May 2004
Volume 45, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2004
Analysis of gene expression profile in the glaucomatous human retina using DNA microarray
Author Affiliations & Notes
  • Z.S. Boyd
    Ophthalmology,
    University of Nebraska Medical Center, Omaha, NE
  • G. Zhan
    Ophthalmology,
    University of Nebraska Medical Center, Omaha, NE
  • H.S. Pawar
    Ophthalmology & Visual Sciences, University of Michigan, Ann Arbor, MI
  • D. Bozinov
    Center for Human Molecular Genetics,
    University of Nebraska Medical Center, Omaha, NE
  • J. Eudy
    Center for Human Molecular Genetics,
    University of Nebraska Medical Center, Omaha, NE
  • J.E. Richards
    Ophthalmology & Visual Sciences, University of Michigan, Ann Arbor, MI
  • R.V. Patil
    Ophthalmology,
    University of Nebraska Medical Center, Omaha, NE
  • Footnotes
    Commercial Relationships  Z.S. Boyd, None; G. Zhan, None; H.S. Pawar, None; D. Bozinov, None; J. Eudy, None; J.E. Richards, None; R.V. Patil, None.
  • Footnotes
    Support  Research to Prevent Blindness
Investigative Ophthalmology & Visual Science May 2004, Vol.45, 4393. doi:
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      Z.S. Boyd, G. Zhan, H.S. Pawar, D. Bozinov, J. Eudy, J.E. Richards, R.V. Patil; Analysis of gene expression profile in the glaucomatous human retina using DNA microarray . Invest. Ophthalmol. Vis. Sci. 2004;45(13):4393.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Abstract: : Purpose: To identify changes in retinal gene expression associated with glaucoma. Methods: We have used human U133A Gene Chip oligonucleotide microarrays (Affymetrix, Inc.) containing probe sets representing 22,000 well characterized transcripts. cRNA targets were generated from 4 normal and 4 glaucomatous retinas and hybridized per manufacturers established protocols. The arrays were scanned and Microarray Analysis Software 5 (Affymetrix) was used to determine the intensity values for each transcript. Ingenuity Pathways Analysis, a web–based software, was used to categorize gene expression array data sets into therapeutically relevant networks. Filtering procedures and analysis methods in GeneSight (Biodiscovery) were used for hierarchical clustering of differentially expressed genes. Results: At the >= 2–fold change, using normal retinal gene expression as baseline, 202 genes were down regulated and 14 genes were up–regulated in the glaucomatous retina. Notably, BCL2L, MAP3K1, IL6ST, glutamine synthase, alpha enolase like 1, vacuolar H+ ATPase, VGEF and to a lesser extent aquaporin–4, were down regulated in the glaucomatous retina. A comparison of the normal and the glaucomatous retina showed major down regulation of genes in the following functional groups (number of genes per cluster in parenthesis): transport (13), cell death/apoptosis (11), gene transcription (9), phosphorylation/dephosphorylation (6), response to stress (6), cell proliferation (4), DNA repair (2), and immune response (1). Conclusions: This study demonstrates the utility of gene microarray technology in identifying global patterns of retinal gene expression, thus providing the first comprehensive list of genes up/down regulated in glaucomatous human retina. Identification of genes in glaucomatous retina contributes to our understanding of retinal biology and potentially provides novel candidate genes for retinal disorders such as glaucoma.

Keywords: gene microarray • retina • gene/expression 
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