Expectations, validity, and reality in pharmacogenetics

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

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

The art and science of drug titration

A “one-size-fits-all” approach has been the standard for drug dosing, in particular for agents with a wide therapeutic index. The scientific principles of drug titration, most commonly used for medications with a narrow therapeutic index, are to give the patient adequate and effective treatment, at the lowest dose possible, with the aim of minimizing unnecessary medication use and side effects. The art of drug titration involves the interplay of scientific drug titration principles with the clinical expertise of the healthcare provider, and an individualized, patient-centered partnership between the provider and the patient to review the delicate balance of perceived benefits and risks from both perspectives. Drug titration may occur as up-, down-, or cross-titration depending on whether the goal is to reach or maintain a therapeutic outcome, decrease the risk of adverse effects, or prevent withdrawal/discontinuation syndromes or recurrence of disease. Drug titration introduces additional complexities surrounding the conduct of clinical trials and real-world studies, confounding our understanding of the true effect of medications. In clinical practice, wide variations in titration schedules may exist due to a lack of evidence and consensus on titration approaches that achieve an optimal benefit-harm profile. Further, drug titration may be challenging for patients to follow, resulting in suboptimal adherence and may require increased healthcare-related visits and coordination of care amongst providers. Despite the challenges associated with drug titration, it is a personalized approach to drug dosing that blends science with art, and with supportive real-world outcomes-based evidence, can be effective for optimizing pharmacotherapeutic outcomes and improving drug safety.

If you build it, they will come: unintended future uses of organised health data collections

BACKGROUND

Health research increasingly relies on organized collections of health data and biological samples. There are many types of sample and data collections that are used for health research, though these are collected for many purposes, not all of which are health-related. These collections exist under different jurisdictional and regulatory arrangements and include: 1) Population biobanks, cohort studies, and genome databases 2) Clinical and public health data 3) Direct-to-consumer genetic testing 4) Social media 5) Fitness trackers, health apps, and biometric data sensors Ethical, legal, and social challenges of such collections are well recognized, but there has been limited attention to the broader societal implications of the existence of these collections.

DISCUSSION

Although health research conducted using these collections is broadly recognized as beneficent, secondary uses of these data and samples may be controversial. We examine both documented and hypothetical scenarios of secondary uses of health data and samples. In particular, we focus on the use of health data for purposes of: Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes

CONCLUSIONS

Current safeguards relating to the use of health data and samples include research ethics oversight and privacy laws. These safeguards have a strong focus on informed consent and anonymization, which are aimed at the protection of the individual research subject. They are not intended to address broader societal implications of health data and sample collections. As such, existing arrangements are insufficient to protect against subversion of health databases for non-sanctioned secondary uses, or to provide guidance for reasonable but controversial secondary uses. We are concerned that existing debate in the scholarly literature and beyond has not sufficiently recognized the secondary data uses we outline in this paper. Our main purpose, therefore, is to raise awareness of the potential for unforeseen and unintended consequences, in particular negative consequences, of the increased availability and development of health data collections for research, by providing a comprehensive review of documented and hypothetical non-health research uses of such data.

Pharmacogenomics in diverse practice settings: implementation beyond major metropolitan areas

AIM

The limited formal study of the clinical feasibility of implementing pharmacogenomic tests has thus far focused on providers at large medical centers in urban areas. Our research focuses on small metropolitan, rural and tribal practice settings.

MATERIALS & METHODS

We interviewed 17 healthcare providers in western Montana regarding pharmacogenomic testing.

RESULTS

Participants were optimistic about the potential of pharmacogenomic tests, but noted unique barriers in small and rural settings including cost, adherence, patient acceptability and testing timeframe. Participants in tribal settings identified heightened sensitivity to genetics and need for community leadership approval as additional considerations.

CONCLUSION

Implementation differences in small metropolitan, rural and tribal communities may affect pharmacogenomic test adoption and utilization, potentially impacting many patients. Original submitted 3 September 2014; Revision submitted 3 December 2014.

