Background: Type 2 diabetes mellitus (T2DM) is the most common lifestyle disease affecting all countries. Due to its asymptomatic onset, it is often diagnosed after irreversible vascular complications have been initiated. Therefore, specific markers characteristic for very early disease stages and suitable for early diagnostics are required. Glycation of plasma proteins, such as human serum albumin (HSA), has been often suggested as marker. However, the total glycation degree of HSA does not provide sufficient information about short-term fluctuations of blood glucose concentrations due to the large number of glycation sites. Analysis of individual modification sites might be more informative, but methods for reliable quantifications are still missing.
Objective: The main objective of this study was to establish and qualify a method of analysis applicable to sensitive and precise quantification of glycations sites in plasma proteins.
Methods: Plasma samples obtained from diabetic patients and non-diseased individuals were separated from low-molecular weight compounds, digested with trypsin, enriched for glycated peptides by boronic acid affinity chromatography (BAC), desalted by solid phase extraction (SPE), and separated by RP-HPLC coupled online to ESI-QqQ-MS. Quantification relied on multiple reaction monitoring (MRM) of multiple glycation sites identified in plasma proteins using a stable isotope dilution approach or internal standardization.
Results: The data presented here suggests high selectivity and precision (relative standard deviations below 10%) of the overall approach appearing to be well suited for the identification of prospective biomarkers. Six glycated peptides corresponding to different glycation sites of HSA were present in plasma samples obtained from T2DM patients at significantly higher levels than in non-diabetic men matched for age. Additionally, each of the studied glycation site of HSA appeared to be affected at different degrees.
Conclusion: The presented approach enables the sensitive and robust quantification of prospective T2D biomarkers promising for clinical diagnostics.