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

Immunoglobulin G N-Glycome as a biomarker of mortality risk in Escherichia coli induced sepsis

Background

Sepsis is a life-threatening syndrome caused by an imbalance in the inflammatory response to an infection that can lead to a high mortality rate. Escherichia coli is a common pathogen that causes sepsis. The role of immunoglobulin G N-glycome in estimating the mortality in patients with sepsis remains unknown. This study aims to reveal the clinical application of immunoglobulin G N-glycome as a potentially novel biomarker to predict mortality risk in Escherichia coli-induced sepsis.

Methods

The serum immunoglobulin G N-glycome levels in 100 adult septic patient serum samples on the day of intensive care unit (ICU) admission, and 100 healthy volunteers were measured and analyzed. Immunoglobulin G N-glycome was compared with existing risk scores on predicting in-hospital death.

Results

We identified that the fucosylation level was significantly decreased in patients. Importantly, bisecting GlcNAc, sialylation, and galactosylation have different levels between sepsis and control groups. In addition, the AUC values of the SOFA score combined with GP4, GP5, and GP9 were 0.76 (95%CI: 0.61 to 0.90), 0.58 (95%CI: 0.40 to 0.7) and 0.57 (95%CI: 0.38 to 0.76). The AUC value of the SOFA score combined with GP4 and GP7 was 0.85 (95%CI: 0.76 to 0.93) in predicting in-hospital mortality in patients with sepsis.

Conclusions

Immunoglobulin G N-glycome concentrations at ICU admission are valuable for predicting the in-hospital mortality risk of patients with sepsis, suggesting that immunoglobulin G N-glycome may be a novel biomarker.

Potentially causal association between immunoglobulin G N-glycans and cardiometabolic diseases: Bidirectional two-sample Mendelian randomization study

BACKGROUND

Observational studies support that altered immunoglobulin G (IgG) N-glycosylation and inflammatory factors are associated with cardiometabolic diseases (CMDs); nevertheless, the causality between them remains unclear.

METHODS

Two-sample Mendelian randomization (MR) analyses were conducted to systematically investigate the bidirectional causality between IgG N-glycans and nine CMDs in both East Asians and Europeans.

RESULTS

In the forward MR analysis, the univariable MR analysis presented suggestive causality of 14 and eight genetically instrumented IgG N-glycans with CMDs in East Asians and Europeans, respectively; the multivariable MR analysis showed that ten and 11 pairs of glycan-CMD associations were identified in East Asian and European populations, respectively. In the reverse MR analysis, based on East Asians and Europeans, the univariable MR analysis presented suggestive causality of seven and 12 genetically instrumented CMDs with IgG N-glycans, respectively; the multivariable MR analysis presented that six and five CMD-glycan causality were found in East Asian and Europeans, respectively.

CONCLUSIONS

The comprehensive MR analyses provide suggestive evidence of bidirectional causality between IgG N-glycans and CMDs. This work helps to understand the molecular mechanism of the occurrence/progression of CMDs, optimize existing and develop new strategies to prevent CMDs, and contribute to the early identification of high-risk groups of CMDs.

Differences in IgG afucosylation between groups with and without carotid atherosclerosis

BACKGROUND

A previous study demonstrated that N-glycosylation profiles of IgG are associated with subclinical atherosclerosis in a British population. However, the generalisability of this finding to other ethnic groups remains to be investigated, and it has yet to account for additional traditional atherosclerotic risk factors. The present study, thus, aims to explore IgG N-glycosylation profiles in Han Chinese with atherosclerosis, and their potential role in atherosclerosis, while controlling for traditional atherosclerotic risk factors.

