SNPs III - SNPs in Biomedicine
Concept: Nucleotide differences in genes can lead to different gene
products and gene expression and, ultimately, to altered phenotypes.
Humans express a wide variety of differences in responses to
environmental and internal stimuli, including the ability to resist
diseases and to respond to medical treatments. Differences in genotypes
can be assessed through the examination of genetic markers (SNPs, RFLPs,
chromosmal aberrations etc.).
SNP websites
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SNPs and Diseases
Examples for diseases that are caused by exchanges in single
nucleotides are:
- Beta-thalassemia
- Muscular dystrophy
- Sickle cell anemia
- Fibro muscular displasia
- Phenyl ketonuria
- Type-II diabetes
- A hyperlipidemous disorder associated with Apo E2
- Hypertension (one form)
- Migraine headaches
Pharmaceutical research laboratories are
highly interested in the identification of causative
SNPs, SNPs which are located within genes and their regulatory regions.
However, they are also searching for SNPs that may
not be located within genes, but that are genetically linked
with genes that lead to disease and/or drug
response phenotypes. Therefore the hunt for causative
SNPs is accompanied by the (equally intense) hunt for
indicative SNPs that are not directly involved in the
causation of a particular phenotype.
SNPS and Responses to Drugs
Not all people respond to drugs and medications in the same way,
in fact it is these differences that
require pharmaceutical companies to test their products on large
numbers of patients in order to develop a clear idea about the safety
and efficacy of new medications. With the advent of
lineage-independent genotyping through SNP-analysis, pharmaceutical
companies hope to be able to utilize this new method to develop
drugs in a more targeted fashion and to significantly narrow down the
number of test subjects by conducting genotyping instead.
Genomics will make three major contributions to drug therapy.
In the first place, new genes, which code for secreted proteins,
will continue to be identified. Second, genomic sciences are
about to identify the most suitable targets for drug intervention.
Although current drug therapy rests on approximately 500 such
targets, the emerging number is estimated to be in the range of
5,000 to 10,000 target molecules. Third, we are learning why
patients respond differently to drugs. The genetic patterns that
define these responses are being identified and used to target
drugs more effectively during their development. This approach
will also allow for individualized drug therapy.
Small molecules such as drugs, insecticides or herbicides usually
exert their effects by modifying biological targets. In the
past, many of these molecules were found empirically with little or
no knowledge of the mechanism of action involved and, in many
cases, the targets that are modified by these substances were identified
in retrospect. Genomics, however, will lend a new
dimension to drug development. The number of molecular targets that are
modified by the complete armamentarium of modern drugs
is not greater than 500. From early experiments and mathematical
approaches it is known that the number of genes that contribute
to multifactorial diseases might not be very high. In fact, the
numbers reported for different forms of diabetes and
hypertension are 5-10 genes per disease. If one assumes10 contributing
genes for 100 multifactorial diseases (including different
forms of cancer, asthma, diabetes, hypertension, atherosclerosis and osteoporosis),
one arrives at 1000 genes,
that dispose patients to the most important multigenetic conditions.
The existence of these genes does, of course, not detract from
the importance of environmental influences. These 1000
disease genes might not always guide the synthesis of proteins
that are good drug targets. However, it appears reasonable
to assume that each of these disease genes, or rather proteins that
are specified by the disease genes
connects with at least 5-10 proteins that represent feasible
levels for drug intervention. On the basis of these
calculations, one can assume that there are 5000-10,000 gene
products that can be used
as targets for drug interventions. Even if the lower number
would turn out to be the proper approximation, the
utilization of information stemming from the Human Genome
Project and from other related programs would allow for
a tenfold increase in the number of drug targets, compared
with the current situation. Such an expansion
of the operational possibilities of drug therapy would lead
to more specific therapies and into therapeutic
methods that are much closer to the molecular causes of
diseases than current therapies.
Drug-metabolizing enzymes found primarily in the liver
are a major determinant of therapeutic drug response.
For example, some people cannot activate codeine into its active
morphine form and, thus, lack efficient pain relief
when given codeine. Others
are high metabolizers for tri-cyclic antidepressants
and need reduced doses, to avoid severe side effects due to
increased levels of activated
compounds in their system.
