Pharmacogenetics: From DNA to Dosage – Just A Click Away

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Pharmacogenetics From DNA to Dosage Just A
Click Away

• Cindy L. Vnencak-Jones, PhD, FACMGVanderbilt
  University Medical Center
• April, 2011

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DISCLOSURE INFORMATION
Cindy L Vnencak-Jones, PhD FACMG

• No relationships to disclose

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Pharmacogenetics From DNA To Dosage Just A
Click Away

• Pharmacogenetics
• influence of genetic variation on an individuals
  response to pharmacologic agents
• Pharmacogenetics testing is not routinely used in
  clinical practice
• when ordered, is done as needed preventing
  usefulness for initial dosing
• many drugs, many genes, many studies result in
  information overload for the provider

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Pharmacogenetics From DNA To Dosage Just A
Click Away

• PREDICT
• Pharmacogenomic Resource for Enhanced Decisions
  In Care and Treatment

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PREDICT Initiative

• Rationale

Provide real-time decision support thereby
facilitating individualized drug therapy to
maximize efficacy, minimize adverse drug
reactions, and reduce health care costs
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PREDICT Initiative

• Assemble multidisciplinary, multidepartment team
• Pathology, Informatics, Pharmacy, Clinicians,
  Ethics, Legal, Regulatory
• Proof of Concept
• Which drug/gene relationship should test the
  model?
• Genotyping
• Which methodology? Research or CLIA lab?
• Informatics
• Data management, Electronic health record,
  decision support
• Implementation 9/15/2010
• Assessment of the initiative ongoing
• Measure utility of decision support and clinical
  impact of genotyping

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PREDICT Initiative
Vanderbilt University
Office of Personalized Medicine
Vanderbilt Informatics Center
Ethics/Legal/ Regulatory
Pharmacy and Therapeutic Committee
PREDICT
VUMC Computational Genetics Core
Molecular Diagnostics Lab
Clinicians
Optimize Patient Management
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PREDICT Process Phase I

• Consent process
• Adult Admitting ED Registration
• CONSENT FOR ROUTINE TESTS, MEDICAL TREATMENT,
  AND GENETIC TESTS TO GUIDE DRUG THERAPY
• Provider discusses genotyping studies
• Blood drawn
• Sample arrives in laboratory
• DNA extracted (day 1)
• Assay performed (day 2)
• Results reviewed and released (day 3)

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PREDICT Process Phase I

• Raw data converted to drug genome interaction
  fact for computerized decision support in
  electronic health record (EHR)
• Provider accesses EHR alerted to results
• Provider receives decision support regarding
  dosing or alternative medications
• Provider optimizes patient management utilizing
  information provided by genotyping studies

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PREDICT Model

• Clopidogrel (PLAVIX) CYP2C19
• FDA issued a black box warning regarding the
  clinical relevance of genotype analysis
• Widely prescribed to patients at our medical
  facility
• Could provide decision support and measure the
  change in prescribing behavior of the provider
  based on the given decision support
• Targeted patient population to launch model
  the cardiac catheterization lab

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FDA Black Box WarningIssued March 12, 2010

• WARNING DIMINISHED EFFECTIVENESS IN POOR
  METABOLIZERS
• Effectiveness of Plavix depends on activation to
  an active metabolite by the cytochrome P450 (CYP)
  system, principally CYP2C19.
• Poor metabolizers treated with Plavix at
  recommended doses exhibit higher cardiovascular
  event rates following acute coronary syndrome
  (ACS) or percutaneous coronary intervention (PCI)
  than patients with normal CYP2C19 function.
• Tests are available to identify a patient's
  CYP2C19 genotype and can be used as an aid in
  determining therapeutic strategy.
• Consider alternative treatment or treatment
  strategies in patients identified as CYP2C19 poor
  metabolizers.

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Clopidogrel - PLAVIX

• Requires gastro-intestinal absorption and
  hepatic biotransformation
• Is an inhibitor to the P2RY12 receptor thereby
  preventing binding of ADP
• Increases risk of bleeding especially GI
  bleeding when combined with warfarin and
  nonsteroidal anti-inflammatory drugs

Simon T. et al, N Engl J Med 2009
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Clopidogrel - PLAVIX
CH3

• Antiplatelet therapy, often prescribed in
  combination with aspirin
• Initial dose 300 mg followed by 75 mg daily
• Indications for use acute coronary syndrome
  recent myocardial infarction or stroke
  peripheral arterial disease or patients managed
  following angioplasty, bypass surgery or stent
  placement

Prodrug
CH3
Active
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Drug Metabolizing Enzymes
Phase II Conjugation with endogenous substituents
to form Glucuronide Acetate Glutathione Sulfat
e Methionine
Phase I Modification of functional
groups Hydrolysis Oxidation Dealkylation Dehydro
genation Reduction Deamination Desulfuration
Evans and Relling, Science 1999
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VeraCode ADME Core Panel

• Absorption
• Distribution
• Metabolism
• Excretion

Illumina
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CYP2C19
Multiple polymorphic sites with clinical
significance
CYtochrome P450Family 2 Subfamily C polypeptide
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W120Rc.358TgtC
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X491Cc.1473AgtC
W212Xc.636GgtA
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g.-806CgtT
3
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3
5
Location 10q24.1 q24.3Gene 90,209
basesmRNA 1,473 Protein 490 amino acid
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2
5
c.681GgtAP681P
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c.395GgtAR132Q
c.1297CgtTR433W
c.1AgtGATGgtGTG
missense
truncation
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splicing
g.19294TgtA
promoter
initiation codon
insertion
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CYP2C19 Clopidogrel

