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Certified Pharmacogenomics Pharmacist (CPxP) Review
A Review Guide for the Certified Pharmacogenomics Pharmacist (CPxP) Exam
CPIC: Clinical Pharmacogenetics Implementation Consortium
CYP: Cytochrome P450
DPYD: Dihydropyrimidine Dehydrogenase
ELSI: Ethical, Legal, and Social Implications
FDA: Food and Drug Administration
HLA: Human Leukocyte Antigen
IM: Intermediate Metabolizer
Indel: Insertion/Deletion
NM: Normal Metabolizer
NUDT15: Nudix Hydrolase 15
PGx: Pharmacogenomics
PharmGKB: Pharmacogenomics Knowledge Base
PM: Poor Metabolizer
SLCO1B1: Solute Carrier Organic Anion Transporter Family Member 1B1
SNP: Single Nucleotide Polymorphism
TPMT: Thiopurine S-methyltransferase
UM: Ultrarapid Metabolizer
VKORC1: Vitamin K Epoxide Reductase Complex Subunit 1
- Core Definition: Pharmacogenomics (PGx) is the study of how an individual's genes affect their response to drugs. The goal is to use this information to guide medication selection and dosing to improve efficacy and reduce adverse events.
- Key Terminology:
- Allele: A specific version or variant of a gene (e.g., a "normal function" allele vs. a "no function" allele).
- Genotype: An individual's pair of alleles for a specific gene (e.g., having one normal and one no function allele).
- Phenotype: The observable trait resulting from the genotype (e.g., being an "Intermediate Metabolizer" of a drug).
- Types of Genetic Variation: The most common type is a Single Nucleotide Polymorphism (SNP), a change in a single DNA base. Other types include insertions, deletions (indels), and copy number variations (having extra copies of a gene).
- Mechanisms of Action: Genetic variations typically affect a drug's response by altering its pharmacokinetics (what the body does to the drug) or its pharmacodynamics (what the drug does to the body).
- Pharmacokinetics: Variations in metabolic enzymes (like CYP2D6) or drug transporters (like SLCO1B1).
- Pharmacodynamics: Variations in the drug's target (like VKORC1 for warfarin) or in genes involved in hypersensitivity reactions (like HLA alleles).
- Metabolizer Phenotypes: Based on their genotype, individuals are categorized into phenotypes that predict enzyme activity:
- Poor Metabolizer (PM): Little to no enzyme function.
- Intermediate Metabolizer (IM): Decreased enzyme function.
- Normal Metabolizer (NM): Fully functional enzyme activity. Expected response.
- Ultrarapid Metabolizer (UM): Increased enzyme function, often due to gene duplication.
- CYP2D6: Metabolizes ~25% of all drugs, including many antidepressants, antipsychotics, beta-blockers, and opioids (e.g., codeine, tramadol). Highly polymorphic with many non-functional and reduced-function alleles.
- CYP2C19: Metabolizes drugs like clopidogrel, proton pump inhibitors, and some antidepressants (e.g., citalopram). The *2 and *3 alleles are common no-function variants, while the *17 allele is an increased-function variant.
- CYP2C9: The primary metabolizer of warfarin and many NSAIDs. The *2 and *3 alleles are common reduced-function variants that increase bleeding risk with standard warfarin doses.
- VKORC1: The molecular target of warfarin. A common SNP in the promoter region makes individuals more sensitive to warfarin, requiring lower doses to achieve a therapeutic INR.
- TPMT & NUDT15: Enzymes that metabolize thiopurine drugs (e.g., azathioprine, mercaptopurine). Individuals with reduced or no function are at high risk of life-threatening myelosuppression and require significant dose reductions.
- SLCO1B1: A drug transporter that helps move statins into the liver. A common variant reduces transporter function, leading to higher statin levels in the blood and a significantly increased risk of statin-induced myopathy.
- HLA Alleles: Human Leukocyte Antigens are involved in immune recognition. Specific variants, like HLA-B*57:01, are strongly associated with a severe hypersensitivity reaction to abacavir. Testing is mandatory before starting the drug. Another example is HLA-B*15:02 and carbamazepine-induced Stevens-Johnson syndrome.
- Star (*) Allele Nomenclature: The standardized naming system for genetic variants. The *1 allele is usually designated as the "wild-type" or normal function allele. Other numbers (e.g., *2, *4, *17) represent different variants.
- Genotype to Phenotype Translation: The core skill. This involves taking the patient's reported genotype (diplotype), such as *CYP2D6 *1/*4*, understanding the function of each allele (*1 = normal function, *4 = no function), and using a scoring system or guideline table to translate this into a predicted phenotype (Intermediate Metabolizer).
- Phenotype to Clinical Recommendation: Using the predicted phenotype to make an actionable clinical recommendation based on evidence-based guidelines (e.g., For a CYP2D6 Poor Metabolizer taking codeine, recommend an alternative analgesic because codeine will be ineffective).
- Limitations of Testing: It is critical to understand that PGx testing does not predict all adverse events or responses. It is one tool among many, and factors like drug interactions, comorbidities, and adherence are still critically important.
CYP2D6 Activity Score Calculation
For many CYP enzymes, an activity score is calculated by assigning a value to each allele and adding them together. This score is then used to determine the phenotype.
- Normal function alleles (e.g., *1, *2) = 1 point
- Reduced function alleles (e.g., *10, *41) = 0.5 points
- No function alleles (e.g., *3, *4, *5) = 0 points
Example: A patient with genotype CYP2D6 *1/*4 has an activity score of 1 + 0 = 1, which corresponds to an Intermediate Metabolizer phenotype.
