Transcript Pharmacogenetics

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Pharmacogenetics
• Hypothesis

Variability in response, toxicity and adverse
effects following drug treatment is influenced
by genetic variation
• Advantages
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Genotyping can be done any time
Not influenced by current treatment
Can be measured very reliably
Genome fully sequenced
Easy to do – peripheral blood sample
Heritability – a starting point
• FHx of response or side effects

Poor man’s pharmacogenetics?
• Antidepressants
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38 family pairs concordant for response to Imipramine (Angst,
1964)
12/12 and 10/12 concordance of first degree relatives (Pare et
al. 1962; Pare & Mack, 1971)
Retrospective study in 4 families who responded to
tranylcypromine but not other ADs (O’Reilly et al. 1994)
67% of 1° rels of fluvoxamine responders responded (Franchini
et al. 1998)
• Antipsychotics
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Afro-Caribbean greater acute response than Caucasians
(Emsley et al. 2002)
Little other supportive data
Definition of some terms
• Pharmacogenetics
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The study of candidate genes that may influence drug effects
and metabolism
• Pharmacogenomics
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The study of all genes (and their expression) in the genome that
may influence drug effects and metabolism
Non-hypothesis based
Needs large-scale high-through put techniques to screen the
genome
Genetic Variation
• Polymorphism
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Genetic variation that occurs with a frequency
≥ 1% in the population
Various types
• SNPs (Single nucleotide polymorphisms)
• Repetitive DNA sequences

Must be functional (?)
• Alter the expression levels or conformation of a
drug-related protein
Single Nucleotide Polymorphism (SNP)
in the Coding Region of a Gene
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SNP results in alteration of the amino acid sequence
of the corresponding protein
• arginine (Arg) substituted for glycine (Gly)
• Distinct protein structures could result in phenotypic
differences between the subjects, such as variation in
response to medication.
Taken from Malhotra et al. 2004 Am.J.Psych.
Pharmacogenetic tree
Absorption/
Excretion
Pharmacokinetics
study of availability of
therapeutic in body
Pharmacogenetics
Metabolism
Distribution
study of correlation
between genetic traits
and response to
therapeutics (efficacy
and adverse effects)
Receptors
Pharmacodynamics
Pharmacodynamics
study
Study
of drug
of drug
andand
target
interaction
target interactions
Transporters
/Channels
Enzymes
CYP450:
• 76% of ADRs are
dose dependent
• CYP450 is one of
the best
characterized
metabolic protein
complexes
CYP 450 and metabolism of TCAs
• Marked genetic variation in hepatic metabolism

