Clinical Pharmacogenetics Implementation Consortium Guidelines for CYP2C9 and VKORC1 genotypes and warfarin dosing

Association between gene polymorphisms and initial warfarin therapy in patients after heart valve surgery

BACKGROUND

Warfarin is widely used for the prevention and treatment of thrombotic events. This study aimed to examine the influence of gene polymorphisms on the early stage of warfarin therapy in patients following heart valve surgery.

METHODS

Nine single nucleotide polymorphisms were genotyped using microarray chips, categorizing patients into three groups: normal responders (Group I), sensitive responders (Group II), and highly sensitive responders (Group III). The primary clinical outcomes examined were time in therapeutic range (TTR) and international normalized ratio (INR) variability. To investigate potential influencing factors, a generalized linear regression model was employed.

RESULTS

Among 734 patients, the prevalence of CYP2C9*3-1075A > C, CYP2C19*3-636G > A, and CYP2C19*17-806C > T variants were 11.2%, 9.9%, and 1.9% of patients, respectively. VKORC1-1639G > A or the linked -1173C > T variant was observed in 99.0% of the patients. Generalized linear model analysis revealed an impact of sensitivity grouping on INR variability. Compared to Group I, Group II showed higher TTR values (p = 0.023), while INR variability was poorer in Group II (p < 0.001) and Group III (p < 0.001). Individual gene analysis identified significant associations between CYP2C9*3-1075A > C (p < 0.001), VKORC1-1639G > A or the linked -1173 C > T (p = 0.009) and GGCX-3261G > A (p = 0.019) with INR variability.

CONCLUSION

The genotypes of CYP2C9, VKORC1, and GGCX were found to have a significant impact on INR variability during the initial phase of warfarin therapy. However, no significant association was observed between TTR and gene polymorphisms. These findings suggest that focusing on INR variability is crucial in clinical practice, and preoperative detection of gene polymorphisms should be considered to assist in the initiation of warfarin therapy.

Being precise with anticoagulation to reduce adverse drug reactions: are we there yet?

Anticoagulants are potent therapeutics widely used in medical and surgical settings, and the amount spent on anticoagulation is rising. Although warfarin remains a widely prescribed oral anticoagulant, prescriptions of direct oral anticoagulants (DOACs) have increased rapidly. Heparin-based parenteral anticoagulants include both unfractionated and low molecular weight heparins (LMWHs). In clinical practice, anticoagulants are generally well tolerated, although interindividual variability in response is apparent. This variability in anticoagulant response can lead to serious incident thrombosis, haemorrhage and off-target adverse reactions such as heparin-induced thrombocytopaenia (HIT). This review seeks to highlight the genetic, environmental and clinical factors associated with variability in anticoagulant response, and review the current evidence base for tailoring the drug, dose, and/or monitoring decisions to identified patient subgroups to improve anticoagulant safety. Areas that would benefit from further research are also identified. Validated variants in VKORC1, CYP2C9 and CYP4F2 constitute biomarkers for differential warfarin response and genotype-informed warfarin dosing has been shown to reduce adverse clinical events. Polymorphisms in CES1 appear relevant to dabigatran exposure but the genetic studies focusing on clinical outcomes such as bleeding are sparse. The influence of body weight on LMWH response merits further attention, as does the relationship between anti-Xa levels and clinical outcomes. Ultimately, safe and effective anticoagulation requires both a deeper parsing of factors contributing to variable response, and further prospective studies to determine optimal therapeutic strategies in identified higher risk subgroups.

Mining local exome and HLA data to characterize pharmacogenetic variants in Saudi Arabia

Pharmacogenomics (PGx) is a promising field of precision medicine where efficacy of drugs is maximized while side effects are minimized for individual patients. Knowledge of the frequency of PGx-relevant variants (pharmacovariants) in the local population is a pre-requisite to informed policy making. Unfortunately, such knowledge is largely lacking from the Middle East. Here, we describe the use of a large clinical exome database (n = 13,473) and HLA haplotypes (n = 64,737) from Saudi Arabia, one of the largest countries in the Middle East, along with previously published data from the local population to ascertain allele frequencies of known pharmacovariants. In addition, we queried another exome database (n = 816) of well-phenotyped research subjects from Saudi Arabia to discover novel candidate variants in known PGx genes (pharmacogenes). Although our results show that only 26% (63/242) of class 1A/1B PharmGKB variants were identified, we estimate that 99.57% of the local population have at least one such variant. This translates to a minimum estimated impact of 9% of medications dispensed by our medical center annually. We also highlight the contribution of rare variants where 71% of the pharmacogenes devoid of common pharmacovariants had at least one potentially deleterious rare variant. Thus, we show that approaches that go beyond the use of commercial PGx kits that have been optimized for other populations should be implemented to ensure universal and equitable access of all members of the local population to personalized prescription practices.

LA-GEM: imputation of gene expression with incorporation of Local Ancestry

Gene imputation and TWAS have become a staple in the genomics medicine discovery space; helping to identify genes whose regulation effects may contribute to disease susceptibility. However, the cohorts on which these methods are built are overwhelmingly of European Ancestry. This means that the unique regulatory variation that exist in non-European populations, specifically African Ancestry populations, may not be included in the current models. Moreover, African Americans are an admixed population, with a mix of European and African segments within their genome. No gene imputation model thus far has incorporated the effect of local ancestry (LA) on gene expression imputation. As such, we created LA-GEM which was trained and tested on a cohort of 60 African American hepatocyte primary cultures. Uniquely, LA-GEM include local ancestry inference in its prediction of gene expression. We compared the performance of LA-GEM to PrediXcan trained the same dataset (with no inclusion of local ancestry) We were able to reliably predict the expression of 2559 genes (1326 in LA-GEM and 1236 in PrediXcan). Of these, 546 genes were unique to LA-GEM, including the CYP3A5 gene which is critical to drug metabolism. We conducted TWAS analysis on two African American clinical cohorts with pharmacogenomics phenotypic information to identity novel gene associations. In our IWPC warfarin cohort, we identified 17 transcriptome-wide significant hits. No gene reached are prespecified significance level in the clopidogrel cohort. We did see suggestive association with RAS3A to P2RY12 Reactivity Units (PRU), a clinical measure of response to anti-platelet therapy. This method demonstrated the need for the incorporation of LA into study in admixed populations.

Pharmacogenomic Considerations for Anticoagulant Prescription in Patients with Hereditary Haemorrhagic Telangiectasia

Hereditary haemorrhagic telangiectasia (HHT) is a vascular dysplasia that commonly results in bleeding but with frequent indications for therapeutic anticoagulation. Our aims were to advance the understanding of drug-specific intolerance and evaluate if there was an indication for pharmacogenomic testing. Genes encoding proteins involved in the absorption, distribution, metabolism, and excretion of warfarin, heparin, and direct oral anticoagulants (DOACs) apixaban, rivaroxaban, edoxaban, and dabigatran were identified and examined. Linkage disequilibrium with HHT genes was excluded, before variants within these genes were examined following whole genome sequencing of general and HHT populations. The 44 genes identified included 5/17 actionable pharmacogenes with guidelines. The 76,156 participants in the Genome Aggregation Database v3.1.2 had 28,446 variants, including 9668 missense substitutions and 1076 predicted loss-of-function (frameshift, nonsense, and consensus splice site) variants, i.e., approximately 1 in 7.9 individuals had a missense substitution, and 1 in 71 had a loss-of-function variant. Focusing on the 17 genes relevant to usually preferred DOACs, similar variant profiles were identified in HHT patients. With HHT patients at particular risk of haemorrhage when undergoing anticoagulant treatment, we explore how pre-emptive pharmacogenomic testing, alongside HHT gene testing, may prove beneficial in reducing the risk of bleeding and conclude that HHT patients are well placed to be at the vanguard of personalised prescribing.

