Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update

The need to diversify genomic studies: Insights from Andean highlanders and Amazonians

More globally diverse perspectives are needed in genomic studies and precision medicine practices on non-Europeans. Here, we illustrate this by discussing the distribution of clinically actionable genetic variants involved in drug response in Andean highlanders and Amazonians, considering their environment, history, genetic structure, and historical biases in the perception of biological diversity of Native Americans.

Leveraging QSP Models for MIPD: A Case Study for Warfarin/INR

Warfarin dosing remains challenging due to substantial inter-individual variability, which can lead to unsafe or ineffective therapy with standard dosing. Model-informed precision dosing (MIPD) can help individualize warfarin dosing, requiring the selection of a suitable model. For models developed from clinical data, the dependence on the study design and population raises questions about generalizability. Quantitative system pharmacology (QSP) models promise better extrapolation abilities; however, their complexity and lack of validation on clinical data raise questions about applicability in MIPD. We have previously derived a mechanistic warfarin/international normalized ratio (INR) model from a blood coagulation QSP model. In this article, we evaluated the predictive performance of the warfarin/INR model in the context of MIPD using an external dataset with INR data from patients starting warfarin treatment. We assessed the accuracy and precision of model predictions, benchmarked against an empirically based reference model. Additionally, we evaluated covariate contributions and assessed the predictive performance separately in the more challenging outpatient data. The warfarin/INR model performed comparably to the reference model across various measures despite not being calibrated with warfarin initiation data. Including CYP2C9 and/or VKORC1 genotypes as covariates improved the prediction quality of the warfarin/INR model, even after assimilating 4 days of INR data. The outpatient INR exhibited higher unexplained variability, and predictions slightly exceeded observed values, suggesting that model adjustments might be necessary when transitioning from an inpatient to an outpatient setting. Overall, this research underscores the potential of QSP-derived models for MIPD, offering a complementary approach to empirical model development.

Patterns of pharmacogenetic variation in nine biogeographic groups

Frequencies of pharmacogenetic (PGx) variants are known to differ substantially across populations but much of the available PGx literature focuses on one or a few population groups, often defined in nonstandardized ways, or on a specific gene or variant. Guidelines produced by the Clinical Pharmacogenetic Implementation Consortium (CPIC) provide consistent methods of literature extraction, curation, and reporting, including comprehensive curation of allele frequency data across nine defined "biogeographic groups" from the PGx literature. We extracted data from 23 CPIC guidelines encompassing 19 genes to compare the sizes of the populations from each group and allele frequencies of altered function alleles across groups. The European group was the largest in the curated literature for 16 of the 19 genes, while the American and Oceanian groups were the smallest. Nearly 200 alleles were detected in nonreference groups that were not reported in the largest (reference) group. The genes CYP2B6 and CYP2C9 were more likely to have higher frequencies of altered function alleles in nonreference groups compared to the reference group, while the genes CYP4F2, DPYD, SLCO1B1, and UGT1A1 were less likely to have higher frequencies in nonreference groups. PGx allele frequencies and function differ substantially across nine biogeographic groups, all but two of which are underrepresented in available PGx data. Awareness of these differences and increased efforts to characterize the breadth of global PGx variation are needed to ensure that implementation of PGx-guided drug selection does not further widen existing health disparities among populations currently underrepresented in PGx data.

Insights into pharmacogenetics, drug-gene interactions, and drug-drug-gene interactions

This review explores genetic contributors to drug interactions, known as drug-gene and drug-drug-gene interactions (DGI and DDGI, respectively). This article is part of a mini-review issue led by the International Society for the Study of Xenobiotics (ISSX) New Investigators Group. Pharmacogenetics (PGx) is the study of the impact of genetic variation on pharmacokinetics (PK), pharmacodynamics (PD), and adverse drug reactions. Genetic variation in pharmacogenes, including drug metabolizing enzymes and drug transporters, is common and can increase the risk of adverse drug events or contribute to reduced efficacy. In this review, we summarize clinically actionable genetic variants, and touch on methodologies such as genotyping patient DNA to identify genetic variation in targeted genes, and deep mutational scanning as a high-throughput in vitro approach to study the impact of genetic variation on protein function and/or expression in vitro. We highlight the utility of physiologically based pharmacokinetic (PBPK) models to integrate genetic and chemical inhibitor and inducer data for more accurate human PK simulations. Additionally, we analyze the limitations of historical ethnic descriptors in pharmacogenomics research. Altogether, the work herein underscores the importance of identifying and understanding complex DGI and DDGIs with the intention to provide better treatment outcomes for patients. We also highlight current barriers to wide-scale implementation of PGx-guided dosing as standard or care in clinical settings.

Implementation of pharmacogenomics: Where are we now?

Pharmacogenomics (PGx), examining the effect of genetic variation on interpatient variation in drug disposition and response, has been widely studied for several decades. However, as cost, as well as turnaround time associated with PGx testing, has significantly improved, the use of PGx in the clinical setting has been gaining momentum. Nevertheless, challenges have emerged in the broader clinical implementation of PGx. In this review, we will outline current models of PGx delivery and methodologies of evaluation, and discuss clinically relevant PGx tests and associated medications. Additionally, we will describe our approach for the broad implementation of pre-emptive DPYD genotyping in patients taking fluoropyrimidines in Ontario, Canada, as an example of clinically actionable PGx testing with sufficient clinical evidence of patient benefit that can become a new standard of patient care. We will highlight challenges associated with PGx testing, including a lack of diversity in PGx studies as well as general limitations that impact the broad adoption of PGx testing. Lastly, we examine the future of PGx, discussing new clinical targets, methodologies and analysis approaches.

Therapeutic drug monitoring of osimertinib in EGFR mutant non-small cell lung cancer by dried blood spot and plasma collection: A pilot study

AIMS

Therapeutic drug monitoring (TDM) has led to significant improvements in individualized medical care, although its implementation in oncology has been limited to date. Tyrosine kinase inhibitors (TKIs) are a group of therapies for which TDM has been suggested. Osimertinib is one such therapy used in the treatment of epidermal growth factor receptor (EGFR) mutation-driven lung cancer. Herein, we describe a prospective pilot study involving 21 patients on osimertinib primarily as a preliminary evaluation of drug levels in a real-world setting.

METHODS

Concentrations of the drug and its primary metabolites were measured with a validated liquid chromatography-mass spectrometry (LC-MS) assay across serial timepoints. As part of this study, inter-individual variability by dose and ethnicity as well as intra-individual variability across timepoints are explored. Furthermore, we attempted to validate dried blood spot (DBS)-based quantitation as an accurate alternative to plasma quantitation.

RESULTS

Successful quantitation of osimertinib and primary metabolites was achieved for our subjects. Compound plasma levels were highly correlated to DBS levels. There was no significant difference in concentrations with ethnicity or dosing or intra-individual variability across timepoints.

CONCLUSIONS

As such, we demonstrate that TDM for osimertinib is practical for future trials. We also validated the use of DBS as an alternative to conventional quantitation for exploration of TDM for osimertinib in larger trials and for other targeted therapies.

