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Pharmacogenomics and
Personalized Medicine
Hyun Kim, Shannon F. Manzi, Laura Chadwick, and Jonathan Picker
CORE PRINCIPLES
CHAPTER CASES
Pharmacogenomics is an important
component of the broader concept of
personalized medicine, which
incorporates a variety of factors, both
genetic and nongenetic, to guide
targeted and individualized therapeutic
decisions.
Case 4-1 (Question 1),
Figure 4-1, Tables 4-1,
4-2
Pharmacogenomic effects can be both
pharmacokinetic and pharmacodynamic
in nature. Pharmacokinetic effects are
observed when variants affect the
absorption, distribution, metabolism, or
excretion of a drug. Pharmacodynamic
polymorphisms may result in variable
amounts of drug target enzymes or
Case 4-2 (Questions
1, 2)
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3
4
5
6
7
receptors, as well as possible changes
in the drug target shape. These
variations may render therapy
ineffective or necessitate dose changes
in certain affected populations.
DNA polymorphisms affecting drug
metabolizing enzymes can result in gain
of function, loss of function, or have no
effect on function of the enzyme
produced. In some cases, significant
toxicity can result.
Case 4-3 (Question 1),
Figure 4-2, Table 4-3
Case 4-4 (Question 1),
Table 4-4
Drug transport proteins and binding
targets can also be affected by
pharmacogenomic variants.
Case 4-5 (Questions
1, 2), Table 4-5
Human leukocyte antigen (HLA) genes
are unique in that the presence of a
variant does not impact the metabolism
of a drug, but instead may indicate the
likelihood of the development of a lifethreatening reaction.
Case 4-6 (Questions
1–3), Table 4-6
Test interpretation is crucial to the
practical application of
pharmacogenomic data. In particular,
cytochrome P450 (CYP) 2D6 is a welldescribed CYP enzyme responsible for
~25% of all drug metabolism. However,
CYP2D6 is a complicated gene locus
subject to multiple variants, pseudogene
interference, and copy number variation,
making interpretation difficult.
Case 4-7 (Questions
1, 2), Table 4-7
Case 4-8 (Question 1)
Age-based development adds a level of
complexity when assessing
Case 4-9 (Question 1),
Figure 4-3
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pharmacogenomic markers in pediatric
patients. Many of the pharmacogenomic
dosing guidelines have not been
validated in infants and children.
Implementation of pharmacogenomics
into practice is increasing but continues
to face many challenges, including the
appropriate determination of when and
whom to test; storage, analysis, and
security of genetic data; and
considerations for using
pharmacogenomic data and
recommendations in practice.
Case 4-10 (Question
1)
Case 4-11 (Questions
1, 2)
INTRODUCTION
Pharmacogenomics is the study and application of gene expression
on drug pharmacokinetics and pharmacodynamics. This term is
often used interchangeably with “pharmacogenetics.” By strict
definition, pharmacogenetics is used in the context of a single gene’s
influence on a drug, whereas pharmacogenomics refers to the
broader study of the full genomic impact on drug behavior.1 Because
genetic variants are specific to the individual, the use of
pharmacogenomics in clinical practice has become a core
component of the personalized medicine and precision medicine
movements.
2,3
The study of pharmacogenomics is not new because there are
cases in the literature from the 1950s and 1960s describing the
influence of a person’s genetics on drug toxicity.
4,5
The first
recognition of individual differences in response to consumption of a
product was favism, a form of hemolytic anemia described by the
ancient Greek physicians before the third century BC.6 They
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recognized that in some people the consumption of fava beans had
potentially severe consequences. Whether this was the source for
Pythagoras’ famous abhorrence of the beans, however, remains
uncertain. More recently, with the advent of newer, cheaper, faster
DNA sequencing techniques, the study of pharmacogenomics has
exploded. We are now able to begin transitioning pharmacogenomic
knowledge from the research realm to the clinic, although not without
challenges.
