Clinical genomics data standards for pharmacogenetics and pharmacogenomics

This special report concerns a talk on data standards given at a workshop entitled 'An International Perspective on Pharmacogenetics: The Intersections between Innovation, Regulation and Health Delivery', which was held by the Organization for Economic Co-operation and Development (OECD) on October 17-19, 2005, in Rome, Italy. The worlds of healthcare and life sciences (HCLS) are extremely fragmented in terms of their underlying information technology, making it difficult to semantically exchange information between disparate entities. While we have reached the point where functional interoperability is ubiquitous, we are still far from achieving true semantic interoperability where a receiving system can use incoming data as though it was created internally. The critical enablers of semantic interoperability are information standards dedicated to HCLS data, spanning all the way from biological research data to clinical research and clinical trials, and finally to healthcare clinical data. The challenge lies in integrating various data standards based on predetermined goals, thereby improving the quality of care provided to patients.     

Systems biology data analysis methodology in pharmacogenomics

Pharmacogenetics aims to elucidate the genetic factors underlying the individual's response to pharmacotherapy. Coupled with the recent (and ongoing) progress in high-throughput genotyping, sequencing and other genomic technologies, pharmacogenetics is rapidly transforming into pharmacogenomics, while pursuing the primary goals of identifying and studying the genetic contribution to drug therapy response and adverse effects, and existing drug characterization and new drug discovery. Accomplishment of both of these goals hinges on gaining a better understanding of the underlying biological systems; however, reverse-engineering biological system models from the massive datasets generated by the large-scale genetic epidemiology studies presents a formidable data analysis challenge. In this article, we review the recent progress made in developing such data analysis methodology within the paradigm of systems biology research that broadly aims to gain a 'holistic', or 'mechanistic' understanding of biological systems by attempting to capture the entirety of interactions between the components (genetic and otherwise) of the system.     

Information management systems for pharmacogenomics

The value of high-throughput genomic research is dramatically enhanced by association with key patient data. These data are generally available but of disparate quality and not typically directly associated. A system that could bring these disparate data sources into a common resource connected with functional genomic data would be tremendously advantageous. However, the integration of clinical and accurate interpretation of the generated functional genomic data requires the development of information management systems capable of effectively capturing the data as well as tools to make that data accessible to the laboratory scientist or to the clinician. In this review these challenges and current information technology solutions associated with the management, storage and analysis of high-throughput data are highlighted. It is suggested that the development of a pharmacogenomic data management system which integrates public and proprietary databases, clinical datasets, and data mining tools embedded in a high-performance computing environment should include the following components: parallel processing systems, storage technologies, network technologies, databases and database management systems (DBMS), and application services.     

Genetic association studies in epilepsy pharmacogenomics: lessons learnt and potential applications

Although epilepsy is one of the most common neurological disorders and genetic factors are well known to play a role in response to antiepileptic drug (AED) treatment, the study of the pharmacogenetics of epilepsy has received relatively little attention and has not resulted in clinical applications to date. Our improved understanding of the pathogenesis of epilepsy and the mechanism of action of AEDs, together with recent advances in genetics and decreasing genotyping costs, have now paved the way for a more systematic application of pharmacogenetics in the field of epilepsy. It is hoped that the resulting knowledge will lead to a more rational treatment of epilepsy, development of more efficacious AEDs, and facilitation of clinical trials of new AEDs. However, there are formidable practical, methodological and theoretical hurdles to overcome before pharmacogenomic information will have any major utility in the clinical setting. Here, we discuss the evidence for a genetic contribution to AED response, review current knowledge in epilepsy pharmacogenetics and discuss potential future avenues with their implications, both for the clinical treatment of epilepsy and new AED development.     

Stroke pharmacogenomics

Circulatory disease accounts for fifteen million deaths each year, of which stroke accounts for four and a half million- with an estimated nine million stroke survivors annually. The overall incidence rate of stroke is 2 to 2.5 per thousand adults with an approximate prevalence of 5 per thousand and an estimated 5-year risk of stroke recurrence of 15 to 40 percent. Conventional risk factors for stroke include: increasing age, hypertension, diabetes mellitus, smoking, increased body mass index, ischemic heart disease, heart failure, atrial fibrillation and lack of physical activity. Age is the strongest risk factor for both ischemic and haemorrhagic stroke with its incidence doubling for each successive decade after the age of fifty-five years. However, there is a substantial portion of patients with significant cerebrovascular disease who do not have any of these stroke risk-factors, leading to the speculation that there are other factors that have not been identified yet So as to improve diagnosis and treatment strategies, as well as to reduce the related public health burden, it could be helpful to successfully identify its extremely complex genetic determinants (polygenic, multiple genes play a role).

