Pharmacogenetics: From DNA to Dosage –

Just A Click Away Cindy L. Vnencak-Jones, PhD, FACMGVanderbilt 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

PREDICT:Pharmacogenomic Resource for Enhanced Decisions In Care and Treatment

Pharmacogenetics: From DNA To Dosage –

Just A Click Away

RationaleProvide 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 teamPathology, Informatics, Pharmacy, Clinicians, Ethics, Legal, Regulatory

Proof of ConceptWhich drug/gene relationship should test the model?

GenotypingWhich methodology? Research or CLIA lab?

InformaticsData management, Electronic health record, decision support

Implementation – 9/15/2010Assessment of the initiative – ongoingMeasure utility of decision support and clinical impact of genotyping

PREDICT Initiative

PREDICTPREDICT

Office of Personalized

Medicine

Vanderbilt UniversityVanderbilt University VanderbiltInformatics

Center

Pharmacy and

Therapeutic Committee

VUMCComputational Genetics Core

Clinicians

Optimize Patient ManagementOptimize Patient Management

Molecular Diagnostics Lab

Ethics/Legal/ Regulatory

PREDICT Initiative

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

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

PREDICT Model

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.

FDA – Black Box WarningIssued March 12, 2010

Simon T. et al, N Engl J Med 2009

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

CH3

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

Active

Clopidogrel - PLAVIX

Evans and Relling, Science 1999

Phase IModification of

functional groups:

HydrolysisOxidation

DealkylationDehydrogenation

ReductionDeaminationDesulfuration

Phase IIConjugation

with endogenous substituents

to form:

GlucuronideAcetate

GlutathioneSulfate

Methionine

Drug Metabolizing Enzymes

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 SLCO2B1Illumina

Multiple polymorphic sites with clinical significance

Location: 10q24.1 – q24.3Gene: 90,209 bases

mRNA: 1,473Protein: 490 amino acid

5’ 3’

CYtochrome P450Family 2

Subfamily Cpolypeptide 19

*17

*4 *6 *2

*7

*8

*3*12

*5

g.-806C>T

W120Rc.358T>C

W212Xc.636G>A

c.1A>GATG>GTG

c.395G>AR132Q

g.19294T>A

c.681G>AP681P c.1297C>T

R433W

X491Cc.1473A>C

splicingpromoter

truncation

initiation codon

missense

insertion

CYP2C19

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

CCCTACACAGATGTGGTGCACGAGGTCCAGAGATACATTGACCTTCTCCCCACCAGCCTGCCCCATGCGGGATGTGTCTACACCACGTGCTCCAGGTCTCTATGTAACTGGAAGAGGGGTGGTCGGACGGGGTACG

Gene 1:SNP-2

Gene 1:SNP-1

AT

Gene 1:SNP-3

SNPs Optimized in 3 pools

SNP-3 SNP-2 SNP-1

Adapted from Illumina

Patient 1Patient 30

+ control

- control

Universal PCR ForwardSequences (1, 2)

GENOMIC DNA TEMPLATE

SNP

(1-20 nt gap)IllumiCode ™Sequence tagidentifies bead

Universal PCR ReverseSequence 3

Locus Specific Oligos

5’3’

5’3’

Locus Specific Oligo

A

G

A/G

Adapted from Illumina

SNP

Assay – Primer Design

Polymerase

TGENOMIC DNA

AUniversal PCR Sequence 1 IllumiCode

Sequence Tag

Universal PCR Sequence 3

Ligase

GUniversal PCR Sequence 2

Adapted from Illumina

SNP specific primer binds and is extended

Assay – Allele Specific Extension and Ligation

Cy3

Universal Primer 1

Universal Primer 2

Cy5

PolymeraseUniversal PCR Sequence 1

BiotinUniversal PCR Sequence 3

A

IllumiCode Sequence Tag

Adapted from Illumina

Primer specific for Gwith red dye does not bind

Assay – PCR Amplification

VeraCode Technology – the glass microbead

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

Adapted from Illumina

A/A G/G

IllumiCode 2

IllumiCode 3

C/T

IllumiCode 1

SNP 1 SNP 2

SNP 3

GA

TC

Assay - Hybridization of PCR Products to VeraCode Beads

Homozygous

Heterozygous

Homozygous

Adapted from Illumina

Red and green signaldetection with the BeadXpress Reader

BeadXpress Reader

Adapted from Illumina

VeraCode Bead Loading & Detection

BEADS FALLINTO GROOVE

PLATE

CAPILLARY FORCE ATTRACTS BEADS INTO GROOVES

BEADS ALIGN TIGHTLY FOR OPTIMAL SCANNING EFFICIENCY Adapted from Illumina

VeraCode Bead Plate Scanning

Reports with Automatic Translation

Visualization of the Results

Samples with call rates >97.34% “Pass”

PREDICT Database

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 Health Record

Electronic Prescription Order

Electronic Prescription Order

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

RACE *2*2 *2 HET WT

Caucasian 5% 21% 74%

African American 3% 24% 73%

Asian 7% 43% 50%

CYP2C19 Genotype

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)

*1*1*1*17

*1,*2*1,*3*1,*4*1*5

*1*7*1*8*1*12*2*17

*17*17

*5*5*4*4*3*3*2*2

1419 patients

9/15/10 - 4/4/11

PREDICT Results

Assay Accuracy

ControlsAverage

Concordance

Paragon Control Cell Lines

99.58%

Coriell Control Cell Lines

98.34%

Assay Reproducibility

150 patients repeated

# of plates

Paragon controls

ADME QA/QC

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

AcknowledgementsVanderbilt 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 LabGladys Garrison, MSJennifer Carter, PhDLisa RochaSonia ByonVickie Fraser

VUMC Computational Genetics CoreHolli Dilks, PhDDoug SelphBrad Winfrey

Vanderbilt Informatics CenterDan Masys, MDJoshua Denny, MDEd Shultz, MDMarc Beller

Pharmacogenetics: From DNA to Dosage –

Just A Click Away Cindy L. Vnencak-Jones, PhD, FACMGVanderbilt University Medical Center

April, 2011