Ethnicity-specific pharmacogenetics: the case of warfarin in African Americans

Machine learning models to predict the warfarin discharge dosage using clinical information of inpatients from South Korea

As warfarin has a narrow therapeutic window and obvious response variability among individuals, it is difficult to rapidly determine personalized warfarin dosage. Adverse drug events(ADE) resulting from warfarin overdose can be critical, so that typically physicians adjust the warfarin dosage through the INR monitoring twice a week when starting warfarin. Our study aimed to develop machine learning (ML) models that predicts the discharge dosage of warfarin as the initial warfarin dosage using clinical data derived from electronic medical records within 2 days of hospitalization. During this retrospective study, adult patients who were prescribed warfarin at Asan Medical Center (AMC) between January 1, 2018, and October 31, 2020, were recruited as a model development cohort (n = 3168). Additionally, we created an external validation dataset (n = 891) from a Medical Information Mart for Intensive Care III (MIMIC-III). Variables for a model prediction were selected based on the clinical rationale that turned out to be associated with warfarin dosage, such as bleeding. The discharge dosage of warfarin was used the study outcome, because we assumed that patients achieved target INR at discharge. In this study, four ML models that predicted the warfarin discharge dosage were developed. We evaluated the model performance using the mean absolute error (MAE) and prediction accuracy. Finally, we compared the accuracy of the predictions of our models and the predictions of physicians for 40 data point to verify a clinical relevance of the models. The MAEs obtained using the internal validation set were as follows: XGBoost, 0.9; artificial neural network, 0.9; random forest, 1.0; linear regression, 1.0; and physicians, 1.3. As a result, our models had better prediction accuracy than the physicians, who have difficulty determining the warfarin discharge dosage using clinical information obtained within 2 days of hospitalization. We not only conducted the internal validation but also external validation. In conclusion, our ML model could help physicians predict the warfarin discharge dosage as the initial warfarin dosage from Korean population. However, conducting a successfully external validation in a further work is required for the application of the models.

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.

Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network

Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have not been used clinically due to the absence of external validation, lack of assessment for clinical utility, and high risk of bias. Moreover, given the high degree of heterogeneity across different datasets used to develop these algorithms, it is unsurprising that prediction errors remain high, and dosing accuracy is dependent on specific ethnic populations. To circumvent these challenges, deep neural models are increasingly used to improve the precision and accuracy of warfarin dose predictions. Hence, this study sought to develop a deep learning-based model using a well-established curated dataset of over 6000 patients from the International Warfarin Pharmacogenomics Consortium (IWPC). Clinically-relevant input data such as physical attributes, medical conditions, concomitant medications, genotype status of functional warfarin genetic polymorphisms, and therapeutic INR were entered followed by applying a unique and robust training and validation method. The deep model yielded a low average mean absolute error (MAE) of 7.6 mg/week and a relatively low mean percentage of error of 40.9% in Asians, 14.2 mg/week MAE and 36.9% in African Americans, and 12.7 mg/week MAE and 45.4% mean percentage of error in White Caucasians. This model also resulted in 36.4% of all patients with a predicted dose within 20% of the administered dose. Hence, our proposed deep model provides an alternative to predicting warfarin dose in the clinical setting upon validation in ethnically-similar datasets.

The Identification of Novel CYP2D6 Variants in US Hmong: Results From Genome Sequencing and Clinical Genotyping

Objective: Hmong individuals represent a unique East Asian subpopulation in whom limited information concerning pharmacogenetic variation exists. The objectives of this study were to comprehensively characterize the highly polymorphic CYP2D6 gene in Hmong, estimate allele and phenotype frequencies and to compare results between two testing platforms. Methods: DNA from 48 self-identified Hmong participants were sequenced using a targeted next-generation sequencing (NGS) panel. Star allele calls were made using Astrolabe, manual inspection of NGS variant calls and confirmatory Sanger sequencing. Structural variation was determined by long-range (XL)-PCR and digital droplet PCR (ddPCR). The consensus diplotypes were subsequently translated into phenotype utilizing the activity score system. Clinical grade pharmacogenetic testing was obtained for 12 of the 48 samples enabling an assessment of concordance between the consensus calls and those determined by clinical testing platforms. Results: A total of 13 CYP2D6 alleles were identified. The most common alleles were CYP2D6*10 and its structural arrangements (37.5%, 36/96) and the *5 gene deletion (13.5%, 13/96). Three novel suballeles (*10.007, *36.004, and *75.002) were also identified. Phenotype frequencies were as follows: ultrarapid metabolizers (4.2%, 2/48), normal metabolizers (41.7%, 20/48) and intermediate metabolizers (52.1%, 25/48); none of the 48 participants were predicted to be poor metabolizers. Concordance of diplotype and phenotype calls between the consensus and clinical testing were 66.7 and 50%, respectively. Conclusion: Our study to explore CYP2D6 genotypes in the Hmong population suggests that this subpopulation is unique regarding CYP2D6 allelic variants; also, a higher portion of Hmong participants (50%) are predicted to have an intermediate metabolizer phenotype for CYP2D6 compared to other East Asians which range between 27 and 44%. Results from different testing methods varied considerably. These preliminary findings underscore the importance of thoroughly interrogating unique subpopulations to accurately predict a patient's CYP2D6 metabolizer status.

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.

Identification of ancestry proportions in admixed groups across the Americas using clinical pharmacogenomic SNP panels

We evaluated the performance of three PGx panels to estimate biogeographical ancestry: the DMET panel, and the VIP and Preemptive PGx panels described in the literature. Our analysis indicate that the three panels capture quite well the individual variation in admixture proportions observed in recently admixed populations throughout the Americas, with the Preemptive PGx and DMET panels performing better than the VIP panel. We show that these panels provide reliable information about biogeographic ancestry and can be used to guide the implementation of PGx clinical decision-support (CDS) tools. We also report that using these panels it is possible to control for the effects of population stratification in association studies in recently admixed populations, as exemplified with a warfarin dosing GWA study in a sample from Brazil.

Differences in Predicted Warfarin Dosing Requirements Between Hmong and East Asians Using Genotype-Based Dosing Algorithms

INTRODUCTION

Warfarin's narrow therapeutic index and high variability in dosage requirements make dosage selection critical. Genetic factors are known to impact warfarin dosage selection. The Hmong are a unique Asian subpopulation numbering over 278,000 in the United States whose participation in genetics-based research is virtually nonexistent. The translational significance of early reports of warfarin pharmacogene differences in Hmong has not been evaluated.