Pharmacogenetics is the field of pharmacology that deals with the influence of genetic variation on drug response by correlating gene expression and gene variants with the efficacy or toxicity of drugs. The principle drugs in stroke medicine are antithrombotics. The aim of this paper was to review the most commonly used drugs for stroke such as rtPA in the acute phase as well as antiplatelets and wafarin for secondary prophylaxis.     

Genetic contributions to alcohol use disorder treatment outcomes: a genome-wide pharmacogenomics study

Naltrexone can aid in reducing alcohol consumption, while acamprosate supports abstinence; however, not all patients with alcohol use disorder (AUD) benefit from these treatments. Here we present the first genome-wide association study of AUD treatment outcomes based on data from the COMBINE and PREDICT studies of acamprosate and naltrexone, and the Mayo Clinic CITA study of acamprosate. Primary analyses focused on treatment outcomes regardless of pharmacological intervention and were followed by drug-stratified analyses to identify treatment-specific pharmacogenomic predictors of acamprosate and naltrexone response. Treatment outcomes were defined as: (1) time until relapse to any drinking (TR) and (2) time until relapse to heavy drinking (THR; ≥ 5 drinks for men, ≥4 drinks for women in a day), during the first 3 months of treatment. Analyses were performed within each dataset, followed by meta-analysis across the studies (N = 1083 European ancestry participants). Single nucleotide polymorphisms (SNPs) in the BRE gene were associated with THR (min p = 1.6E−8) in the entire sample, while two intergenic SNPs were associated with medication-specific outcomes (naltrexone THR: rs12749274, p = 3.9E−8; acamprosate TR: rs77583603, p = 3.1E−9). The top association signal for TR (p = 7.7E−8) and second strongest signal in the THR (p = 6.1E−8) analysis of naltrexone-treated patients maps to PTPRD, a gene previously implicated in addiction phenotypes in human and animal studies. Leave-one-out polygenic risk score analyses showed significant associations with TR (p = 3.7E−4) and THR (p = 2.6E−4). This study provides the first evidence of a polygenic effect on AUD treatment response, and identifies genetic variants associated with potentially medication-specific effects on AUD treatment response.Subject terms: Predictive markers, Behavioural genetics     

High throughput genotyping technologies for pharmacogenomics

Genetic differences between individuals play a role in determining susceptibility to diseases as well as in drug response. The challenge today is first to discover the range of genetic variability in the human population and then to define the particular gene variants, or alleles, that contribute to clinically important outcomes. Consequently, high throughput, automated methods are being developed that allow rapid scoring of microsatellite alleles and single nucleotide polymorphisms (SNPs). Many detection technologies are being used to accomplish this goal, including electrophoresis, standard fluorescence, fluorescence polarization, fluorescence resonance energy transfer, and mass spectrometry. SNP alleles may be distinguished by any one of several methods, including single nucleotide primer extension, allele-specific hybridization, allele-specific primer extension, oligonucleotide ligation assay, and invasive signal amplification. Newer methods require less sample manipulation, increase sensitivity, allow more flexibility, and decrease reagent costs. Recent developments show promise for continuing these trends by combining amplification and detection steps and providing flexible, miniaturized platforms for genotyping.     

阿托伐他汀的药物基因组学研究进展

阿托伐他汀是目前临床上广泛使用的口服降脂药,其对冠心病的一级和二级预防具有重要作用;但其疗效以及不良反应存在显著的个体差异,这与药物相关基因的多态性有关。本文主要介绍了基因多态性在阿托伐他汀的代谢、转运以及不良反应等方面的作用。     

The genetics of aging-- implications for pharmacogenomics

Lifespan experiments of lower organisms and mammals along with recent studies of centenarians are making inroads into delineating genetic factors that determine the ability to achieve exceptional longevity. These models may be helpful for the discovery of both longevity-enabling genes as well as genes associated with increased propensity to develop specific diseases. Both academic and commercial laboratories are putting substantial resources into discovering such genes in order to better understand the genetic and environmental underpinnings of how some people age more slowly than others and markedly delay or even escape age-associated diseases.     

A pharmacogenomics primer

The human genome project and related research initiatives have enabled the identification of a significant number of genetic variants that are predictive of drug response and outcome (pharmacogenomic biomarkers). As yet, incorporation of routine pharmacogenomic testing into clinical practice has been relatively modest. Potential barriers to adoption include a relative lack of prospective controlled trials establishing the benefits of such testing, economic constraints, and ethical concerns, among others. Clinicians considering the use of pharmacogenomic testing in their practice also may be unfamiliar with the concepts and principles underlying this rapidly evolving discipline. Consequently, the purpose of this review is to provide the clinical pharmacologist with a primer on the principles and molecular mechanisms underlying pharmacogenomics. In addition, the methods currently being used to discover novel pharmacogenomic biomarkers and then apply these to clinical practice will be described.