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Same Medicine, Different Result Pharmacogenetics: Where Are We Now?. Dr Richard FitzGerald Molecular & Clinical Pharmacology Institute of Translational Medicine University of Liverpool [email protected] The drugs don’t work. ....... they just make it worse.

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same medicine different result pharmacogenetics where are we now

Same Medicine, Different ResultPharmacogenetics: Where Are We Now?

Dr Richard FitzGerald

Molecular & Clinical Pharmacology

Institute of Translational Medicine

University of Liverpool

[email protected]

the problem variability
‘If it were not for the great variability among individuals, medicine might as well be a science and not an art.’

Sir William Osler, 1892

The problem: variability
pythagoras 6 th century b c
Pythagoras (6th Century B.C.)
  • “…..be far from fava beans

consumptions”

  • Met death in Ancient Italy

because he refused to cross a

field of beans

  • Many theories:
    • Contained souls
    • Looked like testicles
    • flatulence
    • Medical reason

FAVISM

RBC

haemolysis

Fava beans

chemical individuality

First suggested by Sir Archibald Garrod that genetics may affect chemical transformations

He used the example of alkaptonuria (1902)

‘Chemical Individuality’

‘One gene, one enzyme’

the early years one gene one disease
The early years: one gene, one disease
  • Robert Smith investigated debrisoquine (a commercially available anti-hypertensive)
  • He took the tablet, along with most of his laboratory staff
  • He collapsed and became markedly hypotensive. Nobody else did.
drug metabolising enzymes
Drug metabolising enzymes

Most DME have clinically relevant polymorphisms

Those with changes in drug effects are separated from pie.

slide18

Azathioprine

Xanthine

oxidase

TPMT

Thiouric

acid

6-Mercaptopurine

6-Me MP

HGPRT

6-thioinosine nucleotide

IMPDH

6-thioguanine

nucleotides

Immunosupression

Clinical benefit

slide19

TPMT (Thiopurine methyltransferase)

Allelic polymorphism

High

TPMT

89%

Low

TPMT

1/300

Intermediate

TPMT

11%

?very high

TPMT

Severe Bone

Marrow

Suppression

High risk

of marrow

suppression

Low risk

Low risk

? poor

responders

-

+

clinical response

abacavir hypersensitivity
Abacavir Hypersensitivity
  • Nucleoside analogue
  • Reverse transcriptase inhibitor
  • Hypersensitivity 5%
  • Fever, skin rash, gastro-intestinal symptoms, eosinophilia within 6 weeks
  • Re-challenge results in a more serious reaction
abacavir hypersensitivity1

Association with

HLA-B*5701

Clinical phenotype

Causal chemical

Clinical genotype

Abacavir Hypersensitivity
pgx effects on drug usage
PGx: effects on drug usage

Data from RLBUHT courtesy of Prof SayeKhoo

abacavir genetics why so rapidly implemented
Abacavir Genetics: Why so Rapidly Implemented?
  • Implemented even before RCT evidence
    • In some cases, observational study designs may provide adequate evidence
  • Successful implementation was because of several factors:
    • Good and replicated evidence of a large genetic effect size
    • Clinician community amenable to rapid change in clinical practice
    • Vocal and knowledgeable patient lobby
carbamazepine induced hypersensitivity reactions
Carbamazepine-induced hypersensitivity reactions

5% of patients on carbamazepine (CBZ) develop hypersensitivity reactions

10% in prospective SANAD study (UK)

Clinical manifestations

  • Maculopapular exanthema

usually mild

  • Hypersensitivity reaction (HSS)

1/1000 patients

Fever, hepatitis, eosinophilia

  • Stevens-Johnson syndrome

Toxic epidermal necrolysis

5-30% fatality rate

fda warning
FDA warning
  • PATIENTS WITH ASIAN ANCESTRY SHOULD BE SCREENED FOR THE PRESENCE OF HLA-B*1502 PRIOR TO INITIATING TREATMENT WITH Carbamazepine.
slide29

