OSAKA UNIVERSITY

1

Latest Achievement and Future Challenge on Pharmacogenomics

and Personalized Medicine

Clinical Application of Clinical Application of Pharmacogenomics (PGx) Pharmacogenomics (PGx)

Junichi Azuma, M.D.

Osaka University, Japan

OSAKA UNIVERSITY

2

Alcohol drinks and Individuals

Many individuals of Asian descent are extremely sensitive to even small doses of alcohol drinks, principally because of the different activity of key enzymes in different activity of key enzymes in alcohol metabolismalcohol metabolism. Those that seem to predispose individuals to unpleasant effects after alcohol consumption are common in certain ethnic groups including Asians.

OSAKA UNIVERSITY

3

Responses to drugs and Individuals

This phenomenon is not limited to the alcoholic beverages. It is well known that different people frequently show varied responses to drugsvaried responses to drugs. Even if a drug of the same amount is taken, an individual difference occurs in the effectivenesseffectiveness and degree of an adverse adverse drug reactiondrug reaction (ADR). Then unpredictable reactions that may result in significantly high morbidity and mortality may happen.

０４０１０４０４０１０４

OSAKA UNIVERSITY

4

Non responder　Disease　 　　Drug Class　　　　Non responder (%)

Asthma β2 adrenergic agonist 4～755-LO, LTD4

Cancer Various 70～100（breast,lung,brain) Depression SSRIs, Tricyclics, MAOs 20～40

Diabetes Sulfonylurea, Biguanides, 50～75Glitazones

Duodenal ulcer H2 antagonists, 20～70Proton pump inhibitors

Hyperlipidemia HMGCoA reductase, 30～75Resins, Niacin

Pharmacogenomics eds. Kalow, Tyndale, Meyer (p17, Marcel Dekker, May 2001)

OSAKA UNIVERSITY

5

Paradox of DrugDevelopment and Therapy

● Clinical trials for drug development

provide evidence of efficacy and

safety at usual doses in populations. populations.

● Physicians treat individual individual patientwho can vary widely in their response

to drug therapy.

Need PGx Test?Need PGx Test?

OSAKA UNIVERSITY

6

Internet survey on understanding and acceptance of pharmacogenetics in Japan

Purpose:

To identify the issues to solve in communication and education in pharmacogenetics in Japan

Study participants (number of expected responder):

500 from Yahoo internet monitors/panel (ca.200,000)

　　　

　　

Date: 13-18 April 2005

Contents: 22 questions with 4 messages

Principal Investigators: Azuma J, Tsutani K

20-29 30-39 40-49 50-59 60-69 Totalmale 50 50 50 50 50 250female 50 50 50 50 50 250Total 100 100 100 100 100 500

OSAKA UNIVERSITY

7

Q2: Have you ever heard about “Genome” ?　あなたは、「ゲノム」という言葉を聞いたことがありますか。

84

75

84

80

82

16

25

16

20

18

２０－２９

３０－３９

４０－４９

５０－５９

６０－６９

(n=116)

(n=117)

(n=113)

(n=111)

(n=120)

Yes No

(c) Azuma J, Tsutani K

OSAKA UNIVERSITY

8

Ｉｎｔｅｒindividual differences !　

• An effective rate of most drugs is roughly 60-70%, and "a non responder" exists inevitably. One of a cause of this interindividual difference includes a hereditary factor.

• It is important to realize that human genetic variability can affect one or more of the stages in drug response:

①　drug transporters　　　②　drug metabolizing enzymes　　　③　drug target molecules

OSAKA UNIVERSITY

9

Variation in Genes Encoding for Drug Metabolizing Enzyme Activity

GCCCG G CCTC

Patient A

Patient B

Concentration

Concentration

Time

Time

Same Dose

GCCCA A CCTC

Wild type

Mutation

Drug MetabolizingEnzyme

Drug MetabolizingEnzyme

however

High activity

Low activity

different plasma concentrations

OSAKA UNIVERSITY

10

Many CYP450 Enzymes Are Polymorphic: Example CYP 2D6

Family: CYP 2Subfamily: CYP 2D6Gene: CYP 2D6*1

Relative contribution of CYP isozymes and other enzymes to the phase I metabolism of drugs.