Implementation of a pharmacogenetic panel-based test for pharmacotherapy-based supportive care in an adult oncology clinic

The University of Florida Health conducted a pragmatic implementation of a pharmacogenetics (PGx) panel-based test to guide medications used for supportive care prescribed to patients undergoing chemotherapy. The implementation was in the context of a pragmatic clinical trial for patients with non-hematologic cancers being treated with chemotherapy. Patients were randomized to either the intervention arm or control arm and received PGx testing immediately or at the end of the study, respectively. Patients completed the MD Anderson Symptom Inventory (MDASI) to assess quality of life (QoL). A total of 150 patients received PGx testing and enrolled in the study. Clinical decision support and implementation infrastructure were developed. While the study was originally planned for 500 patients, we were underpowered in our sample of 150 patients to test differences in the patient-reported MDASI scores. We did observed a high completion rate (92%) of the questionnaires; however, there were few medication changes (n = 6 in the intervention arm) based on PGx test results. Despite this, we learned several lessons through this pragmatic implementation of a PGx panel-based test in an outpatient oncology setting. Most notably, patients were less willing to undergo PGx testing if the cost of the test exceeded $100. In addition, to enhance PGx implementation success, reoccurring provider education is necessary, clinical decision support needs to appear in a more conducive way to fit in with oncologists' workflow, and PGx test results need to be available earlier in treatment planning.

Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature.

Assessing the Performance of In silico Tools and Molecular Dynamics Simulations for Predicting Pharmacogenetic Variant Impact

The ability of freely available in silico tools to predict the effect of non-synonymous single nucleotide polymorphisms (nsSNPs) in pharmacogenes on protein function is not well defined. We assessed the performance of seven sequence-based (SIFT, PolyPhen2, mutation accessor, FATHMM, PhD-SNP, MutPred2, and SNPs & Go) and five structure-based (mCSM, SDM, DDGun, CupSat, and MAESTROweb) tools in predicting the impact of 118 nsSNPs in the CYP2C19, CYP2C9, CYP2B6, CYP2D6, and DPYD genes with known function (24 normal, one increased, 42 decreased, and 51 no-function). Sequence-based tools had a higher median (IQR) positive predictive value (89% [89-94%] vs. 12% [10-15%], P < 0.001) and lower negative predictive value (30% [24-34%] vs. 90% [80-93%], P < 0.001) than structure-based tools. Accuracy did not significantly differ between sequence-based (59% [37-67%]) and structure-based (34% [23-44%]) tools (P = 0.070). Notably, the no-function CYP2C9*3 allele and decreased function CYP2C9*8 allele were predicted incorrectly as tolerated by 100% of sequenced-based tools and as stabilizing by 60% and 20% of structure-based tools, respectively. As a case study, we performed mutational analysis for the CYP2C9*1, *3 (I359L), and *8 (R150H) proteins through molecular dynamic (MD) simulations using S-warfarin as the substrate. The I359L variant increased the distance of the major metabolic site of S-warfarin to the oxy-ferryl center of CYP2C9, and I359L and R150H caused shifts in the conformation of S-warfarin to a position less favorable for metabolism. These data suggest that MD simulations may better capture the impact of nsSNPs in pharmacogenes than other tools.

Mapping the Pharmacogenetic Landscape in a Ugandan Population: Implications for Personalized Medicine in an Underrepresented Population

Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience widespread polypharmacy. As population-specific genetic studies are crucial to understanding unique genetic profiles and optimizing treatments to reduce medication-related complications in this diverse population, the present study aims to characterize the pharmacogenomics profile of a rural Ugandan population. We analyzed low-pass whole genome sequencing data from 1998 Ugandans to investigate 18 clinically actionable pharmacogenes in this population. We utilized PyPGx to identify star alleles (haplotype patterns) and compared allele frequencies across populations using the Pharmacogenomics Knowledgebase PharmGKB. Clinical interpretations of the identified alleles were conducted following established dosing guidelines. Over 99% of participants displayed actionable phenotypes across the 18 pharmacogenes, averaging 3.5 actionable genotypes per individual. Several variant alleles known to affect drug metabolism (i.e., CYP3A5*1, CYP2B6*9, CYP3A5*6, CYP2D6*17, CYP2D6*29, and TMPT*3C)-which are generally more prevalent in African individuals-were notably enriched in the Ugandan cohort, beyond reported frequencies in other African peoples. More than half of the cohort exhibited a predicted impaired drug response associated with CFTR, IFNL3, CYP2B6, and CYP2C19, and approximately 31% predicted altered CYP2D6 metabolism. Potentially impaired CYP2C9, SLCO1B1, TPMT, and DPYD metabolic phenotypes were also enriched in Ugandans compared with other African populations. Ugandans exhibit distinct allele profiles that could impact drug efficacy and safety. Our findings have important implications for pharmacogenomics in Uganda, particularly with respect to the treatment of prevalent communicable and non-communicable diseases, and they emphasize the potential of pharmacogenomics-guided therapies to optimize healthcare outcomes and precision medicine in Uganda.

Pharmacogenetic guided versus standard warfarin dosing for routine clinical care with its pharmacoeconomic impact: a randomized controlled clinical trial

BACKGROUND

Empirical use of pharmacogenetic test(PGT) is advocated for many drugs, and resource-rich setting hospitals are using the same commonly. The clinical translation of pharmacogenetic tests in terms of cost and clinical utility is yet to be examined in hospitals of low middle income countries (LMICs).

AIM

The present study assessed the clinical utility of PGT by comparing the pharmacogenetically(PGT) guided- versus standard of care(SOC)- warfarin therapy, including the health economics of the two warfarin therapies.

METHODS

An open-label, randomized, controlled clinical trial recruited warfarin-receiving patients in pharmacogenetically(PGT) guided- versus standard of care(SOC)- study arms. Pharmacogenetic analysis of CYP2C9*2(rs1799853), CYP2C9*3(rs1057910) and VKORC1(rs9923231) was performed for patients recruited to the PGT-guided arm. PT(Prothrombin Time)-INR(international normalized ratio) testing and dose titrations were allowed as per routine clinical practice. The primary endpoint was the percent time spent in the therapeutic INR range(TTR) during the 90-day observation period. Secondary endpoints were time to reach therapeutic INR(TRT), the proportion of adverse events, and economic comparison between two modes of therapy in a Markov model built for the commonest warfarin indication- atrial fibrillation.

RESULTS

The study enrolled 168 patients, 84 in each arm. Per-protocol analysis showed a significantly high median time spent in therapeutic INR in the genotype-guided arm(42.85%; CI 21.4-66.75) as compared to the SOC arm(8.8%; CI 0-27.2)(p < 0.00001). The TRT was less in the PG-guided warfarin dosing group than the standard-of-care dosing warfarin group (17.85 vs. 33.92 days) (p = 0.002). Bleeding and thromboembolic events were similar in the two study groups. Lifetime expenditure was ₹1,26,830 in the PGT arm compared to ₹1,17,907 in the SOC arm. The QALY gain did not differ in the two groups(3.9 vs. 3.65). Compared to SOC, the incremental cost-utility ratio was ₹35,962 per QALY gain with PGT test opting. In deterministic and probabilistic sensitivity analysis, the base case results were found to be insensitive to the variation in model parameters. In the cost-effectiveness-acceptability curve analysis, a 90% probability of cost-effectiveness was reached at a willingness-to-pay(WTP) of ₹ 71,630 well below one time GDP threshold of WTP used.

CONCLUSION

Clinical efficacy and the cost-effectiveness of the warfarin pharmacogenetic test suggest its routine use as a point of care investigation for patient care in LMICs.