Genetics in Ischemic Stroke: Current Perspectives and Future Directions

Ischemic stroke is a heterogeneous condition influenced by a combination of genetic and environmental factors. Recent advancements have explored genetics in relation to various aspects of ischemic stroke, including the alteration of individual stroke occurrence risk, modulation of treatment response, and effectiveness of post-stroke functional recovery. This article aims to review the recent findings from genetic studies related to various clinical and molecular aspects of ischemic stroke. The potential clinical applications of these genetic insights in stratifying stroke risk, guiding personalized therapy, and identifying new therapeutic targets are discussed herein.

Functional Characterization of 29 Cytochrome P450 4F2 Variants Identified in a Population of 8380 Japanese Subjects and Assessment of Arachidonic Acid ω-Hydroxylation

Cytochrome P450 4F2 (CYP4F2) is an enzyme that is involved in the metabolism of arachidonic acid (AA), vitamin E and K, and xenobiotics including drugs. CYP4F2*3 polymorphism (rs2108622; c.1297G>A; p.Val433Met) has been associated with hypertension, ischemic stroke, and variation in the effectiveness of the anticoagulant drug warfarin. In this study, we characterized wild-type CYP4F2 and 28 CYP4F2 variants, including a Val433Met substitution, detected in 8380 Japanese subjects. The CYP4F2 variants were heterologously expressed in 293FT cells to measure the concentrations of CYP4F2 variant holoenzymes using carbon monoxide-reduced difference spectroscopy, where the wild type and 18 holoenzyme variants showed a peak at 450 nm. Kinetic parameters [Vmax , substrate concentration producing half of Vmax (S50 ), and intrinsic clearance (CL int ) as Vmax /S50 ] of AA ω-hydroxylation were determined for the wild type and 21 variants with enzyme activity. Compared with the wild type, two variants showed significantly decreased CL int values for AA ω-hydroxylation. The values for seven variants could not be determined because no enzymatic activity was detected at the highest substrate concentration used. Three-dimensional structural modeling was performed to determine the reason for reduced enzymatic activity of the CYP4F2 variants. Our findings contribute to a better understanding of CYP4F2 variant-associated diseases and possible future therapeutic strategies. SIGNIFICANCE STATEMENT: CYP4F2 is involved in the metabolism of arachidonic acid and vitamin K, and CYP4F2*3 polymorphisms have been associated with hypertension and variation in the effectiveness of the anticoagulant drug warfarin. This study presents a functional analysis of 28 CYP4F2 variants identified in Japanese subjects, demonstrating that seven gene polymorphisms cause loss of CYP4F2 function, and proposes structural changes that lead to altered function.

Simulating clinical trials for model-informed precision dosing: using warfarin treatment as a use case

Treatment response variability across patients is a common phenomenon in clinical practice. For many drugs this inter-individual variability does not require much (if any) individualisation of dosing strategies. However, for some drugs, including chemotherapies and some monoclonal antibody treatments, individualisation of dosages are needed to avoid harmful adverse events. Model-informed precision dosing (MIPD) is an emerging approach to guide the individualisation of dosing regimens of otherwise difficult-to-administer drugs. Several MIPD approaches have been suggested to predict dosing strategies, including regression, reinforcement learning (RL) and pharmacokinetic and pharmacodynamic (PKPD) modelling. A unified framework to study the strengths and limitations of these approaches is missing. We develop a framework to simulate clinical MIPD trials, providing a cost and time efficient way to test different MIPD approaches. Central for our framework is a clinical trial model that emulates the complexities in clinical practice that challenge successful treatment individualisation. We demonstrate this framework using warfarin treatment as a use case and investigate three popular MIPD methods: 1. Neural network regression; 2. Deep RL; and 3. PKPD modelling. We find that the PKPD model individualises warfarin dosing regimens with the highest success rate and the highest efficiency: 75.1% of the individuals display INRs inside the therapeutic range at the end of the simulated trial; and the median time in the therapeutic range (TTR) is 74%. In comparison, the regression model and the deep RL model have success rates of 47.0% and 65.8%, and median TTRs of 45% and 68%. We also find that the MIPD models can attain different degrees of individualisation: the Regression model individualises dosing regimens up to variability explained by covariates; the Deep RL model and the PKPD model individualise dosing regimens accounting also for additional variation using monitoring data. However, the Deep RL model focusses on control of the treatment response, while the PKPD model uses the data also to further the individualisation of predictions.

Implementation of Pharmacogenetics in First-Line Care: Evaluation of Its Use by General Practitioners

Pharmacogenetics (PGx) can explain/predict drug therapy outcomes. There is, however, unclarity about the use and usefulness of PGx in primary care. In this study, we investigated PGx tests ordered by general practitioners (GPs) in 2021 at Dept. Clinical Chemistry, Erasmus MC, and analyzed the gene tests ordered, drugs/drug groups, reasons for testing and single-gene versus panel testing. Additionally, a survey was sent to 90 GPs asking about their experiences and barriers to implementing PGx. In total, 1206 patients and 6300 PGx tests were requested by GPs. CYP2C19 was requested most frequently (17%), and clopidogrel was the most commonly indicated drug (23%). Regarding drug groups, antidepressants (51%) were the main driver for requesting PGx, followed by antihypertensives (26%). Side effects (79%) and non-response (27%) were the main indicators. Panel testing was preferred over single-gene testing. The survey revealed knowledge on when and how to use PGx as one of the main barriers. In conclusion, PGx is currently used by GPs in clinical practice in the Netherlands. Side effects are the main reason for testing, which mostly involves antidepressants. Lack of knowledge is indicated as a major barrier, indicating the need for more education on PGx for GPs.

An Adaptive Model Predictive Controller to Address the Biovariability in Blood Clotting Response During Therapy With Warfarin

OBJECTIVE

Effective dosing of anticoagulants aims to prevent blood clot formation while avoiding hemorrhages. This complex task is challenged by several disturbing factors and drug-effect uncertainties, requesting frequent monitoring and adjustment. Biovariability in drug absorption and action further complicates titration and calls for individualized strategies. In this paper, we propose an adaptive closed-loop control algorithm to assist in warfarin therapy management.

METHODS

The controller was designed and tested in silico using an established pharmacometrics model of warfarin, which accounts for inter-subject variability. The control algorithm is an adaptive Model Predictive Control (a-MPC) that leverages a simplified patient model, whose parameters are updated with a Bayesian strategy. Performance was quantitatively evaluated in simulations performed on a population of virtual subjects against an algorithm reproducing medical guidelines (MG) and an MPC controller available in the literature (l-MPC).

RESULTS

The proposed a-MPC significantly (p 0.05) lowers rising time (2.8 vs. 4.4 and 11.2 days) and time out of range (3.3 vs. 7.2 and 12.9 days) with respect to both MG and l-MPC, respectively. Adaptivity grants a significantly (p 0.05) lower number of subjects reaching unsafe INR values compared to when this feature is not present (8.9% vs.15% of subjects presenting an overshoot outside the target range and 0.08% vs. 0.28% of subjects reaching dangerous INR values).

CONCLUSION

The a-MPC algorithm improve warfarin therapy compared to the benchmark therapies.

SIGNIFICANCE

This in-silico validation proves effectiveness of the a-MPC algorithm for anticoagulant administration, paving the way for clinical testing.

