OSHP 4-17 (Gales)Gales)_… · Clinical Pharmacogenomics Barry J. Gales, Pharm.D. Professor, College of Pharmacy Southwestern Oklahoma State University barry.gales@swosu.edu Objectives
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Clinical Pharmacogenomics
Barry J. Gales, Pharm.D.Professor, College of Pharmacy
Southwestern Oklahoma State Universitybarry.gales@swosu.edu
Objectives
Explain the influence that pharmacogenomics has on drug metabolism.
Identify current resources for pharmacogenomics information.
Discuss clinical practice issues surrounding pharmacogenomics.
Review current status and future of pharmacogenomic testing.
Question 1
What region of a gene is responsible for coding for protein production?a. Exonb. Intronc. Regulatoryd. SNPs
Question 2
Where is the best place to get drug specific pharmacogenomic recommendations?a. Wikipediab. Human Genome Projectc. American College of Medical
Geneticsd. Clinical Pharmacogenetics
Implementation Consortium
Question 3
Which of the following are challenges to the implementation of pharmacogenomics?a. Lack of data standardizationb. Lack of EHR integrationc. Cost of testingd. Data variability and discordancee. All of the above
Definitions
Pharmacogenetics – monogenetic variants affecting drug response.
Pharmacogenomics – entire spectrum of genes that interact (enzymes, transport proteins, receptors) to determine drug response.
Terms are frequently used interchangeably
Precision/Personalized Healthcare/Medicine
Human Genome Project
Commissioned by Congress in 1988
Goal – sequence entire human genome by 2005
Initiated in 1990
Completed in 2003 – 99% of gene-containing sequence with a 99.9% accuracy.
Genome Research Resources
Human genome available at National Center for Biotechnology Information website.
International HapMap Project1000 Genomes project – catalog less common
genetic variantsPharmacogenomics Research Network
(PGRN)
Human Genome Facts
3.2 billion nucleotide base pairs
Base pairs code for ~ 22,000 protein-coding genes
Only 0.1% of base pair variation makes us individuals (99.9% genetically identical)
Can now sequence 40 billion bases/hour
Human Genome Facts
Codon – 3 consecutive nucleotides
Codons code for individual amino acids or amino acid chain termination
Substantial coding redundancy – GGC, GGG & GGT all code for glycine
20 amino acids form all human proteins
Human Genome Facts
A gene is a series of codons that specify for a particular protein
Gene regionsExons – encode for final protein
production (1% of genome)Introns – intervening noncoding regionsRegulatory – control gene transcription
Human Genome Facts
Alleles – sequence of nucleic acid bases at a given gene chromosomal locus.
Each gene locus made up of 2 alleles (parents)Homozygous genotype – 2 identical allelesHeterozygous genotype – 2 different allelesPhenotype is the outward expression of the
genotype
Types of Genetic Variations
Rare mutations (< 1% of population) – Cystic Fibrosis, hemophilia & Huntington’s
Polymorphisms (>1% of population) –responsible for most genetic variability in metabolic function or drug responses
Single-nucleotide polymorphisms
SNPs (snips) most common genetic variationOccur ~1/300 base pairsSNPs single base pair differences between individualsProteins &/or function maybe altered
Wild type allele – original or most common Variant allele – less common or variant copy
Drug Metabolizing Phenotypes