A brief review of the basics of human genetics in the context of
pharmacogenomics is discussed here. Students are encouraged to
utilize the selected references at the end of the chapter for further
review. Although somatic tumor genetics and the study of mutations
found in cancer cells are becoming increasingly important when
selecting antineoplastic drugs, this chapter primarily focuses on
germline mutations in human DNA that affect drug absorption,
distribution, metabolism, and excretion.
Genes code for proteins, such as enzymes, structural components
of cells, hormones, antibodies, and transport molecules. In
pharmacogenomics, the gene and the enzyme often share the same
name. For example, the gene that codes for cytochrome P450
CYP3A4 is known as CYP3A4 and the gene that codes for
thiopurine methyltransferase (TPMT) is known as TPMT.
The human genome is made up of 3 billion nucleotide base pairs
arranged on 23 pairs of chromosomes. Nucleotides include adenine
(A), guanine (G), cytosine (C), and thymine (T), with variants in
nucleotide sequences contributing to each individual’s unique
physiologic characteristics, traits, and features, such as hair color,
eye color, height, risk of disease, and ability to process medication.
In most, but not all, cases, two copies of each gene are present:
one inherited from your mother and one from your father. Each copy
of a gene is referred to as an allele. If both the maternal and paternal
alleles are the same, then the individual is considered homozygous
for that gene. If the parental copies differ, then the patient is
considered to be heterozygous for that gene. Nucleotide changes
that differ from the most commonly observed sequence are referred
to as variants. Although the formal variant definition states that the
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observed change occurs in at least 1% of the population, the term is
often used in practice regardless of population frequency.
A change in a single base pair is termed a single-nucleotide
polymorphism, or SNP (pronounced “snip”) (Fig. 4-1). SNP locations
are mapped and named using a reference SNP cluster ID, or rsID,
discussed in more detail in Case 4-5. An SNP that adversely
changes the function of the protein encoded for by a gene is called a
pathogenic variant or, historically and colloquially, a mutation. Many
of the pharmacogenetic variants discussed in this chapter are SNPs.
SNPs are responsible for 90% of pharmacogenetic variability and
can result in gain of function with greater production of the
associated enzyme and higher than normal enzymatic activity, or
loss of function with reduced or no enzyme production and
decreased enzymatic activity. Other variant types include nucleotide
insertions or deletions, commonly referred to as indels. In many
cases, indels terminate protein production as a result of frameshift
changes that alter the translation of amino acids.
Figure 4-1 Example of a single-nucleotide polymorphism (SNP).
In classical Mendelian genetics, most inheritance of disorders
occurs in either a dominant or recessive manner. For dominant
disorders, a change in a single allele is sufficient to elicit an
undesired physiologic effect. These changes can be passed down
from one generation to the next or occur as new, or de novo,
mutations within an individual for the first time. With recessive
disorders, a person must inherit two defective copies of a gene for
there to be a functional consequence. Parents who are heterozygous
for a gene associated with a recessive disorder are usually
unaffected by the disorder and are termed carriers. When both
parents are carriers, one in four of their offspring is at risk for
inheriting the disorder even with no family history of the disease.
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Unlike the discrete pattern of dominant and recessive disorder
inheritance, pharmacogenes, or genes associated with drug action
and kinetics, tend to operate on more of a continuum. Variants within
pharmacogenes often result in a spectrum of effects, ranging from
mild to more pronounced, depending on the number of functional
alleles present. Pharmacogenetic variants are also typically “silent”
in the absence of relevant drug exposure, making family history a
somewhat less reliable tool.
