Background: Anti-double-stranded DNA (anti-dsDNA) antibodies are crucial markers of systemic lupus erythematosus (SLE). Glycosylation is one of the most common post-translational modifications of antibodies, and anti-dsDNA antibody glycosylation is associated with SLE activity. However, the relationship between anti-dsDNA antibody glycosylation and SLE organ involvement remains unclear.

Objectives: To classify the degree of organ system involvement and predict the severity of SLE based on the anti-dsDNA IgG glycoform profiles of patients.

Methods: We enrolled 86 consecutive treatment-naïve SLE patients positive for anti-dsDNA antibodies from the Department of Rheumatology and Immunology at Ruijin Hospital, Shanghai, between 2017 and 2019. Serum samples were used for this study. We quantified and classified the degree of organ involvement in SLE patients according to the number of organ systems involved. We then analysed each glycoform and a combination of glycoforms based on the degree of involvement. A random forest classifier and artificial neural network were applied to evaluate the correlation between the levels of glycoform pairs and the degree of organ involvement.

Results: Pearson’s correlation analysis revealed a strong connection between the involved organs in SLE patients. Bisection (Bis) of IgG3/4, galactosylation (Gal) of IgG1, fucosylation (Fuc) of IgG1, and sialylation (Sia) of IgG2 displayed high area under the curve (AUC) values when combined with other glycoforms to classify the degree of involvement. Random forest analysis showed that the combination of IgG1Gal and IgG3/4Bis had the highest accuracy (0.7692) and AUC (0.8187). In terms of predicting the degree of involvement using an artificial neural network, IgG3/4Bis and IgG1Gal showed the lowest mean squared error (0.0244).

Conclusion: Our study showed the effectiveness of combining glycoforms to classify and predict the degree of SLE organ involvement. Different glycoforms were correlated with the involvement degree to various extents, and the combination of IgG3/4Bis and IgG1Gal exhibited the best correlation with SLE organ involvement.

REFERENCES: NIL.

Acknowledgements: Authors would like to extend thanks and gratitude to all the doctors and students in the Department of Rheumatology and Immunology, Ruijin Hospital.

Disclosure of Interests: None declared.

© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.