$ \text{Activity Score} = (\text{Allele 1 Value}) + (\text{Allele 2 Value}) $
Phenotype Score Ranges (CPIC Example for CYP2D6)
The calculated activity score maps to a specific phenotype:
- Score 0: Poor Metabolizer (PM)
- Score 0.5: Intermediate Metabolizer (IM)
- Score 1.0 - 2.0: Normal Metabolizer (NM)
- Score >2.0: Ultrarapid Metabolizer (UM)
Clinical Pharmacogenetics Implementation Consortium (CPIC)
The leading source for evidence-based, peer-reviewed PGx guidelines. CPIC guidelines are designed to help clinicians understand how to use genetic test results to optimize drug therapy. They provide standardized phenotype definitions and actionable prescribing recommendations.
Pharmacogenomics Knowledge Base (PharmGKB)
A comprehensive online resource that collects, curates, and disseminates knowledge about the impact of human genetic variation on drug responses. It includes clinical guideline annotations, drug labels with PGx information, and summaries of key gene-drug associations.
FDA Table of Pharmacogenomic Biomarkers
A table maintained by the FDA that lists drugs with pharmacogenomic information in their official labeling. This can include information about genomic biomarkers related to therapeutic response, risk for adverse events, or dosing recommendations.
- Clopidogrel & CYP2C19: Clopidogrel is a prodrug that must be activated by CYP2C19. Patients who are CYP2C19 Poor or Intermediate Metabolizers have reduced antiplatelet effect and are at higher risk for major adverse cardiovascular events (e.g., stent thrombosis). Guidelines recommend considering alternative antiplatelet agents (e.g., prasugrel, ticagrelor).
- Warfarin & CYP2C9/VKORC1: This is a classic PGx example. CYP2C9 metabolizes warfarin, while VKORC1 is its target. Variants in both genes explain a significant portion of dose variability. PGx-guided dosing algorithms (e.g., from warfarindosing.org) use genotype information to predict a more appropriate starting dose.
- Statins & SLCO1B1: A common variant in the SLCO1B1 gene impairs the uptake of statins into the liver, increasing systemic exposure and the risk of myopathy. This is particularly important for simvastatin. Guidelines recommend lower starting doses or considering alternative statins for at-risk individuals.
- SSRIs & CYP2D6/CYP2C19: Many selective serotonin reuptake inhibitors (SSRIs) are metabolized by these enzymes. Poor Metabolizers may have increased drug levels and a higher risk of side effects, while Ultrarapid Metabolizers may have sub-therapeutic levels and treatment failure. Guidelines recommend alternative drugs or dose adjustments based on phenotype.
- Tricyclic Antidepressants (TCAs) & CYP2D6/CYP2C19: TCAs have a narrow therapeutic index. Poor Metabolizers are at high risk for toxicity (e.g., cardiotoxicity), while Ultrarapid Metabolizers may fail therapy. Dosing recommendations are strongly tied to genotype.
- Codeine/Tramadol & CYP2D6: Both are prodrugs that must be converted to their active opioid forms (morphine and O-desmethyltramadol, respectively) by CYP2D6.
- Poor Metabolizers: Will get little to no pain relief.
- Ultrarapid Metabolizers: Are at high risk for life-threatening opioid toxicity, even at standard doses. Guidelines recommend avoiding their use in both PMs and UMs.
- Thiopurines & TPMT/NUDT15: Used in oncology and autoimmune diseases. Variants in either gene can lead to profound, life-threatening bone marrow suppression. Genotype-guided dosing is the standard of care.
- Fluoropyrimidines (5-FU, Capecitabine) & DPYD: DPYD is the rate-limiting enzyme in the breakdown of these common chemotherapy drugs. Patients with reduced DPYD function are at high risk for severe toxicity.
- Testing Strategies:
- Reactive Testing: Testing for a specific gene after a drug has been selected.
- Preemptive Testing: Testing a panel of PGx genes preemptively and storing the results in the EHR to be used whenever a relevant drug is prescribed in the future.
- Clinical Workflow: Developing a process for ordering tests, receiving results, integrating results into the EHR as actionable CDS, and providing consultation to prescribers and patients.
- Ethical, Legal, and Social Implications (ELSI): Understanding key ethical issues, including patient privacy, genetic discrimination (protected by GINA in the US), data security, and ensuring equitable access to testing and interpretation.
- Translate Genotype to Action: The core competency is not just knowing the genes, but being able to translate a complex genetic report into a clear, concise, and actionable clinical recommendation for a specific patient.
- Be an Evidence-Based Guide: The field is full of hype. A CPxP must be grounded in the evidence, relying on high-quality resources like CPIC to differentiate between clinically validated gene-drug pairs and those with limited or emerging evidence.
- Genetics is Only One Piece of the Puzzle: Always maintain a holistic view of the patient. Genetic information must be integrated with other clinical factors like age, organ function, comorbidities, and interacting medications to make the best decision.
- Master of Communication: A CPxP must be able to explain complex genetic concepts in simple terms to both healthcare providers and patients, empowering them to make informed decisions without causing undue anxiety.
- Embrace Lifelong Learning: Pharmacogenomics is one of the most rapidly evolving fields in medicine. A commitment to continuous learning is essential to stay current with new guidelines, gene-drug associations, and testing technologies.