To prospectively identify subjects at risk for SJS

  • 4877 CBZ naive subjects from 23 hospitals
  • The Taiwan SJS Consortium

HLA-B*1502 testing → 0 incidence of SJS/TEN

slide30

University of Liverpool (SANAD, EUDRAGENE, Swiss, WT Sanger, Harvard)

  • EPIGEN Consortium (Ireland, Duke University, UCL, Belgium)
  • Faculty of 1000 -top 2% of published articles in biology and medicine
  • American Academy of Neurology meeting- voted as one of the top articles in neurology this year
slide31

HLA-A*3101

HLA-A*3101

22 patients with HSS 43 patients with MPE

2691 healthy control subjects 1296 healthy control subjects

McCormack et al. NEJM 2011

slide32

Pooled analysis of case-control studies

P=0.03

P=8 x10-7

P=8 x10-5

P=1x10-7

P=

McCormack et al. NEJM 2011

slide33
GWAS identifies HLA-A*3101 allele as a genetic risk factor for CBZ-induced cutaneous adverse drug reactions in Japanese population

HLA-A*3101

Ozeki et al. Hum Mol Genet 2011

conclusions
Conclusions
  • HLA-A*3101 - a prospective marker for CBZ hypersensitivity
  • Associated with several phenotypes
  • Further work needed to enable clinical use
  • Need for consortia
  • Possibility of rare variants and CNVs

(exome-sequencing/WGS)

  • Mechanistic studies to follow genetics
flucloxacillin induced cholestatic hepatitis whole genome scan
Flucloxacillin-Induced Cholestatic Hepatitis: Whole Genome Scan
  • Illumina 1 million SNP array
  • Strong (P=10-30) association with SNP in LD with HLA-B*5701
  • Weaker association with novel marker on chromosome 3 (p < 1.4 x 10-8 )
  • Weak association with copy number polymorphism

Daly at al, 2009

Performed in collaboration with the Serious Adverse Event Consortium

slide36

Implicated SNP is in the SLCO1B1 gene (transporter)

Shown with simvastatin 40mg and 80mg

C variant may account for 60% of the cases of myopathy

conclusions1
Conclusions
  • Clear adverse effect of the CYP2C19*2 polymorphism on clinical and pharmacodynamic outcomes
    • PD Meta-analysis limited by multiple outcome measures
  • Potential utility in CYP2C19*2 as marker of clopidogrel non-response and risk of adverse outcome
  • Translation into clinical practice
    • Increase dose of clopidogrel from 75mg/day to 150mg/day
      • Evidence from CURRENT-OASIS 7 trial
      • Bleeding risk
    • Use of alternative anti-platelet drugs (Prasugrel, Ticagrelor)
      • Better platelet inhibition
      • Higher rates of bleeding (+ other adverse effects)
      • Benefit may be only seen in those with the CYP2C19*2 allele
      • Cost
warfarin a more complex variation
Warfarin: a more complex variation
  • Widely used drug
  • A variety of acute/chronic indications
  • Large numbers of patients
  • 6% of all patients over 80 years of age
  • Narrow therapeutic index
  • Drug interactions and alcohol
  • Efficacy
slide42

Bleeding complications:

      • 10-24 per 100-patient years
  • 10% of all ADR-related hospital admissions
the clinical phenotype
The clinical phenotype
  • 10-50 fold variability in dose requirements
  • Increased age; decreased requirements
    • 8% decrease in warfarin dose per decade
    • Enhanced responsiveness (PD)
    • Reduced clearance (PK)
slide45

Warfarin and metabolism by CYP2C9

CYP2C9*1 Wild Type Arg144 Ile359

CYP2C9*2 Arg144Cys

: interaction with cytochrome

P450 reductase

CYP2C9*3 Ile359Leu

: substrate binding site

: affects Km, Vmax

Variant alleles have 5-12% of the activity of wild-type

  • Steward et al, Pharmacogenetics (1997), 7, 361-367
warfarin and pharmacokinetics