Clinical versus fixed warfarin dosing and the impact on quality of anticoagulation (The ClinFix trial)

Different dosing strategies exist to initiate warfarin, most commonly fixed warfarin dosing (FWD), clinical warfarin dosing (CWD), and genetic-guided warfarin dosing (GWD). Landmark trials have shown GWD to be superior when compared to FWD in the EU-PACT trial or CWD in the GIFT trial. COAG trial did not show differences between GWD and CWD. We aim to compare the anticoagulation quality outcomes of CWD and FWD. This is a prospective cohort study with a retrospective comparator. Recruited subjects in the CWD (prospective) arm were initiated on warfarin according to the clinical dosing component of the algorithm published in www.warfarindosing.org. The primary efficacy outcome was the percentage time in the therapeutic range (PTTR) from day 3 to 6 till day 28 to 35. The study enrolled 122 and 123 patients in the CWD and FWD, respectively. The PTTR did not differ statistically between CWD and FWD (62.2 ± 26.2% vs. 58 ± 25.4%, p = 0.2). There was also no difference between both arms in the percentage of visits with extreme subtherapeutic international normalized ratio (INR) (<1.5; 15 ± 18.3% vs. 16.8 ± 19.1%, p = 0.44) or extreme supratherapeutic INR (>4; 7.7 ± 14.7% vs. 7.5 ± 12.4%, p = 0.92). We conclude that CWD did not improve the anticoagulation quality parameters compared to the FWD method.

Ancestry, ethnicity, and race: explaining inequalities in cardiometabolic disease

Population differences in cardiometabolic disease remain unexplained. Misleading assumptions over genetic explanations are partly due to terminology used to distinguish populations, specifically ancestry, race, and ethnicity. These terms differentially implicate environmental and biological causal pathways, which should inform their use. Genetic variation alone accounts for a limited fraction of population differences in cardiometabolic disease. Research effort should focus on societally driven, lifelong environmental determinants of population differences in disease. Rather than pursuing population stratifiers to personalize medicine, we advocate removing socioeconomic barriers to receipt of and adherence to healthcare interventions, which will have markedly greater impact on improving cardiometabolic outcomes. This requires multidisciplinary collaboration and public and policymaker engagement to address inequalities driven by society rather than biology per se.

QPGx-CARES: Qatar pharmacogenetics clinical applications and research enhancement strategies

Pharmacogenetic (PGx)-informed medication prescription is a cutting-edge genomic application in contemporary medicine, offering the potential to overcome the conventional "trial-and-error" approach in drug prescription. The ability to use an individual's genetic profile to predict drug responses allows for personalized drug and dosage selection, thereby enhancing the safety and efficacy of treatments. However, despite significant scientific and clinical advancements in PGx, its integration into routine healthcare practices remains limited. To address this gap, the Qatar Genome Program (QGP) has embarked on an ambitious initiative known as QPGx-CARES (Qatar Pharmacogenetics Clinical Applications and Research Enhancement Strategies), which aims to set a roadmap for optimizing PGx research and clinical implementation on a national scale. The goal of QPGx-CARES initiative is to integrate PGx testing into clinical settings with the aim of improving patient health outcomes. In 2022, QGP initiated several implementation projects in various clinical settings. These projects aimed to evaluate the clinical utility of PGx testing, gather valuable insights into the effective dissemination of PGx data to healthcare professionals and patients, and identify the gaps and the challenges for wider adoption. QPGx-CARES strategy aimed to integrate evidence-based PGx findings into clinical practice, focusing on implementing PGx testing for cardiovascular medications, supported by robust scientific evidence. The current initiative sets a precedent for the nationwide implementation of precision medicine across diverse clinical domains.

Genetic polymorphisms and major bleeding risk during vitamin K antagonists treatment: The BLEEDS case-cohort

BACKGROUND

Major bleeding occurs annually in 1%-3% of patients on vitamin K antagonists (VKAs), despite close monitoring. Genetic variants in proteins involved in VKA response may affect this risk.

AIM

To determine the association of genetic variants (cytochrome P450 enzymes 2C9 [CYP2C9] and 4F2 [CYP4F2], gamma-glutamyl carboxylase [GGCX]) with major bleeding in VKA users, separately and combined, including vitamin K epoxide reductase complex subunit-1 (VKORC1).

METHODS

A case-cohort study was established within the BLEEDS cohort, which includes 16,570 patients who initiated VKAs between 2012 and 2014. We selected all 326 major bleeding cases that occurred during 17,613 years of follow-up and a random subcohort of 978 patients. We determined variants in CYP2C9, CYP4F2, GGCX, VKORC1 and evaluated the interaction between variant genotypes. Hazard ratios for major bleeding with 95% confidence intervals (95% CI) were estimated by weighted Cox regression.

RESULTS

Genotype was determined in 256 cases and 783 subcohort members. Phenprocoumon was the most prescribed VKA for both cases and the subcohort (78% and 75%, respectively). Patients with major bleeding were slightly older than subcohort patients. CYP4F2-TT carriership was associated with a 1.6-fold (95% CI 0.9-2.8) increased risk of major bleeding compared with CC-alleles, albeit not statistically significant. For the CYP2C9 and GGCX variants instead, the major bleeding risk was around unity. Carrying at least two variant genotypes in CYP2C9 (poor metabolizer), CYP4F2-TT, and VKORC1-AA was associated with a 4.0-fold (95%CI 1.4-11.4) increased risk, while carriers of both CYP4F2-TT and VKORC1-AA had a particularly increased major bleeding risk (hazard ratio 6.7, 95% CI 1.5-29.8) compared with carriers of CC alleles in CYP4F2 and GG in VKORC1. However, the number of major bleeding cases in carriers of multiple variants was few (8 and 5 patients, respectively).

CONCLUSIONS

CYP4F2 polymorphism was associated with major bleeding, especially in combination with VKORC1 genetic variants. These variants could be considered to further personalize anticoagulant treatment.

Development of a comprehensive cardiovascular disease genetic risk assessment test

Background

Despite monogenic and polygenic contributions to cardiovascular disease (CVD), genetic testing is not widely adopted, and current tests are limited by the breadth of surveyed conditions and interpretation burden.

Methods

We developed a comprehensive clinical genome CVD test with semi-automated interpretation. Monogenic conditions and risk alleles were selected based on the strength of disease association and evidence for increased disease risk, respectively. Non-CVD secondary findings genes, pharmacogenomic (PGx) variants and CVD polygenic risk scores (PRS) were assessed for inclusion. Test performance was modeled using 2,594 genomes from the 1000 Genomes Project, and further investigated in 20 previously tested individuals.

Results

The CVD genome test is composed of a panel of 215 CVD gene-disease pairs, 35 non-CVD secondary findings genes, 4 risk alleles or genotypes, 10 PGx genes and a PRS for coronary artery disease. Modeling of test performance using samples from the 1000 Genomes Project revealed ~6% of individuals with a monogenic finding in a CVD-associated gene, 6% with a risk allele finding, ~1% with a non-CVD secondary finding, and 93% with CVD-associated PGx variants. Assessment of blinded clinical samples showed complete concordance with prior testing. An average of 4 variants were reviewed per case, with interpretation and reporting time ranging from 9-96 min.

Conclusions

A genome sequencing based CVD genetic risk assessment can provide comprehensive genetic disease and genetic risk information to patients with CVD. The semi-automated and limited interpretation burden suggest that this testing approach could be scaled to support population-level initiatives.

