Soal dan Pembahasan Farmakogenomik dan Personalized Medicine

1
SOAL DAN PEMBAHASAN
FARMAKOGENOMIK DAN PERSONALIZED MEDICINE
*daftar pustaka dan jurnal terlampir di akhir
1. Apa yang dimaksud dengan farmakogenetik dan farmakogenomik ?
Jawab :
Farmakogenomik adalah ilmu yang mempelajari cara gen berpengaruh terhadap tubuh
merespons obat.
Farmakogenetik adalah ilmu bagian dari farmakogenomik yang mempelajari variasi
gen yang mempengaruhi respons obat tersebut.
2. Apakah yang dimaksud dengan personalized medicine ?
Jawab :
Personalized medicine adalah pendekatan baru dalam pencegahan dan pengobatan
penyakit berdasarkan genetik masing-masing individu dan variabilitas gaya hidup
dengan fondasi farmakogenomik, yaitu menerjemahkan informasi genetik dari
responden penelitian menjadi praktik kesehatan medis.
3. Apa yang menyebabkan manusia dengan usia, penyakit, obat, serta dosis yang sama
tetapi respons obat yang ditimbulkan berbeda-beda ?
Jawab :
Manusia yang sama dalam segi usia, penyakit, obat yang digunakan, dosis obat yang
digunakan dapat merespons berbeda-beda, disebabkan oleh faktor berikut :
a) Perbedaan etnis / ras
Misalnya manusia ras Asia dapat merespons berbeda terhadap obat tertentu
dibandingkan dengan manusia ras Afrika.
b) Variasi genetik
Adanya polimorfisme pada nukleotida tunggal (SNP) berupa substitusi nukleotida
tunggal di posisi spesifik dalam genom. Adanya SNP ini berpengaruh terhadap

2
proses transkripsi dan translasi gen serta berdampak pada farmakokinetika dan
farmakodinamik obat.
c) Metabolisme obat
Variasi metabolisme obat (termasuk farmakokinetika) juga dipengaruhi oleh
aktivitas enzim seperti kelompok sitokrom CTP450 meliputi CYP2D6, CYP2C9,
CYP3A4, dan CYP2C19 yang masing-masing dikode oleh gen yang berbeda-beda.
Adanya variasi genetik dapat menimbulkan polimorfisme genetik yang
mengakibatkan pengelompokkan manusia menjadi :
- Poor metabolizers
- Intermediate metabolizers
- Normal metabolizers
- Ultrarapid metabolizers
d) Variasi farmakodinamika
Variasi konsentrasi obat sebagai akibat dari variasi interaksi antara obat aktif
dengan molekul efektornya berperan dalam respons manusia terhadap penggunaan
obat.
4. Gen apakah yang dapat menyebabkan perbedaan respons dari obat warfarin ?
Jawab :

3
Mekanisme farmakokinetika = CYP2C9 → CYP2C9*2 dan CYP2C9*3
Mekanisme farmakodinamika = CYP4F2 dan VKORC1
Warfarin terdiri dari 2 macam bahan baku yaitu rasemat S-warfarin dan R-warfarin.
Aktivitas S-warfarin > R-warfarin karena S-warfarin dimetabolisme oleh enzim
CYP2C9 menjadi bentuk inaktif sedangkan R-warfarin dimetabolisme oleh banyak
enzim seperti CYP 3A4 CYP 1A1, dan CYP 1A2. Jika ada SNP pada CYP 2C9,
warfarin tetap dalam bentuk aktif sehingga dapat terjadi perdarahan.
Jika variasi genetik ↓ aktivitas CYP2C9 → ↑ konsentrasi plasma S-warfarin → ↑ INR
→ ↑ risiko perdarahan.
Jika pasien memiliki alel CYP 2C9*2 dan CYP 2C9*3 → membutuhkan dosis warfarin
yang lebih rendah karena metabolismenya lebih lambat dibandingkan dengan pasien
yang memiliki wild type allele.
VKORC1 (Vitamin K epoxide reductase) berperan dalam respons farmakodinamika →
VKORC1 haplotype A membutuhkan dosis warfarin yang lebih rendah karena
penurunkan ekspresi MRA.
5. Gen apakah yang dapat menyebabkan perbedaan respons dari obat clopidogrel ?
Jawab :

4
Clopidogrel adalah prodrug yang membutuhkan konversi in vivo agar menjadi aktif
secara farmakologis yaitu thiolactone dengan bantuan CYP2C19 (utama), CYP1A2,
CYP2B6, CYP3A, dan CYP2C9 di liver.
Jika pasien minum clopidogrel bersama obat yang menghambat CYP3A4 → ↓ efek
antiplatelet dari clopidogrel.
Jika terdapat 1 alel menyebabkan upregulates CYP2C19*17.
Jika pasien sehat dengan setidaknya 1 alel yang mengalami penurunan fungsi →
heterozigot atau homozigot untuk *2 atau *3 → menghasilkan lebih sedikit metabolit
aktif dibandingkan dengan 2 alel CYP2C19.
Pada pasien kategori poor metabolizers → terjadi ↓ paparan dan ↓ inhibisi agregasi
platelet → alternatif obat : prasugrel dan ticagrelor.

5
Daftar Pustaka :
1. Close, Sandra. Clopidogrel Pharmacogenetics : Metabolism and Drug Interactions.
Drug Metabolism Drug Interactions 2011 ; 26 (2) : 45-51.
2. Daly, Ann. Pharmacogenetics : A General Review on Progress to Date. British
Medical Bulletin. 2017.
3. Goetz, Laura et al. Personalized Medicine : Motivation, Challenges, and Progress.
American Society for Reproductive Medicine : Fertility and Sterility. 2018.
4. Li, Jiayi et al. Warfarin Pharmacogenomics. P&T. 2009.
5. Roden, DM et al. Genomic Medicine = Pharmacogenomics. The Lancet. 2019.
6. Schleidgen, Sebastian et al. What is Personalized Medicine : Sharpening a Vague
Term Based on a Systematic Literature Review. BMC Medical Ethic. 2013.

British Medical Bulletin, 2017, 1–15
doi: 10.1093/bmb/ldx035
Invited Review
Pharmacogenetics: a general review on progress
to date
Ann K. Daly*
Institute of Cellular Medicine, Newcastle University, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
*Correspondence address. Institute of Cellular Medicine, Newcastle University, Framlington Place, Newcastle upon Tyne
NE2 4HH, UK. E-mail: a.k.daly@ncl.ac.uk
Editorial Decision 15 September 2017; Accepted 20 September 2017
Abstract
Background: Pharmacogenetics is not a new subject area but its relevance
to drug prescribing has become clearer in recent years due to develop-
ments in gene cloning and DNA genotyping and sequencing.
Sources of data: There is a very extensive published literature concerned
with a variety of different genes and drugs.
Areas of agreement: There is general agreement that pharmacogenetic
testing is essential for the safe use of drugs such as the thiopurines and
abacavir.
Areas of controversy: Whether pharmacogenetic testing should be applied
more widely including to the prescription of certain drugs such as warfarin
and clopidogrel where the overall beneﬁt is less clear remains controversial.
Growing points: Personal genotype information is increasingly being made
available directly to the consumer. This is likely to increase demand for perso-
nalized prescription and mean that prescribers need to take pharmacogenetic
information into account. Projects such as 100 000 genomes are providing
complete genome sequences that can form part of a patient medical record.
This information will be of great value in personalized prescribing.
Areas timely for developing research: Development of new drugs targeting
particular genetic risk factors for disease. These could be prescribed to
those with an at risk genotype.
Key words: pharmacogenetics, pharmacogenomics, cytochrome P450, polymorphism, thiopurine methyltransferase,
warfarin, abacavir, clopidogrel
© The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Introduction
The term pharmacogenetics has been in use since
1959.1
Pharmacogenetics was first used in relation
to phenotypic variation in metabolism and response
to certain drugs. This was well established to be a
common phenomenon in the case of some drug
treatments by the end of the 1950s.2–4
After only
limited progress in the 1960s and 1970s, a combin-
ation of improved analytical methods, more exten-
sive drug development programmes and human
gene cloning resulted in the genetic basis of this
phenotypic variation becoming much better under-
stood during the 1980s. As gene cloning advanced
to sequencing of the entire human genome, the term
pharmacogenomics, which was first used in 1997,5
started to be used in addition to pharmacogenetics.
Essentially the two terms are now used interchange-
ably though the scope of pharmacogenomics is
broader and extends to the development of new
drugs to target specific disease genes.
The terms personalized medicine, stratified medi-
cine and precision medicine are close relatives of
pharmacogenetics but these are broader terms
which also cover additional non-genetic factors.
Nevertheless, pharmacogenetics is an important
component of these areas.
Pharmacogenetics is primarily concerned with
human germline DNA variation but there have also
been important recent advances in understanding
variation in tumour DNA, especially in the design
of drugs that target mutated genes within tumours.
The current article will focus only on recent devel-
opments and current challenges in pharmacogenet-
ics in germline DNA. Targeted therapies where the
response depends on tumour genotype are outside
the scope of this article but have been reviewed
recently elsewhere.6
Current pharmacogenetics knowledge can be con-
sidered on an individual gene, therapeutic area or indi-
vidual drug basis. This article will provide a general
background on gene families of particular relevance
to pharmacogenetics but the emphasis will be on indi-
vidual drugs. Three different types of example will be
considered: (i) use of pharmacogenetic testing to pre-
dict individual drug dose, (ii) use of pharmacogenetic
testing to predict absence of response to a drug and
(iii) use of pharmacogenetic testing to predict indivi-
duals at serious risk of toxicity if a drug is prescribed.
The underlying biological basis for each example
together with the evidence that genotyping for a
pharmacogenetic polymorphism is helpful will be
considered in detail. The Clinical Pharmacogenetics
Implementation Consortium (CPIC), which is based
in the United States of America (USA), has provided
specific pharmacogenetic guidelines relating to
some of the drug examples discussed here7,8
and
where appropriate reference will be made to these
recommendations, including their relevance outside
North America. Where there are recommendations
by pharmaceutical regulators, such as the US Food
and Drug Administration (FDA) and European
Medicines Agency (EMA), these are also discussed.
General information on individual polymorphisms
and the relevance of pharmacogenetics to specific
drugs is collated and curated by the US-based
Pharmacogenomics Research Network (PGRN) on
the PharmGKB website.9
Genes of particular relevance
to pharmacogenetics
Variation in drug metabolism is one of the best stud-
ied areas of pharmacogenetics. Most drugs undergo
metabolism, though there are some exceptions to
this, including biological agents but also some small
molecule drugs. A detailed description of drug meta-
bolism is outside the scope of this article but a brief
introduction to gene families relevant to this area is
provided in this section. The cytochromes P450 are
the most important gene family that contribute to the
oxidative metabolism of a range of different drugs.
This metabolism is usually referred to as Phase I
metabolism. Four different cytochromes P450
CYP2D6, CYP2C9, CYP3A4 and CYP2C19 have
particularly important roles in this process and are
each encoded by different genes. All are subject to
well studied genetic polymorphisms and, in the case
of CYP2D6 and CYP2C19, significant percentages
of the population completely lack one of these
enzymes due to the presence of inactivating genetic
2 A.K. Daly, 2017

