Longitudinal study reveals plasma glycans associations with prediabetes/type 2 diabetes in KORA study
Jiefei Niu1,2,3, Elke Rodriguez4,5,6, Tamara Štambuk7
1Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764, Neuherberg, Germany. jiefei.niu@helmholtz-munich.de.
Background:
Altered plasma N-glycosylation is increasingly recognized as a contributor to metabolic dysregulation. This study aimed to investigate the role of plasma N-glycans in glucose metabolism and the progression from normoglycemia to prediabetes and type 2 diabetes (T2D).
Methods:
We analyzed longitudinal data from 473 participants in the Cooperative Health Research in the Region of Augsburg (KORA) cohort over 7 years. N-glycan profiles were measured using hydrophilic interaction ultrahigh-performance liquid chromatography with fluorescence detection (HILIC-UHPLC-FLR). Glycan associations with incident prediabetes/T2D and related traits, such as body mass index (BMI), fasting glucose, homeostasis model assessment of insulin resistance (HOMA-IR) were evaluated using longitudinal models based on N-glycan measurements obtained at F4 and FF4. Classification performance at FF4 was assessed using machine learning models interpreted with SHapley Additive exPlanation (SHAP) values. Mendelian randomization (MR) and glycan quantitative trait loci (glycan-QTL) analyses were conducted to explore causality and genetic determinants.
Results:
During follow-up, 231 individuals progressed to prediabetes/T2D, while 242 remained normoglycemic. Nineteen glycans were associated with diabetes progression in the basic model; 12 remained significant after full adjustment. Glycans such as GP18 and GP32 were also linked to metabolic traits. A glycan-clinical model achieved high classification accuracy (AUC = 0.895). MR supported causal roles for GP18, GP19, and S1. Glycan-QTL analysis revealed SNPs and genes (FUT8, ST3GAL4) are associated with key glycans.
Conclusions:
Plasma N-glycans are diagnostic of early glycemic deterioration and supported by genetic and causal evidence, highlighting their potential as biomarkers for diabetes risk stratification.
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