реакций.Материалы и методы: В исследовании принимал участие 51 пациент (21 - основная группа, получавшая назначения в соответ- ствии с рекомендациями, основанными на результатах фармакогенетического тестирования, а 30 - группа сравнения, получавшая назначения без них) мужского пола с синдромом отмены алкоголя. Для оценки эффективности и безопасности терапии синдрома отмены алкоголя, которую осуществляли с использованием бензодиазепинового транквилизатора феназепама (бромдигидрохлор- фенилбензодиазепина), а также стандартной дезинтоксикационной и витаминотерапии, применялись международные психоме- трические шкалы и шкалы оценки выраженности нежелательных реакций. Определение полиморфизмов генов CYP2D6*4 (1846G&gt;A, rs3892097), CYP2C19*2 (681G&gt;A, rs4244285), CYP2C19*3 (636G&gt;A, rs4986893), CYP2C19*17 (-806C&gt;T, rs12248560), CYP3A5*3 (6986A&gt;G, rs776746) и ABCB1*6 (3435C&gt;T, rs1045642) осуществлялось методом полимеразной цепной реакции в реальном времени с аллель-специфиче- ской гибридизацией. Интерпретацию результатов фармакогенетического тестирования осуществляли с использованием свободно распространяемого программного обеспечения PharmacoGenomeX2 (www.pgx2.com).Результаты: Получены статистически значимые различия в количестве баллов по всем психометрическим шкалам у пациентов основной группы и группы сравнения. Например, по шкале оценки тяжести синдрома отмены алкоголя к 3-му дню исследования количество баллов в основной группе составляло 13,5 [11,2; 16,0], а в группе контроля - 18,0 [17,0; 22,0] (p &lt; 0,001); к 5-му в основ- ной группе - 6,5 [4,2; 8,0], в группе контроля - 15,0 [14,0; 16,0] (p &lt; 0,001). По шкале безопасности UKU также была получена стати- стически значимая разница. К 3-му дню исследования количество баллов по шкале UKU в основной группе составило 6,0 [5,0; 7,0], а в группе контроля - 7,0 [6,0; 8,0] (p = 0,030); к 5-му дню разница возрастала. В основной группе - 5,5 [3,0; 9,0], в группе контроля - 14,0 [12,0; 19,0] (p &lt; 0,001). Группы были репрезентативны (при включении в исследование разница в количестве баллов отсутствовала). Выводы: Персонализация дозы лекарств в соответствии с фармакогенетическими алгоритмами у пациентов с синдромом отмены алкоголя, способна снизить риск развития нежелательных реакций и фармакорезистентности, что позволяет рекомендовать исполь- зование фармакогенетических систем поддержки принятия решений для подбора дозы лекарств. Introduction: Implementation of the clinical decision support systems capable of forming the recommendations on drug and dose selec- tion according to the results of pharmacogenetic testing is an urgent task. Fulfillment of this task will allow increasing the efficacy of ther- apy and decreasing the risk of undesirable side effects.Materials and methods: The study involved 51 patients (21 - the main group receiving appointments in accordance with the recommenda- tions based on the results of pharamogenetic testing, and 30 - the comparison control group receiving appointments without them) male with alcohol withdrawal syndrome. In order to assess the effectiveness and safety of alcohol withdrawal syndrome, which was performed with the benzodiazepine tranquilizer of phenazepam (bromodihydrochlorophenylbenzodiazepine), as well as standard detoxification and vitamin therapy, international psychometric scales and scales of assessment in expressions of adverse reactions. Genotyping Determination of genetic polymorphisms CYP2D6*4 (1846G&gt;A, rs3892097), CYP2C19*2 (681G&gt;A, rs4244285), CYP2C19*3 (636G&gt;A, rs4986893), CYP2C19*17 (-806C&gt;T, rs12248560), CYP3A5*3 (6986A&gt;G, rs776746) and ABCB1*6 (3435C&gt;T, rs1045642) were realized using real-time polymerase chain reaction with allele specific hybridization. Interpretation of the results of pharmacogenetic testing was carried out with the help of free soft- ware PharmacoGenomeX2 (www.pgx2.com)Results: Statistically significant differences in the number of scores for all psychometric scales in the patients of the main group and the comparison group were obtained. For example, on the scale of assessing the severity of alcohol withdrawal syndrome by the 3rd day of the study, the score in the main group was 13.5 [11.2; 16,0], and in the control group - 18,0 [17,0; 22.0] (p &lt;0.001); to the 5th in the main group - 6.5 [4.2; 8.0], in the control group - 15.0 [14.0; 16.0] (p &lt;0.001). On the UKU security scale, a statistically significant difference was also obtained. By the 3rd day of the study, the UKU score in the main group was 6.0 [5.0; 7,0], and in the control group - 7,0 [6,0; 8.0] (p = 0.030); by the 5th day the difference increased. In the main group, 5.5 [3.0; 9.0], in the control group - 14.0 [12.0; 19.0] (p &lt;0.001). The groups were representative (when included in the study, the difference in the number of points was absent).Conclusion: Personalization of the dose of drugs in accordance with pharmacogenetic algorithms in patients with alcohol withdrawal syn- drome, can reduce the risk of unwanted reactions and pharmacoresistance, which allows to recommend the use of pharmacogenetic deci- sion support systems for drug dosage selection.