Alcohol misuse, genetics, and major bleeding among warfarin therapy patients in a community setting

PURPOSE

Little is known about the impact of alcohol consumption on warfarin safety, or whether demographic, clinical, or genetic factors modify risk of adverse events. We conducted a case-control study to assess the association between screening positive for moderate/severe alcohol misuse and the risk of major bleeding in a community sample of patients using warfarin.

METHODS

The study sample consisted of 570 adult patients continuously enrolled in Group Heath for at least 2 years and receiving warfarin. The main outcome was major bleeding validated through medical record review. Cases experienced major bleeding, and controls did not experience major bleeding. Exposures were Alcohol Use Disorders Identification Test Consumption Questionnaire (AUDIT-C) scores and report of heavy episodic drinking (≥5 drinks on an occasion). The odds of major bleeding were estimated with multivariate logistic regression models. The overall sample was 55% male, 94% Caucasian, and had a mean age of 70 years.

RESULTS

Among 265 cases and 305 controls, AUDIT-C scores indicative of moderate/severe alcohol misuse and heavy episodic drinking were associated with increased risk of major bleeding (OR = 2.10, 95% CI = 1.08-4.07; and OR = 2.36, 95% CI = 1.24-4.50, respectively). Stratified analyses demonstrated increased alcohol-related major bleeding risk in patients on warfarin for ≥1 year and in those with a low-dose genotype (CYP2C9*2/*3, VKORC1(1173G>A), CYP4F2*1), but not in other sub-groups evaluated.

CONCLUSIONS

Alcohol screening questionnaires, potentially coupled with genetic testing, could have clinical utility in selecting patients for warfarin therapy, as well as refining dosing and monitoring practices.

The role of expectations, hype and ethics in neuroimaging and neuromodulation futures

The production of expectations or future-goals for the development of techniques which “read” and modulate brain function, represent an important practical tool for neuroscientists. These visions-of-the-future assist scientists by providing focus for both individual and cross-disciplinary research programs; they encourage the development of new industrial sectors, are used to justify the allocation of government resources and funding, and via the media can help capture the imagination and support of the public. However, such expectations need to be tempered by reality. Over-hyping brain imaging and modulation will lead to disappointment; disappointment that in turn can undermine its potential. Similarly, if neuroscientists focus their attention narrowly on the science without concomitant consideration of its future ethical, legal and social implications, then their expectations may remain unrealized. To develop these arguments herein we introduce the theoretical concept of expectations and the practical consequences of expectations. We contextualize these reflections by referring to brain imaging and modulation studies on deception, which encompass the measurement-suppression-augmentation range.

Genetic risk factors for major bleeding in patients treated with warfarin in a community setting

The influence of warfarin pharmacogenomics on major bleeding risk has been little studied in long-term users and non-specialist care settings. We conducted a case-control study to evaluate associations between CYP2C9*2/*3, VKORC1(1173), and CYP4F2*3 variants and major bleeding among patients treated with warfarin in a community setting. We calculated major bleeding odds ratios, adjusting for race, duration of warfarin use, age, gender, and body mass index. In 265 cases and 305 controls with 3.4 and 3.7 mean years of warfarin use, respectively, CYP4F2*3 was associated with decreased major bleeding risk (odds ratio: 0.62; 95% confidence interval: 0.43-0.91). CYP2C9*2/*3 and VKORC1(1173) had null associations overall, but there was a nonsignificant increase in major bleeding risk in patients with duration <6 months (odds ratio: 1.30; 95% confidence interval: 0.60-2.83; odds ratio: 1.23; 95% confidence interval: 0.57-2.64, respectively). In summary, in the largest study of warfarin pharmacogenomics and major bleeding to date, we found a 38% lower risk in patients with CYP4F2*3, potentially reflecting interaction with warfarin and dietary vitamin K intake and warranting additional evaluation.

Genome-wide association studies in pharmacogenomics: successes and lessons

OBJECTIVE

As genotyping technology has progressed, genome-wide association studies (GWAS) have matured into efficient and effective tools for mapping genes underlying human phenotypes.

METHODS

Recent studies have shown the utility of the GWAS approach for examining pharmacogenomic traits, including drug metabolism, efficacy, and toxicity.

RESULTS

Application of GWAS to pharmacogenomic outcomes presents unique challenges and opportunities.

