Immunoglobulin G N-glycosylation signatures in incident type 2 diabetes and cardiovascular disease

Abstract

<p> </p> <p><strong>Objective:</strong> N-glycosylation is a functional posttranslational modification of immunoglobulins (Ig). We hypothesized that specific IgG N-glycans are associated with incident type 2 diabetes and cardiovascular disease (CVD).</p> <p><strong>Research Design and Methods: </strong>We performed case-cohort studies within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (type 2 diabetes: subcohort [N=2,127], incident cases [N=741]; CVD: subcohort [N=2,175], cases [myocardial infarction and stroke, N=417]). Relative abundances of 24 IgG N-glycan peaks (IgG-GPs) were measured by ultraperformance liquid chromatography, and 8 glycosylation traits were derived based on structural similarity. Endpoint-associated IgG-GPs were preselected with fractional polynomials, and prospective associations estimated in confounder-adjusted Cox models. Diabetes risk associations were validated in 3 independent studies.</p> <p><strong>Results:</strong> After adjustment for confounders and multiple testing correction, IgG-GP7, IgG-GP8, IgG-GP9, IgG-GP11, and IgG-GP19 were associated with type 2 diabetes risk. A score based on these IgG-GPs was associated with a higher diabetes risk in EPIC-Potsdam and independent validation studies (N cases=843, N total=3,149; pooled estimate per standard deviation [SD] increase: 1.50, 95% confidence interval [95%CI] 1.37-1.64). Associations of IgG-GPs with CVD risk differed between men and women. In women, IgG-GP9 was inversely associated with CVD risk (hazard ratio [HR] per SD 0.80, 95%CI 0.65-0.98). In men, a weighted score based on IgG-GP19 and IgG-GP23 was associated with higher CVD risk (HR per SD 1.47, 95%CI 1.20-1.80). In addition, several derived traits were associated with cardiometabolic disease incidence. </p> <p><strong>Conclusions:</strong> Selected IgG glycans are associated with cardiometabolic risk beyond classic risk factors, including clinical biomarkers.</p>