Pharmacogenetic Warfarin Dosing Algorithm in the Russian Population

Background. To date, there are many pharmacogenetic algorithms for selecting the dose of warfarin. However, there is very little information about the predictive accuracy of the algorithms. We decided to evaluate the predictive accuracy of the Gage algorithm, using a calculator, located on the web site (http://www.warfarindosing.org) in two ethnic groups (Caucasians and Asians), living in Russia.Aim. To compare the actual warfarin dose (AWD) to the calculated warfarin dose (CWD), using the algorithm in two ethnic groups taking warfarin.Materials and methods. We included 114 patients (66 Caucasians and 48 Asians): the mean age was60.91 ± 12.34 years; 61 (53.51 %) men, and 53 (46.49 %) women. The comparative characteristics of the algorithm were tested using the mean absolute error (MAE) between AWD and CWD, and percentage of patients, whose CWD fell within 20 % of AWD (percentage within 20 %). Genotyping for CYP2C9*2, CYP2C9*3, CYP4F*2 and VKORC1 was performed by real-time polymerase chain reaction (RT-PCR) method using Pharmacogenetics Warfarin reagent kits (DNA technology, Russia).Results. The Gage algorithm produced the predictive accuracy with MAE = 1.02 ± 0.16 mg/day and percentage within 20 % for Asian patients was 39.6 %. We obtained MAE = 1.33 ± 0.16 mg/day and percentage within 20 % for Caucasian patients was 40.9 %. In two ethnic groups (Caucasians and Asians) of the Russian population, overall performance of warfarin pharmacogenetic dosing by the Gage algorithm was similar.Conclusions. Despite the performance limitation of the current warfarin pharmacogenetic dosing Gage algorithm, constant international normalized ratio monitoring is important.

Pharmacogenetics of alcohol addiction: current perspectives.

Genetics of alcohol addiction is currently a contradictive and complex field, where data in the most studies reflect methods’ limitations rather than meaningful and complementary results. In our review, we focus on the genetics of alcohol addiction, leaving genetics of acute alcohol intoxication out of the scope. A review of the literature on pharmacogenetic biomarkers development for the pharmacotherapy personalization reveals that today the evidence base concerning these biomarkers is still insufficient. In particular, now the researches with the design of randomized controlled trials and meta-analysis investigating the effect of the SNPs as biomarkers on the therapy efficacy are available for naltrexone only. For other medications, there are only a few studies in small samples. It decreases the possibilities to implement the pharmacogenetic algorithms for the pharmacotherapy personalization in patients with alcohol use disorders (AUD). In view of the importance of the precision approaches development not in addiction medicine only, but in other fields of medicine also to increase the efficacy and safety of the therapy, studies on pharmacogenetic biomarkers development for the medications used in patients with AUD (eg, naltrexone, disulfiram, nalmefene, acamprosate, etc.) remain relevant to this day.

Warfarin loading dose guided by pharmacogenetics is effective and safe in cardioembolic stroke patients - a randomized, prospective study.

Warfarin treatment is commonly started with a fixed loading dose that might be associated with an increased risk of bleeding. An individual maintenance dose can then be estimated based on a pharmacogenetic algorithm. Starting treatment with the estimated dose implies a longer time to reach the therapeutic range. Our goal was to compare the safety and efficacy of initiating warfarin treatment with a loading dose guided by pharmacogenetics versus a maintenance dose. The primary endpoint was time in the therapeutic range (TTR) in the first 10 days of treatment. Secondary endpoints were time to the first international normalized ratio (INR) in therapeutic range (2.0-3.0) and occurrence of serious adverse events. Consenting cardioembolic stroke patients were genotyped for CYP2C9 (cytochrome P450 2C9 gene) and VKORC1 (vitamin K epoxide reductase complex, subunit 1 gene) polymorphisms and a maintenance warfarin dose was estimated. Patients were randomized into two groups. The loading dose group (LDG) patients received twice the estimated dose in the first 2 days of treatment. The maintenance dose group (MDG) patients received the estimated dose directly from day one. The TTR in the first 10 days was significantly higher in the LDG than in the MDG (50.5% vs. 38.3%, p = 0.003). The time to the first INR in this range was significantly shorter in the LDG (5.24 vs. 7.3 days). There were no significant differences in the INR above this range or serious adverse events. Warfarin loading dose guided by pharmacogenetics after recent cardioembolic stroke improved the efficacy of warfarin initiation without increasing the risk of adverse events.