polymorphisms in both copies of the gene.10
The
presence of these variant alleles which code for
inactive forms of the enzyme results in absence of
activity. In addition, some individuals who are usu-
ally termed ultrarapid metabolizers, have higher than
normal CYP2D6 or CYP2C19 activity. In the case of
CYP2D6, this is due to one or more additional copies
of the gene being present11
and for CYP2C19, the
presence of polymorphisms resulting in increased
gene expression.12
Following Phase I metabolism, drugs frequently
undergo a second round of metabolism involving
conjugation reactions. This metabolism is referred
to as Phase II metabolism and may involve conjuga-
tion with a range of different chemical species
including glucuronic acid, sulphate or methyl
groups. There is a well studied polymorphism with
clinical implementation of phenotype testing which
affects methylation of the drug mercaptopurine
where ~0.3% of individuals lack an enzyme called
thiopurine methyltransferase (TPMT) which again
arises due to the presence of inactivating genetic
polymorphisms on both copies of the gene.13
The
TPMT gene product is of minor importance com-
pared with the CYP family in terms of drug meta-
bolism generally but is current the most important
pharmacogenetic example of a polymorphism
affecting Phase II metabolism.
Genetic polymorphism can also lead to altera-
tions in drug targets. Depending on the individual
drug, these targets can be specific receptors on the
cell surface, enzymes, ion channels or transporters
for physiological mediators. There is now a large
body of data from studies on polymorphisms in
these targets that can modulate drug response
though findings from these studies are not always in
complete agreement. One very well studied example
of a drug target subject to extensive genetic poly-
morphism affecting drug response is vitamin K
epoxide reductase which is encoded by the gene
VKORC1 and is the target for warfarin and other
coumarin anticoagulants. This enzyme has a key
role in regeneration of reduced vitamin K during
the blood coagulation process. Common poly-
morphisms affect the amount of enzyme present
and this affects the amount of anticoagulant drug
required to achieve enzyme inhibition whereas rare
mutations can lead to complete loss of warfarin
responsiveness.14
In addition to variation in drug metabolism and
drug targets, pharmacogenetics also covers the area
of adverse drug reactions which may involve an
exaggerated drug response, interaction with an
inappropriate target or an inappropriate immune
response to the drug. As discussed below, a very
strong association between a particular human
leucocyte antigen (HLA) allele (HLA-B*57:01) and
hypersensitivity reactions to the anti-HIV drug aba-
cavir has been well validated and is a good example
of a pharmacogenetic test used widely in the clinic
prior to drug prescription, with abacavir not now
being prescribed for individuals positive for HLA-
B*57:01. HLA proteins are involved in T-cell
mediated immune reactions and several other asso-
ciations between HLA genotypes and adverse drug
reactions have also been identified.15
The main pharmacogenetic polymorphisms for
which there is evidence for well replicated functional
effects are listed in Table 1. Specific individual drug
examples relating to each are considered below.
Variation in dose
Warfarin and related coumarin
anticoagulants
Up to the present, drugs have been generally pre-
scribed at a single dose, with dosing on an individ-
ual basis rare. Warfarin and other coumarin
anticoagulants are an important exception to this
with individualized dosing based on response
measured by the coagulation rate an essential part
of ensuring an adequate drug response while avoid-
ing potentially fatal bleeding. This individualized
dosing has involved starting treatment at a standard
dose which is then titrated over a period of days or
weeks until the required coagulation rate based on
prothrombin time (international normalized ratio
(INR)) is achieved. The cytochrome P450 CYP2C9
has a key role in warfarin metabolism. The gene
encoding this enzyme has been well studied with the
effect of two common variant alleles CYP2C9*2 and
3
General review of pharmacogenetics, 2017

CYP2C9*3, which each code for proteins with single
amino acid changes (nonsynonymous mutations),
detected. Both proteins show slower than normal
oxidation of the more active enantiomer S-warfarin
with the decreased activity of the CYP2C9*3 variant
greater than that for the CYP2C9*2 variant.25
It is
also well established that on average individuals who
carry one or two copies of these CYP2C9 variant
alleles require a lower dose of warfarin to achieve
the target INR value.25
Following the studies demon-
strating that CYP2C9 genotype was a predictor of
warfarin dose requirement, the gene encoding the
VKORC1 target was cloned and sequenced.26
This
led to studies on polymorphism in VKORC1 and the
possibility that variation in this gene could also affect
dose requirement. While nonsynonymous mutations
are rare in VKORC1, polymorphisms in non-coding
sequences are common and some of these appear to
result in lower gene expression.27
The presence of
polymorphisms in VKORC1 that are associated with
decreased expression correlates well with a lower
warfarin dose requirement. The finding of specific
associations of CYP2C9 and VKORC1 genotypes
with stable warfarin dose requirement prompted sev-
eral RCTs to determine whether genotype-guided
dosing during initiation of coumarin anticoagulant
treatment would result in a better outcome of
treatment.
Use of algorithms that include genotype for both
CYP2C9 and VKORC1 to predict initial coumarin
anticoagulant dosing have given mixed results in
RCTs. A study based in Europe which used a point
of care genotyping assay which enabled the
genotype-guided dose to be determined prior to the
start of treatment reported that genotype-guided
dosing resulted in a significantly increased percent-
age of time in the target INR range during the first 3
months of dosing.28
On the other hand, a USA-
based study with a generally similar protocol except
that genotype information was only incorporated
into dosing ~2 days after the start of dosing failed to
demonstrate any advantage for genotyping.29
The
discrepant findings might relate to the US study
including African-American patients as well as
Europeans combined with the lack of genotype data
at the start of dosing and use of a different dosing
Table
1
Summary
of
key
pharmacogenetic
polymorphisms
in
germline
DNA
relevant
to
drug
treatment
Gene
Gene
product
Effect
of
polymorphism
Examples
of
drugs
affected
References
CYP2D6
Cytochrome
P450
CYP2D6
Variant
alleles
may
result
in
(i)
absence
of
activity,
(ii)
decreased
activity
or
(iii)
increased
activity
Debrisoquine,
tricyclic
antidepressants,
metoprolol,
timolol,
tamoxifen,
codeine,
tramadol,
eliglustat
16
CYP2C19
Cytochrome
P450
CYP2C19
Clopidogrel,
diazepam,
omeprazole
17
CYP2C9
Cytochrome
P450
CYP2C9
Warfarin,
diclofenac,
ibuprofen,
phenytoin,
glipizide
and
other
sulphonylureas
18
CYP3A5
Cytochrome
P450
CYP3A5
No
activity
in
many
individuals
Tacrolimus
19
BCHE
Butyrylcholinesterase
Absence
of
activity
Succinylcholine
20
TPMT
Thiopurine
methyltransferase
Absence
of
activity
6-Mercaptopurine,
azathioprine
13
NAT2
N-acetyltransferase
2
Absence
of
activity
Isoniazid,
hydralazine
21
UGT1A1
UDP-glucuronosyltransferase
1A1
Decreased
gene
expression
or
enzyme
activity
Irinotecan,
atazanavir,
bilirubin
22
SLCO1B1
Organic
anion
transporting
polypeptide
1B1
Decreased
transport
activity
Statins
23
VKORC1
Vitamin
K
epoxide
reductase
Common
polymorphisms
decrease
expression
Rare
mutations
are
associated
with
resistance
to
coumarin
anticoagulant
treatment
Warfarin
and
other
coumarin
anticoagulants
24
HLA-B
HLA-B
antigen
Many
common
polymorphisms
affecting
peptide
presentation
to
T
cells
Abacavir,
carbamazepine
and
others
15
4 A.K. Daly, 2017

