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Fucosylation on IgG in COVID-19 patients and the healthy controls. B, bisecting N-acetylglucosamine (GlcNAc); F, fucose; G, galactose; GP, glycan peak; S, Sialic acid; ↑, the glycan in COVID-19 group is significantly higher than that in the controls; ↓, the glycan in COVID-19 group is significantly lower than that in the controls.
Source publication
Coronavirus disease 2019 (COVID-19) remains a major health challenge globally. Previous studies have suggested that changes in the glycosylation of IgG are closely associated with the severity of COVID-19. This study aimed to compare the profiles of IgG N-glycome between COVID-19 patients and healthy controls. A case-control study was conducted, in...
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Background
Epilepsy is a chronic brain disease that recurs during childhood, and more than half of adult epilepsy originates from childhood. Studies suggested that immunoglobulin G (IgG) glycosylation are closely related to neurological diseases. Here we analyzed the characteristics of the immunoglobulin glycosylation profile of children with epile...
Citations
... Recent studies have also suggested that sialylation exerts its anti-inflammatory effects through CDC mediation (Quast et al., 2015). Moreover, acute immune responses result in an increase in sialylation (Hou et al., 2021). Furthermore, another study demonstrated that sialylation has a minimal effect on the ADCC pathway in the absence of fucosylation (Li et al., 2017), Associations of the normalized initial glycans and HIE as determined by multivariate logistic regression analyses. ...
Introduction
Hypoxic-ischemic encephalopathy (HIE) is one of severe neonatal brain injuries, resulting from inflammation and the immune response after perinatal hypoxia and ischemia. IgG N-glycosylation plays a crucial role in various inflammatory diseases through mediating the balance between anti-inflammatory and pro-inflammatory responses. This study aimed to explore the effect of IgG N-glycosylation on the development of HIE.
Methods
This case-control study included 53 HIE patients and 57 control neonates. An ultrahigh-performance liquid chromatography (UPLC) method was used to determine the features of the plasma IgG N-glycans, by which 24 initial glycan peaks (GPs) were quantified. Multivariate logistic regression was used to examine the association between initial glycans and HIE, by which the significant parameters were used to develop a diagnostic model. Though receiver operating characteristic (ROC) curves, area under the curve (AUC) and 95% confidence interval (CI) were calculated to assess the performance of the diagnostic model.
Results
There were significant differences in 11 initial glycans between the patient and control groups. The levels of fucosylated and galactosylated glycans were significantly lower in HIE patients than in control individuals, while sialylated glycans were higher in HIE patients (p < 0.05). A prediction model was developed using three initial IgG N-glycans and fetal distress, low birth weight, and globulin. The ROC analysis showed that this model was able to discriminate between HIE patients and healthy individuals [AUC = 0.798, 95% CI: (0.716–0.880)].
Discussion
IgG N-glycosylation may play a role in the pathogenesis of HIE. Plasma IgG N-glycans are potential noninvasive biomarkers for screening individuals at high risk of HIE.
... In severe cases, low IgG sialylation contributes to the ADCC-regulated enhancement of inflammatory cytokines. 50,51 In the present study, no significant differences between studied groups in the expression of sialic acid, galactose, and N-acetylglucosamine were observed. On the other hand, a high positive correlation was found between IgG glycans reactivities with RCA-I recognizing the non-reducing terminal β1,4-D-galactose (Galβ1,4) and the expression of SNA-reactive α2,6-linked SA. ...
Introduction
Immunoglobulin G (IgG) glycosylation affects its effector functions and is essential in many steps of the inflammatory cascade. Therefore, it may be an important parameter for assessing the body’s immune response during the course of COVID-19 (Coronavirus disease 2019).
Methods
The N- and O-glycosylation of serum IgG in severe COVID-19 patients (n=87), convalescents (n=50), and healthy subjects (n=65) were examined using a modified lectin-ELISA method with specific biotinylated lectins. The obtained data were analyzed using STATISTICA 13.3PL software.
Results
We showed significantly higher expression of Lewisx oligosaccharide structures in severe COVID-19 patients than in the other two groups. Moreover, significantly lower expression of Lewisy sugar structures in IgG glycans was observed in the convalescents when compared with COVID-19 patients and healthy subjects. The lowest expression of highly branched N-glycans in cases of severe COVID-19 indicates that the development of the disease is associated with the presence of typical IgG biantennary N-glycans. The lack of significant differences in the expression of Tn antigen in IgG between studied groups and the significantly lower expression of T antigen in convalescents compared to the patients with severe COVID-19 and healthy subjects indicates a decrease in the content of the T antigen in IgG O-glycans in subjects recovered from COVID-19. Substantially higher reactivities of IgG O-glycans with Jacalin observed in COVID-19 patients and convalescents in comparison to the control group were most probably caused by increased expression of core 3 O-glycans in IgG.
