The routine clinical diagnosis of sicca syndrome remains difficult; the results of the standard tests, such as the Schirmer test, tear film break-up time and the rose Bengal test, correlate neither with the course of the disease nor with one another.
We introduce two procedures that can be used to differentiate patients with sicca syndrome from healthy individuals on the basis of tear fluid protein patterns. Electrophoretic separation of the tear proteins or measurement by high-performance liquid chromatography (HPLC) was followed by digital image processing and multivariate discriminant analysis.
In addition to analysis of tear protein patterns, these methods permit diagnostic classification. Statistical evaluation reveals whether an unidentified sample is to be classified as sicca syndrome or "healthy". Both HPLC analysis and protein electrophoresis detect differences in protein patterns between the tear fluid of healthy individuals and patients with sicca syndrome and point to a diagnosis accordingly.
Both of the techniques presented - electrophoresis and HPLC - could potentially be used for diagnostic purposes in the detection of sicca syndrome. The HPLC method of tear protein analysis is more reliable, lends itself more readily to automation and achieved greater success rates in the experiments we describe; for these reasons it is the preferred approach.