OBJECTIVES

(i) To validate previously identified allele frequency differences relevant to warfarin dosing in Hmong versus East Asians and (ii) to compare predicted warfarin sensitivity and maintenance doses between a Hmong population and an East Asian cohort.

METHOD

DNA collected from two independent cohorts (n=236 and n=198) of Hmong adults were genotyped for CYP2C9 (*2, *3), VKORC1 (G-1639A), and CYP4F2 (*3). Allele frequencies between the combined Hmong cohort (n=433) and East Asians (n=1165) from the 2009 International Warfarin Pharmacogenetics Consortium (IWPC) study were compared using a χ² test. Percentages of Hmong and East Asian participants predicted to be very sensitive to warfarin were compared using a χ² test, and the predicted mean warfarin maintenance dose was compared with a t test.

RESULTS

The allele frequencies of CYP2C9*3 in the combined Hmong cohort and CYP4F2*3 in the VIP-Hmong cohort are significantly different from those in East Asians (18.9% vs 3.0%, p<0.001 and 9.8% vs 22.1%, p<0.001, respectively). Comparing the combined Hmong cohort to the East Asian cohort, the percentage of participants predicted to be very sensitive to warfarin was significantly higher (28% vs 5%, p<0.01) and the mean predicted warfarin maintenance dose was significantly lower (19.8 vs 21.3 mg/week, p<0.001), respectively.

CONCLUSION

The unique allele frequencies related to warfarin when combined with nongenetic factors observed in the Hmong translate into clinically relevant differences in predicted maintenance dose requirements for Hmong versus East Asians.

Implications of Polymorphisms in the BCKDK and GATA-4 Gene Regions on Stable Warfarin Dose in African Americans

VKORC1 and CYP2C9 genotypes explain less variability in warfarin dose requirements in African Americans compared with Europeans. Variants in BCKDK and GATA-4 gene regions, purported to regulate VKORC1 and CYP2C9 expression, have been shown to play an important role in warfarin dose requirements in Europeans and Asians, respectively. We sought to determine whether rs56314408 near BCKDK or GATA-4 rs2645400 influence warfarin dose requirements in 200 African Americans. Unlike the strong linkage disequilibrium (LD) between rs56314408 and VKORC1 rs9923231 in Europeans, they were not in LD in African Americans. No associations were found on univariate analysis. On multivariable analysis, rs56314408 was associated (P = 0.027) with dose in a regression model excluding VKORC1 rs9923231, and GATA-4 rs2645400 was associated (P = 0.032) with dose in a model excluding CYP2C (CYP2C9*2, *3, *5, *6, *8, and *11, CYP2C rs12777823) variants. Neither variant contributed to dose in the model that included both VKORC1 rs9923231 and CYP2C variants. Our results do not support contributions of the studied variants to warfarin dose requirements in African Americans. However, they illustrate the value of studies in African descent populations, who have low LD in their genome, in teasing out genetic variation underlying drug response associations. They also emphasize the importance of confirming associations in persons of African ancestry.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

Genetic Factors Influencing Warfarin Dose in Black-African Patients: A Systematic Review and Meta-Analysis

Warfarin is the most commonly used oral anticoagulant in sub-Saharan Africa. Dosing is challenging due to a narrow therapeutic index and high interindividual variability in dose requirements. To evaluate the genetic factors affecting warfarin dosing in black-Africans, we performed a meta-analysis of 48 studies (2,336 patients). Significant predictors for CYP2C9 and stable dose included rs1799853 (CYP2C9*2), rs1057910 (CYP2C9*3), rs28371686 (CYP2C9*5), rs9332131 (CYP2C9*6), and rs28371685 (CYP2C9*11) reducing dose by 6.8, 12.5, 13.4, 8.1, and 5.3 mg/week, respectively. VKORC1 variants rs9923231 (-1639G>A), rs9934438 (1173C>T), rs2359612 (2255C>T), rs8050894 (1542G>C), and rs2884737 (497T>G) decreased dose by 18.1, 21.6, 17.3, 11.7, and 19.6 mg/week, respectively, whereas rs7294 (3730G>A) increased dose by 6.9 mg/week. Finally, rs12777823 (CYP2C gene cluster) was associated with a dose reduction of 12.7 mg/week. Few studies were conducted in Africa, and patient numbers were small, highlighting the need for further work in black-Africans to evaluate genetic factors determining warfarin response.

Recommendations for Clinical Warfarin Genotyping Allele Selection: A Report of the Association for Molecular Pathology and the College of American Pathologists

The goal of the Association for Molecular Pathology (AMP) Clinical Practice Committee's AMP Pharmacogenomics (PGx) Working Group is to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The AMP PGx Working Group considered functional impact of the variants, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations for PGx testing when developing these recommendations. The ultimate goal is to promote standardization of PGx gene/allele testing across clinical laboratories. These recommendations are not to be interpreted as prescriptive but to provide a reference guide. Of note, a separate article with recommendations for CYP2C9 allele selection was previously developed by the PGx Working Group that can be applied broadly to CYP2C9-related medications. The warfarin allele recommendations in this report incorporate the previous CYP2C9 allele recommendations and additional genes and alleles that are specific to warfarin testing.

The Advantages and Challenges of Diversity in Pharmacogenomics: Can Minority Populations Bring Us Closer to Implementation?

Health disparities exist among minorities in the United States, with differences seen in disease prevalence, mortality, and responses to medications. These differences are multifactorial with genetic variation explaining a portion of this variability. Pharmacogenomics aims to find the effect of genetic variations on drug response, with the goal of optimizing drug therapy and development. Although genome-wide association studies have been useful in unbiasedly surveying the genome for genetic drivers of clinically relevant phenotypes, most of these studies have been conducted in mainly participants of European and Asian descent, contributing to a growing health disparity in precision medicine. Diversity is important to pharmacogenomic studies, and there may be real advantages to the use of these complex genomes in pharmacogenomics. In this review we will outline some of the advantages and confounders of pharmacogenomics in minorities, describe the role of genetic variation in pharmacologic pathways, and highlight a number of population-specific findings.