Conclusion
Severe COVID-19 is accompanied by the expression in serum IgG of sialylated biantennary and highly branched N-glycans, decorated by fucose of Lewisx and Lewisy structures. The higher reactivity of IgG O-glycans with Jacalin in severe COVID-19 patients and convalescents indicates that the disease development and the recovery process are most probably accompanied by increased expression of the core 3 O-glycans.
... [37][38][39] For example, many acute infections including SARS-CoV-2, tuberculosis, pediatric meningococcal sepsis, and dengue virus reduce levels of sialic acid on the IgG Fc region. [51][52][53][54][55][56][57][58][59][60][61][62] By reducing the sialic acid content, these IgG responses induce downstream immune functions to help combat the pathogen. Conversely, IgG N-glycan sialic acid increases in populations diagnosed with certain cancers including renal cell carcinoma, castration-resistant prostate cancer, precancerous advanced colonic adenomas, and smoldering myeloma as well as during pregnancy. ...
Background
Lyme disease is caused by the bacteria Borreliella burgdorferi sensu lato (Bb) transmitted to humans from the bite of an infected Ixodes tick. Current diagnostics for Lyme disease are insensitive at the early disease stage and they cannot differentiate between active infections and people with a recent history of antibiotic-treated Lyme disease.
Methods
Machine learning technology was utilized to improve the prediction of acute Lyme disease and identify sialic acid and galactose sugar structures (N-glycans) on immunoglobulins associated specifically at time points during acute Lyme disease time. A plate-based approach was developed to analyze sialylated N-glycans associated with anti-Bb immunoglobulins. This multiplexed approach quantitates the abundance of Bb-specific IgG and the associated sialic acid, yielding an accuracy of 90% in a powered study.
Findings
It was demonstrated that immunoglobulin sialic acid levels increase during acute Lyme disease and following antibiotic therapy and a 3-month convalescence, the sialic acid level returned to that found in healthy control subjects (p < 0.001). Furthermore, the abundance of sialic acid on Bb-specific IgG during acute Lyme disease impaired the host’s ability to combat Lyme disease via lymphocytic receptor FcγRIIIa signaling. After enzymatically removing the sialic acid present on Bb-specific antibodies, the induction of cytotoxicity from acute Lyme disease patient antigen-specific IgG was significantly improved.
Interpretation
Taken together, Bb-specific immunoglobulins contain increased sialylation which impairs the host immune response during acute Lyme disease. Furthermore, this Bb-specific immunoglobulin sialyation found in acute Lyme disease begins to resolve following antibiotic therapy and convalescence.
Funding
Funding for this study was provided by the Coulter-Drexel Translational Research Partnership Program as well as from a Faculty Development Award from the Drexel University College of Medicine Institute for Molecular Medicine and Infectious Disease and the Department of Microbiology and Immunology.
... In hospitalized COVID-19 patients, the sialic acid and galactose content on total IgG N-glycans was reduced compared to patients with mild cases of COVID-19 and healthy controls 25 . Furthermore, anti-spike IgG isolated from hospitalized COVID-19 patients contained lowered core-fucose levels in severe patients [26][27][28][29][30][31] , promoting macrophage release of IL-6 and TNF-α and the destruction of endothelial barriers in vitro by binding FcγR IIA and IIIA 32 . ...
... IgG N-glycosylation and effector function have been well characterized during acute SARS-CoV-2 infection [26][27][28][29][30] . However, IgM antibodies also play vital roles during immune responses, promote affinity maturation, maintain hemostasis at mucosal sites including the gut and lung, and induce significantly higher levels of complement deposition compared to IgG 73 . ...
The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been studied during human acute viral infection. The analysis of IgM N-glycosylation from healthy controls and hospitalized coronavirus disease 2019 (COVID-19) patients reveals increased high-mannose and sialylation that correlates with COVID-19 severity. These trends are confirmed within SARS-CoV-2-specific immunoglobulin N-glycan profiles. Moreover, the degree of total IgM mannosylation and sialylation correlate significantly with markers of disease severity. We link the changes of IgM N-glycosylation with the expression of Golgi glycosyltransferases. Lastly, we observe antigen-specific IgM antibody-dependent complement deposition is elevated in severe COVID-19 patients and modulated by exoglycosidase digestion. Taken together, this work links the IgM N-glycosylation with COVID-19 severity and highlights the need to understand IgM glycosylation and downstream immune function during human disease.
... Fc N-glycosylation stabilizes the structure of the Fc fragment and regulates the anti-inflammatory and proinflammatory functions of IgG (16) through the following pathways: antibodydependent cell cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), antibody-dependent cellular phagocytosis (ADCP), and other types of receptor-mediated immune regulation (17,18). Increased core fucosylated and sialylated glycans promote the binding affinity of IgG with the activated receptor FcgRIIIa, which mediates ADCC, thus initiating activation signals and upregulating inflammatory responses (19). In addition, galactosylated glycans promote downstream CDC reactions by binding to complement 1q (C1q) (20). ...
