The long and winding road to warfarin pharmacogenetic testing

Biobanking with genetics shapes precision medicine and global health

Precision medicine provides patients with access to personally tailored treatments based on individual-level data. However, developing personalized therapies requires analyses with substantial statistical power to map genetic and epidemiologic associations that ultimately create models informing clinical decisions. As one solution, biobanks have emerged as large-scale, longitudinal cohort studies with long-term storage of biological specimens and health information, including electronic health records and participant survey responses. By providing access to individual-level data for genotype-phenotype mapping efforts, pharmacogenomic studies, polygenic risk score assessments and rare variant analyses, biobanks support ongoing and future precision medicine research. Notably, due in part to the geographical enrichment of biobanks in Western Europe and North America, European ancestries have become disproportionately over-represented in precision medicine research. Herein, we provide a genetics-focused review of biobanks from around the world that are in pursuit of supporting precision medicine. We discuss the limitations of their designs, ongoing efforts to diversify genomics research and strategies to maximize the benefits of research leveraging biobanks for all.

Health Economics Tools and Precision Medicine: Opportunities and Challenges

Precision medicine - individualizing care for patients and addressing variations in treatment response - is likely to be important in improving the nation's health in a cost-effective manner. Despite this promise, widespread use of precision medicine, specifically genomic markers, in clinical care has been limited in practice to date. Lack of evidence, clear evidence thresholds, and reimbursement have been cited as major barriers. Health economics frameworks and tools can elucidate the effects of legal, regulatory, and reimbursement policies on the use of precision medicine while guiding research investments to enhance the appropriate use of precision medicine. Despite the capacity of economics to enhance the clinical and human impact of precision medicine, application of health economics to precision medicine has been limited - in part because precision medicine is a relatively new field - but also because precision medicine is complex, both in terms of its applications and implications throughout medicine and the healthcare system. The goals of this review are several-fold: (1) provide an overview of precision medicine and key policy challenges for the field; (2) explain the potential utility of economics methods in addressing these challenges; (3) describe recent research activities; and (4) summarize opportunities for cross-disciplinary research.

Chinese Patients With Heart Valve Replacement Do Not Benefit From Warfarin Pharmacogenetic Testing on Anticoagulation Outcomes

BACKGROUND

Genotype-guided warfarin dosing has been shown in some randomized trials to improve anticoagulation outcomes in individuals of European ancestry; yet, its utility in Chinese patients with heart valve replacement remains unresolved.

METHODS

A total of 2264 patients who underwent heart valve replacement at Wuhan Asia Heart Hospital were enrolled in this study. Patients were randomly divided into 2 groups, namely, a genotype-guided and a traditional clinically guided warfarin dosing group. In the genotype-guided group (n = 1134), genotyping for CYP2C9 and VKORC1 (-1639 G→A) was performed using TaqMan genotyping assay. Warfarin doses were predicted with the International Warfarin Pharmacogenetics Consortium algorithm. Patients in the control group (n = 1130) were clinically guided. The primary outcome was to compare the incidence of adverse events (major bleeding and thrombotic) during a 90-day follow-up period between 2 groups. Secondary objectives were to describe effects of the pharmacogenetic intervention on the first therapeutic-target-achieving time, the stable maintenance dose, and the hospitalization days.

RESULTS

A total of 2245 patients were included in the analysis. Forty-nine events occurred during follow-up. Genotype-guided dosing strategy did not result in a reduction in major bleeding (0.26% versus 0.63%; hazard ratio, 0.44; 95% confidence interval, 0.13-1.53; P = 0.20) and thrombotic events (0.89% versus 1.61%; hazard ratio, 0.56; 95% confidence interval, 0.27-1.17; P = 0.12) compared with clinical dosing group. Compared with traditional dosing, patients in the genotype-guided group reached their therapeutic international normalized ratio in a shorter time (3.8 ± 2.0 versus 4.4 ± 2.0 days, P < 0.001). There was no difference in hospitalization days (P = 0.28).

CONCLUSIONS

Warfarin pharmacogenetic testing according to the International Warfarin Pharmacogenetics Consortium algorithm cannot improve anticoagulation outcomes in Chinese patients with heart valve replacement.

