ISSN 1916-6958

2010; Volume 1 (Number 1):
Pages 14-20

REVIEW ARTICLE

Beyond single nucleotide polymorphisms

Roberto CANAPARO* & Loredana SERPE

Department of Anatomy, Pharmacology and Forensic
Medicine, Division of Pharmacology and Experimental Therapeutics, University of Torino,
Torino, Italy

*Corresponding author:
[email-masked]

ABSTRACT

Similar medications have been known to cause
considerable heterogeneity in efficacy and toxicity across human populations.
Therefore, individualized, or personalized, therapy has been highlighted as a
declared goal of modern medicine. In this paper, we briefly describe the main
strategies for dose individualization and then focus our attention on Single
Nucleotide Polymorphisms (SNPs), the main source of human genetic and
phenotypic variation. This genetic variation was long recognized as the
principal genetic contribution to the variability of drug action, but the
advent of more powerful molecular technologies has uncovered other abundant DNA
variations and changed this perception. It should also be taken in
consideration that most drug effects are determined by the interplay of several
genes (the genomic approach), rather than candidate gene approaches. Although
pharmacogenetics and pharmacogenomics mainly focus on human genetic variations
linked to SNPs, we believe that this approach is only a starting point, from
which it will be necessary to proceed to a more complex stage of research to
better individualize drug therapy.

Key words

Pharmacogenetics; Pharmacogenomics;
Pharmacokinetics; Single nucleotide polymorphism

RÉSUMÉ

Il est bien connu
qu’un même médicament peut montrer une hétérogénéité dans son efficacité et sa
toxicité au sein de l’espèce humaine. Pour cette raison la médecine moderne met
de plus en plus l’accent sur une médecine individualisée ou personnalisée. Cet
article décrit brièvement les stratégies principales pour une posologie
individualisée et focalise ensuite l’attention sur les SNPs (polymorphismes
d’une seule paire de base du génome), la source principale de variation
génétique et phénotypique humaine. Cette variation génétique a été longtemps
reconnue comme la contribution génétique principale à la variabilité de
l’action des médicaments. L’arrivée de technologies moléculaires plus
performantes a découvert de nombreuses autres variations de l’ADN et a ainsi
changé cette perception. Il faut en effet prendre en considération que la
plupart des effets des médicaments sont déterminés par l’interaction de
plusieurs gènes (l’approche génomique) plutôt que d’un gène unique. Quoique la
pharmacogénétique et la pharmacogénomique se focalisent actuellement surtout
sur les variations génétiques humaines en relation avec les SNPs, nous croyons
que cette approche n’est qu’un point de départ à partir duquel il sera
nécessaire d’instaurer des étapes plus complexes de recherche pour aboutir à
une médecine mieux individualisée.

Mots clés:

Pharmacogénétique;
Pharmacogénomique; Pharmacocinétique; SNP

RESUMEN

Medicamentos
similares puede producir una respuesta heterogénea en cuanto a su eficacia y
toxicidad. Por lo que una terapéutica individualizada, o personalizada, es considerada
como un objetivo específico de la medicina moderna. En este artículo,
describimos brevemente las estrategias principales para la individualización de
la dosis y posteriormente enfocamos la atención sobre el polimorfismo de un
solo nucleótido (PSN), la principal fuente de variación genética y fenotípica
humana. Esta variación genética fue extensamente reconocida como la principal
contribución genética a la variabilidad de los efectos farmacológicos. Sin
embargo, el desarrollo de técnicas moleculares más avanzadas ha descubierto
otras variaciones de ADN abundantes y ha cambiado esta perspectiva. También
debe de considerarse que la mayoría de los efectos farmacológicos están
determinados por la interacción de varios genes por lo que también el trabajo
hace un análisis no solo bajo la óptica de algunos genes específicos sino de de
una perspectiva genómica. Resumiendo, aunque la farmacogenética y la farmacogenómica
enfocan su atención en las variaciones genéticas humanas, principalmente
ligadas al PSN, nosotros consideramos que esta perspectiva es sólo el principio
desde el cual tendremos necesariamente que movernos a un nivel más complejo de
investigación para individualizar la farmacoterapia.

Palabras clave

Farmacogenética;
Farmacogenómica; Farmacocinética; Polimorfismo de un solo nucleótido

INTRODUCTION

The rule ‘the right drug at the right dose
at the appropriate time in the right patient’ may appear to be a very ambitious
goal in drug therapy, but an overview of scientific pharmacological literature over
the last 30 years indicates it as one of the main targets in third-millennium
medicine. There are many reasons for the move from the ‘one drug fits all’
approach to personalized medicine: 1) the enormous increase, during the 20th
century, in the range of therapies against all major diseases, 2) the
increasing life expectancy, 3) drug therapy sometimes fails to be curative, 4)
adverse drug reactions are the fifth leading cause of death in the United
States [1] [2], 5) powerful new technologies have produced advances in
biomedical research.