Pharmacogenomic genotypes define genetic ancestry in patients and enable population-specific genomic implementation

The importance of genetic ancestry characterization is increasing in genomic implementation efforts, and clinical pharmacogenomic guidelines are being published that include population-specific recommendations. Our aim was to test the ability of focused clinical pharmacogenomic SNP panels to estimate individual genetic ancestry (IGA) and implement population-specific pharmacogenomic clinical decision-support (CDS) tools. Principle components and STRUCTURE were utilized to assess differences in genetic composition and estimate IGA among 1572 individuals from 1000 Genomes, two independent cohorts of Caucasians and African Americans (AAs), plus a real-world validation population of patients undergoing pharmacogenomic genotyping. We found that clinical pharmacogenomic SNP panels accurately estimate IGA compared to genome-wide genotyping and identify AAs with ≥70 African ancestry (sensitivity >82%, specificity >80%, PPV >95%, NPV >47%). We also validated a new AA-specific warfarin dosing algorithm for patients with ≥70% African ancestry and implemented it at our institution as a novel CDS tool. Consideration of IGA to develop an institutional CDS tool was accomplished to enable population-specific pharmacogenomic guidance at the point-of-care. These capabilities were immediately applied for guidance of warfarin dosing in AAs versus Caucasians, but also provide a real-world model that can be extended to other populations and drugs as actionable genomic evidence accumulates.

Essential Characteristics of Pharmacogenomics Study Publications

Pharmacogenomics (PGx) can be seen as a model for biomedical studies: it includes all disease areas of interest and spans in vitro studies to clinical trials, while focusing on the relationships between genes and drugs and the resulting phenotypes. This review will examine different characteristics of PGx study publications and provide examples of excellence in framing PGx questions and reporting their resulting data in a way that maximizes the knowledge that can be built on them.

Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines

Despite monumental advances in genomics, relatively few health care provider organizations in the United States offer personalized or precision medicine as part of the routine clinical workflow. The gaps between research and applied genomic medicine may be a result of a cultural gap across various stakeholders representing scientists, clinicians, patients, policy makers, and third party payers. Scientists are trained to assess the health care value of genomics by either quantifying population-scale effects, or through the narrow lens of clinical trials where the standard of care is compared with the predictive power of a single or handful of genetic variants. While these metrics are an essential first step in assessing and documenting the clinical utility of genomics, they are rarely followed up with other assessments of health care value that are critical to stakeholders who use different measures to define value. The limited value assessment in both the research and implementation science of precision medicine is likely due to necessary logistical constraints of these teams; engaging bioethicists, health care economists, and individual patient belief systems is incredibly daunting for geneticists and informaticians conducting research. In this narrative review, we concisely describe several definitions of value through various stakeholder viewpoints. We highlight the existing gaps that prevent clinical translation of scientific findings generally as well as more specifically using two present-day, extreme scenarios: (1) genetically guided warfarin dosing representing a handful of genetic markers and more than 10 years of basic and translational research, and (2) next-generation sequencing representing genome-dense data lacking substantial evidence for implementation. These contemporary scenarios highlight the need for various stakeholders to broadly adopt frameworks designed to define and collect multiple value measures across different disciplines to ultimately impact more universal acceptance of and reimbursement for genomic medicine.

Genetic Ancestry Analysis Reveals Misclassification of Commonly Used Cancer Cell Lines

BACKGROUND

Given the scarcity of cell lines from underrepresented populations, it is imperative that genetic ancestry for these cell lines is characterized. Consequences of cell line mischaracterization include squandered resources and publication retractions.

METHODS

We calculated genetic ancestry proportions for 15 cell lines to assess the accuracy of previous race/ethnicity classification and determine previously unknown estimates. DNA was extracted from cell lines and genotyped for ancestry informative markers representing West African (WA), Native American (NA), and European (EUR) ancestry.

RESULTS

Of the cell lines tested, all previously classified as White/Caucasian were accurately described with mean EUR ancestry proportions of 97%. Cell lines previously classified as Black/African American were not always accurately described. For instance, the 22Rv1 prostate cancer cell line was recently found to carry mixed genetic ancestry using a much smaller panel of markers. However, our more comprehensive analysis determined the 22Rv1 cell line carries 99% EUR ancestry. Most notably, the E006AA-hT prostate cancer cell line, classified as African American, was found to carry 92% EUR ancestry. We also determined the MDA-MB-468 breast cancer cell line carries 23% NA ancestry, suggesting possible Afro-Hispanic/Latina ancestry.

CONCLUSIONS

Our results suggest predominantly EUR ancestry for the White/Caucasian-designated cell lines, yet high variance in ancestry for the Black/African American-designated cell lines. In addition, we revealed an extreme misclassification of the E006AA-hT cell line.

IMPACT

Genetic ancestry estimates offer more sophisticated characterization leading to better contextualization of findings. Ancestry estimates should be provided for all cell lines to avoid erroneous conclusions in disparities literature.

Landmarks of pharmacogenomics and some considerations for clinical practice

Since the completion of the Human Genome Project 28 years ago, myriad genomics applications have risen in areas such as agriculture, livestock, infectious agents, forensics, bioenergy, ancestry, health, disease, and medicine. This was driven partly by the US government's ability to use a unique program to facilitate genome sequencing to the point where the cost of sequencing a whole human genome is not prohibitive. However, application of this knowledge of the double helix twisted DNA at the bedside in psychiatric clinical practice has little to report, despite US Food and Drug Administration (FDA) approval of nearly 40 psychotropic drugs, as well as specific guidelines for their application. Patients with treatment-resistant mental illness, history of unresponsiveness to psychotropic medications, and history or family history of serious adverse effects to psychotropic drugs may qualify for pharmacogenomics (PGx) testing with insurance reimbursement, or a low, out-of-pocket, payment of not greater than US $300. Psychiatric mental health nurse practitioners and providers who utilize PGx will not only improve patient care outcomes, but also contribute to the acceleration of the potential diagnostic and preventive capabilities of PGx testing.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Pharmacogenetics of warfarin dosing in patients of African and European ancestry

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

Creating and validating a warfarin pharmacogenetic dosing algorithm for Colombian patients

Purpose

Warfarin is an oral anticoagulant associated with adverse reaction to drugs due to wide inter- and intra-individual dosage variability. Warfarin dosage has been related to non-genetic and genetic factors. CYP2C9 and VKORC1 gene polymorphisms affect warfarin metabolism and dosage. Due to the central role of populations’ ethnical and genetic origin on warfarin dosage variability, novel algorithms for Latin American subgroups are necessary to establish safe anticoagulation therapy.

