Ischemic stroke is associated with the pro-inflammatory potential of N-glycosylated immunoglobulin G

Abstract

BackgroundGlycosylation significantly affects protein structure and function and thus participates in multiple physiologic and pathologic processes. Studies demonstrated that immunoglobulin G (IgG) N-glycosylation associates with the risk factors of ischemic stroke (IS), such as aging, obesity, dyslipidemia, type 2 diabetes, and hypertension.MethodsThe study aimed to investigate the association between IgG N-glycosylation and IS in a Chinese population. IgG glycome composition in patients with IS (n = 78) and cerebral arterial stenosis (CAS) (n = 75) and controls (n = 77) were analyzed by ultra-performance liquid chromatography.ResultsEleven initial glycans and 10 derived glycans in IgG glycome representing galactosylation, sialylation, and bisecting GlcNAc significantly differed between IS patients and CAS and healthy controls after controlling for gender, age, obesity, diabetes, hypertension, and dyslipidemia. Logistic regression models incorporating IgG glycan traits were able to distinguish IS from CAS (area under receiver–operator characteristic curves (AUC), 0.802; 95% confidence interval (CI), 0.732–0.872) and controls (AUC, 0.740; 95% CI, 0.661–0.819). The canonical correlation analysis indicated that initial N-glycan structures are significantly correlated with inflammation markers (r = 0.566, p < 0.001).ConclusionOur findings indicated that loss of galactose and sialic acid, as well as addition of bisecting GlcNAc, might involve in pro- or anti-inflammatory IgG functionality and further contribute to the pathogenesis of IS. IgG glycan profiles may be developed as clinical useful biomarkers for chronic disease in the future.Electronic supplementary materialThe online version of this article (10.1186/s12974-018-1161-1) contains supplementary material, which is available to authorized users.

Next-Generation (Glycomic) Biomarkers for Cardiometabolic Health: A Community-Based Study of Immunoglobulin G N-Glycans in a Chinese Han Population

“…Our previous studies have shown that the decreasing galactosylation and sialylation and the increasing bisecting GlcNAc are risk factors of many inflammatory and chronic diseases (Adua et al, 2017), including hypertension (Wang et al, 2016b), stroke (Liu et al, 2018b), T2DM (Lemmers et al, 2017), and dyslipidemia (Liu et al, 2018a), which are consistent with this study. The changes to IgG N-glycans, which were reported in metabolic syndrome, hypertriglyceridemic waist phenotype, and abdominal obesity in this study, might suggest that aberrant glycosylation of IgG is not disease specific, but a general phenomenon associated with reducing the anti-inflammatory function of circulating IgG.…”

“…N-glycans attach to the conserved asparagine 297 of both heavy chains in the fragment crystallizable region of IgG and act as a switch between proinflammatory and anti-inflammatory responses of IgG (Gornik et al, 2012;Jefferis, 2009). Changes to the IgG Nglycan profiles are involved in several inflammatory diseases, such as hypertension (Gao et al, 2017;Liu et al, 2018c;Wang et al, 2016b), stroke (Liu et al, 2018b), T2DM (Ge et al, 2018;Lemmers et al, 2017), Parkinson's disease , and rheumatoid arthritis (Sebastian et al, 2016).…”

Type 2 Diabetes Mellitus is Associated with the Immunoglobulin G N-Glycome through Putative Proinflammatory Mechanisms in an Australian Population

“…Unlike protein biosynthesis, glycans have no direct genetic templates. They are generated through intricate interactions among many genetic and environmental factors, and reflect the dynamic status of these factors (Adua et al, 2017;Hou et al, 2019;Liu et al, 2018b). These unique characteristics have received interest from the biomarker discovery and diagnostics research communities in relation to the possible role and potential use of N-glycans in complex diseases such as T2DM.…”

Glycomics for Type 2 Diabetes Biomarker Discovery: Promise of Immunoglobulin G Subclass-Specific Fragment Crystallizable N-glycosylation in the Uyghur Population

“…Dimension reduction based on the least absolute shrinkage and selection operator (LASSO) method was performed with R (version 2.7.2) to select IgG subclass-specific Fc N-glycans for making them comparable after logistic regression analysis ( Jones and Pewsey, 2009;Liu et al, 2018a). Stepwise (forward) logistic regression analysis was used for model selection in SPSS Statistics (version 25.0; IBM) ( Jennrich and Sampson, 1968).…”

“…The fivefold cross-validation, which is one typical choice of cross-validation and is recommended as a good compromise between the bias and the variance (Hastie et al, 2008), was performed to evaluate the performance of the discriminant model using R package ''boot'' (Liu et al, 2018a). Each split of data set in the cross-validation is 4/5 for training and 1/5 for testing.…”