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. 2009 Jan;8(1):239-45.
doi: 10.1021/pr8003776.

Proteomic identification of salivary biomarkers of type-2 diabetes

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Proteomic identification of salivary biomarkers of type-2 diabetes

Paturi V Rao et al. J Proteome Res. 2009 Jan.

Abstract

The identification of biomarkers to noninvasively detect prediabetes/diabetes will facilitate interventions designed to prevent or delay progression to frank diabetes and its attendant complications. The purpose of this study was to characterize the human salivary proteome in type-2 diabetes to identify potential biomarkers of diabetes. Whole saliva from control and type-2 diabetic individuals was characterized by multidimensional liquid chromatography/tandem mass spectrometry (2D-LC-MS/MS). Label-free quantification was used to identify differentially abundant protein biomarkers. Selected potential biomarkers were then independently validated in saliva from control, diabetic, and prediabetic subjects by Western immunoblotting and ELISA. Characterization of the salivary proteome identified a total of 487 unique proteins. Approximately 33% of these have not been previously reported in human saliva. Of these, 65 demonstrated a greater than 2-fold difference in abundance between control and type-2 diabetes samples. A majority of the differentially abundant proteins belong to pathways regulating metabolism and immune response. Independent validation of a subset of potential biomarkers utilizing immunodetection confirmed their differential expression in type-2 diabetes, and analysis of prediabetic samples demonstrated a trend of relative increase in their abundance with progression from the prediabetic to the diabetic state. This comprehensive proteomic analysis of the human salivary proteome in type-2 diabetes provides the first global view of potential mechanisms perturbed in diabetic saliva and their utility in detection and monitoring of diabetes. Further characterization of these markers in a larger cohort of subjects may provide the basis for new, noninvasive tests for diabetes screening, detection, and monitoring.

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