Van Eyk, Dunn - Proteomic and Genomic Analysis of Cardiovascular Disease - 2003 (522919), страница 42
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Theearliest form of atherosclerotic lesion is “fatty streak”, an aggregration of lipid-richmacrophages, foam cells and T-cells within intima. Fatty streaks precede intermediate lesions, which are composed of macrophages and smooth muscle cells(SMC) and develop to more advanced, complex occlusive plaques that containmacrophages, SMC, T-cells, atheromatous core and calcium. Complicated lesionsocclude the artery and may be ruptured resulting in thrombus formation [1]. Surgical bypass and angioplasty are the interventional therapies but they are limitedby the problems of restenosis and graft occlusions.
Smooth muscle cell proliferation and migration are the key factors in the development of restenosis [2]. Eventhough many important features of atherogenesis have already been characterized,more basic information is still needed to fully understand pathophysiologicalmechanisms involved in atherosclerosis and develop novel therapeutic strategies [3].The events in atherogenesis have been importantly clarified by studies in animal models, including rabbits, pigs, non-human primates and rodents [4]. Theavailability of spontaneously hypercholesterolemic models, Watanabe heritable hyperlipidemic rabbit (WHHL) and mice deficient in apolipoprotein E (apoE) or thelow-density lipoprotein receptor develop advanced lesions and are the modelsmost often used in genetic and pathophysiological studies.
Also, several featuresof atherosclerosis can be mimicked in cell culture models, for example by treatingcultured macrophages with oxidized low density lipoprotein to generate foam cells[5]. Although animal and cell culture models are very useful in studying atherogenesis, they give a partial figure of the complexity of human disease.
On theother hand, the use of human samples is limited by the availability of samples,since fresh arterial samples can only be collected from amputation operations,biopsies, organ donors and fast autopsies.Proteomic and Genomic Analysis of Cardiovascular Disease.Edited by Jennifer E. van Eyk, Michael J. DunnCopyright © 2003 WILEY-VCH Verlag GmbH & Co.
KGaA, WeinheimISBN: 3-527-30596-31429 Genes Involved in Atherosclerosis9.2Genes Influencing AtherogenesisAtherosclerotic lesions are heterogenous and they consist of many cell types including SMC, endothelial cells, fibroblasts, macrophages and T cells. These celltypes produce many proteins that are involved in atherogenesis. These proteins include lipoprotein receptors, growth factors, cytokines, matrix metalloproteinasesand cell adhesion molecules.Macrophage scavenger receptors are membrane glycoproteins that are involvedin internalisation of modified LDL. They mediate accumulation of modified lipoproteins in macrophages and participate foam cell formation [6]. They also anchormacrophages to atherosclerotic lesions and bind glycosylation end products,which is an important problem in diabetes [7].Cell-cell or cell-matrix interactions are mediated by adhesion molecules that canalso function in cell migration, signalling and other vascular responses.
Endothelium expresses adhesion molecules like integrins and selectins that increase the adhesion of monocytes and T-lymphocytes to endothelium [8]. Members of immunoglobulin superfamily e.g vascular cell adhesion molecule (VCAM-1) [9], intracellular adhesion molecules (ICAMs) [10] and platelet – endothelial cell molecule (PECAM) [11] serve as ligands for integrins. Adhesion molecule expression can beregulated by different cytokines.
Leukocyte adhesion is mediated by E-, L- and Pselectins which interact with ligands on leukocytes [12].Growth factors can stimulate cell proliferation, inhibit proliferation and act aschemoattractans. Peptide growth factors platelet derived growth factor (PDGF), fibroblast growth factor (FGF), vascular endothelial growth factor (VEGF) and insulin like growth factor (IGF-1) are involved in many important cellular processes inatherogenesis. These can induce SMC proliferation and are generally expressed inthe normal artery, whereas they are upregulated in atherosclerotic lesions [1, 13].Leukocytes move into the artery wall and SMC from the media to intima in a process called chemotaxis. Leukocyte chemotaxis is induced e.g.
by colony stimulating growth factors (CSFs) and SMC chemotaxis by PDGF and IGF-1 [1, 14]. Cytokines e.g. interleukin 1 (IL-1) and interferon c (IFNc) modulate inflammatory processes [1].Peroxisome proliferator-activated receptors (PPARs) are nuclear receptor-typetranscription factors that modulate inflammation and influence lipid metabolism[15].