DOSE INDIVIDUALIZATION

To date, the main strategy for dose
individualization is to determine dosage from the drug’s pharmacokinetic
properties; the classic example of this approach is carboplatin, an analogue of
cisplatin, which is used to treat lung and ovarian cancer [3] [4]. Alternatively, initial treatment doses can be used
to establish the individual’s pharmacokinetic (PK) response to the drug, with
subsequent doses being based on this information; this strategy has been used
for oral busulfan, an alkylating agent that is used to treat leukemia, which
has linear kinetics but high interindividual variability [5] [6] [7] [8] [9]. Another PK-based method for dose individualization
is the population pharmacokinetic model. This approach studies the variability
of plasma drug concentrations among individuals who receive standard regimens
determined from PK data relating to the target patient population. Population
pharmacokinetic models aim to account for observed interindividual variation in
terms of patient variables called covariates; these include all sources of
variability. Population modeling enables the relative importance of covariates
to be quantified; Bayesian estimation, which evaluates an individual’s data
relative to the population pharmacokinetic model, can then be used to estimate
patient-specific pharmacokinetic parameters from which to calculate the optimal
dose for an individual [10] [11] [12] [13] [14]. Epirubicin, an anthracycline used in breast cancer
therapy, and digoxin, used in the treatment of various heart conditions,
exemplify how population modeling can lead to dose individualization [13] [15]. However, each of these strategies suffers from some
disadvantages, such as subtherapeutic or supratherapeutic dosing during the
initial stages and difficulty of adaptation to clinical practice. It has
therefore been suggested, following the complete mapping and understanding of
all human genes through the Human Genome Project, that pharmacogenetics and
pharmacogenomics might have the potential to overcome these drawbacks and to
facilitate reaching the goal of optimizing drug therapy [16] [17] [18] [19] [20] [21] [22].

PHARMACOGENETICS AND PHARMACOGENOMICS

The British physician Archibald Garrod was
probably the first to realize that certain individuals inherited a
predisposition to alcaptonuria or other conditions [23]. In particular, he observed that parental consanguinity
was more common than usual among parents of children with alcaptonuria.
However, it was probably William Bateson [24], a biologist who was ahead of his time, who interpreted
Garrod’s reports as recessive inheritance when he popularized Mendelian
genetics in Britain.
Bateson discovered genetic linkage and introduced the term ‘genetics’ at some
time between 1902 and 1913. With particular foresight, Garrod went on to
develop the concept known as the ‘Chemical Individuality in Man’ [24]. He proposed that drugs undergo biotransformation by
specific pathways, similar to endogenous substrates. As occurs with inborn
errors of metabolism, defects in such pathways could alter drug concentrations
and therefore their effects [24].

The concept of familial clustering of
unusual xenobiotic responses was reinforced during the 1940s with the
observation of a high incidence of hemolysis, on exposure to antimalarial
drugs, among individuals with glucose-6-phosphate dehydrogenase deficiency [25]. In the 1950s, Evans et al. identified N-acetylation
as a major route of isoniazid elimination [26]. Although individuals varied substantially in terms
of the extent to which a single dose of the drug was acetylated, variability
between monozygotic twins was found to be small compared with that between
dizygotic twins. This observation laid the groundwork for later studies that
have defined the clinical consequences and genetic basis underlying the fast
and slow acetylator phenotypes. More generally, the past half century has seen
developments towards understanding the molecular basis of drug disposition and
action, and of the mechanisms that determine the observed variability in drug
action. The concept of a familial component in drug action thus initiated the
field of ‘pharmacogenetics’ even before the discovery of DNA as the repository
of genetic information. An increased understanding of the molecular, cellular,
and genetic determinants of drug action elicited an appreciation that variants
in many genes might contribute to variability in drug action. The concept of
using whole-genome information to predict drug action is one definition of the
more recent term, ‘pharmacogenomics’ [27] [28] [29].

