Brief
Description of this PGA:
The goal of this PGA is to begin linking genes to function,
dysfunction and structural abnormalities of the cardiovascular system
caused by clinically relevant, genetic and environmental stimuli.
The principal biological theme to be pursued is how the transcriptional
network of the cardiovascular system responds to genetic and environmental
stresses to maintain normal function and structure, and how this network
is altered in disease.
Project 1 - Take a multidisciplinary approach combining
well-defined mouse models of cardiomyopathy and vasculopathy with
an integrated analysis of physiology, pathology, and RNA expression
profiling to search for prototypical patterns of gene expression in
response to various genetic and non-genetic perturbations.
Project 2 - Perform transcriptional profiling using
human myocardium and vascular tissues obtained at the time of cardiac
transplant and compare the transcriptional profile data with those
of various mouse models.
Projects 3 and 4 - Screen for mutations that cause cardiovascular
malformations with particular emphasis on hypertrophic cardiomyopathy,
dilated cardiomyopathy, and selected sets of patients with congenital
heart disease.
Project 5 - Examine 200 candidate genes, identified
by the mouse and human expression studies, in 2000 individuals drawn
from the Framingham Heart Study. In these studies, a single nucleotide
DNA polymorphism analysis (SNP) will be correlated with echocardiographic
evidence of left ventricle mass, cardiac chamber size and aortic root
size.
The data generated by all of the above studies will
be analyzed by state-of-the-art informatics to search for common and
disease-specific pathways. The data will be extensively annotated
and made freely available to the scientific community through our
interactive website.
In summary, this PGA will generate a high quality, comprehensive
data set for the functional genomics of structural and functional
adaptation of the cardiovascular system by integrating expression
data from animal models and human tissue samples, mutation screening
of candidate genes in patients, and DNA polymorphisms in a well characterized
general population Such a data set will serve as a benchmark for future
basic, clinical and pharmacogenomic studies.
Resources
to be developed by this PGA: