Pharmacogenomics of warfarin in populations of African descent

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

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

Ethnic Diversity and Warfarin Pharmacogenomics

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

Leveraging the Genetic Diversity of Human Stem Cells in Therapeutic Approaches

Since their discovery 15 years ago, human pluripotent stem cell (hPSC) technologies have begun to revolutionize science and medicine, rapidly expanding beyond investigative research to drug discovery and development. Efforts to leverage hPSCs over the last decade have focused on increasing both the complexity and in vivo fidelity of human cellular models through enhanced differentiation methods. While these evolutions have fostered novel insights into disease mechanisms and influenced clinical drug discovery and development, there are still several considerations that limit the utility of hPSC models. In this review, we highlight important, yet underexplored avenues to broaden their reach. We focus on (i) the importance of diversifying existing hPSC collections, and their utilization to investigate therapeutic strategies in individuals from different genetic backgrounds, ancestry and sex; (ii) considerations for the selection of therapeutically relevant hPSC-based models; (iii) strategies to adequately increase the scale of cell-based studies; and (iv) the advances and constraints of clinical trials in a dish. Moreover, we advocate for harnessing the translational capabilities of hPSC models along with the use of innovative, scalable approaches for understanding genetic biases and the impact of sex and ancestry on disease mechanisms and drug efficacy and response. The next decade of hPSC innovation is poised to provide vast insights into the genetic basis of human disease and enable rapid advances to develop, repurpose, and ensure the safety of the next generation of disease therapies across diverse human populations.

Polymorphism of the CYP2C9 and VKORC1 genes in patients on the public health system of a municipality in Southern Brazil

Background

Genetic factors can be responsible for part of the populational and interindividual differences observed in warfarin users.

Objectives

To identify occurrence of polymorphisms of the CYP2C9 and VKORC1 genes in patients taking warfarin and relate these profiles to their medication dosages and the Time in Therapeutic Range (TTR).

Methods

Monthly interviews were conducted for data collection. Data were collected on demographic characteristics and medications in use, especially warfarin, including reason for prescription and weekly dose. TTR was calculated as the percentage of days with international normalized ratio (INR) between 2 and 3. The CYP2C9 and VKORC1 genes were analyzed at a Human Genetics Laboratory.

Results

49 patients (74.2%) had polymorphisms of the CYP2C9 and/or VKORC1 genes; the remaining 17 (25.8%) did not have these polymorphisms. The average weekly dose of warfarin was lower among those who had a polymorphism for any of the genes compared to those who did not, with a significant difference (p = 0.035). The mean TTR was also lower among patients with polymorphism. However, the difference between the two groups was not significant for this variable (p = 0.438).

Conclusions

An association was observed between the polymorphisms and the warfarin doses taken by the patients. However, there was no association with adverse events or the time spent within the therapeutic range in this sample.

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.

Return of Research-Related Genetic Test Results and Genetic Discrimination Concerns: Facilitators and Barriers of Genetic Research Participation in Diverse Groups

BACKGROUND

Most genetics studies lack the diversity necessary to ensure that all groups benefit from genetic research.

OBJECTIVES

To explore facilitators and barriers to genetic research participation.

METHODS

We conducted a survey on genetics in research and healthcare from November 15, 2017 to February 28, 2018 among adult Kaiser Permanente (KP) members who had been invited to participate in the KP biobank (KP Research Bank). We used logistic regression to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) comparing the willingness to participate in genetic research under different return of results scenarios and genetic discrimination concerns between groups, according to their demographic characteristics.

RESULTS

A total of 57,331 KP members were invited to participate, and 10,369 completed the survey (18% response rate). Respondents were 65% female, 44% non-Hispanic White (NH White), 22% Asian/Native Hawaiian or other Pacific Islander (Asian/PI), 19% non-Hispanic Black (NH Black), and 16% Hispanic. Respondents willing to participate in genetic research ranged from 22% with no results returned to 87% if health-related genetic results were returned. We also found variation by race/ethnicity; when no results were to be returned, Asian/PIs, Hispanics, and NH Blacks were less likely to want to participate than NH Whites (p < 0.05). However, when results were returned, disparities in the willingness to participate disappeared for NH Blacks and Hispanics. Genetic discrimination concerns were more prevalent in Asian/PIs, Hispanics, and NH Blacks than in NH Whites (p < 0.05).

CONCLUSIONS

Policies that prohibit the return of results and do not address genetic discrimination concerns may contribute to a greater underrepresentation of diverse groups in genetic research.

