Download 11:30 AM Using Genetics for Drug Prescribing: Will it Happen?

Using genetics for drug
prescribing: will it happen?
• Hype and hope
• Relating DNA polymorphisms to variable
human physiology and drug responses:
examples
• A view to the future
Take-home messages
• Diversity among human genomes can explain
variability in human physiology, and its response
to the environment.
• Pharmacogenetic information is now affecting
drug development, and will enter clinical practice
(a personal opinion).
• “Proving” genotype-phenotype relations requires
collaborations among clinical investigators, basic
biologists, information managers and
statisticians, systems biologists, technologists,
ethicists…
Case presentations
• Grade 4 diarrhea occurs in a 65 year old man
receiving irinotecan for colon cancer.
• A 70 year old woman starts coumadin 5 mg/day for
atrial fibrillation. One week later, her INR is 12.
• A 78 year man develops a QT interval of 700 msec
and Torsades de Pointes a day after starting
dofetilide.
• Life-threatening sepsis arises in a 9-year-old girl
after 6-MP therapy for ALL.
• A 68 year old man presents with a large anterior
myocardial infarction, and has a VF arrest in the
Emergency Room.
Pharmacogenetics:
Large single gene effects
“idiosyncratic” drug
response
understand the biology
identify causative DNA
variants
“idiosyncratic” response
now predictable and
avoidable
6-thioguanines (6-TGNs)
azathioprine
cytotoxic
“single nucleotide
polymorphisms” (SNPs)
*1/*3A
*1/*1
6-TGN concentrations
1/300
*3A/*3A
HH
HL
LL
*1/*1
*1/*3A
*3A/*3A
(mutant) (heterozygote) (wild-type)
An “idiosyncratic” drug response
AR, 78 year old man
• Chronic heart disease with history of bypass
surgery and valve replacement
• Cardiac arrest 4 days after major abdominal
surgery; placed on dofetilide (a potent and highly
selective blocker of a potassium current called IKr)
to prevent recurrence. 2 days later:
Torsades de Pointes
• Also characteristic of the
congenital long QT syndrome
• Drug-induced QT
prolongation and torsades is
the single commonest cause
for drug withdrawal or
relabeling in the past decade.
AR: An “idiosyncratic” drug
response
• DNA variant resulting in R583C identified in
KCNQ1, a gene controlling QT duration and
mutated in a common form of the congenital
Long QT Syndrome.
• R583C alters protein function in vitro: reduces
IKs.
• Absent in >1000 controls  “mutation”. This
man has the congenital long QT syndrome,
that remained asymptomatic for 78 years.
How did AR avoid arrhythmias for
2,000,000,000 heart beats?
The concept of reduced repolarization reserve
• Redundancy (“reserve”) in cardiac repolarization allowed him to
maintain a normal QT until other lesions (heart disease,
dofetilide) were superimposed.
Patient 1
Patient 2
Same QT-prolonging drug
Redundancy in physiologic systems:
“high risk pharmacokinetics”
low margin between doses needed for efficacy and doses
producing toxicity (therapeutic index)
PLUS
a single pathway for drug elimination that is genetically
variable or subject to inhibition by interacting drugs
Drug A
Drug B
Drug C
Drug D
TPMT
CYP2C9
transport by drug
efflux pump
CYP3A4
inactive metabolite
6-MP
inactive metabolite
warfarin
inhibitor drug
renal excretion
digoxin
inhibitor drug
inactive metabolite
terfenadine
(Seldane)
Redundancy in physiologic systems:
“high risk pharmacokinetics”
TPMT
Drug A
CYP2C9
Drug B
Drug C
transport by drug
efflux pump
Drug D
CYP3A4
inactive metabolite
6-MP
inactive metabolite
warfarin
inhibitor drug
renal excretion
digoxin
inhibitor drug
inactive metabolite
terfenadine
(Seldane)
Drug E
CYP2C9
transporter
CYP3A4
TPMT
inactive metabolite
renal excretion
inactive metabolite
inactive metabolite
Drug E will be an
especially attractive
agent if it also has a
high therapeutic index
Redundancy in physiologic
systems as a protective
mechanism
• arrhythmia susceptibility
• susceptibility to adverse drug reactions
and interactions
• “multi-hit” requirement for
carcinogenesis
Pharmacogenetics:
Large single gene
effects
“idiosyncratic”
drug response
Pharmacogenomics:
Discovering new
biology
unusually variable
drug response
understand the
biology
identify associated
DNA polymorphisms
identify causative
DNA variants
“idiosyncratic”
response now
predictable and
avoidable
1950
• adjust dose or
change drugs
• discover new biology
and new drug targets
1980
2020
PHARMACOGENOMICS
Smaller effect;
multiple
variants
Large single
variant effect
PHARMACOGENETICS
Single gene
Small number
of genes
Complex biologic
pathway
Whole
genome
PHARMACOGENOMICS
Smaller effect;
multiple
variants
Large single
variant effect
(large populations)
PHARMACOGENETICS
(snlall groups)
Single gene
•
•
•
•
Small number
of genes
Complex biologic
pathway
Whole
genome
Rare coding region variants (polymorphisms or
mutations)
Commoner coding and regulatory variants
Detectible effects of polymorphisms in >1 gene
Pathway analysis and whole genome approaches
Variants in the warfarin target
Variants in the warfarin target – 2
Single Nucleotide Polymorphisms (SNPs) in the VKORC1
promoter
C CG A TC T C T G
T G CGC
Reider et al.
