Advances in pharmacogenomic research and development

Technological achievements in the last 5 to 10 yr and their application to sequencing and polymorphism discovery in the human genome have fostered a renewed interest in the genetic basis of drug response. Consequently, the field of pharmacogenetics/pharmacogenomics has been gaining momentum, fueled not only on technology but also on results of empirical studies of the human genome and on genetic epidemiology studies of real drugs in patient populations. This review discusses some of the recent advances in pharmacogenomic research and development over the last few years that include understanding the architecture of the human genome, the creation of population deoxyribonucleic acid (DNA)/data banks, assessment of the clinical validity of genetic markers, and experience with regulatory aspects of pharmacogenomics.     

Translating pharmacogenomics: challenges on the road to the clinic

Pharmacogenomics is one of the first clinical applications of the postgenomic era. It promises personalized medicine rather than the established "one size fits all" approach to drugs and dosages. The expected reduction in trial and error should ultimately lead to more efficient and safer drug therapy. In recent years, commercially available pharmacogenomic tests have been approved by the Food and Drug Administration (FDA), but their application in patient care remains very limited. More generally, the implementation of pharmacogenomics in routine clinical practice presents significant challenges. This article presents specific clinical examples of such challenges and discusses how obstacles to implementation of pharmacogenomic testing can be addressed.     

'You don't make genetic test decisions from one day to the next'--using time to preserve moral space

The part played by time in ethics is often taken for granted, yet time is essential to moral decision making. This paper looks at time in ethical decisions about having a genetic test. We use a patient-centred approach, combining empirical research methods with normative ethical analysis to investigate the patients' experience of time in (i) prenatal testing of a foetus for a genetic condition, (ii) predictive or diagnostic testing for breast and colon cancer, or (iii) testing for Huntington's disease (HD). We found that participants often manipulated their experience of time, either using a stepwise process of microdecisions to extend it or, under the time pressure of pregnancy, changing their temporal 'depth of field'. We discuss the implications of these strategies for normative concepts of moral agency, and for clinical ethics.     

Pharmacogenomics: catechol O-methyltransferase to thiopurine S-methyltransferase

1. Pharmacogenomics is the study of the role of inheritance in variation in the drug response phenotype-a phenotype that can vary from adverse drug reactions at one end of the spectrum to lack of therapeutic efficacy at the other. 2. The thiopurine S-methyltransferase (TPMT) genetic polymorphism represents one of the best characterized and most clinically relevant examples of pharmacogenomics. This polymorphism has also served as a valuable "model system" for studies of the ways in which variation in DNA sequence might influence function. 3. The discovery and characterization of the TPMT polymorphism grew directly out of pharmacogenomic studies of catechol O-methyltransferase (COMT), an enzyme discovered by Julius (Julie) Axelrod and his coworkers. 4. This review will outline the process by which common, functionally significant genetic polymorphisms for both COMT and TPMT were discovered and will use these two methyltransferase enzymes to illustrate general principles of pharmacogenomic research-both basic mechanistic and clinical translational research-principles that have been applied to a series of genes encoding methyltransferase enzymes.     

Reading the runes of my genome: a personal exploration of retail genetics

Since 2007, retail genetic companies have offered personal genome scans: DNA testing based on single nucleotide polymorphisms (SNPs) which are interpreted to provide genetic risks of some common diseases and trait information. There is much discussion of the validity, benefits and risks of this testing, and its ethics and regulation, but little information about the experiences of those who have purchased this testing. This paper offers an autobiographical ethnography, describing the author's use of genome scans purchased from deCODEme and 23andMe. The genetic disease risks provided were generally very modest and there were significant variations in the risks from the two companies. Risks were skeptically interpreted through a frame of knowledge of family disease histories. It is suggested that this personal medicine is likely to disappoint and it does not live up to its claims. Rather than being empowering personalized medicine, these scans are a geneticized medicine of the genomic person.     