A Framework for Prioritizing Research Investments in Precision Medicine

INTRODUCTION

The adoption of precision medicine (PM) has been limited in practice to date, and yet its promise has attracted research investments. Developing foundational economic approaches for directing proper use of PM and stimulating growth in this area from multiple perspectives is thus quite timely.

METHODS

Building on our previously developed expected value of individualized care (EVIC) framework, we conceptualize new decision-relevant metrics to better understand and forecast the expected value of PM. Several aspects of behavior at the patient, physician, and payer levels are considered that can inform the rate and manner in which PM innovations diffuse throughout the relevant population. We illustrate this framework and the methods using a retrospective evaluation of the use of OncotypeDx genomic test among breast cancer patients.

RESULTS

The enriched metrics can help inform many facets of PM decision making, such as evaluating alternative reimbursement levels for PM tests, implementation and education programs for physicians and patients, and decisions around research investments by manufacturers and public entities. We replicated prior published results on evaluation of OncotypeDx among breast cancer patients but also illustrated that those results are based on assumptions that are often not met in practice. Instead, we show how incorporating more practical aspects of behavior around PM could lead to drastically different estimates of value.

CONCLUSION

We believe that the framework and the methods presented can provide decision makers with more decision-relevant tools to explore the value of PM. There is a growing recognition that data on adoption is important to decision makers. More research is needed to develop prediction models for potential diffusion of PM technologies.

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.

Web resources for pharmacogenomics

Pharmacogenomics is the study of the impact of genetic variations or genotypes of individuals on their drug response or drug metabolism. Compared to traditional genomics research, pharmacogenomic research is more closely related to clinical practice. Pharmacogenomic discoveries may effectively assist clinicians and healthcare providers in determining the right drugs and proper dose for each patient, which can help avoid side effects or adverse reactions, and improve the drug therapy. Currently, pharmacogenomic approaches have proven their utility when it comes to the use of cardiovascular drugs, antineoplastic drugs, aromatase inhibitors, and agents used for infectious diseases. The rapid innovation in sequencing technology and genome-wide association studies has led to the development of numerous data resources and dramatically changed the landscape of pharmacogenomic research. Here we describe some of these web resources along with their names, web links, main contents, and our ratings.

Personalized medicine and genome-based treatments: Why personalized medicine ≠ individualized treatments

The sequencing of the human genome and decreasing costs of sequencing technology have led to the notion of ‘personalized medicine’. This has been taken by some authors to indicate that personalized medicine will provide individualized treatments solely based on one’s DNA sequence. We argue this is overly optimistic and misconstrues the notion of personalization. Such interpretations fail to account for economic, policy and structural constraints on the delivery of healthcare. Furthermore, notions of individualization based on genomic data potentially take us down the road of genetic reductionism obscuring the role of environmental factors in disease and ill health. We propose that one should see personalized medicine as a way of using personal genomic information to stratify individuals into subpopulations and suggest that personalized medicine be seen within a broader idea of personalized healthcare, reflecting healthcare that integrates personal genomic data into cultural, environmental and personal contexts.

A pharmacogenetic versus a clinical algorithm for warfarin dosing

BACKGROUND

The clinical utility of genotype-guided (pharmacogenetically based) dosing of warfarin has been tested only in small clinical trials or observational studies, with equivocal results.

METHODS

We randomly assigned 1015 patients to receive doses of warfarin during the first 5 days of therapy that were determined according to a dosing algorithm that included both clinical variables and genotype data or to one that included clinical variables only. All patients and clinicians were unaware of the dose of warfarin during the first 4 weeks of therapy. The primary outcome was the percentage of time that the international normalized ratio (INR) was in the therapeutic range from day 4 or 5 through day 28 of therapy.

RESULTS

At 4 weeks, the mean percentage of time in the therapeutic range was 45.2% in the genotype-guided group and 45.4% in the clinically guided group (adjusted mean difference, [genotype-guided group minus clinically guided group], -0.2; 95% confidence interval, -3.4 to 3.1; P=0.91). There also was no significant between-group difference among patients with a predicted dose difference between the two algorithms of 1 mg per day or more. There was, however, a significant interaction between dosing strategy and race (P=0.003). Among black patients, the mean percentage of time in the therapeutic range was less in the genotype-guided group than in the clinically guided group. The rates of the combined outcome of any INR of 4 or more, major bleeding, or thromboembolism did not differ significantly according to dosing strategy.