Patients and methods

We genotyped CYP2C9*2 (c.430C > T), CYP2C9*3 (c.1075A > C), CYP4F2 (c.1297G > A), and VKORC1 (−1639 G > A) polymorphisms in 152 Colombian patients who received warfarin. We evaluated the impact on the variability of patients’ warfarin dose requirements. Multiple linear regression analysis, using genetic and non-genetic variables, was used for creating an algorithm for optimal warfarin maintenance dose.

Results

Median weekly prescribed warfarin dosage was significantly lower in patients having the VKORC1-1639 AA genotype and poor CYP2C9*2/*2,*2/*3 metabolizers than their wild-type counterparts. We found a 2.3-fold increase in mean dose for normal sensitivity patients (wild-type VKORC1/CYP2C9 genotypes) compared to the other groups (moderate and high sensitivity); 31.5% of the patients in our study group had warfarin sensitivity-related genotypes. The estimated regression equation accounted for 44.4% of overall variability in regard to warfarin maintenance dose. The algorithm was validated, giving 45.9% correlation (R²=0.459).

Conclusion

Our results describe and validate the first algorithm for predicting warfarin maintenance in a Colombian mestizo population and have contributed toward the understanding of pharmacogenetics in a Latin American population subgroup.

A New Approach towards Minimizing the Risk of Misdosing Warfarin Initiation Doses

It is a challenge to be able to prescribe the optimal initial dose of warfarin. There have been many studies focused on an efficient strategy to determine the optimal initial dose. Numerous clinical, genetic, and environmental factors affect the warfarin dose response. In practice, it is common that the initial warfarin dose is substantially different from the stable maintenance dose, which may increase the risk of bleeding or thrombosis prior to achieving the stable maintenance dose. In order to minimize the risk of misdosing, despite popular warfarin dose prediction models in the literature which create dose predictions solely based on patients' attributes, we have taken physicians' opinions towards the initial dose into consideration. The initial doses selected by clinicians, along with other standard clinical factors, are used to determine an estimate of the difference between the initial dose and estimated maintenance dose using shrinkage methods. The selected shrinkage method was LASSO (Least Absolute Shrinkage and Selection Operator). The estimated maintenance dose was more accurate than the original initial dose, the dose predicted by a linear model without involving the clinicians initial dose, and the values predicted by the most commonly used model in the literature, the Gage clinical model.

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

Pharmacogenomics of CYP2C9: Functional and Clinical Considerations

CYP2C9 is the most abundant CYP2C subfamily enzyme in human liver and the most important contributor from this subfamily to drug metabolism. Polymorphisms resulting in decreased enzyme activity are common in the CYP2C9 gene and this, combined with narrow therapeutic indices for several key drug substrates, results in some important issues relating to drug safety and efficacy. CYP2C9 substrate selectivity is detailed and, based on crystal structures for the enzyme, we describe how CYP2C9 catalyzes these reactions. Factors relevant to clinical response to CYP2C9 substrates including inhibition, induction and genetic polymorphism are discussed in detail. In particular, we consider the issue of ethnic variation in pattern and frequency of genetic polymorphisms and clinical implications. Warfarin is the most well studied CYP2C9 substrate; recent work on use of dosing algorithms that include CYP2C9 genotype to improve patient safety during initiation of warfarin dosing are reviewed and prospects for their clinical implementation considered. Finally, we discuss a novel approach to cataloging the functional capabilities of rare 'variants of uncertain significance', which are increasingly detected as more exome and genome sequencing of diverse populations is conducted.

Pharmacogenomics Guided-Personalization of Warfarin and Tamoxifen

The use of pharmacogenomics to personalize drug therapy has been a long-sought goal for warfarin and tamoxifen. However, conflicting evidence has created reason for hesitation in recommending pharmacogenomics-guided care for both drugs. This review will provide a summary of the evidence to date on the association between cytochrome P450 enzymes and the clinical end points of warfarin and tamoxifen therapy. Further, highlighting the clinical experiences that we have gained over the past ten years of running a personalized medicine program, we will offer our perspectives on the utility and the limitations of pharmacogenomics-guided care for warfarin and tamoxifen therapy.

Warfarin Pharmacogenomics in Diverse Populations

Genotype-guided warfarin dosing algorithms are a rational approach to optimize warfarin dosing and potentially reduce adverse drug events. Diverse populations, such as African Americans and Latinos, have greater variability in warfarin dose requirements and are at greater risk for experiencing warfarin-related adverse events compared with individuals of European ancestry. Although these data suggest that patients of diverse populations may benefit from improved warfarin dose estimation, the vast majority of literature on genotype-guided warfarin dosing, including data from prospective randomized trials, is in populations of European ancestry. Despite differing frequencies of variants by race/ethnicity, most evidence in diverse populations evaluates variants that are most common in populations of European ancestry. Algorithms that do not include variants important across race/ethnic groups are unlikely to benefit diverse populations. In some race/ethnic groups, development of race-specific or admixture-based algorithms may facilitate improved genotype-guided warfarin dosing algorithms above and beyond that seen in individuals of European ancestry. These observations should be considered in the interpretation of literature evaluating the clinical utility of genotype-guided warfarin dosing. Careful consideration of race/ethnicity and additional evidence focused on improving warfarin dosing algorithms across race/ethnic groups will be necessary for successful clinical implementation of warfarin pharmacogenomics. The evidence for warfarin pharmacogenomics has a broad significance for pharmacogenomic testing, emphasizing the consideration of race/ethnicity in discovery of gene-drug pairs and development of clinical recommendations for pharmacogenetic testing.

Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping

We performed a whole-genome scan of genetic variants in splicing regulatory elements (SREs) and evaluated the extent to which natural selection has shaped extant patterns of variation in SREs. We investigated the degree of differentiation of single nucleotide polymorphisms (SNPs) in SREs among human populations and applied long-range haplotype- and multilocus allelic differentiation-based methods to detect selection signatures. We describe an approach, sampling a large number of loci across the genome from functional classes and using the consensus from multiple tests, for identifying candidates for selection signals. SRE SNPs in various SNP functional classes show different patterns of population differentiation compared with their non-SRE counterparts. Intronic regions display a greater enrichment for extreme population differentiation among the potentially tissue-dependent transcript ratio quantitative trait loci (trQTLs) than SRE SNPs in general and includ outlier trQTLs for cross-population composite likelihood ratio, suggesting that incorporation of context annotation for regulatory variation may lead to improved detection of signature of selection on these loci. The proportion of extremely rare SNPs disrupting SREs is significantly higher in European than in African samples. The approach developed here will be broadly useful for studies of function and disease-associated variation in the human genome.

Genotype-guided dosing of warfarin through modeling and simulation

Current genotype-guided algorithms for warfarin dosing fail to deliver optimal performance in two aspects: 1) these algorithms are not able to achieve the same level of benefits in non-white populations, since they were developed based on multivariate regression analysis with mostly European/White data and did not include genetic variants found frequently in non-white populations; 2) these algorithms do not account for the dynamic dose/response relationship and were limited in their usefulness to guide dosing during the initiation phase, as the possession of variant VKORC1 and/or CYP2C9 polymorphisms has been associated with a more rapid attainment of target international normalized ratio (INR) and higher risk of over-anticoagulation even in genotype-guided patients. To address these shortcomings, we report on the novel use of a previously published kinetic/pharmacodynamic (K/PD) model to develop a warfarin dosing nomogram to be used across genotypes and ethnicities. Our approach leverages data from both ethnically diverse and European patients, while accounting for the differential dose/response behaviors due to VKORC1 and CYP2C9 genotypes. According to simulations, the utilization of our dosing nomogram could enable effective attainment of therapeutic INR within one week in both ethnically diverse and European populations, while maintaining uniform INR response profiles across genotypes. Furthermore, in silico clinical trial simulations using the K/PD model could be a feasible approach to help to further refine our dosing nomogram to be more applicable in the clinical setting and explore possible outcomes even before prospective clinical trials are initiated.

Integrated analysis of genetic variation and gene expression reveals novel variant for increased warfarin dose requirement in African Americans

Essentials Genetic variants controlling gene regulation have not been explored in pharmacogenomics. We tested liver expression quantitative trait loci for association with warfarin dose response. A novel predictor for increased warfarin dose response in African Americans was identified. Precision medicine must take into account population-specific variation in gene regulation.

SUMMARY

Background Warfarin is commonly used to control and prevent thromboembolic disorders. However, because of warfarin's complex dose-requirement relationship, safe and effective use is challenging. Pharmacogenomics-guided warfarin dosing algorithms that include the well-established VKORC1 and CYP2C9 polymorphisms explain only a small proportion of inter-individual variability in African Americans (AAs). Objectives We aimed to assess whether transcriptomic analyses could be used to identify regulatory variants associated with warfarin dose response in AAs. Patients/Methods We identified a total of 56 expression quantitative trait loci (eQTLs) for CYP2C9, VKORC1 and CALU derived from human livers and evaluated their association with warfarin dose response in two independent AA warfarin patient cohorts. Results We found that rs4889606, a strong cis-eQTL for VKORC1 (log10 Bayes Factor = 12.02), is significantly associated with increased warfarin daily dose requirement (β = 1.1; 95% confidence interval [CI] 0.46 to 1.8) in the discovery cohort (n = 305) and in the replication cohort (β = 1.04; 95% CI 0.33 -1.7; n = 141) after conditioning on relevant covariates and the VKORC1 -1639G>A (rs9923231) variant. Inclusion of rs4889606 genotypes, along with CYP2C9 alleles, rs9923231 genotypes and clinical variables, explained 31% of the inter-patient variability in warfarin dose requirement. We demonstrate different linkage disequilibrium patterns in the region encompassing rs4889606 and rs9923231 between AAs and European Americans, which may explain the increased dose requirement found in AAs. Conclusion Our approach of interrogating eQTLs identified in liver has revealed a novel predictor of warfarin dose response in AAs. Our work highlights the utility of leveraging information from regulatory variants mapped in the liver to uncover novel variants associated with drug response and the importance of population-specific research.

Correlations between the enantio- and regio-selective metabolisms of warfarin

AIM

To clarify whether the activities of multiple CYPs associated with warfarin metabolism would be correlated with each other.

METHODS

Oral clearances (CLpo) of warfarin enantiomers were estimated in 378 Chinese, Caucasians and African-Americans. The partial metabolic clearances (CLm) for 7-hydroxywarfarin enantiomers were also measured. In addition, CLpo and CLm were determined in a patient on warfarin and rifampicin.

RESULTS

Correlations between CLpo for warfarin enantiomers existed across the three populations. In addition, there was a significant correlation between the CLm for 7-hydroxylation of warfarin enantiomers. Under induced conditions by rifampicin, there were significant correlations between the enantio- and regio-selective metabolisms of warfarin.

CONCLUSION

Metabolic activities of CYP2C9, CYP1A2 and CYP3A4 may be regulated by common transcriptional mechanism(s).

Prediction of atorvastatin plasmatic concentrations in healthy volunteers using integrated pharmacogenetics sequencing

AIM

To use variants found by next-generation sequencing to predict atorvastatin plasmatic concentration profiles (AUC) in healthy volunteers.

SUBJECTS & METHODS

A total of 60 healthy Mexican volunteers were enrolled in this study. We used variants with a predicted functional effect across 20 genes involved in atorvastatin metabolism to construct a regression model using a support vector approach with a radial basis function kernel to predict AUC refining it afterwards in order to explain a greater extent of the variance.

RESULTS

The final support vector regression model using 60 variants (including six novel variants) explained 94.52% of the variance in atorvastatin AUC.

CONCLUSION

An integrated analysis of several genes known to intervene in the different steps of metabolism is required to predict atorvastatin's AUC.