Evaluation of Drug-Drug Interaction Potential of Enarodustat (JTZ-951) Using a Cytochrome P450 Probe Cocktail

The drug interaction potential of enarodustat (doses: 25, 50 mg) on the activity of cytochrome P450 (CYP) 1A2, 2C9, 2C19, 2D6, and 3A4 was evaluated after once-daily administration for 15 days in a phase 1 multiple-ascending-dose study in healthy subjects. Probe substrates specific for the enzymes, i.e., caffeine (CYP1A2), tolbutamide (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A4), were administered orally as a cocktail with (day 15) and without (day -3) enarodustat. Drug interaction was based on geometric mean maximum plasma concentration (Cmax ) and area under the plasma concentration-time curve from the time of dosing to infinity (AUCinf ) ratios (day 15/day -3) for CYP1A2, 2C9, 2C19, 2D6, 3A4, and urinary excretion of dextromethorphan metabolite dextrorphan for CYP2D6. At the 2 enarodustat doses, for caffeine, the geometric mean ratios (range) for Cmax and AUCinf were 0.99-1.06 and 1.61-1.63, respectively. The ratios for peak concentrations and total exposures were 0.98-1.07 and 0.71-1.78 for tolbutamide and omeprazole, respectively. For dextrorphan the Cmax and AUCinf ratios were 0.83-0.90 and 1.02-1.04, respectively. The mean dextrorphan cumulative amount excreted into the urine from the time of dosing to 24 hours values on day -3 and day 15 were 8.25 mg and 8.20 mg at the lower dose, and 9.40 mg and 9.51 mg at the higher dose. The ratios for midazolam Cmax and AUCinf were 1.42-1.63. Overall, there was a lack of enarodustat dose dependency regarding the geometric mean ratios and 90% confidence intervals and urinary excretion of dextrorphan. There were some cases where the 90% confidence intervals at the 2 enarodustat doses were outside the 0.80-1.25 range, but changes in the geometric mean ratios were all <2-fold.

Targeted next-generation sequencing of genes involved in Warfarin Pharmacodynamics and pharmacokinetics pathways using the Saudi Warfarin Pharmacogenetic study (SWAP)

BACKGROUND

Warfarin is an oral anticoagulant commonly used for treatment and prophylaxis against thromboembolic events. Warfarins's narrow therapeutic index window is one of the main challenges in clinical practice; thus, it requires frequent monitoring and dose adjustment to maintain patients' therapeutic range. Warfarin dose variation and response are attributed to several inter-and intra-individuals factors, including genetic variants in enzymes involved in warfarin pharmacokinetics (PK) and pharmacodynamics (PD) pathways. Thus, we aim to utilize the next-generation sequencing (NGS) approach to identify rare and common genetic variants that might be associated with warfarin responsiveness.

METHOD AND RESULTS

A predesigned NGS panel that included 16 genes involved in Warfarin PK/PD pathways was used to sequence 786 patients from the Saudi Warfarin Pharmacogenetic Cohort (SWAP). Identified variants were annotated using several annotation tools to identify the pathogenicity and allele frequencies of these variants. We conducted variants-level association tests with warfarin dose. We identified 710 variants within the sequenced genes; 19% were novel variants, with the vast majority being scarce variants. The genetic association tests showed that VKORC1 (rs9923231, and rs61742245), CYP2C9 (rs98332238, rs9332172, rs1057910, rs9332230, rs1799853, rs1057911, and rs9332119), CYP2C19 (rs28399511, and rs3758581), and CYP2C8 (rs11572080 and rs10509681) were significantly associated with warfarin weekly dose. Our model included genetics, and non-genetic factors explained 40.1% of warfarin dose variation.

CONCLUSION

The study identifies novel variants associated with warfarin dose in the Saudi population. These variants are more likely to be population-specific variants, suggesting that population-specific studies should be conducted before adopting a universal warfarin genotype-guided dosing algorithm.

Control-Relevant Adaptive Personalized Modeling From Limited Clinical Data for Precise Warfarin Management

Warfarin is a challenging drug to administer due to the narrow therapeutic index of the International Normalized Ratio (INR), the inter- and intra-variability of patients, limited clinical data, genetics, and the effects of other medications. Goal: To predict the optimal warfarin dosage in the presence of the aforementioned challenges, we present an adaptive individualized modeling framework based on model (In)validation and semi-blind robust system identification. The model (In)validation technique adapts the identified individualized patient model according to the change in the patient's status to ensure the model's suitability for prediction and controller design. Results: To implement the proposed adaptive modeling framework, the clinical data of warfarin-INR of forty-four patients has been collected at the Robley Rex Veterans Administration Medical Center, Louisville. The proposed algorithm is compared with recursive ARX and ARMAX model identification methods. The results of identified models using one-step-ahead prediction and minimum mean squared analysis (MMSE) show that the proposed framework effectively predicts the warfarin dosage to keep the INR values within the desired range and adapt the individualized patient model to exhibit the true status of the patient throughout treatment. Conclusion: This paper proposes an adaptive personalized patient modeling framework from limited patientspecific clinical data. It is shown by rigorous simulations that the proposed framework can accurately predict a patient's doseresponse characteristics and it can alert the clinician whenever identified models are no longer suitable for prediction and adapt the model to the current status of the patient to reduce the prediction error.

Pharmacogenomics in Stroke and Cardiovascular Disease: State of the Art

There is considerable interindividual variability in the response to antiplatelet and anticoagulant therapies, and this variation may be attributable to genetic variants. There has been an increased understanding of the genetic architecture of stroke and cardiovascular disease, which has been driven by advancements in genomic technologies and this has raised the possibility of more targeted pharmaceutical treatments. Pharmacogenetics promises to use a patient's genetic profile to treat those who are more likely to benefit from a particular intervention by selecting the best possible therapy. Although there are numerous studies indicating strong evidence for the effect of specific genotypes on the outcomes of vascular drugs, the adoption of pharmacogenetic testing in clinical practice has been slow. This resistance may stem from sometimes conflicting findings among pharmacogenetic studies, a lack of stroke-specific randomized controlled trials to test the effectiveness of genetically-guided therapies, and the practical and cost-effective implementation of genetic testing within the clinic. Thus, this review provides an overview of the genetic variants that influence the individual responses to aspirin, clopidogrel, warfarin and statins and the different methods for pharmacogenetic testing and guidelines for clinical implementation for stroke patients.

Comparison of Maintenance Dose Predictions by Warfarin Dosing Algorithms Based on Chinese and Western Patients

Warfarin has a long record of safe and effective clinical use, and it remains one of the most commonly prescribed drugs for the prevention and treatment of thromboembolic conditions even in the era of direct oral anticoagulants. To address its large interindividual variability and narrow therapeutic window, the Clinical Pharmacogenetics Implementation Consortium has recommended using pharmacogenetic dosing algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al, to dose warfarin when genotype information is available. In China, dosing algorithms based on local patient populations have been developed and evaluated for predictive accuracy of warfarin maintenance doses. In this study, percentage deviations of doses predicted by 15 Chinese dosing algorithms from that by IWPC and Gage algorithms were systematically evaluated to understand the differences between Chinese and Western algorithms. In general, dose predictions by Chinese dosing algorithms tended to be lower than those predicted by IWPC or Gage algorithms for the most prevalent VKORC1 and CYP2C9 genotypes in the Chinese population. The extent of negative prediction deviation appeared to be largest in the younger age group with smaller body weight. Our findings are consistent with previous reports that Asians have a higher sensitivity to warfarin and require lower doses than Western populations.

Leveraging a pharmacogenomics knowledgebase to formulate a drug response phenotype terminology for genomic medicine

MOTIVATION

Despite the increasing evidence of utility of genomic medicine in clinical practice, systematically integrating genomic medicine information and knowledge into clinical systems with a high-level of consistency, scalability and computability remains challenging. A comprehensive terminology is required for relevant concepts and the associated knowledge model for representing relationships. In this study, we leveraged PharmGKB, a comprehensive pharmacogenomics (PGx) knowledgebase, to formulate a terminology for drug response phenotypes that can represent relationships between genetic variants and treatments. We evaluated coverage of the terminology through manual review of a randomly selected subset of 200 sentences extracted from genetic reports that contained concepts for 'Genes and Gene Products' and 'Treatments'.