algorithm.30
Subsequent to publication of the find-
ings from the two RCTs, a large RCT comparing
warfarin with a recently developed novel oral anti-
coagulant reported that knowledge of CYP2C9 and
VKORC1 genotype may be important in prescribing
warfarin.31
In particular, patients positive for several
variant alleles in these genes were more likely to
experience bleeding soon after starting warfarin
treatment and might therefore benefit from use of an
alternative anticoagulant. This trial included larger
numbers of patients than the previous genetic algo-
rithm dosing based studies and these larger numbers
enabled the question of early bleeding, which is a
relatively rare event, to be assessed.
In summary, there is still uncertainty concerning
the value of genotyping prior to treating patients with
warfarin but some positive evidence pointing to a
benefit in fixing dose if genotype data is available at
the start of treatment. The possibility of treating
patients who are more likely to suffer bleeding on
warfarin due to their combined CYP2C9/VKORC1
genotype with an alternative anticoagulant has been
proposed.31
This is certainly feasible in view of the
development of effective alternatives to warfarin in
the direct-acting oral anticoagulants (DOACs) such
as rivaroxaban and dabigatran which are increasingly
being prescribed in preference to warfarin for many
patients. There are some disadvantages with DOACs
and, in view of the fact that treatment with warfarin
has been very effective for many patients over many
years, there is still a place for this drug, especially if
its prescription can be combined with routine geno-
typing in the future. The cost of DOACs is high at
present and more studies are needed to confirm
superiority of these drugs over warfarin.32
Thiopurines
The thiopurines azathioprine and 6-mercaptopurine
(6MP) are used widely as immunosuppressants, with
6MP also a key drug in treatment of childhood acute
lymphoblastic leukaemia. Azathioprine is a precursor
of 6-mercaptopurine. Metabolism of 6MP is com-
plex but there is an important contribution to detoxi-
cation from thiopurine methyltransferase (TPMT),
which, as discussed in the previous section, is subject
to a well understood genetic polymorphism.13
If trea-
ted with thioguanine drugs, the ~0.3% of Europeans
who lack TPMT activity will have higher than nor-
mal levels of thioguanine nucleotides, which are gen-
erated from 6MP and are essentially the active form
of the drug. Thioguanine nucleotides have several
different inhibitory effects on purine nucleotide inter-
conversion. High levels of thioguanine nucleotides
are associated with myelosuppression and use of
thiopurine drugs in individuals who lack TPMT at
the normal dose may result in this serious toxicity.
For this reason, it is now recommended that patients
have their TMPT status determined prior to thiopur-
ine drug prescription. As reviewed recently,33
this
can be done either by measuring levels of the enzyme
in red blood cells or by genotyping for two common
variant alleles. In general, individuals who lack
TPMT will not be prescribed thioguanines as immu-
nosuppressants but, in leukaemia patients, a greatly
decreased dose is prescribed (~20-fold lower than
normal) with close monitoring during treatment.34
Approximately 10% of European populations are
heterozygous; these individuals will be identified
accurately only by genotyping but measurement of
TPMT enzyme levels, which will be lower than aver-
age, is a reasonable predictor. It has been recom-
mended that these individuals can still be prescribed
thiopurines but that lower drug doses (30–70% of
normal) should be used initially with monitoring of
full blood counts with upward titration of dose over
time if appropriate.34,35
Tacrolimus
Tacrolimus is used widely as an immunosuppressant
in solid organ and haematopoetic stem cell transplant
patients. Though a very effective drug, it has a nar-
row therapeutic range. Since this drug was first used
in the 1990s, therapeutic drug monitoring to measure
plasma levels and adjust dose if necessary has been
routine. It is well established that individuals who
express the cytochrome P450 CYP3A5 require on
average a higher dose of this drug to achieve the
required plasma levels.19
Only ~10% of Europeans
express this cytochrome P450 with the majority lack-
ing this enzyme due to being homozygous for a
5

polymorphism affecting RNA splicing (CYP3A5*3
allele). Expression of this enzyme is higher in those
from the African subcontinent, including African-
Americans, with ~55% of African-Americans being
positive for one or two copies of the normal
CYP3A5*1 allele.36
The majority of cytochrome
P450-mediated metabolism of tacrolimus is via the
universally expressed CYP3A4. The other widely
used calcineurin inhibitor cyclosporine is also meta-
bolized by CYP3A4 with CYP3A5 only making a
minor contribution with most studies indicating no
significant difference in metabolism between CYP3A5
expressors and non-expressors.37
Current recommen-
dations from CPIC for tacrolimus dosing suggest that
if CYP3A5 genotype information is available prior to
this drug being prescribed, a starting dose 1.5–2 times
higher than normal could be used.38
However, there
is currently no recommendation for routine genotyp-
ing prior to prescription since therapeutic drug moni-
toring to determine levels of this drug is used
routinely worldwide.
Eliglustat
Eliglustat is a recently developed treatment for
Gaucher disease type 1.39
This is a rare lysosomal
storage disorder in most populations but affects ~1
in every 800 individuals of Ashkenazi Jewish des-
cent. It is a licensed drug in both the European
Union and the United States but regulators mandate
CYP2D6 testing before prescription with specific
dose recommendations for both extensive metaboli-
zers (84 mg twice daily) and poor metabolizers
(84 mg once daily) because there is a risk of cardiac
arrthymias at high plasma concentrations. Patients
who genotype as ultrarapid metabolizers should not
be treated with this drug because it is not possible
to establish a safe dose. Though metabolism by
CYP2D6 is relevant to many drugs,40
this appears
to be the first example of a drug where a CYP2D6
genotyping test is mandated before treatment with
very specific guidelines on dosing.
Succinylcholine
Succinylcholine is a valuable muscle relaxant used in
anaesthesia. The existence of a rare inability to
metabolize this drug normally resulting in succinyl-
choline apnoea has been well established since the
1950s. This is due to impaired butyrylcholinesterase
activity. The gene encoding this Phase I metabolizing
enzyme, BCHE, has been well studied and a number
of different mutations responsible for the deficiency
have been identified.20
Use of a biochemical test
rather than direct genotyping is still the preferred
method for identifying those carrying mutations due
to the rarity of the problem and the number of differ-
ent mutations. The test will be done when patients
show sensitivity to succinylcholine and testing of
other family members may also be performed.41
Screening for the more common BCHE variants is
also included in at least one direct to consumer gen-
etic testing service available in the UK.42
Irinotecan
Irinotecan is an anticancer drug which, following
conversion to an active metabolite (SN-38), acts as a
topoisomerase I inhibitor. The overall metabolic
pathway for this drug is complex but glucuronida-
tion by the enzyme UGT1A1 is an important detoxi-
cating step for SN-38.43
UGT1A1 is also the main
enzyme responsible for the bilirubin glucuronidation
and is subject to a well-characterized polymorphism
which results in raised serum bilirubin. This is usu-
ally referred to as Gilbert’s syndrome. The most
common polymorphism associated with Gilbert’s
syndrome is a 2 bp insertion in the promoter region
(UGT1A1*28 allele) but additional polymorphisms
which result in amino acid substitutions can also
give rise to the condition.44
Individuals homozygous
or heterozygous for polymorphisms associated with
Gilbert’s syndrome appear to be at increased risk of
toxicity with irinotecan.43
The FDA-approved drug
label recommends that UGT1A1*28 genotyping
should be performed prior to administration of this
drug due to the increased risk of neutropenia in
patients homozygous for this allele.45
A lower dose
of the drug for homozygotes is suggested with a spe-
cific recommendation from a Dutch working group
on pharmacogenetics of a 30% reduction in those
receiving more than 250 mg/m2
but no specific rec-
ommendation for lower doses.46
6 A.K. Daly, 2017

In general, though there is now considerable
data to suggest that UGT1A1*28 genotype is an
important predictor of neutropenia related to irino-
tecan, additional genetic factors may also need to
be considered to provide a comprehensive individ-
ual risk prediction. Overall, pharmacogenetics data
relating to irinotecan is quite limited probably
because this drug is used mainly in small numbers
of patients with advanced tumours. For example, a
recent systematic review on colorectal cancer treat-
ment regimens including this drug involved only
five studies with ~1700 patients.47
Isoniazid
Since the 1950s, isoniazid has been a key drug in the
treatment of tuberculosis. Variation between indivi-
duals in urinary excretion profiles was described soon
after the drug was first used.48
Acetylation of the
drug was established to be an important metabolic
pathway. The incidence of a common adverse reac-
tion, peripheral neuritis, appeared higher in those
showing slow conversion of the parent drug to acety-
lisoniazid.49
Further studies led to the conclusion that
isoniazid acetylation was subject to a genetic poly-
morphism with some individuals (~10% of East
Asians but 50% of Europeans) described as slow
acetylators. Slow acetylation was shown to be a reces-
sive trait. As reviewed in detail elsewhere,21
the rele-
vant gene, which is now termed N-acetyltransferase 2
(NAT2) was subsequently cloned and sequenced with
a number of coding region polymorphisms shown to
be diagnostic for the slow acetylator phenotype.
While isoniazid remains a very valuable drug in the
treatment of tuberculosis, it is now well recognized
that ~2% of patients treated with this drug, usually
in combination with other agents, suffer potentially
serious hepatotoxicity.50
The risk appears higher in
slow acetylators, though it has also been suggested
that this group show a better overall response to
treatment due to slower drug clearance.
A small RCT based in Japan involving differential
dosing with isoniazid on the basis of NAT2 genotype
showed significant findings, with a lower incidence
of hepatotoxicity when slow acetylators were given a
lower drug dose.51
This is an interesting finding but
needs further follow up before clinical implementa-
tion of dosing based on genotype.
Absence of benefit from prescribed
drug
A relatively large number of drugs in use today are
prodrugs. It has been suggested that the overall
impact of pharmacogenetic polymorphism in relation
to prodrugs is higher than for drugs where the parent
drug represents the active form.52
If an enzyme activ-
ity that contributes to active drug formation is com-
pletely absent, there may be no benefit to the patient
from the drug. Two well established examples are
considered in detail in this section.
Codeine and related compounds
Codeine requires activation to morphine by CYP2D6
for effective analgesia. Codeine can also be converted
to other metabolites but these lack analgesic activity
(see Fig. 1 or https://www.pharmgkb.org/pathway/
PA146123006). O-demethylation of codeine was
shown to be subject to similar genetic variation to
debrisoquine in early studies54
and a clear difference
between CYP2D6 poor metabolizers and extensive
metabolizers in extent of analgesia from this drug
was demonstrated in volunteers.55
Data on patients
in relation to response is still quite limited but it is
generally accepted that CYP2D6 poor metabolizers
are unlikely to benefit from codeine as an analgesic.
There is also more limited evidence that other opioids
especially tramadol may also be ineffective.56
For
some codeine-related analgesics, especially hydroco-
done and oxycodone, the parent drug is able to
bind more tightly to the mu opioid receptor57
but
the morphone metabolites shows stronger bind-
ing. For these compounds, it remains uncertain
whether the level of interaction by the parent drug is
adequate for analgesia in poor metabolizers. Current
CPIC recommendations suggest avoiding codeine, tra-
madol, oxycodone and hydrocodone use in CYP2D6
poor metabolizers and instead using morphine or a
nonopioid analgesic as an alternative.56
An additional issue with codeine and related pro-
drugs arises with CYP2D6 ultrarapid metabolizers
7