Rabbit indolethylamine N-methyltransferase three-dimensional structure prediction: a model approach to bridge sequence to function in pharmacogenomic studies

Pharmacogenomics is the study of the genetic basis for individual variation in response to drugs and other xenobiotics. Successful prediction of effects of genetic variations that change encoded amino acid sequences on protein function and their consequent biomedical implications depends on three-dimensional (3D) structures of the encoded amino acid sequences. To bridge sequence to function, thus facilitating an in-depth pharmacogenomic study, we tested the feasibility of the use of a semi-computational approach to predict 3D structures of rabbit and human indolethylamine N-methyltransferases (INMTs) from their amino acid sequences, which share less than 26% sequence identity with known protein 3D structures. Herein, we report 3D models of INMTs predicted by using the crystal structure of rat catechol O-methyltransferase as a template, testing of the models both computationally and experimentally, and successful use of the models in retrospective prediction of the effects of genetic polymorphisms and in identification of residues that contribute to observed species-specific differences in substrate affinity. The results encourage the use of the semi-computational approach to predict 3D protein structures for use in pharmacogenomic studies when de novo prediction of protein 3D structures from their amino acid sequences is still not feasible and X-ray crystallography and/or solution nuclear magnetic resonance spectroscopy can only determine 3D structures for a small number of known amino acid sequences.Electronic Supplementary Material available.     

Indirect Estimation of the Comparative Treatment Effect in Pharmacogenomic Subgroups

Evidence of clinical utility is a key issue in translating pharmacogenomics into clinical practice. Appropriately designed randomized controlled trials generally provide the most robust evidence of the clinical utility, but often only data from a pharmacogenomic association study are available. This paper details a method for reframing the results of pharmacogenomic association studies in terms of the comparative treatment effect for a pharmacogenomic subgroup to provide greater insight into the likely clinical utility of a pharmacogenomic marker, its’ likely cost effectiveness, and the value of undertaking the further (often expensive) research required for translation into clinical practice. The method is based on the law of total probability, which relates marginal and conditional probability. It takes as inputs: the prevalence of the pharmacogenomic marker in the patient group of interest, prognostic effect of the pharmacogenomic marker based on observational association studies, and the unstratified comparative treatment effect based on one or more conventional randomized controlled trials. The critical assumption is that of exchangeability across the included studies. The method is demonstrated using a case study of cytochrome P450 (CYP) 2C19 genotype and the anti-platelet agent clopidogrel. Indirect subgroup analysis provided insight into relationship between the clinical utility of genotyping CYP2C19 and the risk ratio of cardiovascular outcomes between CYP2C19 genotypes for individuals using clopidogrel. In this case study the indirect and direct estimates of the treatment effect for the cytochrome P450 2C19 subgroups were similar. In general, however, indirect estimates are likely to have substantially greater risk of bias than an equivalent direct estimate.     

Pharmacogenetics and pharmacogenomics: role of mutational analysis in anti-cancer targeted therapy

The goal of cancer pharmacogenomics is to obtain benefit from personalized approaches of cancer treatment and prevention. Recent advances in genomic research have shed light on the crucial role of genetic variants, mainly involving genes encoding drug-metabolizing enzymes, drug transporters and targets, in driving different treatment responses among individuals, in terms of therapeutic efficacy and safety. Although a considerable amount of new targeted agents have been designed based on a finely understanding of molecular alterations in cancer, a wide gap between pharmacogenomic knowledge and clinical application still persists. This review focuses on the relevance of mutational analyses in predicting individual response to antitumor therapy, in order to improve the translational impact of genetic information on clinical practice.     

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.     

Pharmacogenomics: Catechol O-Methyltransferase to Thiopurine S-Methyltransferase

1. Pharmacogenomics is the study of the role of inheritance in variation in the drug response phenotype—a phenotype that can vary from adverse drug reactions at one end of the spectrum to lack of therapeutic efficacy at the other.2. The thiopurine S-methyltransferase (TPMT) genetic polymorphism represents one of the best characterized and most clinically relevant examples of pharmacogenomics. This polymorphism has also served as a valuable “model system” for studies of the ways in which variation in DNA sequence might influence function.3. The discovery and characterization of the TPMT polymorphism grew directly out of pharmacogenomic studies of catechol O-methyltransferase (COMT), an enzyme discovered by Julius (Julie) Axelrod and his coworkers.4. This review will outline the process by which common, functionally significant genetic polymorphisms for both COMT and TPMT were discovered and will use these two methyltransferase enzymes to illustrate general principles of pharmacogenomic research—both basic mechanistic and clinical translational research—principles that have been applied to a series of genes encoding methyltransferase enzymes.     

