Immunoglobulin G N-glycosylation Research Articles

Automated high throughput IgG N-glycosylation sample preparation method development on the Tecan Freedom EVO platform.

Glycomics, focusing on the role of glycans in biological processes, particularly their influence on the folding, stability and receptor interactions of glycoconjugates like antibodies, is vital for our understanding of biology. Changes in immunoglobulin G (IgG) N-glycosylation have been associated with various physiological and pathophysiological conditions. Nevertheless, time-consuming manual sample preparation is one of the limitations in the glycomics diagnostic implementation. The study aimed to develop an automated method for sample preparation on the Tecan Freedom Evo 200 platform and compare its efficiency and precision with the manual counterpart. The initial method development included 32 pooled blood plasma technical replicates. An additional 24 pooled samples were used in the method comparison along with 78 random duplicates of plasma samples collected from 10,001 Dalmatians biobank to compare the manual and automated methods. The development resulted in a new automated method. For the automated method, glycan peaks comprising 91% of the total sample glycan showed a variation of less than 5% while 92% of the total sample showed a variation of less than 5% for the manual method. The results of the Passing-Bablok regression indicated no differences between the automated and manual methods for 12 glycan peaks (GPs). However, for 8 GPs systematic difference was present, while both systematic and proportional differences were present for four GPs. The developed automated sample preparation method for IgG glycan analysis reduced exposure to hazardous chemicals and offered a simplified workflow. Despite slight differences between the methods, the new automated method showed high precision and proved to be highly comparable to its manual counterpart.

The Causality between Human Immunoglobulin G (IgG) N-Glycosylation and Aging: A Mendelian Randomization Study.

Immunoglobulin G (IgG) N-glycosylation is considered a potential biomarker for aging and various pathological conditions. However, whether these changes in IgG N-glycosylation are a consequence or a contributor to the aging process remains unclear. This study aims to investigate the causality between IgG N-glycosylation and aging using Mendelian randomization (MR) analysis. We utilized genetic variants associated with IgG N-glycosylation traits, the frailty index (FI), and leukocyte telomere length (LTL) from a previous genome-wide association study (GWAS) on individuals of European ancestry. Two-sample and multivariable MR analyses were conducted, employing the inverse-variance weighted (IVW) method. Sensitivity analyses were performed to assess potential confounding factors. Using the IVW method, we found suggestive evidence of a causal association between GP14 and FI (β 0.026, 95% CI 0.003 to 0.050, p = 0.027) and LTL (β -0.020, 95% CI -0.037 to -0.002, p = 0.029) in the two-sample MR analysis. In the multivariable MR analysis, suggestive evidence was found for GP23 and FI (β -0.119, 95% CI -0.219 to -0.019, p = 0.019) and GP2 and LTL (β 0.140, 95% CI 0.020 to 0.260, p = 0.023). In conclusion, our results supported a potentially causal effect of lower GP23 levels on an advanced aging state. Additional verification is required to further substantiate the causal relationship between glycosylation and aging.

An integrated method for IgG N-glycans enrichment and analysis: Understanding the role of IgG glycosylation in diabetic foot ulcer

Diabetic foot ulcer (DFU) is the most common and serious complication of diabetes, and its incidence, disability, and mortality rates are increasing worldwide. The pathogenesis of DFU is associated with dysregulated inflammation mediated by abnormal immunoglobulin G (IgG) glycosylation. In this study, we developed a comprehensive method for IgG N-linked glycosylation in the serum of DFU patients. Through analysis, we identified 31 IgG1 glycans, 32 IgG2 glycans, and 30 IgG4 glycans in the DFU serum. Furthermore, 13 IgG1 glycans, 12 IgG2 glycans, and 5 IgG4 glycans in the DFU groups were found to be significantly different from those of the control groups (p < 0.05). Of these, compared with the control group, one glycan was unique to DFU patients, and seven glycans were not detected in the DFU group. In terms of glycan characteristics, we observed a substantial decrease in galactosylation, sialylation and bisecting GlcNAcylation, and a significant increase in agalactosylation. Abnormal IgG N-glycosylation modifications were significantly associated with the chronic inflammation that is characteristic of DFU. Further, this is the first comprehensive analysis of subclass-specific IgG N-glycosylation in DFU patients, which not only fills the gap of DFU in terms of the pathological mechanisms related to IgG glycosylation but also may provide valuable clues for the immunotherapeutic pathway of DFU.

