PharmGKB and the International Warfarin Pharmacogenetics Consortium: The Changing Role for Pharmacogenomic Databases and Single-Drug Pharmacogenetics

Department of Genetics, Stanford University Medical Center, Stanford, California 94305, USA.
Human Mutation (Impact Factor: 5.14). 04/2008; 29(4):456-60. DOI: 10.1002/humu.20731
Source: PubMed


PharmGKB, the pharmacogenetics and pharmacogenomics knowledge base ( is a publicly available online resource dedicated to the dissemination of how genetic variation leads to variation in drug responses. The goals of PharmGKB are to describe relationships between genes, drugs, and diseases, and to generate knowledge to catalyze pharmacogenetic and pharmacogenomic research. PharmGKB delivers knowledge in the form of curated literature annotations, drug pathway diagrams, and very important pharmacogene (VIP) summaries. Recently, PharmGKB has embraced a new role--broker of pharmacogenomic data for data sharing consortia. In particular, we have helped create the International Warfarin Pharmacogenetics Consortium (IWPC), which is devoted to pooling genotype and phenotype data relevant to the anticoagulant warfarin. PharmGKB has embraced the challenge of continuing to maintain its original mission while taking an active role in the formation of pharmacogenetic consortia.

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    • ", efforts are being undertaken to include the in - formation available on biochemical pathways involved in the drug – microbiome interactions from the SEED ( Aziz et al . , 2012 ) and KEGG ( Kanehisa et al . , 2012 ) databases . Future plans include directly linking current interactions to existing pharmacogenomics databases [ e . g . , PharmGKB ( Owen et al . , 2008 ) , CTD ( Davis et al . , 2008 ) , and PACdb ( Gamazon et al . , 2010 ) ] and to human microbiome sequence databases ( Ge - vers et al . , 2012 ; Huang et al . , 2014 ) . Given the recency of the subject and the short time elapsed since the Pharmacomicrobiomics portal was publicly released , it remains difficult to evaluate the usabilit"
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    ABSTRACT: Abstract The Human Microbiome Project (HMP) is a global initiative undertaken to identify and characterize the collection of human-associated microorganisms at multiple anatomic sites (skin, mouth, nose, colon, vagina), and to determine how intra-individual and inter-individual alterations in the microbiome influence human health, immunity, and different disease states. In this review article, we summarize the key findings and applications of the HMP that may impact pharmacology and personalized therapeutics. We propose a microbiome cloud model, reflecting the temporal and spatial uncertainty of defining an individual's microbiome composition, with examples of how intra-individual variations (such as age and mode of delivery) shape the microbiome structure. Additionally, we discuss how this microbiome cloud concept explains the difficulty to define a core human microbiome and to classify individuals according to their biome types. Detailed examples are presented on microbiome changes related to colorectal cancer, antibiotic administration, and pharmacomicrobiomics, or drug-microbiome interactions, highlighting how an improved understanding of the human microbiome, and alterations thereof, may lead to the development of novel therapeutic agents, the modification of antibiotic policies and implementation, and improved health outcomes. Finally, the prospects of a collaborative computational microbiome research initiative in Africa are discussed.
    Omics: a journal of integrative biology 05/2014; 18(7). DOI:10.1089/omi.2014.0018 · 2.36 Impact Factor
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    • "Regardless of the choice of approach to identify the genotype-phenotype association, population variations in prevalence and relative importance of different allele variants, for example, CYP2D6, HLA-B, UGT1A1, and SLC6A4, remind investigators of the importance of ethnicity and population stratification [35] [36], which could magnify the sample size ISRN Pharmacology requirement for statistical power in most pharmacogenomic studies. For example, although the algorithms based on the work of Gage et al. [37] and the International Warfarin Pharmacogenetics Consortium (IWPC) [38] [39] are clinically useful, they do not include detection of the CYP2C9 * 8, an allele commonly occurring in African Americans. The lower success with algorithm-based dose prediction in African Americans [40] is likely related to exclusion of this allele in most dosing algorithms. "
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    ABSTRACT: The mapping of the human genome and subsequent advancements in genetic technology had provided clinicians and scientists an understanding of the genetic basis of altered drug pharmacokinetics and pharmacodynamics, as well as some examples of applying genomic data in clinical practice. This has raised the public expectation that predicting patients' responses to drug therapy is now possible in every therapeutic area, and personalized drug therapy would come sooner than later. However, debate continues among most stakeholders involved in drug development and clinical decision-making on whether pharmacogenomic biomarkers should be used in patient assessment, as well as when and in whom to use the biomarker-based diagnostic tests. Currently, most would agree that achieving the goal of personalized therapy remains years, if not decades, away. Realistic application of genomic findings and technologies in clinical practice and drug development require addressing multiple logistics and challenges that go beyond discovery of gene variants and/or completion of prospective controlled clinical trials. The goal of personalized medicine can only be achieved when all stakeholders in the field work together, with willingness to accept occasional paradigm change in their current approach.
    02/2013; 2013(8):641089. DOI:10.1155/2013/641089
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    • "PharmGKB ( Hernandez-Boussard et al. 2008 ; Giacomini et al. 2007 ; Kawamoto et al. 2009 ; Klein and Altman 2004 ; Owen et al. 2008 ; Thorn et al. 2005 ) is a web-based, public portal of genotype-phenotype information relevant to pharmacogenetics. PharmGKB editors collect, curate and disseminate data on human genetic variations which impact drug response. "
    Omics for Personalized Medicine, 01/2013: pages 187-211; Springer India., ISBN: 8132211839
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