Pharmacogenomics: advancing personalized medicine.

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Presentation transcript:

Pharmacogenomics: advancing personalized medicine

Pharmacogenomics Will allow: individualized medication use based on genetically determined variation in effects and side effects use of medications otherwise rejected because of side effects More accurate methods of determining appropriate dosage

Pharmacogenomics

Challenges to drug design

Drug responses are genetic! Drug metabolism/response can be monogenic – alteration of the key metabolizing enzyme can alter drug’s effect Drug responses are polymorphic – Drugs trigger downstream events that can vary among patients

Drug response curve

Variation in drug response is hereditary Variations in absorption rates Variations in drug metabolism Variations in drug inactivation/elimination Variation in target receptors

Genetic variants in drug metabolism Thiopurine methyltransferase “null variants” – incidence of about 1 in 300 – Pts. Cannot metabolize chemo drugs used to treat leukemia(6-mercaptopurine, 6- thioguanine & azathioprine) into their inactive methylated forms – Pts. Can be treated with times less chemo than commonly prescribed – Genotyping or functional enzyme assay is now the STANDARD PRACTICE in cancer centers

Warfarin = coumadin Warfarin inhibits vitamin K reductase, which is the enzyme responsible for recycling oxidated vitamin K back into the system. For this reason, drugs in this class are also referred to as vitamin K antagonists.

Warfarin Discovered 60 years ago and one of the most widely prescribed drugs in the world Intended to prevent and treat thromboembolisms – Afib, recurrent stroke, DVT, pulmonary embolism, heart valve prosthesis Multi-source anticoagulant – 1, 2, 2.5, 3, 4, 5, 6, 7.5 and 10 mg tablet strengths Significant increase in Rx’s over past 10 years especially in the elderly

Trends in Warfarin Use: 1.5-fold Increase (45%)

Safety of Warfarin Major risk is bleeding: frequent and severe 1.2 – 7 major bleeding episodes per 100 patients Responsible for 1 in 10 hospital admissions Relative risk of fatal extracranial bleeds %

Dosing of Warfarin is Complex Narrow therapeutic index – Small separation between dose-response curves for preventing emboli and excess coagulation Nonlinear dose-response (INR) – Small changes in dose may cause large changes in INR with a time lag Wide range (50x) of doses (2-112 mg/week) to achieve target INR of 2-3 – Patient intrinsic and extrinsic factors

DNA testing for Warfarin sensitivity The FDA Clinical Pharmacology Subcommittee of the Advisory Committee for Pharmaceutical Sciences has recommended testing for variations in the CYP2C9 and VKORC1 in patients requiring warfarin therapy. The drug label will reflect this recommendation soon.

Warfarin Metabolism Two polymorphic genes, CYP2C9 and VKORC1, affect warfarin metabolism and response. Allelic frequencies of these two genes are usually associated with ethnicity. Here are the concerns with prescribing warfarin to patients with CYP2C9 or VKORC1 polymorphisms: Overdose can result in bleeding which can be fatal. Under dose can result in thrombosis which can be fatal

VKORC1 Variants VKORC1 polymorphisms may explain up to 25% of patient variability in response to warfarin. Patients with VKORC1 polymorphisms are at risk for exaggerated anticoagulant response.

CYP2C9 variants take more time to achieve stable dosing, and are associated with increased risk of bleeding events. Low CYP2C9 activity results in higher plasma levels of warfarin so the patient is at risk for bleeding

Warfarin Sensitivity The Warfarin Sensitivity DNA Test determines the presence of specific variations in the CYP2C9 and VKORC1 genes that confer sensitivity to warfarin and thus significantly reduce the required maintenance dose. CYP2C9 is involved in warfarin metabolism and VKORC1 influences warfarin's anticoagulation effect through vitamin K.

Mechanistic Basis of Dosing Problem Large interindividual variability related to S-warfarin metabolism by CYP2C9 (genetics) – *1 (wild type), *2 and *3 (variant alleles) Genotype (N = 188) Prevalence % Enzyme Activity S/R Warfarin (mg/L) Weekly Doses (mg) Clearance/LB W (ml/min/kg) 2C9 *1/*1 63%100% 0.45 (0.11) 34.1 (19.5) (0.025) 2C9 *1/*X 31%50-70% 0.69 (0.28) 19.0 (10.8) (0.021) 2C9 *X/*X 6%10% 1.43 (0.63) 11.5 (7.2) (0.011) Herman et al, The Pharmacogenomics J 4:

Dosing Adjustments Based on Genotype-Specific S-Warfarin Clearance Stefanovic and Samardzija, Clin Chem & Lab Med, 42(1) 2004

Pharmacogenomics and asthma As many as two-thirds of patients with asthma may not attain full control of their asthma. Up to one-third of patients treated with inhaled corticosteroids (ICSs) may not achieve objective improvements in airway function However, not simple because host factors such as age, disease severity, concomitant drugs, and disease etiology, can affect responses.

Beta Agonists Beta 2-adrenergic receptor (2-AR) gene

Leukotriene Modifiers

Inhaled Corticosteroids Polymorphisms of TBX21 the gene coding for transcription factor T- bet (T-box expressed in T cells), associated with significant improvement in methacholine responsiveness in children with asthma.

Statins Subjects with the apoE*2 allele had greater lipid reductions with statin treatment

ACE inhibitors widely used drugs for treatment of hypertension, heart failure, and prevention of diabetic nephropathy A polymorphism occurs in the ACE gene in which the two alleles differ by the presence (insertion) or absence (deletion) of a 287 basepair insertion. The insertion/deletion (I/D)polymorphism has been noted to account for 47% of the variability in serum ACE levels DD homozygotes have the highest serum ACE levels.

SNPs = Single Nucleotide Polymorphisms Occur throughout the genome Occur about every 1,000 bases May be “linked” to differences in drug response Under intense study by pharmaceutical companies.

Pharmacogenomics will most likely use “panels” of polymorphisms to calculate the relative risk–benefit ratio of a particular therapeutic course for an individual patient

SNPs Characterization of SNPs may help in identifying subsets of individuals at risk for specific diseases SNPs may predict drug responses/adverse reactions

“therapy with the right drug at the right dose in the right patient”