Association between immunoglobulin G N-glycosylation and lupus nephritis in female patients with systemic lupus erythematosus: a case-control study.

Lupus nephritis (LN) is a crucial complication of systemic lupus erythematosus (SLE) and has important clinical implications in guiding treatment. N-glycosylation of immunoglobulin G (IgG) plays a key role in the development of SLE by affecting the balance of anti-inflammatory and proinflammatory responses. This study aimed to evaluate the performance of IgG N-glycosylation for diagnosing LN in a sample of female SLE patients. This case-control study recruited 188 women with SLE, including 94 patients with LN and 94 age-matched patients without LN. The profiles of plasma IgG N-glycans were detected by hydrophilic interaction chromatography with ultra-performance liquid chromatography (HILIC-UPLC). A multivariate logistic regression model was used to explore the associations between IgG N-glycans and LN. A diagnostic model was developed using the significant glycans as well as demographic factors. The performance of IgG N-glycans in the diagnosis of LN was evaluated by receiver operating characteristic (ROC) curve analysis, and the area under the curve (AUC) and its 95% confidence interval (CI) were calculated. There were significant differences in 9 initial glycans (GP2, GP4, GP6, GP8, GP10, GP14, GP16, GP18 and GP23) between women with SLE with and without LN (P < 0.05). The levels of sialylated, galactosylated and fucosylated glycans were significantly lower in the LN patients than in the control group, while bisected N-acetylglucosamine (GlcNAc) glycans were increased in LN patients (P < 0.05). GP8, GP10, GP18, and anemia were included in our diagnostic model, which performed well in differentiating female SLE patients with LN from those without LN (AUC = 0.792, 95% CI: 0.727 to 0.858). Our findings indicate that decreased sialylation, galactosylation, and core fucosylation and increased bisecting GlcNAc might play a role in the development of LN by upregulating the proinflammatory response of IgG. IgG N-glycans can serve as potential biomarkers to differentiate individuals with LN among SLE patients.

Divergent Enzymatic Assembly of a Comprehensive 64-Membered IgG N-Glycan Library for Functional Glycomics.

N-Glycosylation, a main post-translational modification of Immunoglobulin G (IgG), plays a significant role in modulating the immune functions of IgG. However, the precise function elucidation of IgG N-glycosylation remains impeded due to the obstacles in obtaining comprehensive and well-defined N-glycans. Here, an easy-to-implement divergent approach is described to synthesize a 64-membered IgG N-glycan library covering all possible biantennary and bisected N-glycans by reprogramming biosynthetic assembly lines based on the inherent branch selectivity and substrate specificity of enzymes. The unique binding specificities of 64 N-glycans with different proteins are deciphered by glycan microarray technology. This unprecedented collection of synthetic IgG N-glycans can serve as standards for N-glycan structure identification in complex biological samples and the microarray data enrich N-glycan glycomics to facilitate biomedical applications.

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study.

The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID-19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial. We conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran's Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results. We found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92-0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy. Our study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels.

