CYPs/Pharmacogenomics Flashcards
CYP3A4 (Polymorphisms, Key Features, Metabolizing Drugs, Inducers/Inhibitors)
MOST COMMON CYP-DEPENDENT REACTIONS 1. No Polymorphisms 2. Large Active site - binds multiple shapes 3. Metabolizes Benzodiazepines (-azolams & -azepams) with the help of CYP2C19 with -azepams Metabolizes Propanolol 4. Induced by Echinacea + St. John’s Wort (acts by nuclear receptor) 5. Metabolizes high doses of Acetaminophen (with CYP2E1 to produce bad NAPQI)
CYP2D6 (Polymorphisms, Key Features, Metabolizing Drugs, Inducers/Inhibitors)
- MOST COMMON POLYMORPHISMS AMONG ALL CYPS Poor Metabolizers: Inherit 2 mutant CYP2D6 alleles, low enzyme activity, standard drug active longer, need lower dose Ultra-Rapid Metabolizers: duplification/amplification of CYP2D6 allele, standard drug may not reach therapeutic level, need to raise dose 2. Metabolizes Metoprolol, Opioids (Hydrocodone + Codeine)*, CNS drugs *For pro-drug, poor metabolizers need higher dose and rapid metabolizers need smaller dose (actually need to consider alternative because dosing unpredictable according to CPIC)
CYP2C19 (Polymorphisms, Key Features, Metabolizing Drugs, Inducers/Inhibitors)
- Some polymorphisms 2. Metabolizes long-acting -azepams with CYP3A4 (functionalizes mLcs for glucuronidation, poor metabolizers have longer -azepam half-lives) Metabolizes Omeprazole (-prazoles) + Clopidogrel [Plavix] 3. Induced by Ginkgo + St. John’s Wort
CYP2C9 (Polymorphisms, Key Features, Metabolizing Drugs, Inducers/Inhibitors)
- Some polymorphisms 2. Metabolizes Warfarin (poor metabolism causes reduced clearance, change number of days required to determine stable anticoagulation) Metabolizes NSAIDS (Ibuprofen + Celecoxib) - poor metabolizers have reduced clearance
- Induced by Gingko + St. John’s Wort
CYP2E1 (Polymorphisms, Key Features, Metabolizing Drugs, Inducers/Inhibitors)
- No significant polymorphisms 2. Metabolize high doses of Acetaminophen to produce toxic NAPQI 3. Induced by St. John’s Wort, High Ethanol
Human CYP 450 Allele Nomenclature
Gene Superfamily - Family - Subfamily - Isoform - Allele CYP - 2 - D - 6 - *1
Reference Allele
*1 - reference allele *1 allele encodes for protein that performs reference amount of activity ““normal”” may not be the most prevalent allele depending on specific ethnic population
Pharmacogenetics v. Pharmacogenomics
Genetics: Drug effect influenced by ONE locus/gene - has Mendelian Inheritance Genomics: Drug effect influenced by MULTIPLE loci/genes, sometimes in combination with non-genetic factors (environment) - has unknown inheritance
Metabolizer Phenotypes
- Ultra Rapid: diplotype containing increased functioning alleleletype - usually gene duplication or amplification - copy number variant *1/*1xN
- Extensive: “normal” functioning, possess reference alleletypes or fully-functional variants
- Intermediate: abnormal functioning - slightly low or high - gray area
- Poor: contain partial functioning/non-functioning alleletype - gene deletion, nonsense mutations (missense cause partial function)
How Phenotypes affect Dosage for Standard Drugs and Pro-Drugs
Standard Drugs
Poor M: Less metabolism, high toxicity risk
Ultra Rapid M: More metabolism, low effectiveness
Pro-Drugs
Poor M: Less metabolism, low effectiveness
Ultra Rapid M: More metabolism, high toxicity risk
List 6 Examples of Inter-Individual Variability in Pharmacogenomics
- Codeine - affects biotransformation
- Clopidogrel - affects biotransformation
- Tacrolimus - affects elimination
- Thiopurine - affects elimination
- Warfarin - affects elimination
- Somatic Pharmacogenomics in Cancer
Somatic Pharmacogenomics in Cancer
(what somatic means, and give an example)
Somatic - cannot be inherited, cancer is an acquired disease
non-small cell lung cancer - hyperactivation of EGFR (an RTK) signaling - more cells divide and proliferate
treat: tyrosine kinase inhibitors - EGFR inhibition - effective at shrinking tumor
Secondary mutations make drug target site dysfunctional, less sensitive to drug, these few cells survive, then proliferate, causing tumor recurrence
CPIC
Guidelines for translating lab results into drug prescribing decisions
HOW results should be used to optimize drug therapy
Guidelines for dosing and dose adjusting based on lab results