Glycation of glucose sensitive lysine residues K36, K438 and K549 of albumin is associated with prediabetes

Abstract Prediabetes is a risk factor for the development of diabetes. Early diagnosis of prediabetes may prevent the onset and progression of diabetes and its associated complications. Therefore, this study aimed at the identification of novel markers for efficient prediction of prediabetes. In this pursuit, we have evaluated the ability of glycated peptides of albumin in predicting prediabetes. Glycated peptides of in vitro glycated albumin were characterized by data dependent acquisition and parallel reaction monitoring using LC-HRMS. Amongst 14 glycated peptides characterized in vitro, four peptides, particularly, FK(CML)DLGEENFK, K(AML)VPQVSTPTLVEVSR, K(CML)VPQVSTPTLVEVSR, and K(AML)QTALVELVK, corresponding to 3 glucose sensitive lysine residues K36, K438, and K549, respectively showed significantly higher abundance in prediabetes than control. Additionally, the abundance of three of these peptides, namely K(AML)QTALVELVK, K(CML)VPQVSTPTLVEVSR and FK(CML)DLGEENFK was >1.8-fold in prediabetes, which was significantly higher than the differences observed for FBG, PPG, and HbA1c. Further, the four glycated peptides showed a significant correlation with FBG, PPG, HbA1c, triglycerides, VLDL, and HDL. This study supports that glycated peptides of glucose sensitive lysine residues K36, K438 and K549 of albumin could be potentially useful markers for prediction of prediabetes. Significance Undiagnosed prediabetes may lead to diabetes and associated complications. This study reports targeted quantification of four glycated peptides particulary FK(CML)DLGEENFK, K(AML)VPQVSTPTLVEVSR, K(CML)VPQVSTPTLVEVSR, and K(AML)QTALVELVK, corresponding to 3 glucose sensitive lysine residues K36, K438 and K549 respectively by parallel reaction monitoring in healthy and prediabetic subjects. These peptides showed significantly higher abundance in prediabetes than healthy subjects, and showed significant correlation with various clinical parameters including FBG, PPG, HbA1c, and altered lipid profile. Therefore, together these four peptides constitute a panel of markers that can be useful for prediction of prediabetes.