RESULTS

Results showed that our proposed drug response phenotype terminology could cover 96% of the drug response phenotypes in genetic reports. Among 18 653 sentences that contained both 'Genes and Gene Products' and 'Treatments', 3011 sentences were able to be mapped to a drug response phenotype in our proposed terminology, among which the most discussed drug response phenotypes were response (994), sensitivity (829) and survival (332). In addition, we were able to re-analyze genetic report context incorporating the proposed terminology and enrich our previously proposed PGx knowledge model to reveal relationships between genetic variants and treatments. In conclusion, we proposed a drug response phenotype terminology that enhanced structured knowledge representation of genomic medicine.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Rates of Divergent Pharmacogenes in a Psychiatric Cohort of Inpatients with Depression-Arguments for Preemptive Testing

Background: The international drug agencies annotate pharmacogenes for many years. Pharmacogenetic testing is thus far only established in few settings, assuming that only few patients are actually affected by drug-gene interactions. Methods: 108 hospitalized patients with major depressive disorder were genotyped for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NAT2, DPYD; VKORC1 and TMTP. Results: We found 583 (mean 5.4, median 5) divergent phenotypes (i.e., divergent from the common phenotypes considered normal, e.g., extensive metabolizer) in the 12 analyzed pharmacokinetic genes. The rate for at least one divergent phenotype was 100% in our cohort for CYP, but also for all 12 important pharmacogenes: patients had at least two divergent phenotypes. Compared to a large Danish cohort, CYP2C9 NM and IM status, CYP2C19 UM, CYP2D6 UM and DYPD (GAS 0, 1, 2) genotypes differed statistical significantly. For CYP2D6 and CYP2C19, 13% of the patients were normal metabolizers for both enzymes in our cohort, but this value was 27.3% in the Danish cohort, which is a highly significant difference (p < 0.0001). Conclusion: Divergent phenotypes in pharmacogenes are not the exception, but the rule. Patients with divergent phenotypes seem more prone for hospitalization, emphasizing the need for pre-emptive testing to avoid inefficacy and adverse drug effects in all patients.

Hyper-responsiveness to warfarin in a young patient with the VKORC1 -1639GA/CYP2C9*1*46 genotype: a case report

BACKGROUND

Warfarin is the most widely used oral anticoagulant; nevertheless, dosing of warfarin is problematic for clinicians worldwide. Inter-individual variability in response to warfarin is attributed to genetic as well as non-genetic factors. Pharmacogenomics studies have identified variants in CYP2C9 and VKORC1 genes as significant predictors of warfarin dose, however, phenotypes of rare variants are not well characterized.

CASE PRESENTATION

We report a case of hyper-responsiveness to warfarin in a 22-year-old outpatient with Crohn's disease who presented with a swollen, red, and painful left calf. Deep venous thrombosis (DVT) in the left lower extremity was confirmed via ultrasonography, and hence, anticoagulation therapy of heparin and concomitant warfarin was initiated. Warfarin dose of 7.5 mg/day was estimated by the physician based on clinical factors. Higher than the expected international normalized ratio (INR) value of 4.5 necessitated the reduction of the warfarin dose to 5 and eventually to 2.5 mg/day to reach a therapeutic INR value of 2.6. Pharmacogenetic profiling of the VKORC1 -1639G > A and CYP2C9 *2, *3, *4, *5, *8, *14, *20, *24, *26, *33, *40, *41, *42, *43, *45, *46, *55, *62, *63, *66, *68, *72, *73 and *78 revealed a VKORC1-1639GA/CYP2C9*1*46 genotype. The lower catalytic activity of the CYP2C9*46 (A149T) variant was previously reported in in vitro settings.

CONCLUSIONS

This is the first report on a case of warfarin hyper-responsive phenotype of a patient with the heterozygous CYP2C9*1*46 polymorphism.

Bringing pharmacomicrobiomics to the clinic through well-designed studies

Pharmacomicrobiomic studies investigate drug-microbiome interactions, such as the effect of microbial variation on drug response and disposition. Studying and understanding the interactions between the gut microbiome and drugs is becoming increasingly relevant to clinical practice due to its potential for avoiding adverse drug reactions or predicting variability in drug response. The highly variable nature of the human microbiome presents significant challenges to assessing microbes' influence. Studies aiming to explore drug-microbiome interactions should be well-designed to account for variation in the microbiome over time and collect data on confounders such as diet, disease, concomitant drugs, and other environmental factors. Here, we assemble a set of important considerations and recommendations for the methodological features required for performing a pharmacomicrobiomic study in humans with a focus on the gut microbiome. Consideration of these factors enable discovery, reproducibility, and more accurate characterization of the relationships between a given drug and the microbiome. Furthermore, appropriate interpretation and dissemination of results from well-designed studies will push the field closer to clinical relevance and implementation.

A Systematic Review of Polygenic Models for Predicting Drug Outcomes

Polygenic models have emerged as promising prediction tools for the prediction of complex traits. Currently, the majority of polygenic models are developed in the context of predicting disease risk, but polygenic models may also prove useful in predicting drug outcomes. This study sought to understand how polygenic models incorporating pharmacogenetic variants are being used in the prediction of drug outcomes. A systematic review was conducted with the aim of gaining insights into the methods used to construct polygenic models, as well as their performance in drug outcome prediction. The search uncovered 89 papers that incorporated pharmacogenetic variants in the development of polygenic models. It was found that the most common polygenic models were constructed for drug dosing predictions in anticoagulant therapies (n = 27). While nearly all studies found a significant association with their polygenic model and the investigated drug outcome (93.3%), less than half (47.2%) compared the performance of the polygenic model against clinical predictors, and even fewer (40.4%) sought to validate model predictions in an independent cohort. Additionally, the heterogeneity of reported performance measures makes the comparison of models across studies challenging. These findings highlight key considerations for future work in developing polygenic models in pharmacogenomic research.

Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing

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

Ethnic Diversity and Warfarin Pharmacogenomics

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

Clinical Phenotypes of Cardiovascular and Heart Failure Diseases Can Be Reversed? The Holistic Principle of Systems Biology in Multifaceted Heart Diseases

Recent advances in cardiology and biological sciences have improved quality of life in patients with complex cardiovascular diseases (CVDs) or heart failure (HF). Regardless of medical progress, complex cardiac diseases continue to have a prolonged clinical course with high morbidity and mortality. Interventional coronary techniques together with drug therapy improve quality and future prospects of life, but do not reverse the course of the atherosclerotic process that remains relentlessly progressive. The probability of CVDs and HF phenotypes to reverse can be supported by the advances made on the medical holistic principle of systems biology (SB) and on artificial intelligence (AI). Studies on clinical phenotypes reversal should be based on the research performed in large populations of patients following gathering and analyzing large amounts of relative data that embrace the concept of complexity. To decipher the complexity conundrum, a multiomics approach is needed with network analysis of the biological data. Only by understanding the complexity of chronic heart diseases and explaining the interrelationship between different interconnected biological networks can the probability for clinical phenotypes reversal be increased.

Comparison of Warfarin Initiation at 3 mg Versus 5 mg for Anticoagulation of Patients with Mechanical Mitral Valve Replacement Surgery: A Prospective Randomized Trial

Background

The increased warfarin sensitivity observed after mechanical mitral valve replacement (MVR) operations dictates clinical discretion in warfarin dose initiation. Evidence is still lacking with regard to anticoagulation management of MVR patients.

Objective

This study aimed to compare initiating warfarin at the recommended dosing regimen versus empirically lowered doses intended to account for the variation in warfarin sensitivity.

Methods

A prospective, single-blind, randomized, comparative study was conducted in postoperative MVR patients. Patients were randomly assigned to either the 5 mg group (n = 25) or the 3 mg group (n = 25) and were initiated on a 5 or 3 mg warfarin dose, respectively. Time to target international normalized ratio (INR), time in therapeutic range, occurrence of bleeding/thromboembolic events, and cost of bridging with enoxaparin were assessed for both groups.

Results

Target INR was achieved earlier in the 5 mg group than in the 3 mg group (p = 0.033), with a mean ± SD of 5.3 ± 2.0 and 6.6 ± 2.0, respectively (95% confidence interval of the mean difference 1.022–1.890). Bleeding events did not differ significantly between the two groups. The cost of enoxaparin consumption per patient was significantly higher in the 3 mg group versus the 5 mg group (p = 0.002).

Conclusions

The initiation of warfarin at a 5 mg dose in MVR patients was more efficacious than the 3 mg dose in terms of time to reach the target INR. Moreover, the cost of enoxaparin bridging was significantly reduced with a 5 mg warfarin initiation dose. Bleeding events were comparable.