CONCLUSIONS

Genotype-guided dosing of warfarin did not improve anticoagulation control during the first 4 weeks of therapy. (Funded by the National Heart, Lung, and Blood Institute and others; COAG ClinicalTrials.gov number, NCT00839657.).

Clopidogrel and warfarin pharmacogenetic tests: what is the evidence for use in clinical practice?

PURPOSE OF REVIEW

To review the most promising genetic markers associated with the variability in the safety or efficacy of warfarin and clopidogrel and highlight the verification and validation initiatives for translating clopidogrel and warfarin pharmacogenetic tests to clinical practice.

RECENT FINDINGS

Rapid advances in pharmacogenetics, continuous decrease in genotyping cost, development of point-of-care devices and the newly established clinical genotyping programs at several institutions hold the promise of individualizing clopidogrel and warfarin based on genotype. Guidelines have been established to assist clinicians in prescribing clopidogrel or warfarin dose based on genotype. However, the clinical utility of clopidogrel and warfarin is still limited. Accordingly, large randomized clinical trials are underway to define the role of clopidogrel and warfarin pharmacogenetics in clinical practice.

SUMMARY

Pharmacogenetics has offered compelling evidence toward the individualization of clopidogrel and warfarin therapies. The rapid advances in technology make the clinical implementation of clopidogrel and warfarin pharmacogenetics possible. The clinical genotyping programs and the ongoing clinical trials will help in overcoming some of the barriers facing the clinical implementation of clopidogrel and warfarin pharmacogenetics.

Personalized Medicine in the Context of Comparative Effectiveness Research

The world of patient-centered outcomes research (PCOR) seems to bridge the previously disjointed worlds of comparative effectiveness research (CER) and personalized medicine (PM). Indeed, theoretical reasoning on how information on medical quality should inform decision making, both at the individual and the policy level, reveals that personalized information on the value of medical products is critical for improving decision making at all levels. However, challenges to generating, evaluating and translating evidence that might lead to personalization need to be critically assessed. In this paper, I discuss two different concepts of personalized medicine - passive personalization (PPM) and active personalization (APM) that are important to distinguish in order to invest efficiently in PCOR and develop objective evidence on the value of personalization that will aid in its translation. APM constitutes the process of actively seeking identifiers, which can be genotypical, phenotypical or even environmental, that can be used to differentiate between the marginal benefits of treatment across patients. In contrast, PPM involves a passive approach to personalization where, in the absence of explicit research to discover identifiers, patients and physicians "learn by doing" mostly due to the repeated use of similar products on similar patients. Benchmarking the current state of PPM sets the bar to which the expected value of any new APM agenda should be evaluated. Exploring processes that enable PPM in practice can help discover new APM agendas, such as those based on developing predictive algorithms based on clinical, phenotypical and preference data, which may be more efficient that trying to develop expensive genetic tests. It can also identify scenarios or subgroups of patients where genomic research would be most valuable since alternative prediction algorithms were difficult to develop in those settings. Two clinical scenarios are discussed where PPM was explored through novel econometric methods. Related discussions around exploring PPM processes, multi-dimensionality of outcomes, and a balanced agenda for future research on personalization follow.

VKORC1 Asp36Tyr geographic distribution and its impact on warfarin dose requirements in Egyptians

The VKORC1 Asp36Tyr single nucleotide polymorphism (SNP) is one of the most promising predictors of high warfarin dose, but data on its population prevalence is incomplete. We determined the frequency of this SNP in participants from seven countries on four continents and investigated its effect on warfarin dose requirement. One thousand samples were analysed to define the population prevalence of this SNP. Those samples included individuals from Egypt, Ghana, Sudan, Kenya, Saudi Arabia, Peru and African Americans from the United States. A total of 206 Egyptian samples were then used to investigate the effect of this SNP on warfarin dose requirements. This SNP was most frequent among Kenyans and Sudanese, with a minor allele frequency (MAF) of 6% followed by Saudi Arabians and Egyptians with a MAF of 3% and 2.5%, respectively. It was not detected in West Africans, based on our data from Ghana, and a large cohort of African Americans. Egyptian carriers of the VKORC1 Tyr36 showed higher warfarin dose requirement (57.1 ± 29.4 mg/week) than those with the Asp36Asp genotype (35.8 ± 16.6 mg/week; p=0.03). In linear regression analysis, this SNP had the greatest effect size among the genetic factors (16.6 mg/week increase in dose per allele), and improved the warfarin dose variability explained in Egyptians (model R2 from 31% to 36.5%). The warfarin resistant VKORC1 Asp36Tyr appears to be confined to north-eastern Africa and nearby Middle-Eastern populations, but in those populations where it is present, it has a significant influence on warfarin dose requirement and the percent of warfarin dose variability that can be explained.

