International warfarin genotype-guided dosing algorithms in the Turkish population and their preventive effects on major and life-threatening hemorrhagic events

Evaluation of a warfarin dosing algorithm including CYP2C9, VKORC1, and CYP4F2 polymorphisms and non-genetic determinants for the Iranian population

BACKGROUND

The response to warfarin, as an oral anticoagulant agent, varies widely among patients from different ethnic groups. In this study, we tried to ascertain and determine the relationship between non-genetic factors and genetic polymorphisms with warfarin therapy; we then proposed a new warfarin dosing prediction algorithm for the estimation of drug sensitivity and resistance in the Iranian population.

METHODS

Overall, 200 warfarin-treated patients with stable doses were recruited, the demographic and clinical characteristics were documented, and genotyping was done using a sequencing assay.

RESULTS

The outcomes of our investigation showed that the genetic polymorphisms of VKORC1(-1639 G > A), CYP2C9*3, CYP2C9*2, amiodarone use, and increasing age were found to be related to a significantly lower mean daily warfarin dose. In contrast, the CYP4F2*3 variant and increased body surface area were linked with an increased dose of warfarin in the Iranians. Our descriptive model could describe 56.5% of the variability in response to warfarin. This population-specific dosing model performed slightly better than other previously published warfarin algorithms for our patient's series. Furthermore, our findings provided the suggestion that incorporating the CYP4F2*3 variant into the dosing algorithm could result in a more precise calculation of warfarin dose requirements in the Iranian population.

CONCLUSIONS

We proposed and validated a population-specific dosing algorithm based on genetic and non-genetic determinants for Iranian patients and evaluated its performance. Accordingly, by using this newly developed algorithm, prescribers could make more informed decisions regarding the treatment of Iranian patients with warfarin.

Warfarin pharmacogenomics in African populations: the importance of ethnicity-based algorithms

Tweetable abstract It is well accepted that pharmacogenomics (PGx) information from Asia and Europe should not be applied to Africa. More work is needed on different ethnic groups to generate population-specific algorithms that can be used effectively and safely.

Validation and comparison between two warfarin dosing clinical algorithms and warfarin fixed dosing in specialized heart center: cross-sectional study

Background

Warfarin is well known as a narrow therapeutic index that has prodigious variability in response which challenges dosing adjustment for the maintenance of therapeutic international normalized ratio. However, an appreciated population not on new oral anticoagulants may still need to be stabilized with warfarin dosing.

Objective

The current study's main objective was to validate and compare two models of warfarin clinical algorithm models namely the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) with warfarin 5 mg fixed standard dosing strategy in a sample of Sudanese subjects.

Method

We have conducted a cross-sectional study recruited from the out-patient clinic at a tertiary specialized heart center. We included subjects with unchanged warfarin dose (stabilized), and with therapeutic international normalized ratio. The predicted doses of warfarin in the two models were calculated by three different methods (accuracy, clinical practicality, and the clinical safety of the clinical algorithms).

Main outcome measure

The primary outcomes were the measurements of the clinical (accuracy, practicality, and safety) in each of the two clinical algorithms models compared to warfarin 5 mg fixed standard dose strategy.

Results

We have enrolled 71 Sudanese subjects with mean age (51.7 ± 14 years), of which (49, 69.0%) were females. There was no significant difference between the warfarin 5 mg fixed standard dose strategy and the predicted doses of the two clinical algorithm models (MAE 1.44, 1.45, and 1.49 mg/day [P =0.4]) respectively. In the clinical practicality, all of the three models had a high percent of subjects (95.0%, 51.9%, and 66.7%) in the ideal dose range in middle dose group (3-7 mg/ day) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithm models respectively. However, a small percent of subjects was exhibited in the warfarin low dose group ≤ 3 mg/day (0.0%, 15.0%, and 10.0%) and warfarin high dose group ≥ 7 mg/day (0.0%, 33.3%, and 33.3%) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithms respectively. In terms of clinical safety, the percent of subjects with severely over-prediction were 28.2%, 22.5%, and 22.5% for warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively. While the percent of severely under-prediction was 12.7%, 7.0%, and 5.6% for the warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively.

Conclusion

The Gage and IWPC clinical algorithm models were accurate, more clinically practical, and clinically safe than warfarin 5 mg standard dosing in the study population. The cardiologist can use either models (Gage and IWPC) to stratify subjects for accurate, practical, and clinically safe warfarin dosing..

Determining the adjusted initial treatment dose of warfarin anticoagulant medicine using kernel-based support vector regression

BACKGROUND AND OBJECTIVE

A novel research field in bioinformatics is pharmacogenomics and the corresponding applications of artificial intelligence tools. Pharmacogenomics is the study of the relationship between genotype and responses to medical measures such as drug use. One of the most effective drugs is warfarin anticoagulant, but determining its initial treatment dose is challenging. Mistakes in the determination of the initial treatment dose can result directly in patient death.