Novel Insight into the Etiology of Haff Disease by Mapping the N-Glycome with Orthogonal Mass Spectrometry

Consumption of boiled crayfish may lead to Haff disease (HD), which is considered to result from an unidentified toxin, although the etiology is still obscure. Profiling of the N -glycome in HD would assist in deciphering the underlying molecular mechanism of the disease, whereas HD-associated glycosylation has never been explored. Herein, we enrolled 90 serum samples with HD patients and healthy controls from the Wuhan Center for Disease Control & Prevention between 2019 and 2020. N -glycome profiles of both serum and serum-derived immunoglobulin G (IgG) in HD were characterized by means of high-throughput-based orthogonal mass spectrometry. It was observed that HD is associated with an increase in the core fucosylation and mono-galactosylation of total serum glycoproteins. The serum level of IgG was found to serve as a good indicator for HD patients. In addition, differential galactosylation and sialylation of IgG were strongly correlated with HD. It was notable that the changes in the galactosylation and sialylation of IgG1 and IgG2 were subclass specific. Interestingly, altered sialylation and galactosylation of IgG2 or IgG3/4 strongly correlated with clinical markers for HD. Our study reveals the association of differential IgG N-glycosylation with HD, providing new insight into the etiology of this rare disease.

Unravelling the genetic causality of immunoglobulin G N-glycans in ischemic stroke.

Evidence suggests that immunoglobulin G (IgG) N-glycosylation is associated with ischemic stroke (IS). However, the causality of IgG N-glycosylation for IS remains unknown. Two-sample Mendelian randomization (MR) analyses were performed to investigate the potential causal effects of genetically determined IgG N-glycans on IS using publicly available summarized genetic data from East Asian and European populations. Genetic instruments were used as proxies for IgG N-glycan traits. IgG N-glycans were analysed using ultra-performance liquid chromatography. Four complementary MR methods were performed, including the inverse variance weighted method (IVW), MR‒Egger, weighted median and penalized weighted median. Furthermore, to further test the robustness of the results, MR based on Bayesian model averaging (MR-BMA) was then applied to select and prioritize IgG N-glycan traits as risk factors for IS. After correcting for multiple testing, in two-sample MR analyses, genetically predicted IgG N-glycans were unrelated to IS in both East Asian and European populations, and the results remained consistent and robust in the sensitivity analysis. Moreover, MR-BMA also showed consistent results in both East Asian and European populations. Contrary to observational studies, the study did not provide enough genetic evidence to support the causal associations of genetically predicted IgG N-glycan traits and IS, suggesting that N-glycosylation of IgG might not directly involve in the pathogenesis of IS.

Physical Exercise Induces Significant Changes in Immunoglobulin G N-Glycan Composition in a Previously Inactive, Overweight Population.

Regular exercise improves health, modulating the immune system and impacting inflammatory status. Immunoglobulin G (IgG) N-glycosylation reflects changes in inflammatory status; thus, we investigated the impact of regular exercise on overall inflammatory status by monitoring IgG N-glycosylation in a previously inactive, middle-aged, overweight and obese population (50.30 ± 9.23 years, BMI 30.57 ± 4.81). Study participants (N = 397) underwent one of three different exercise programs lasting three months with blood samples collected at baseline and at the end of intervention. After chromatographically profiling IgG N-glycans, linear mixed models with age and sex adjustment were used to investigate exercise effects on IgG glycosylation. Exercise intervention induced significant changes in IgG N-glycome composition. We observed an increase in agalactosylated, monogalctosylated, asialylated and core-fucosylated N-glycans (padj = 1.00 × 10-4, 2.41 × 10-25, 1.51 × 10-21 and 3.38 × 10-30, respectively) and a decrease in digalactosylated, mono- and di-sialylated N-glycans (padj = 4.93 × 10-12, 7.61 × 10-9 and 1.09 × 10-28, respectively). We also observed a significant increase in GP9 (glycan structure FA2[3]G1, β = 0.126, padj = 2.05 × 10-16), previously reported to have a protective cardiovascular role in women, highlighting the importance of regular exercise for cardiovascular health. Other alterations in IgG N-glycosylation reflect an increased pro-inflammatory IgG potential, expected in a previously inactive and overweight population, where metabolic remodeling is in the early stages due to exercise introduction.

Associations between plasma protein, IgG and IgA N-glycosylation and metabolic health markers in pregnancy and gestational diabetes.

