In diabetic patients, dry eye and other ocular surface diseases occur more often than in healthy subjects. The aim of this study was to analyze the tear protein patterns of patients suffering from diabetes mellitus type II (dia) and to compare them to the patterns of healthy volunteers (ctrl). Tear proteins of nonstimulated tears of 20 patients (ctrl n=10, dia n=10) were separated using two-dimensional electrophoretic techniques. The protein patterns of each group were analyzed by a multivariate analysis of discriminance. Furthermore, for all spots of each gel, a 50 x 50 variables pH/Mr (molecular weight) array was generated and subsequently analyzed by a multivariate analysis of discriminance. Additionally, an artificial neural network was trained using the matrix data as input and a sensitivity analysis was performed to figure out, which spots were the most important to differentiate between the tear protein patterns. In both groups a complex staining pattern could be obtained. In diabetic patients significantly more spots were detected compared to the control group (P<0.02). The analysis of discriminance found a highly significant difference between dia and ctrl (P<0.00001). Using the matrix data, the analysis of discriminance showed a significant difference between the two groups, too (P<0.0001). The sensitivity analysis by means of the artificial neural network revealed several spots that were more expressed or more frequently present in the diabetic group. Our findings reveal that the composition of tear proteins of diabetic patients is different from that of healthy subjects. The use of the two-dimensional electrophoretic technique could give more insight into the diabetic-related changes in the tear film composition.
Electrophoretic analysis of tear protein patterns could detect changes in tear proteins of smokers in comparison to nonsmokers. These changes were correlated with an increase of dry-eye-related subjective symptoms in smokers. Thus, electrophoretic analysis of tear proteins provided greater insight into the pathogenesis of smoking-induced ocular surface diseases.
Tear proteins of nonstimulated tears of 29 patients (healthy subjects, n = 8; dry-eye syndrome patients, n = 12; diabetic dry-eye patients, n = 9) were electrophoretically separated and stained by SYPRO Orange, followed by Coomassie blue staining. Both, the fluorescent and the Coomassie stains were subsequently analyzed by an automated two-dimensional algorithm for finding and quantification of peaks and by a discriminant analysis. Using SYPRO Orange, an average number of peaks/sample between three (at 200 ms) and 15 (at 3000 ms) could be found. In comparison, Coomassie staining resulted only in an average number of six peaks/sample. This corresponds to a sensitivity obtained at approx. 400-600 ms exposure time of SYPRO Orange stained gels. For all exposure times, the protein patterns of the three clinical groups were statistically significantly different from each other (P < 0.05). Only at 200 ms the distances between the groups decreased slightly. The Coomassie-stained gels revealed only a mid range discrimination power similar to that of 200-400 ms exposure in the fluorescing gels. The use of SYPRO Orange provides faster results than those obtained by Coomassie staining. In addition, the sensitivity of staining can be varied even in the same gel by changing the exposure time. The use of the two-dimensional algorithm allows to distinguish between the three clinical groups in accordance to earlier studies using one-dimensional densitographic raw data. Thus, the high speed of evaluation and the more sensitive results as compared to earlier studies could be a step further in the use of tear protein patterns in the diagnosis of DRY.
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