Kurzfassung

The study of dry-eye syndrome is gaining in importance because of the high frequency of occurrence and the difficulties in treating the disease. The National Eye Institute/Industry Workshop adopted the following definition of dry eye (Lemp, 1995). Dry eye is a disorder of the tear film due to tear deficiency or excessive tear evaporation which causes damage to the interpalpebral ocular surface and is associated with symptoms of ocular discomfort. Patients suffering from dry-eye syndromes show...The study of dry-eye syndrome is gaining in importance because of the high frequency of occurrence and the difficulties in treating the disease. The National Eye Institute/Industry Workshop adopted the following definition of dry eye (Lemp, 1995). Dry eye is a disorder of the tear film due to tear deficiency or excessive tear evaporation which causes damage to the interpalpebral ocular surface and is associated with symptoms of ocular discomfort. Patients suffering from dry-eye syndromes show several clinical signs resulting from aqueous, mucin or lipid deficiency.

Studies have demonstrated that the electrophoretic analysis of tear proteins is able to detect differences in the tear protein profiles between patients with dry eye syndrome and healthy subjects (Mackie and Seal, 1984). Furthermore, altered protein profiles in tears were found, not only in dry eye, but also in some other ocular and systemic diseases (e.g., diabetes mellitus [Herber et al, 2002, Herber et al, 2001, Dogru et al, 2001 and Stolwijk et al, 1994]) and in cases with other factors that might interfere with the ocular surface (e.g., contact lenses and smoking [Marquardt and Christ, 1986, Grus et al, 2002). All these studies provide evidence that specific proteins or peptides in tear film can be used as diagnostic biomarkers for dry eye, ocular surface diseases, and even systemic disease states such as diabetes mellitus.

Previous investigation of tear film proteins have been extensively analyzed by one-dimensional (1-D) gel electrophoretic techniques, high-performance liquid chromatography, (Khalil et al, 1988) two-dimensional (2-D) gel electrophoresis,(Reitz et al,1998) or other chromatographic approaches and lately using surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) ProteinChip Array technology (Gruz et al, 2005). The SELDI-TOF-MS technology seems to be ideally suitable for the mass screening of peptides and proteins in tears. This highly sensitive approach dramatically reduces the analysis time and provides protein profiles with great mass accuracy. Thus, it becomes a very useful tool in the search for potential biomarkers for diagnosis and new therapeutics in ocular diseases as dry eye (Gruz et al, 2005).

Complex patterns of tear proteins and peptides were detected. The different chromatographic surfaces revealed the selective enrichment of proteins such as lipocalin and lysozyme. Discriminant analysis by Gruz et al (2005) using the SELDI-TOF-MS ProteinChip Array technology demonstrated highly significant changes in the protein profiles in patients with dry eye. In the peptide range, seven candidate biomarkers were determined with the help of multivariate discriminant analysis. Five identified biomarkers are PRP3, PRP4, NACPP4, calgranulin A and C-terminal fragment of α-1-antitrypsin and two biomarkers at 3700 and 3916 Da remain to be identified at this time. The biological importance underlying genetic polymorphism of PRP4 and NCAPP4 is still unknown and further studies will be needed to shed light on functions and relevance of these seven biomarker proteins in dry-eye disease and their roles in the pathogenesis of the disease.

The objective of this work is to identify the remaining two biomarkers (3700 and 3916 Da) and to find functions, correlations and relevance of these protein biomarkers for dry-eye disease by comparing the protein profiles of tears from patients with dry eye and healthy control subjects and analyzing those using univariate analysis, multivariate statistical techniques, and artificial neural networks. The important of this analysis phases studies is to build a multivariate panel of markers that will classify the two groups as accurately as possible and protein biomarker patterns which can lead to powerful diagnostic tools, to advances in predictive medicine and a discovery of new therapeutic targets for drug development.
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