CONCLUSION

In the current review, we discuss the potential promises and potential caveats of this approach specifically as it relates to pharmacogenomic studies. Concerns with study design, power and sample size, and analysis are reviewed. We further examine the features of successful pharmacogenomic GWAS, and describe consortia efforts that are likely to expand the reach of pharmacogenomic GWAS in the future.

Statin myotoxicity: a review of genetic susceptibility factors

The 3-hydroxy-3-methylglutaryl coenzyme A (HMGCoA) reductase inhibitors (statins) are among the most common medications prescribed worldwide, but their efficacy and toxicity vary between individuals. One of the major factors contributing to intolerance and non-compliance are the muscle side-effects, which range from mild myalgia through to severe life-threatening rhabdomyolysis. One way to address this is pharmacogenomic screening, which aims to individualize therapy to maximize efficacy whilst avoiding toxicity. Genes encoding proteins involved in the metabolism of statins as well as genes known to cause inherited muscle disorders have been investigated. To-date only polymorphisms in the SLCO1B1 gene, which encodes the protein responsible for hepatic uptake of statins, and the COQ2 gene, important in the synthesis of coenzyme Q10, have been validated as being strongly associated with statin-induced myopathy. The aim of this review is to summarize studies investigating genetic factors predisposing to statin myopathy and myalgia, as the first step towards pharmacogenomic screening to identify at risk individuals.

Are health technology assessments of pharmacogenetic tests feasible? A case study of CYP2D6 testing in the treatment of breast cancer with tamoxifen

This paper reports the process and experience of the design and conduct of a UK-based health technology assessment (HTA) of CYP2D6 pharmacogenetic testing to inform the targeted use of tamoxifen for the treatment of breast cancer. Examples of particular challenges for conducting a HTA are highlighted. It is clear from the HTA process described here that a common finding of similar future HTAs will have gaps in the evidence base, particularly in relation to evidence to inform cost–effectiveness. The lack of evidence is likely to be sufficiently large to result in extreme uncertainty and possibly decisions not to recommend a pharmacogenetic test for use in clinical practice. This has clear negative implications, which may hamper moving pharmacogenetic tests from the research environment into clinical practice and requires attention from both manufacturers of pharmacogenetic tests and key decision-makers responsible for market authorization and reimbursement.

Pharmacovigilance

Any substance that is capable of producing a therapeutic effect can also produce unwanted or adverse effects. It is important to understand the basic concepts related to Adverse Drug Reactions (ADRs): epidemiology, classification, predisposing factors, evaluation parameters, and surveillance methods. Pharmacovigilance is defined as the science and activities relating to the detection, evaluation, understanding, and prevention of ADRs or any other drug-related problems. It involves patients, medical professionals, the pharmaceutical industry, drug regulatory agencies, and academic scientists. Pharmacoinformatics, the application of information technology with regard to the drug design, development, and drug use has played a major role in the appropriate implementation of pharmacovigilance at industry, regulatory, and hospital levels. The functioning of international regulatory agencies and drug safety departments of pharmaceutical industries has been greatly influenced by pharmacoinformatics. Pharmacoinformatics has changed the way in which health care is practiced. Modern information technology can be used by health care professionals for various purposes and, thereby, make a substantial contribution to optimize the quality of medication use in institutions with due importance of safety. Pharmacoinformatics has a major influence in the development of pharmacogenetics and its individual applications including improving drug safety. Pharmacoinformatics will play a major role in the future development and practice of pharmacovigilance. The present chapter is aimed at providing the readers an insight into the importance and basic concepts of pharmacovigilance, and the process involved in it. Application of pharmacoinformatics in improving drug safety at various levels from an industry, regulatory and hospital perspective is discussed.