Ultra-rapid Metabolizer (UM)–rapidly convert prodrugs (toxicity) & clear drugs ( efficacy)
Extensive Metabolizer (EM) – normal patient
Intermediate Metabolizer (IM)
Poor Metabolizer (PM) – slowly convert prodrugs ( efficacy) & clear drugs (toxicity)
CYP2D6 Substrates
Analgesics – codeine & tramadol (prodrugs)Antiarrhythmics – propafenone & flecainideAntipsychotics – haloperidol & thioridazineBeta-blockers – carvedilol & metoprololSSRIs – fluoxetine, paroxetine & sertralineTCAs - amitrip, desip, imip & nortriptSERM – tamoxifen (prodrug)
CYP2D6 Polymorphism
PMs – 5-10% white population, don’t convert prodrugs or clear drugs
IMs – Asian and African populations, may require lower doses to be therapeutic
EMs – normal population, may be more susceptible to drug interactions
UMs – rapidly convert prodrugs (codeine -toxicity) & clear drugs ( efficacy)
CYP2C19 Substrates
SSRI – citalopram & escitalopramPPIs – lansoprazole, omeprazole,
pantoprazoleMiscellaneous
Clopidogrel (prodrug)CyclophosphamideDiazepamVoriconazole
CYP2C19 Polymorphism
PMs – [omeprazole] tenfold & H. pylori clearance, 13-23% Asian & 2-6% white
IMs – 10-30% of AsiansEMs – normal population, may be more
susceptible to drug interactionsUMs – may need higher doses of voriconizole
CYP2C9 Substrates
NSAIDS – diclofenac, ibuprofen, celecoxib,indomethacin, naproxen, piroxicam
Diabetic Agents – tolbutamide, glimepiride, glipizide, glyburide, nateglinide
Miscellaneous AgentsWarfarinPhenytoin
CYP2C9 Polymorphism
PMs – require phenytoin & warfarin doses, in whites vs. Asians & Africans
IMs – require phenytoin & warfarin doses, in whites vs. Asians & Africans
EMs – normal population, may be more susceptible to drug interactions
UMs – require phenytoin & warfarin doses
CYP2A6 Substrates
Nicotine – inability to metabolize nicotine associated with lower rates of smoking, amount smoked and greater success in being able to quit smoking.
CYP2A6 Polymorphism
PMs – 20% Asians vs. <1% whites, associated with reduced smoking rates
IMs – associated with reduced smoking ratesEMs – normal population, may be more
susceptible to drug interactionsUMs - ???
CYP2B6 Substrates
Cyclophosphamide & Ifosfamide
Efavirenz – NNRTIPMs & IMs experienced significant CNS ADRs at a higher rate while on efavirenz.
Efavirenz dose reduction reduced ADRs and was clinically efficacious.
Drug Transporter Gene PolymorphismsP-glycoprotein
throughout the body, digoxin, cyclosporine, tacrolimus, protease inhibitors, anthracyclines, vincaalkaloids, dexamethasone, phenytoin, phenobarbital
Solute carrier (SLC) – simvastatin
Drug Target Gene PolymorphismsReceptors – Beta-1 adrenergic receptor gene
(ADRB1)Enzymes – vitamin K oxidoreductase
(VKOR) & ACEIon Channels – K-ATP channelsIntracellular Signaling Proteins – G-Proteins
& GDP
American College of Medical Genetics (ACMG)Genomic sequencing is NOT a routine
screening test – targeted testing
Genomic sequencing identifies a causative variant in ~25% of tested patients
Genomic sequencing and result reporting should be done in conjunction with a geneticist
American College of Medical Genetics (ACMG)Incidental Findings Reporting (6.2% time)
57 genes tied to 24 disorders that can be treated by early interventions
Do not test children for adult onset diseases Only disclose disorders clearly tied to
genetic findings (near certainty) 3-5% “Non-father” findings
Genet Med 2013;15:565-74.
