High performance liquid chromatography analysis of tear protein patterns in diabetic and non-diabetic dry-eye patients

PURPOSE. To analyze and compare the high performance liquid chromatography (HPLC) runs of tear proteins from diabetic (DIDRY) and non-diabetic (DRY) d ry-eye patients, and healthy subjects (CTRL). The patterns were analyzed us ing multivariate statistical methods. METHODS. Tears (total 56 eyes: CTRL. n=16, DIDRY: n=21, and DRY: n=19) were analyzed by HPLC, using a size-exclusion column with an eluent of 0.5 M so dium phosphate buffer. The patients were primarily grouped according to the results of the basic secretory test (BST) in combination with subjective s ymptoms such as burning, foreign body sensations, tearing, and "dryness" of the eyes. Patients with BST values less than or equal to 10 mm/5 min plus two subjective symptoms were grouped as dry-eye patients. Before statistica l analysis, each HPLC run was quantitatively analyzed using ScanPacK softwa re (ScanPacK, Gottingen, Germany), and a data set was created from each HPL C run. The data were then analyzed by multivariate analysis of discriminanc e. RESULTS. The HPLC patterns of CTRL, DIDRY and DRY were significantly differ ent (Wilks' lambda: 0.0209; p<0.01). The area of the sIgA peak was signific antly smaller (p<0.05) in dry-eye tears than controls. There was a good cor relation between the extent of separation in the multivariate analysis and the BST value (r = -0.71). Classification of all samples resulted in 98% co rrect assignments. CONCLUSIONS. The analysis of HPLC patterns and subsequent statistical evalu ation are useful for the detection of dry eyes. The HPLC method and the sta tistical routines described allow a shorter analysis time than electrophore sis. HPLC analysis in combination with statistical analysis can be used as a diagnostic tool for the detection of dry eyes, and also improves the qual ity of analysis of disease-associated tear proteins in clinical research.