A cross-sectional evaluation of five warfarin anticoagulation services in Uganda and South Africa

Introduction

Warfarin is the most commonly prescribed oral anticoagulant in sub-Saharan Africa and requires ongoing monitoring. The burden of both infectious diseases and non-communicable diseases is high and medicines used to treat comorbidities may interact with warfarin. We describe service provision, patient characteristics, and anticoagulation control at selected anticoagulation clinics in Uganda and South Africa.

Methods

We evaluated two outpatient anticoagulation services in Kampala, Uganda and three in Cape Town, South Africa between 1 January and 31 July 2018. We collected information from key staff members about the clinics’ service provision and extracted demographic and clinical data from a sample of patients’ clinic records. We calculated time in therapeutic range (TTR) over the most recent 3-month period using the Rosendaal interpolation method.

Results

We included three tertiary level, one secondary level and one primary level anticoagulation service, seeing between 30 and 800 patients per month. Care was rendered by nurses, medical officers, and specialists. All healthcare facilities had on-site pharmacies; laboratory INR testing was off-site at two. Three clinics used warfarin dose-adjustment protocols; these were not validated for local use. We reviewed 229 patient clinical records. Most common indications for warfarin were venous thrombo-embolism in 112/229 (49%), atrial fibrillation in 74/229 (32%) and valvular heart disease in 30/229 (13%). Patients were generally followed up monthly. HIV prevalence was 20% and 5% at Ugandan and South African clinics respectively. Cardiovascular comorbidity predominated. Furosemide, paracetamol, enalapril, simvastatin, and tramadol were the most common concomitant drugs. Anticoagulation control was poor at all included clinics with median TTR of 41% (interquartile range 14% to 69%).

Conclusions

TTR was suboptimal at all included sites, despite frequent patient follow-up. Strategies to improve INR control in sub-Saharan patients taking warfarin are needed. Locally validated warfarin dosing algorithms in Uganda and South Africa may improve INR control.

Genotype-guided warfarin therapy: current status

Warfarin pharmacogenomics has been an extensively studied field in the last decades as it is focused on personalized therapy to overcome the wide interpatient warfarin response variability and decrease the risk of side effects. In this expert review, besides briefly summarizing the current knowledge about warfarin pharmacogenetics, we also present an overview of recent studies that aimed to assess the efficacy, safety and economic issues related to genotype-based dosing algorithms used to guide warfarin therapy, including randomized and controlled clinical trials, meta-analyses and cost-effectiveness studies. To date, the findings still present disparities, mostly because of standard limitations. Thus, further studies should be encouraged to try to demonstrate the benefits of the application of warfarin pharmacogenomic dosing algorithms in clinical practice.

Precision medicine: does ethnicity information complement genotype-based prescribing decisions?

Inter-ethnic differences in drug response are all too well known. These are underpinned by a number of factors, including pharmacogenetic differences across various ethnic populations. Precision medicine relies on genotype-based prescribing decisions with the aim of maximizing efficacy and mitigating the risks. When there is no access to genotyping tests, ethnicity is frequently regarded as a proxy of the patient's probable genotype on the basis of overall population-based frequency of genetic variations in the ethnic group the patient belongs to, with some variations being ethnicity-specific. However, ever-increasing transcontinental migration of populations and the resulting admixing of populations have undermined the utility of self-identified ethnicity in predicting the genetic ancestry, and therefore the genotype, of the patient. An example of the relevance of genetic ancestry of a patient is the inadequate performance of European-derived pharmacogenetic dosing algorithms of warfarin in African Americans, Brazilians and Caribbean Hispanics. Consequently, genotyping a patient potentially requires testing for all known clinically actionable variants that the patient may harbour, and new variants that are likely to be identified using state-of the art next-generation sequencing-based methods. Furthermore, self-identified ethnicity is associated with a number of ethnicity-related attributes and non-genetic factors that potentially influence the risk of phenoconversion (genotype-phenotype discordance), which may adversely impact the success of genotype-based prescribing decisions. Therefore, while genotype-based prescribing decisions are important in implementing precision medicine, ethnicity should not be disregarded.

VKORC1-1639A allele influences warfarin maintenance dosage among Blacks receiving warfarin anticoagulation: a retrospective cohort study

AIM

The study objectives were to investigate the association between selected CYP2C9 and VKORC1 single nucleotide polymorphisms with serious bleeding or thrombotic risk, and to estimate mean daily maintenance dose of warfarin and international normalized ratio measurements among Blacks receiving warfarin anticoagulation.

METHODS

We conducted a retrospective cohort study among 230 Black adults receiving warfarin for a minimum of three consecutive months with a confirmed date of first dosage.

