April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
MicroRNA Profiling and Global Proteomics in Giant Cell Arteritis
Author Affiliations & Notes
  • Guey-Shuang Wu
    Ophthalmology, Hlth Sci Campus, Univ of Southern CA, Los Angeles, California
  • Xiaohua Li
    Ophthalmology, Hlth Sci Campus, Univ of Southern CA, Los Angeles, California
  • Gabriel Gugiu
    Beckman Reseach Institute, City of Hope, Duarte, California
  • Terry D. Lee
    Beckman Reseach Institute, City of Hope, Duarte, California
  • Narsing A. Rao
    Ophthalmology, Hlth Sci Campus, Univ of Southern CA, Los Angeles, California
  • Footnotes
    Commercial Relationships  Guey-Shuang Wu, None; Xiaohua Li, None; Gabriel Gugiu, None; Terry D. Lee, None; Narsing A. Rao, None
  • Footnotes
    Support  NIH grant EY003040
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 4300. doi:
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      Guey-Shuang Wu, Xiaohua Li, Gabriel Gugiu, Terry D. Lee, Narsing A. Rao; MicroRNA Profiling and Global Proteomics in Giant Cell Arteritis. Invest. Ophthalmol. Vis. Sci. 2011;52(14):4300.

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

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Abstract

Purpose: : Giant cell arteritis (GCA) is a leading cause of blindness in the elderly. MicroRNAs play regulatory roles in a wide range of biological events through post-transcriptional repression of target mRNAs. New technologies for tissue retrieval from formalin-fixed paraffin-embedded (FFPE) sections have demonstrated improved recovery for both RNA and proteins. In this study, we sought the disease mechanism by microRNA expression and proteomics analysis using archival FFPE sections with clinical diagnosis of giant cell arteritis (GCA).

Methods: : Genome-wide microRNA PCR array was carried out using a total of 4 groups: GCAs, E1 and E2, and controls, C1 and C2 with each containing 18 sections from 6 age-matched patients. The bioinformatics limitation and p-value (<0.05) stringency were applied to truncate the raw data to 255 downregulated microRNAs. Validated target software, miRWalk was used for the search. For mass spectrometry-based proteomics (Water’s Synapt G2), both experimentals and controls (in triplicate) used one FFPE section/run.

Results: : MicroRNA targets were identified using selected 17 validated pathways from miRWalk database. The significantly downregulated microRNA and therefore, the upregulated targets include TLR4 (let-7i), MyD88 (548i, 374b, let-7i), TRAF6 (let-7a), IRAK4 (144, 10a, let-7c), NFΚB (let-7i, let-7a) and TNFα (548i, 374b, 24), signifying the TLR4 pathway. MicroRNAs in iNOS induction (92a, 17, 122, 184, 205, 17a) were also found. In proteomics, protective proteins, SOD, HSP 27, protein DJ-1, anti-inflammatory histones, and HSP 70 were upregulated. The mitochondrial stress is represented by loss of mitochondrial crystallins and increase in glycolysis enzymes and 14-3-3 proteins.

Conclusions: : Using microRNA, we identified a TLR4-driven innate immunity that leads to mitochondrial oxidative stress in GCA. Proteomics reflected the outcome of mitochondrial stress by revealing:1) increase in protective systems; 2) oxidative damage to the functional proteins; and 3) action to replenish the lost vital enzymes. The knowledge gained by this study may provide new insight into the microRNA-based interventions for GCA.

Keywords: inflammation • gene/expression • proteomics 
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