Background
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.
Methods
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.
Results
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).
Conclusion
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.
... Globally, 617 597 680 confirmed cases and 6 532 705 deaths of have been reported to the World Health Organization (WHO) as of October 7, 2022 [2] . The susceptibility of individuals to the disease depends on health status, such as cardiovascular health conditions, sub-optimal health status, and preexisting comorbidities [3][4] , and so do the severity and mortality of COVID-19 patients [5] . Environmental factors, such as temperature, wind speed, and humidity, also play crucial roles in the transmission of respiratory viruses, causing the characteristic pattern of seasonal outbreaks (e.g., severe acute respiratory syndrome [SARS]) [6][7] . ...
Objective
This general non-systematic review aimed to gather information on reported statistical models examing the effects of meteorological factors on coronavirus disease 2019 (COVID-19) and compare these models.
Methods
PubMed, Web of Science, and Google Scholar were searched for studies on “meteorological factors and COVID-19” published between January 1, 2020, and October 1, 2022.
Results
The most commonly used approaches for analyzing the association between meteorological factors and COVID-19 were the linear regression model (LRM), generalized linear model (GLM), generalized additive model (GAM), and distributed lag non-linear model (DLNM). In addition to these classical models commonly applied in environmental epidemiology, machine learning techniques are increasingly being used to select risk factors for the outcome of interest and establishing robust prediction models.
Conclusion
Selecting an appropriate model is essential before conducting research. To ensure the reliability of analysis results, it is important to consider including non-meteorological factors ( e.g. , government policies on physical distancing, vaccination, and hygiene practices) along with meteorological factors in the model.
... The levels of bisecting N-acetylglucosamine (GlcNAc) and galactosylation of IgG were negatively related to COVID-19 severity (13). Additionally, the fucosylation and sialylation of IgG were observed to be positively correlated with COVID-19 severity, which closely contributed to the ADCCregulated enhancement of inflammatory cytokines (14,15). Moreover, previous studies also found that decreased fucosylation, galactosylation, and sialylation of anti-SARS-CoV-2 IgG1, as well as high bisection were early inflammatory signals promoting more severe disease in COVID-19 patients (16)(17)(18). ...
... IGP22, which directly measures IgG N-glycans, and IGP30, which measures the percentage of disialylation of fucosylated digalactosylated structures in total IgG glycans, were positively associated with the risk of COVID-19 hospitalization and severity. Previous studies on IgG glycosylation demonstrated that IGP22 and IGP30 were significantly higher in COVID-19 cases (15). Nonetheless, recent findings indicate that a lack of or decrease in sialylation, whether in anti-SARS-CoV-2 spike protein-specific (anti-S) IgG1 (17,18) or total IgG N-glycans, is protective against severe symptoms and cytokine storm in COVID-19 (18,26). ...
... Five IgG N-glycosylation traits, including two directly measured IgG N-glycans (IGP10 and IGP14) and three total IgG N-glycansderived traits (IGP34, IGP36, and IGP50), were associated with reduced risk of COVID-19 severity, consistent with prior findings that total IgG fucosylation levels were lower in severe COVID-19 cases (15). The IGP34 trait measures the ratio of fucosylated (without bisecting GlcNAc) monosialylated and disialylated structures in total IgG glycans, while IGP36 measures the ratio of all fucosylated sialylated structures with and without bisecting GlcNAc. ...
Background
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.
Methods
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.
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.
Conclusions
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.
... Along these lines, it is known that fucose-deficient IgGs bind preferentially to FcγR3a (refs. 74,75), whereas high galactosylation appears to further increase FcγR3a binding 76,77 . Galactose and sialic acid content has been shown to alter FcγR2 binding and activity 78 . ...
Despite the success of COVID-19 vaccines, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern have emerged that can cause breakthrough infections. Although protection against severe disease has been largely preserved, the immunological mediators of protection in humans remain undefined. We performed a substudy on the ChAdOx1 nCoV-19 (AZD1222) vaccinees enrolled in a South African clinical trial. At peak immunogenicity, before infection, no differences were observed in immunoglobulin (Ig)G1-binding antibody titers; however, the vaccine induced different Fc-receptor-binding antibodies across groups. Vaccinees who resisted COVID-19 exclusively mounted FcγR3B-binding antibodies. In contrast, enhanced IgA and IgG3, linked to enriched FcγR2B binding, was observed in individuals who experienced breakthrough. Antibodies unable to bind to FcγR3B led to immune complex clearance and resulted in inflammatory cascades. Differential antibody binding to FcγR3B was linked to Fc-glycosylation differences in SARS-CoV-2-specific antibodies. These data potentially point to specific FcγR3B-mediated antibody functional profiles as critical markers of immunity against COVID-19.
