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Transcript
PHARMACOGENOMICS
John N. van den Anker, MD, PhD, FCP, FAAP
Children’s National Medical Center, Washington, DC, USA &
Intensive Care, Erasmus MC-Sophia Children’s Hospital,
Rotterdam, the Netherlands
Disclosure presentation
John N. van den Anker
I do not have anything to disclose related
to the content of my presentation
Individual variability in drug response
can have serious consequences
Stevens-Johnson Syndrome (SJS)
Adverse Drug Reaction
The Ideal Medication
Effectively treats or
prevents disease
Has no adverse effects
Paradox of Modern Drug Development
1. Clinical trials provide evidence of efficacy
and safety at usual doses in populations
+
=
Efficacious & Safe
2. Physicians treat individual patients who can
vary widely in their response to drug therapy
No Response
+
=
Efficacious & Safe
Adverse Drug Reaction
Adverse Drug Reactions
• 4-6th leading cause of death in the USA1
• Health care costs: $137-177 billion annually (USA)2-3
• Cause 7% of all hospital admissions4
• Cause serious reactions in over 2,000,000 hospitalized
patients (6.7%) each year in the USA1
• Cause fatal reactions in over 100,000 hospitalized patients
each year in the USA1
• 50% of newly approved therapeutic health products have
serious ADRs, discovered only after the product is on the
market (Health Canada, 2007)
• 95% of all ADRs are unreported
1. Lazarou et al, JAMA, 1998
2. Johnson et al, Arch Intern Med 1995
3. Ernst et al, J. Am. Pharm. Assoc. 2001
4. Pirmohamed et al, BMJ, 2004
5. MjoÈrndal et al, EACPT3, 1999
Factors Contributing to
Variability in Drug Response
Gender Weight
Ethnicity
Diet
Compliance
Genetic Factors
20-95%
Concomitant Disease
Concomitant Drugs
Age
Patient genotype is currently an unknown
factor in the prescribing of medicines
Determinants of Drug Response in Infants
Disease
Growth and Development
Environment
Drug
Genetics
Absorption
Distribution
Receptor Interaction
Biotransformation
Excretion
Exposure
Response
The Challenge of Optimizing the Use of
Medicines in Paediatric Patients: Determining
the Source(s) of Variability…...
Ontogeny
Pharmacogenetics
From DNA to mRNA to protein
ATG ATC CCC TTT
Met Ile Pro Phe
3 billion correct basepairs ….and 1 mutation
•
•
atgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacga
gttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccag
gtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtac
gtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcagga
cgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtc
caggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttca
gtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcactacgtacatgtccaggtgca
ggacgagttcagtacgtacatgtccaggtgcaggacgaattcagtacgtacatgtccaggtgcaggacgagttcagtacgtaca
tgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagt
tcagtacgtacatgtccaggtgcaggacgagttca
gacgaattcagtacgtacatg
atgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacga
gttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccag
gacgacttcagtacgtacatg
gtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtac
gtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcagga
cgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtc
caggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttca
gtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgc
aggacgagttcagtacgtacatgtccaggtgcaggacgacttcagtacgtacatgtccaggtgcaggacgagttcagtacgtac
atgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacgagttcagtacgtacatgtccaggtgcaggacga
gttcagtacgtacatgtccaggtgcaggacgagttca
slow
CYP2D6
intermediate
rapid
ultrarapid
anti-depressants,
anti-psychotics,
anti-arrhythmics,
beta-blockers,
pain medications,
anti-emetics,
anti-cancer drugs
CYP2C19
Poor
metabolizer
anti-convulsants,
proton pump inhibitors,
benzodiazepines,
anti-malarials
normal
CYP2D6 Pharmacogenetics
Drug
Drug
EM
PM
“Functional” overdose
Stable metabolites,
Excretion
Stable metabolites,
Excretion
CYP2D6 Pharmacogenetics
 CYP2D6 activity displays bimodal distribution
in Caucasian subjects
 5-10% of Caucasian population deficient in
CYP2D6 activity
 “Poor metabolizers” or “PMs” have two
“inactive” forms (alleles) of the CYP2D6 gene
 PMs at increased risk for concentration-
dependent side effects with “normal” drug
doses
 Some drugs may not work (codeine; tramadol)
CYP2D6 Pharmacogenetics: Caucasians
Bertilsson et al. Clin. Pharmacol. Ther. 51:288-97, 1992
Number of Individuals
120
N = 1,011
80
40
12.6
0
0.01
Faster
0.1
1
CYP2D6 Activity
10
100
Slower
CYP2D6 Activity: Chinese
Bertilsson et al. Clin. Pharmacol. Ther. 51:288-97, 1992
Number of Individuals
120
N = 1,011
N = 695
80
40
12.6
0
0.01
Faster
0.1
1
CYP2D6 Activity
10
100
Slower
Individuals
Unravelling CYP2D6 Pharmacogenetics
40
30
20
EM
Extensive
Metabolizer
Griese et al.