Ask the Experts: Pharmacogenomics and genome-wide association studies

Hakon Hakonarson is an associate professor of pediatrics at The University of Pennsylvania School of Medicine (PA, USA). He is a physician–scientist and director of The Children’s Hospital of Philadelphia’s Center for Applied Genomics, a high-throughput highly automated genotyping facility founded to identify the genetic causes of complex medical disorders in children, such as autism and cancer, with the objective of developing new therapies. The Center represents a US$40 million commitment from The Children’s Hospital of Philadelphia to genotype approximately 100,000 children; a research undertaking that has gained nationwide attention, including news features in prestigious newspapers and scientific journals. Hakonarson has an extensive track record in human genetics and has developed an international reputation among his peers. He has served previously in several senior posts in the biopharmaceutical industry and has been the principal and coprincipal investigator on several NIH-sponsored grants. He has published numerous high-impact papers on genomic discoveries and their translations in some of the most prestigious scientific medical journals. Time Magazine listed Hakonarson’s autism gene discovery, reported in Nature in 2009, among the top ten medical breakthroughs of that year. With over 15 years of experience in pioneering genomics and pharmacogenomics research, as well as genome-wide mapping and association studies, Hakonarson has intimate knowledge of the complexities of large-scale genomics projects and has put together the necessary infrastructure and workflow processes to unravel these complexities.

Getting our priorities straight: a novel framework for stakeholder-informed prioritization of cancer genomics research

PURPOSE

Prioritization of translational research on genomic tests is critically important given the rapid pace of innovation in genomics. The goal of this study was to evaluate a stakeholder-informed priority-setting framework in cancer genomics.

METHODS

An external stakeholder advisory group including patients/consumers, payers, clinicians, and test developers used a modified Delphi approach to prioritize six candidate cancer genomic technologies during a 1-day meeting. Nine qualitative priority-setting criteria were considered. We used a directed, qualitative content-analysis approach to investigate the themes of the meeting discussion.

RESULTS

Stakeholders primarily discussed six of the original nine criteria: clinical benefits, population health impacts, economic impacts, analytical and clinical validity, clinical trial implementation and feasibility, and market factors. Several new priority-setting criteria were identified from the workshop transcript, including "patient-reported outcomes," "clinical trial ethics," and "trial recruitment." The new criteria were incorporated with prespecified criteria to develop a novel priority-setting framework.

CONCLUSION

This study highlights key criteria that stakeholders can consider when prioritizing comparative effectiveness research for cancer genomic applications. Applying an explicit priority-setting framework to inform investment in comparative effectiveness research can help to ensure that critical factors are weighed when deciding between many potential research questions and trial designs.

Building the evidence base for decision making in cancer genomic medicine using comparative effectiveness research

The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. The aim of this study was to identify approaches to help stakeholders make evidence-based decisions and to describe potential challenges and opportunities in using CER to produce evidence-based guidance. We identified general CER approaches for genomic applications through literature review, the authors' experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Evidence generation and synthesis approaches used in CER include comparative observational and randomized trials, patient-reported outcomes, decision modeling, and economic analysis. Significant challenges to conducting CER in cancer genomics include the rapid pace of innovation, lack of regulation, and variable definitions and evidence thresholds for clinical and personal utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. CER offers a variety of methodological approaches that can address stakeholders' needs and help ensure an effective translation of genomic discoveries.

Commentary: Children and predictive genomic testing: disease prevention, research protection, and our future

Genetic testing offered by direct-to-consumer companies-herein referred to as "predictive genomic testing"--has come under federal scrutiny. Critics claim testing yields uninterpretable and potentially harmful information. Supporters assert individuals have a right to this information, which could catalyze preventive health actions. Despite contentions that predictive genomic testing is a tool of primary disease prevention, little discussion has focused on its use with children. This partly stems from concerns expressed in existing professional guidelines about the potential for psychological and behavioral harm to children engendered by predictive genetic tests for Mendelian diseases. Conducting research to understand the actual benefits and harms is important for policy development and practice guidance and can be ethically justified within the pediatric regulatory framework of research that offers a prospect of direct benefit. Child health psychologists are well poised to contribute to this research effort, and promote the translation of genomic discoveries to improve pediatric medicine.

The long-term results of using low-concentration atropine eye drops for controlling myopia progression in schoolchildren

PURPOSE

The purpose of this article was to evaluate the long-term efficacy of a low-concentration (LC) atropine eye drop regimen (0.05%-0.1%) for controlling myopia progression in schoolchildren.