who have extra copies of CYP2D6 and higher than
normal activity. Under certain circumstances such
individuals may suffer serious, potentially fatal,
adverse reactions with codeine due to high levels of
morphine being generated. This appears to be a par-
ticular problem with babies and children though
there are also some reports of adverse reactions in
adults. This concern was prompted by a report of a
breast fed baby who died 13 days after birth.58
Further investigation found that stored breast milk
contained a high level of morphine which had been
generated by high CYP2D6 activity in the mother
who was an ultrarapid metabolizer. The baby had a
normal CYP2D6 genotype. Other reports of serious
toxicity where either children or adults were ultrara-
pid metabolizers and were prescribed codeine as an
analgesic have also appeared.59,60
It is possible that
genotype for the UGT2B7 gene which codes for the
morphine glucuronidating enzyme may also affect
susceptibility to this toxicity in ultrarapid metaboli-
zers.59
After further reports of fatalities or serious
toxicities in children in the USA,61
regulatory author-
ities worldwide have issued recommendations not to
prescribe codeine for analgesia in children with
restrictions on use and dosing for up to 18 years
old.62
The particular problem with children may
relate to differences in expression of genes relevant
to drug metabolisn including CYP2D6 or simply
Fig. 1 Genes contributing to morphine and codeine metabolism. This ﬁgure illustrates the key role of CYP2D6 in
the conversion of codeine to morphine. Codeine may also be metabolized directly to norcodeine and codeine-6-
glucuronide but these metabolites are believed to lack analgesic activity (https://www.pharmgkb.org/pathway/
PA146123006).53
Reproduced with permission of PharmGKB and Stanford University.
8 A.K. Daly, 2017

overall ratio of liver mass to body mass with
increased clearance of a number of drugs seen in this
patient group.63
CPIC guidelines recommend avoid-
ing use of codeine and also related compounds such
as tramadol in CYP2D6 ultrarapid metabolizers,
both children and adults.56
Currently, routine CYP2D6 genotyping is not
being performed prior to prescription of codeine or
related opioids, though it is possible that prescribers
may occasionally have access to this data from
patient medical records in centres where pharmaco-
genetic testing is being done preemptively.
Clopidogrel
Clopidogrel is a very widely used antiplatelet drug which
is also a prodrug. Though developed comparatively
recently and first licensed for use in the USA and
Europe in the 1990s, detailed knowledge about the
enzymes involved in its activation in humans was
relatively limited until just over 10 years ago when a
study on response by measurement of platelet aggre-
gation rate in volunteers of known cytochrome
P450 genotype for a variety of different isoforms
were performed.64
This indicated an important contri-
bution by the cytochrome P450 CYP2C19 to response
because of a limited response in volunteers heterozy-
gous for the absence of activity allele CYP2C19*2. A
subsequent in vitro metabolism study confirmed that
though a number of different cytochromes P450
contribute to clopidogrel activation, CYP2C19 makes
an important contribution to both activation steps
(see Fig. 2 or https://www.pharmgkb.org/pathway/
PA154424674).66
Response to clopidogrel was also
investigated by a genome-wide assocation study
concerned with response to the drug in a healthy vol-
unteer group.67
This was consistent with a significant
role for CYP2C19 and no polymorphisms outside the
CYP2C locus showed genome-wide significance, so
there was no evidence for a strong effect by other gen-
etic factors on clopidoprel response.
A large number of clinical studies concerned with
the relevance of CYP2C19 metabolizer status to clo-
pidogrel response have now been reported. In par-
ticular, an early meta-analysis on the risk of further
cardiovascular events in patients treated with
clopidogrel following percutaneous coronary inter-
vention confirmed a significant association for car-
riage of at least one CYP2C19*2 allele.68
However, a
subsequent larger meta-analysis and systematic review
found that a small increase in risk for CYP2C19*2
carriage was abolished after correcting for factors such
as small study numbers.69
Subsequently, a large num-
ber of observational studies concerned with both car-
diovascular and cerebrovascular events have appeared,
some reporting no association and others effects by
CYP2C19 genotype. RCTs where CYP2C19 poor
metabolizers and those heterozygous for variant
alleles are given alternative antiplatelet agents where
CYP2C19 does not contribute to metabolism, par-
ticularly ticagrelor, are in progress worldwide. These
include the Tailor PCI study70
and the POPular
study.71
One recent report from China where
CYP2C19 poor metabolizers are more common than
in Europe or the USA found a reduced rate of adverse
cardiovascular events when poor metabolizers were
treated with ticagrelor in place of clopidogrel.72
In 2010, the FDA added a boxed warning to the
clopidogrel label stating that CYP2C19 poor meta-
bolizers may not benefit from treatment with this
drug and that a genetic test to determine CYP2C19
status is available.73
CPIC guidelines recommend the
use of alternative antiplatelet drugs such as prasugrel
and ticagrelor in both poor metabolizers and those
carrying one loss of activity allele.74
At present, it
appears that genotyping is not being performed
widely but prescription of alternative antiplatelet
drugs to clopidogrel for all patients needing this
treatment is increasing.
Idiosyncratic toxicity
Idiosyncratic adverse drug reactions can occur in
response to a wide range of drugs. These reactions
are generally very rare but may have serious,
potentially fatal, consequences. In the past 20
years, progress has been made in identifying gen-
etic risk factors for several of these reactions.75,76
Up to the present, the strongest genetic risk fac-
tors are certain HLA alleles and this has resulted
in clinical implementation of HLA genotyping
prior to prescription of some drugs as discussed
9

below. Additional HLA associations with idiosyn-
cratic adverse drug reactions have also been
reported but their predictive value is insufficient
to justify clinical implementation.
This section focusses on two well-established HLA
associations with idiosyncratic adverse drug reactions
for which genotyping has been implemented prior to
prescription in a number of countries worldwide.
Abacavir
A severe hypersensitivity reaction to the reverse tran-
scriptase inhibitor abacavir which is a cheap and
effective drug used widely to treat HIV. This reaction
affects ~5% of patients treated and involves a skin
rash with gastrointestinal and respiratory symptoms.
Though it may be initially relatively mild and resolves
following drug withdrawal, reexposure subsequently
is likely to result in more severe, potentially fatal,
symptoms. An association between abacavir hyper-
sensitivity and a HLA haplotype including HLA-
B*57:01, HLA-DR7 and HLA-DQ3 was initially
demonstrated by Mallal and colleagues using a candi-
date gene approach77
and then replicated in other
cohorts.78,79
These findings were confirmed in a large
RCT.80
The findings from this trial led to widespread
Fig. 2 Genes contributing to clopidogrel metabolism. The role of CYP2C19 in both activation steps is shown
here https://www.pharmgkb.org/pathway/PA154424674.65
Reproduced with permission of PharmGKB and
Stanford University.
10 A.K. Daly, 2017