RESULTS

A lower mean daily maintenance dosage of warfarin was required to maintain an international normalized ratio measurement within the therapeutic range among Blacks with the VKORC1-1639G>A variant alleles ([G/A vs G/G, p = 0.02], [A/A vs G/A, p = 0.008] and [A/A vs G/G, p = 0.001]).

CONCLUSION

Data indicated that VKORC1-1639A variant allele influenced warfarin daily maintenance dosage among our small, likely admixed Black patient population.

The challenges of implementing pharmacogenomic testing in the clinic

INTRODUCTION

Pharmacogenomic testing has the potential to greatly benefit patients by enabling personalization of medication management, ensuring better efficacy and decreasing the risk of side effects. However, to fully realize the potential of pharmacogenomic testing, there are several important issues that must be addressed. Areas covered: In this expert review we discuss current challenges impacting the implementation of pharmacogenomic testing in the clinical practice. We emphasize issues related to testing methods, reporting of the results, test selection, clinical interpretation of the results, cost-effectiveness, and the long-term use of pharmacogenomic results in clinical practice. We identify opportunities and future directions to facilitate clinical implementation. Expert commentary: Several key elements are necessary to optimally integrate pharmacogenomic testing into clinical practice. Collaborative efforts among laboratories are needed to improve standardization of testing and reporting of the results. Clinicians need educational opportunities to improve understanding of which test to order and how to interpret the results. The electronic health records and other clinical systems need to improve their storage of the pharmacogenomics test results and interoperability to facilitate the use of clinically actionable results to improve patient care.

Suboptimal cotrimoxazole prophylactic concentrations in HIV-infected children according to the WHO guidelines

AIMS

A clinical study was conduct in HIV-infected children to evaluate the prophylactic doses of cotrimoxazole [sulfamethoxazole (SMX) and trimethoprim (TMP)] advised by the WHO.

METHODS

Children received lopinavir-based antiretroviral therapy with cotrimoxazole prophylaxis (200 mg of SMX/40 mg of TMP once daily). A nonlinear mixed effects modelling approach was used to analyse plasma concentrations. Factors that could impact the pharmacokinetic profile were investigated. The model was subsequently used to simulate individual exposure and evaluate different administration schemes.

RESULTS

The cohort comprised 136 children [average age: 1.9 years (range: [0.7-4]), average weight: 9.5 kg (range: [6-16.3])]. A dose per kg was justified by the significant influence of implementing an allometrically scaled body size covariate on SMX and TMP pharmacokinetics. SMX and TPM clearance were estimated at 0.49 l h^-1 /9.5 kg and 3.06 l h^-1 /9.5 kg, respectively. The simulated exposures obtained after administration of oral dosing recommended by the WHO for children from 10 to 15 kg were significantly lower than in adults for SMX and TMP. This could induce a reduction of effectiveness of cotrimoxazole. Simulations show that regimens of 30 mg kg^-1 of SMX and 6 mg kg^-1 of TMP in the 5-10 kg group and 25 mg kg^-1 of SMX and 5 mg kg^-1 of TMP in the 10-15 kg group are more suitable doses.

CONCLUSIONS

In this context of high prevalence of opportunistic infections, a lower exposure to cotrimoxazole in children than adults was noted. To achieve comparable exposure to adults, a dosing scheme per kg was proposed.

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.

Frequency of Common CYP2C9 Polymorphisms and Their Impact on Warfarin Dose Requirement in Pakistani Population

Polymorphisms in cytochrome P450 (CYP) 2C9 (CYP2C9) gene result in interindividual variability in warfarin dose requirement. There is a need for characterization of genotype frequency distribution in different populations for construction of customized dosing algorithms to enhance the efficacy and reduce the toxicity of warfarin therapy. This study was carried out in Pakistani population to evaluate the contribution of common CYP2C9 polymorphisms to warfarin therapy. A total of 550 stable patients taking warfarin were enrolled after medical history, physical examination, and laboratory investigations. Single blood sample was collected after informed consent. Genomic DNA was extracted, and genotype analysis for CYP2C9*2 and CYP2C9*3 polymorphisms was done by polymerase chain reaction-restriction fragment length polymorphism assay. A number of samples were also analyzed by direct DNA sequencing for validation of the results. Data were analyzed using SPSS version 20. Genotype frequency distribution of CYP2C9*2 and CYP2C9*3 was found to be different from other populations. Of these 2 polymorphisms, CYP2C9*2 did not demonstrate significant effect on warfarin dose requirement, whereas CYP2C9*3 did show significant effect ( P value = .012). It is concluded that there is a need to study genotype frequency distribution and their effect on warfarin dose variability among different populations due to diversity in outcome.