Comparison of Two Different Techniques Of Warfarin Dosing Determination - A Chemometrics Study.

A high prevalence of genetic polymorphisms increases sensitivity to warfarin therapy. In this study, we investigated 47 patients with effective long-term therapy by warfarin well-controlled by monitoring of International Normalised Ratio (INR). All patients were tested for gene polymorphisms VKORC1, CYP2C9*C2, and CYP2C9*C3, which were used for a dose calculation employing a program www.WarfarinDosing.org. The main goal was to investigate whether the warfarin doses determined by INR are in accordance with the doses calculated according to the pharmacogenetic algorithm. For this purpose, several chemometric tools, namely principal component analysis, cluster analysis, correlation analysis, correspondence analysis, Passing-Bablock regression, Bland-Altman method, descriptive statistics, and ANOVA were used. We also analysed the relationship between the dose of warfarin determined by INR and several constitutional and genetic factors. Statistically significant association between clinically optimized warfarin dose and indication for the treatment, age, and warfarin sensitivity determined by VKORC1, CYP2C9 gene polymorphisms were confirmed. Finally, we confirmed a good concordance between the INR determined warfarin doses and pharmacogenetic approach.

Pharmacogenetics of warfarin dosing in patients of African and European ancestry.

Despite the introduction of direct acting oral anticoagulants, warfarin remains the most commonly prescribed oral anticoagulant. However, warfarin therapy is plagued by the large inter- and intrapatient variability. The variability in dosing fueled research to identify clinical and genetic predictors and develop more accurate dosing algorithms. Observational studies have demonstrated the significant impact of single nucleotide polymorphisms in CYP2C9 and VKORC1 on warfarin dose in patients of European ancestry and African-Americans. This evidence supported the design and conduct of clinical trials to assess whether genotype-guided dosing results in improved anticoagulation control and outcomes. The trial results have shown discordance by race, with pharmacogenetic algorithms improving dose and anticoagulation control among European ancestry patients compared with African-American patients. Herein, we review the evidence from observational and interventional studies, highlight the need for inclusion of minority race groups and propose the need to develop race specific dosing algorithms.

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.

Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with devastating adverse events. Remarkable efforts have been made to develop the machine learning based warfarin dosing algorithms incorporating clinical factors and genetic variants such as polymorphisms in CYP2C9 and VKORC1. The most widely validated pharmacogenetic algorithm is the IWPC algorithm based on multivariate linear regression (MLR). However, with only a single algorithm, the prediction performance may reach an upper limit even with optimal parameters. Here, we present novel algorithms using stacked generalization frameworks to estimate the warfarin dose, within which different types of machine learning algorithms function together through a meta-machine learning model to maximize the prediction accuracy. Compared to the IWPC-derived MLR algorithm, Stack 1 and 2 based on stacked generalization frameworks performed significantly better overall. Subgroup analysis revealed that the mean of the percentage of patients whose predicted dose of warfarin within 20% of the actual stable therapeutic dose (mean percentage within 20%) for Stack 1 was improved by 12.7% (from 42.47% to 47.86%) in Asians and by 13.5% (from 22.08% to 25.05%) in the low-dose group compared to that for MLR, respectively. These data suggest that our algorithms would especially benefit patients requiring low warfarin maintenance dose, as subtle changes in warfarin dose could lead to adverse clinical events (thrombosis or bleeding) in patients with low dose. Our study offers novel pharmacogenetic algorithms for clinical trials and practice.

