The potential of genomics
in cardiovascular disease was illustrated by the case
of four brothers with hypertrophic cardiomyopathy, three
of whom succumbed to sudden cardiac death. Linkage analysis
performed by Seidman and colleagues at Brigham &
Women's Hospital localized a mutation to a specific
region of the chromosome. Since this mutation was identified
in the surviving brother, an implantable cardioverter
defibrillator was implanted and the patient is alive
and well.
The greatest challenge is to understand the genetic
basis of polygenic complex diseases, such as heart disease
and hypertension. The lack of powerful tools to date
has been a limitation in this challenge. The use of
single nucleotide polymorphism (SNP), made possible
by the information and sequencing from the Human Genome
Project, provides greater frequency and fidelity than
that gained with the technique of sequence length polymorphism,
and represents a major step forward. The sequencing
technology made possible through the Human Genome Project
is an important advancement, along with the preliminary
map of the human genome. |
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The concept of genomic variation, that is, that within
a genome there is a high amount of sequence variation,
is the most important contribution. This sequence variation
determines many of the differences between people, determines
susceptibility to environmental changes and disease,
among other factors. Functional or physiological genomics
will be important for investigators to understand the
function of many newly-discovered genes, their physiology
and their role in disease. Comparative genomics across
different species will allow understanding of the evolution
of life, inheritance, and disease development. Computational
biology will be needed, as well as discussion about
the social, legal and ethical implications of genomics.
The single nucleotide polymorphism is the most common
genetic variation, and although it may not always have
functional consequences (dependent on its location)
it serves as an important marker for DNA and thus for
the ability to map genes for disease. There are three
million SNPs, and within each gene there may be several
hundred SNPs, allowing a greater chance to find genes
for disease and moves study from pedigree and sib pair
to population study. Thus, it is thought that the use
of SNPs and population studies will allow for identifying
the genes responsible for common diseases, such as diabetes,
hypertension, and other cardiovascular diseases. The
SNP map, reaching its completion by the SNP Consortium
supported by 13 countries, will contain all the SNPs
in the genome and will facilitate research.
A microarray chip is a single microchip that can hold
the genetic sequences of specific genes important for
disease. Using DNA from a patient and the microarray
chip, it will be possible to quickly assess whether
a variation or mutation for a specific disease occurs
within the patient's own genome. Such chips will be
available for both research and patient management.
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The application of genomic information to disease
to understand the etiology, natural history, select
treatment and predict outcomes. For example, in hypertrophic
cardiomyopathy, the work by Seidman and colleagues has
shown that regardless of the phenotype, there is tremendous
variation in natural history depending on genotype.
Specific mutations are predictive of sudden cardiac
death, which can direct therapy and impact patient outcomes.
Various mutations in hypertrophic cardiomyopathy predict
a range of different natural histories. Genomic information
can influence treatment outcome, as shown by a study
in patients with neuroblastoma. It was demonstrated
that patients with a loss of a specific allele had a
worse prognosis in response to chemotherapy compared
to those who maintain the allele region.
In the arena of drug therapy, by understanding the target
gene sequence variation it will be possible to understand
individual responses to drug. A disease gene can affect
disease pathways by influencing genes secondarily activated
in response to drugs. Thus, by understanding differential
responses at the transcription and cellular level to
a single drug or treatment intervention, it could be
possible to determine efficacy and safety. Metabolism
genes that determine metabolism of drugs will predict
pharmacokinetics and safety. Many studies in different
fields have demonstrated the ability of pharmacogenetic
predictors, DNA polymorphisms, to predict treatment
outcome. However, the sensitivity and specificity remains
to be shown. A study that looked at the cholesterol
ester transfer protein, which transfers cholesterol
ester from HDL to LDL, showed that patients with a specific
polymorphism responded as well to pravastatin treatment
as those patients without the polymorphism, compared
to those with the polymorphism and no statin treatment
whose disease progressed. Pharmacogenomics will improve
efficacy, allow for personalized therapy, improved safety,
better selection for clinical trials and improved cost
management. The redevelopment of drugs that have failed
will also be possible.
Molecular gene profiling will provide the ability to
segment patients into responders, non-responders, severe
versus mild phenotype, disease remission versus recurrence,
and likely to have a side effect or not.
The tools available to study genes are sequencing and
SNPs for genotyping; transcriptional profiling for mRNA
expression; protein or proteomics by mass spectrometry;
2D elelectrophoresis and rapid frequencing; and clinical
trials, population studies and model organisms for disease
physiology study. These will allow genotype-to-phenotype
correlation and provide a variety of opportunities for
molecular pattern recognition, and ultimately the identification
of individual genes and their roles in health and disease.
