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Proteomics as a research tool in clinical and experimental ophthalmology
Author(s) -
Cryan Lorna M.,
O'Brien Colm
Publication year - 2008
Publication title -
proteomics – clinical applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 54
eISSN - 1862-8354
pISSN - 1862-8346
DOI - 10.1002/prca.200780094
Subject(s) - macular degeneration , diabetic retinopathy , disease , blindness , medicine , proteomics , bioinformatics , glaucoma , identification (biology) , neuroscience , computational biology , pathology , biology , ophthalmology , diabetes mellitus , optometry , genetics , endocrinology , botany , gene
Abstract It is estimated that 37 million people worldwide suffer from blindness and 124 million people have impaired vision. While the relatively recently developed therapies, antivascular endothelial growth factor inhibitors for the treatment of age‐related macular degeneration, and prostaglandin analogues for the treatment of glaucoma are beneficial for some patients, there are many individuals with sight‐threatening diseases for whom no effective pharmacological therapy is available. For many of these diseases, the molecular mechanisms remain to be comprehensively elucidated, thus precluding the design of successful therapies against specific pathological targets. The current review summarises recent attempts to elucidate molecular mechanisms of ocular diseases, including diabetic retinal disease, age‐related macular degeneration and inherited blindness using proteomic methodologies. A novel hypothesis can be generated from global protein expression analysis of disease tissue, which can then be addressed with cellular and in vivo functional studies. For example, the identification of extracellular carbonic anhydrase from the vitreous of diabetic retinopathy patients using MS based proteomics led to the elucidation of a new pathway involved in intraretinal edema, which could be inhibited by a number of agents targeting different proteins in this pathway in relevant animal models. The potential of protein biomarkers for diagnosis and the identification of novel disease mechanisms are also discussed.

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