IgG glycan patterns are associated with type 2 diabetes in independent European populations

Abstract

Background: Type 2 diabetes results from interplay between genetic and acquired factors. Glycans on proteins reflect genetic, metabolic and environmental factors. However, associations of IgG glycans with type 2 diabetes have not been described. We compared IgG N-glycan patterns in type 2 diabetes with healthy subjects.

Methods: In the DiaGene study, a population-based case-control study, (1886 cases and 854 controls) 58 IgG glycan traits were analyzed. Findings were replicated in the population-based CROATIA-Korcula-CROATIA-Vis-ORCADES studies (162 cases and 3162 controls), and meta-analyzed. AUCs of ROC-curves were calculated using 10-fold cross-validation for clinical characteristics, IgG glycans and their combination.

Results: After correction for extensive clinical covariates, 5 IgG glycans and 13 derived traits significantly associated with type 2 diabetes in meta-analysis (after Bonferroni correction). Adding IgG glycans to age and sex increased the AUC from 0.542 to 0.734. Adding them to the extensive model did not substantially improve the AUC. The AUC for IgG glycans alone was 0.729.

Conclusions: Several IgG glycans and traits firmly associate with type 2 diabetes, reflecting a pro-inflammatory and biologically-aged state. IgG glycans showed limited improvement of AUCs. However, IgG glycans showed good prediction alone, indicating they may capture information of combined covariates. The associations found may yield insights in type 2 diabetes pathophysiology.

General significance: This work shows that IgG glycomic changes have biomarker potential and may yield important insights into pathophysiology of complex public health diseases, illustrated here for the first time in type 2 diabetes.

Keywords: Ageing; Glycosylation; IgG; Inflammation; Prediction; Type 2 diabetes.