ClinicalTrials.gov ID

NCT04235569, 22 January 2020.

Effects of genetic polymorphism of drug-metabolizing enzymes on the plasma concentrations of antiepileptic drugs in Chinese population

As a chronic brain disease, epilepsy affects ~50 million people worldwide. The traditional antiepileptic drugs (AEDs) are widely applied but showing various problems. Although the new AEDs have partially solved the problems of traditional AEDs, the current clinical application of traditional AEDs are not completely replaced by new drugs, particularly due to the large individual differences in drug plasma concentrations and narrow therapeutic windows among patients. Therefore, it is still clinically important to continue to treat patients using traditional AEDs with individualized therapeutic plans. To date, our understanding of the molecular and genetic mechanisms regulating plasma concentrations of AEDs has advanced rapidly, expanding the knowledge on the effects of genetic polymorphisms of genes encoding drug-metabolizing enzymes on the plasma concentrations of AEDs. It is increasingly imperative to summarize and conceptualize the clinical significance of recent studies on individualized therapeutic regimens. In this review, we extensively summarize the critical effects of genetic polymorphisms of genes encoding drug-metabolizing enzymes on the plasma concentrations of several commonly used AEDs as well as the clinical significance of testing genotypes related to drug metabolism on individualized drug dosage. Our review provides solid experimental evidence and clinical guidance for the therapeutic applications of these AEDs.

From Pharmacogenetics to Pharmaco-Omics:Milestones and Future Directions

The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.

Nine-gene pharmacogenomics profile service: The Mayo Clinic experience

PURPOSE

The Pharmacogenomics (PGx) Profile Service was a proof-of-concept project to implement PGx in patient care at Mayo Clinic.

METHODS

Eighty-two healthy individuals aged 18 and older underwent genotyping of CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLCO1B1, HLA-B*58:01, and VKORC1. A PGx pharmacist was involved in ordering, meeting with patients, interpreting, reviewing, and documenting results.

RESULTS

Ninety three percent were CYP1A2 rapid metabolizers, 92% CYP3A4 normal metabolizers, and 88% CYP3A5 poor metabolizers; phenotype frequencies for CYP2C19 and CYP2D6 varied. Seventy-three percent had normal functioning SLCO1B1 transporter, 4% carried the HLA-B*58:01 risk variant, and 35% carried VKORC1 and CYP2C9 variants that increased warfarin sensitivity.

CONCLUSION

Pre-emptive PGx testing offered medication improvement opportunity in 56% of participants for commonly used medications. A collaborative approach involving a PGx pharmacist integrated within a clinical practice with regards to utility of PGx results allowed for implementation of the PGx Profile Service.

KEY POINTS

The Mayo Clinic PGx (PGx) Profile Service was a proof-of-concept project to utilize PGx testing as another clinical tool to enhance medication selection and decrease serious adverse reactions or medication failures. Over one-half of participants in the pilot using the PGx Profile Service were predicted to benefit from pre-emptive PGx testing to guide pharmacotherapy. PGx pharmacists played a crucial role in the PGx Profile Service by educating participants, identifying medication-gene interactions, and providing evidence-based (CPIC and DPWG) PGx recommendations for past, current, and future medication us.

Electrochemical Sensor for the Direct Determination of Warfarin in Blood

Detecting warfarin levels in the blood is of critical importance in anticoagulant therapy because it is imperative that the concentration of the drug is maintained within a specific range. In this paper, we present a proof-of-concept of a novel sensing device based on ion-selective electrode (ISE) technology for the direct detection of warfarin in blood samples without any sample pretreatment. We used tetradodecylammonium chloride (TDDA) as an ion-exchanger to fabricate an ion-selective membrane. The ISE we developed showed high sensitivity, with a limit of detection (LOD) of 1.25 × 10−7 M and 1.4 × 10−5 M for detecting warfarin in buffer and blood, respectively. The sensor also exhibited promising selectivity in identifying the presence of various ions including chloride and salicylate, the most abundant ions in blood with a calibration slope of 58.8 mV/dec. We envision combining the ISE with a microfluidic system and a simple potentiometer to produce a sensitive, selective, and portable point-of-care testing device for monitoring the level of warfarin in patients’ blood during treatment.

Systematic review of warfarin-induced skin necrosis case reports and secondary analysis of factors associated with mortality

OBJECTIVE

Warfarin-induced skin necrosis (WSN) is a rare (0.0.1%-0.1%) and severe adverse reaction. The clinical characteristics of this reaction and its mortality rate have not been explored in a large population. Therefore, we present the case of a Peruvian patient who developed WSN and perform a systematic review of case reports of WSN.

METHODS

A systematic search was performed using the Pubmed/Medline, Scopus, Web of Science and Embase databases. Patient clinical data were collected and extracted from every case report. Furthermore, we analysed the factors associated with mortality because of WSN using the Poisson regression model with robust variations, obtaining risk ratios (RR) and their respective confidence intervals (95% CI).

RESULTS

We identified 90 case reports that included a total of 111 patients with WSN (mean age 52.5 years), 20.72% of whom died of complications because of WSN. Being male (RR: 2.87; 95% CI 1.21-6.83) and having three or more affected regions (RR: 6.81; 95% CI 2.62-17.74) were associated with an increased risk of death caused by WSN.

CONCLUSION

This systematic review identified 90 case reports of WSN with three or more affected body regions. Male sex was associated with an increased risk of death. Further studies are needed to analyse and confirm these results.

Race and Drug Toxicity: A Study of Three Cardiovascular Drugs with Strong Pharmacogenetic Recommendations

The Clinical Pharmacogenetics Implementation Consortium (CPIC^®) establishes evidence-based guidelines for utilizing pharmacogenetic information for certain priority drugs. Warfarin, clopidogrel and simvastatin are cardiovascular drugs that carry strong prescribing guidance by CPIC. The respective pharmacogenes for each of these drugs exhibit considerable variability amongst different ethnic/ancestral/racial populations. Race and ethnicity are commonly employed as surrogate biomarkers in clinical practice and can be found in many prescribing guidelines. This is controversial due to the large variability that exists amongst different racial/ethnic groups, lack of detailed ethnic information and the broad geographic categorization of racial groups. Using a retrospective analysis of electronic health records (EHR), we sought to determine the degree to which self-reported race/ethnicity contributed to the probability of adverse drug reactions for these drugs. All models used individuals self-reporting as White as the comparison group. The majority of apparent associations between different racial groups and drug toxicity observed in the "race only" model failed to remain significant when we corrected for covariates. We did observe self-identified Asian race as a significant predictor (p = 0.016) for warfarin hemorrhagic events in all models. In addition, patients identifying as either Black/African-American (p = 0.001) or Other/Multiple race (p = 0.019) had a lower probability of reporting an adverse reaction than White individuals while on simvastatin even after correcting for other covariates. In both instances where race/ethnicity was predictive of drug toxicity (i.e., warfarin, simvastatin), the findings are consistent with the known global variability in the pharmacogenes described in the CPIC guidelines for these medications. These results confirm that the reliability of using self-identified race/ethnic information extracted from EHRs as a predictor of adverse drug reactions is likely limited to situations where the genes influencing drug toxicity display large, distinct ethnogeographic variability.

A systems omics-based approach to decode substance use disorders and neuroadaptations

Substance use disorders (SUDs) are a group of neuropsychiatric conditions manifesting due to excessive dependence on potential drugs of abuse such as psychostimulants, opioids including prescription opioids, alcohol, inhalants, etc. Experimental studies have generated enormous data in the area of SUDs, but outcomes from such data have remained largely fragmented. In this review, we attempt to coalesce these data points providing an important first step towards our understanding of the etiology of SUDs. We propose and describe a 'core addictome' pathway that behaves central to all SUDs. Besides, we also have made some notable observations paving way for several hypotheses; MECP2 behaves as a master switch during substance use; five distinct gene clusters were identified based on respective substance addiction; a central cluster of genes serves as a hub of the addiction pathway connecting all other substance addiction clusters. In addition to describing these findings, we have emphasized the importance of some candidate genes that are of substantial interest for further investigation and serve as high-value targets for translational efforts.