The landscape of very important pharmacogenes variants and potential clinical relevance in the Chinese Jingpo population: a comparative study with worldwide populations

BACKGROUND

Pharmacogenomics is a facet of personalized medicine that explores how genetic variants affect drug metabolism and adverse drug reactions. Therefore, this study aims to detect distinct pharmacogenomic variations among the Jingpo population and explore their clinical correlation with drug metabolism and toxicity.

METHODS

Agena MassARRAY Assay was used to genotype 57 VIP variants in 28 genes from 159 unrelated Jingpo participants. Subsequently, the chi-squared test and Bonferroni's statistical tests were utilized to conduct a comparative analysis of genotypes and allele frequencies between the Jingpo population and the other 26 populations from the 1000 Genome Project.

RESULTS

We discovered that the KHV (Kinh in Ho ChiMinh City, Vietnam), CHS (Southern Han Chi-nese, China) and JPT (Japanese in Tokyo, Japan) exhibited the smallest differences from the Jingpo with only 4 variants, while ESN (Esan in Nigeria) exhibited the largest differences with 30 variants. Besides, a total of six considerably different loci (rs4291 in ACE, rs20417 in PTGS2, rs1801280 and rs1799929 in NAT2, rs2115819 in ALOX5, rs1065852 in CYP2D6, p < 3.37 × 10-5) were identified in this study. According to PharmGKB, rs20417 (PTGS2), rs4291 (ACE), rs2115819 (ALOX5) and rs1065852 (CYP2D6) were found to be associated with the metabolism efficiency of non-steroidal anti-inflammatory drugs (NSAIDs), aspirin, montelukast and tamoxifen, respectively. Meanwhile, rs1801280 and rs1799929 (NAT2) were found to be related to drug poisoning with slow acetylation.

CONCLUSION

Our study unveils distinct pharmacogenomic variants in the Jingpo population and discovers their association with the metabolic efficiency of NSAIDs, montelukast, and tamoxifen.

Ascorbic acid-induced warfarin resistance after breast cancer surgery: a case report and literature review

Warfarin is an anticoagulant that requires INR-based dosage adjustment. Ascorbic acid may impair warfarin effectiveness according to limited literature. We report a rare case of a 63-year-old woman with an aortic valve replacement history who developed warfarin resistance after taking ascorbic acid for anemia following breast cancer surgery. Despite increasing the warfarin dose from 6 mg to 10 mg daily, her INR remained below the therapeutic range. After ruling out other causes of warfarin resistance, we discontinued ascorbic acid and observed a rapid increase in INR to target values. The temporal relationship and the absence of other confounding factors confirmed the causality of ascorbic acid in this case. We recommend that patients concomitantly taking vitamin C and warfarin should monitor their INR values closely and discontinue ascorbic acid as soon as possible if they exhibit signs of warfarin resistance.

Correlation between Metabolic Parameters and Warfarin Dose in Patients with Heart Valve Replacement of Different Genotypes

Background

Warfarin has become the first choice for anticoagulation in patients who need lifelong anticoagulation due to its clinical efficacy and low price. However, the anticoagulant effect of warfarin is affected by many drugs, foods, etc. accompanied by a high risk of bleeding and embolism. The Vitamin K epoxide reductase complex 1 (VKORC1) and Cytochrome P450 2C9 (CYP2C9) genotypic variation can influence the therapeutic dose of warfarin. However, it is not clear whether there is a correlation between warfarin dose and liver function, kidney function and metabolic markers such as uric acid (UA) in patients with different genotypes. We performed a single-center retrospective cohort study to evaluate the factors affecting warfarin dose and to establish a dose conversion model for warfarin patients undergoing heart valve replacement.

Methods

We studied 343 patients with a mechanical heart valve replacement, compared the doses of warfarin in patients with different warfarin-related genotypes (CYP2C9 and VKORC1), and analyzed the correlation between liver function, kidney function, UA and other metabolic markers and warfarin dose in patients with different genotypes following heart valve replacement.

Results

Genotype analysis showed that 72.01% of patients had CYP2C9*1/*1 and VKORC1 mutant AA genotypes. Univariate regression analysis revealed that the warfarin maintenance dose was significantly correlated with gender, age, body surface area (BSA), UA and genotype. There was no correlation with liver or kidney function. Multiple linear regression analysis showed that BSA, genotype and UA were the independent factors influencing warfarin dose.

Conclusions

There is a significant correlation between UA content and warfarin dose in patients with heart valve replacement genotypes CYP2C9*1/*1/VKORC1(GA+GG), CYP2C9*1/*1/VKORC1AA and CYP2C9*1/*1/VKORC1AA.

Pharmacogenetic considerations in therapy with novel antiplatelet and anticoagulant agents

Antiplatelets and anticoagulants are extensively used in cardiovascular medicine for the prevention and treatment of thrombosis in the venous and arterial circulations. Wide inter-individual variability has been observed in response to antiplatelets and anticoagulants, which triggered researchers to investigate the genetic basis of this variability. Data from extensive pharmacogenetic studies pointed to strong evidence of association between polymorphisms in candidate genes and the pharmacokinetics and pharmacodynamic action and clinical response of the antiplatelets clopidogrel and the anticoagulant warfarin. In this review, we conducted an extensive search on Medline for the time period of 2009-2023. We also searched the PharmGKB website for levels of evidence of variant-drug combinations and for drug labels and clinical guidelines. We focus on the pharmacogenetics of novel antiplatelets and anticoagulants while excluding acetylsalicylic acid, warfarin and heparins, and discuss the current knowledge with emphasis on the level of evidence.

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.

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

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

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.

Genetic-Guided Pharmacotherapy for Coronary Artery Disease: A Systematic and Critical Review of Economic Evaluations

BACKGROUND

Genetic-guided pharmacotherapy (PGx) is not recommended in clinical guidelines for coronary artery disease (CAD). We aimed to examine the extent and quality of evidence from economic evaluations of PGx in CAD and to identify variables influential in changing conclusions on cost-effectiveness.

METHODS AND RESULTS

From systematic searches across 6 databases, 2 independent reviewers screened, included, and rated the methodological quality of economic evaluations of PGx testing to guide pharmacotherapy for patients with CAD. Of 35 economic evaluations included, most were model-based cost-utility analyses alone, or alongside cost-effectiveness analyses of PGx testing to stratify patients into antiplatelets (25/35), statins (2/35), pain killers (1/35), or angiotensin-converting enzyme inhibitors (1/35) to predict CAD risk (8/35) or to determine the coumadin doses (1/35). To stratify patients into antiplatelets (96/151 comparisons with complete findings of PGx versus non-PGx), PGx was more effective and more costly than non-PGx clopidogrel (28/43) but less costly than non-PGx prasugrel (10/15) and less costly and less effective than non-PGx ticagrelor (22/25). To predict CAD risk (51/151 comparisons), PGx using genetic risk scores was more effective and less costly than clinical risk score (13/17) but more costly than no risk score (16/19) or no treatment (9/9). The remaining comparisons were too few to observe any trend. Mortality risk was the most common variable (47/294) changing conclusions.

CONCLUSIONS

Economic evaluations to date found PGx to stratify patients with CAD into antiplatelets or to predict CAD risk to be cost-effective, but findings varied based on the non-PGx comparators, underscoring the importance of considering local practice in deciding whether to adopt PGx.