adoption of genetic testing for B*57:01 prior to initi-
ation of abacavir treatment with a requirement for test-
ing from regulators including the FDA and EMA.81,82
Carbamazepine
The anticonvulsant drug carbamazepine can give rise
to skin rash in some patients. This skin rash can
sometimes be very severe and involve skin blistering
in the conditions known as Stevens–Johnson syn-
drome and toxic epidermal necrolysis. A study based
in Taiwan involved genotyping for HLA alleles in
cases of carbamazepine-induced Stevens–Johnson
syndrome and reported a very strong association of
this adverse drug reaction with the Class I allele
HLA-B*15:02.83
Genotyping for this allele is now
recommended in individuals of Han Chinese, Thai,
Malaysian, Indonesian, Philippino and South Indian
ethnicity prior to carbamazepine prescription in a
number of countries84
but the association does not
extend to most other ethnic groups, probably because
the frequency of HLA-B*15:02 is much lower outside
East Asia. A randomized clinical trial based in
Taiwan showed that genotyping for HLA-B*15:02
combined with treatment of those positive for this
allele with an alternative drug was strongly associated
with a decrease in the incidence of carbamazepine-
induced Stevens–Johnson syndrome and toxic epider-
mal necrolysis.85
HLA-B*15:02 does not appear to
be a risk factor for more common mild skin rash reac-
tions induced by carbamazepine but an association
involving another HLA allele A*31:01 and
carbamazepine-induced skin rash of varying severity
has now been shown for both European and Japanese
individuals.86,87
However, genotyping for this add-
itional HLA risk factor is considered to have more
limited clinical utility so is not done routinely.
Non-HLA risk factors
The two HLA examples discussed in detail above
have been implemented clinically but it should be
emphasized that HLA genotype is not a universal
predictor for idiosyncratic adverse drug reactions
with some examples of non-HLA genetic risk fac-
tors for adverse drug reactions also identiﬁed,
though these are currently less well established and
have lower predictive value. One of the best examples
of a non-HLA genetic risk factor that contributes to
an adverse drug reaction relates to statin-induced
myopathy. This usually involves an asymptomatic rise
in creatine phosphokinase levels which reverses fol-
lowing drug discontinuation but on rare occasions
can be more serious.88
A polymorphism in the gene
SLCO1B1, which codes for a transporter which
transports statins and various other drugs into
hepatocytes, has been reproducibly associated
with increased risk of statin-related myopathy.89
The mechanism underlying toxicity may involve an
increased plasma level of the drug which facilitates
inappropriate transfer into muscle tissue. It is likely
that additional genetic risk factors may contribute to
statin myopathy but these are still not well under-
stood. Because the effect of SLCO1B1 genotype
varies between different statins but is particularly
relevant to simvastatin, CPIC guidelines for pre-
scription of this drug based on SLCO1B1 genotype
have been developed.90
These recommend a lower
dose of simvastatin or an alternative drug in those posi-
tive for the variant allele (rs4149056). Implementation
of these guidelines is very limited worldwide and
the relevance of SLCO1B1 genotype to other sta-
tins is still less well studied. In view of the very
widespread use of statins, this pharmacogenetic
example still shows potential for more widespread
adoption.
Clinical implementation of
pharmacogenetic testing and future
prospects
Despite continuing strong interest in the clinical
application of pharmacogenetic testing especially as
precision medicine becomes increasingly import-
ant,91
widespread adoption of pharmacogenetic
testing has not taken place to date with only the
few examples discussed in detail above, especially
TPMT testing prior to thiopurine prescription and
HLA-B*57:01 typing prior to abacavir prescrip-
tion, being adopted widely. Ongoing clinical trials,
such as the Tailor PCI study on clopidogrel may
lead to increased testing though it is also possible
that use of alternative drugs not requiring a genetic
11

test may become the default, especially as these
become cheaper. Testing may well be more likely to
be required in the future with newly developed
drugs similar to the example relating to eliglustat
and CYP2D6 testing discussed above.
Table 1 summarizes a number of key pharmaco-
genetic polymorphisms where relevance to drug
treatment has been demonstrated clearly. For most
of these, however, with the exception of the two
examples mentioned above, there is still only lim-
ited data showing clear benefit for genotyping prior
to drug prescription due to lack of randomized clin-
ical trials or unclear outcomes from such trials.
Increasingly, genomic information relating to indi-
vidual patients which will include data on the
examples listed in Table 1 is becoming available to
prescribers. In the UK, the 100 000 genomes study
will provide pharmacogenetic information on the
large number of patients who have been included in
the study.92
Precise arrangements for making this
information available to prescribers are still unclear
but it seems likely to be available in the near future.
The availability of these data as part of an elec-
tronic medical record is likely to drive the imple-
mentation of genotype-guided prescribing, as is
already happening in some centres internationally
based on more limited DNA sequencing.93
In sev-
eral European countries, U-PGx, a project on pre-
emptive genotyping for a range of pharmacogenetic
polymorphisms is in progress; the genotypic infor-
mation generated is being made available to prescri-
bers and outcomes observed.94
Direct to consumer
genetic testing by companies such as 23andMe is
also providing pharmacogenetic information; there
are examples reported where patients request that
these data be used to guide their treatment.95
In addition to using already well-established
pharmacogenetics knowledge more efficiently,
developments in genomics including genome-wide
association studies provide well-replicated data on
genetic risk factors for complex diseases. Some of
these novel risk factors may be useful therapeutic
targets for either newly developed or existing
drugs.96,97
Knowledge of patient genotype for these
targets is likely to be important in prescribing these
drugs in the future.
All these developments mean that pharmacoge-
netic information is likely to be available routinely
in the future, especially in technologically advanced
settings, and this may influence prescribing of a
range of drugs beyond those where testing prior to
prescription is required currently. Already, as dis-
cussed elsewhere, precision cancer treatment based
mainly on the tumour genotype is being implemen-
ted successfully.6
Conflict of interest statement
The authors have no potential conflicts of interest.
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platelet effect and clinical efficacy of clopidogrel
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68. Mega JL, Simon T, Collet JP, et al. Reduced-function
CYP2C19 genotype and risk of adverse clinical out-
comes among patients treated with clopidogrel pre-
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69. Bauer T, Bouman HJ, van Werkum JW, et al. Impact of
CYP2C19 variant genotypes on clinical efficacy of anti-
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70. https://clinicaltrials.gov/ct2/show/NCT01742117 (7 April
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71. Bergmeijer TO, Janssen PW, Schipper JC, et al. CYP2C19
genotype-guided antiplatelet therapy in ST-segment eleva-
tion myocardial infarction patients—rationale and design
of the patient outcome after primary PCI (POPular) genet-
ics study. Am Heart J 2014;168:16–22.e1.
72. Shen DL, Wang B, Bai J, et al. Clinical value of
CYP2C19 genetic testing for guiding the antiplatelet ther-
apy in a Chinese population. J Cardiovasc Pharmacol
2016;67:232–6.
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SafetyInformationforPatientsandProviders/ucm203888.
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74. Scott SA, Sangkuhl K, Stein CM, et al. Clinical Pharmaco-
genetics Implementation Consortium guidelines for
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CYP2C19 genotype and clopidogrel therapy: 2013
update. Clin Pharmacol Ther 2013;94:317–23.
75. Daly AK. Pharmacogenomics of adverse drug reactions.
Genome Med 2013;5:5.
76. Collins SL, Carr DF, Pirmohamed M. Advances in the
pharmacogenomics of adverse drug reactions. Drug Saf
2016;39:15–27.
77. Mallal S, Nolan D, Witt C, et al. Association
between presence of HLA-B*5701, HLA-DR7, and
HLA-DQ3 and hypersensitivity to HIV-1 reverse tran-
scriptase inhibitor abacavir. Lancet 2002;359:727–32.
78. Hetherington S, Hughes AR, Mosteller M, et al. Genetic
variations in HLA-B region and hypersensitivity reac-
tions to abacavir. Lancet 2002;359:1121–2.
79. Hughes AR, Mosteller M, Bansal AT, et al. Association
of genetic variations in HLA-B region with hypersensi-
tivity to abacavir in some, but not all, populations.
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80. Mallal S, Phillips E, Carosi G, et al. HLA-B*5701
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safetyinformationforpatientsandproviders/ucm123927.htm
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86. Ozeki T, Mushiroda T, Yowang A, et al. Genome-wide
association study identiﬁes HLA-A*3101 allele as a gen-
etic risk factor for carbamazepine-induced cutaneous
adverse drug reactions in Japanese population. Hum
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A*3101 and carbamazepine-induced hypersensitivity reac-
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91. Cardon LR, Harris T. Precision medicine, genomics and
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genetic-test-results-in-a-clinical-setting-a-case-report.php
96. Barrett JC, Dunham I, Birney E. Using human genetics
to make new medicines. Nat Rev Genet 2015;16:561–2.
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human genetic evidence for approved drug indications.
Nat Genet 2015;47:856–60.
15