Lack of Major Involvement of Common CYP2C Gene Polymorphisms in the Risk of Developing Cross-Hypersensitivity to NSAIDs

Cross-hypersensitivity to non-steroidal anti-inflammatory drugs (NSAIDs) is a relatively common, non-allergic, adverse drug event triggered by two or more chemically unrelated NSAIDs. Current evidence point to COX-1 inhibition as one of the main factors in its etiopathogenesis. Evidence also suggests that the risk is dose-dependent. Therefore it could be speculated that individuals with impaired NSAID biodisposition might be at increased risk of developing cross-hypersensitivity to NSAIDs. We analyzed common functional gene variants for CYP2C8, CYP2C9, and CYP2C19 in a large cohort composed of 499 patients with cross-hypersensitivity to NSAIDs and 624 healthy individuals who tolerated NSAIDs. Patients were analyzed as a whole group and subdivided in three groups according to the main enzymes involved in the metabolism of the culprit drugs as follows: CYP2C9, aceclofenac, indomethacin, naproxen, piroxicam, meloxicam, lornoxicam, and celecoxib; CYP2C8 plus CYP2C9, ibuprofen and diclofenac; CYP2C19 plus CYP2C9, metamizole. Genotype calls ranged from 94 to 99%. No statistically significant differences between patients and controls were identified in this study, either for allele frequencies, diplotypes, or inferred phenotypes. After patient stratification according to the enzymes involved in the metabolism of the culprit drugs, or according to the clinical presentation of the hypersensitivity reaction, we identified weak significant associations of a lower frequency (as compared to that of control subjects) of CYP2C8*3/*3 genotypes in patients receiving NSAIDs that are predominantly CYP2C9 substrates, and in patients with NSAIDs-exacerbated cutaneous disease. However, these associations lost significance after False Discovery Rate correction for multiple comparisons. Taking together these findings and the statistical power of this cohort, we conclude that there is no evidence of a major implication of the major functional CYP2C polymorphisms analyzed in this study and the risk of developing cross-hypersensitivity to NSAIDs. This argues against the hypothesis of a dose-dependent COX-1 inhibition as the main underlying mechanism for this adverse drug event and suggests that pre-emptive genotyping aiming at drug selection should have a low practical utility for cross-hypersensitivity to NSAIDs.

Influence of NQO1 Polymorphisms on Warfarin Maintenance Dose: A Systematic Review and Meta-Analysis (rs1800566 and rs10517)

This meta-analysis was conducted to analyze the effect of NQO1 polymorphism on the warfarin maintenance dosage. Using strict inclusion and exclusion criteria, we searched PubMed, EMBASE, and the Cochrane Library for eligible studies published prior to July 7, 2021. The required data were extracted, and experts were consulted when necessary. Review Manager Version 5.4 software was used to analyze the relationship between NQO1 polymorphisms and the warfarin maintenance dosage. Four articles involving 757 patients were included in the meta-analysis. Patients who were NQO1 rs10517 G carriers (AG carriers or GG carriers) required a 48% higher warfarin maintenance dose than those who were AA carriers. Patients with NQO1 rs1800566 CT carriers required a 13% higher warfarin dose than those who were CC carriers, with no associations observed with the other comparisons of the NQO1 rs1800566 genotypes. However, the results obtained by comparing the NQO1 rs1800566 genotypes require confirmation, as significant changes in the results were found in sensitivity analyses. Our meta-analysis suggests that the NQO1 rs10517and NQO1 rs1800566 variant statuses affect the required warfarin maintenance dose.

Predicting Range of Initial Warfarin Dose Based on Pharmacometabolomic and Genetic Inputs

Anticoagulation response to warfarin during the initial stage of therapy varies among individuals. In this study, we aimed to combine pharmacometabolomic and pharmacogenetic data to predict interindividual variation in warfarin response, and, on this basis, suggest an initial daily dose range. The baseline metabolic profiles, genotypes, and clinical information of 160 patients with heart valve disease served as the variables of the function of the last international normalized ratio measured before a patient's discharge (INR_day7 ) to screen for potential biomarkers. The partial least-squares model showed that two baseline metabolites (uridine and guanosine), one single-nucleotide variation (VKORC1), and four clinical parameters (weight, creatinine level, amiodarone usage, and initial daily dose) had good predictive power for INR_day7 (R²  = 0.753 for the training set, 0.643 for the test set). With these biomarkers, a machine learning algorithm (two-dimensional linear discriminant analysis-multinomial logit model) was used to predict the subgroups with extremely warfarin-sensitive or less warfarin-sensitive patients with a prediction accuracy of 91% for the training set and 90% for the test set, indicating that individual responses to warfarin could be effectively predicted. Based on this model, we have successfully designed an algorithm,"IniWarD," for predicting an effective dose range in the initial 7-day warfarin therapy. The results indicate that the daily dose range suggested by the IniWarD system is more appropriate than that of the conventional genotype-based method, and the risk of bleeding or thrombus due to warfarin could thus be avoided.

Edoxaban in Cardiovascular Disease Management: Review

In the past decade, direct oral anticoagulants (DOACs) have transformed the world of anti-thrombotic therapy. Edoxaban is the most recently approved DOAC. Though intended for use primarily in stroke prevention, it has found applications in various other conditions including thromboembolic and peripheral arterial disease. This review aims to provide a detailed outline of the growing indications, evidence for use in special populations, pharmacogenetics, and side effect profile of edoxaban.

Performance Evaluation of Warfarin Dose Prediction Algorithms and Effects of Clinical Factors on Warfarin Dose in Chinese Patients

BACKGROUND

The clinical utility of warfarin dose prediction algorithms remains controversial, our purpose is to evaluate the performance of warfarin dose prediction algorithms and the effects of clinical factors on warfarin dose in Chinese patients.

METHODS

Clinical data of 217 patients who received warfarin treatment were used to assess 6 warfarin dose prediction algorithms (OHNO, IWPC [International Warfarin Pharmacogenetics Consortium], HUANG, KIM, BRESS, and MIAO). The predicted dose (PD) was compared with the warfarin optimal dose (WOD, defined as the dose that maintains the international normalized ratio within the target range of 2.0-3.0). A multiple regression analysis with WOD as the dependent variable was performed to evaluate the effects of clinical factors on warfarin dose.

RESULTS

The mean absolute error analysis ranked the predictive accuracies of the algorithms as OHNO > IWPC > HUANG > KIM > BRESS > MIAO. Stratified analysis indicated that HUANG most accurately predicted that patients required lower WODs (≤3 mg/d), whereas OHNO was the most effective in predicting medium WODs (3-5 mg/d). KIM was effective in predicting high WODs (>5 mg/d). Multiple linear regression analysis showed that VKORC1 (rs9923231) and body mass index were significantly positively correlated with WOD, whereas concurrent atrial fibrillation status, CYP2C9*3 (rs1057910), and sex were significantly negatively correlated with WOD.

CONCLUSIONS

In Chinese patients, OHNO should be given priority during the prediction and selection of warfarin dose. When using OHNO to predict warfarin dose (≤3 mg/d or >5 mg/d), HUANG or KIM algorithms can provide precise predictions. At the same time, physicians should pay close attention to clinical factors, such as VKORC1 (rs9923231), concurrent atrial fibrillation status, CYP2C9*3 (rs1057910), body mass index, and sex, to improve warfarin dose adjustment strategies in Chinese patients.

Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine

Response to medications, the principal treatment modality for acute and chronic diseases, is highly variable, with 40-70% of patients exhibiting lack of efficacy or adverse drug reactions. With ~ 15-30% of this variability explained by genetic variants, pharmacogenomics has become a valuable tool in our armamentarium for optimizing treatments and is poised to play an increasing role in clinical care. This review presents the progress made toward elucidating genetic underpinnings of drug response including discovery of race/ancestry-specific pharmacogenetic variants and discusses the current evidence and evidence framework for actionability. The review is framed in the context of changing demographics and evolving views related to race and ancestry. Finally, it highlights the vital role played by cohort studies in elucidating genetic differences in drug response across race and ancestry and the informal collaborations that have enabled the field to bridge the "bench to bedside" translational gap.

