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2005 Sep 1;207(2 Suppl):52-6.The human genome project and novel aspects of cytochrome P450 research.1.1Division of Molecular Toxicology, IMM, Karolinska Institutet, SE-171 77 Stockholm, Sweden. maging@ki.seAbstractCurrently, 57 active cytochrome P450 (CYP) genes and 58 pseudogenes are known to be present in the human genome. Among the genes discovered by initiatives in the human genome project are CYP2R1, CYP2W1, CYP2S1, CYP2U1 and CYP3A43, the latter apparently encoding a pseudoenzyme. The function, polymorphism and regulation of these genes are still to be discovered to a great extent. The polymorphism of drug metabolizing CYPs is extensive and influences the outcome of drug therapy causing lack of response or adverse drug reactions. The basis for the differences in the global distribution of the polymorphic variants is inactivating gene mutations and subsequent genetic drift. However, polymorphic alleles carrying multiple active gene copies also exist and are suggested in case of CYP2D6 to be caused by positive selection due to development of alkaloid resistance in North East Africa about 10,000-5000 BC. The knowledge about the CYP genes and their polymorphisms is of fundamental importance for effective drug therapy and for drug development as well as for understanding metabolic activation of carcinogens and other xenobiotics. Here, a short review of the current knowledge is given.PMID:
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Bench-to-bedside review: Fulfilling promises of the Human Genome Project
Jean-Daniel Chiche*, Alain Cariou and Jean-Paul Mira
Corresponding author:
Jean-Daniel
Associate Professor of Critical Care Medicine, Medical Intensive Care Unit and Cochin Institute of Molecular Genetics, H?pital Cochin, Université René Descartes, Paris, France
Associate Professor of Critical Care Medicine, Medical Intensive Care Unit, H?pital Cochin, Université René Descartes, Paris, France
Professor of Critical Care Medicine, Medical Intensive Care Unit and Cochin Institute of Molecular Genetics, H?pital Cochin, Université René Descartes, Paris, France
For all author emails, please .
Critical Care 2002, 6:212-215&
doi:10.1186/cc1491
The electronic version of this article is the complete one and can be found online at:
Published:20 March 2002
& 2002 BioMed Central Ltd
Since most common diseases have been shown to be influenced by inherited variations
in our genes, completion of the Human Genome Project and mapping of the human genome
single-nucleotide polymorphisms will have a tremendous impact on our approach to medicine.
New developments in genotyping techniques and bioinformatics, enabling detection of
single-nucleotide polymorphisms, already provide physicians and scientists with tools
that change our understanding of human biology. In the near future, studies will relate
genetic polymorphisms to features of critical illnesses, increased susceptibility
to common diseases, and altered response to therapy. Novel insights into the contribution
of genetic factors to critical illnesses and advances in pharmacogenomics will be
used to select the most effective therapeutic agent and the optimal dosage required
to elicit the expected drug response for a given individual. Implementation of genetic
criteria for patient selection and individual assessment of the risks and benefits
of treatment emerges as a major challenge to the pharmaceutical industry.
polymorphismIntroduction
In 1995, the genomic sequence of the bacteria Haemophilus influenzae was the first complete genomic sequence of a free-living organism to be published
[]. Since then, scientists have totally sequenced the genomes of more than one hundred
bacteria and completed genetic maps of large multicellular organisms [,,,]. The draft sequence of the human genome, recently published by the Human Genome
Project public consortium [] and by a private company [], represents a milestone in science. Today, the genetic blueprint for a human is
nearly completed and covers 96% of the genome. Embedded within our genomes are the
sequences of the approximately 30,000 genes that underlie human biology and medicine.
As we enter the post genome-sequencing era, we are already facing new challenges.
Successful translation of this structural knowledge into clinical benefits will depend
upon our ability to relate individual genes to specific diseases, to find the genetic
variations that influence an individual's risk of becoming ill, and to use genetic
information to tailor drug therapy. The purpose of this review is to put some of the
predictable consequences of the advances in genomics into clinical perspective.
