May 2006
Volume 47, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2006
Proteinchip Biomarker Profiling Study in Aqueous Humor of Glaucoma Patients
Author Affiliations & Notes
  • F.H. Grus
    Dept, University, Mainz, Germany
  • U. Thiel
    Dept, University, Mainz, Germany
  • N. Wiegel
    Dept, University, Mainz, Germany
  • A. Wirthlin
    Proteognostics, Baar, Switzerland
  • N. Pfeiffer
    Dept, University, Mainz, Germany
  • Footnotes
    Commercial Relationships  F.H. Grus, None; U. Thiel, None; N. Wiegel, None; A. Wirthlin, Proteognostics, I; N. Pfeiffer, None.
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science May 2006, Vol.47, 200. doi:
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      F.H. Grus, U. Thiel, N. Wiegel, A. Wirthlin, N. Pfeiffer; Proteinchip Biomarker Profiling Study in Aqueous Humor of Glaucoma Patients . Invest. Ophthalmol. Vis. Sci. 2006;47(13):200.

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

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Abstract

Purpose: : Glaucoma is characterized by a progressive loss of retinal ganglion cells that results in a characteristic optic neuropathy associated with visual field loss. The aim of this study was to analyze the protein and peptide profiles in the aqueous humor of glaucoma patients and compare them to those of non–glaucoma patients.

Methods: : 46 patients were included in this study: a control group (CTRL, n=24) and a group consisting of patients with primary open–angle glaucoma (POAG, n=22). Aqueous humor was taken from control subjects undergoing cataract surgery, and from POAG patients undergoing trabeculectomy. The aqueous samples were analyzed using SELDI–TOF–MS ProteinChip Arrays with two different chromatographic surfaces (CM10 cation exchange and H50 reversed phase) prepared by means of a laboratory liquid handling robotic workstation. The data were analyzed by multivariate statistical techniques and artificial neural networks.

Results: : About 250 protein peaks (mass/charge ratios) could be consistently clustered in both groups. After exclusion of peaks with low signal–to–noise ratio and/or poor resolution and peaks representing differentially charged proteins, a multivariate analysis of discriminance and artificial neural networks were performed to find differentially expressed protein biomarkers between both groups. The analyses revealed 8 biomarkers, which discriminated glaucoma from non–glaucoma controls with a sensitivity of 90% and a specificity of 87%. These biomarkers were purified further and identified by tandem mass spectrometry (Maldi–TOFTOF) as e.g. Cystatin and Transthyretin.

Conclusions: : With use of these potential biomarkers, glaucoma can be distinguished from control subjects with high accuracy in this pilot study. Glaucoma patients revealed characteristic differences of protein/peptide profiles from control patients in aqueous humor. The identified biomarkers could provide more insight the pathogenesis of the disease process.

Keywords: proteomics • pathology: human • anterior chamber 
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