Monitoring human circulating N-glycome could provide valuable insight into an individual's metabolic status. Therefore, we examined if aberrant carbohydrate metabolism in gestational diabetes mellitus (GDM) associates with alterations in plasma protein, immunoglobulin G (IgG) and immunoglobulin A (IgA) N-glycosylation. Plasma protein, IgG and IgA N-glycans were enzymatically released, purified and chromatographically profiled in 48 pregnant women with normal glucose tolerance and 41 pregnant women with GDM, all sampled at 24-28 weeks of gestation. Linear mixed models adjusting for age and multiple testing (FDR<0.05) were used to investigate the associations between glycosylation features, metabolic markers and GDM status. Fasting insulin exhibited significant associations to numerous glycan traits, including plasma protein galactosylation, sialylation, branching, core fucosylation and bisection, to IgG core fucosylated, bisected (FA2B) and afucosylated disialylated (A2G2S2) glycan and to IgA trisialylated triantennary (A3G3S3) glycan (padj range: 4.37x10-05-4.94x10-02). Insulin resistance markers HOMA2-IR and HOMA2-%B were mostly associated to the same glycan structures as fasting insulin. Both markers showed positive association with high-branched plasma glycans (padj = 1.12x10-02 and 2.03x10-03) and negative association with low-branched plasma glycans (padj = 1.21x10-02 and 2.05x10-03). Additionally, HOMA2-%B index was significantly correlated with glycosylation features describing IgG sialylation. Multiple plasma protein IgG and IgA glycans showed significant associations with total cholesterol and triglyceride levels. None of the tested glycan traits showed a significant difference between GDM and normoglycemic pregnancies. Markers of glucose homeostasis and lipid metabolism in pregnancy show extensive associations to various N-glycosylation features. However, plasma protein, IgG and IgA N-glycans were not able to differentiate pregnant women with and without GDM, possibly due to numerous physiological changes accompanying pregnancy, which confound the impact of GDM on protein glycosylation.

Storage stability and HILIC-UHPLC-FLR analysis of immunoglobulin G N-glycome from saliva.

Immunoglobulin G (IgG) is the most abundant antibody in the blood and plays a critical role in host immune defense against infectious agents. Glycosylation is known to modulate the effector functions of IgG and is involved in disease development and progression. It is no surprise that the N-glycome of IgG from plasma has already been proposed as a biomarker for various physiological and pathological conditions. However, because saliva is easy to collect, it could be useful for exploring the functional role of salivary IgG N-glycosylation and its potential as a diagnostic biomarker. Therefore, in this study, we described a method for N-glycome analysis of IgG from saliva samples. Salivary IgG N-glycans were analyzed by ultra-high-performance liquid chromatography based onhydrophilic interactions with fluorescence detection (HILIC-UHPLC-FLR). In addition, we compared IgG N-glycan profiles from saliva with those from plasma, assessed the stability of salivary IgG N-glycan profiles under different storage conditions, and evaluated the effects of using a saliva preservation medium. This study provides an ultrasensitive UHPLC method for the analysis of total IgG N-glycosylation from saliva, gives insight into storage stability of salivary IgG, and highlights its (dis)advantages for further biomarker-related research.

Comparative analysis of transferrin and IgG N-glycosylation in two human populations

Human plasma transferrin (Tf) N-glycosylation has been mostly studied as a marker for congenital disorders of glycosylation, alcohol abuse, and hepatocellular carcinoma. However, inter-individual variability of Tf N-glycosylation is not known, mainly due to technical limitations of Tf isolation in large-scale studies. Here, we present a highly specific robust high-throughput approach for Tf purification from human blood plasma and detailed characterization of Tf N-glycosylation on the level of released glycans by ultra-high-performance liquid chromatography based on hydrophilic interactions and fluorescence detection (HILIC-UHPLC-FLD), exoglycosidase sequencing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We perform a large-scale comparative study of Tf and immunoglobulin G (IgG) N-glycosylation analysis in two human populations and demonstrate that Tf N-glycosylation is associated with age and sex, along with multiple biochemical and physiological traits. Observed association patterns differ compared to the IgG N-glycome corroborating tissue-specific N-glycosylation and specific N-glycans’ role in their distinct physiological functions.