Scores to predict major bleeding risk during oral anticoagulation therapy: a prospective validation study

BACKGROUND

Clinical scores may help physicians to better assess the individual risk/benefit of oral anticoagulant therapy. We aimed to externally validate and compare the prognostic performance of 7 clinical prediction scores for major bleeding events during oral anticoagulation therapy.

METHODS

We followed 515 adult patients taking oral anticoagulants to measure the first major bleeding event over a 12-month follow-up period. The performance of each score to predict the risk of major bleeding and the physician's subjective assessment of bleeding risk were compared with the C statistic.

RESULTS

The cumulative incidence of a first major bleeding event during follow-up was 6.8% (35/515). According to the 7 scoring systems, the proportions of major bleeding ranged from 3.0% to 5.7% for low-risk, 6.7% to 9.9% for intermediate-risk, and 7.4% to 15.4% for high-risk patients. The overall predictive accuracy of the scores was poor, with the C statistic ranging from 0.54 to 0.61 and not significantly different from each other (P=.84). Only the Anticoagulation and Risk Factors in Atrial Fibrillation score performed slightly better than would be expected by chance (C statistic, 0.61; 95% confidence interval, 0.52-0.70). The performance of the scores was not statistically better than physicians' subjective risk assessments (C statistic, 0.55; P=.94).

CONCLUSION

The performance of 7 clinical scoring systems in predicting major bleeding events in patients receiving oral anticoagulation therapy was poor and not better than physicians' subjective assessments.

Insurance coverage policies for personalized medicine

Adoption of personalized medicine in practice has been slow, in part due to the lack of evidence of clinical benefit provided by these technologies. Coverage by insurers is a critical step in achieving widespread adoption of personalized medicine. Insurers consider a variety of factors when formulating medical coverage policies for personalized medicine, including the overall strength of evidence for a test, availability of clinical guidelines and health technology assessments by independent organizations. In this study, we reviewed coverage policies of the largest U.S. insurers for genomic (disease-related) and pharmacogenetic (PGx) tests to determine the extent that these tests were covered and the evidence basis for the coverage decisions. We identified 41 coverage policies for 49 unique testing: 22 tests for disease diagnosis, prognosis and risk and 27 PGx tests. Fifty percent (or less) of the tests reviewed were covered by insurers. Lack of evidence of clinical utility appears to be a major factor in decisions of non-coverage. The inclusion of PGx information in drug package inserts appears to be a common theme of PGx tests that are covered. This analysis highlights the variability of coverage determinations and factors considered, suggesting that the adoption of personal medicine will affected by numerous factors, but will continue to be slowed due to lack of demonstrated clinical benefit.

CYP2C9 and VKORC1 polymorphisms influence warfarin dose variability in patients on long-term anticoagulation

OBJECTIVES

The main aim of this study was to determine whether CYP2C9 and VKORC1 polymorphisms influence warfarin dose variability during initial dose-finding phase and during maintenance treatment after 360 days.

METHODS

Two hundred and six consecutive patients who were beginning warfarin therapy were selected. They were assessed for general and clinical characteristics; prescribed warfarin dose; response to therapy on days 7-10, 30, 60, 180, and 360; adverse events; and CYP2C9 2, 3, 5, 6, 8, 11, and VKORC1 1639G >A assays.

RESULTS

During the first 30 days of anticoagulation, the relative variability of warfarin dose was significantly associated with CYP2C9*2 and CYP2C9*3 polymorphisms (p = 0.02) and with VKORC1 1639G >A genotypes (p = 0.04). Warfarin variability was also statistically different according to predicted metabolic phenotype and to VKORC1 genotypes after 360 days of treatment, and in the phase between 180 and 360 days (long-term dose variability). Both CYP2C9 and VKORC1 polymorphisms were associated with the international normalized ratio (INR) made between 7 and 10 days/initial dose ratio, adjusted for covariates (p < 0.01 and p = 0.02, respectively). Patients carrying VKORC1 and CYP2C9 variants presented lower required dose (at the end of follow-up of 360 days) compared to patients carrying wild-type genotypes (p = 0.04 and p = 0.03, respectively).