Up to 30-fold variation in plasma concentrations between
individuals
• N.B. cardiac arrhythmias occur at concentrations just 10fold higher than monoamine uptake blockade
• Main rate limiting step in TCA metabolism is
mediated by CYP2D6 isoenzyme
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7% of Caucasians have a functional impairment of this
enzyme which can lead to toxic levels occurring
Drug Concentrations by Genotype
Metabolizer Status
Genotype
Ultrarapid
Response to average daily dose
Conc.
Time
Extensive
Intermediate
Poor
normal
activity
reduced
activity
no
activity
= Adverse Events
= Therapeutic
Window
Regional distribution of ultrarapid
metabolisers
Ingelman-Sundberg (2001) Journal of Internal Medicine 250: 186
CYP2D6 and dosing of
antidepressants
Source: Kirchheiner et al., Mol Psychiatry 9: 442-47392
CYP2D6 and dosing of
antipsychotics
Source: Kirchheiner et al., Mol Psychiatry 9: 442-47392
CYP450 Polymorphism Findings
• No confirmed association between CYP450
polymorphisms and response to antipsychotics
or antidepressants identified to date (see Vetti et
al. 2010)
• CYP2D6 and CYP1A2 associated with
increased side effects of antipsychotics (TD and
PSx)(Basile et al. 2000; Lam et al. 2001)
• CYP2D6 and CYP2C19 associated with
increased side effects with sertraline (Wang et
al. 2001)
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N.B. wide therapeutic index with SSRIs
P-glycoproteins and antidepressant
response
• P-glucoproteins (P-gp) are transport
proteins that occur around the body,
including in the BBB
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Includes the MDR1 (ABCBB1) protein
Can influence the entry of drugs into the brain
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Organ/plasma ration of antidepressants
in ABCB1 mutant mice
Uhr, M. et al. 2008 Neuron 57: 203-209
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P-gp polymorphisms and response to
antidepressants
• 362 patients treated with P-gp
substrates (amitriptyline,
citalopram, paroxetine,
venlafaxine) or non-substrate
(mirtazepine)
• 9.5% non-remitters carried C
allele vs 45% of remitters
• C-carriers treated with P-gp
substrate significant increased
risk of remission
Uhr, M. et al. 2008 Neuron 57: 203-209
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Pharmacodynamics
• The interaction of a drug with a target
molecule
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Receptors, enzymes, transporters, ion
channels
• Leads to therapeutic effects
• Can lead to side effects
5-HTT/SERT 5HTTLPR polymorphism
Serotonin transport gene polymorphisms
•
The brain serotonin
transporter (5HTT) is the
principal site of action of
many antidepressants.1
Transcriptional activity of
the 5HTT gene is
modulated by a gene
linked polymorphic region
(5HTTLPR).2
The short (s) allele is
associated with lower
transcriptional efficiency
than the long (l) allele.2
•
•
1.
2.
3.
Serretti A et al. Prog Neuro Psychopharmacol Biol Psychiatry 2005;29:1074-1084
Lesch KP et al. Science 1996 ;274:1527-1531
Diagram from Canli T & Lesch KP. Nat Neurosci 2007;10:1103-1109
Genetic (5-HTTLPR polymorphism)
influence on response to stress
Trier Social Stress Test in healthy
subjects2
Association of stressful life events aged 2126yrs and depression outcome aged 26 as
a function of 5HTT geneotype.1
Meta analysis demonstrates greater amygdala activity in s allele carriers
when shown pictures of fearful faces.3
1. Caspi A et al. Science 2003; 301:386-389
3. Munafo MR et al. Biol Psychiatry 2008;63:852-857
2. Way BM & Taylor SE. Biol Psychiatry 2010;67:487-492
SSRIs and 5-HTT/SERT
(from Schosser & Kasper, 2009)
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5-HTTLPR effects may be mediated
via complex and indirect effects
5-HT Receptors and
antidepressants
• 5-HT1A polymorphism
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Functional
Associated with alterations in expression of 5-HT1A
receptors (Lemonde et al. 2003)
Associated with response to TCAs and SSRIs
(Serretti et al. 2004; Lemonde et al. 2004)
• 5-HT2A polymorphism
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Association found in largest pharmacogenetics study
(n = 1953, 768 SNPs examined)
79.9% vs 62.4% response rates for homozygous
patients (McMahon et al. 2006)
Antidepressants and other
polymorphisms
• Glutamate receptor polymorphism associated with response to
citalopram (Paddock et al. 2007)
 GRIK4
• Glutamate receptor polymorphism associated with treatment
emergent suicidal ideation with citalopram (Laje et al. 2007; Menke
et al. 2008)
 GRIK2 (kainate-sensitive ionotropic glut receptor – GluR6)
 GRIA3 (ionotropic glut receptor – AMPA3)
• CREB1 (cAMP response element binding protein 1) associated with
treatment emergent suicidality in men (Perlis et al. 2007)
• NET polymorphisms and response to nortriptyline Uher et al. 2009)
• GR polymorphisms associated with response to escitalopram and
nortriptyline (Uher et al. 2009)
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CLOCK gene – multiple effects
• CLOCK 3111T/C Polymorphism
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Associated with “eveningness” (healthy
subjects)
Associated with a higher recurrence of
episodes (BP)
Associated with lifetime insomnia (BP+UP)
CLOCK gene variants and insomnia
during SSRI treatment
HAMD insomnia score
p=0.0443
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
p=0.0379
p=0.0195 p=0.0050
TT
TC
CC
T0
T1
T2
T3
T4
T5
T6
Weeks of
treatment
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Zang & Malhotra (2011) - summary
• Most pharmacogenetic studies of
antipsychotic drugs have used a candidate
gene approach, focusing on
polymorphisms in genes coding for
receptors in the dopamine and 5-HT
systems, as well as genes coding for
enzymes that metabolize drugs, such as
COMT and CYP2D6.
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Zang & Malhotra (2011) - summary
• Regarding genetic variants predicting
antipsychotic drug efficacy, previous studies
have produced promising results for a few
polymorphisms including the -141C Ins/Del in
DRD2, Ser9Gly in DRD3, -1438G/A in HTR2A,
5-HTTLPR and Val108Met in COMT.