Association of IgG N-glycomics with prevalent and incident type 2 diabetes mellitus from the paradigm of predictive, preventive, and personalized medicine standpoint.

Type 2 diabetes mellitus (T2DM), a major metabolic disorder, is expanding at a rapidly rising worldwide prevalence and has emerged as one of the most common chronic diseases. Suboptimal health status (SHS) is considered a reversible intermediate state between health and diagnosable disease. We hypothesized that the time frame between the onset of SHS and the clinical manifestation of T2DM is the operational area for the application of reliable risk assessment tools, such as immunoglobulin G (IgG) N-glycans. From the viewpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS and dynamic monitoring by glycan biomarkers could provide a window of opportunity for targeted prevention and personalized treatment of T2DM. Case-control and nested case-control studies were performed and consisted of 138 and 308 participants, respectively. The IgG N-glycan profiles of all plasma samples were detected by an ultra-performance liquid chromatography instrument. After adjustment for confounders, 22, five, and three IgG N-glycan traits were significantly associated with T2DM in the case-control setting, baseline SHS, and baseline optimal health participants from the nested case-control setting, respectively. Adding the IgG N-glycans to the clinical trait models, the average area under the receiver operating characteristic curves (AUCs) of the combined models based on repeated 400 times fivefold cross-validation differentiating T2DM from healthy individuals were 0.807 in the case-control setting and 0.563, 0.645, and 0.604 in the pooled samples, baseline SHS, and baseline optimal health samples of nested case-control setting, respectively, which presented moderate discriminative ability and were generally better than models with either glycans or clinical features alone. This study comprehensively illustrated that the observed altered IgG N-glycosylation, i.e., decreased galactosylation and fucosylation/sialylation without bisecting GlcNAc, as well as increased galactosylation and fucosylation/sialylation with bisecting GlcNAc, reflects a pro-inflammatory state of T2DM. SHS is an important window period of early intervention for individuals at risk for T2DM; glycomic biosignatures as dynamic biomarkers have the ability to identify populations at risk for T2DM early, and the combination of evidence could provide suggestive ideas and valuable insight for the PPPM of T2DM. The online version contains supplementary material available at 10.1007/s13167-022-00311-3.

Assessment of the Causal Effect of IgG N-Glycosylation Level on Risk of Dementia: A 2-Sample Mendelian Randomization Study.

Previous prospective studies highlighted aberrant immunoglobulin G (IgG) N-glycosylation as a risk factor for dementia [such as Alzheimer's disease (AD) and vascular dementia (VaD)]. It is unclear whether this association is causal or explained by confounding or reverse causation. The aim is to examine the association of genetically predicted IgG N-glycosylation with dementia using 2-sample Mendelian randomization (MR). Independent genetic variants for IgG N-glycosylation traits were selected as instrument variables from published genome-wide association studies (GWAS) among individuals of European ancestry. We extracted their corresponding summary statistics from large-scale clinically diagnosed AD GWAS dataset and FinnGen biobank VaD GWAS dataset. The inverse variance weighted (IVW) was performed to calculate the effect estimates. Meanwhile, multiple sensitivity analyses were used to assess horizontal pleiotropy and outliers. There were no associations of genetically predicted IgG N-glycosylation traits with the risk of AD and VaD using the IVW method (all Bonferroni corrected p > 0.0013). These estimates of four additional sensitivity analyses methods were consistent with the IVW estimates in terms of direction and magnitude. Additionally, the MR-PRESSO global test and the intercept of MR-Egger regression indicated no evidence of horizontal pleiotropy. Meanwhile, the heterogeneity test showed no significant heterogeneity using the Cochran Q statistic. The leave-one-out sensitivity analyses also did not detect any significant change. Our MR study did not support evidence for the hypothesis that IgG N-glycosylation level may be causally associated with the risk of dementia.