METHODS

Some of the most successful techniques for estimating the initial treatment dose are kernel-based methods. However, all the available studies use pre-defined and constant kernels that might not necessarily address the problem's intended requirements. The present study seeks to define and present a new computational kernel extracted from a data set. This process aims to utilize all the data-related statistical features to generate a dose determination tool proportional to the data set with minimum error rate. The kernel-based version of the least square support vector regression estimator was defined. Through this method, a more appropriate approach was proposed for predicting the adjusted dose of warfarin.

RESULTS AND CONCLUSION

This paper benefits from the International Warfarin Pharmacogenomics Consortium (IWPC) Database. The results obtained in this study demonstrate that the support vector regression with the proposed new kernel can successfully estimate the ideal dosage of warfarin for approximately 68% of patients.

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 was

60.91 ± 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.

Pharmacogenomics-based practice in North Cyprus: its adoption by pharmacists and their attitudes and knowledge

Background Pharmacogenomics is a branch of biotechnological science integrating medicine, pharmacology, and genomics techniques. Moreover, it focuses on creating drug therapies in order to analyze genetic differences in patients causing various responses to a single therapeutic regimen. Objective This cross sectional study aimed to examine the attitude, knowledge and adoption among pharmacists in North Cyprus and the most appropriate method to improve education among them. Setting Community pharmacy setting. Method A total of 103 out of 140 pharmacists responded to a pre-tested and validated questionnaire consisting of 25 items during July through September 2016. Main outcome measure Pharmacists attitude, knowledge and adoption towards pharmacogenomic tests. Result Data showed that most of the pharmacists in North Cyprus had positive attitude and knowledge scores with mean value of 28.3 ± 5.3 (out of 40) and 6.9 ± 0.8 (out of 10) respectively, further findings showed that there is a significant difference among age groups in their total attitude score (p < 0.05). Conclusion Even though pharmacogenomics is a field promising a variety of benefits, it is vital to implement it in clinical settings in order to improve outcomes. Our findings highlight the necessity for more education on the availability and interpretation of pharmacogenomics tests.

Interpretation of the effect of CYP2C9, VKORC1 and CYP4F2 variants on warfarin dosing adjustment in Turkey

It was aimed to underline the importance and explain the meaning of genetic testing in warfarin dosing and investigate and evaluate the contributions of the CYP2C9, VKORC1, and CYP4F2 variants in a Turkish population. Two hundred patients were genotyped for CYP2C9 (rs1799853, rs1057910 and rs56165452), VKORC1 (rs9934438, rs8050894, rs9923231, rs7294 and rs2359612) and CYP4F2 (rs2108622), yet, only 127 patients were found suitable for further evaluation in terms of their personal response to warfarin due to long term usage and available INR and dose usage information. The DNA sequences were determined by the ABI PRISM 3100 Genetic Analyzer to 3130xl System (Applied Biosystems, Foster City, California). Warfarin dose application suggestions by warfaringdosing.org, FDA and MayoClinic were followed. Dose requirements in the Turkish population were found higher than the suggested doses by warfarindosing.org. The multivariate logistic regression analysis reveals the utilization of VCORC1 genetic evaluation is valuable in warfarin dosing (low and moderate vs. high) in this study (p < 0.001). The present study provides findings for clinicians to adapt the genetic data to the daily practice. We observed that the VKORC1 variant showed a more potent impact in warfarin dosing in this study.

A novel acenocoumarol pharmacogenomic dosing algorithm for the Greek population of EU-PACT trial

Aim: To generate and validate a pharmacogenomic-guided (PG) dosing algorithm for acenocoumarol in the Greek population. To compare its performance with other PG algorithms developed for the Greek population. Patients & methods: A total of 140 Greek patients participants of the EU-PACT trial for acenocoumarol, a randomized clinical trial that prospectively compared the effect of a PG dosing algorithm with a clinical dosing algorithm on the percentage of time within INR therapeutic range, who reached acenocoumarol stable dose were included in the study. Results: CYP2C9 and VKORC1 genotypes, age and weight affected acenocoumarol dose and predicted 53.9% of its variability. EU-PACT PG algorithm overestimated acenocoumarol dose across all different CYP2C9/VKORC1 functional phenotype bins (predicted dose vs stable dose in normal responders 2.31 vs 2.00 mg/day, p = 0.028, in sensitive responders 1.72 vs 1.50 mg/day, p = 0.003, in highly sensitive responders 1.39 vs 1.00 mg/day, p = 0.029). The PG algorithm previously developed for the Greek population overestimated the dose in normal responders (2.51 vs 2.00 mg/day, p < 0.001). Conclusion: Ethnic-specific dosing algorithm is suggested for better prediction of acenocoumarol dosage requirements in patients of Greek origin.

