Transcript Presentation

Pharmacogenetics:
From DNA to Dosage –
Just A Click Away
Cindy L. Vnencak-Jones, PhD, FACMG
Vanderbilt University Medical Center
April, 2011
DISCLOSURE INFORMATION
Cindy L Vnencak-Jones, PhD FACMG
No relationships to disclose
Pharmacogenetics:
From DNA To Dosage –
Just A Click Away
Pharmacogenetics:
• influence of genetic variation on an individual’s
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
Pharmacogenetics:
From DNA To Dosage –
Just A Click Away
PREDICT:
Pharmacogenomic Resource for Enhanced
Decisions In Care and Treatment
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
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
PREDICT Initiative
Office of
Personalized
Medicine
Pharmacy
and
Therapeutic
Committee
Vanderbilt University
Ethics/Legal/ Regulatory
PREDICT
Vanderbilt
Informatics
Center
VUMC
Computational
Genetics Core
Molecular
Diagnostics Lab
Clinicians
Optimize Patient Management
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)
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
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
FDA – Black Box Warning
Issued 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.
Clopidogrel - PLAVIX
Simon T. et al, N Engl J Med 2009
• 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 antiinflammatory drugs
Clopidogrel - PLAVIX
Prodrug
CH3
Active
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
Drug Metabolizing Enzymes
Phase I
Modification of
functional groups:
Hydrolysis
Oxidation
Dealkylation
Dehydrogenation
Reduction
Deamination
Desulfuration
Evans and Relling, Science 1999
Phase II
Conjugation
with
endogenous
substituents
to form:
Glucuronide
Acetate
Glutathione
Sulfate
Methionine
VeraCode ADME Core Panel
• Absorption
• Distribution
• Metabolism
• Excretion
ADME Core (34 genes, 185 markers)
ABCB1
CYP2C9
NAT1
SULT1A1
ABCC2
CYP2D6
NAT2
TPMT
ABCG2
CYP2E1
SLC15A2
UGT1A1
CYP1A1
CYP3A4
SLC22A1
UGT2B15
CYP1A2
CYP3A5
SLC22A2
UGT2B17
CYP2A6
DPYD
SLC22A6
UGT2B7
CYP2B6
GSTM1
SLCO1B1
VKORC1
CYP2C19
GSTP1
SLCO1B3
CYP2C8
GSTT1
SLCO2B1
Illumina
CYP2C19
Multiple polymorphic sites with clinical significance
W120R
c.358T>C
*8
g.-806C>T
*17
W212X
c.636G>A
CYtochrome P450
Family 2
Subfamily C
polypeptide 19
*3
X491C
c.1473A>C
*12
3’
5’
*4
c.1A>G
ATG>GTG
*6 *2 c.681G>A
c.395G>A
R132Q
*7
g.19294T>A
P681P
Location: 10q24.1 – q24.3
Gene: 90,209 bases
mRNA: 1,473
Protein: 490 amino acid
*5
c.1297C>T
R433W
missense
truncation
splicing
promoter
initiation codon
insertion
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
ADME Assay Design
Gene 1:SNP-1
CCCTACACAGATGTGGTGCACGAGGTCCAGAGATACATTGACCTTCTCCCCACCAGCCTGCCCCATGC
A
GGGATGTGTCTACACCACGTGCTCCAGGTCTCTATGTAACTGGAAGAGGGGTGGTCGGACGGGGTACG
T
Gene 1:SNP-2
Gene 1:SNP-3
SNP-3
SNP-2
Patient 1
Patient 30
SNP-1
SNPs Optimized in 3 pools
+ control
- control
Adapted from Illumina
Assay – Primer Design
Universal PCR Forward
Sequences (1, 2)
5’
A
Universal PCR Reverse
Sequence 3
3’
3’
G
SNP
(1-20 nt gap)
5’
Locus Specific Oligo
Locus Specific Oligos
A/G
IllumiCode ™
Sequence tag
identifies bead
GENOMIC DNA TEMPLATE
SNP
Adapted from Illumina
Assay – Allele Specific
Extension and Ligation
Polymerase
GENOMIC DNA
Universal PCR
Sequence 1
T
A
Ligase
SNP specific primer
binds and is extended
Universal PCR
Sequence 2
IllumiCode
Sequence Tag
Universal PCR
Sequence 3
G
Adapted from Illumina
Assay – PCR Amplification
Polymerase
IllumiCode
Sequence Tag
Universal PCR
Sequence 1
Universal PCR
Sequence 3
Biotin
Cy3
Universal Primer 1
Cy5
Universal Primer 2
A
Primer specific for G
with red dye does not bind
Adapted from Illumina
VeraCode Technology –
the glass microbead
• Cylindrical glass microbeads
• 240 μm length x 28 μm diameter
• Bar-coded for identification
Adapted from Illumina
Assay - Hybridization of PCR
Products to VeraCode Beads
A
IllumiCode 1
SNP 1
G
IllumiCode 2
A/A
SNP 2
Homozygous
IllumiCode 3
SNP 3
T
C
G/G
Homozygous
Red and green signal
detection with the
BeadXpress Reader
C/T
Heterozygous
Adapted from Illumina
BeadXpress Reader
Adapted from Illumina
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
VeraCode Bead Plate Scanning
Reports with Automatic Translation
Visualization of the Results
PREDICT Database
Samples with call rates
>97.34% “Pass”
Electronic Health Record
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”
Electronic Prescription Order
Electronic Prescription Order
Clopidogrel Response
CYP2C19 Genotype
RACE
*2*2
*2 HET
WT
Caucasian
5%
21%
74%
• Genetic Factors
– Polymorphisms in
CYP2C19 and other
CYPs, as well as SNPs
in P2RY12,GpIIb/IIIa
• Cellular Factors
African American
3%
24%
73%
Asian
7%
43%
50%
– P2RY12 and non P2Y
pathways
• Clinical Factors
– Drug-drug
interactions,
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 <97.30% (7/185 SNPs
no call)
• Locus performance (<95% call rates)
PREDICT Results
9/15/10 - 4/4/11
*1*1
*1*17
*1,*2
*1,*3
*1,*4
*1*5
*1*7
*1*8
*1*12
*2*17
*17*17
1419 patients
*5*5
*4*4
*3*3
*2*2
Assay Accuracy
Controls
Average
Concordance
Paragon Control
Cell Lines
99.58%
Coriell Control Cell
Lines
98.34%
Assay Reproducibility
150 patients repeated
ADME QA/QC
Paragon controls
# of plates
Locus Performance
(<95% call rates)
80 plates
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
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
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
Ellen Clayton, MD, JD
Kyle Brothers, MD
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
Ed Shultz, MD
Marc Beller
Pharmacogenetics:
From DNA to Dosage –
Just A Click Away
Cindy L. Vnencak-Jones, PhD, FACMG
Vanderbilt University Medical Center
April, 2011