IgG N-Glycosylation from Patients with Pemphigus Treated with Rituximab.

Pemphigus is a life-threatening auto-immune blistering disease of the skin and mucous membrane that is caused by the production of auto-antibodies (auto-Abs) directed against adhesion proteins: desmoglein 1 and 3. We demonstrated in the “Ritux3” trial, the high efficacy of rituximab, an anti-CD20 recombinant monoclonal antibody, as the first-line treatment for pemphigus. However, 25% of patients relapsed during the six-month period after rituximab treatment. These early relapses were associated with a lower decrease in anti-desmoglein auto-Abs after the initial cycle of rituximab. The N-glycosylation of immunoglobulin-G (IgG) can affect their affinity for Fc receptors and their serum half-life. We hypothesized that the extended half-life of Abs could be related to modifications of IgG N-glycans. The IgG N-glycome from pemphigus patients and its evolution under rituximab treatment were analyzed. Pemphigus patients presented a different IgG N-glycome than healthy donors, with less galactosylated, sialylated N-glycans, as well as a lower level of N-glycans bearing an additional N-acetylglucosamine. IgG N-glycome from patients who achieved clinical remission was not different to the one observed at baseline. Moreover, our study did not identify the N-glycans profile as discriminating between relapsing and non-relapsing patients. We report that pemphigus patients present a specific IgG N-glycome. The changes observed in these patients could be a biomarker of autoimmunity susceptibility rather than a sign of inflammation.

A Preliminary Study on Change of Serum Immunoglobulin G Glycosylation in Patients With Migraine.

Background and ObjectiveMigraine is a common neurological disease, but its pathogenesis is still unclear. Previous studies suggested that migraine was related to immunoglobulin G (IgG). We intended to analyze the immune characteristics of migraine from the perspective of IgG glycosylation and provide theoretical assistance for exploring its pathogenesis.MethodsThe differences in the serum level of IgG glycosylation and glycopeptides between patients with episodic migraine and healthy controls were analyzed by applying the poly(glycerol methacrylate)@chitosan (PGMA@CS) nanomaterial in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We constructed a binary classification model with a feedforward neural network using PyTorch 1.6.0 in Python 3.8.3 to classify the episodic migraine and healthy control groups.ResultsTwenty patients with migraine and 20 healthy controls were enrolled and the blood samples and clinical information were collected. Forty-nine IgG N-glycopeptides were detected in the serum of the subjects. The serum level of N-glycopeptide IgG1 G0-NF (p = 0.012) was increased in patients with migraine. The serum level of N-glycopeptide IgG3/4 G2FS (p = 0.041) was decreased in patients with migraine with family history of headache. It was found that the serum level of the IgG1 G1 (p = 0.004) and IgG2 G0 (p = 0.045) was increased in patients with migraine with aura, while the serum level of IgG2 G0N (p = 0.043) in patients with migraine with aura was significantly lower than that in patients with migraine without aura. In addition, a linear feedforward neural network (FFNN) was used to construct a binary classification model by detected IgG N-glycopeptides. The area under the curve (AUC) value of the binary classification model, which was constructed with 7 IgG N-glycopeptides, was 0.857, suggesting a good prediction performance. Among these IgG N-glycopeptides that were constructed the model, IgG1 G0-NF was overlapped with the differential IgG N-glycopeptide between patients with migraine and healthy controls detected with MALDI-TOF-MS.ConclusionOur results indicated that the serum level of N-glycopeptides IgG1 G0-NF might be one of the important biomarkers for the diagnosis of migraine. To the best of our knowledge, this is the first study about the changes of IgG N-glycosylation in patients with migraine by the method of MALDI-TOF-MS. The results indicated a relationship between the migraine and immune response.