The prevalence of unique SNPs in the renin-angiotensin system highlights the need for pharmacogenetics in Indigenous Australians

Genetic differences between ethnic populations affect susceptibility to disease and efficacy of drugs. This study examined and compared the prevalence of single nucleotide polymorphisms (SNPs) in genes of the renin-angiotensin system (RAS) in a desert community of Indigenous Australians and in non-Indigenous Australians. The polymorphisms were angiotensinogen, AGT G-217A (rs5049); AGT G+174A (rs4762); Angiotensin II type 1 receptor, AGTR1 A+1166C (rs5186); angiotensin converting enzyme, ACE A-240T (rs4291), ACE T-93C (rs4292); renin, REN T+1142C (rs5706). They were measured using allelic discrimination assays. The prevalence of REN T+1142C SNP was similar in the two populations; 99% were homozygous for the T allele. All other SNPs were differently distributed between the two populations (P < 0.0001). In non-Indigenous Australians, the A allele at position 204 of ACE rs4291 was prevalent (61.8%) whereas in the Indigenous Australians the A allele was less prevalent (28%). For rs4292, the C allele had a prevalence of 37.9% in non-Indigenous Australians but in Indigenous Australians the prevalence was only 1%. No Indigenous individuals were homozygous for the C allele of AGTR1 (rs5186). Thus the prevalence of RAS SNPs in this Indigenous Australian desert community was different from non-Indigenous Australians as was the prevalence of cytokine SNPs (as shown in a previous study). These differences may affect susceptibility to chronic renal and cardiovascular disease and may alter the efficacy of drugs used to inhibit the RAS. These studies highlight the need to study the pharmacogenetics of drug absorption, distribution, metabolism and excretion in Indigenous Australians for safe prescribing guidelines.

Pharmacogenetic-guided Warfarin Dosing Algorithm in African-Americans

We aim to develop warfarin dosing algorithm for African-Americans. We explored demographic, clinical, and genetic data from a previously collected cohort of 163 African-American patients with a stable warfarin dose. We explored 2 approaches to develop the algorithm: multiple linear regression and artificial neural network (ANN). The clinical significance of the 2 dosing algorithms was evaluated by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual dose. Linear regression model and ANN model predicted the ideal dose in 52% and 48% of the patients, respectively. The mean absolute error using linear regression model was estimated to be 10.8 mg compared with 10.9 mg using ANN. Linear regression and ANN models identified several predictors of warfarin dose including age, weight, CYP2C9 genotype *1/*1, VKORC1 genotype, rs12777823 genotype, rs2108622 genotype, congestive heart failure, and amiodarone use. In conclusion, we developed a warfarin dosing algorithm for African-Americans. The proposed dosing algorithm has the potential to recommend warfarin doses that are close to the appropriate doses. The use of more sophisticated ANN approach did not result in improved predictive performance of the dosing algorithm except for patients of a dose of ≥49 mg/wk.

A systematic analysis and comparison of warfarin initiation strategies

OBJECTIVE

Randomized trials have reported inconsistent evidence on the effectiveness of algorithms that use genotypes to initiate warfarin therapy. The Clarification of Optimal Anticoagulation through Genetics (COAG) trial initiated therapy on the basis of predicted maintenance doses, with a pharmacogenetic-guided algorithm in one study group and a clinically guided algorithm in the other. The European Pharmacogenetics of Anticoagulant Therapy (EU-PACT) consortium initiated therapy on the basis of loading doses, with an algorithm-based prediction in one study group and a fixed-dose regimen in the other. To understand the differences between these trials, we compared the initial doses between alternative dosing algorithms (the pharmacogenetic-guided and clinically guided algorithms developed by Gage and colleagues and those developed by the International Warfarin Pharmacogenetics Consortium) and between the COAG and EU-PACT dose-initiation strategies.

METHODS

This was a secondary analysis of the COAG trial - a double-blind, randomized-controlled trial (2009-2013) - conducted at 18 clinical centers in the USA, which included 1010 adults initiating warfarin therapy, of whom 719 achieved maintenance dose.

RESULTS

Among COAG participants, the distribution of initial doses differed between algorithms, but showed similar prediction accuracy for maintenance dose. However, had the COAG trial implemented the EU-PACT strategy, the 3-day initial dose would have been 4.8 mg greater among participants randomized to pharmacogenetic-guided dosing, but only 2.5 mg greater among participants randomized to clinically guided dosing (P<0.001).

CONCLUSION

Compared with the COAG trial, the EU-PACT trial used systematically larger loading doses in the pharmacogenetic-guided group and might have inadequately adjusted for clinical variability in warfarin dose requirements in the fixed-dose group.

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

Warfarin Pharmacogenetics Reevaluated: Subgroup Analysis Reveals a Likely Underestimation of the Maximum Pharmacogenetic Benefit by Clinical Trials

OBJECTIVES

Various patient subgroups were examined to determine which ones obtain the largest pharmacogenetic improvements in warfarin dose accuracy. Subgrouping schemes of recent clinical trials were analyzed for comparison.

METHODS

The accuracy of a pharmacogenetic dose algorithm was determined retrospectively in comparison to that of a clinical algorithm in subgroups of the International Warfarin Pharmacogenetics Consortium (IWPC) patient database (n = 2,274) and of newly studied clinic patients (n = 146).

RESULTS

White patients with low-dose genotypes (*1*3/AA, *2*2/AA, *2*3/GA, *2*3/AA, *3*3/GG, *3*3/GA, and *3*3/AA) achieved the largest pharmacogenetic improvements in warfarin dose accuracy. Mean absolute dosing error (MAE) in this subgroup of IWPC and newly studied patients was reduced 75.7% and 89.7%, respectively. White IWPC patients with >2 variants or ≥2 mg/day absolute difference between pharmacogenetic and clinical dose predictions obtained MAE reductions of 71.1% and 65.3%, respectively. By comparison, unstratified populations and subgroups of a major clinical trial, when replicated in IWPC patients, obtained smaller MAE reductions of 31.8% to 48.2%. Blacks and Asians obtained substantially smaller dose accuracy improvements overall than whites.

CONCLUSIONS

Patient subgroups were identified that obtained the largest pharmacogenetic improvements in warfarin dose accuracy. These subgroups have not been analyzed in clinical trials to date, likely resulting in underestimation of the pharmacogenetic benefit.

Race-Specific Influence of CYP4F2 on Dose and Risk of Hemorrhage Among Warfarin Users

OBJECTIVE

The p.V433M in cytochrome P450 4F2 (rs2108622, CYP4F2*3) is associated with a higher warfarin dose and lower risk of hemorrhage among European Americans. We evaluate the influence of CYP4F2*3 on warfarin dose, time to target international normalized ratio (INR), and stable dose, proportion of time spent in target range (PTTR), as well as the risk of overanticoagulation and hemorrhage among European and African Americans.

