Type 1 autoimmune pancreatitis (AIP) is a kind of IgG4-related disease in which higher IgG4 and total IgG levels have been found in patient serum. Due to the similar imaging features and laboratory parameters between AIP and pancreatic ductal adenocarcinoma (PDAC), a differential diagnosis is still challenging. Since IgG profiles can be potential bio-signatures for disease, we developed and validated a method which coupled on-bead enzymatic protein elution process to an efficient UHPLC–MS/MS method to determine IgG subclass and glycosylation. A stable-isotope labeled IgG was incorporated as internal standard to achieve accurate quantification. For calibration curves, the correlation coefficients for total IgG and the four IgG subclasses were higher than 0.995. Intraday (n = 5) and interday (n = 3) precisions of the peak area ratios of LLOQ, low, medium, and high QC samples were all less than 6.6% relative standard deviation (% RSD), and the accuracies were between 93.5 and 114.9%. Calibration curves, precision, and accuracy were also evaluated for 26 IgG glycopeptides. The method was applied to samples from healthy controls and patients with AIP and PDAC. Distinct IgG patterns were discovered among the groups, and 7 glycopeptides showed high potential in differentiating AIP and PDAC. The results demonstrated that the developed method is suitable for multi-feature analysis of human IgG, and the discovered IgG profiles can be used as bio-signatures for AIP and PDAC.
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