Coronavirus Disease 2019-Related Alterations of Total and Anti-Spike IgG Glycosylation in Relation to Age and Anti-Spike IgG Titer.

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been affecting the world since January 2020 and has caused millions of deaths. To gain a better insight into molecular changes underlying the COVID-19 disease, we investigated here the N-glycosylation of three immunoglobulin G (IgG) fractions isolated from plasma of 35 severe COVID-19 patients, namely total IgG1, total IgG2, and anti-Spike IgG, by means of MALDI-TOF-MS. All analyses were performed at the glycopeptide level to assure subclass- and site-specific information. For each COVID-19 patient, the analyses included three blood withdrawals at different time-points of hospitalization, which allowed profiling longitudinal alterations in IgG glycosylation. The COVID-19 patients presented altered IgG N-glycosylation profiles in all investigated IgG fractions. The most pronounced COVID-19-related changes were observed in the glycosylation profiles of antigen-specific anti-Spike IgG1. Anti-Spike IgG1 fucosylation and galactosylation showed the strongest variation during the disease course, with the difference in anti-Spike IgG1 fucosylation being significantly correlated with patients’ age. Decreases in anti-Spike IgG1 galactosylation and sialylation in the course of the disease were found to be significantly correlated with the difference in anti-Spike IgG plasma concentration. The present findings suggest that patients’ age and anti-S IgG abundance might influence IgG N-glycosylation alterations occurring in COVID-19.

Changes of IgG N-Glycosylation in Thyroid Autoimmunity: The Modulatory Effect of Methimazole in Graves' Disease and the Association With the Severity of Inflammation in Hashimoto's Thyroiditis.

The N-glycome of immunoglobulin G (IgG), the most abundant glycoprotein in human blood serum, reflects pathological conditions of autoimmunity and is sensitive to medicines applied in disease therapy. Due to the high sensitivity of N-glycosylation, the IgG N-glycan profile may serve as an indicator of an ongoing inflammatory process. The IgG structure and its effector functions are strongly dependent on the composition of N-glycans attached to the Fc fragment, and the binding of antigens is regulated by Fab sugar moieties. Because of the crucial role of N-glycans in IgG function, remodeling of its N-oligosaccharides can induce pathological changes that ultimately contribute to the development of autoimmunity; restoration of their physiological structure is critical to the reduction of disease symptoms. Our recently published data have shown that the pathology of autoimmune thyroid diseases (AITDs), including Hashimoto’s thyroiditis (HT) and Graves’ disease (GD), is accompanied by alterations of the composition of IgG N-glycans. The present study is a more in-depth investigation of IgG glycosylation in both AITDs, designed to determine the relationship between the severity of thyroid inflammation and IgG N-glycan structures in HT, and to assess the impact of immunosuppressive therapy on the N-glycan profile in GD patients. The study material consisted of human serum samples collected from donors with elevated anti-thyroglobulin (Tg) and/or anti-thyroperoxidase (TPO) IgGs without symptoms of hypothyroidism (n=68), HT patients characterized by high autoantibody titers and advanced destruction of the thyroid gland (n=113), GD patients with up-regulated IgG against thyroid-stimulating hormone receptor (TSHR) before (n=62) and after (n=47) stabilization of TSH level as a result of methimazole therapy (study groups), and healthy donors (control group, n=90). IgG was isolated from blood serum using protein G affinity chromatography. N-glycans were released from IgG by PNGase F digestion and analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) after 2-aminobenzamide (2-AB) labeling. UPLC-MS chromatograms were integrated into 25 peaks (GP) in the Waters UNIFI Scientific Information System, and N-glycans were assigned based on the glucose unit values and mass-to-charge ratios (m/z) of the detected ions. The Kruskal-Wallis non-parametric test was used to determine the statistical significance of the results (p<0.05). The obtained results suggest that modifications of IgG sialylation, galactosylation and core-fucosylation are associated with the severity of HT symptoms. Methimazole therapy implemented in GD patients affected the IgG N-glycan profile; as a result, the content of the sialylated and galactosylated oligosaccharides with core fucose differed after treatment. Our results suggest that N-glycosylation of IgG undergoes dynamic changes during the intensification of thyroiditis in HT, and that in GD autoimmunity it is affected significantly by immunosuppressive therapy.

