December 2002
Volume 43, Issue 13
Free
ARVO Annual Meeting Abstract  |   December 2002
Gene Expression Profiling in Human Retina using a Retina Custom cDNA Microarray
Author Affiliations & Notes
  • I Chowers
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • D Liu
    Biostatistics Johns Hopkins University School Of Public Health Baltimore MD
  • RH Farkas
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • T Gunatilaka
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • A Hackam
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • E Duh
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • M Kageyama
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • G Parmigiani
    Biostatistics Johns Hopkins University School Of Public Health Baltimore MD
  • PA Campochiaro
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • DJ Zack
    Wilmer Eye Institute Johns Hopkins University School Of Medicine Baltimore MD
  • Footnotes
    Commercial Relationships   I. Chowers, None; D. Liu, None; R.H. Farkas, None; T. Gunatilaka, None; A. Hackam, None; E. Duh, None; M. Kageyama, Santen Pharmaceutical Co., Ltd. E; G. Parmigiani, None; P.A. Campochiaro, None; D.J. Zack, Santen Pharmaceutical Co., Ltd F. Grant Identification: Support: RPB, FFB, Macula Vision Foundation, Michael Panitch Fund, Santen Pharmaceutical Co., LTD
Investigative Ophthalmology & Visual Science December 2002, Vol.43, 3922. doi:
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    • Get Citation

      I Chowers, D Liu, RH Farkas, T Gunatilaka, A Hackam, E Duh, M Kageyama, G Parmigiani, PA Campochiaro, DJ Zack; Gene Expression Profiling in Human Retina using a Retina Custom cDNA Microarray . Invest. Ophthalmol. Vis. Sci. 2002;43(13):3922.

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

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Abstract

Abstract: : Purpose: To characterize the gene expression profiles of normal human retina across different demographic conditions, and to compare the gene expression profile of retina with other tissues. Methods: A human retina custom cDNA microarray that contains 10,000 different cDNA of genes and Ests from retina cDNA libraries, as well as selected genes that may be involved in a variety of retinal disorders, was constructed. High throughput gene expression profiling was performed in 30 retinas from 16 donors (age range 29-90 years, 10 male and 6 female), and in human liver and brain tissue. Statistical analysis was performed to determine the variability of expression patterns across the different retinas, as well as to identify differentially expressed genes across different demographic conditions and different tissues. Significant analysis of microarray (SAM) was used to predict the false discovery rate in the group of the identified differentially expressed genes. Complimentary molecular biology techniques were used to confirm the microarray technique results. Results: Across the different retinas, the expression level of half of the genes on the array (5000 genes) changed less than two-fold, and the expression level of 97% of the genes on the array (9700 genes) changed less than 4 fold. A group of genes and Ests that were highly expressed in the retina compared to liver and brain was identified. This group included genes that were not previously known to be preferentially expressed in the retina, as well as Ests representing novel genes. In addition, groups of genes and Ests that were expressed differentially between retinas from different demographics were identified. For example, at a median false discovery rate of 0 % (as estimated by SAM) 17 genes were considered to be differentially expressed between retinas from old vs young patients - 15 of these genes had on average more than 1.5-fold expression level difference among the groups. Conclusion: These results confirm the feasibility of our custom retina cDNA microarray slide to identify differentially expressed genes among groups of retina samples. We have identified the expression pattern of 10.000 different genes and Ests in a group of retinas with variable demographics and the data obtained will facilitate the characterization of novel genes that are preferentially expressed in the retina, and the identification of genes that may have a role in retinal aging.

Keywords: 417 gene/expression • 554 retina • 309 aging 
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