CYP2C9 genotype

Number of patients

Aggregate mean dose (mg)

CYP2C9*1*1

639

5.5

CYP2C9*1*2

207

4.5

CYP2C9*1*3

109

3.4

CYP2C9*2*2

7

3.6

CYP2C9*2*3

11

2.7

CYP2C9*3*3

5

1.6

Warfarin and pharmacokinetics
warfarin and pharmacodynamics
Polymorphisms in vitamin K epoxide reductase (VKOR)C1

Associated reductions in warfarin dose

Accounts for greater variance in dose than CYP2C9

Variation in genes encoding γ-glutamylcarboxylase and factors II, VII and X

Warfarin and pharmacodynamics
genetic and environmental factors and dose requirements of warfarin

55%

Age: p<0.0001, r2 = 0.10

Body weight: p=0.0018, r2 = 0.05

Genetic and Environmental Factors and Dose Requirements of Warfarin

Independent effects of VKORC1 and CYP2C9:

VKORC1: p<0.0001, r2 = 0.29

CYP2C9: p=0.0003, r2 = 0.11

Wadelius et al. 2005

warfarin multiple genes factors
Warfarin: multiple genes/factors

GENETIC

  • Cytochrome P450 polymorphisms
  • Vitamin K epoxide reductase
  • Phase II metabolising genes
  • Drug transporters
  • Clotting factors
  • Disease genes

ENVIRONMENTAL

  • Sex
  • Age
  • Smoking
  • Interacting drugs
  • Alcohol
  • Compliance
  • Diet
slide54

Pharmacogenetic algorithm was superior to clinical algorithm or fixed dosing

  • Greatest benefit seen in 46% of the population who require either <3mg/day or >7mg/day
two randomised controlled trials
Two Randomised Controlled Trials

COAG

EU-PACT

EU FP7 sponsored EU trials

3 trials: warfarin, phenprocoumon, acenocoumarol

900 patients in each (2700 total)

Final study design completed

%TIR as primary outcome measure

  • NIH-sponsored US trial
  • 1200 patients
  • Genetic algorithm vs clinical algorithm
  • %TIR as primary outcome measure
slide58

New technologies:

Pharmacogenomics

Proteomics

Metabolomics

Systems Biology

Minimise risk and maximize benefit

Uncertainty reduced but not abolished

Pre-clinical

Phases I, II, III

Phase IV

pgx and prospective utility
PGx and Prospective Utility
  • Drug development process
  • Potential prospective use of PGx to enhance success
  • Increase confidence
  • US$1 billion to market a new drug
  • Target discovery
  • Proof of concept
  • Candidate gene/whole genome association
current status of genetic tests
Current Status of Genetic Tests

“Today, there is no mechanism to ensure that genetic tests are supported by adequate evidence

before they are marketed or that marketing claims for such tests are truthful and not misleading. Misleading claims about tests

may lead health-care providers and patients to make inappropriate decisions about whether to test or how to interpret test results.”

Science, 4 April 2008

personalised medicines the future
Personalised Medicines: The Future?
  • Many recent advances
  • Here to stay, and likely to be supported by increasing evidence
  • Evolutionary process, not revolutionary
  • Lot of cynicism about personalised medicine approaches
  • Evidence being required is much greater with other tests
personalised vs empirical paradigms
Personalised vs. Empirical Paradigms

Empirical (intuitive) medicine

Personalised (precision) medicine

terminology
Terminology

Personalised Medicine

not

Personal Medicine

  • We cannot truly personalise medicines
  • No test or prediction rule will be 100% effective
slide65

“ What we know about the genome today is not enough for all the miracles many expect from this field. There’s a lot about what regulates the genes and how they interact that we still need to understand. We won’t have the answers by tomorrow.”

Arno Motulsky

29th April 2008

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