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Pharmacogenomics databases Nicky Mulder Some info extracted from slides from Russ Altman’s pharmacogenetics course What do we need? • Need machine learning and other tools for associating genotypes to phenotypes • Databases with useful info but also adequate security and privacy • Database of all known PK and PD genes • Knowledgebase of drugs, gene-drug interactions, dosing info, etc. • Tools for studying effects of SNPs • Tools to enable point of care usage Informatics issues in PG • Standards for data representation & exchange • Genes • Phenotype • High-throughput data • Analysis of literature • Find pgx papers • Extract gene-drug interactions • Integration of data from multiple sources • Gene sequence, protein sequence • SNP databases • Drug info databases • Representation and manipulation of pathways (PK & PD pathways) Standard terminologies for PGx • Need standard terminology/ontology for concepts: • Genes • Pathways • Drugs • Diseases • Symptoms (Adverse events) From PharmGKB Ontologies • Formal specification of terms with relationships between them • Usually organised in hierarchical structure • Terms should be defined • Allows unambigiuous naming of entities • Facilitates searching and data exchange Example ontologies • Gene Ontology (gene products) • Disease ontology • Phenotype ontology • Anatomy ontology • MESH terms • SNOMED Disease ontology • Developed to create a single structure for the classification of disease which unifies representation of disease among the many varied terminologies and vocabularies into a relational ontology • Originally (2003, 2004) based on ICD-9 code ICD = International Statistical Classification of Diseases and Related Health Problems developed by WHO • Organized into eight main nodes: • • • • • • Cellular proliferations e.g. cancer Mental health Anatomical entity Infectious agent e.g. anthrax Metabolism Genetic diseases DO example PATO: Phenotype and Trait Ontology • Generic ontology for describing traits or phenotypes that can be measured either quantitatively or qualitatively (e.g. bone length). • Species independent • Can be used in combination with a wide range of other ontologies • Consists of two main term types: • Attributes • Values • These are related to each other Human phenotype ontology • http://www.human-phenotype-ontology.org/ • standardized vocabulary of phenotypic abnormalities encountered in human disease • Developed using the medical literature, Orphanet, DECIPHER, and OMIM • Contains ~11,000 terms and >115,000 annotations to hereditary diseases Phenotype example SNOMED • http://www.nlm.nih.gov/research/umls/Snomed/snomed_main.html • Systematized Nomenclature of Medicine ->Clinical Terms • Arranged in a hierarchy with levels of specificity • Used in electronic health records SNOMED structure http://ihtsdo.org/fileadmin/user_upload/doc/download/doc_StarterGuide_Current-en-US_INT_20141202.pdf?ok Standard terminologies for PGx • Need standard terminology/ontology for concepts: • Genes • Pathways • Drugs • Diseases • Symptoms (Adverse events) From PharmGKB Genes and variants • Genes: • Human Genome Nomenclature Committee (http://www.genenames.org/) • GeneCards (http://www.genecards.org) • OMIM (http://www.omim.org/) • SNPs and their locations • • • • • dbSNP HapMap Human Genome Mutation Database HGVBase Ensembl, UCSC browser HGNC GeneCards Variant data GeneCards Variant data dbSNP Pathways • MetaCYC • KEGG • Reactome • Biocarta • And many others (including pathway display programs cytoscape, genmapp) Pathways from GeneCards Drug data • KEGG drug taxonomy: http://www.genome.jp/kegg/drug/ • DrugBank • PubChem • MedlinePlus • RxNorm • PHARMGKB includes all of these KEGG drug taxonomy • Has target-based classification: • • • • • • Antiinfectives Antineoplastics Antidiabetic agents Neuropsychiatric agents Anti-allergic agents Topical steroids • Has drug interaction database with known adverse drug-drug interactions associated with contraindications (CI) and precautions (P) • Drug-structure maps –development through chemical structure KEGG search for aspirin Aspirin page Interactions with other drugs Pharmacogonetics/genomics databases • Aim is to gather data on pharmaco-genes and pathways with links to relevant sources, e.g. drugs, gene info, variant info, etc. • Examples: • PharmaADME • ePKGene • PharmGKB PharmaADME • http://www.pharmaadme.org/joomla/ • List of drug metabolizing (ADME) genetic biomarkers applicable to pharmaceutical clinical trials & FDA • Developed by industry • Provides list of genes “to be screened to identify predictors of pharmacokinetic variability that could impact drug safety and efficacy in the current drug development process” • Genes grouped into four categories: • Phase I and II metabolism enzymes, responsible for the modification of functional groups and the conjugation with endogenous moieties respectively; • transporters, responsible for the uptake and excretion of drugs in and out of cells; • modifiers, that can either alter the expression of other ADME genes or affect the biochemistry of ADME enzymes ePKGene • https://www.druginteractioninfo.org/applications/pharmacogeneticsdatabase/ • Pharmacogenetics DB from U. Washington • Can search for a compound –links to PubChem • Provide gene(s) whose SNPs may affect response to drug • Provides info on populations • Can search by gene and get variants and their impact PharmGKB • https://www.pharmgkb.org/ • “PharmGKB is a comprehensive resource that curates knowledge about the impact of genetic variation on drug response for clinicians and researchers. ” • Can search genes, drugs, diseases and pathways • Includes variant annotations, drug-centred pathway, clinical info, drug dosage guidelines, gene-drug associations, etc • Uses ontologies What PharmGKB does • Annotates genetic variants and gene-drug-disease relationships from literature • Summarizes important pharmacogenomic genes, associations between genetic variants and drugs, and drug pathways • Curates FDA drug labels containing pharmacogenomic information • Curates and participates in writing pharmacogenomic-based drug dosing guidelines • Publishes pharmacogenomic-based drug dosing guidelines, important pharmacogene summaries and drug-centered pathways • Displays all information on the website and provides comprehensive downloads https://www.pharmgkb.org/page/overview PharmGKB link between genes and PK/PD https://www.pharmgkb.org/page/overview PharmGKB home page A tour through PharmGKB Search for CYP2D6 Downloads available from PharmGKB Summary • Pharmaco-related data includes: • • • • Genes, functions, variants Pathway Disease, phenotype, adverse effect Drugs • May be multiple entry points • Essential to use standard terminologies and ontologies • Aggregated into pharmacogenomics databases Personalized/precision medicine • Medicine is personal: • We are all different • Some of our differences translate into how we react to drugs as individuals • Therefore personalized medicine is important • Issues: • • • • Some people need twice the standard dose to be effective Drugs may work for some but not others Some people have side-effects others don’t Some people get diseases and others don’t • Goal: The Right Dose of The Right Drug for The Right Indication for The Right Patient at The Right Time.