METHODS

Data of this case-control study were obtained from an established umbrella Health Examination Cohort Study (registration number: ChiCTR2100048740). The investigation was conducted at the Health Care Centre of the First Affiliated Hospital of Shantou University Medical College in China, from August 1, 2021, to July 31, 2022. A sample of 69 carotid atherosclerosis (CAS) cases was recruited from the umbrella cohort, along with 69 controls without carotid atherosclerosis, matched by traditional atherosclerosis-related risk factors, including gender, age, smoking, alcohol consumption, hypertension, diabetes, dyslipidemia and obesity. Subsequently, serum IgG N-glycosylation was profiled using Ultra-Performance Liquid Chromatography.

RESULTS

After propensity score matching, the relative abundance of IgG fucosylation in CAS cases was significantly lower than that in controls [95.32 (92.96, 95.99) vs. 95.96 (94.70, 96.58), P = 0.022]. The traditional atherosclerosis-related risk factors showed no statistically significant difference between CAS cases and controls (P > 0.05).

CONCLUSIONS

The reduced fucosylation of IgG in CAS cases underscores the pivotal role of afucosylation in CAS. Enhancing the inflammatory capability of IgG via initiating antibody-dependent cell-mediated cytotoxicity could be the potential mechanism behind this, which should be further verified by functional studies.

Protein glycosylation in cardiovascular health and disease

Protein glycosylation, which involves the attachment of carbohydrates to proteins, is one of the most abundant protein co-translational and post-translational modifications. Advances in technology have substantially increased our knowledge of the biosynthetic pathways involved in protein glycosylation, as well as how changes in glycosylation can affect cell function. In addition, our understanding of the role of protein glycosylation in disease processes is growing, particularly in the context of immune system function, infectious diseases, neurodegeneration and cancer. Several decades ago, cell surface glycoproteins were found to have an important role in regulating ion transport across the cardiac sarcolemma. However, with very few exceptions, our understanding of how changes in protein glycosylation influence cardiovascular (patho)physiology remains remarkably limited. Therefore, in this Review, we aim to provide an overview of N-linked and O-linked protein glycosylation, including intracellular O-linked N-acetylglucosamine protein modification. We discuss our current understanding of how all forms of protein glycosylation contribute to normal cardiovascular function and their roles in cardiovascular disease. Finally, we highlight potential gaps in our knowledge about the effects of protein glycosylation on the heart and vascular system, highlighting areas for future research.

The connections of sialic acids and diabetes mellitus: therapeutic or diagnostic value?

Modulation of sialic acids is one of the important pathological consequences of both type 1 and type 2 diabetes mellitus with or without the micro- and macrovascular complications. However, the mechanistic, therapeutic and/or diagnostic implications of these observations are uncoordinated and possibly conflicting. This review critically analyses the scientific investigations connecting sialic acids with diabetes mellitus. Generally, variations in the levels and patterns of sialylation, fucosylation and galactosylation were predominant across various tissues and body systems of diabetic patients, but the immune system seemed to be most affected. These might be explored as a basis for differential diagnosis of various diabetic complications. Sialic acids are predominantly elevated in nearly all forms of diabetic conditions, particularly nephropathy and retinopathy, which suggests some diagnostic value but the mechanistic details were not unequivocal from the available data. The plausible mechanistic explanations for the elevated sialic acids are increased desialylation by sialidases, stimulation of hexosamine pathway and synthesis of acute phase proteins as well as oxidative stress. Additionally, sialic acids are also profoundly associated with glucose transport and insulin resistance in human-based studies while animal-based studies revealed that the increased desialylation of insulin receptors by sialidases, especially NEU1, might be the causal link. Interestingly, inhibition of the diabetes-associated NEU1 desialylation was beneficial in diabetes management and might be considered as a therapeutic target. It is hoped that the article will provide an informed basis for future research activities on the exploitation of sialic acids and glycobiology for therapeutic and/or diagnostic purposes against diabetes mellitus.

Recent advances in N-glycan biomarker discovery among human diseases

N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.