Pharmacogenomics Implications of Using Herbal Medicinal Plants on African Populations in Health Transition

The most accessible points of call for most African populations with respect to primary health care are traditional health systems that include spiritual, religious, and herbal medicine. This review focusses only on the use of herbal medicines. Most African people accept herbal medicines as generally safe with no serious adverse effects. However, the overlap between conventional medicine and herbal medicine is a reality among countries in health systems transition. Patients often simultaneously seek treatment from both conventional and traditional health systems for the same condition. Commonly encountered conditions/diseases include malaria, HIV/AIDS, hypertension, tuberculosis, and bleeding disorders. It is therefore imperative to understand the modes of interaction between different drugs from conventional and traditional health care systems when used in treatment combinations. Both conventional and traditional drug entities are metabolized by the same enzyme systems in the human body, resulting in both pharmacokinetics and pharmacodynamics interactions, whose properties remain unknown/unquantified. Thus, it is important that profiles of interaction between different herbal and conventional medicines be evaluated. This review evaluates herbal and conventional drugs in a few African countries and their potential interaction at the pharmacogenomics level.

Warfarin pharmacogenomics: current best evidence

The utility of using genetic information to guide warfarin dosing has remained unclear based on prior observational studies and small clinical trials. Two larger trials of warfarin and one of the acenocoumarol and phenprocoumon have recently been published. The COAG trial addressed the incremental benefit of adding genetic information to clinical information and demonstrated no benefit from the pharmacogenetic-based dosing strategy on the primary outcome. The EU-PACT UK trial compared an algorithm approach using genetic and clinical information to one that used a relatively fixed starting dose. The pharmacogenetic-based algorithms improved the primary outcome. The study of acenocoumarol and phenprocoumon compared a pharmacogenetic with a clinical algorithm and demonstrated no benefit on the primary outcome. The evidence to date does not support an incremental benefit of adding genetic information to clinical information on anticoagulation control. However, compared with fixed dosing, a pharmacogenetic algorithm can improve anticoagulation control.

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.

Genomic architecture of pharmacological efficacy and adverse events

The pharmacokinetic and pharmacodynamic disciplines address pharmacological traits, including efficacy and adverse events. Pharmacogenomics studies have identified pervasive genetic effects on treatment outcomes, resulting in the development of genetic biomarkers for optimization of drug therapy. Pharmacogenomics-based tests are already being applied in clinical decision making. However, despite substantial progress in identifying the genetic etiology of pharmacological response, current biomarker panels still largely rely on single gene tests with a large portion of the genetic effects remaining to be discovered. Future research must account for the combined effects of multiple genetic variants, incorporate pathway-based approaches, explore gene-gene interactions and nonprotein coding functional genetic variants, extend studies across ancestral populations, and prioritize laboratory characterization of molecular mechanisms. Because genetic factors can play a key role in drug response, accurate biomarker tests capturing the main genetic factors determining treatment outcomes have substantial potential for improving individual clinical care.

Characterizing multi-omic data in systems biology

In today's biology, studies have shifted to analyzing systems over discrete biochemical reactions and pathways. These studies depend on combining the results from scores of experimental methods that analyze DNA; mRNA; noncoding RNAs, DNA, RNA, and protein interactions; and the nucleotide modifications that form the epigenome into global datasets that represent a diverse array of "omics" data (transcriptional, epigenetic, proteomic, metabolomic). The methods used to collect these data consist of high-throughput data generation platforms that include high-content screening, imaging, flow cytometry, mass spectrometry, and nucleic acid sequencing. Of these, the next-generation DNA sequencing platforms predominate because they provide an inexpensive and scalable way to quickly interrogate the molecular changes at the genetic, epigenetic, and transcriptional level. Furthermore, existing and developing single-molecule sequencing platforms will likely make direct RNA and protein measurements possible, thus increasing the specificity of current assays and making it possible to better characterize "epi-alterations" that occur in the epigenome and epitranscriptome. These diverse data types present us with the largest challenge: how do we develop software systems and algorithms that can integrate these datasets and begin to support a more democratic model where individuals can capture and track their own medical information through biometric devices and personal genome sequencing? Such systems will need to provide the necessary user interactions to work with the trillions of data points needed to make scientific discoveries. Here, we describe novel approaches in the genesis and processing of such data, models to integrate these data, and the increasing ubiquity of self-reporting and self-measured genomics and health data.