Series
www.thelancet.com Published online August 5, 2019 http://dx.doi.org/10.1016/S0140-6736(19)31276-0 1
Genomic Medicine 2
Pharmacogenomics
Dan M Roden, Howard L McLeod, MaryV Relling, Marc SWilliams, George A Mensah, Josh F Peterson, Sara LVan Driest
Genomic medicine, which uses DNA variation to individualise and improve human health, is the subject of this
Series of papers. The idea that genetic variation can be used to individualise drug therapy—the topic addressed
here—is often viewed as within reach for genomic medicine. We have reviewed general mechanisms underlying
variability in drug action, the role of genetic variation in mediating beneficial and adverse effects through variable
drug concentrations (pharmacokinetics) and drug actions (pharmacodynamics), available data from clinical trials,
and ongoing efforts to implement pharmacogenetics in clinical practice.
Introduction
One tenet of clinical medicine is that patients vary in their
response to drugs: doses effective in some patients will
inevitably be ineffective or cause adverse drug reactions
(ADRs) in others. ADRs have been implicated as an
important cause of hospital admissions, in one series
accounting for 6·5% of all hospitalisations in two large
UK hospitals.1
In the 1990s, a large survey suggested that
ADRs occurring in hospitals were the fourth to sixth
leading cause of in-hospital mortality in the USA,2
and a
follow-up survey in 2010 showed no improvement.3
Fewer
data are available on the consequences of the lack of
efficacy, beyond recognising that only a proportion of a
given patient population derives benefit from a given
medication. The treatment of common diseases, such as
hypertension, arrhythmias, or depression often involves a
series of therapeutic trials among different drugs or
classes of drugs, and the health-care burden imposed by
lack of efficacy during these periods of trial and error can
be considerable. For example, ineffective antidepressant
therapy has been speculated to increase risk for suicide.4
There are many reasons for variability in drug
response. The inability of selected drug therapy to target
the underlying disease mechanism (which might or
might not be known), drug interactions, disease-related
changes in drug concentrations or responsiveness, poor
compliance, and system errors, such as failure to deliver
the correct drug or dose to the patient, are commonly
cited. In some instances, therapeutic non-responsiveness
and ADRs vary by race or ethnicity and can contribute to
disparities in clinical outcomes.5,6
This Series paper will
address how variation in the germline genome affects
drug response. Tumour sequencing, identification of
driver mutations, and implementation of mutation-
specific therapy, which are having a major impact in
cancer, have been reviewed in detail elsewhere and will
not be addressed further here.7
Mechanisms underlying variable drug responses
Archibald Garrod, who developed the concept of inborn
errors of metabolism, speculated a century ago that
aberrant metabolism of exogenous substances could
account for unusual reactions to food or drugs.8
During
and after World War 2, the first instances of genetically
determined ADRs were described, including haemolytic
anaemia in African-American soldiers with G6PD
deficiency exposed to antimalarials, malignant hyper
thermia during anaesthesia, and prolonged paralysis
following treatment with succinylcholine in patients with
pseudocholinesterase deficiency. The term pharma
co
genetics (panel) was coined by Motulsky14
at the University
of Washington, Seattle, WA, USA and Kalow15
at the
University of Toronto, Toronto, ON, Canada.
One review suggested that common genetic factors
contribute to variable serious ADRs in a third of cases.16
The field of pharmacogenomics aims to define these
Published Online
August 5, 2019
http://dx.doi.org/10.1016/
S0140-6736(19)31276-0
This is the second in a Series of
five papers about genomic
medicine
Department of Medicine
(Prof D M Roden MD,
J F Peterson MD,
S LVan Driest MD), Department
of Pharmacology
(Prof D M Roden), Department
of Biomedical Informatics
(Prof D M Roden, J F Peterson)
and Department of Pediatrics
(S LVan Driest),Vanderbilt
University Medical Center,
Nashville,TN, USA; DeBartolo
Family Personalized Medicine
Institute, Moffitt Cancer
Center,Tampa, FL, USA
(Prof H L McLeod PharmD);
Pharmaceutical Department,
Panel: Comments on nomenclature
The term pharmacogenetics was coined in the 1950s and captures the idea that large
effect size DNA variants contribute importantly to variable drug actions in an individual.
The term pharmacogenomics is now used by many to describe the idea that multiple
variants across the genome that can differ across populations affect drug response.
The International Conference on Harmonisation, a worldwide consortium of regulatory
agencies, has defined pharmacogenomics as the study of variations of DNA and RNA
characteristics as related to drug response, and pharmacogenetics as the study of
variations in DNA sequence as related to drug response.9
Pharmacogeneticists adopted a star nomenclature (eg, CYP2C19*2) to describe variants
in genes (sometimes termed pharmacogenes) underlying variability in drug response.
Some star alleles can include more than one variant (eg, TPMT*3A designates an allele
defined by the presence of two single-nucleotide polymorphisms [SNPs]), and
distinguishing this allele from those carrying only one of the SNPs can be challenging.10
Although the star nomenclature persists, as our understanding of the numbers of variants
in important pharmacogenes increases, attempts are being made to reconcile the
notation with alternate variant nomenclature, such as the conventional rs designation.11,12
Most variants studied to date partially or completely inhibit function of the encoded
protein. Occasionally, variants increase activity of drug-metabolising enzymes; examples
include CYP2C19*17 and CYP2D6 duplications.
The field is also adopting a standard set of definitions of pharmacogenetic phenotypes;
for pharmacokinetic genesthese include normal metabolisers, poor metabolisers (carrying
two loss-of-function alleles), intermediate metabolisers (carrying one loss-of-function
allele), and ultrarapid metabolisers (carrying gain-of-function alleles or gene duplications)
and for pharmacodynamic genesthese include designations such as positive or negative for
high-risk alleles.13
These are convenient shorthand designations, which often have some
overlap in drug response (figure 1A).

Series
2 www.thelancet.com Published online August 5, 2019 http://dx.doi.org/10.1016/S0140-6736(19)31276-0
St Jude Children’s Research
Hospital, Memphis,TN, USA
(Prof MV Relling PharmD);
Genomic Medicine Institute,
Geisinger, Danville, PA, USA
(Prof M SWilliams MD); and
Center forTranslation Research
and Implementation Science,
National Heart, Lung, and
Blood Institute, National
Institutes of Health, Bethesda,
MD, USA (G A Mensah MD)
Correspondence to:
Prof Dan M Roden, Department
of Medicine, Vanderbilt
University Medical Center,
Nashville,TN 37232–0575, USA
dan.roden@vumc.org
genetic mechanisms, and ultimately to implement
genetic testing to improve drug efficacy and reduce
toxicity. Furthermore, an understanding of the genetic
basis of variable drug response can be used as a tool to
expand the use of existing drugs to new indications and
to develop new drugs. Well recognised examples of
genetically determined variability in drug response often
involve single DNA variants common in a population
and associated with relatively large effect sizes and
clearly definable metaboliser phenotypes (figure 1A).
As a result, the implementation of pharmacogenomic
information into the clinical flow of medicine has been
viewed as within reach. However, several barriers are
now identified and need to be overcome to routinely
use pharmacogenomic variant data in improving drug
prescribing.
Two conceptual pathways describe an organism’s
overall response to drug exposure. Pharmacokinetics
defines variability in the processes (absorption, distribu
tion, metabolism, and elimination) modulating delivery
of drug and active metabolites to and removal from
their site or sites of action. Pharmacodynamics describes
variability in drug action that is not attributable to
variable drug concentrations, which can reflect vari
ability in the interaction of active drug with its effector
molecules or other mechanisms such as vari
ability
in disease mechanisms. The earliest examples of
pharmacogenomic variability involved variability in
pharmacodynamic processes. With the development of
robust methods to measure concentrations of drugs and
their metabolites in plasma and other sites in the 1960s
and 1970s came the ability to define patients who are
pharmacokinetic outliers in whom unusually high or
low plasma concentrations were associated with variable
efficacy or ADRs. This in turn led to studies defining
variants in key drug metabolising or transport genes as
the basis for these responses. More recently, agnostic
methods such as the genome-wide association study
(GWAS) have validated the role of these candidate genes
and have identified new loci associated with variable
drug responses.17
The majority of clinically actionable
pharmacogenetic traits described to date have a pharma
cokinetic basis (table 1).
Common genetic variants can produce large
drug response effects
Pharmacokinetic gene variation
Two scenarios illustrate how single gene variants affecting
pharmacokinetics can have especially large effects. The
first is with administration of a prodrug, a pharmaco
logically inactive substance that requires bioactivation
by drug metabolism to achieve its therapeutic effects
(figure 2). Such bioactivation pathways usually involve a
single drug-metabolising enzyme and genetic variants
that result in loss of function of these enzymes can
decrease or block drug action. Examples include codeine
bioactivated to its major active metabolite morphine by
CYP2D6 and the antiplatelet drug clopidogrel bioac
tivated by CYP2C19. Although these effects are well
established and might contribute to the perception
that pharmacogenomic variants are within reach for
implementation, it is important to recognise that there is
a spectrum of even these large pharmacogenomic effects.
Thus, in the case of clopidogrel, increasing the dose
resulted in an antiplatelet effect in heterozygotes for
CYP2C19*2 (the terminology for variants is further
explained in the panel), encoding a+ common loss-of-
function variant, because they still have demonstrable
CYP2C19 activity. By contrast, a dose increase did not
generate an antiplatelet effect in individuals homo
zygous for the variant because they completely lack
CYP2C19 activity.18
A GWAS of clopidogrel inhibition in
429 patients with ADP-related platelet activation resulted
in very strong signals (p<10–
¹³) at the CYP2C19 locus.19
Although the pharmaco
logical effect of CYP2C19*2 is
large, the total variability in clopidogrel antiplatelet effect
attributable to this variant was only 12%.19
This effect is
large for a single genetic variant; however, the finding
also emphasises that other genetic and environmental
factors have a role in observed variability in clopidogrel
drug action.
Most variants studied to date confer partial or complete
loss of function. However, gain-of-function variants in
bioactivation pathways have been described and can be
associated with excess drug response. Examples include
CYP2C19*17, which has been associated with bleeding
during clopidogrel therapy,20
and CYP2D6 duplications,
Figure 1: Profile of drug responses as influenced by a single pharmacogene variant (A) or multiple gene
variants (B)
Minimal Excessive
Frequency
Minimal
Drug response
Excessive
Frequency
A
B
Many predictors of minimal response
Many predictors of excessive response
Poor metabolisers
Intermediate metabolisers
Normal metabolisers
Ultrarapid metabolisers
Low
High
High
Low