Pharmacogenetics 1998,
Raimundo et al. CPT 2004,
Toscano et al.
Pharmacogenetics 2006
UM
ultrarapid
metabolizer
~ 10-15 %
IM
Intermediate
Metabolizer
~ 10-15 %
PM
Poor Metabolizer
~ 5-10 % Caucasians
10
0.1
1
10
100
MRS
 full-term healthy male infant
 day 7 pp: intermittent periods of difficulty in breastfeeding
 day 11: the baby had regained his birthweight
 day 12: grey skin, milk intake had fallen
 day 13: the baby was found dead
 autopsy: no abnormality
 blood concentration of morphine (metabolite of codeine):
70 ng/mL versus 0-2.2 ng/mL (typical)
Pharmacogenetics of Codeine
site of action
codeine
Cytochrome P450
2D6
morphine
plasma morphine levels
after 170 mg codeine p.o.
morphine [pmol/ml]
60
50
Poor Metabolizer
40
Extensive Metabolizer
30
20
10
0
0
5
10
15
20
time [h]
Eckhardt et al., Pain 1998
25
Explanation:
 medication mother due to episiotomy pain:
codeine 60 mg plus paracetamol 1000 mg every 12 hrs for
2 weeks
 Morphine concentration in stored milk: 87 ng/mL
 mother: CYP2D6 genotype: CYP2D6*2x2 gene duplication
= Ultra rapid metabolizer phenotype
Prior to this publication!
The American Academy of Pediatrics and
“Drugs in Pregnancy in Lactation”, the major
reference guide to fetal and neonatal risk, list
codeine as compatible with breastfeeding
– Briggs et al., 2005; Pediatrics, 2001
Estimated 1846 newborn infants are at risk for
this codeine ADR annually in Canada
(340,000 births, 73% breastfed, 52% mothers receive codeine post-childbirth,1.4% risk genotype)
FDA drug label change and
public health advisories
Health Canada
Public Advisory
May 10, 2006
Aug. 21, 2008
Aug 17, 2007
August 20, 2009
2 year old boy
Received tonsillectomy for sleep apnea
Received standard codeine dose
Died of respiratory depression
High levels of morphine in blood
Boy carried CYP2D6 gene duplication
Kelly, Rieder, van den Anker et al. More codeine fatalities after
tonsillectomy in North American children. Pediatrics 2012;129(5):1343-7
Transporters
Receptors
Phosphatases
2nd messengers
Targets
Protein kinases
GI Lumen
Blood
Cell
Opioids and pharmacogenomics
Why personalizing opioid therapy?
• Wide unpredictable interpatient variability
• Narrow therapeutic indices  Inadequate pain relief and side effects ~ 50%
• Genetic factors: up to 60% (Angst 2012)
Sadhasivam et al. (2012)
Candidate genes
1. 410 pain genes
2. <10% translated to human pain
3. Opioid + genetic ≈ 2000 hits
Division of genes
• Pharmacokinetic: affect the availability at the site of action
Phase I and II enzymes, transporters etc.