DESIGN

CYP4F2*3 was genotyped in 1238 patients initiated on warfarin in a prospective inception cohort. Multivariable linear regression was used to assess warfarin dose and PTTR; proportional hazards analysis was performed to evaluate time to target INR and stable dose, overanticoagulation, and hemorrhage.

SETTING

Two outpatient anticoagulation clinics.

PARTICIPANTS

A total of 1238 anticoagulated patients.

OUTCOMES

Warfarin dose (mg/day), time to target INR and stable dose, PTTR, overanticoagulation (INR more than 4), and major hemorrhage.

RESULTS

Minor allele frequency for the CYP4F2*3 variant was 30.3% among European Americans and 8.4% among African Americans. CYP4F2*3 was associated with higher dose among European Americans but not African Americans. Compared to CYP4F2*1/*1, *1/*3 was associated with a statistically nonsignificant increase in dose (4.5%, p=0.22) and *3/*3 was associated with a statistically significant increase in dose (13.2%, p=0.02). CYP4F2 genotype did not influence time to target INR, time to stable dose, or PTTR in either race group. CYP4F2*3/*3 was associated with a 31% lower risk of over anticoagulation (p=0.06). Incidence of hemorrhage was lower among participants with CYP4F2 *3/*3 compared with *1/*3 or *1/*1 (incidence rate ratio = 0.45, 95% confidence interval 0.14-1.11, p=0.09). After controlling for covariates, CYP4F2 *3/*3 was associated with a 52% lower risk of hemorrhage, although this was not statistically significant (p=0.24).

CONCLUSION

Possession of CYP4F2*3 variant influences warfarin dose among European Americans but not African Americans. The CYP4F2-dose, CYP4F2-overanticoagulation, and CYP4F2-hemorrhage association follows a recessive pattern with possession of CYP4F2*3/*3 genotype likely demonstrating a protective effect. These findings need further confirmation.

Novel genetic predictors of venous thromboembolism risk in African Americans

Venous thromboembolism (VTE) is the third most common life-threatening cardiovascular condition in the United States, with African Americans (AAs) having a 30% to 60% higher incidence compared with other ethnicities. The mechanisms underlying population differences in the risk of VTE are poorly understood. We conducted the first genome-wide association study in AAs, comprising 578 subjects, followed by replication of highly significant findings in an independent cohort of 159 AA subjects. Logistic regression was used to estimate the association between genetic variants and VTE risk. Through bioinformatics analysis of the top signals, we identified expression quantitative trait loci (eQTLs) in whole blood and investigated the messenger RNA expression differences in VTE cases and controls. We identified and replicated single-nucleotide polymorphisms on chromosome 20 (rs2144940, rs2567617, and rs1998081) that increased risk of VTE by 2.3-fold (P< 6 × 10(-7)). These risk variants were found in higher frequency among populations of African descent (>20%) compared with other ethnic groups (<10%). We demonstrate that SNPs on chromosome 20 are cis-eQTLs for thrombomodulin (THBD), and the expression of THBD is lower among VTE cases compared with controls (P= 9.87 × 10(-6)). We have identified novel polymorphisms associated with increased risk of VTE in AAs. These polymorphisms are predominantly found among populations of African descent and are associated with THBD gene expression. Our findings provide new molecular insight into a mechanism regulating VTE susceptibility and identify common genetic variants that increase the risk of VTE in AAs, a population disproportionately affected by this disease.

Poor warfarin dose prediction with pharmacogenetic algorithms that exclude genotypes important for African Americans

OBJECTIVES

Recent clinical trial data cast doubt on the utility of genotype-guided warfarin dosing, specifically showing worse dosing with a pharmacogenetic versus clinical dosing algorithm in African Americans. However, many genotypes important in African Americans were not accounted for. We aimed to determine whether omission of the CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*11 alleles and rs12777823 G > A genotype affects performance of dosing algorithms in African Americans.

METHODS

In a cohort of 274 warfarin-treated African Americans, we examined the association between the CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*11 alleles and rs12777823 G > A genotype and warfarin dose prediction error with pharmacogenetic algorithms used in clinical trials.

RESULTS

The http://www.warfarindosing.org algorithm overestimated doses by a median (interquartile range) of 1.2 (0.02-2.6) mg/day in rs12777823 heterozygotes (P<0.001 for predicted vs. observed dose), 2.0 (0.6-2.8) mg/day in rs12777823 variant homozygotes (P = 0.004), and 2.2 (0.5-2.9) mg/day in carriers of a CYP2C9 variant (P < 0.001). The International Warfarin Pharmacogenetics Consortium (IWPC) algorithm underdosed warfarin by 0.8 (-2.3 to 0.4) mg/day for patients with the rs12777823 GG genotype (P < 0.001) and overdosed warfarin by 0.7 (-0.4 to 1.9) mg/day in carriers of a variant CYP2C9 allele (P = 0.04). Modifying the http://www.warfarindosing.org algorithm to adjust for variants important in African Americans led to better dose prediction than either the original http://www.warfarindosing.org (P < 0.01) or IWPC (P < 0.01) algorithm.

CONCLUSION

These data suggest that, when providing genotype-guided warfarin dosing, failure to account for variants important in African Americans leads to significant dosing error in this population.

Pyrosequencing of the CYP2C9 -1766T>C polymorphism as a means of detecting the CYP2C9*8 allele

The CYP2C9 c.449G>A (p.R150H, rs7900194) polymorphism, which confers the CYP2C9*8 allele, is common in persons of African descent and results in reduced clearance of the narrow therapeutic index drugs, warfarin and phenytoin. Because of significant homology in DNA sequence at the 449G>A locus among CYP2C genes, the 449G>A variant cannot be reliably detected via PCR-based genotyping assays that require a short PCR product, such as pyrosequencing. Herein, we propose genotyping for the CYP2C9 c.-1766T>C polymorphism via pyrosequencing as an alternative and accurate means of identifying the CYP2C9*8 allele.

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

AIM

To determine the accuracy of international warfarin pharmacogenetic algorithms developed on large multiethnic cohorts (comprising more than 1000 subjects) to predict therapeutic warfarin doses in Turkish patients.