Responsible for metabolism of 40% of all Rx drugs

OSAKA UNIVERSITY

11

Metabolic pathway of Venlafaxine

O-desmethylvenlafaxine

HOOH

CH 3

CH 3

CH 2 N

CH 3 OOH

H

CH 3

CH 2 N

OH

CH 3

CH 3

CH 2 N

CH 3 O

CYP2D6Venlafaxine

N-desmethylvenlafaxine

(ODV)CYP3A

CYP２C19

OSAKA UNIVERSITY

12

Plasma concentration of venlafaxine

time(hr)

Venlafaxine

Plasma concentration (ng/ml)

0

50

100

150

200

0 5 10 15 20 25

Main metabolic enzyme likely to be CYP2D6, but

OSAKA UNIVERSITY

13

Main CYP2D6 polymorphism in Japanese population

CYP2D6*5

CYP2D6*4

CYP2D6*2

genotype activity

CYP2D6*10 Decreased

None

None

(≒Normal)

A deletion of the entire CYP2D6 gene

G1934AAberrant 3' splice recognition site

G4268CC2938T296Arg→Cys 486Ser→Thr

gene structure

34Pro→Ser

G4268CC188T486Ser→Thr

Exon with a mutation affecting the activityExon at least with one mutation

CYP2D6*1 Nomal

(%)

43.0

12.3

0.2

4.5

36.3

CYP2D6*36 Decreased

34Pro→Ser 6 AA changesC188T 1.8

OSAKA UNIVERSITY

14

Relationship between CYP2D6*10 andthe plasma concentration of venlafaxine

Venlafaxine

121110987654321 *1/*2*10/*10

*1/*1

*1/*10

*2/*10

*1/*2

*5/*10

*10/*10

*10/*10

*1/*10*1/*2

*2/*10

Plasma concentration (ng/ml)

200

150

100

50

0

time(hr)

0 5 10 15 20 25

OSAKA UNIVERSITY

15

Pharmacogenetics of CYP2D6

0

20

40

60

80

100

120

No. of subjects

Ultra-rapidmetabolism

Extensive metabolism

PoormetabolismCutoff

PM = 5-10 % Cauc Americans>1 % Japanese

Intermediatemetabolism

0 0.01 0.10 1 10 100

Debrisoquin:4-Hydroxydebrisoquin Metabolic Ratio

Adapted from: Bertilsson L et al, Clin Pharmacol Ther 51:388-97,1992

OSAKA UNIVERSITY

16

Treatment of Pulmonary Tuberculosis in Japan

• Approximately 20％ of the patients treated with Rifampicin and INH develop hepatotoxicity.

• Metabolic enzyme of INH is NAT2.• Rifampicin strongly induces many drug metabolizing enzymes.

OSAKA UNIVERSITY

17

Metabolic Pathways of IsoniazidMetabolic Pathways of Isoniazid

N-acetyltransferase2(NAT2)

Hydrolysis

amidase

Acetylation

Diacetylhydrazine（excretion）

Hydrazine

Acetylisoniazid

CONHNHCOCH3

NIsoniazid

(INH)

Isonicotinic acid

COOH

N

AcetylhydrazineNH2 NH2

N

CONHNH2

Hepatotoxicmajoralternative

OSAKA UNIVERSITY

18

Genetic polymorphism of NAT2

803481C→T

590G→A

857G→A

845341

191G→A

282C →T

T→C

434A→C

A→G

A→C

190C→T

499G→A

759C→T

* * *** * * **** * *

NAT2*5

859T→CDel

411

364

* * *111T→C

G→A

A→T

NAT2*6 NAT2*7

Active allele（wild）： NAT2*4

Low-active alleles（mutant）： NAT2* NAT2* NAT2*5 6 7

The 4 genotypes can explain almost all Japanese phenotypes.