Knowledge and attitudes on implementing cardiovascular pharmacogenomic testing

Pharmacogenomics has the potential to inform drug dosing and selection, reduce adverse events, and improve medication efficacy; however, provider knowledge of pharmacogenomic testing varies across provider types and specialties. Given that many actionable pharmacogenomic genes are implicated in cardiovascular medication response variability, this study aimed to evaluate cardiology providers' knowledge and attitudes on implementing clinical pharmacogenomic testing. Sixty-one providers responded to an online survey, including pharmacists (46%), physicians (31%), genetic counselors (15%), and nurses (8%). Most respondents (94%) reported previous genetics education; however, only 52% felt their genetics education prepared them to order a clinical pharmacogenomic test. In addition, most respondents (66%) were familiar with pharmacogenomics, with genetic counselors being most likely to be familiar (p < 0.001). Only 15% of respondents had previously ordered a clinical pharmacogenomic test and a total of 36% indicated they are likely to order a pharmacogenomic test in the future; however, the vast majority of respondents (89%) were interested in pharmacogenomic testing being incorporated into diagnostic cardiovascular genetic tests. Moreover, 84% of providers preferred pharmacogenomic panel testing compared to 16% who preferred single gene testing. Half of the providers reported being comfortable discussing pharmacogenomic results with their patients, but the majority (60%) expressed discomfort with the logistics of test ordering. Reported barriers to implementation included uncertainty about the clinical utility and difficulty choosing an appropriate test. Taken together, cardiology providers have moderate familiarity with pharmacogenomics and limited experience with test ordering; however, they are interested in incorporating pharmacogenomics into diagnostic genetic tests and ordering pharmacogenomic panels.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Pharmacogenomics - a minor rather than major force in clinical medicine

INTRODUCTION

Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making.

AREAS COVERED

Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides.

EXPERT OPINION

Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.

Cost-Effectiveness Analysis of Pharmacogenomics (PGx)-Based Warfarin, Apixaban, and Rivaroxaban Versus Standard Warfarin for the Management of Atrial Fibrillation in Ontario, Canada

OBJECTIVE

To assess the cost-effectiveness of pharmacogenomics (PGx)-based warfarin (i.e., warfarin dosing following genetic testing), apixaban, and rivaroxaban oral anticoagulation versus standard warfarin for the treatment of newly diagnosed patients with nonvalvular atrial fibrillation (AF) aged ≥ 65 years.

METHODS

We developed a Markov decision-analytic model to compare costs [2017 Canadian dollars (C$)] and quality-adjusted life years (QALYs) from the Ontario health care payer perspective over a life-time horizon. The parameters used in the model were derived from the published literature, the Ontario health care administrative database, and expert opinion. To account for the uncertainty of model parameters, we conducted extensive deterministic and probabilistic sensitivity analyses. The results were summarized using incremental cost-effectiveness ratios (ICERs) and cost-effectiveness acceptability curves.

RESULTS

We found that PGx-based warfarin had an ICER of C$17,584/QALY compared with standard warfarin, and apixaban had an ICER of C$64,590/QALY compared with PGx-based warfarin in our base-case analysis. Rivaroxaban was extendedly dominated by PGx-based warfarin and apixaban. The probabilistic sensitivity analysis showed that apixaban, rivaroxaban, PGx-based warfarin, and standard warfarin were cost-effective at some willingness-to-pay (WTP) thresholds. PGx-based warfarin had a higher probability of being cost-effective than apixaban (51.3% versus 14.3%) at a WTP threshold of C$50,000/QALY. At a WTP threshold of C$100,000/QALY, apixaban had a higher probability of being cost-effective than PGx-based warfarin (54.6% versus 22.6%).

CONCLUSION

We found that PGx-based warfarin for patients with AF is cost-effective at a WTP threshold of C$50,000/QALY. Apixaban had a higher probability of being cost-effective (> 50%) at a WTP threshold of C$93,000/QALY.

New insights into the role of VKORC1 polymorphisms for optimal warfarin dose selection in Caribbean Hispanic patients through an external validation of a population PK/PD model

Warfarin, an oral anticoagulant, has been used for decades to prevent thromboembolic events. The complex interplay between CYP2C9 and VKORC1 genotypes on warfarin PK and PD properties is not fully understood in special sub-groups of patients. This study aimed to externally validate a population pharmacokinetic/pharmacodynamic (PK/PD) model for the effect of warfarin on international normalized ratio (INR) and to evaluate optimal dosing strategies based on the selected covariates in Caribbean Hispanic patients. INR, and CYP2C9 and VKORC1 genotypes from 138 patients were used to develop a population PK/PD model in NONMEM. The structural definition of a previously published PD model for INR was implemented. A numerical evaluation of the parameter-covariate relationship was performed. Simulations were conducted to determine optimal dosing strategies for each genotype combinations, focusing on achieving therapeutic INR levels. Findings revealed elevated IC50 for G/G, G/A, and A/A VKORC1 haplotypes (11.76, 10.49, and 9.22 mg/L, respectively), in this population compared to previous reports. The model-guided dosing analysis recommended daily warfarin doses of 3-5 mg for most genotypes to maintain desired INR levels, although subjects with combination of CYP2C9 and VKORC1 genotypes * 2/* 2-, * 2/* 3- and * 2/* 5-A/A would require only 1 mg daily. This research underscores the potential of population PK/PD modeling to inform personalized warfarin dosing in populations typically underrepresented in clinical studies, potentially leading to improved treatment outcomes and patient safety. By integrating genetic factors and clinical data, this approach could pave the way for more effective and tailored anticoagulation therapy in diverse patient groups.

The African Liver Tissue Biorepository Consortium: Capacitating Population-Appropriate Drug Metabolism, Pharmacokinetics, and Pharmacogenetics Research in Drug Discovery and Development

Pharmaceutical companies subject all new molecular entities to a series of in vitro metabolic characterizations that guide the selection and/or design of compounds predicted to have favorable pharmacokinetic properties in humans. Current drug metabolism research is based on liver tissue predominantly obtained from people of European origin, with limited access to tissue from people of African origin. Given the interindividual and interpopulation genomic variability in genes encoding drug-metabolizing enzymes, efficacy and safety of some drugs are poorly predicted for African populations. To address this gap, we have established the first comprehensive liver tissue biorepository inclusive of people of African origin. The African Liver Tissue Biorepository Consortium currently includes three institutions in South Africa and one in Zimbabwe, with plans to expand to other African countries. The program has collected 67 liver samples as of July 2023. DNA from the donors was genotyped for 120 variants in 46 pharmacogenes and revealed variants that are uniquely found in African populations, including the low-activity, African-specific CYP2C9*5 and *8 variants relevant to the metabolism of diclofenac. Larger liver tissue samples were used to isolate primary human hepatocytes. Viability of the hepatocytes and microsomal fractions was demonstrated by the activity of selected cytochrome P450s. This resource will be used to ensure the safety and efficacy of existing and new drugs in African populations. This will be done by characterizing compounds for properties such as drug clearance, metabolite and enzyme identification, and drug-drug and drug-gene interactions. SIGNIFICANCE STATEMENT: Standard optimization of the drug metabolism of new molecular entities in the pharmaceutical industry uses subcellular fractions such as microsomes and isolated primary hepatocytes, being done mainly with tissue from donors of European origin. Pharmacogenetics research has shown that variants in genes coding for drug-metabolizing enzymes have interindividual and interpopulation differences. We established an African liver tissue biorepository that will be useful in ensuring drug discovery and development research takes into account drug responses in people of African origin.