Genetic Variants in PTGS1 and NOS3 Genes Increase the Risk of Upper Gastrointestinal Bleeding: A Case-Control Study

Objective: To assess the association between PTGS1 and NOS3 variant alleles and the risk to develop upper gastrointestinal bleeding (UGIB) secondary to complicated peptic disease. Methods: A case-control study was conducted in a Brazilian complex hospital from July 2016 to March 2020. Case: Patients with UGIB diagnosis. Control: Patients admitted for surgery not related to gastrointestinal disorders. Variables: UGIB (outcome), genetic variants in PTGS1 and NOS3 genes (independent), and sex, age, schooling, ethnicity, previous history of gastrointestinal disorders, Helicobacter pylori serology, comorbidity, drug therapy, and lifestyle (confounding). The single-nucleotide polymorphisms (SNPs) of the PTSG1 gene (rs1330344, rs3842787, rs10306114, and rs5788) and NOS3 gene (rs2070744 and rs1799983) were determined using the real-time polymerase chain reaction. Helicobacter pylori serology was determined through the chemiluminescence technique. Logistic regression models were built and deviations of allelic frequencies from Hardy-Weinberg equilibrium were verified. Results: 200 cases and 706 controls were recruited. Carriers of the AG genotype of rs10306114 (OR: 2.55, CI 95%: 1.13-5.76) and CA + AA genotypes of rs5788 (OR: 2.53, CI 95%: 1.14-5.59) were associated with an increased risk for the UGIB development. In nonsteroidal anti-inflammatory drugs (NSAIDs) users, the six variants evaluated modified the magnitude of the risk of UGIB, whereas in low-dose aspirin (LDA) users, an increased risk of UGIB was observed for four of them (rs1330344, rs10306114, rs2070744, and rs1799983). Personal ulcer history (p-value: < 0.001); Helicobacter pylori infection (p-value: < 0.011); NSAIDs, LDA, and oral anticoagulant use (p-value: < 0.001); and alcohol intake (p-value: < 0.001) were also identified as independent risk factors for UGIB. Conclusion: This study presents two unprecedented analyses within the scope of the UGIB (rs10306114 and rs2070744), and our findings showing an increased risk of UGIB in the presence of the genetic variants rs10306114 and rs5788, regardless of the drug exposure. Besides, the presence of the evaluated variants might modify the magnitude of the risk of UGIB in LDA/NSAIDs users. Therefore, our data suggest the need for a personalized therapy and drug use monitoring in order to promote patient safety.

Genetic Associations With Stable Warfarin Dose Requirements in Han Chinese Patients

ABSTRACT

Warfarin is a commonly prescribed anticoagulant for valvular heart disease that plays an important role in clinical management to prevent thrombotic events. In this study, we aim to perform a comprehensive study to investigate the genetic biomarkers of stable warfarin dose in the Han Chinese population. We performed an integrative study on 211 Han Chinese patients with valvular heart disease. A total of 40 single nucleotide polymorphisms (SNPs) in 10 important genes (CYP2C9, VKORC1, ABCB1, CYP4F2, APOE, PROC, GGCX, EPHX1, CALU, and SETD1A) which are involved in the warfarin metabolic pathway and equilibrium of coagulation and anticoagulation were selected. We applied MassARRAY technology to genotype the 40 SNPs identified in these Han Chinese patients. Our results showed that 13 SNPs on 6 genes (CYP2C9, VKORC1, ABCB1, PROC, EPHX1, and SETD1A) were associated with the individual stable warfarin dose. Two VKORC1 SNPs (rs9934438 and rs2359612) were the strongest genetic factors determining warfarin dose requirements (P = 8 × 10-6 and 9 × 10-6, respectively). Rs4889599 in SETD1A was first reported to be associated with warfarin dose at a significant level of 0.001 in our study (Padjust = 0.040 after Bonferroni correction). We discovered that genetic variants in CYP2C9, VKORC1, ABCB1, PROC, EPHX1, and SETD1A may affect the stable warfarin dose requirement in Han Chinese patients with valvular disease. The discovery of these potential genetic markers will facilitate the development of advanced personalized anticoagulation therapy in Han Chinese patients.

Planning and Conducting a Pharmacogenetics Association Study

Pharmacogenetics (PGx) association studies are used to discover, replicate, and validate the association between an inherited genotype and a treatment outcome. The objective of this tutorial is to provide trainees and novice PGx researchers with an overview of the major decisions that need to be made when designing and conducting a PGx association study. The first critical decision is to determine whether the objective of the study is discovery, replication, or validation. Next, the researcher must identify a patient cohort that has all of the data necessary to conduct the intended analysis. Then, the investigator must select and define the treatment outcome, or phenotype, that will be analyzed. Next, the investigator must determine what genotyping approach and genetic data will be included in the analysis. Finally, the association between the genotype and phenotype is tested using some statistical analysis methodology. This tutorial is divided into five sections; each section describes commonly used approaches and provides suggestions and resources for designing and conducting a PGx association study. Successful PGx association studies are necessary to discover and validate associations between inherited genetic variation and treatment outcomes, which enable clinical translation to improve efficacy and reduce toxicity of treatment.

Biomarkers for Antiplatelet Therapies in Acute Ischemic Stroke: A Clinical Review

Stroke is one of the world's leading causes of disability and death. Antiplatelet agents are administered to acute ischemic stroke patients as secondary prevention. Clopidogrel involves biotransformation by cytochrome P450 (CYP) enzymes into an active metabolite, and single nucleotide polymorphisms (SNPs) can influence the efficacy of this biotransformation. Despite the therapeutic advantages of aspirin, there is significant inter-individual heterogeneity in response to this antiplatelet drug. In this clinical review, the recent advances in the biomarkers of antiplatelet agents in acute ischemic stroke are discussed. The studies reviewed herein highlight the clinical relevance of antiplatelet resistance, pharmacotherapy of antiplatelet agents predicting drug response, strategies for identifying aspirin resistance, pharmacogenetic variants of antiplatelet agents, miRNAs, and extracellular vesicles (EVs) as biomarkers toward the personalized approach in the management of acute ischemic stroke. The precise pathways contributing to antiplatelet resistance are not very well known but are presumably multi-factorial. It is essential to understand the clinical relevance of clopidogrel and aspirin-related single nucleotide polymorphism (SNPs) as potential predictive and prognostic biomarkers. Prasugrel is a next-generation antiplatelet agent that prevents ADP-platelet activation by binding irreversibly to P2Y12 receptor. There are sporadic reports of prasugrel resistance and polymorphisms in the Platelet endothelial aggregation receptor-1 (PEAR1) that may contribute to a change in the pharmacodynamics response. Ticagrelor, a direct-acting P2Y12-receptor antagonist, is easily absorbed and partly metabolized to major AR-C124910XX metabolite (ARC). Ticagrelor's primary active metabolite, ARC124910XX (ARC), is formed via the most abundant hepatic cytochrome P450 (CYP) enzyme, CYP3A4, and CYP3A5. The integration of specific biomarkers, genotype as well as phenotype-related data in antiplatelet therapy stratification in patients with acute ischemic stroke will be of great clinical significance and could be used as a guiding tool for more effective, personalized therapy.