... In hospitalized COVID-19 patients, the sialic acid and galactose content on total IgG N-glycans was reduced compared to patients with mild cases of COVID-19 and healthy controls [17][18][19]. Furthermore, anti-spike IgG isolated from hospitalized COVID-19 patients contained lowered core-fucose levels in severe patients [24][25][26][27][28], promoting macrophage release of IL-6 and TNF-α and the destruction of endothelial barriers in vitro by binding FcγR IIA and IIIA [29]. ...
... IgG N-glycosylation and effector function have been well characterized during acute COVID-19 infection [17][18][19] [24][25][26][27][28]. However, IgM antibodies also play vital roles during immune responses, promote a nity maturation, maintain hemostasis at mucosal sites including the gut and lung, and induce signi cantly higher levels of complement deposition compared to IgG [76]. ...
The glycosylation of IgG plays a critical role during human SARS-CoV-2, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been studied during acute viral infection in humans. In vitro evidence suggests that the glycosylation of IgM inhibits T cell proliferation and alters complement activation rates. The analysis of IgM N-glycosylation from healthy controls and hospitalized COVID-19 patients reveals that mannosylation and sialyation levels associate with COVID-19 severity. Specifically, we find increased di- and tri-sialylated glycans and altered mannose glycans in total serum IgM in severe COVID-19 patients when compared to moderate COVID-19 patients. This is in direct contrast with the decrease of sialic acid found on the serum IgG from the same cohorts. Moreover, the degree of mannosylation and sialylation correlated significantly with markers of disease severity: D-dimer, BUN, creatinine, potassium, and early anti-COVID-19 amounts of IgG, IgA, and IgM. Further, IL-16 and IL-18 cytokines showed similar trends with the amount of mannose and sialic acid present on IgM, implicating these cytokines' potential to impact glycosyltransferase expression during IgM production. When examining PBMC mRNA transcripts, we observe a decrease in the expression of Golgi mannosidases that correlates with the overall reduction in mannose processing we detect in the IgM N-glycosylation profile. Importantly, we found that IgM contains alpha-2,3 linked sialic acids in addition to the previously reported alpha-2,6 linkage. We also report that antigen-specific IgM antibody-dependent complement deposition is elevated in severe COVID-19 patients. Taken together, this work links the immunoglobulin M N-glycosylation with COVID-19 severity and highlights the need to understand the connection between IgM glycosylation and downstream immune function during human disease.
... Immunologically, the IgG N-glycosylation of the Fc region plays a vital role in directing antibody-dependent cellular cytotoxicity (ADCC) and complement-mediated cytotoxicity [21][22][23][24]. ADCC is promoted by reduced fucose, galactose, and sialic acid content enabling the Fc portion of IgG to bind receptors such as Fc-RIIIa on immune cells to signal for activation [25][26][27][28]. In contrast, the addition of fucose, galactose, and sialic acids alters the conformation of the Fc region on IgG to promote inhibitory Fc-RIIb receptor binding, resulting in an anti-inflammatory response [29][30][31]. ...
... RT-PCR and rapid antigen tests have helped to accurately diagnose patients early in the disease progression [112], yet predicting a patient's outcome and hospitalization requirements remain challenging. A case-control study determined that during severe disease, IgG N-glycans lost significant levels of fucose and had lower levels of sialic acid content compared to patients with a mild case of COVID [28]. Because IgG N-glycans can promote complement deposition and ADCC, the N-glycan profile could identify patients in a highly proinflammatory state and associated with a heightened risk for a cytokine storm. ...
IgG N-glycans are an emerging source of disease-specific biomarkers. Over the last decade, the continued development of glycomic databases and the evolution of glyco-analytic methods have resulted in increased throughput, resolution, and sensitivity. IgG N-glycans promote adaptive immune responses through antibody-dependent cellular cytotoxicity (ADCC) and complement activation to combat infection or cancer and promote autoimmunity. In addition to the functional assays, researchers are examining the ability of protein-specific glycosylation to serve as biomarkers of disease. This literature review demonstrates that IgG N-glycans can discriminate between healthy controls, autoimmune disease, infectious disease, and cancer with high sensitivity. The literature also indicates that the IgG glycosylation patterns vary across disease state, thereby supporting their role as specific biomarkers. In addition, IgG N-glycans can be collected longitudinally from patients to track treatment responses or predict disease reoccurrence. This review focuses on IgG N-glycan profiles applied as diagnostics, cohort discriminators, and prognostics. Recent successes, remaining challenges, and upcoming approaches are critically discussed.