A major group of enzymes involved in drug metabolism are
cytochrome P450 monooxygenases, enzymes that contain as an active
center a porphyrinring system (like hemoglobin). These
enzymes (CYP450) are predominantly involved
in electron transfer reactions and have derived their
name from the characteristic shift in light
absorption which they exhibit upon undergoing oxydation.
Cytochrome
P450 monooxygenases are found in almost all species from
bacteria to humans; they usually
act in pathways that enable organisms to degrade toxic
substances. In humans, as in most vertebrates,
cytochrome P450 monooxygenases are most prevalently
expressed in
liver tissue. As a consequence of their detoxifying
function cytochrome P450 monooxygenases
also play an important role in the metabolism of a
wide variety of drugs that we use to combat
disease.
According to their reaction to drugs, patients can
roughly be categorized as:
- Responders, who degrade a drug either after it has
done it's job, or who alter the drug from a
precursor into its active form
- Non-responders, who are unable to metabolize the
drug and either develop problems because a
drug does not get removed from their systems or because
the drug does not get altered into its active form
- Toxic responders, who metabolize a substance, thereby
creating a product which is toxic for them
While some evidence has been established for the
association of drug responses to beta-blockers,
antidepressants, anti-psychotics, and codeine with genetic variations
(e.g. about 5-8% of caucasians
are "poor metabolizers", due to a variety of different
SNPs in CYP2D6, leading to toxic and/or
non-responsiveness), significant controversy still
exists between different "camps". For example, some scientists
argue that polymorphism dependent upon race/ethnic origin for
CYP2D6 is now well-established.
However, others point out that, despite consistent reports of
ethnic differences in pharmacologic
response to antidepressants and neuroleptics, there is a paucity
of data on controlled clinical trials and studies determining
polymorphic characteristics of CYP2D6 enzymes in African-Americans.
There is little and conflicting information available on black
populations (Africans, bushmen, Australian Aborigines or African
Americans). The prevalence of poor metabolizers in Black populations
has been estimated from 0 to 19%, compared with consistent
reports of poor metabolizer status in Caucasians (5-10%) and
Asians (0-2%). Within the extensive metabolizer category,
Asians have higher metabolic ratios (that is, slower metabolism)
than Caucasian extensive metabolizers. A high frequency of
a mutant gene, CYP2D6*10 has been associated with the slower
metabolic rate in Asians. Previous research suggests that
slower metabolic rates compared with Caucasians may also be
characteristic of Black populations. Recent reports suggest
that a novel gene mutant in Black populations, CYP2D6*17,
associated with a slower metabolic rate, may occur in a high
frequency in these populations. Common clinical practice,
supported by controlled clinical studies in Asians, have led
to a reduction in dosage recommendations for many antidepressants
and neuroleptics for this ethnic group. It is imperative that
the determinants of bioavailability be established in
African-Americans as well as in other populations in
order to establish rational drug therapy guidelines. (Bradford
LD, Kirlin WG 1998.Int J Neuropsychopharmcol 1998 Dec;1(2):173-185)
However, regardless of this controversy about the applicability
of findings in individuals to whole population groups, previous research
confirms the notion that SNP genotyping may be valid tool to
accurately predict the response of a patient to a drug and, in some
cases, may even surpass traditional phenotping in a clinical trial
setting. (McElroy et al. 2000. CYP2D6 Genotyping as an alternative to
Phenotyping for Determination of Metabolic Status in a Clinical Trial
Setting. AAPS Pharmsci 2000; 2(4) article 33). SNP genotyping may
even be more powerful if it is applied to the examination of SNP
combinations in haplotyping. From the work by Dysdale et al. on
asthmatics (PNAS 2000 vo. 97, no.19:10483-10488):
"In summary, ... striking divergence in ethnic distribution was
found for several haplotypes.
Five haplotype pairs were common in ... [patients], ... In
contrast, no isolated SNP had
any predictive utility. ... These findings are a delineation
of phylogeny, and in vivo
and in vitro relevance, of haplotypic combinations of SNPs. The
results
indicate that the unique interactions of multiple SNPs
within a haplotype
ultimately affect biologic and therapeutic phenotype and that
individual
SNPs may have poor predictive power as pharmacogenetic loci"
(emphasis added).
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