Budd-Chiari syndrome in children: Challenges and outcome

Budd-Chiari syndrome (BCS) is an uncommon disease of the liver, characterised by obstruction of the hepatic venous outflow tract. The etiological spectrum of BCS as well as venous obstruction pattern show wide geographical and demographic variations across the globe. Compared to adults with BCS, children have primary BCS as the predominant etiology, earlier clinical presentation, and hence better treatment outcome. Underlying prothrombotic conditions play a key role in the etiopathogenesis of BCS, though work-up for the same is often unyielding in children. Use of next-generation sequencing in addition to conventional tests for thrombophilia leads to better diagnostic yield. In recent years, advances in radiological endovascular intervention techniques have revolutionized the treatment and outcome of BCS. Various non-invasive markers of fibrosis like liver and splenic stiffness measurement are being increasingly used to assess treatment response. Elastography techniques provide a novel non-invasive tool for measuring liver and splenic stiffness. This article reviews the diagnostic and therapeutic advances and challenges in children with BCS.

Pharmacogenomics of Cardiovascular Drugs for Atherothrombotic, Thromboembolic and Atherosclerotic Risk

PURPOSE OF REVIEW

Advances in pharmacogenomics have paved the way for personalized medicine. Cardiovascular diseases still represent the leading cause of mortality in the world. The aim of this review is to summarize the background, rationale, and evidence of pharmacogenomics in cardiovascular medicine, in particular, the use of antiplatelet drugs, anticoagulants, and drugs used for the treatment of dyslipidemia.

RECENT FINDINGS

Randomized clinical trials have supported the role of a genotype-guided approach for antiplatelet therapy in patients with coronary heart disease undergoing percutaneous coronary interventions. Numerous studies demonstrate how the risk of ineffectiveness of new oral anticoagulants and vitamin K anticoagulants is linked to various genetic polymorphisms. Furthermore, there is growing evidence to support the association of some genetic variants and poor adherence to statin therapy, for example, due to the appearance of muscular symptoms. There is evidence for resistance to some drugs for the treatment of dyslipidemia, such as anti-PCSK9.

SUMMARY

Pharmacogenomics has the potential to improve patient care by providing the right drug to the right patient and could guide the identification of new drug therapies for cardiovascular disease. This is very important in cardiovascular diseases, which have high morbidity and mortality. The improvement in therapy could be reflected in the reduction of healthcare costs and patient mortality.

Approaches to Precision-based Anticoagulation management in the critically Ill

Anticoagulant therapy is commonly associated with a high incidence of avoidable adverse events, especially in the acute care setting. This has led to several initiatives by key national health care stakeholders, including specific attention to The Joint Commission's National Patient Safety Goals, to improve anticoagulation management. The subject of special populations has long been identified as challenging by clinicians with the use of anticoagulants. This is driven in part by numerous variables that can contribute to hard outcomes such as bleeding, thrombosis, length of stay, hospital re-admission, morbidity, and mortality. Despite the notable effort to improve the use of anticoagulants with numerous clinical trials, guidelines, guidance statements, and other sources of published evidence, notable difficulties continue to challenge practitioners in managing this class of medications. This is especially the case with very diverse critically ill populations where countless variables exist, many of which were never explored in trials or have historically been frequently excluded. Trials evaluating anticoagulation therapy often can only account for small portions of variables that may affect thrombosis and hemostasis, and study methods often do not reflect the constantly changing dynamic conditions seen in unique critically ill patients. Clinicians providing care to the numerous critically ill populations are faced with conditions that lead to relatively small therapeutic windows, which makes designing safe optimal anticoagulation management plans difficult when dealing with complex patients and mechanical support devices. The approach to crafting a successful management plan for anticoagulant therapy must incorporate the numerous variables that are continuously assessed and revised during the patient's time in the intensive care unit. We explore considerations and approaches when developing, assessing, and implementing an individualized or precision-based management plan that involves the use of anticoagulants in the critically ill. The skills and thought process provided will assist clinicians in managing this unique, variable, and challenging population.

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.

The Need for the Closer Monitoring of Novel Drugs in MS: A Siponimod Retrospective Cohort Study (Realhes Study)

BACKGROUND

Severe cases of lymphopenia have been reported during siponimod clinical trials, which may negatively impact its benefit/risk profile.

OBJECTIVE

We aimed to evaluate the incidence of lymphopenia following the initiation of siponimod treatment in clinical practice. The secondary objectives included the analysis of factors predisposing to and the clinical relevance of lymphopenia events.

METHODS

In this multicenter retrospective cohort study, information collected from the medical records of 129 patients with MS from 15 tertiary hospitals in Spain who initiated treatment with Siponimod were followed-up for at least 3 months, including at least one lymphocyte count evaluation per patient.

RESULTS

Of the 129 patients, 121 (93.6%) reported lymphopenia events, including 110 (85.3%) with grade ≤ 3 and 11 (8.5%) with grade 4 lymphopenia, higher than those reported in the pivotal clinical trial (73.3% and 3.3% for grade ≤ 3 and grade 4 lymphopenia, respectively). The study included an unexpectedly high proportion of male subjects (72.9%), which might have led to an underestimation of the actual magnitude of the risk.

CONCLUSIONS

In this study, the incidence and severity of lymphopenia after starting siponimod treatment were higher than those reported in previous clinical trials. Therefore, our results reinforce the need for the closer monitoring of novel MS drugs in clinical practice, as well as larger and longer follow-up studies to properly characterize this risk.

High-Evidence, Actionable Phenotype Gene Distribution in a Multispecialty, Tertiary Care Clinic: Potentially Actionable Genes and a Referring Department Profile

Background There has been a trend in recent years toward individualized medicine. Pharmacogenomics (PGx) is the use of patient-specific genetic variations to guide medication selection and treatment. Objective: The primary objective was to characterize the population of referring department patients and identify the number of high-evidence, actionable phenotype (HEAP) genes in this referred population to help guide marketing efforts to the most applicable patient populations and departments. Practice description: Located in a destination, tertiary care clinic. Providers refer patients to a Pharmacogenomics (PGx) specialist for a comprehensive medication review using their pharmacogenomic results. Practice Innovation: The practice is innovative because it has been using PGx in the pharmacy and medical practices since 2016 and has been routinely developing and incorporating PGx best practice alerts (BPAs) into the electronic medical record (EMR) since 2020. Evaluation Methods Genetic results were analyzed from a 27-gene PGx panel test which tests for both pharmacokinetic and pharmacodynamic genes. High-Evidence Actionable Phenotypes (HEAP) are defined as phenotypes with guideline support that may suggest an action by healthcare provider. Low-Evidence Nonactionable Phenotypes (LENP) are defined as phenotypes that do not recommend action. Results There were 1,236 atypical phenotypes identified in the 154 patients referred. Of the atypical genes, 39.97% were HEAP and 60.03% were LENP. Of the HEAP's identified, the majority came from CYP2D6, VKORC1, and UGT1A1. At least 1 HEAP was found in 98.7% of patients (n=152). Conclusion There are a variety of High Evidence Actionable Phenotypes (HEAPs) with a high likelihood of at least one HEAP gene in every patient. These phenotypes can result in serious safety concerns when combined with a medication impacted by one of these HEAP genes. Thus, referral to a pharmacogenomics consultation service may lead to an overall decrease in morbidity and mortality with potential cost avoidance.

Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank

Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.