• Pharmacodynamic: target and downstream signaling cascade
Mu-opioid receptor, inwardly rectifying potassium channel etc
• Pain sensitivity: susceptibility to pain
Sodium channel, interleukines etc.
PK RELATED GENES
Metabolism fentanyl
CYP3A4 Gene
• Important drug metabolizing enzyme
Highly expressed in liver and intestine
broad substrate specificity (app. 50%)
• Identified SNPs
22 alleles identified (CYPallele homepage)
Rare or lack phenotypic effect
• Caucasian
*1G and *22 allele
CYP3A4 SNPs
CYP3A4*1G  reduced activity  higher plasma levels
 Less fentanyl required
 More side effects
Studies
Dong (2012),Yuan (2011) and Zhang (2010): Lower fentanyl requirement postoperative
CYP3A4*22
Yuan (2011) correlation between plasma levels and requirement (r=-0.552, p<0.001)
However, not associated with AEs and Pain score
PD RELATED GENES
OPRM1 and Fentanyl
118A>G
• Higher fentanyl requirement (Zhang 2011)
• Higher VAS pain score (Wu 2009)
118A>G relevant?
Liao 2013: N=97, post-operative pain, fentanyl
requirement+AEs
CYP3A4*18 >> A118G
304A>G
Lower fentanyl requirement (Landau 2009)
Association with morphine requirement not found
(Wong 2010)
OPRM1 related genes
Stat6
PAIN SENSITIVITY GENES
Pain sensitivity genes
Action potential
• SCN9A
Α-subunit Nav1.7 channel, nociceptive neurons
R1150W  increased sensitivity to pain (Reimann
2010)
• KCNS1
Voltage gated K channel (Kv 9.1), sensory neurons
1465A>G  increased sensitivity to pain (Costigan
2010)
NICU study
• n=132
• Mechanical ventilation (PNA<3 days)
• 2 level III NICUs
• Continous morphine vs placebo during max. 7 days
• Loading dose 100 µg/kg  10 µg/kg/hr
• Additional morphine (50 µg/kg  5-10 µg/kg/hr)
Objective
Determine if polymorphisms in PD related genes (OPRM1
118A>G, COMT Val158Met, ARRB2 8622C>T) are
associated with additional morphine requirement (AMR) in
newborns.
Results NICU
OPRM1
% AMR
118AA
31.0
118AG/118GG
34.3
COMT
% AMR
158Val/Val
57.1
158Val/Met or 158Met/Met
26.9
ARRB2
% AMR
8622CC
11.1
8622CT/8622TT
34.3
OR* [95%CI]
4.93 [1.22-20]
OR*[95%CI]
0.161 [0.04-0.650]
OR* [95%CI]
5.52 [0.371-82.2]
*corrected OR and 95%CI for postconceptional age, sex, allocation
group, location centre .
 OPRM1 and COMT significant after Bonferroni correction
Pharmacogenomics
Avoid adverse drug reactions
Maximize drug efficacy for individual patients
Pharmacogenetic Profile:
All Patients with
Same Diagnosis
High risk of ADR (50%):
treat with alternative
drug or dose
Moderate risk of ADR (12.5%):
treat with alternative
drug or dose
10% risk of
adverse reaction
Low risk of ADR (0%):
treat with conventional dose
What do we need to do!
All children are at risk for ADRs, but not all
children are at equal risk.
Find the kids at highest risk for serious
ADRs due to genetic factors
• Identify children with ADRs
• Identify ‘matched’ children on same medications,
without ADRs
• Whenever possible, DNA samples are collected
from biological parents of ADR patients
• Look for genetic variation in key drug ADME
enzymes
• Develop new dosing guidelines
• Bedside-benchtop-bedside science
WE CAN’T TREAT CHILDREN LIKE ADULTS
Increased Risk of Severe
ADRs in Children
>75% of approved drugs used
in children are untested in
pediatric populations
Young children cannot
evaluate or express their own
response to medications
Pediatric dosage forms not
available
Children metabolize and
transport drugs differently
than adults