Genotype-guided versus traditional clinical dosing of warfarin in patients of Asian ancestry: a randomized controlled trial

BackgroundGenotype-guided warfarin dosing has been shown in some randomized trials to improve anticoagulation outcomes in individuals of European ancestry, yet its utility in Asian patients remains unresolved.MethodsAn open-label, non-inferiority, 1:1 randomized trial was conducted at three academic hospitals in South East Asia, involving 322 ethnically diverse patients newly indicated for warfarin (NCT00700895). Clinical follow-up was 90 days. The primary efficacy measure was the number of dose titrations within the first 2 weeks of therapy, with a mean non-inferiority margin of 0.5 over the first 14 days of therapy.ResultsAmong 322 randomized patients, 269 were evaluable for the primary endpoint. Compared with traditional dosing, the genotype-guided group required fewer dose titrations during the first 2 weeks (1.77 vs. 2.93, difference −1.16, 90% CI −1.48 to −0.84, P < 0.001 for both non-inferiority and superiority). The percentage of time within the therapeutic range over 3 months and median time to stable international normalized ratio (INR) did not differ between the genotype-guided and traditional dosing groups. The frequency of dose titrations (incidence rate ratio 0.76, 95% CI 0.67 to 0.86, P = 0.001), but not frequency of INR measurements, was lower at 1, 2, and 3 months in the genotype-guided group. The proportions of patients who experienced minor or major bleeding, recurrent venous thromboembolism, or out-of-range INR did not differ between both arms. For predicting maintenance doses, the pharmacogenetic algorithm achieved an R2 = 42.4% (P < 0.001) and mean percentage error of −7.4%.ConclusionsAmong Asian adults commencing warfarin therapy, a pharmacogenetic algorithm meets criteria for both non-inferiority and superiority in reducing dose titrations compared with a traditional dosing approach, and performs well in prediction of actual maintenance doses. These findings imply that clinicians may consider applying a pharmacogenetic algorithm to personalize initial warfarin dosages in Asian patients.Trial registrationClinicalTrials.gov NCT00700895. Registered on June 19, 2008.

Pharmacogenetic studies with oral anticoagulants. Genome-wide association studies in vitamin K antagonist and direct oral anticoagulants.

Oral anticoagulants (OAs) are the recommended drugs to prevent cardiovascular events and recurrence in patients with atrial fibrillation (AF) and cardioembolic stroke. We conducted a literature search to review the current state of OAs pharmacogenomics, focusing on Genome Wide Association Studies (GWAs) in patients treated with vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs).VKAs: Warfarin, acenocoumarol, fluindione and phenprocoumon have long been used, but their interindividual variability and narrow therapeutic/safety ratio makes their dosage difficult. GWAs have been useful in finding genetic variants associated with VKAs response. The main genes involved in VKAs pharmacogenetics are: VKORC1, CYP2C19 and CYP4F2. Variants in these genes have been included in pharmacogenetic algorithms to predict the VKAs dose individually in each patient depending on their genotype and clinical variables.DOACs: Dabigatran, apixaban, rivaroxaban and edoxaban have been approved for patients with AF. They have stable pharmacokinetics and do not require routine blood checks, thus avoiding most of the drawbacks of VKAs. Except for a GWAs performed in patients treated with dabigatran, there is no Genome Wide pharmacogenomics data for DOACs. Pharmacogenomics could be useful to predict the better clinical response and avoid adverse events in patients treated with anticoagulants, identifying the most appropriate anticoagulant drug for each patient. Current pharmacogenomics data show that the polymorphisms affecting VKAs or DOACs are different, concluding that personalized medicine based on pharmacogenomics could be possible. However, more studies are required to implement personalized medicine in clinical practice with OA and based on pharmacogenetics of DOACs.

Pharmacogenetic algorithm for individualized controlled ovarian stimulation in assisted reproductive technology cycles

Controlled ovarian stimulation (COS) is crucial for optimizing in-vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) success. Multiple factors influence the ovarian response to COS, making predictions about oocyte yields not so straightforward. As a result, the ovarian response may be poor or suboptimal, or even excessive, all of which have negative consequences for the affected patient. There is a group of patients that present with a suboptimal response to COS despite normal biomarkers of ovarian reserve, such as AFC and AMH. These patients have a lower number of retrieved oocytes than what was expected based on their ovarian reserve, thus showing the inadequacy of using only the traditional ovarian reserve biomarkers to predict the ovarian response. Suboptimal response to COS might be related to ovarian sensitivity to exogenous gonadotropins modulated by genetic factors. The understanding of the gene polymorphisms related to reproductive function can help to improve the clinical management of this patient population and to explain some of the individual patient variability in response to COS. The development of a pharmacogenetic approach concerning COS in the context of assisted reproduction seems attractive as it might help to understand the relationship between genetic variants and ovarian response to exogenous gonadotropins. The patient's genetic profile could be used to select the most appropriate gonadotropin type, predict the optimal dosage for each drug, develop a cost-effective treatment plan, maximize the success rates, and lastly, decrease the time-to-pregnancy.