The nucleotides, including any variants if present, make up alleles
that determine a person’s genotype for a given gene. The term
phenotype refers to the expression, or physical manifestation, of a
genotype. In some cases, a phenotype is visibly obvious, such as
skin color, eye color, or hair color. In other cases, it is measurable,
such as is the case for a person’s blood type or the amount of a
CYP450 metabolizing enzyme they generate. In the context of
pharmacogenomics and metabolizing enzymes, patients are often
classified as having a phenotype of ultrarapid metabolizers,
extensive metabolizers, intermediate metabolizers, or poor
metabolizers based on their genotype.7 There are several other
relevant phenotypes relating to pharmacogenomics that are
discussed in this chapter, particularly those that deal with drug
targets or pharmacodynamic responses.
The complexity of most drug metabolism pathways can make
applying phenotypes to clinical drug dosing decisions complex. It is
rare for a pathway to involve a single enzyme resulting in one
inactive metabolite that is immediately excreted by the body. Instead,
most drugs utilize multiple metabolizing enzyme pathways, rely on
several drug transporters, and have many metabolites of varying
activity. Each of these pathways may be subject to variable gene
expression, coupled with indirect genetic and environmental effects
on other characteristics such as disease, weight, nutrition, and age.
With the spectrum of factors to consider, using pharmacogenomic
interpretations in a clinical setting can be extremely complicated.
For common pharmacogenes, the representation of a person’s
genotype is often noted by a “*,” known as a star allele. For example,
a normal or “wild-type” allele status is often denoted as *1/*1.8 As
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other alleles are discovered, they are numbered sequentially as *2,
*3, and so on. Because discoveries are inevitably sometimes
reported simultaneously from different sources, there is occasionally
an overlap of star alleles and the variants represented. There are
several worldwide databases for reporting new pharmacogenomic
variants, including the Human Cytochrome P450 (CYP) Allele
Nomenclature Database, http://www.cypalleles.ki.se/, and the
Database of Genomic Variants, http://dgv.tcag.ca/dgv/app/home.
During drug development and postmarketing analyses, it often
becomes clear that some patients either have severe adverse drug
reactions (ADRs) or do not respond to the population-derived
standard dose. Adverse drug reactions (ADRs) are defined as
unintended outcomes occurring in the absence of medication error or
lack of proper adherence to the drug, and are costly.
9,10
The 2000
Institute of Medicine (IOM) “To Err Is Human” report cited over 2
million reported ADRs in the United States per year resulting in
~100,000 deaths and at a cost of $29 billion annually.11 It is
estimated that 87.7% of outer quadrant adults are taking at least one
prescription drug, 35.8% are taking more than five prescription
drugs, 37.9% use over-the-counter medications, and 63.7% use
dietary supplements.12 It is well known that ADRs often go unnoticed
and even more frequently unreported, making the actual numbers
likely far higher.
The clinical application of pharmacogenomics has allowed us to
not only explain some of these historical reactions but also helps
clinicians predict who may be at higher risk for developing an
adverse reaction if exposed to a drug or drug class.13 With this
understanding, clinical decisions can be made to lower a person’s
risk of adverse reactions. Given that >90% of individuals carry at
least one potential clinically significant pharmacogene genotype,
overall risk in the pharmacogenetic space is not insignificant.
14
Avoidance of ADRs has a measurable impact on a patient’s quality
of life, decreases overall health care costs, and lessens the time
burden on health care providers managing the adverse reactions.
However, acceptance of clinical pharmacogenomic testing is not
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universal and there remains the challenge of conclusively validating
the genetic variant association with the adverse reaction.
15
Guidelines for drug dosing and selection have been developed by
the Clinical Pharmacogenomics Implementation Consortium (CPIC,
pronounced “See-Pick”) and the Pharmacogenetics Working Groups
of the Royal Dutch Pharmacists Association (DPWG). Each
guideline is rated on the level of evidence available to support the
recommendation.16 Currently, there are 26 CPIC Level I Evidence
published guidelines available on www.pharmgkb.org, a website
supported by the National Institutes of Health (NIH) and hosted by
Stanford University.17 The site houses a wealth of information,
including pathway diagrams, annotated bibliographies, and look-up
tables. Importantly, the guidelines do not address who should be
tested but instead focus on what to do with the data if available.
