Methods: In this study, we applied label-free differential protein expression analysis using multidimensional liquid chromatography/tandem mass spectrometry (2D-LC-MS/MS) to explore the proteomic profile of saliva samples collected from 50 and 100 subjects with type 1 and 2 diabetes, respectively.
Results: For each type of diabetes, saliva samples were pooled into five groups based on the subject’s hemoglobin A1C levels;<7, 7-8, 8-9, 9-10 and >10. Cluster analysis and principle component analysis demonstrated a differential pattern of protein biomarker expression based on the A1C levels. In addition, the proteomic profiling demonstrates similar A1C-related biomarkers between the type 1 and 2 diabetes.
Conclusions: This cross-sectional study provides proof-of-principle for using salivary protein surrogates for A1C.