Series
which have been associated with an excess narcotic
effect, including respiratory arrest, due to rapid and
increased accumulation of morphine during codeine
therapy (figure 2).21
The second situation in which single pharmacokinetic
variants can exert very large effects is during admin
istration of an active drug with a narrow therapeutic
range (ie, a small margin between therapeutic and toxic
doses), which undergoes elimination by a single drug
metabolising system (figure 2). The antileukaemic
drug 6-mercaptopurine is bioinactivated by TPMT and
xanthine oxidase. Loss-of-function TPMT variants result
in decreased inactivation, higher parent drug concen
trations, and increased generation of cytotoxic thio
guanine nucleotide metabo
lites; these nucleotides are
incorporated into DNA and associate with drug effect.
Individuals homozygous for loss-of-function variants in
TPMT will exhibit life-threatening bone marrow toxicity
with usual drug doses due to cytotoxic thioguanine nucle
otide accumulation.22
These nucleotides are themselves
metabolised by NUDT15, and NUDT15 loss-of-function
variants have also been associated with toxicity.22,23
The
thiopurine immunosuppressant drug azathioprine is
metabolised to 6-mercaptopurine and variants in TPMT
and NUDT15 are similarly associated with risk of
haematological toxicity.22
Similarly, variants in DPYD increase plasma concen
trations, and toxicity risk, of 5-fluorouracil and other
fluoropyrimidines such as capecitabine.24
Notably, loss-of-function variants can be mimicked by
interactions with drugs that inhibit the same drug
metabolism pathways, described as a phenocopy.
Examples of phenocopies include CYP2D6 inhibition by
some selective serotonin-reuptake inhibitors, CYP2C19
inhibition by many proton-pump inhibitors, and
xanthine oxidase inhibition by allopurinol, which by
inhibiting an alternate pathway for azathioprine and
6-mercaptopurine metabolism, can increase generation
of cytotoxic thioguanine nucleotides and thereby increase
toxicity.
Drugs metabolised predominantly by a single enzyme
but with wide therapeutic margins can have substantial
variability in pharmacokinetics because of pharmaco
genomic variants. However, because of the wide
therapeutic margin, these pharmacokinetic differences
might not drive clinically relevant variability in drug
efficacy or toxicity. Similarly, drugs with narrow thera
peutic margins that are inactivated by multiple enzymatic
pathways are also less susceptible to unusual responses
caused by pharmacogenomic variants, unless a combi
nation of genetic variants or interacting drugs affects
multiple pathways. For example, drug interactions or a
disease inhibiting one metabolic pathway combined with
genetic variation inhibiting a second pathway can account
for unusual drug responses.25
Drug transport into and out of cells by specific drug
transport molecules is another important potential
mediator of variable drug concentrations at effector sites
and thus drug action. The drug efflux transporter
OATP1B1 encoded by SLCO1B1 is responsible for
removal of simvastatin from the systemic circulation.
The common SLCO1B1*5 loss-of-function variant has
been associated with elevated simvastatin plasma
concentrations and an increased risk for simvastatin
Drug
Pharmacokinetic mechanisms
CYP2B6 Efavirenz
CYP2C19 Clopidogrel, SSRIs,TCAs, voriconazole, proton
pump inhibitors*
CYP2C9 Celecoxib*, phenytoin, warfarin
CYP2D6 Codeine, oxycodone, tramadol, SSRIs,TCAs,
ondansetron, tamoxifen, atomoxetine
CYP3A5 Tacrolimus
DPYD 5-fluorouracil, capecitabine, tegafur
TPMT and NUDT15 Azathioprine, mercaptopurine, thioguanine
SLCO1B1 Simvastatin
UGT1A1 Atazanavir
Pharmacodynamic mechanisms
CFTR Ivacaftor
CYP4F2 Warfarin
G6PD Rasburicase
HLA-B Abacavir, allopurinol, carbamazepine, phenytoin
IFNL3 (IL28B) Interferon
RYR1 and CACNA1S Inhaled anesthetics, succinylcholine
VKORC1 Warfarin
SSRI=selective serotonin reuptake inhibitor.TCA=tricyclic antidepressant.
*Guidelines in progress.
Table 1: Drugs and genes with guidelines from the Clinical
Pharmacogenetics ImplementationConsortium for use in clinical practice
For the Clinical
Pharmacogenetics
Implementation Consortium
see https://cpicpgx.org
Figure 2:The impact of variable pharmacokinetic gene function on the effect
of bioactivation of prodrug versus inactivation of an active drug
Codeine dose
CYP2D6 function
Prodrug
Active drug
Active drug concentration
TPMT function
No function
Decreased function
Normal function
Increased function
No morphine
Lower morphine
concentration
Expected morphine
concentration
High morphine
concentration
High risk of
haematological
toxicity
Risk of
haematological
toxicity
Expected drug
effect
Azathioprine or
6-mercaptopurine
dose
Normal function
No function
Decreased function

Series
myopathy,26,27
and contributes to variability in metho
trex
ate clearance in children treated for acute leukaemia.28
Warfarin is a well studied example of a drug in which
variable actions are determined by both pharmacokinetic
and pharmacodynamic gene variants, and in which
variant frequency is highly dependent on ancestry.
Warfarin is administered as a racemate, and bio
inac
tivation of the more active S-enantiomer is accom
plished
by CYP2C9. Gene variants that decrease CYP2C9 activity
are there
fore associated with an increase in S-warfarin
plasma concentration and a resultant intensified
pharmacological effect, manifest as an increase in the
international normal
ised ratio (INR) or bleeding risk.
The CYP2C9*2 and CYP2C9*3 variants are most com
mon in European ancestry populations; CYP2C9*3
reduces CYP2C9 activity to a greater extent than does the
CYP2C9*2 variant. Thus, patients heterozygous for
CYP2C9*2 might exhibit only a small pharmacogenomic
effect, whereas patients homozygous for CYP2C9*3
might exhibit drastic decreases in warfarin dose require
ment, and can be difficult to anticoagulate because of
day-to-day variability in INR.29,30
In populations of African
ancestry, these variants are rarer and other variants have
been reported.31,32
Pharma
codynamic variation also influences warfarin
effect. Traditional genetic linkage methods identified
loss-of-function variants in VKORC1 as the cause of the
rare syndrome of familial warfarin resistance, an absence
of a rise in INR even with exposure to very large doses of
warfarin;33
subsequent studies showed that VKORC1
encodes the warfarin target. A common promoter
polymorphism in VKORC1 is associated with variability
in hepatic mRNA concentrations and in warfarin
dose requirement.34
Moreover, rarer reduction-of-
function coding region variants in VKORC1, associated
with increased warfarin dose requirements, have been
described and vary by ancestry; for example, a variant
encoding D36Y is common (minor allele frequency of
5%) in Ashkenazi populations.35
Multiple GWAS of variability in warfarin steady state
dose requirements have yielded very strong signals at
CYP2C9, VKORC1, and at CYP4F2 (a gene responsible
for bioinactivation of vitamin K).36–39
In African-American
patients, a GWAS identified a separate signal (whose
specific function remains to be defined) near CYP2C8–
CYP2C9.32
An estimated 50% of the variability in
warfarin dose requirement has been attributed to
common genetic variation identified in these studies.
Other pharmacodynamic gene variants
As mentioned above, some of the earliest well defined
pharmacogenetic syndromes involve pharmacodynamic
mechanisms. The risk of malignant hyperthermia on
exposure to inhaled anaesthetics or succinylcholine is
mediated by variants in RYR1 or CACNA1S.40
Variants
reducing G6PD function caused a high incidence of
haemolytic anaemia in African-American soldiers exposed
to antimalarials during World War 2 and increase the
risk for haemolytic anaemia and methaemoglobinaemia
with rasburicase, a recombinant urate oxidase used to
treat hyperuricemia.41
Variants in IFNL3 (also known as
IL28B) predict response to pegylated interferon alpha
and ribavirin in hepatitis C although the introduction
of newer therapeutics has reduced the impetus for
genotyping.42
ADRs described to this point are related to exaggerated
drugeffect,sometimesduetohighplasmaconcentrations,
such as bleeding with anticoagulants or hypotension with
antihypertensives, and these have been termed type A
ADRs. Type B ADRs are those unrelated to the drug’s
known and intended pharmacological effects and are
often considered non-dose-dependent. Type B reactions
include serious immunologically mediated ADRs such
as the Stevens-Johnson syndrome and toxic epidermal
necrolysis (SJS/TEN). Candidate gene and GWAS ap
proaches that use very small case numbers, often less
than 100, and large numbers of drug-exposed controls,
have implicated specific HLA variants in SJS/TEN. These
studies also highlight the importance of ancestry in drug
response. For example, HLA-B*15:02 confers risk of
carbamazepine-related SJS/TEN in southeast Asia where
the allele is relatively common.43
In European ancestry
populations, however, this allele is rare, and a different
HLA risk allele (HLA-A*31:01) has been implicated.44
In
these cases, the HLA variant is judged necessary, but not
sufficient to induce the immunological response.45
In
fact, a very strong association exists between flucloxacillin-
related hepatotoxicity and HLA-B*57:01,46
but it has been
estimated that only one case will develop for every
13
000 patients with the HLA-B*57:01-positive genotype
who have been exposed to the drug.45
For other drugs,
the number needed to test is smaller (eg, in the case of
abacavir,47
the number needed to test in patients with
HLA-B*57:01 is 13). Variable susceptibility to type B
reactions also depends on plasma drug concentration.
For example, HLA variants associate with ADRs caused
by the antiseizure medication phenytoin, a CYP2C9
substrate, and several studies have reported that risk of
ADRs is increased in patients who also carry CYP2C9
loss-of-function alleles.48,49
Implementing pharmacogenomics
Clinical trial data
Because preclinical and clinical mechanistic studies
support the role of genetic variation as a contributor
to variable drug responses, retrospective analyses and
prospective trials have been mounted to test the
hypothesis that pharmacogenomically guided therapy
will improve clinical drug outcomes.
After candidate gene studies identified HLA-B*57:01 as
a strong risk factor for abacavir-related SJS/TEN,50
a
randomised controlled trial (RCT) was done in 1956
patients to compare conventional antiretroviral regimens,
including abacavir, to a pharmacogenomically guided