• Patients with reduced function alleles have
• significantly lower levels of the active
  metabolite
• diminished platelet inhibition and higher rate of
  platelet aggregation
• higher rate of major adverse cardiovascular
  events and higher risk of stent thrombosis

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ADME Assay Design
Gene 1SNP-1
CCCTACACAGATGTGGTGCACGAGGTCCAGAGATACATTGACCTTCTCCC
CACCAGCCTGCCCCATGC GGGATGTGTCTACACCACGTGCTCCAGGTCT
CTATGTAACTGGAAGAGGGGTGGTCGGACGGGGTACG
A T
Gene 1SNP-2
Gene 1SNP-3
SNP-3
SNP-2
SNP-1
Patient 1
Patient 30
SNPs Optimized in 3 pools
control
- control
Adapted from Illumina
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Assay Primer Design
5
3
A
(1-20 nt gap)
G
Locus Specific Oligo
SNP
Locus Specific Oligos
A/G
GENOMIC DNA TEMPLATE
SNP
Adapted from Illumina
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Assay Allele Specific Extension and Ligation
T
GENOMIC DNA
SNP specific primer binds and is extended
Adapted from Illumina
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Assay PCR Amplification
Universal PCR Sequence 3
IllumiCode Sequence Tag
Biotin
Universal PCR Sequence 1
A
Primer specific for G with red dye does not bind
Adapted from Illumina
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VeraCode Technology the glass microbead

• Cylindrical glass microbeads
• 240 µm length x 28 µm diameter
• Bar-coded for identification

Adapted from Illumina
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Assay - Hybridization of PCR Products to VeraCode
Beads
IllumiCode 1
IllumiCode 2
SNP 1
SNP 2
Homozygous
Homozygous
Red and green signal detection with the
BeadXpress Reader
IllumiCode 3
SNP 3
Heterozygous
Adapted from Illumina
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BeadXpress Reader
Adapted from Illumina
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VeraCode Bead Loading Detection
CAPILLARY FORCE ATTRACTS BEADS INTO GROOVES
BEADS FALL INTO GROOVE PLATE
BEADS ALIGN TIGHTLY FOR OPTIMAL SCANNING
EFFICIENCY
Adapted from Illumina
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VeraCode Bead Plate Scanning
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Reports with Automatic Translation
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Visualization of the Results
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PREDICT Database
Samples with call rates gt97.34 Pass
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Electronic Health Record
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Electronic Health Record
Currently, CYP2C19 results sent to EHR, all other
data is stored but can be sent to EHR
in the future when drug genome interactions
decisions become actionable
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Electronic Prescription Order
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Electronic Prescription Order
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Clopidogrel Response

• Genetic Factors
• Polymorphisms in CYP2C19 and other CYPs, as well
  as SNPs in P2RY12,GpIIb/IIIa
• Cellular Factors
• P2RY12 and non P2Y pathways
• Clinical Factors
• Drug-drug interactions, elevated body mass,
  smoking, diabetes, poor compliance

CYP2C19 Genotype
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ADME QA/QC

• Allele frequencies of all genotypes
• Discordant results controls and repeat patients
  (which SNPs and frequency)
• Assay performance of samples per plate with
  average call rates lt97.30 (7/185 SNPs no call)
• Locus performance (lt95 call rates)

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PREDICT Results
9/15/10 - 4/4/11
11117
1,2 1,31,4 15
1718 112 217
1717
55 44 33 22
1419 patients
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Assay Accuracy
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Assay Reproducibility
150 patients repeated
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ADME QA/QC
Paragon controls
of plates
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Locus Performance (lt95 call rates)
80 plates
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Summary

• Implemented a mid-throughput assay to screen 34
  genes (185 SNPs) involved in drug absorption,
  distribution, metabolism and excretion
• Detected polymorphisms similar in frequencies to
  that previously reported
• Established QA/QC parameters for assay
• Developed a process to enable decision support to
  providers for drug dosing based on DNA findings
  which will facilitate genetically informed
  medicine

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Summary

• Implemented a scalable process to allow expansion
  to other actionable SNPs with associated decision
  support rules
• Process enables retrospective auto-population of
  stored data in patients EHR for future without
  the need for repeat testing
• Measure clinical utility and impact of genotyping
  data and decision support services
• Phase II - system permits identification of at
  risk patient populations for preemptive
  genotyping

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Acknowledgements

• Vanderbilt University
• Nicholas Zeppos - Chancellor
• Jeff Balser, MD, PhD Vice Chancellor VUMC
• Gordon Bernard, MD Vice Chancellor Research
• Office of Personalized Medicine
• Dan Roden, MD
• PREDICT Implementation Team
• Jill Pulley, MBA
• Russ Wilke, MD
• Jim Jirjis, MD
• Josh Peterson, MD
• John McPherson, MD
• Andrea, Ramirez, MD
• Mike Laposata, MD, PhD
• Center for Biomedical Ethics and Society

• Molecular Diagnostics Lab
• Gladys Garrison, MS
• Jennifer Carter, PhD
• Lisa Rocha
• Sonia Byon
• Vickie Fraser
• VUMC Computational Genetics Core
• Holli Dilks, PhD
• Doug Selph
• Brad Winfrey
• Vanderbilt Informatics Center
• Dan Masys, MD
• Joshua Denny, MD

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Pharmacogenetics From DNA to Dosage Just A
Click Away

• Cindy L. Vnencak-Jones, PhD, FACMGVanderbilt
  University Medical Center
• April, 2011