Use of a glycomics array to establish the anti-carbohydrate antibody repertoire in type 1 diabetes

Paul M. H. Tran, Fran Dong, Eileen Kim, Katherine P. Richardson, Lynn K. H. Tran, Kathleen Waugh, Diane Hopkins, Richard D. Cummings, Peng George Wang, Marian J. Rewers, Jin-Xiong She and Sharad Purohit ()
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Paul M. H. Tran: Medical College of Georgia, Augusta University
Fran Dong: University of Colorado Denver, Mail Stop A-140
Eileen Kim: Medical College of Georgia, Augusta University
Katherine P. Richardson: Medical College of Georgia, Augusta University
Lynn K. H. Tran: Medical College of Georgia, Augusta University
Kathleen Waugh: University of Colorado Denver, Mail Stop A-140
Diane Hopkins: Medical College of Georgia, Augusta University
Richard D. Cummings: Beth Israel Deaconess Medical Center, Harvard Medical School
Peng George Wang: Southern University of Science and Technology
Marian J. Rewers: University of Colorado Denver, Mail Stop A-140
Jin-Xiong She: Medical College of Georgia, Augusta University
Sharad Purohit: Medical College of Georgia, Augusta University

Nature Communications, 2022, vol. 13, issue 1, 1-11

Abstract: Abstract Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.

Date: 2022
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DOI: 10.1038/s41467-022-34341-2

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