A Case of Unexplained Warfarin Resistance: A Case Report and Literature Review

Adjusting the exact warfarin dose has always been challenging since it has a narrow therapeutic window. Numerous factors, including poor drug compliance, drug-drug interactions, and malabsorption syndromes, affect the warfarin plasma concentration, leading to oversensitivity or resistance to warfarin. Patients who need more than 15 mg/d of warfarin for maintained anticoagulant effects are considered warfarin resistant. We describe a 62-year-old man referred to our center with bruising on his feet in June 2021. The patient had a history of valve replacement (mechanical prosthetic valves in 2013), hypothyroidism, and atrial fibrillation. He presented with warfarin resistance (first noticed in 2013) and did not reach the desired warfarin therapeutic effect despite receiving 60 mg of warfarin daily. Upon admission, the patient was on warfarin (100 mg/d) with an international normalized ratio (INR) of 1.5. He underwent laboratory and molecular genetic tests, which showed no mutation in the CYP2C9 and VKORC1, the genes associated with warfarin resistance. A stepwise diagnosis is required to identify the underlying cause. Assessing the patient's compliance, drug history, dietary habits, malabsorption diseases, and genetics may be necessary. We evaluated these possible reasons for resistance and found no correlation. The patient's warfarin intake was monitored closely to reach the INR therapeutic target of 3-3.5. He decided to leave the hospital with personal consent. He was discharged with a cardiologist referral and 24 warfarin tablets daily (120 mg/d) with an INR of 1.8. The patient was followed up 6 months and 2 years after discharge and was on the same daily dose of warfarin as at discharge, with no complications.

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

BACKGROUND

Existing pharmacogenetic algorithms cannot fully explain warfarin dose variability in all patients. CYP2C9*13 is an important allelic variant in the Han Chinese population. However, adjustment of warfarin dosing in CYP2C9*13 variant carriers remains unclear. To the best of our knowledge, this study is the first to assess the effects of adjusting warfarin dosages in Han Chinese patients harbouring CYP2C9*13 variants.

METHODS

In total, 971 warfarin-treated Han Chinese patients with atrial fibrillation were enrolled in this study. Clinical data were collected, and CYP2C9*2, *3, *13 and VKORC1-1639 G > A variants were genotyped. We quantitatively analysed the effect of CYP2C9*13 on warfarin maintenance dose and provided multiplicative adjustments for CYP2C9*13 using validated pharmacogenetic algorithms.

RESULTS

Approximately 0.6% of the Han Chinese population carried CYP2C9*13 variant, and the genotype frequency was between those of CYP2C9*2 and CYP2C9*3. The warfarin maintenance doses were significantly reduced in CYP2C9*13 carriers. When CYP2C9*13 variants were not considered, the pharmacogenetic algorithms overestimated warfarin maintenance doses by 1.03-1.16 mg/d on average. The actual warfarin dose in CYP2C9*13 variant carriers was approximately 40% lower than the algorithm-predicted dose. Adjusting the warfarin-dosing algorithm according to the CYP2C9*13 allele could reduce the dose prediction error.

CONCLUSION

Our study showed that the algorithm-predicted doses should be lowered for CYP2C9*13 carriers. Inclusion of the CYP2C9*13 variant in the warfarin-dosing algorithm tends to predict the warfarin maintenance dose more accurately and improves the efficacy and safety of warfarin administration in Han Chinese patients.

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.

NAT2 phenotype alters pharmacokinetics of rivaroxaban in healthy volunteers

Rivaroxaban is a direct inhibitor of factor Xa, a member of direct oral anticoagulant group of drugs (DOACs). Despite being a widely extended alternative to vitamin K antagonists (i.e., acenocoumarol, warfarin) the interindividual variability of DOACs is significant, and may be related to adverse drug reaction occurrence or drug inefficacy, namely hemorrhagic or thromboembolic events. Since there is not a consistent analytic practice to monitor the anticoagulant activity of DOACs, previously reported polymorphisms in genes coding for proteins responsible for the activation, transport, or metabolism of DOACs were studied. The study population comprised 60 healthy volunteers, who completed two randomized, crossover bioequivalence clinical trials between two different rivaroxaban formulations. The effect of food, sex, biogeographical origin and 55 variants (8 phenotypes and 47 single nucleotide polymorphisms) in drug metabolizing enzyme genes (such as CYP2D6, CYP2C9, NAT2) and transporters (namely, ABCB1, ABCG2) on rivaroxaban pharmacokinetics was tested. Individuals dosed under fasting conditions presented lower tmax (2.21 h vs 2.88 h, β = 1.19, R2 =0.342, p = 0.012) compared to fed volunteers. NAT2 slow acetylators presented higher AUC∞ corrected by dose/weight (AUC∞/DW; 8243.90 vs 7698.20 and 7161.25 h*ng*mg /ml*kg, β = 0.154, R2 =0.250, p = 0.044), higher Cmax/DW (1070.99 vs 834.81 and 803.36 ng*mg /ml*kg, β = 0.245, R2 =0.320, p = 0.002), and lower tmax (2.63 vs 3.19 and 4.15 h, β = -0.346, R2 =0.282, p = 0.047) than NAT2 rapid and intermediate acetylators. No other association was statistically significant. Thus, slow NAT2 appear to have altered rivaroxaban pharmacokinetics, increasing AUC∞ and Cmax. Nonetheless, further research should be conducted to verify NAT2 involvement on rivaroxaban pharmacokinetics and to determine its clinical significance.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Identification of Drugs Acting as Perpetrators in Common Drug Interactions in a Cohort of Geriatric Patients from Southern Italy and Analysis of the Gene Polymorphisms That Affect Their Interacting Potential

BACKGROUND

Pharmacogenomic factors affect the susceptibility to drug-drug interactions (DDI). We identified drug interaction perpetrators among the drugs prescribed to a cohort of 290 older adults and analysed the prevalence of gene polymorphisms that can increase their interacting potential. We also pinpointed clinical decision support systems (CDSSs) that incorporate pharmacogenomic factors in DDI risk evaluation.

METHODS

Perpetrator drugs were identified using the Drug Interactions Flockhart Table, the DRUGBANK website, and the Mayo Clinic Pharmacogenomics Association Table. Allelic variants affecting their activity were identified with the PharmVar, PharmGKB, dbSNP, ensembl and 1000 genome databases.

RESULTS

Amiodarone, amlodipine, atorvastatin, digoxin, esomperazole, omeprazole, pantoprazole, simvastatin and rosuvastatin were perpetrator drugs prescribed to >5% of our patients. Few allelic variants affecting their perpetrator activity showed a prevalence >2% in the European population: CYP3A4/5*22, *1G, *3, CYP2C9*2 and *3, CYP2C19*17 and *2, CYP2D6*4, *41, *5, *10 and *9 and SLC1B1*15 and *5. Few commercial CDSS include pharmacogenomic factors in DDI-risk evaluation and none of them was designed for use in older adults.

CONCLUSIONS

We provided a list of the allelic variants influencing the activity of drug perpetrators in older adults which should be included in pharmacogenomics-oriented CDSSs to be used in geriatric medicine.