Chapter 7: Pharmacogenomics

There is great variation in drug-response phenotypes, and a “one size fits all” paradigm for drug delivery is flawed. Pharmacogenomics is the study of how human genetic information impacts drug response, and it aims to improve efficacy and reduced side effects. In this article, we provide an overview of pharmacogenetics, including pharmacokinetics (PK), pharmacodynamics (PD), gene and pathway interactions, and off-target effects. We describe methods for discovering genetic factors in drug response, including genome-wide association studies (GWAS), expression analysis, and other methods such as chemoinformatics and natural language processing (NLP). We cover the practical applications of pharmacogenomics both in the pharmaceutical industry and in a clinical setting. In drug discovery, pharmacogenomics can be used to aid lead identification, anticipate adverse events, and assist in drug repurposing efforts. Moreover, pharmacogenomic discoveries show promise as important elements of physician decision support. Finally, we consider the ethical, regulatory, and reimbursement challenges that remain for the clinical implementation of pharmacogenomics.

What to Learn in This Chapter

• Interactions between drugs (small molecules) and genes (proteins)
• Methods for pharmacogenomic discovery
  • Association- and expression-based methods
  • Cheminformatics and pathway-based methods
• Database resources for pharmacogenomic discovery and application (PharmGKB)
• Applications of pharmacogenomics into a clinical setting

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

Adverse environmental conditions influence age-related innate immune responsiveness

Hutchinson-Gilford progeria syndrome (HGPS) is a rare premature aging disorder that belongs to a group of conditions called laminopathies which affect nuclear lamins. Mutations in two genes, LMNA and ZMPSTE24, have been found in patients with HGPS. The p.G608G LMNA mutation is the most commonly reported mutation. The aim of this work was to compile a comprehensive literature review of the clinical features and genetic mutations and mechanisms of this syndrome as a contribution to health care workers. This review shows the necessity of a more detailed clinical identification of Hutchinson-Gilford progeria syndrome and the need for more studies on the pharmacologic and pharmacogenomic approach to this syndrome.     

Pharmacogenetics of cardiovascular drugs.

Pharmacogenetics is a field aimed at understanding the genetic contribution to inter-patient variability in drug efficacy and toxicity. Treatment of cardiovascular disease is, in most cases, guided by evidence from well-controlled clinical trials. Given the solid scientific basis for the treatment of most cardiovascular diseases, it is common for patients with a given disease to be treated in essentially the same manner. Thus, the clinical trials have been very informative about treating large groups of patients with a given disease, but are slightly less informative about the treatment of individual patients. Pharmacogenetics and pharmacogenomics have the potential of taking the information derived from large clinical trials and further refining it to select the drugs with the greatest likelihood for benefit, and least likelihood for harm, in individual patients, based on their genetic make-up. In this paper, the current literature on cardiovascular pharmacogenetics is emphasised, and how the use of pharmacogenetic/pharmacogenomic information may be particularly useful in the future in the treatment of cardiovascular diseases is also highlighted.     

Implementation of Genetics to Personalize Medicine

Background: We stand on the verge of integrating individual genetic and genomic information into health care provision and maintenance to improve health, increase efficiency, and decrease costs. We are beginning to integrate information on inherited susceptibility, gene expression, and predicted pharmacogenomic response to refine our medical management.Objective: This article reviews the current utility of genetics and genomics in a wide array of clinical circumstances, considers the future applications, and defines some of the obstacles and potential solutions to clinical integration of genomic medicine.Methods: Using the search terms genetics, genomics, pharmacogenomics, newborn screening, long QT syndrome, BRCA1/BRCA2, maturity onset diabetes of youth, diabetes, hemochromatosis, coronary artery disease, copy number changes, genetic discrimination, and genetic education, the PubMed database was searched from January 2000 to March 2007 to identify pertinent articles. Search results were restricted to English-language and human studies.Results: Several areas of medicine have begun to incorporate genetics into clinical practice, including newborn screening and breast cancer risk stratification and treatment. Molecular genetic tests are, and will increasingly become, available for inherited arrhythmias, diabetes, cancer, coronary artery disease, and pharmacogenomics. However, there are many barriers to implementation, including the cost of testing, the genetic literacy of patients and health care providers, and concerns about genetic discrimination.Conclusion: Genetics and genomics will be increasingly utilized in every field of medicine; however, health care providers and patients must have realistic expectations about its predictive power and current limitations.     