Single-nucleotide polymorphisms: learning from our differences
Most common diseases and many drug responses have been shown to be influenced by inherited
differences in our genes. Thus, studying generic variance can improve our understanding
and treatment of disease. If a region of the human genome is sequenced from two randomly
chosen individuals, 99.3% of the examined DNA will be identical []. Much of the genetic variation between individuals lies in differences known as
single-nucleotide polymorphisms (SNPs); a single base is swapped for an alternate,
and both versions exist in the general population at frequencies greater than 1% []. As SNPs constitute the bulk of human genetic variation, they can be used to track
inheritance of genes in traditional family-based linkage studies. By epidemiological
association, SNPs can also be used to test susceptibilities to common diseases such
as heart disease, cancer, and diabetes.
Based on the promise of SNP research, an international subset of academic centers,
pharmaceutical companies, and a private foundation teamed up to create the SNP Consortium
in 1999. Whereas the initial goal of the consortium was to discover 300,000 SNPs that
would be freely available by April 2001, this has been exceeded, and the SNP, in collaboration
with the International Human Genome Sequencing Consortium, has created a catalogue
of more than 1.4 million SNPs []. This publicly available SNP map promises to advance our knowledge of the links
between genes and diseases.
Linking SNPs to phenotypes: disease markers or more?
One of the most difficult challenges faced by physicians and scientists is to establish
the link between gene variations and a disease. Of the 1.4 million SNPs currently
on the public map, only 60,000 are located in protein coding regions, called exons,
and relatively few of these transform amino acids []. The SNPs that change the amino acid sequence, and variants in gene regulatory regions
that control protein expression levels, are most likely to have a direct impact on
the protein product of a gene []. In cases where change of a single base in the genome sequence is sufficient to
cause disease, it has become possible to identify this change and improve our understanding
of the disease. For instance, sickle cell anemia is caused by the substitution of
a thymine for adenine at a single position in the gene that encodes the hemoglobin
Using ever more powerful approaches, literally hundreds of rare human diseases have
been related to genetic defects. However, the genetic contributions have proven more
difficult to establish for the common diseases that account for most morbidity and
mortality. In most cases, the influence of gene variants is subtle and the risk of
contracting the disease is also influenced by environmental factors []. Even if the causal mutations are common in the population, their effects will,
therefore, be difficult to discover. As the effects of any given SNP may be modest,
it will be necessary to study large numbers of patient samples to observe associations
in a reproducible fashion. Therefore, comprehensive studies will rely on the development
of fast and efficient tools to identify the small number of relevant SNPs out of the
millions in the human genome.
A phenomenon called linkage disequilibrium should permit the use of SNPs to track
associations to disease, without necessarily finding each functionally relevant SNP
beforehand. In a certain region, SNPs often track together in the population. In linkage
disequilibrium, such nearby SNPs can serve as proxies for each other in a disease
study. Hence, a subset of SNPs spaced throughout the genome might allow a comprehensive
test of common genetic variation across the entire genome. Although the specific number
of SNPs needed for linkage disequilibrium studies is unknown, the 1.4 million SNPs
in the public domain should offer a sufficient number to explore most regions of the
Impact of SNP research on clinical trial design
Besides all the consequences of genetics on our understanding of the pathophysiology
of critical illnesses, advances in SNP research also promise to change current practices
in clinical trials []. The SNP effort will undoubtedly serve as the bedrock of pharmacogenomics, the emerging
field of personalized medicine in which drugs and preventative strategies are specifically
tailored to suit an individual's genetic profile. One can speculate that many of the
recent advances in genetics will soon be brought into clinical trials with two main
directions. First, whereas treatment allocation has been based mainly on phenotype,
genetic characterization based on the genetic profile of an individual will help researchers
to identify suitable subjects to test a working hypothesis. This approach will also
facilitate interpretation of the results of clinical trials, and ultimately enable
clinicians to tailor treatment to patients with specific genotype. For instance, an
analysis based on the main studies of anti-tumor necrosis factor (TNF) strategies
in septic patients found an absolute decrease in mortality of 3.5%, suggesting that
these therapies could be beneficial in septic patients with uncontrolled TNF release
[]. Targeting patients whom carry the TNF2 allele and produce high levels of TNF-α
[], may reveal a beneficial effect of treatment with anti-TNF antibodies for septic
shock [,]. Second, as interindividual variability in the response to drugs remains a substantial
clinical problem, a major objective of pharmacogenomic research is to decrease adverse
responses to therapy through determination of adequate therapeutic targets and genetic
polymorphisms that alter drug specificity, metabolism, and toxicity []. Ultimately, genetic information will be used to select the most effective therapeutic
agent and the optimal regimen to elicit the expected drug response for a given individual.