NF-jB is a transcription factor associated with oxidative stress and inflammation. NF-jB regulates the expression of many important atherogenic genes including VCAM-1 and ICAM-1 [16]. Macrophages, SMC and T-cells in atheroscleroticlesions undergo apoptosis. Apoptosis is controlled by number of different genesor gene families e.g.
Bcl-2, caspases and nitric oxide (NO) [17]. Matrix metalloproteinases degrade extracellular matrix components which is essential for matrix remodelling, infiltration of inflammatory cells, plaque rupture and angiogenesis [18].Number of genes encoded by the human genome has been estimated to be*32,000–38,000 [19].
Not all genes are expressed in cardiovascular system. The total number of expressed sequence tags (ESTs) expressed in cardiovascular system9.3 DNA Arrays: The Principlewas evaluated by EST sequencing and microarray analysis and estimated as 20,930–27,160 genes [20]. Genes expressed in human heart have also been studied byEST sequencing, and over 40 000 different ESTs were produced [21].The analysis of changes in gene expression during atherogenesis enables thestudies of the molecular mechanisms behind the pathological process. Severalmethods are available for studying the gene expression.
Every expressed gene in atissue can be sequenced from a cDNA library of the tissue in a process called expressed sequence tag (EST) sequencing. The SAGE technique (Serial Analysis ofGene Expression) leverages DNA sequencing as a measure of transcript abundance. Real-time quantitative PCR can be used to quantify mRNAs. By differentialdisplay it is possible to identify differentially expressed genes between two ormore samples. DNA arrays have revolutionized expression studies since they havethe ability to profile the expression of thousands of genes in a single experiment[22].9.3DNA Arrays: The PrincipleDNA arrays have been applied to gene expression studies in bacteria, plants, yeastand mammals.
Disease-related changes in gene expression have been identified incancer, inflammatory diseases and heart diseases. Array analyses have also beenused for identification of new drug targets and mechanisms of drug action.Two types of DNA arrays have been utilized for the profiling of gene expression: cDNA arrays and oligonucleotide arrays. In addition, arrays differ with respect to methods of arraying, chemistry, linkers, hybridization and detection. In acDNA array, cDNA fragments usually produced by PCR are spotted to microscopeslides (microarrays) or nylon membranes (macroarrays) [23, 24]. Oligonucleotidearrays developed by Affymetrix are composed of thousands of oligonucleotides, 25nucleotides in length [25]. mRNAs from samples of interest are labelled with fluorescent dyes (Cy3 and Cy5) or radioactive nucleotides (33-P) and hybridized withimmobilized targets.
Two-colour fluorescent detection can be used with glass microarrays. Arrays with radioactive detection are more sensitive than fluorescent arrays, requiring only 0.5 lg of mRNA in contrast to 2–5 lg of mRNA needed forarrays with fluorescent detection. After hybridisation, signal intensities are measured with confocal fluorescent microscopy or phosphoimager, and special software is used for the rapid identification of differentially expressed genes.
Clustering methods can be used to find patterns in differentially expressed genes [26].Comparison of expression data from multiple arrays requires normalization.Use of signal intensities of a subset of genes e.g. housekeeping genes or commercial hybridization controls can be used for the normalization for divergent samples. If intensities of all genes are used, samples have to be closely related [3]. Todescribe the difference in signal intensities and thus in expression, intensity ratios have to be calculated. We have developed a formula where signals are normalized and intensity scores (fold increase or decrease) are calculated1431449 Genes Involved in Atherosclerosisscore int GDA1 n:m int GDA2 n 1Where the int GDA 1 and GDA 2 are intensities of filters 1 and 2, m is the average of all intensities on filter 1 divided by the average of intensities on filter 2 andn is 0.2 ´ m.
The rationale for using the formula was to avoid false results causedby very low signal intensities which with the current formulation only producevalues *1. The formula also takes into account possible differences in the general background of the filters. Genes showing ³ 1.5–2 – fold increase or decreaseshould be processed further. Statistical significances of the differences are calculated according to Claverie [27].Gene expression studies produce similar needs to use bioinformatics irrespective of the array method used. The enormous amount of data has to be analyzedand presented in a meaningful way, which has been identified as the greatestchallenge in the array research. Computational biology and mathematical modelling need to be integrated with DNA array related work.
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