Context, ethics and pharmacogenetics

Most of the literature on pharmacogenetics assumes that the main problems in implementing the technology will be institutional ones (due to funding or regulation) and that although it involves genetic testing, the ethical issues involved in pharmacogenetics are different from, even less than, 'traditional' genetic testing. Very little attention has been paid to how clinicians will accept this technology, their attitudes towards it and how it will affect clinical practice. This paper presents results from interviews with clinicians who are beginning to use pharmacogenetics and explores how they view the ethics of pharmacogenetic testing, its use to exclude some patients from treatment, and how this kind of testing fits into broader debates around genetics. In particular this paper examines the attitudes of breast cancer and Alzheimer's disease specialists. The results of these interviews will be compared with the picture of pharmacogenetics painted in the published literature, as a way of rooting this somewhat speculative writing in clinical practice.     

The relevance of alternative RNA splicing to pharmacogenomics

The importance of alternative RNA splicing in the generation of genetic diversity is now widely accepted. This article highlights how alternative RNA splicing can have an impact on drug efficacy and safety, and demonstrates its potential pharmacogenomic value. The analysis of the repertoire of alternative RNA splicing events could potentially identify markers of pharmacogenomic relevance with high sensitivity and specificity and also provides a route through which genes can be selected for single nucleotide polymorphism (SNP) genotyping. Recent methodological advances, including microarray and splice-dedicated expression profiling, have made it possible to perform high-throughput alternative splicing analyses.     

Evaluating online direct-to-consumer marketing of genetic tests: informed choices or buyers beware?

Commercialization of genetic technologies is expanding the horizons for the marketing and sales of genetic tests direct-to-consumers (DTCs). This study assesses the information provision and access requirements that are in place for genetic tests that are being advertised DTC over the Internet. Sets of key words specific to DTC genetic testing were entered into popular Internet search engines to generate a list of 24 companies engaging in DTC advertising. Company requirements for physician mediation, genetic counseling arrangements, and information provision were coded to develop categories for quantitative analysis within each variable. Results showed that companies offering risk assessment and diagnostic testing were most likely to require that testing be mediated by a clinician, and to recommend physician-arranged counseling. Companies offering enhancement testing were less likely to require physician mediation of services and more likely to provide long-distance genetic counseling. DTC advertisements often provided information on disease etiology; this was most common in the case of multifactorial diseases. The majority of companies cited outside sources to support the validity of claims about clinical utility of the tests being advertised; companies offering risk assessment tests most frequently cited all information sources. DTC advertising for genetic tests that lack independent professional oversight raises troubling questions about appropriate use and interpretation of these tests by consumers and carries implications for the standards of patient care. These implications are discussed in the context of a public healthcare system.     

The use of single-nucleotide polymorphism maps in pharmacogenomics

Single-nucleotide polymorphisms (SNPs), common variations among the DNA of individuals, are being uncovered and assembled into large SNP databases that promise to enable the dissection of the genetic basis of disease and drug response (i.e., pharmacogenomics). Although great strides have been made in understanding the diversity of the human genome, such as the frequency, distribution, and type of genetic variation that exists, the feasibility of applying this information to uncover useful pharmacogenomic markers is uncertain. The health care industry is clamoring for access to SNP databases for use in research in the hope of revolutionizing the drug development process. As the reality of using SNPs to uncover drug response markers is rarely addressed, this review discusses practical issues, such as patient sample size, SNP density and genome coverage, and data interpretation, that will be important for determining the applicability of pharmacogenomic information to medical practice.     

Improving the prediction of complex diseases by testing for multiple disease-susceptibility genes

Studies have argued that genetic testing will provide limited information for predicting the probability of common diseases, because of the incomplete penetrance of genotypes and the low magnitude of associated risks for the general population. Such studies, however, have usually examined the effect of one gene at time. We argue that disease prediction for common multifactorial diseases is greatly improved by considering multiple predisposing genetic and environmental factors concurrently, provided that the model correctly reflects the underlying disease etiology. We show how likelihood ratios can be used to combine information from several genetic tests to compute the probability of developing a multifactorial disease. To show how concurrent use of multiple genetic tests improves the prediction of a multifactorial disease, we compute likelihood ratios by logistic regression with simulated case-control data for a hypothetical disease influenced by multiple genetic and environmental risk factors. As a practical example, we also apply this approach to venous thrombosis, a multifactorial disease influenced by multiple genetic and nongenetic risk factors. Under reasonable conditions, the concurrent use of multiple genetic tests markedly improves prediction of disease. For example, the concurrent use of a panel of three genetic tests (factor V Leiden, prothrombin variant G20210A, and protein C deficiency) increases the positive predictive value of testing for venous thrombosis at least eightfold. Multiplex genetic testing has the potential to improve the clinical validity of predictive testing for common multifactorial diseases.