Background: Immunoglobulin G (IgG) N-glycans have been shown to regulate the inflammatory response in the context of disease. In recent years, it has been found to be associated with several neurodegenerative disorders. In this study, we examined the relationship between IgG N-glycans and mild cognitive impairment (MCI) in a high-risk population for MCI, specifically patients with cerebrovascular stenosis.
Methods: In a case-control study, we investigated IgG N-glycans and cytokines in MCI and non-MCI patients in a population with cerebrovascular stenosis. A multifactorial logistic regression analysis was employed to investigate the potential association between IgG N-glycoprotein and MCI, with familial error rates being corrected for using the Benjamin-Hochberg method. To construct discriminatory models, logistic stepwise regression was employed and evaluated for their diagnostic efficacy.
Results: A statistically significant difference was found in eight of the IgG-GPs between the two groups. Three IgG-GPs were correlated with MCI, with an overall false discovery rate <0.05. Specifically, IgG-GP7 (non-sialylated glycan) was positively correlated with MCI, while IgG-GP14 (digalactosylated glycans) and IgG-GP18 (bis-sialylated glycan) were negatively correlated with MCI. The model constructed by combining IgG N-glycans (IgG-GP7, IgG-GP14, IgG-GP18) and cytokines (IL-1β, IL-10, BDNF and VEGF) demonstrated the highest diagnostic efficacy [AUC: 0.939, 95 % CI: (0.910-0.967)].
Discussion: In the present study, we observed that agalactosylation and no-sialylation play a role in the progression of MCI by influencing the pro-inflammatory impact of IgG. The integration of IgG N-glycan and cytokines into a discriminative model demonstrated strong diagnostic efficacy, suggesting its potential use as a screening tool for early prediction of MCI in patients with cerebrovascular stenosis.
Keywords: Glycosylation; High-risk group; Immunoglobulin G; Inflammation; Mild cognitive impairment.
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