The association between plasma IgG N-glycosylation and viral encephalitis in children: a hospital-based case-control...

Viral encephalitis (VE) is an acute inflammatory disease caused by viral infection. Children are at a significantly higher risk of developing VE than adults. Immunoglobulin G (IgG) N-glycosylation plays a key role in regulating the balance between anti-inflammatory and pro-inflammatory responses. This study aimed to investigate the profile of IgG N-glycosylation among children with VE.

This case-control study included 117 children with VE and 117 healthy controls. Plasma IgG N-glycans were detected using hydrophilic interaction liquid chromatography with the ultra-high-performance liquid chromatography (HILIC-UPLC). An enzyme-linked immunosorbent assay (ELISA) kit was applied to detect inflammatory cytokines. Canonical correlation analysis (CCA) was performed to investigate the correlation between IgG N-glycans and inflammatory cytokines. The Least Absolute Shrinkage and Selection Operator (LASSO) and machine learning algorithms were used to identify the significant glycans.

Among 24 initially detected glycans, 14 were significantly higher and 3 lower in children with VE compared to the healthy controls (P < 0.05). Moreover, children with VE showed lower levels of fucosylation (P < 0.001) and agalactosylation (G0) (P < 0.001), whereas higher levels of bisecting N-acetylglucosamine (GlcNAc) (P = 0.026), sialylation (P < 0.001), and monogalactosylation (G1) (P < 0.001). Notably, the level of bisecting GlcNAc was significantly higher in VE children who had a shorter hospital stay compared to those with a longer hospital stay (P = 0.034). The levels of interferon-gamma (IFN-γ), interleukin-2 (IL-2), IL-6, high-sensitivity C-reactive protein (hs-CRP), and tumor necrosis factor-α (TNF-α) were significantly higher in children with VE than in the healthy controls (P < 0.001). IgG N-glycans composition was strongly correlated with inflammatory cytokines (r = 0.849). GP1, GP3, GP6, GP7, GP9, GP16, GP21, GP22, GP23, and GP24 were identified by Boruta algorithms to develop a glycan-based diagnostic model for VE. The areas under the receiver operating characteristic curve (AUCs) were 0.987 for the training set and 0.998 for the validation set.

IgG N-glycosylation may contribute to the pathogenesis of VE. IgG N-glycans may act as potential biomarkers for monitoring VE in high-risk children.