Clinical Pharmacogenetics Implementation Consortium (CPIC)International consortium providing guidance on how to use & incorporate existing pharmacogenetic data into the EHR NOTwhether to obtain pharmacogenetic data
CPIC guidelines & additional information are at the Pharmacogenomics Knowledge Base website (www.PharmGKB.org)
Published CPIC Guidelines
Do NOT address merit/need of/for testingUtilize a standard formatFull articles available on PharmGKB.orgPharmGKB.org summarizes genotypes,
phenotypes, implications, therapeutic recommendations & strength of recommendations
Actionable CPIC Guidelines
Abacavir Allopurinol Amitriptyline Atazanavir Azathioprine BoceprevirCapecitabine Carbamazepine Citalopram Clomipramine Clopidogrel CodeineDesipramine Doxepin EscitalopramFluoruracil Fluvoxamine Imipramine
Actionable CPIC Guidelines
Ivacaftor Mercaptopurine NortriptylineParoxetine PEG Interferon alfa - 2a & 2bPhenytoin Rasburicase Sertraline Simvastatin Tacrolimus TegafurThioguanine Trimipramine Warfarin
Clinical Genome Resource (ClinGen)
NIH sponsoredLaunched in 2013Genetic data from patients, clinicians,
laboratories and researchersAuthoritative central resource that defines the
clinical relevance of genomic variantsClinVar database developed to handle data
Clinical Genome Resource (ClinGen) Goals
Centralized shareable databaseStandardize annotation, interpretation and
weighting of genomic variantsAssess the “medical action ability” of variantsStructure genomic data for EHR useEnhance genomic use in diverse populationsDevelop expert panels to interpret data
Genomic Testing Results
52,000 adults followed for 5 years – 64.8% received a drug known to be influenced by pharmacogenomics (potential issue)
91% of patients had actionable results following 5 gene preemptive testing
Clin Pharmacol Ther 2012;92:235-42.
Genomic Testing Results
78% pediatric patients with actionable results following 4 gene preemptive testing
97% US patients with actionable results following 12 pharmacogene testing
738,000,000 RXs in 2013 for the 30 most common drugs with actionable results
Am J Med Genet C Semin Med Genet 2014;166C:45-55.Annu Rev Pharmacol Toxicol 2015;55:89-106.
Genomic Testing Results
5 CYP Isoenzymes
22,225 patients tested
20,534 patients with medication lists
Mean age 60y (1-108 y)
Mean # drugs 9.1 (1-49) Am J Health-Syst Pharm 2016;73:61-7
Genomic Testing Results
7% with NO at risk phenotype33% with ONE at risk phenotype41% with TWO at risk phenotypes17% with THREE at risk phenotypes2% with FOUR at risk phenotypes6 patients had FIVE at risk phenotypes
Genomic Testing Results
69.1% with at least one DDI, DGI or DDGI
8.9% with >1 “Change” interaction36.7% with >1 “Consider Change” interaction23.5% with >1 “Monitor” interaction30.9% with >1 “No Change” needed
Genomic Testing Results
Top 10 Interacting Drugs1. Metoprolol 2. Clopidogrel3. Hcodone/APAP 4. Warfarin5. Tramadol 6. Carvedilol7. Oxycodone 8. Omeprazole9. Citalopram 10. Bupropion
Clinical Practice Issues
Testing discordance between laboratories is not uncommon
Data is in silos not large usable poolsClinical presentation may be discordant with
genetic testing resultsData on UMs & PMs most useful currentlyHow to protect genetic patient information
Clinical Practice Issues
How do we determine what are “actionable findings”?
Does the action ability of findings differ for initiation of drug therapy vs. continuation of drug therapy?
Clinical Practice Issues
Will hospitals be expected to utilize/develop pharmacogenomic driven patient specific formularies?
Will insurers be expected to consider pharmacogenomics when making drug coverage and prior authorization decisions?
Clinical Practice Issues
Exome testing – sequences only protein producing section of the DNA. This is faster cheaper and the most common type of assay.
Genome testing – sequences whole DNA profile. Slower, more expensive but potentially may provide important data from the reactive region and introns we will need.
Reactive vs. Pre-emptive GenotypingReactive – ordered when a drug is being considered, delay in reporting, limited data (2C19 for clopidogrel)
Pre-emptive – data in EHR, more complete data, continuously available, less expensive in long run, requires good decision support software; Run at birth????
Question 1
What region of a gene is responsible for coding for protein production?a. Exonb. Intronc. Regulatoryd. SNPs
Question 2
Where is the best place to get drug specific pharmacogenomic recommendations?a. Wikipediab. Human Genome Projectc. American College of Medical
Geneticsd. Clinical Pharmacogenetics Implementation Consortium
Question 3
Which of the following are challenges to the implementation of pharmacogenomics?a. Lack of data standardizationb. Lack of EHR integrationc. Cost of testingd. Data variability and discordancee. All of the above
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