25 = 32 possible combinations
NEJM 2005
Haplotype A: CCGATCTCTG
Haplotype B: TCGGTCCGCG
Variants in both drug metabolism
(CYP2C9) and drug target (VKORC1)
genes affect warfarin dose requirement
Reider et al., NEJM 2005
• 554 patients on chronic warfarin; early
dropouts not included
• CYP2C9 genotype predicts 9% of dosage
variability
• VKORC1 haplotype accounts for 23%
• Illustrates
• Multi-gene effects can be detected
• Understanding mechanisms in rare syndromes can
inform the study of common biologic problems
• Increasing importance of haplotypes
A 68 year old man presents with a
large MI, and has a VF arrest in the ER
Patient 1
Patient 2
Same acute MI
?“reduced antifibrillatory reserve”
Reduced cardiac sodium current
predisposes to serious arrhythmias
Sodium channel blocking
drugs increase mortality
% survival
Placebo (n=725)
encainide or
flecainide (n=730)
Loss of function mutations in the
sodium channel gene cause a
distinctive ECG and ↑↑risk of VF
Brugada syndrome
Days from randomization
Hypothesis: Variable sodium channel expression is a
candidate mechanism for variability in basal conduction
velocity, and in susceptibility to slowed conduction with
exogenous stressors (drugs, myocardial ischemia). Slow
conduction predisposes to sudden death due to VF.
6 sodium channel promoter variants,
found only in Asians
C287T
G-354C
-835insGC
T-847G
T-1062C
T-1418C
6 variants: 26 = 64 possible combinations
promoter
intron 1
exon 1
(non-coding)
-2000 bp
-1000
0
1000
6 sodium channel promoter variants,
found only in Asians, in very tight
linkage disequilibrium
T
T
T ---
G
C
75.5%
Haplotype B
C
C
G ins
C
T
24%
Haplotype C
C
T
T ---
C
C
0.5%
T-847G
-835insGC
G-354C
C287T
T-1418C
Haplotype A
T-1062C
Frequency*
Frequency
promoter
intron 1
exon 1
(non-coding)
-2000 bp
-1000
0
1000
Haplotype B  ↓↓promoter activity
Fold activity
18
CHO cells
15
Cardiomyocytes
n=13, p=0.04
n=9, p=0.006
12
9
6
3
0
A
B
Wild Type
6-change
haplotype
A
Wild Type
B
6-change
haplotype
Ventricular conduction is slower with
the reduction of function allele
QRS duration (msec)
140
120
normals
100
80
60
34
AA
AB
8
BB
140
120
100
45
21
5
AA
AB
BB
80
71 probands
with Brugada
Syndrome
Genotype-dependent incremental conduction
slowing by sodium channel blockers
200
QRS
duration
(msec)
+20
msec
+17
msec
+29
msec
AA
AB
BB
160
120
80
Who has the longest QRS duration?
Brugada Syndrome mutation + drug exposure + BB haplotype
“Genes load the gun, environment pulls the
trigger”
Pharmacogenetics:
Large single gene
effects
“idiosyncratic”
drug response
Pharmacogenomics:
Discovering new
biology
unusually variable
drug response
understand the
biology
identify associated
DNA polymorphisms
identify causative
DNA variants
“idiosyncratic”
response now
predictable and
avoidable
1950
• adjust dose or
change drugs
• discover new biology
and new drug targets
1980
2020
The future
Moving to widespread
practice
Routine
patient visit
identify or look up
DNA variants in
that patient
adjust dose or
change drugs
2050
Nature
Oct. 5, 2005
Genotypes:
CYP2D6:
CYP2C9:
NAT:
TPMT:
UGT1A1:
ACE:
CETP:
BRCA1:
b1 AR:
b2 AR:
KCNQ1:
HERG:
KCNE1:
KCNE2:
Apoe:
ABCA1:
*4/*4
wt/*2
slow
wt/wt
6/6
ID
BB
negative
S49/G389
R16/G27
R583C
wt/wt
wt/wt
wt/wt
2/3
wt/wt
Genotypes:
CYP2D6:
CYP2C9:
NAT:
TPMT:
UGT1A1:
ACE:
CETP:
BRCA1:
b1 AR:
b2 AR:
KCNQ1:
HERG:
KCNE1:
KCNE2:
Apoe:
ABCA1:
*4/*4
wt/*2
slow
wt/wt
6/6
ID
BB
negative
S49/G389
R16/G27
R583C
wt/wt
wt/wt
wt/wt
2/3
wt/wt