Although it has long been considered that myocardial gene expression is not subject to major regulation because the cardiomyocytes do not divide, it is now widely accepted that the myocardium can develop a remarkable plasticity at the gene level [1-9]. This adaptation of the nuclear activity is the direct consequence of variations in physiological conditions, and is strongly associated with the adaptation of both metabolic [10-14] and contractile  properties of the heart. A large-scale analysis of the regulation of gene expression in response to changes in physiological parameters is the goal of functional genomics.
Because of its fundamental function for the organism, the heart is extraordinarily receptive to variations of extracellular conditions, which are often referred to as a "stress" for the cardiac myocyte: increased contractile performance , oxygen deprivation [17, 18], burst of free radicals , endothelial dysfunction , increased preload [21, 22], cellular stretch  are just a few examples of the changes in extracellular conditions that directly affect the cardiac cell. All these stimuli, either physiological or deleterious, are detected by different sensors (receptors, ion channels or transmembrane proteins) , relaying the information to transmitters (signaling pathways) , which in turn regulate the activity of the effectors (enzymes and transcription factors) [25, 26]. The effectors are directly responsible for the adaptation of the expression of different genes in response to the initial stimulus (Fig. 5.1). In other words, the gene expression profile is the "end-point" of the effects of any stimulus on the heart (Fig. 5.1). Determining this profile helps deciphering the fundamental characteristics of a specific stimulus. Comparing the profiles in response to different stimuli also helps to determine the similarities and differences between these stimuli. The accumulation of gene profiles in response to different conditions leads to the elaboration of a compendium of cardiac gene expression. This compendium can subsequently be used, for instance, to analyze the effects of a drug on cardiac gene expression in different physiological conditions .
Genomics and proteomics are complementary, but they also address very different questions. The analysis of gene expression as an "end-point" of the effects of a specific stimulus on the heart is in sharp contrast with the concept of the gene as a "starting point' leading to the expression of specific proteins (Fig. 5.1). The "end-point strategy" consists in looking at the gene not as a protein provider, but
Proteomic and Genomic Analysis of Cardiovascular Disease. Edited by Jennifer E. van Eyk, Michael J. Dunn
Copyright © 2003 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 3-527-30596-3
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