SNP

Whether we are discussing pharmacogenetics -
the study of the relationship between individual gene variants and variable
drug effects [30] - or pharmacogenomics - the study of the relationship
between variants in a large collection of genes, up to the whole genome, and
variable drug effects [30] - we are chiefly talking about Single Nucleotide
Polymorphisms (SNPs). An SNP is a change in one nucleotide (base pair) in a DNA
sequence. SNPs can be in coding regions (where they may be either synonymous or
non-synonymous) or, more commonly, in non-coding regions; they frequently vary
with ethnicity [30]. It has been estimated that there are at least 10
million SNPs within the human population [31], averaging one every 300 nucleotides, of the
approximately 3 billion nucleotide base pairs that constitute the genome of an
individual. It is precisely in these heritable variations among individuals on which
the principles of pharmacogenetics and pharmacogenomics are based.

There are many cases in which SNPs have been
correlated with significant changes in drug effects [17] [32]. One of the best examples of SNPs relating to the
outcome of therapy is the polymorphism of the gene thiopourine S-methyl
transferase (TPMT). TPMT is a cytosolic drug-metabolizing enzyme that catalyzes
the S-methylation of 6-MP and azathioprine. In their original study, Weinshilboum
et al. demonstrated a very clear tri-modal frequency of TPMT activity in red
blood cells from 298 unrelated control adults [33]. One in 300 subjects lacked TPMT activity and 11% had
intermediate levels. Family studies showed that the frequency distribution was
due to inheritance. While phenotypic studies have shown a clear tri-modal
distribution, the genetic basis of phenotypic variation has proved more
complex. Seventeen variant TPMT alleles have been identified to date, although
3 variant alleles account for the majority (>95%) of persons with
intermediate (1 variant allele) or low (2 variant alleles) TPMT activity [34] [35]. Subsequent clinical studies have demonstrated very
clearly that TPMT polymorphism can predict toxicity of 6-MP and consequences of
therapy. Children with acute lymphocytic leukemia (ALL) with intermediate or no
TPMT activity are at higher risk of myelosuppression when prescribed standard
doses of 6-MP [36]. Moreover, a number of studies have shown that TPMT
phenotype or genotype influences the effectiveness of therapy, with low TPMT
activity being associated with higher levels of cytotoxic 6-thioguanine
nucleotides (6-TGN) and reduced relapse [37]. Another example of SNPs influencing therapeutic
efficacy involves polymorphism of genes belonging to the superfamily of
cytochrome P450 enzymes (CYP) [38]. For example, patients carrying some of the 78
variants of CYP2D6 currently identified (http://www.imm.ki.se/cypalleles)
have a greater risk of adverse effects from metoprol, venlafaxine or tricyclic
antidepressants [39] [40] [41].

CYP2C19 is important in the metabolism of
proton-pump inhibitors (omeprazole, lansoprazole, rabeprazole, and
pantoprazole), fluoxetine, sertaline and nelfinavir. Several inactive genetic
variants exist, although two (CYP2C19*2 and CYP2C19*3) account for more than 95
percent of cases involving poor metabolism of these drugs [42]. Marked differences in the plasma levels of
protein-pump inhibitors occur between genotypes and phenotypes and are
reflected in drug-induced changes in gastric pH [43].  CYP2C9 is involved
in the hydroxylation of the S-form of the anti-epileptic agent phenytoin and
the anticoagulant warfarin. Many CYP2C9 variant alleles have now been reported
(http://www.imm.ki.se/cypalleles).
Of these, decreased activity has been confirmed in cases with CYP2C9*3, by
means of an expression system using COS cells and yeast, and an in vivo test on healthy volunteers and
patients whose genetic polymorphism was known [44] [45]. For example, oral clearance of (S)-warfarin
decreased to below half in subjects with heterozygous polymorphism for CYP2C9*3
(CYP2C9*1/*3) and to below 10% in patients who were homozygous for CYP2C9*3 [46].

BEYOND SNPs

Several pharmacogenetic research studies
published in recent decades have demonstrated gene-drug interactions in cases
where a SNP has been identified in one or more genes with functional
consequences [47]. Nevertheless, many other studies show a poor
correlation between SNPs in candidate genes and phenotypes. For instance,
Irinotecan is a prodrug that has been widely used to treat advanced cancers and
is activated by human carboxylesterase 2. Although the carboxylesterase 2 gene
exhibits several instances of polymorphism, and although an intronic SNP has
been found to be associated with reduced carboxylesterse mRNA expression in
colorectal tumors, none of the variations in this gene have been found to be
associated with protein activity [48] [49]. Furthermore, CYP3A4 is the human enzyme known to be
involved in the metabolism of numerous medications. Thus far, no completely
inactivating mutations have been discovered in the human CYP3A4 gene, although
a common polymorphism in the CYP3A4 promoter has been described [50] [51] [52].