DNA and RNA Molecules as a Foundation of Therapy Strategies for Treatment of Cardiovascular Diseases

There has always been a tendency of medicine to take an individualised approach to treating patients, but the most significant advances were achieved through the methods of molecular biology, where the nucleic acids are in the limelight. Decades of research of molecular biology resulted in setting medicine on a completely new platform. The most significant current research is related to the possibilities that DNA and RNA analyses can offer in terms of more precise diagnostics and more subtle stratification of patients in order to identify patients for specific therapy treatments. Additionally, principles of structure and functioning of nucleic acids have become a motive for creating entirely new therapy strategies and an innovative generation of drugs. All this also applies to cardiovascular diseases (CVDs) which are the leading cause of mortality in developed countries. This review considers the most up-to-date achievements related to the use of translatory potential of DNA and RNA in treatment of cardiovascular diseases, and considers the challenges and prospects in this field. The foundations which allow the use of translatory potential are also presented. The first part of this review focuses on the potential of the DNA variants which impact conventional therapies and on the DNA variants which are starting points for designing new pharmacotherapeutics. The second part of this review considers the translatory potential of non-coding RNA molecules which can be used to formulate new generations of therapeutics for CVDs.

Pharmacogenomic implications of the differential distribution of CYP2C9 metabolic phenotypes among Latin American populations

The CYP2C9 gene encodes the major drug metabolism enzyme CYP2C9. This gene is highly polymorphic, and no-function (CYP2C9*3) plus decreased function (CYP2C9*2, *5, *8 and *11) star alleles (haplotypes) are commonly used to predict CYP2C9 metabolic phenotypes. This study explores the pharmacogenomic implications of the differential distribution of genotype-predicted CYP2C9 phenotypes across Latin American populations. Data from 1,404 individuals from the South American countries Brazil, Colombia and Peru, from Puerto Rico in the Caribbean and from persons with Mexican ancestry living in North America were analysed. The results showed that the distribution of CYP2C9 alleles and diplotypes, and diplotype-predicted CYP2C9 phenotypes vary significantly across the distinct country cohorts, as well as among self-identified White, Brown and Black Brazilians. Differences in average proportions of biogeographical ancestry across the study groups, especially Native American and African ancestry, are the likely explanation for these results. The differential distribution of genotype-predicted CYP2C9 phenotypes has potentially clinically-relevant pharmacogenomic implications, through its influence on the proportion of individuals at high risk for adverse response to medications that are CYP2C9 substrates, the proportion on individuals with CPIC therapeutic recommendations for dosing and choice of nonsteroidal antinflammatory drugs (NSAIDs) and the number of individuals that need to be genotyped in order to prevent adverse effects of NSAIDs. Collectively, these findings are likely to impact the perceived benefits, cost-effectiveness and clinical adoption of pharmacogenomic screening for drugs that are predominantly metabolized by CYP2C9.

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Towards Evidence-Based Implementation of Pharmacogenomics in Southern Africa: Comorbidities and Polypharmacy Profiles across Diseases

Pharmacogenomics may improve patient care by guiding drug selection and dosing; however, this requires prior knowledge of the pharmacogenomics of drugs commonly used in a specific setting. The aim of this study was to identify a preliminary set of pharmacogenetic variants important in Southern Africa. We describe comorbidities in 3997 patients from Malawi, South Africa, and Zimbabwe. These patient cohorts were included in pharmacogenomic studies of anticoagulation, dyslipidemia, hypertension, HIV and breast cancer. The 20 topmost prescribed drugs in this population were identified. Using the literature, a list of pharmacogenes vital in the response to the top 20 drugs was constructed leading to drug-gene pairs potentially informative in translation of pharmacogenomics. The most reported morbidity was hypertension (58.4%), making antihypertensives the most prescribed drugs, particularly amlodipine. Dyslipidemia occurred in 31.5% of the participants, and statins were the most frequently prescribed as cholesterol-lowering drugs. HIV was reported in 20.3% of the study participants, with lamivudine/stavudine/efavirenz being the most prescribed antiretroviral combination. Based on these data, pharmacogenes of immediate interest in Southern African populations include ABCB1, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLC22A1, SLCO1B1 and UGT1A1. Variants in these genes are a good starting point for pharmacogenomic translation programs in Southern Africa.

The STROMICS genome study: deep whole-genome sequencing and analysis of 10K Chinese patients with ischemic stroke reveal complex genetic and phenotypic interplay

Ischemic stroke is a leading cause of global mortality and long-term disability. However, there is a paucity of whole-genome sequencing studies on ischemic stroke, resulting in limited knowledge of the interplay between genomic and phenotypic variations among affected patients. Here, we outline the STROMICS design and present the first whole-genome analysis on ischemic stroke by deeply sequencing and analyzing 10,241 stroke patients from China. We identified 135.59 million variants, > 42% of which were novel. Notable disparities in allele frequency were observed between Chinese and other populations for 89 variants associated with stroke risk and 10 variants linked to response to stroke medications. We investigated the population structure of the participants, generating a map of genetic selection consisting of 31 adaptive signals. The adaption of the MTHFR rs1801133-G allele, which links to genetically evaluated VB9 (folate acid) in southern Chinese patients, suggests a gene-specific folate supplement strategy. Through genome-wide association analysis of 18 stroke-related traits, we discovered 10 novel genetic-phenotypic associations and extensive cross-trait pleiotropy at 6 lipid-trait loci of therapeutic relevance. Additionally, we found that the set of loss-of-function and cysteine-altering variants present in the causal gene NOTCH3 for the autosomal dominant stroke disorder CADASIL displayed a broad neuro-imaging spectrum. These findings deepen our understanding of the relationship between the population and individual genetic layout and clinical phenotype among stroke patients, and provide a foundation for future efforts to utilize human genetic knowledge to investigate mechanisms underlying ischemic stroke outcomes, discover novel therapeutic targets, and advance precision medicine.

Enzymatic activity of 38 CYP2C9 genotypes on ibuprofen

BACKGROUND AND OBJECTIVE

Ibuprofen, a common non-steroidal anti-inflammatory drug, is used clinically for pain relief and antipyretic treatment worldwide. However, regular or long-term use of ibuprofen may lead to a series of adverse reactions, including gastrointestinal bleeding, hypertension and kidney injury. Previous studies have shown that CYP2C9 gene polymorphism plays an important role in the elimination of various drugs, which leads to the variation in drug efficacy. This study aimed to evaluate the effect of 38 CYP2C9 genotypes on ibuprofen metabolism.

METHODS

Thirty-eight recombinant human CYP2C9 microsomal enzymes were obtained using a frugiperda 21 insect expression system according to a previously described method. Assessment of the catalytic function of these variants was completed via a mature incubation system: 5 pmol CYP2C9*1 and 38 CYP2C9 variants recombinant human microsomes, 5 μL cytochrome B5, ibuprofen (5-1000 μM), and Tris-HCl buffer (pH 7.4). The ibuprofen metabolite contents were determined using HPLC analysis. HPLC analysis included a UV detector, Plus-C18 column, and mobile phase [50% acetonitrile and 50% water (containing 0.05% trifluoroacetic acid)]. The kinetic parameters of the CYP2C9 genotypes were obtained by Michaelis-Menten curve fitting.

RESULTS

The intrinsic clearance (CL_int) of eight variants was not significantly different from CYP2C9*1; four CYP2C9 variants (CYP2C9*38, *44, *53 and *59) showed significantly higher CL_int (increase by 35%-230%) than that of the wild-type; the remaining twenty-six variants exhibited significantly reduced CL_int (reduced by 30%-99%) compared to that of the wild-type.

CONCLUSION

This is the first systematic evaluation of the catalytic characteristics of 38 CYP2C9 genotypes involved ibuprofen metabolism. Our results provide a corresponding supplement to studies on CYP2C9 gene polymorphisms and kinetic characteristics of different variants. We need to focus on poor metabolizers (PMs) with severely abnormal metabolic functions, because they are more susceptible to drug exposure.