PHARMACOKINETIC IMPLICATIONS
CASE 4-1
QUESTION 1: A.S. is a 2-year-old female diagnosed with active multidrug
resistant tuberculosis (MDR TB). The Centers for Disease Control and
Prevention (CDC) treatment protocol recommends isoniazid, rifampin,
ethambutol, and pyrazinamide for initial therapy. Her mother is concerned
because several family members in their home country of China had developed
serious “liver problems” when they took isoniazid, and she insists on the “gene
test” for A.S.
What genetic testing is A.S.’s mother referring to and what are the risks of
toxicity in relation to isoniazid therapy?
Isoniazid is part of the four-drug regimen used to treat both active
and latent tuberculosis (TB) infection because it is bactericidal
against Mycobacterium tuberculosis organisms.18 One of the most
commonly reported side effects, sometimes leading to premature
discontinuation of the drug, is drug-induced liver injury (DILI).
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The metabolism of isoniazid is complex, with the Nacetyltransferase-2 (NAT2) enzyme playing a key role in the
pathway.19 In the metabolism of isoniazid, NAT2 acetylates both the
parent drug and a hydrazine metabolite, converting the hydrazine
metabolite to acetyl hydrazine (AcHz).20 The AcHz metabolite is
believed to be the main cause of the liver injury observed with
isoniazid therapy.
The NAT2 enzyme is generated from a gene of the same name,
with several known polymorphisms leading to alleles associated with
either slow or rapid acetylation rates. Individuals homozygous for
slow alleles are considered “slow acetylators,” those homozygous for
rapid alleles “rapid acetylators,” and heterozygotes deemed
“intermediate acetylators” (Table 4-1). When NAT2 acetylation rates
are reduced, it allows for a buildup of AcHz; therefore, DILI has been
found to be highest in patients who are slow acetylators.21 In addition
to isoniazid, NAT2 is also a known acetylator of drugs and/or
metabolites in other drug pathways, although the clinical effects of
NAT2 genotype on these drugs are less studied: sulfonamides
(sulfamethoxazole, metabolites of sulfasalazine); and aromatic and
aliphatic amines (procainamide, dapsone, metabolite of clonazepam,
mescaline).
22
Table 4-1
NAT2 Genotypes and Phenotypes
NAT2 Allele Activity
Slow *5–7, *10, *12D, *14, *17, *19
Rapid *4 (wild type), *11, *12A–C, *13, *18
NAT2 Phenotype Summary
Genotype
Acetylator
Rate Clinical Manifestation With Isoniazid Therapy
Homozygous
slow
Slow Increased risk of adverse drug events
Heterozygous Intermediate No increased risk of adverse drug events or
treatment failure related to genotype
Homozygous Fast/rapid Possible increased risk of treatment failure
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rapid
The “gene test” mentioned by A.S.’s mother is a test for the NAT2
gene. A variety of pharmacogenomic tests are available to examine
SNPs in the NAT2 gene and assign a patient’s genotype, either from
a targeted assay or as part of a more extensive gene panel.
Preemptive NAT2 testing before isoniazid therapy is not currently the
standard of care; however, evidence suggests that this practice may
be beneficial in some populations with a high prevalence of DILI in
slow acetylators.
23–28
Asian cohorts have been found to have the
highest rates of DILI in the setting of a slow acetylator status (see
summary of studies in Table 4-2). Although there are no formal
dosing guidelines set for isoniazid therapy in the context of genotype
or acetylator status, a study completed by Azuma et al with 155
Japanese patients with TB proposed a modified, genotype-based
dosing regimen with successful outcomes that were both clinically
and statistically significant (results summarized in Table 4-3).
29
Table 4-2
Summary of NAT2 Genotypes and Hepatotoxicity Risk With
Isoniazid Studies
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