Mutant alleles　0　→　 Rapid acetylator type (RA-type)

Mutant alleles　1　→　 Intermediate acetylator type (IA-type)

Mutant alleles　2　→　 Slow acetylator type (SA-type)*

OSAKA UNIVERSITY

19

INHINH--RFP induced hepatotoxicityRFP induced hepatotoxicity

How to Rationalize Dosing ？

INH＋RFP

slow acetylator　(SA type)　

　intermediate acetylator (IA type)

　rapid acetylator (RA type)

Continue

Change regimen

DelayedCured

Liver Toxicity Increase dose

OSAKA UNIVERSITY

20

Trough plasma concentration of INH in relation to NAT2 genotype

RA-type

Trough conc. of INH (mg/mL)Standard dose of INH

MIC0.05-0.2 mg/mL

0 2 4 6 8

Dose (mg/kg)

10

1

0.1

0.01

0.001

n=60 IA-type

IA-type + HTJapan 400 mg/daySA-type + HT(8 mg/kg/day)

Europe& USA

300 mg/day

(5 mg/kg/day)

Frequency of slow acetylator(SA-type)

Japanese 10 %

Caucasians 50 %

HT: hepatotoxicity

OSAKA UNIVERSITY

21

Next clinical trial for genotype based chemotherapy against pulmonary tuberculosis

Collectively, it could be proposed that the dose adjustment of INH based on NAT2 genotypes is a promising strategy for tuberculosis therapy. Based on the obtained results, optimum INH dose for appropriate plasma concentration was calculated once daily as follows, 450 mg for RA-type, 300 mg for IA-type and 150 mg for SA-type, respectively.　

IA-type300mg

RA-type450mg

SA-type150mg

(Once a day)

Trial groupINH dose

Control groupall

300mg

Prof. Dr. med. Uwe FuhrUniversity of Cologne

NAT2Gene chip

OSAKA UNIVERSITY

22

THE PRINCIPAL RESEARCH QUESTION

　　We want to examine whether a dose individualization based on NAT2 genotype may improve the risk/benefit ratio of isoniazid treatment in tuberculosis by reducing variation in drug concentrations. Specifically, our major hypotheses are that :

●　The incidence of drug-induced hepatotoxicity in subjects with 　no high activity NAT2 allele (SA)can be reduced.

●　The incidence of early treatment failure in subjects with two high activity NAT2 alleles (RA)can be reduced by a corresponding doseadjustment of isoniazid within the standard multi-drug therapy of tuberculosis.

●　As an additional research question, we want to quantitatively assess role of NAT2 genotype and other covariates (e.g. age, sex, body weight) in pharmaco-kinetics and –dynamics of isoniazid.

●　Finally, the impact of a NAT2-based isoniazid dose adjustment on the costs of healthcare will be evaluated.

OSAKA UNIVERSITY

23

Nicotine and CYP2A670ー80% of nicotine metabolized by CYP2A6

　CYP2A6 polymorphism

decreased

null

normal

Activity

21%

20%

49%

Frequency

CYP2A6 *9

CYP2A6 *4

Genotype

CYP2A6 *1

3’5’

3’5’

3’

T- 48G

5’

Blood concentration of nicotine varied depending on CYP2A6 polymorphism; Clin Pharmacol Ther, 2003,74,69-76

OSAKA UNIVERSITY

24

CPT-11 and UGT1A1 genepolymorphism

The patients with UGT1A1*28 are at higher risk for

severe toxicity by CPT-11.

SN-38

SN-38 G

UGT1A1(&1A7)

UGT1A1UGT1A1**2828(TA)6(TA)6→→(TA)7(TA)7Promoter regionPromoter region

Intestinal lumenBone marrow

Carboxylesterase

β-Glucuronidase

IrinotecanIrinotecanCPTCPT--1111

OSAKA UNIVERSITY

25

WARNINGS

Patients with Reduced UGT1A1 Activity

Individuals who are homozygous for the UGT1A1*28allele are at increased risk for neutropenia following initiation of CAMPTOSAR treatment. A reduced initial dose should be considered for patients known to be homozygous for the UGT1A1*28 allele (see DOSAGE AND ADMINISTRATION).

Heterozygous patients (carriers of one variant allele and one wild-type allele which results in intermediate UGT1A1 activity) may be at increased risk for neutropenia; however, clinical results have been variable and such patients have been shown to tolerate normal starting doses.

OSAKA UNIVERSITY

26

DOSAGE AND ADMINISTRATION

Dosing for patients with bilirubin >2 mg/dLcannot be recommended since such patients were not included in clinical studies.

A reduction in the starting dose by at least one level of CAMPTOSAR should be considered for patients known to be homozygous for the UGT1A1*28 allele (See CLINICAL PHARMACOLOGY and WARNINGS). The appropriate dose reduction in this patient population is not known.