CONCLUSIONS

Genetic information on CYP2C9 and VKORC1 is important both for the initial dose-finding phase and during maintenance treatment with warfarin.

CYP2C9 and VKORC1 polymorphisms are differently distributed in the Brazilian population according to self-declared ethnicity or genetic ancestry

BACKGROUND

Warfarin-dosing pharmacogenetic algorithms have presented different performances across ethnicities, and the impact in admixed populations is not fully known.

AIMS

To evaluate the CYP2C9 and VKORC1 polymorphisms and warfarin-predicted metabolic phenotypes according to both self-declared ethnicity and genetic ancestry in a Brazilian general population plus Amerindian groups.

METHODS

Two hundred twenty-two Amerindians (Tupinikin and Guarani) were enrolled and 1038 individuals from the Brazilian general population who were self-declared as White, Intermediate (Brown, Pardo in Portuguese), or Black. Samples of 274 Brazilian subjects from Sao Paulo were analyzed for genetic ancestry using an Affymetrix 6.0(®) genotyping platform. The CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), and VKORC1 g.-1639G>A (rs9923231) polymorphisms were genotyped in all studied individuals.

RESULTS

The allelic frequency for the VKORC1 polymorphism was differently distributed according to self-declared ethnicity: White (50.5%), Intermediate (46.0%), Black (39.3%), Tupinikin (40.1%), and Guarani (37.3%) (p<0.001), respectively. The frequency of intermediate plus poor metabolizers (IM+PM) was higher in White (28.3%) than in Intermediate (22.7%), Black (20.5%), Tupinikin (12.9%), and Guarani (5.3%), (p<0.001). For the samples with determined ancestry, subjects carrying the GG genotype for the VKORC1 had higher African ancestry and lower European ancestry (0.14±0.02 and 0.62±0.02) than in subjects carrying AA (0.05±0.01 and 0.73±0.03) (p=0.009 and 0.03, respectively). Subjects classified as IM+PM had lower African ancestry (0.08±0.01) than extensive metabolizers (0.12±0.01) (p=0.02).

CONCLUSIONS

The CYP2C9 and VKORC1 polymorphisms are differently distributed according to self-declared ethnicity or genetic ancestry in the Brazilian general population plus Amerindians. This information is an initial step toward clinical pharmacogenetic implementation, and it could be very useful in strategic planning aiming at an individual therapeutic approach and an adverse drug effect profile prediction in an admixed population.

Clinical Pharmacogenomics of Warfarin and Clopidogrel

Genetic polymorphisms significantly influence responses to warfarin and clopidogrel. Polymorphisms in the cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase genes change warfarin pharmacokinetics and pharmacodynamics, respectively. Because these polymorphisms influence warfarin dose requirements, they may primarily help determine therapeutic warfarin doses in patients who newly start on the drug. To assist in estimating therapeutic warfarin doses, the warfarin label provides a pharmacogenomic dosing table and various warfarin pharmacogenomic dosing algorithms are available. On the other hand, polymorphisms in the CYP2C19 gene affect clopidogrel pharmacokinetics. These polymorphisms may be useful to identify clopidogrel nonresponders who may benefit from taking an alternative antiplatelet agent such as prasugrel and ticagrelor. Although both drugs have pharmacogenomic tests available for clinical use, their clinical utilities have not been established and are currently being actively studied. In this review, clinical application of warfarin and clopidogrel pharmacogenomics will be focused. With the current level of evidence, potential patients who may get benefit from warfarin and clopidogrel pharmacogenomic testing will be discussed. In addition, the interpretation of the warfarin and clopidogrel test results and the current barriers to widespread use of warfarin and clopidogrel pharmacogenomic testing will be discussed.