METHODS

This retrospective, case-control study enrolled myopic schoolchildren who had been followed-up for at least 3 years from 1999 to 2007. Children who received LC doses of atropine eye drops [initial prescription 0.05%, if progression over -0.5 diopter (D) during a 6-month follow-up then changed to 0.1% atropine] every night at bedtime were included in the LC atropine group, and untreated children served as controls.

RESULTS

A total of 117 children were included in this study. The mean age was 8.4 years. There were 97 children in the LC atropine group and 20 children in the control group. The mean follow-up duration was 4.5 years. In a mixed model analysis, the adjusted myopia progression in the LC atropine group was -0.23 D/year, significantly lower than that of the control group, which was -0.86 D/year (P<0.001). About 80% of the treatment group had slow myopia progression (less than -0.5 D progression per year). In a multivariate analysis, factors such as initial spherical refraction with less myopia and treatment with LC atropine were significantly associated with less myopia progression, but age, sex, and initial astigmatism were not significantly associated (P<0.001, P<0.001, P=0.442, 0.494, and 0.547, respectively).

CONCLUSION

The results of this study demonstrate that long-term and regular instillation of LC atropine eye drops is effective for controlling myopia progression and provides a possible strategy for an initial myopia regimen.

Genomic medicine and neurology

The application of genetics to the understanding of neurology has been highly successful over the past several decades. During the past 10 years, tools were developed to begin genetic investigations into more common disorders such as Alzheimer disease, multiple sclerosis, autism, and Parkinson disease. The era of genomic medicine now has begun and will have an increasing effect on the daily care of common neurologic diseases. Thus it is important for neurologists to have a basic understanding of genomic medicine and how it differs from the traditional clinical genetics of the past. This article provides some basic information about genomic medicine and pharmacogenetics in neurology to help neurologists to begin to adopt these principles into their practice.

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.

Added predictive value of high-throughput molecular data to clinical data and its validation

Hundreds of 'molecular signatures' have been proposed in the literature to predict patient outcome in clinical settings from high-dimensional data, many of which eventually failed to get validated. Validation of such molecular research findings is thus becoming an increasingly important branch of clinical bioinformatics. Moreover, in practice well-known clinical predictors are often already available. From a statistical and bioinformatics point of view, poor attention has been given to the evaluation of the added predictive value of a molecular signature given that clinical predictors or an established index are available. This article reviews procedures that assess and validate the added predictive value of high-dimensional molecular data. It critically surveys various approaches for the construction of combined prediction models using both clinical and molecular data, for validating added predictive value based on independent data, and for assessing added predictive value using a single data set.

Pharmacogenetics of drug hypersensitivity

Drug hypersensitivity reactions and severe cutaneous adverse drug reactions, such as Stevens-Johnson syndrome and toxic epidermal necrolysis, are examples of serious adverse drug reactions mediated through a combination of metabolic and immunological mechanisms that could traditionally not have been predicted based on the pharmacological characteristics of the drug alone. The discovery of new associations between these syndromes and specific HLA has created the promise that risk for these reactions could be predicted through pharmacogenetic screening, thereby avoiding serious morbidity and mortality associated with these types of drug reactions. Despite this, several hurdles exist in the translation of these associations into pharmacogenetic tests that could be routinely used in the clinical setting. HLA-B*5701 screening to prevent abacavir hypersensitivity syndrome is an example of a test now in widespread routine clinical use in the developed world.

Genetic variations in human glutathione transferase enzymes: significance for pharmacology and toxicology

Glutathione transferase enzymes (GSTs) catalyze reactions in which electrophiles are conjugated to the tripeptide thiol glutathione. While many GST-catalyzed transformations result in the detoxication of xenobiotics, a few substrates, such as dihaloalkanes, undergo bioactivation to reactive intermediates. Many molecular epidemiological studies have tested associations between polymorphisms (especially, deletions) of human GST genes and disease susceptibility or response to therapy. This review presents a discussion of the biochemistry of GSTs, the sources-both genetic and environmental-of interindividual variation in GST activities, and their implications for pharmaco- and toxicogenetics; particular attention is paid to the Theta class GSTs.