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V.I. Shestopalov, T. Nikolskaya, I. Gariev, P. Yang, R. Hernandez; New Bioinformatics Approach in Studies of Optic Nerve Head Astrocytes in Glaucoma . Invest. Ophthalmol. Vis. Sci. 2003;44(13):1097.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: Glaucoma is a complex neurodegenerative disease with both genetic and physiological determinants. Pathology in glaucoma affects multiple ocular tissues and results in progressive excavation of optic nerve head (ONH), loss of retinal ganglion cells and blindness. Astrocytes of the ONH undergo dramatic changes in phenotype, tissue localization and surface markers, which may be causative to axonal degeneration. We sought to develop strategy for automated analysis of high-throughput (HT) data to investigate complex changes in human glaucomatous astrocytes compared to normal aged–matched controls at the system level. Methods: We developed a new bioinformatics approach, which allows to compare and analyze microarray data at system level. The newly designed software application sort raw experimental data for differentially expressed genes and maps them to corresponding metabolic and regulatory pathways, arranged into proprietary GeneGo DatabaseTM (GGDB). Using this approach we compared microarray data obtained in normal and glaucomatous human ONH astrocytes. Results: We revealed 1551 genes, differentially expressed in glaucoma, 100 of which were localized to 21 metabolic and 8 regulatory GGDB maps. Our data from reactive astrocytes showed discernible difference in expression of genes implicated in metabolism of phosphatidilinositol (20 genes), carbohydarates (19), aminoacids (10), purines (6), phospholipids (3), fatty acids (3); and regulation via different GPCR receptors (32), insulin (9), erithropoietins (8) and AKT kinase (4). These data suggests coordinate induction of stress genes, genes controlling cell motility and membrane remodeling in reactive ONH astrocytes, and is consistent with these cells migration into lamina cribrosa of the ONH, reported previously. Conclusions: Bioinformatics-based analysis confirmed our previous findings on glaucoma-induced pathology in astrocytes and suggested new avenues for future research. Our new approach combines the advantages and resolution of microarray-based expression profiling with the power of systems biology to study complex diseases like glaucoma. In addition to a substantial acceleration of HT data processing and comparison, this approach helps determine global pathological changes in the affected tissue at the level of metabolic and regulatory pathways.
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