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Glycation end-products specific auto-antibodies in Systemic Lupus Erythematosus



Mohd Wajid Ali Khan*



Department of Chemistry, College of Science, University of Hail, Hail-2440, Saudi Arabia



Mohd Wajid Ali Khan E-mail: wajidkhan11@gmail.com; mw.khan@uoh.edu.sa


Article Type

Research Article



Received January 12, 2022; Revised March 11, 2022; Accepted March 31, 2022, Published March 31, 2022



Systemic lupus erythematosus (SLE) is an autoimmune disease, which is highly inflammatory. Compared to a healthy control group, SLE patients exhibit a higher concentration of advanced glycation end products (AGEs) and a lower concentration of receptors for AGEs (RAGE) in serum, however, the exact aetiology is still unclear. In the present study, non-enzymatic glycation induced modification of human serum albumin (HSA) has been studied by biophysical techniques. Glycated HSA (G-HSA) was used as an antigen, and serum autoantibody levels were estimated in SLE and normal humans (NH) against it, using direct binding ELISA and competitive inhibition ELISA. Compared to N-HSA, remarkable structural modifications were observed in G-HSA. Modified HSA also showed increased pentosidine fluorescence (213.7 13.4 AU). Glycation of HSA induced a conversion of α-helix and random coil to β-sheet and β-turns. Serum immuno assays results exhibited significantly (p < 0.001) higher binding of G-HSA with serum autoantibodies from SLE patients when compared with native HSA (N-HSA). Furthermore, competitive ELISA results showed significantly (p < 0.001) high percent inhibition of serum IgG from SLE patients with modified antigen. Chronic inflammation with excessive oxidative stress in SLE patients could be a possible reason for structural alterations in blood proteins, generating highly immunogenic unique new-epitopes. These in turn induce the generation of specific autoantibodies against G-HSA that may serve as a potential biomarker for SLE pathogenesis.



SLE, glycation, AGEs, autoantibodies, HAS



Ali Khan, Bioinformation 18(3): 127-133 (2022)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.