OSAKA UNIVERSITY

27

Metabolism of bilirubin

Hemoglobin

Unconjugated bilirubin

spleen

Unconjugated bilirubin ＋ albumin

Direct (conjugated) bilirubin

RBC

UDPUDP--glucuronosyl transferase (UGT)1A1glucuronosyl transferase (UGT)1A1

polymorphism

PhenobarbitalLow calorie

into bile acid

into blood stream

OATP

MRP2MRP3

OSAKA UNIVERSITY

28

UGT1A1 Molecular Assay UGT1A1 GENE

TATA box exon1 2 3 4 5

*28 *6　*27

5‘ 3‘

*29 *7mutation method

*28 (TA)6 → (TA)7 Melting Curve

*6 211G → A

*27 686C → A

*29 1099C →G

*7 1456T →G

PCR-RFLP

OSAKA UNIVERSITY

29

FDA Clears Genetic Test That Advances Personalized Medicine Test Helps

Determine Safety of Drug TherapyFDA News August 22, 2005 Today, FDA cleared for marketing a new blood test that will help doctors make personalized drug treatment decisions for some patients. The Invader UGT1A1 Molecular Assay detects variations in a gene that affects how certain drugs are broken down and cleared by the body. Doctors can use this information to help determine the right drug dosage for individual patients, and minimize harmful drug reactions.“This test represents the power of DNA-based testing to provide individualized medical care,” said Daniel Schultz, MD, Director of FDA’s Center for Devices and Radiological Health. “These technologies can significantly improve patient management and reduce the risk of ineffective or even harmful drug therapy by telling doctors how to individualize drug dosing."The Invader assay joins a growing list of genetic tests used by physicians to personalize treatment decisions, including the Roche AmpliChip, used to individualize dosage of antidepressants, antipsychotics, beta-blockers, and some chemotherapy drugs, and TRUGENE HIV-1 Genotyping Kit, used to detect variations in the genome of the human immunodeficiency virus that make the virus resistant to some anti-retroviral drugs.

OSAKA UNIVERSITY

30

UGT1A1　gene and allele frequency

Frequency

Allele Control (n=230) High indirect Bil (n=22)

*1 52.2% 4.5% *

*6 22.2% 31.8%

*28 10.9% 45.5% *

*60 14.8% 18.2%

n: number of allele*60 :-3279T>G

* :p<0.001 cross test

Simultaneous assay system : UGT1A1　*6、*28、*60　etc

OSAKA UNIVERSITY

31

Candidate Genes for a genetic factor related to SSRI response

Polymorphism in pharmacogenetic factors analyzed in the present study

Gene/Polymorphism

PK1： Metabolic enzyme CYP2D6　IM / EM

Drug Transporter MDR-1 C3435T

5HT transporter 5HT transporter LPR/VNTR

5HTR1A Gly272Asp

5HTR2A A-1438G, T102C

TPH(1) A218C

MAO-A VNTR

Target molecule

5HT receptors

5HT synthase

5HT oxidase

PK2：CNS (BBB)

PD

cooperated with Kansai Medical University

OSAKA UNIVERSITY

32

FDA Approves BiDil Heart Failure Drug for Black Patients (1)

The Food and Drug Administration (FDA) approved BiDil (bye-DILL), a drug for the treatment of heart failure in self-identified black patients, representing a step toward the promise of personalized medicine.　 （June 23, 2005 ）

Heart failure is a condition in which the heart is weakened and does not pump enough blood. It can be caused by a variety of damage to the heart, including heart attacks, high blood pressure, and infections.

The approval of BiDil was based in part on the results of the African-American Heart Failure Trial (A-HeFT). The study, which involved 1,050 self-identified black patients with severe heart failure who had already been treated with the best available therapy, was conducted because two previous trials in the general population of severe heart failure patients found no benefit, but suggested a benefit of BiDil in black patients. Patients on BiDil experienced a 43% reduction in death and a 39%decrease in hospitalization for heart failure compared to placebo, and a decrease of their symptoms of heart failure.

is marketed by NitroMed, Inc. of Lexington, MA.

OSAKA UNIVERSITY

33

β1AR Ser49Gly and Risk in CHF

Eur Heart J 2000;21:1853-8.