Association Between Immunoglobulin G N-glycosylation and Vascular Cognitive Impairment in a Sample With Atherosclerosis: A Case-Control Study.

BackgroundAtherosclerosis is considered a crucial component in the pathogenesis of decreased cognitive function, as occurs in vascular cognitive impairment (VCI). Inflammation and the immune response play a significant role in the development of many chronic diseases. Immunoglobulin G (IgG) N-glycosylation has been implicated in the development of a variety of diseases by affecting the anti-inflammatory and proinflammatory responses of IgG. This study aimed to investigate the association between IgG N-glycosylation and VCI in a sample of patients with atherosclerosis through a case-control study.MethodWe recruited a total of 330 patients with atherosclerosis to participate in this case-control study, including 165 VCI patients and 165 sex- and age-matched participants with normal cognitive function. The plasma IgG N-glycans of participants were separated by ultrahigh-performance liquid chromatography. An enzyme-linked immunosorbent assay (ELISA) kit was used to determine the corresponding serum inflammatory factors. Atherosclerosis was diagnosed by carotid ultrasound, and the diagnosis of VCI was based on the “Guidelines for the Diagnosis and Treatment of Vascular Cognitive Impairment in China (2019)”. A multivariate logistic regression model was used to explore the association between IgG N-glycans and VCI. We also analyzed the relationship between IgG N-glycans and the inflammatory state of VCI through canonical correlation analysis (CCA).ResultsThrough the multivariate logistic regression analysis, 8 glycans and 13 derived traits reflecting decreased sialylation and galactosylation and increased bisecting GlcNAc significantly differed between the case and control groups after adjusting for confounding factors (P < 0.05, q < 0.05). Similarly, the differences in TNF-α, IL-6, and IL-10 were statistically significant between the case and control groups after adjusting for the effects of confounding factors (P < 0.05, q < 0.05). The CCA results showed that VCI-related initial N-glycans were significantly correlated with VCI-related inflammatory factors (r = 0.272, P = 0.004). The combined AUC value (AUCcombined = 0.885) of 7 initial glycans and inflammatory factors was higher than their respective values (AUCinitial glycans = 0.818, AUCinflammatory factors = 0.773).ConclusionThe findings indicate that decreased sialylation and galactosylation and increased bisecting GlcNAc reflected by IgG N-glycans might affect the occurrence of VCI in patients with atherosclerosis though promoting the proinflammatory function of IgG. IgG N-glycans may serve as potential biomarkers to distinguish VCI in individuals with atherosclerosis.

Investigation of the causal relationships between human IgG N-glycosylation and 12 common diseases associated with changes in the IgG N-glycome.

Changes in the N-glycosylation of immunoglobulin G (IgG) are often observed in pathological states, such as autoimmune, inflammatory, neurodegenerative, cardiovascular diseases and some types of cancer. However, in most cases, it is not clear if the disease onset causes these changes, or if the changes in IgG N-glycosylation are among the risk factors for the diseases. The aim of this study was to investigate the casual relationships between IgG N-glycosylation traits and 12 diseases, in which the alterations of IgG N-glycome were previously reported, using two sample Mendelian randomization (MR) approach. We have performed two sample MR using publicly available summary statistics of genome-wide association studies of IgG N-glycosylation and disease risks. Our results indicate positive causal effect of systemic lupus erythematosus (SLE) on the abundance of N-glycans with bisecting N-acetylglucosamine in the total IgG N-glycome. Therefore, we suggest regarding this IgG glycosylation trait as a biomarker of SLE. We also emphasize the need for more powerful GWAS studies of IgG N-glycosylation to further elucidate the causal effect of IgG N-glycome on the diseases.