Han Chinese specific cytochrome P450 polymorphisms and their impact on the metabolism of anti-hypertensive drugs with adrenoreceptor blocking properties

Introduction: Cytochrome P450 (CYP) is a monooxygenase superfamily mediating the elimination of anti-hypertensive drugs. Polymorphisms of CYP would lead to differential drug efficacy. Building relationships between genotype and phenotype will benefit individual medical treatment of hypertension.Areas covered: The review systematically summarizes the polymorphisms of four CYPs (CYP2C9, CYP2C19, CYP2D6, and CYP3A4) concentrated distributed in the Han Chinese population. Moreover, the activity of variants on metabolizing anti-hypertensive drugs are reviewed, especially drugs with adrenoceptor blocking properties, as well as their clinical relevancies.Expert opinion: The polymorphisms of CYP can cause stratification in drug exposure of antihypertensive drugs. Although the clinical relevance has been built partially, the translational medicine still lacks reliable data support. Furthermore, the studies have demonstrated that even the same CYP variant will exhibit different catalytic capability for different drugs, which is another obstacle to hinder its application. With the deepening of multiomics research and structural biology, nucleotide polymorphisms can be combined with transcriptome, proteome, metabolome and molecular structure analyses to study the susceptibility to hypertension and drug efficacy. A complete data chain would be further estabolished by combining studies of pharmacokinetics-pharmacodynamics, which can effectively promote the precise application of anti-hypertensive drugs.

Retention and molecular-recognition mechanisms of molecularly imprinted polymers for warfarin derivatives and their application for the determination of warfarin in human serum

Monodisperse molecularly imprinted polymers (MIPs) for warfarin (WF), 4'-chlorowarfarin (CWF), 4'-bromowarfarin (BWF), 4'-nitrowarfarin (NWF) and 4'-methylwarfarin (MWF) (MIP_WF, MIP_CWF, MIP_BWF, MIP_NWF and MIP_MWF, respectively) were prepared using 4-vinylpyridine (4-VPY) and ethylene glycol dimethacrylate as a functional monomer and crosslinker, respectively, by multi-step swelling and polymerization. The retention and molecular-recognition properties of those MIPs were evaluated in HILIC, and reversed- and normal-phase modes. According to ¹H NMR studies, one-to-three complex formation of one WF or CWF molecule with three 4-VPY molecules occurred. Via computational approaches, the intermolecular interaction modes and energies between WF derivatives and 4-VPYs were evaluated by semi-empirical quantum chemistry methods and density functional theory calculations. Three major possible hydrogen bonding interaction modes were identified: the interactions between the 4-hydroxy group, α-proton (methylene C-H) and α-proton (methyl C-H) of the WF derivative and the nitrogen atoms of 4-VPYs. In HILIC and normal-phase modes, the interaction energies showed satisfactory correlations with the retention factors of the WF derivatives. In reversed-phase mode, the retention factors of the WF derivatives were described by the hydrophobicity and the acidity of the 4-hydroxy groups of the WF derivatives. These results demonstrate that three hydrogen bonding interactions in HILIC and normal-phase modes, and hydrogen bonding or ionic interactions and hydrophobic interactions in reversed-phase mode play important roles in the retention and molecular-recognition of the WF derivatives on MIPs. Furthermore, MIP_BWF was successfully applied to the determination of WF in human serum by column-switching LC with high accuracy, precision and selectivity and without template-leakage problems.

S-warfarin limited sampling strategy with a population pharmacokinetic approach to estimate exposure and cytochrome P450 (CYP) 2C9 activity in healthy adults

PURPOSE

S-warfarin is used to phenotype cytochrome P450 (CYP) 2C9 activity. This study evaluated S-warfarin limited sampling strategy with a population pharmacokinetic (PK) approach to estimate CYP2C9 activity in healthy adults.

METHODS

In 6 previously published studies, a single oral dose of warfarin 10 mg was administered alone or with a CYP2C9 inducer to 100 healthy adults. S-warfarin concentrations were obtained from adults during conditions when subjects were not on any prescribed medications. A population PK model was developed using non-linear mixed effects modeling. Limited sampling models (LSMs) using single- or 2-timepoint concentrations were compared with full PK profiles from intense sampling using empiric Bayesian post hoc estimations of S-warfarin AUC derived from the population PK model. Preset criterion for LSM selection and validation were a correlation coefficient (R²) >0.9, relative percent mean prediction error (%MPE) >-5 to <5%, relative percent mean absolute error (%MAE) ≤ 10%, and relative percent root mean squared error (%RMSE) ≤ 15%.

RESULTS

S-warfarin concentrations (n=2540) were well described with a two-compartment model. Mean apparent oral clearance was 0.56 L/hr and volume of distribution was 35.5 L. Clearance decreased 33% with the CYP2C9 *3 allele and increased 42% with lopinavir/ritonavir co-administration. During CYP2C9 constitutive conditions, LSMs at 48 hr and at 72 hr as well as 2-timepoint LSMs were within acceptable limits for R², %MPE, %MAE, and %RMSE. During CYP2C9 induction, S-warfarin LSMs had unacceptable %MPE, %MAE, and %RMSE.

CONCLUSIONS

Phenotyping studies with S-warfarin in healthy subjects can utilize a single- and/or a 2-timepoint LSM with a population PK approach to estimate constitutive CYP2C9 activity.

Pharmacogenetics of Anticoagulation and Clinical Events in Warfarin-Treated Patients: A Register-Based Cohort Study with Biobank Data and National Health Registries in Finland

Purpose

To assess the association between VKORC1 and CYP2C9 variants and the incidence of adverse drug reactions in warfarin-treated patients in a real-world setting.

Materials and Methods

This was a register-based cohort study (PreMed) linking data from Finnish biobanks, national health registries and patient records between January 1st 2007 and June 30th 2018. The inclusion criteria were: 1) ≥18 years of age, 2) CYP2C9 and VKORC1 genotype information available, 3) a diagnosis of a cardiovascular disease, 4) at least one warfarin purchase, 5) regular INR tests. Eligible individuals were divided into two warfarin sensitivity groups; normal responders, and sensitive and highly sensitive responders based on their VKORC1 and CYP2C9 genotypes. The incidences of clinical events were compared between the groups using Cox regression models.

Results

The cohort consisted of 2508 participants (45% women, mean age of 69 years), of whom 65% were categorized as normal responders and 35% sensitive or highly sensitive responders. Compared to normal responders, sensitive and highly sensitive responders had fewer INR tests below 2 (median: 33.3% vs 43.8%, 95% CI: −13.3%, −10.0%) and more above 3 (median: 18.2% vs 6.7%, 95% Cl: 8.3%, 10.8%). The incidence (per 100 patient-years) of bleeding outcomes was 5.4 for normal responders and 5.6 for the sensitive and highly sensitive responder group (HR=1.03, 95% CI: 0.74, 1.44). The incidence of thromboembolic outcomes was 4.9 and 7.8, respectively (HR=1.48, 95% CI: 1.08, 2.03).

Conclusion

In a real-world setting, genetically sensitive and highly sensitive responders to warfarin had more high INR tests and required a lower daily dose of warfarin than normal responders. However, the risk for bleeding events was not increased in sensitive and highly sensitive responders. Interestingly, the risk of thromboembolic outcomes was lower in normal responders compared to the sensitive and highly sensitive responders.

Trial Registration

NCT04001166.

Genetic polymorphisms associated with upper gastrointestinal bleeding: a systematic review

Non-variceal upper gastrointestinal bleeding (non-variceal UGIB) is a frequent and severe adverse drug reaction. Idiosyncratic responses due to genetic susceptibility to non-variceal UGIB has been suggested. A systematic review was conducted to assess the association between genetic polymorphisms and non-variceal UGIB. Twenty-one publications and 7134 participants were included. Thirteen studies evaluated genetic polymorphism in patients exposed to non-steroidal anti-inflammatory drugs, low-dose aspirin, and warfarin. Eight studies present at least one methodological problem. Only six studies clearly defined that the outcome evaluated was non-variceal UGIB. Genetic polymorphisms involved in platelet activation and aggregation, angiogenesis, inflammatory process, and drug metabolism were associated with risk of non-variceal UGIB (NOS3, COX-1; COX-2; PLA2G7; GP1BA; GRS; IL1RN; F13A1; CDKN2B-AS1; DPP6; TBXA2R; TNF-alpha; VKORC1; CYP2C9; and AGT). Further well-designed studies are needed (e.g., clear restriction to non-variceal UGIB; proper selection of participants; and adjustment of confounding factors) to provide strong evidence for pharmacogenetic and personalized medicine.