Hence, the implementation of genetic criteria to select patient populations and of
individual assessment of the risks and benefits of treatment is emerging as a major
challenge for pharmaceutical companies.
Among the hurdles to overcome for successful integration of genetics in clinical practices,
it will be necessary to improve our ability to detect SNPs at a lower cost. Methods
to identify SNPs are based on modifications of the traditional DNA sequencing approach,
which can use a range of detection methods, such as radioactivity, fluorescence resonance
energy transfer, or fluorescence polarization. More recently, arrays on glass slides,
DNA chip-based microarrays, and mass spectrometry genotyping technologies have been
introduced to simultaneously determine the genotype of large numbers of SNPs [,,]. It is not yet clear which of these powerful methods will become most useful. At
a current average price of one dollar per genotype, SNP detection in large-scale genotyping
studies is still prohibitively expensive. Even at one cent per genotype, the cost
per patient in a typical association study testing 100,000 SNPs will possibly add
one million US dollars to the cost of a clinical trial []. Significant advances will be necessary to make extensive genotyping a standard
part of clinical trials.
Perspectives and limitations of SNP research
There are still many significant technical and analytical problems that must be solved
before the promise of SNPs can be fulfilled. Whereas the current SNP maps provide
us with invaluable tools to track statistically significant associations between SNPs
and disease or drug response, we do not fully understand the genetic architecture
of common traits underlying disease susceptibility and variability in drug response.
Interpretation of association studies is complicated by the number of genes, the number
of variants in each gene, and the frequency of a variant within a population. Location
of a variant SNP in the coding region, the regulatory region, or the noncoding region
of the genome also affects susceptibility to disease in a way that is still unclear.
In addition, the interaction of individual SNPs and the degree to which they track
together in linkage disequilibrium may be of the utmost importance in the determination
of a given phenotype.
Other issues must be addressed to unlock the full potential of SNPs. Given the large
number of SNPs and the low probability that any specific one causes disease, the sample
sizes in association studies need to be large enough to achieve adequate statistical
power. This also raises the problem of accurately phenotyping individuals, since the
same disease may manifest itself with different patterns in different patients. Finally,
new ethical issues will arise, which will have to be solved as SNP technology improves
and becomes widely used. Whereas current genetic tests typically track single-disease
genes, SNPs will provide tests that associate a genetic profile with individual predisposition
to a broad list of diseases. Physicians and scientists are just beginning to address
the question of how to keep such sensitive phenotypical and genotypical information
confidential so that it is not misused by either employers or insurance companies.
Most importantly, our patients will have to cope with this information, sometimes
left in the expectation of preventive strategies and therapeutic solutions.
As the first round of human genome sequencing nears completion, identifying functions
for each of the 30,000 or more human genes, and determining which of these genes play
a role in disease, will emerge as one of the great challenges of twenty-first century
biomedicine. Yet, physicians and scientists have undertaken the task of characterizing
and cataloging a shared universe of generic differences that underlies our susceptibility
to diseases and alters our response to drugs. Although this work appears to be quite
demanding, it provides tremendous opportunities in our search to understand, and ultimately
treat, diseases that account for most of the mortality and morbidity in our intensive
care units.
Abbreviations
SNP = single-nucleotide polymorphism, TNF = tumor necrosis factor.
Competing interests
None declared.
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