• Studies with larger samples and better designs
are needed to validate these findings.
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Zang & Malhotra (2011) - summary
• Regarding genetic variants predicting
antipsychotic-induced side effects, different
studies have been inconsistent.
• For tardive dyskinesia, the Taq1A in
DRD2, the Ser9Gly in DRD3, the T102C
SNP (single nucleotide polymorphism) in
HTR2A and the loss of functional variants
in CYP2D6 may warrant further research.
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Pharmacogenetics of antipsychotic induced
weight gain
(Lett et al. 2011 Mol Psychiatry)
• Replicated data for leptin and 5-HT2C
genes
• Also evidence for:
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DRD2, TNF, SNAP-25 and MC4R genes
• Preliminary evidence for:
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CNR1, MDR1, ADRA1A and INSIG2
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Combinations of genes
• Combining information from key response-related genes
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Can constantly refine predictions by adding additional genes
Will need adjustments for ethnic mix
• Examples:
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DRD3 and 5-HT2C polymorphisms have additive effects on risk
of TD (Segman & Lerer 2002)
DRD3 and CYP1A2 polymorphisms additive effects on risk of
TD (Basile et al. 2000)
Response in Alzheimers predicted by combination of
polymorphisms of APOE, PS1 and PS2 (Cacabelos et al. 2000)
• Problems
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What statistical methods should be used?
Effects additive or synergistic?
Genes investigated in the short term
response to antidepressants
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5-HTTLPR
SERT-STin2
5HT1A C-1019G
5-HT1B
5HT2A T102C
5HT2A G1438A
5HT2C
5HT6 C267T
TPH1 A218C
TPH2
• NET T-182C
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COMT
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MAOA
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DRD2 S311C •
DRD4 VNTR
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ACE I/D
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polymorphism •
G-protein beta3 •
C825T
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ADRB1 G1165C •
CRHR1
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NOS C276T
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IL-1beta C511T •
CRHR1
DTNBP1
FKBP5
CLOCK
BDNF
DTNBP1
nNOS
IL-1beta
APOE
MDR1P-gp
A-161T
Dysbindin
Genes investigated in the short term
response to antidepressants
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5-HTTLPR
SERT-STin2
5HT1A C-1019G
5-HT1B
5HT2A T102C
5HT2A G1438A
5HT2C
5HT6 C267T
TPH1 A218C
TPH2
• NET T-182C
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COMT
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MAOA
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DRD2 S311C •
DRD4 VNTR
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ACE I/D
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polymorphism •
G-protein beta3 •
C825T
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ADRB1 G1165C •
CRHR1
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NOS C276T
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IL-1beta C511T •
CRHR1
DTNBP1
FKBP5
CLOCK
BDNF
DTNBP1
nNOS
IL-1beta
APOE
MDR1P-gp
A-161T
Dysbindin
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1.
Number of episodes
2.
Side effects (yes/no)
3.
Delusional features (yes/no)
4.
Baseline HAM-D
5.
Length of current episode
6.
Lithium augmentation (yes/no)
7.
Current medical condition (y/n)
8.
Personality disorders (yes/no)
9.
Sex (female/male)
10.
Age at onset
11.
Polarity (UP/BP)
12.
Plasma level
13.
Baseline VAS
HAMD
improvement
1.
Number of episodes
2.
Side effects (yes/no)
3.
Delusional features (yes/no)
4.
Baseline HAM-D
5.
Length of current episode
6.
Lithium augmentation (yes/no)
7.
Current medical condition (y/n)
8.
Personality disorders (yes/no)
9.
Sex (female/male)
10.
Age at onset
11.
Polarity (UP/BP)
12.
Plasma level
13.
Baseline VAS
HAMD
improvement
21% Variance
explained
Genes investigated in the short term
response to antidepressants
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5-HTTLPR
SERT-STin2
5HT1A C-1019G
5-HT1B
5HT2A T102C
5HT2A G1438A
5HT2C
5HT6 C267T
TPH1 A218C
TPH2
• NET T-182C
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COMT
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MAOA
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DRD2 S311C •
DRD4 VNTR
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ACE I/D
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polymorphism •
G-protein beta3 •
C825T
•
ADRB1 G1165C •
CRHR1
•
NOS C276T
•
IL-1beta C511T •
CRHR1
DTNBP1
FKBP5
CLOCK
BDNF
DTNBP1
nNOS
IL-1beta
APOE
MDR1P-gp
A-161T
Dysbindin
Prediction of Clozapine
response (Arranz et al. 2000)
• 200 schizophrenia patients (all white
Caucasians of British origin) treated with
clozapine (133 responded)
• 19 polymorphisms analysed
• 6 with strongest association with response (5HT2A X 2, 5-HT2C X 2, 5-HTT, H2) combined
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PPV: 0.76 ± 0.08
NPV: 0.82 ± 0.16
Sensitivity 95.9% ± 0.04% (for identifying
“satisfactory” responders)
Specificity 38.3 % ± 0.14% (for identifying poor
responders)
• Utility?
N.B. Ethical, Legal and Social
Implications
• Use of genetic information by insurers,
employers...
• Who should have access to personal genetic
information, and how will it be used?
• Privacy and confidentiality.
• Who owns and controls genetic information?
• Stigmatization.
• How does personal genetic information affect an
individual and society's perceptions of that
individual?
•
More information at http://www.royalsoc.ac.uk/displaypagedoc.asp?id=17570
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Pharmacogenetics Conclusions
Pharmacogenetics:
Any relevance to clinical practice?
Possibly….
• CYP450 chip technology may be helpful for a minority of
patients
• Use of pharmacogenetics for efficacy predictions (e.g.
for clozapine) less clear
• The future (5-10 years) does potentially look very
interesting