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Objective: N-glycosylation is a functional posttranslational modification of immunoglobulins (Igs). We hypothesized that specific IgG N-glycans are associated with incident type 2 diabetes and cardiovascular disease (CVD)., Research Design and Methods: We performed case-cohort studies within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (2,127 in the type 2 diabetes subcohort [741 incident cases]; 2,175 in the CVD subcohort [417 myocardial infarction and stroke cases]). Relative abundances of 24 IgG N-glycan peaks (IgG-GPs) were measured by ultraperformance liquid chromatography, and eight glycosylation traits were derived based on structural similarity. End point-associated IgG-GPs were preselected with fractional polynomials, and prospective associations were estimated in confounder-adjusted Cox models. Diabetes risk associations were validated in three independent studies., Results: 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 (843 total cases, 3,149 total non-cases, pooled estimate per SD increase 1.50 [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., Conclusions: Selected IgG N-glycans are associated with cardiometabolic risk beyond classic risk factors, including clinical biomarkers., (© 2022 by the American Diabetes Association.)

Objective: Plasma protein N -glycan profiling integrates information on enzymatic protein glycosylation, which is a highly controlled ubiquitous posttranslational modification. Here we investigate the ability of the plasma N -glycome to predict incidence of type 2 diabetes and cardiovascular diseases (CVDs; i.e., myocardial infarction and stroke)., Research Design and Methods: Based on the prospective European Prospective Investigation of Cancer (EPIC)-Potsdam cohort ( n = 27,548), we constructed case-cohorts including a random subsample of 2,500 participants and all physician-verified incident cases of type 2 diabetes ( n = 820; median follow-up time 6.5 years) and CVD ( n = 508; median follow-up time 8.2 years). Information on the relative abundance of 39 N -glycan groups in baseline plasma samples was generated by chromatographic profiling. We selected predictive N -glycans for type 2 diabetes and CVD separately, based on cross-validated machine learning, nonlinear model building, and construction of weighted prediction scores. This workflow for CVD was applied separately in men and women., Results: The N -glycan-based type 2 diabetes score was strongly predictive for diabetes risk in an internal validation cohort (weighted C-index 0.83, 95% CI 0.78-0.88), and this finding was externally validated in the Finland Cardiovascular Risk Study (FINRISK) cohort. N -glycans were moderately predictive for CVD incidence (weighted C-indices 0.66, 95% CI 0.60-0.72, for men; 0.64, 95% CI 0.55-0.73, for women). Information on the selected N -glycans improved the accuracy of established and clinically applied risk prediction scores for type 2 diabetes and CVD., Conclusions: Selected N -glycans improve type 2 diabetes and CVD prediction beyond established risk markers. Plasma protein N -glycan profiling may thus be useful for risk stratification in the context of precisely targeted primary prevention of cardiometabolic diseases., (© 2020 by the American Diabetes Association.)