MATERIALS & METHODS

We investigated two Turkish warfarin-treated cohorts: patients with no history of hemorrhagic or thromboembolic event and patients with major and life-threatening hemorrhagic events.

RESULTS

International pharmacogenetic algorithms showed good performances in predicting the therapeutic dose of patients with no history of bleedings, but they did not significantly detect the incorrect warfarin dose of patients with major and life-threatening hemorrhagic events.

CONCLUSION

Although genetic information can predict the therapeutic warfarin dose, the accuracy of the international pharmacogenetic algorithms is not sufficient to be used for warfarin screening in Turkish patients.

Revisiting Warfarin Dosing Using Machine Learning Techniques

Determining the appropriate dosage of warfarin is an important yet challenging task. Several prediction models have been proposed to estimate a therapeutic dose for patients. The models are either clinical models which contain clinical and demographic variables or pharmacogenetic models which additionally contain the genetic variables. In this paper, a new methodology for warfarin dosing is proposed. The patients are initially classified into two classes. The first class contains patients who require doses of >30 mg/wk and the second class contains patients who require doses of ≤30 mg/wk. This phase is performed using relevance vector machines. In the second phase, the optimal dose for each patient is predicted by two clinical regression models that are customized for each class of patients. The prediction accuracy of the model was 11.6 in terms of root mean squared error (RMSE) and 8.4 in terms of mean absolute error (MAE). This was 15% and 5% lower than IWPC and Gage models (which are the most widely used models in practice), respectively, in terms of RMSE. In addition, the proposed model was compared with fixed-dose approach of 35 mg/wk, and the model proposed by Sharabiani et al. and its outperformance were proved in terms of both MAE and RMSE.

Novel single nucleotide polymorphism in CYP2C9 is associated with changes in warfarin clearance and CYP2C9 expression levels in African Americans

Warfarin is a widely used anticoagulant whose active S-enantiomer is primarily metabolized by the CYP2C9 enzyme. The CYP2C9*2 and CYP2C9*3 alleles are associated with lower warfarin dose requirement and decreased enzyme activity. In contrast, we previously identified a novel single-nucleotide polymorphism (SNP) (rs7089580A > T) in CYP2C9 that is associated with higher warfarin dose requirement in African Americans (AAs). In this study, we examine the effect of rs7089580 on warfarin pharmacokinetics and CYP2C9 expression in 63 AA patients and 32 AA liver tissues, respectively. We found oral clearance of S-warfarin to be higher among carriers of the minor rs7089580 allele (T) compared with wild-type homozygotes (3.73 ± 1.46 vs 2.95 ± 1.39 mL/min; P = 0.04). CYP2C9 messenger RNA expression in liver tissue was also higher among A/T and T/T genotypes compared with A/A (P < 0.02). Our findings indicate that rs7089580 is associated with higher S-warfarin clearance and CYP2C9 expression and may help explain the higher dose requirement of warfarin in AAs. Furthermore, rs7089580 is in complete linkage disequilibrium with the promoter SNP rs12251841 in AAs, which may provide a biologically plausible explanation for the observed effect on CYP2C9 expression levels. Given the many clinically relevant substrates of CYP2C9, identifying polymorphisms that affect expression levels and metabolism across ethnicities is essential for individualization of doses with a narrow therapeutic index.

Race influences warfarin dose changes associated with genetic factors

Warfarin dosing algorithms adjust for race, assigning a fixed effect size to each predictor, thereby attenuating the differential effect by race. Attenuation likely occurs in both race groups but may be more pronounced in the less-represented race group. Therefore, we evaluated whether the effect of clinical (age, body surface area [BSA], chronic kidney disease [CKD], and amiodarone use) and genetic factors (CYP2C9*2, *3, *5, *6, *11, rs12777823, VKORC1, and CYP4F2) on warfarin dose differs by race using regression analyses among 1357 patients enrolled in a prospective cohort study and compared predictive ability of race-combined vs race-stratified models. Differential effect of predictors by race was assessed using predictor-race interactions in race-combined analyses. Warfarin dose was influenced by age, BSA, CKD, amiodarone use, and CYP2C9*3 and VKORC1 variants in both races, by CYP2C9*2 and CYP4F2 variants in European Americans, and by rs12777823 in African Americans. CYP2C9*2 was associated with a lower dose only among European Americans (20.6% vs 3.0%, P < .001) and rs12777823 only among African Americans (12.3% vs 2.3%, P = .006). Although VKORC1 was associated with dose decrease in both races, the proportional decrease was higher among European Americans (28.9% vs 19.9%, P = .003) compared with African Americans. Race-stratified analysis improved dose prediction in both race groups compared with race-combined analysis. We demonstrate that the effect of predictors on warfarin dose differs by race, which may explain divergent findings reported by recent warfarin pharmacogenetic trials. We recommend that warfarin dosing algorithms should be stratified by race rather than adjusted for race.

Oral anticoagulation: a critique of recent advances and controversies

There have recently been significant advances in the field of oral anticoagulation, but these have also led to many controversies. Warfarin is still the commonest drug used for clotting disorders but its use is complicated owing to wide inter-individual variability in dose requirement and its narrow therapeutic index. Warfarin dose requirement can be influenced by both genetic and environmental factors. Two recent randomized controlled trials (RCTs) came to different conclusion regarding the utility of genotype-guided dosing; we critically explore the reasons for the differences. The new generation of oral anticoagulants have been demonstrated to be as efficacious as warfarin, but further work is needed to evaluate their safety in real clinical settings.

Warfarin pharmacogenetics

The cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase complex 1 (VKORC1) genotypes have been strongly and consistently associated with warfarin dose requirements, and dosing algorithms incorporating genetic and clinical information have been shown to be predictive of stable warfarin dose. However, clinical trials evaluating genotype-guided warfarin dosing produced mixed results, calling into question the utility of this approach. Recent trials used surrogate markers as endpoints rather than clinical endpoints, further complicating translation of the data to clinical practice. The present data do not support genetic testing to guide warfarin dosing, but in the setting where genotype data are available, use of such data in those of European ancestry is reasonable. Outcomes data are expected from an on-going trial, observational studies continue, and more work is needed to define dosing algorithms that incorporate appropriate variants in minority populations; all these will further shape guidelines and recommendations on the clinical utility of genotype-guided warfarin dosing.