liminfoPharmGKB Reference
Free reference guide: PharmGKB Reference
About PharmGKB Reference
The PharmGKB Pharmacogenomics Reference is a searchable guide to the PharmGKB knowledge base, covering CPIC (Clinical Pharmacogenetics Implementation Consortium) guidelines, gene-drug associations, clinical annotations, and evidence level classifications from 1A through Level 4.
This reference documents key pharmacogenes including CYP2D6, CYP2C19, CYP2C9, DPYD, TPMT/NUDT15, SLCO1B1, and HLA genes, with diplotype-to-phenotype conversion tables, star allele nomenclature, and genotype-based prescribing recommendations for drugs like Codeine, Clopidogrel, Warfarin, and Abacavir.
It also covers the PharmGKB REST API, bulk data downloads, DPWG guidelines comparison, drug label annotations (FDA/EMA), PK/PD pathway diagrams, allele frequency tables across ethnic populations, and the PharmCAT automated clinical annotation tool for VCF-based pharmacogenomic testing.
Key Features
- CPIC guideline levels (A through D) with gene-drug pair evidence classifications
- Detailed CYP2D6, CYP2C19, CYP2C9 pharmacogene profiles with star alleles and Activity Scores
- Diplotype-to-phenotype mapping for Normal, Intermediate, Poor, and Ultrarapid Metabolizers
- HLA gene drug hypersensitivity associations including HLA-B*57:01, HLA-B*15:02, HLA-B*58:01
- Clinical annotation structure with evidence levels 1A/1B/2A/2B/3/4 explained
- PharmGKB REST API endpoints and bulk data download formats (TSV, Creative Commons)
- Allele frequency comparison tables across European, African, and East Asian populations
- PharmCAT workflow from VCF input through star allele calling to CPIC-guided prescribing reports
Frequently Asked Questions
What is PharmGKB and what does this reference cover?
PharmGKB (Pharmacogenomics Knowledge Base) is a Stanford University-operated database of gene-drug-disease relationships. This reference covers its key components: CPIC guidelines, clinical annotations with evidence levels, major pharmacogenes (CYP2D6, CYP2C19, CYP2C9, HLA genes), star allele nomenclature, the REST API, and the PharmCAT interpretation tool.
What are CPIC guidelines and evidence levels?
CPIC (Clinical Pharmacogenetics Implementation Consortium) publishes genotype-based prescribing guidelines. Level A means a published guideline exists with actionable prescribing changes. Level B indicates a guideline is in progress with sufficient evidence. Level C has annotations with moderate evidence, and Level D has annotations with weak evidence. This reference details each level with specific gene-drug examples.
How do CYP2D6 metabolizer phenotypes affect drug prescribing?
CYP2D6 metabolizer status directly impacts drug efficacy and toxicity. Poor Metabolizers (PM, e.g., *4/*4) have reduced Codeine analgesic effect and Tamoxifen efficacy. Ultrarapid Metabolizers (UM, e.g., *1/*1xN) face increased Tramadol toxicity risk. Normal Metabolizers (NM, *1/*1) receive standard doses. Activity Scores from 0 to 3+ quantify enzyme function.
Which HLA gene variants require pre-treatment testing?
HLA-B*57:01 testing is required before Abacavir use to prevent hypersensitivity reactions. HLA-B*15:02 testing is recommended before Carbamazepine in Southeast Asian populations to prevent Stevens-Johnson Syndrome (SJS/TEN). HLA-B*58:01 testing is advised before Allopurinol. These are all CPIC Level A guidelines with clinical-grade recommendations.
What is the star allele nomenclature system?
Star alleles (*) are the standard naming convention for pharmacogene variants. *1 represents the wild-type (normal function) reference allele. Numbered variants (*2, *3, etc.) indicate specific mutations classified as Normal function, Decreased function, No function (Loss of Function), or Increased function (Gain of Function). PharmVar (pharmvar.org) maintains the definitive star allele definitions.
How does PharmCAT work for pharmacogenomic testing?
PharmCAT (Pharmacogenomics Clinical Annotation Tool) is an open-source tool developed by PharmGKB. It accepts VCF files as input, calls star alleles, converts diplotypes to phenotypes, matches results against CPIC guidelines, and generates prescribing recommendation reports. It automates the entire pharmacogenomic interpretation pipeline.
How can I access PharmGKB data programmatically?
PharmGKB provides a REST API at api.pharmgkb.org/v1/data with endpoints for genes (/gene?symbol=CYP2D6), drugs (/drug?name=warfarin), clinical annotations (/clinicalAnnotation), and guidelines (/guideline). Bulk downloads are also available in TSV format under Creative Commons BY-SA 4.0 license, covering clinical annotations, drug labels, pathways, and variant annotations.
What is the difference between CPIC and DPWG guidelines?
CPIC is a US-based consortium while DPWG (Dutch Pharmacogenetics Working Group) provides European-focused guidelines. Both offer genotype-based prescribing recommendations, but they may differ on specific gene-drug pairs. PharmGKB hosts comparison tables showing where CPIC and DPWG recommendations align or diverge, which this reference documents.