Role of pharmacogenomics in the management of traditional and novel oral anticoagulants

Warfarin is the most commonly prescribed oral anticoagulant. However, it remains a difficult drug to manage mostly because of its narrow therapeutic index and wide interpatient variability in anticoagulant effects. Over the past decade, there has been substantial progress in our understanding of genetic contributions to variable warfarin response, particularly with regard to warfarin dose requirements. The genes encoding for cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) are the major genetic determinants of warfarin pharmacokinetics and pharmacodynamics, respectively. Numerous studies have demonstrated significant contributions of these genes to warfarin dose requirements. The CYP2C9 gene has also been associated with bleeding risk with warfarin. The CYP4F2 gene influences vitamin K availability and makes minor contributions to warfarin dose requirements. Less is known about genes influencing warfarin response in African-American patients compared with other racial groups, but this is the focus of ongoing research. Several warfarin pharmacogenetic dosing algorithms and United States Food and Drug Administration-cleared genotyping tests are available for clinical use. Clinical trials are ongoing to determine the clinical utility and cost-effectiveness of genotypeguided warfarin dosing. Results from these trials will likely influence clinical uptake and third party payer reimbursement for genotype-guided warfarin therapy. There is still a lack of pharmacogenetic data for the newly approved oral anticoagulants, dabigatran and rivaroxaban, and with other oral anticoagulants in the research and development pipeline. These data, once known, could be of great importance as routine monitoring parameters for these agents are not available.

Pharmacogenetics in type 2 diabetes: potential implications for clinical practice

Pharmacogenetic research aims to study how genetic variation may influence drug efficacy and/or toxicity; pharmacogenomics expands this quest to the entire genome. Pharmacogenetic findings may help to uncover new drug targets, illuminate pathophysiology, clarify disease heterogeneity, aid in the fine-mapping of genetic associations, and contribute to personalized treatment. In diabetes, there is precedent for the successful application of pharmacogenetic concepts to monogenic forms of the disease, such as maturity onset diabetes of the young or neonatal diabetes. Whether similar insights will be produced for the common form of type 2 diabetes remains to be seen. With recent advances in genetic approaches, the successive application of candidate gene studies, large-scale genotyping studies and genome-wide association studies has begun to generate suggestive results that may lead to changes in clinical practice. However, many potential barriers to the translation of pharmacogenetic discoveries to the clinical management of diabetes still remain. Here, we offer a contemporary overview of the field in its current state, identify potential obstacles, and highlight future directions.

Bridging the efficacy-effectiveness gap: a regulator's perspective on addressing variability of drug response

Drug regulatory agencies should ensure that the benefits of drugs outweigh their risks, but licensed medicines sometimes do not perform as expected in everyday clinical practice. Failure may relate to lower than anticipated efficacy or a higher than anticipated incidence or severity of adverse effects. Here we show that the problem of benefit-risk is to a considerable degree a problem of variability in drug response. We describe biological and behavioural sources of variability and how these contribute to the long-known efficacy-effectiveness gap. In this context, efficacy describes how a drug performs under conditions of clinical trials, whereas effectiveness describes how it performs under conditions of everyday clinical practice. We argue that a broad range of pre- and post-licensing technologies will need to be harnessed to bridge the efficacy-effectiveness gap. Successful approaches will not be limited to the current notion of pharmacogenomics-based personalized medicines, but will also entail the wider use of electronic health-care tools to improve drug prescribing and patient adherence.

Statistical Optimization of Pharmacogenomics Association Studies: Key Considerations from Study Design to Analysis

Research in human genetics and genetic epidemiology has grown significantly over the previous decade, particularly in the field of pharmacogenomics. Pharmacogenomics presents an opportunity for rapid translation of associated genetic polymorphisms into diagnostic measures or tests to guide therapy as part of a move towards personalized medicine. Expansion in genotyping technology has cleared the way for widespread use of whole-genome genotyping in the effort to identify novel biology and new genetic markers associated with pharmacokinetic and pharmacodynamic endpoints. With new technology and methodology regularly becoming available for use in genetic studies, a discussion on the application of such tools becomes necessary. In particular, quality control criteria have evolved with the use of GWAS as we have come to understand potential systematic errors which can be introduced into the data during genotyping. There have been several replicated pharmacogenomic associations, some of which have moved to the clinic to enact change in treatment decisions. These examples of translation illustrate the strength of evidence necessary to successfully and effectively translate a genetic discovery. In this review, the design of pharmacogenomic association studies is examined with the goal of optimizing the impact and utility of this research. Issues of ascertainment, genotyping, quality control, analysis and interpretation are considered.