Series
strategy in which abacavir was dropped from treatment if
the HLA-B risk allele was present.47
A rash, thought to be
related to abacavir, developed in 7·8% of controls and
3·4% of patients in the pharmacogenomically guided
group. However, subsequent protocol-mandated skin
testing confirmed that the rash was related to abacavir in
2·7% of controls and in none of the patients in the pharma
cogenomically guided group. This unambiguous outcome
resulted in the US Food and Drug Administration (FDA)
label requiring preprescription testing for HLA-B*57:01 in
all individuals starting abacavir treatment and not using
the drug in genotype-positive patients.
An RCT compared standard therapy to pharmaco
genomically guided dosing in 783 patients starting
treatment with azathioprine or 6-mercaptopurine for
inflammatory bowel disease.51
TPMT intermediate
metabolisers (defined in the panel) received 50% of the
standard dose while poor metabolisers received 0–10% of
the standard dose. Overall, serious ADRs or disease
progression did not differ in the genotype-guided versus
standard therapy groups. However, among the 78 patients
with TPMT loss-of-function variants (77 intermediate
metabolisers and one poor metaboliser), a benefit of
pharmacogenomically guided therapy was clear: the
incidence of serious haematological ADRs was 22·9% in
thecontrolgroupversus2·6%inthepharmacogenomically
guided group (relative risk 0·11, 95% CI 0·01–0·85).
These results highlight the fact that any benefit of
pharmacogenomic testing will be confined to the subset
in whom the target genetic variants are present, and that
the apparent benefits will be diluted if testing is evaluated
in the entire population comprising mostly low-risk
patients. As discussed further in this Series paper, most
patients harbour one or more functionally important
variants in key pharmacogenes, suggesting that pre-
emptive testing of a panel of multiple pharmacogenes
should be a strategy to be considered for pharmacogenetic
implementation.
Retrospective analyses of the effect of common genetic
variants on outcomes after clopidogrel was initiated for
acute coronary syndrome have shown a consistent effect
of loss of function genotypes.5,52,53
Investigators in the
Implementing Genomics in Practice (IGNITE) network
summarised outcomes of genotyping to direct the choice
of antiplatelet therapies between clopidogrel and alternate
therapies in patients with CYP2C19 loss-of-function
alleles. Among 1815 patients at seven institutions, those
with loss-of-function alleles (31·5%) had more cardio
vascular events if treated with clopidogrel compared
with treatment with alternate drugs (23·4/100 patient-
years vs 8·7/100 patient-years, hazard ratio 2·26, 95% CI
1·18 to 4·32; p=0·013).54
One small prospective RCT
reported a large decrease in late coronary events with a
pharmacogenomically driven strategy for clopidogrel.55
Nevertheless, to date, cardiovascular professional soci
eties have not recommended genetic testing to guide
clopido
grel therapy, despite the fact that some have
argued the evidence is stronger than for other recom
mended tests.56
Multiple large RCTs have evaluated the effect of a
pharmacogenomically driven strategy including intensive
INR monitoring versus a conventional clinical approach
for warfarin. The first three large trials57–59
used a primary
endpoint of time in therapeutic INR range or time
required to achieve stable anticoagulation. Two studies
used a clinical algorithm as the control,57,58
and one used a
clinically conventional fixed-dose regimen.59
The fixed-
dose study showed a significant improvement in the
primary outcome, whereas no difference in outcome
was reported in the other two studies. The largest of
these trials, the US-based Clarification of Optimal Anti
coagulation Through Genetics (COAG), included
27% African-American patients and integrated CYP2C9
variants that are much more common in European
ancestry individuals, while other CYP2C9 variants that
have a role in patients of African origin were not assayed.60
As a result, the null result in COAG has been speculated
to reflect, in part, a lack of considering ancestry-specific
genetics.61
Several other RCTs have reported that pharmaco
genomically guided warfarin therapy improves outcome.
The Genetic Informatics Trial (known as GIFT)62
randomly assigned 1650 patients following hip or knee
replacement to a warfarin dose strategy guided clinically
or by genotype and focused on the primary outcome of
warfarin-related ADRs (major bleeding, INR
>
4, venous
thromboembolism, and death) rather than time in
therapeutic range. The primary endpoint occurred in
10·8% of patients in the genotype-guided group versus
14·7% in the clinically guided group (p=0·02). An RCT in
southeast Asia showed that a pharmacogenomically
guided strategy resulted in fewer dose titrations in the
first 2 weeks of therapy (the primary endpoint for the
trial).63
In all these warfarin trials, the frequency of serious
bleeding was low, and none of the trials were powered
to detect an effect of genotype on bleeding itself.
Retrospective analyses of large numbers of patients
presenting with warfarin-related bleeding, ascertained
through administrative databases or electronic health
records (EHRs), have reported a significant effect
of CYP4F2 V433M (odds ratio [OR] 0·62, 95% CI
0·43–0·91)64
and of CYP2C9*3 (adjusted OR 2·05, 95% CI
1·04–4·04).65
A smaller study of African-Americans with
bleeding attributed to warfarin at INR values of less than
4 identified variants thought to regulate expression of
EPHA7, a gene expressed in the vascular endothelium.66
The feasibility of a pharmacogenetically driven strategy
with dose adjustment based on four DPYD variants was
evaluated in 1103 patients receiving fluoropyrimidines.
There were 85 variant carriers, and although they had a
higher incidence of serious toxicity compared with
non-carriers, the rates were lower than those seen in
historical controls.24

Series
These trials have identified many major issues (table 2).
A genetic testing strategy for an individual drug can
only show benefit in patients with the variant genotype.
In the case of drug metabolising enzymes and drug
transporters, the pharmacogenomic effect size is much
larger in homo
zygotes than in heterozygotes. Although
trials can be mounted with surrogate endpoints, such as
time in therapeutic range, acceptance by the clinical
practice community, and thus the payer community, is
more likely to occur if data are available on a hard
outcome such as death. However, the study of these
clinical endpoints might require very large studies even
if only high-risk populations are included. These issues
contribute to slow uptake of genetic testing for warfarin
and clopidogrel, as does increasing availability of
alternate therapies, which appear to be at least as effec
tive without known major pharmacogenomic issues
identified to date. By contrast, uptake is more likely
when alternate drugs are not available or when ADRs
are serious and clearly related to genetic variants,
particularly if a regulatory agency or professional society
recommends testing, as in the case of abacavir.
Current status
Experiments that implement pharmacogenomics have
used a point-of-care strategy or pre-emptive strategy. The
Example Perceived obstacle Potential solutions
Pharmacogenes
Majority of individuals in most
populations are wild type
Less than 1% of individuals areTPMT poor
metabolisers67
Very large numbers needed to test for
successful prospective trials and for clinical
benefit
Prespecify plan to analyse subset with variant;
and conduct trials across multiple drugs and genes, which
inform panel-based testing
Rare variants with uncertain effect 46 of 64 haplotypes for CYP2C9 have
unknown function68
Insufficient data to ascertain phenotype with
absolute certainty
Assay only variants with known function; include
uncertainty on clinical reports; and functional studies
Spectrum of effects due to variants
within one gene
Distinct variants in CYP2C19 confer complete
loss of function, partial loss of function,
or gain of function
Need to express genetic effect as
quasi-continuous trait
Use activity scores to annotate variant effect
Complexity of gene assays Different assay technologies required for
CYP2C19, CYP2D6, and HLA
Lack of comprehensive local infrastructure for
multiple laboratory developed tests
Development of off-the-shelf assays for pharmacogenes;
and reliance on send-out laboratories for some or all
pharmacogenomic testing
Drug effects
Hard endpoints are rare No deaths recorded in the 1650 patients
randomly assigned to treatment with
warfarin in the GIFT trial62
Robust methods to prove impact of
genotype-guided therapy on hard endpoints
not well developed
Use surrogate, but clinically relevant, endpoints such as
major bleeding, length of hospitalisation, symptom
control, or health-care cost; and do large retrospective
analyses of hard endpoints using EHR-linked biobank data
Efficacy endpoints poorly defined
outside of clinical trials
Serial assessment of depression symptoms
inconsistently documented in EHR data
Cannot do retrospective analyses on efficacy Prospective data collection with oversampling of
participants with pharmacogenetic variants
Health-care institutions and local health information technology
Results for each gene require
interpretation to discrete clinical
guidance
Clinical decision support for warfarin provides
dosing calculation, not genetic test results
Lack of technological infrastructure for
interpretation from gene test results to
functional effect to dosing guidance
Widespread sharing of technical solutions and clinical
decision support across institutions
Functional predictions and clinical
guidance evolve with new evidence
New evidence for the role of NUDT15 variants
in thiopurine toxicity23
Need to continually assess evidence, which is
consistently expanding to include more drugs
and more genes
Continued support for development of guidelines to
guide appropriate testing
Provider resistance to receiving or
using pharmacogenomic
information
No agreement among health-care providers
about who should take responsibility for
results69
Limited ordering of pharmacogenomic testing
or lack of use of pharmacogenomic guidance
Identification and recruitmentof clinical champions for
specificdrug–gene interactions; increased provider
education; and interruptive prescriber alerts makingthe
pharmacogenomic-informed choicesthedefault
Evolving EHR systems EHR system changes or upgrades might cause
loss of reporting or decision support
functionality
Large ongoing costs of system maintenance Commitment from EHR vendors for continual support of
pharmacogenomic implementation; and computable
guidelines for pharmacogenomics
Health-care systems
Patient movement across EHR
systems
A patient’s pharmacogenomic results do not
follow them when they receive care in
another system
Loss of potential benefit of test or potential
for repeat testing
Provision of pharmacogenetic results to patients; and
portability of results for transfer to other EHR systems
Diversity of pharmacogenomic
assays
Depending on TPMT genotype interpretation,
a patient might be labelled as poor or
intermediate metaboliser
Lack of consistency of results across
CLIA-approved tests
Standardisation of minimal test requirements; and
standardisation of interpretation of variant effects
Reimbursement challenges Pharmacogenomic testing is variably
reimbursed across clinical scenarios, states,
genes–drugs, and payers
Pharmacogenomic testing is not cost-effective Increase data available on cost benefit and improve and
standardise analyses to promote reimbursement; and
develop comprehensive cost-effectiveness model as
opposed to models for individual drug–gene pairs
TPMT=thiopurine s-methyltransferase. GIFT=Genetic InformaticsTrial. EHR=electronic health records. CLIA=Clinical Laboratory Improvement Amendments.
Table 2: Issues, obstacles, and potential solutions in pharmacogenomic implementation

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