Allergy-specific Phenome-Wide Association Study for Immunogenes in Turkish Children

To dissect the role of immunogenetics in allergy and asthma, we performed a phenome-wide association study in 974 Turkish children selected from a cross-sectional study conducted using ISAAC (International Study of Asthma and Allergies in Children) Phase II tools. We investigated 9 loci involved in different immune functions (ADAM33, ADRB2, CD14, IL13, IL4, IL4R, MS4A2, SERPINE1, and TNF) with respect to 116 traits assessed through blood tests, hypertonic saline challenge tests, questionnaires, and skin prick tests. Multiple associations were observed for ADAM33: rs2280090 was associated with reduced MEF240% (i.e., the ratio of Mean Expiratory Flow after 240s of hypertonic saline inhalation with respect to the age- and ancestry-matched reference value) and with an increased risk of allergic bronchitis (p = 1.77*10⁻⁴ and p = 7.94*10⁻⁴, respectively); rs3918396 was associated with wheezing and eczema comorbidity (p = 3.41*10⁻⁴). IL4 rs2243250 was associated with increased FEV240 (Forced Expiratory Flow Volume after 240s of hypertonic saline inhalation; p = 4.81*10⁻⁴) and CD14 rs2569190 was associated with asthma diagnosis (p = 1.36*10⁻³). ADAM33 and IL4 appeared to play a role in the processes linked to allergic airway inflammation and lung function. Due to its association with wheezing and eczema comorbidity, ADAM33 may also be involved in the atopic march.

Haplotype analysis of non-HLA immunogenetic loci in Turkish and worldwide populations

Immunogenes (i.e., genes related to the immune system and its functions) are involved in the predisposition to numerous traits and their variation contributes to the phenotypic variability observed among human groups. Turkish population presents particular genetic features since its genetic pool is an admixture of European, Middle-Eastern, and Central Asian ancestries. Here, we analyzed the haplotype structure of four immunogenetic loci (i.e., ADAM33; IL13-IL4; IL4R; MS4A2) in 482 subjects from five different regions of Turkey. Genotyping was performed using KASP technology. Turkish data were compared with the haplotype information available from the 1000 Genomes Project Phase 3 (26 human populations from 5 ancestry groups). We did not observe significant differences among Turkish groups. Comparing other ancestries, we identified haplotype similarity of Turkish subjects with European populations in IL13-IL4, IL4R, and ADAM33 loci; and with central Asians in MS4A2 region. Considering loci displaying Turkish-European haplotype similarity (i.e., IL13-IL4, IL4R, and ADAM33), we observed differences between Turkish subjects and northern/western Europeans. Conversely, no significant difference was determined in MS4A2 between Turkish and central Asian populations. Finally, we assessed the haplotypes responsible for the differences between Turkish and European samples and the potential functional effects on the immunogenetic loci investigated.

Nutritional habits, lifestyle, and genetic predisposition in cardiovascular and metabolic traits in Turkish population

OBJECTIVES

Cardiovascular and metabolic traits (CMT) are influenced by complex interactive processes including diet, lifestyle, and genetic predisposition. The present study investigated the interactions of these risk factors in relation to CMTs in the Turkish population.

METHODS

We applied bootstrap agglomerative hierarchical clustering and Bayesian network learning algorithms to identify the causative relationships among genes involved in different biological mechanisms (i.e., lipid metabolism, hormone metabolism, cellular detoxification, aging, and energy metabolism), lifestyle (i.e., physical activity, smoking behavior, and metropolitan residency), anthropometric traits (i.e., body mass index, body fat ratio, and waist-to-hip ratio), and dietary habits (i.e., daily intakes of macro- and micronutrients) in relation to CMTs (i.e., health conditions and blood parameters).

RESULTS

We identified significant correlations between dietary habits (soybean and vitamin B12 intakes) and different cardiometabolic diseases that were confirmed by the Bayesian network-learning algorithm. Genetic factors contributed to these disease risks also through the pleiotropy of some genetic variants (i.e., F5 rs6025 and MTR rs180508). However, we also observed that certain genetic associations are indirect since they are due to the causative relationships among the CMTs (e.g., APOC3 rs5128 is associated with low-density lipoproteins cholesterol and, by extension, total cholesterol).

CONCLUSIONS

Our study applied a novel approach to integrate various sources of information and dissect the complex interactive processes related to CMTs. Our data indicated that complex causative networks are present: causative relationships exist among CMTs and are affected by genetic factors (with pleiotropic and non-pleiotropic effects) and dietary habits.