This method is beginning to change as
haplotype studies and other approaches appear in the literature [30] [53]. An important manuscript in this context evaluated
whether the response to inhaled b2-agonist
therapy for asthma was best predicted by individual SNPs or by gene haplotype
in the b2-adrenoceptor gene (ADRB2) [54]. None of the 13 SNPs were significant predictors of
response to b2-agonist therapy. Of the 8,192
haplotypes theoretically possible for (ADRB2), only 5 were commonly observed.
Importantly, haplotype analyses did define a patient group with a significantly
superior response to b2-agonist therapy. A study correlating
thiopurine-related adverse drug reactions with TPMT gene polymorphism, one of
the best pharmacogenetic examples, noted that 78% of adverse drug reactions
were not associated with the TPMT genotype. Researchers are thus moving from
SNPs to other human genetic variations, such as small insertions or deletions
of repetitive DNA sequences in the promoter region of the TPMT gene, in an
attempt to elucidate this association [55] [56].

The idea to move onwards from SNPs to other
human genetic variations arises from the advent of genome-scanning technologies
that have uncovered an unexpectedly-large number of structural variations in
the human genome. These consist of microscopic and submicroscopic variants,
including deletions, duplications, insertions, inversions and translocations,
which involve segments of DNA that are larger than 1 kb [57]. For example, gene deletions and duplications have
been discovered in debrisoquin hydroxylase (CYP2D6), probably the
best-characterized genetic polymorphism among the cytochrome P450 enzymes, and
concordance between genotype and phenotype has been well established for many
drug substrates [58]. However, this monogenic approach, in which a single
DNA variant site is associated with a specific alteration, has been criticized
in that it fails to consider potential polygenic contributions. For instance,
the field of systems biology reflects gene–gene interactions resulting from a
particular stimulus that affects a complex circuitry of pathways, ending in a
response by the cell or organism [59]. Gene–gene sensing, or gene–gene warfare within the
genome, has been called molecular drive or meiotic drive [60]. Gene conversion can lead to one gene repairing, or
altering the expression of, its neighbor gene [47]. Gene silencing can occur through several different
mechanisms, including DNA hypermethylation and RNA interference [61].

Genomic imprinting also results from DNA
methylation [47]. Nutrition and dietary supplementation have been
shown to affect epigenetic gene regulation in man [62]. Extensive transmission distortion can lead to
unequal genetic sharing among relatives [47]. Several studies have suggested that more than 70% of
all human multi-exon genes are alternatively spliced [47]. Exonic splicing enhancers can be disabled by a
synonymous single-nucleotide polymorphism, regarded by many as unimportant
compared to a non-synonymous single-nucleotide polymorphism [47]. Stochastic events (random noise during transcription
and other cellular processes) can also markedly affect gene expression [47]. Another area of active inquiry is the
transcriptional regulation of normal proteins, which can be highly variable
because of allelic variants in regions of DNA that regulate expression [63] [64]. Variation in the function or expression of genes
encoding various factors, such as AhR (arylhydrocarbon receptor), PPAR
(peroxisome proliferator activated receptor), PXR (pregnane X receptor) and CAR
(constitutive androstane receptor), that control the transcription of genes
encoding drug-metobolizing enzymes and transporters, could also contribute to
variable drug action [65] [66] [67] [68] [69]. Finally, transcriptional mutagenesis results in
mutated mRNA and, therefore, in mutated protein, although the mutation does not
exist in the DNA [47].

CONCLUSIONS

Although pharmacogenetics and pharmacogenomics
focus attention on human genetic variation mainly linked to SNPs, we have shown
in outline that this approach is only a starting point, from which it will be
necessary to proceed to a more complex stage of research. We believe, however, that
SNPs comprise a useful step in individualizing therapy, although we are less
optimistic than some [70]. The chief role of SNPs, in our view, is as one
covariate in population pharmacokinetic models [71] [72], with the goal of preventing subtherapeutic or
supratherapeutic dosage (during the initial stages) in particular therapeutic
groups [73] [74]. They may also help to avoid high-risk subjects
developing severe adverse drug reactions [35]. In summary, it is clear that no single approach is
likely to identify, in all individuals, the contribution made by all genes and
gene products responsible for a particular drug response.

ACKNOWLEDGEMENTS

The authors thank Dr Gian Paolo Zara for
valuable discussion and helpful suggestions during preparation of this review.

CONFLICT OF INTERESTS/DISCLAIMERS

R C is member of the Editorial Board of the
journal.

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