pdf).
Cardiovascular diseases are the leading cause of death in the world, as a consequence of overpopulation. To identify potential biomarkers and/or therapeutic targets for cardiovascular diseases, one must use an integrative genomics approach. In this chapter, we describe a case study that aims to identify potential biomarkers for cardiovascular diseases using microarray, bioinformatics and systems biology methods. We describe the integration of microarray data into a bioinformatics framework and the use of this integrated data as the basis for further analysis.
Cardiovascular diseases are the leading cause of death in the world. In the western world alone, cardiovascular diseases account for more than one third of deaths. [@ref-1] According to the International Committee for Heart Disease, cardiovascular diseases are responsible for the deaths of 36% of people in the world and are the single leading cause of death among women aged 15--69 years and men aged 15--69 years. [@ref-1] The etiology of cardiovascular diseases is multifactorial and includes genetic, behavioral and environmental factors. At the genetic level, hypertension is believed to be largely under the control of genes and their gene products.
One approach to discover genes associated with cardiovascular diseases is to identify genes or gene clusters related to different cardiovascular phenotypes. In this approach, subjects are grouped according to cardiovascular phenotype. This approach is used in large-scale quantitative trait locus (QTL) studies and genome-wide linkage analysis, or for genes discovered from genetic association studies. [@ref-2]
Another approach to discover genes for cardiovascular diseases is to perform gene expression profiling to identify genes that are differentially expressed between disease and non-disease. This approach is generally used to identify genes associated with specific disease conditions. [@ref-4]
In this chapter, we describe the use of a systems biology approach to identify potential biomarkers for cardiovascular diseases using a microarray dataset of rat aortas.
Data source and study design
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Microarray
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Rats were randomly selected from a large colony and euthanized according to the Institutional Animal Care and Use Committee (IACUC) of The University of Texas MD Anderson Cancer Center (UTMDACC) under the protocol IACUC-10-013. Briefly, the rats were anesthetized with a cocktail of ketamine hydrochloride and xylazine hydrochloride and euthanized by an injection of sodium pentobarb
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