0 1 2 3 4 5

20

40

60

0

p = 0.016

p = 0.12

Follow-up (years)

Risk of end-point (％)

△

▲

☆

Ser49 homozygotes without β-blockers (n=63)

Gly49 variant without β-blockers (n=28)

Ser49 homozygotes with β-blockers (n=59)

Gly49 variant with β-blockers (n=33)

△

▲

☆

★

★

Increased down regulation

β-blocker more effective in patients with Gly allele

OSAKA UNIVERSITY

34

Heart failure and Polymorphism

α2c AR Del322-325

Allele frequency

CHF healthy

0.62

0.11

???

Black 0.41

White 0.04

Yellow ???

（2002,10 reported）

α2A

α2C

Norepinephrine

β1 β3β2

Cardiac-cellmembrane

Sympatheticnerve

α2CDel322-325Decreased Function in vitro

β１Ａｒｇ３８９GlyＩｎｃｒｅａｓｅｄ

Function in vitro

These two polymorphism of receptors act

synergistically to increase the risk

of heart failure in black.

Japanese ?

N Engl J Med (2002) 347, 1135-42

OSAKA UNIVERSITY

35

Allelic frequency of adrenergic receptor polymorphisms in healthy and CHF

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Ser49Gly Arg389Gly Arg16Gly Gln27Glu α2c Del

CHF (n = 66)

Healthy (n = 119)

β1 AR α2ｃ AR

Allele　frequency

β2 AR

• Allelic frequency of α2c AR Del322-325 in healthy Japanese is 0.14

• CHF＞Healthy : Black and White

OSAKA UNIVERSITY

36

Clinical significances of polymorphismsin β-blocker therapy against

Chronic Heart Failure

Mega trial of β-Blocker Treatment in Japanese Patients with Chronic Heart Failure (J-CHF)

Patient： NYHA II or III

EF<40%, 1500 patients (multicenter, 300 hospitals）

Drug：Carvedilol (2.5mg、5mg、20mg/day)

Endpoint：Mortality, Cardiovascular death, Mobility

Surrogate Marker : Cardiac function

Sub analysis : Genotyping

Directed by A Kitabatake MD, PhD (Hokkaido University)

Supported by Japanese Circulation Society

OSAKA UNIVERSITY

37

Chronic Heart Failure

ββblokerbloker

responderresponder nonnon--responderresponder

CAUSEPlasma Concentration

of β blockerPolymorphisms

Drug Metabolizing Enzyme

Function of Target Molecules of β blocker

PolymorphismsAR and Target Molecules

OSAKA UNIVERSITY

38

Individual Difference in βblocker Effect

0

5

10

15

20

25

Before

After

(%)

（33例：41.8％） （41例：51.9％） （5例：6.3％）

%FS ±3%

Responder Non-responder Bad-responder

11.8

21.7

14.9 15.0

19.3

12.2

Responder ; improvement of

3 % in the fractional shortening

%FS

7９patients

For Individualized Medication

Genotyping

OSAKA UNIVERSITY

39

Allelic frequency of adrenergic receptor polymorphisms in responder and non-responder

0.3

0.4

0.5

0.6

Arg16Responder (n=31)

Non-responder (n=15)

Allele　frequency

Gly49 Gly389 C-470.2

Glu270.1

0

Ser49Gly Arg389Gly T-47C Arg16Gly Gln27Glu α2c Del

β2ARβ1AR α2ｃ AR

OSAKA UNIVERSITY

40

Polymorphisms associated with response to β-blocker

Ratio of responder (%)

0 20 40 60 80 100

C/C(n=10)

T+ (n=34)

G/G(n=35)

T+ (n=38)

C/C (n=31)

G+ (n=3)

A/A(n=66)

G+ (n=64)

T+ (n=30)C/C(n=39)

C+ (n=13)

T/T(n=56)

p=0.017

T+ (n=59)SNP A p=0.001

p=0.008SNP B

SNP C p=0.011

No responderSNP D p=0.029

C/C (n=5)SNP E p=0.033

SNP F

SNP Gp=0.004

OSAKA UNIVERSITY

41

遺伝子多型のスコア化によるβ遮断薬の反応性予測

Score ＝ 2x SNP A + SNP B + SNP C + SNP D + SNP E + SNP F + 2x SNP G

SNP A: T alleleSNP B: G alleleSNP C: C alleleSNP D: A alleleSNP E: G alleleSNP F: T alleleSNP G: C allele

各SNPを判定し、左記のアレルの数を上の式に当てはめて多型スコアを計算した。

SNPのA及びGは有意性が特に大きいため2を乗じた。

≧8points 7points≧

Responder（n=47） 46 1

Non responder（n=22） 9 13

OSAKA UNIVERSITY

42

Individualized Medicine (1)

Patient a

Ｘ

Patient b

Gene A

Gene B×

×

Responder

Non responder

Drug Ｘ

Rationalize

Dosing

ADR？

Cured

NotCured

DIAGNOSISDIAGNOSIS

Gene A

Gene B

OSAKA UNIVERSITY

43

Individualized Medicine (2)

×

Cured

Gene analysis

×

DrugＸ

Drug SelectionRationalize DosingClass of Drugs

Gene A

Gene B

Responder

Responder

Cured

Patient a

Patient b

DIAGNOSISDIAGNOSIS

Gene A

Gene B

DrugＹ

OSAKA UNIVERSITY

44

OSAKA UNIVERSITY

45

Next generation-full automatic systemConventional method

＜PCR＞

＜GenelyzerTM＞

Toshiba

＜Full automatic system＞

≪Future≫

Electrochemical method　

＜PCR＞

＜Hybri. apparatus＞

＜Detector＞

＜Labeling＞

＜DNA extraction＞ ＜DNA extraction＞

≪Present≫

＜Image processing＞

Only inject blood sample into cassette

○ scene of hospital

○ rapid testing

Point of Care

OSAKA UNIVERSITY

46

Pharmacogenomics Clinical Trial Management SystemPharmacogenomics Clinical Trial Management System

with high speed, high security, high quality & efficiency using IT net work infrastructure

Osaka Univ.

Ｍ／Ｃ Ｍ／Ｃ Ｍ／Ｃ

IT infrastructures

Ｍ／Ｃ

Ｍ／Ｃ

Privacy protection

PGx DB

1) PKI card for certification & coding

3) Coding & scrambling on inputting patient’s clinical data at clinical sites

2) Fiber & high-speed broad bands to share the information of clinical trials

PKI cardﾞ

IP-VPN（MPLS net work）

PGx analysis center

Pgtt Inc

Security measures: Clinical trial DB

C

Osaka Medical CenterRespiratory & Allergic disease

Toneyama Hospital Kinki-CyuoChest Medical Center

Osaka Hospital JATA-Osaka

OSAKA UNIVERSITY

47

IP-VPN network with secured security　 Internet Protocol ‒Virtual Private Network (IP-VPN) runs over the Multi-Protocol Label Suitching (MPLS) public IT network, which lets users set up a fully meshed IP-VPN.

Security

MPLSMPLSNetworkNetwork

ＲｏｕｔｅｒＲｏｕｔｅｒ

ＲｏｕｔｅｒＲｏｕｔｅｒ

Reliability

Flexibility

Economical

Performance

ＲｏｕｔｅｒＲｏｕｔｅｒ

ＲｏｕｔｅｒＲｏｕｔｅｒ

CROCRO

CompanyCompany

×

network intrusions and hackers

HospitalsHospitals

HospitalsHospitals

OSAKA UNIVERSITY

48

Application of PGｘ providing individualized medicines

　Bood samples（I.D.)

Clinical trials/Treatmentsbased on

genetic variation

Patients（I.D.)

DoctorsPharmacists

Published Evidence

New Evidencefrom

research institute

IT Network

GenotypingData & Gene Bank

Genetic Information Center（I.D.)

･Process information･Bioinformatics･Expect pharmacokinetics/ adverse effects in vivo

･Simulate response in silico

Personalized Medicationright treatment for the right

patient at the right time.

Patent obtaining

New Drug Discovery & Development

PG-TipTop Inc.

Creation of database for pharmacogenomic ｓ

薬効ゲノム情報

OSAKA UNIVERSITY

49

TTPPTTGGTTPPTTGG

TTPPTTGG TTPPTTGGPPGGTT

TT

Optimize medication most suitable for each patient

ｈｔｔｐ://ｗｗｗ.ｐｇｔｉｐｔｏｐ.ｃｏｍ