Wei Wang, Edith Cowan UniversityFollow
Youxin Wang, Edith Cowan UniversityFollow
NPJ Aging and Mechanisms of Disease
School of Medical and Health Sciences
National Key R&D Program of China European Commission Horizon 2020 National Natural Science Foundation of China China-Australian Collaborative Grant
Immunoglobulin G (IgG) functionality can drastically change from anti- to proinflammatory by alterations in the IgG N-glycan patterns. Our previous studies have demonstrated that IgG N-glycans associated with the risk factors of dementia, such as aging, dyslipidemia, type 2 diabetes mellitus, hypertension, and ischemic stroke. Therefore, the aim is to investigate whether the effects of IgG N-glycan profiles on dementia exists in a Chinese Han population. A case–control study, including 81 patients with dementia, 81 age- and gender-matched controls with normal cognitive functioning (NC) and 108 non-matched controls with mild cognitive impairment (MCI) was performed. Plasma IgG N-glycans were separated by ultra-performance liquid chromatography. Fourteen glycan peaks reflecting decreased of sialylation and core fucosylation, and increased bisecting N-acetylglucosamine (GlcNAc) N-glycan structures were of statistically significant differences between dementia and NC groups after controlling for confounders (p < 0.05; q < 0.05). Similarly, the differences for these 14 initial glycans were statistically significant between AD and NC groups after adjusting for the effects of confounders (p < 0.05; q < 0.05). The area under the receiver operating curve (AUC) value of the model consisting of GP8, GP9, and GP14 was determined to distinguish dementia from NC group as 0.876 [95% confidence interval (CI): 0.815–0.923] and distinguish AD from NC group as 0.887 (95% CI: 0.819–0.936). Patients with dementia were of an elevated proinflammatory activity via the significant changes of IgG glycome. Therefore, IgG N-glycans might contribute to be potential novel biomarkers for the neurodegenerative process risk assessment of dementia.
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Multidisciplinary biological approaches to personalised disease diagnosis, prognosis and management