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Physiologic genomics encompasses
translating genomics and proteomics into functional
biology, defining functions of novel gene proteins,
characterizing novel roles for known genes, discovering
new biological pathways and facilitating translational
research efforts. Angiotensin is a good example of characterizing
novel roles for known genes. A number of different actions
for angiotensin have been discovered, and other novel
functions could be discovered through physiologic genomics.
The important question when doing this sort of study
is under what conditions are the functions recruited,
which involves the complexity of protein-protein interaction
and environmental cues. The tools and techniques available
in physiologic genomics are gene transfer knockouts
of expression, model organisms, protein-protein interaction,
mRNA expression, and computational biology, among others.
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Messenger RNA mediates phenotypic
expression. In a single normal phenotype, environmental
factors interacting with genetic factors can cause perturbation
to the phenotype and lead to changes in gene expression
and translation and can result in new transcription
proteins, which can mediate disease phenotype. Study
of gene expression, therefore, can inform understanding
of disease pathways and understanding of genes by the
company they keepthe tissue in which it is expressed,
the disease conditions in which it is expressed. Blocking
expression can prove the function of genes.
One approach in this regard would be to understand all
the genes expressed in the cardiovascular system. Dzau
and colleagues have sequenced eight cDNA library and
of the genes in the human myocardium and catalogued
their express sequence tag (EST) to allow molecular
cloning of the cDNA. The cDNA library can be placed
into a bioinformatics platform to create a microarray
to look at what genes are being expressed, under what
conditions, and the differentially-expressed genes.
Functional genomics can thus be explored and translated
into quantitative genomics using real-time PCR and other
approaches to look at the level of gene expression in
various diseases.
In the human heart, throughout any condition, about
25,000 of 35,000 genes may be expressed. This permits
the creation of a custom-built chip to study any condition
for human heart disease if it is possible to obtain
the tissue. The CardioChip has been designed for this
purpose. The human genome sequence and the cDNA library
provides for placing known DNA sequences, which can
be oligonucleotides to cDNA, on a microarray chip and
then immobilized. With this approach, it is possible
to look at 11,000 cDNAs with one chip simultaneously.
Microarray analysis can then allow exploration of what
genes are expressed in certain conditions, for example
heart failure or hypertrophic cardiomyopathy. One such
analysis of genes upregulated by greater than two-fold
in the failing heart identified natriuretic peptide
(validating the approach), heat shock protein, insulin-like
growth factor, cytokine-induced nuclear protein, and
a variety of unknown genes, providing the opportunity
to discover new genes that may be involved in heart
failure. Such new genes can be manipulated in animal
studies to validate whether they can produce a phenotype
of heart failure. |
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Gene Discovery
Using Gene Analysis |
Gene analysis can be used
to identify genes involved with disease progression
and those with disease reduction. Therapy can then be
directed at enhancing the expression of genes that are
beneficial and at reducing the expression of genes that
are deleterious. In cardiovascular disease, a homologue
of angiotensin converting enzyme was identified by genomic
sequencing in a human heart failure myocardial library.
Determining whether overexpression of this homologue
is involved with disease formation or modulation is
important.
In Tangier's disease, using a combination of linkage
analysis and gene expression analysis, it was demonstrated
that ABC-1 is abnormally expressed and results in low
HDL levels in those patients. Investigators are looking
at whether there are variations of ABC-1 in human atherosclerosis
and whether ABC-1 abnormality is a target for therapy.
CD-36, a fatty acid transporter, has been shown using
linkage analysis and expression profiling to be elevated
in insulin resistance. |
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Genomics can be applied
to understand pathophysiology, understand and predict
natural history, and predict treatment outcome. Novel
therapeutics, gene-based, antisense, oligonucleotide,
transcriptional factor decoy, ribozyme or recombinatory
chemistry, can be developed based on this knowledge.
In terms of genetic therapies, in vivo and ex vivo gene
therapy, cell-based therapy, somatic cells, autologous,
progenitor or stem cells, and the use of embryonic stem
cells can be imagined. This provides a larger armamentarium
to treat cardiovascular disease. In coronary artery
disease, a variety of conditions are amenable for such
molecular and genetic therapeutics based on the information
derived from genome and research in genome sciences:
angiogenesis, bypass vascular graft, restenosis, regional
vascular and myocardial protection, and systemic risk
factors.
Genomics will truly bring together many different fields.
Cardiovascular medicine will be very different in the
future. Bench research, including cell biology, biochemistry
and physiology will allow understanding of genes and
function. Clinical investigation will validate the function
and disease, and will involve patient-oriented research
looking at disease and function links and population
studies to validate the observations made at the individual
patient level. Gene mapping and discovery will allow
identification of new genes, which then feeds this bi-directional
cycle. Cardiovascular medicine in the post-genome era
will be shaped by this bi-directional circle. Physician-scientists
will play an important role in every aspect of this
cycle but, importantly, will play a role in trying to
bring this information to patient care. |
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