Association of Glutathione Peroxidase 3 (GPx3) and miR-196a with Carbohydrate Metabolism Disorders in the Elderly

The escalating prevalence of carbohydrate metabolism disorders (CMDs) prompts the need for early diagnosis and effective markers for their prediction. Hyperglycemia, the primary indicator of CMDs including prediabetes and type 2 diabetes mellitus (T2DM), leads to overproduction of reactive oxygen species (ROS) and oxidative stress (OxS). This condition, resulting from chronic hyperglycemia and insufficient antioxidant defense, causes damage to biomolecules, triggering diabetes complications. Additionally, aging itself can serve as a source of OxS due to the weakening of antioxidant defense mechanisms. Notably, previous research indicates that miR-196a, by downregulating glutathione peroxidase 3 (GPx3), contributes to insulin resistance (IR). Additionally, a GPx3 decrease is observed in overweight/obese and insulin-resistant individuals and in the elderly population. This study investigates plasma GPx3 levels and miR-196a expression as potential CMD risk indicators. We used ELISA to measure GPx3 and qRT-PCR for miR-196a expression, supplemented by multivariate linear regression and receiver operating characteristic (ROC) analysis. Our findings included a significant GPx3 reduction in the CMD patients (n = 126), especially in the T2DM patients (n = 51), and a decreasing trend in the prediabetes group (n = 37). miR-196a expression, although higher in the CMD and T2DM groups than in the controls, was not statistically significant, potentially due to the small sample size. In the individuals with CMD, GPx3 levels exhibited a negative correlation with the mass of adipose tissue, muscle, and total body water, while miR-196a positively correlated with fat mass. In the CMD group, the analysis revealed a weak negative correlation between glucose and GPx3 levels. ROC analysis indicated a 5.2-fold increased CMD risk with GPx3 below 419.501 ng/mL. Logistic regression suggested that each 100 ng/mL GPx3 increase corresponded to a roughly 20% lower CMD risk (OR = 0.998; 95% CI: 0.996-0.999; p = 0.031). These results support the potential of GPx3 as a biomarker for CMD, particularly in T2DM, and the lack of a significant decline in GPx3 levels in prediabetic individuals suggests that it may not serve reliably as an early indicator of CMDs, warranting further large-scale validation.

IgG N-glycans are associated with prevalent and incident complications of type 2 diabetes

AIMS/HYPOTHESIS

Inflammation is important in the development of type 2 diabetes complications. The N-glycosylation of IgG influences its role in inflammation. To date, the association of plasma IgG N-glycosylation with type 2 diabetes complications has not been extensively investigated. We hypothesised that N-glycosylation of IgG may be related to the development of complications of type 2 diabetes.

METHODS

In three independent type 2 diabetes cohorts, plasma IgG N-glycosylation was measured using ultra performance liquid chromatography (DiaGene n = 1815, GenodiabMar n = 640) and mass spectrometry (Hoorn Diabetes Care Study n = 1266). We investigated the associations of IgG N-glycosylation (fucosylation, galactosylation, sialylation and bisection) with incident and prevalent nephropathy, retinopathy and macrovascular disease using Cox- and logistic regression, followed by meta-analyses. The models were adjusted for age and sex and additionally for clinical risk factors.

RESULTS

IgG galactosylation was negatively associated with prevalent and incident nephropathy and macrovascular disease after adjustment for clinical risk factors. Sialylation was negatively associated with incident diabetic nephropathy after adjustment for clinical risk factors. For incident retinopathy, similar associations were found for galactosylation, adjusted for age and sex.

CONCLUSIONS

We showed that IgG N-glycosylation, particularly galactosylation and to a lesser extent sialylation, is associated with a higher prevalence and future development of macro- and microvascular complications of diabetes. These findings indicate the predictive potential of IgG N-glycosylation in diabetes complications and should be analysed further in additional large cohorts to obtain the power to solidify these conclusions.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Identification and validation of IgG N-glycosylation biomarkers of esophageal carcinoma

Introduction

Altered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC.

Methods

In total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score.

Results

In the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P<0.001), 0.69 (95% CI: 0.55-0.87, P<0.001), 0.56 (95% CI: 0.45-0.69, P<0.001), 0.52 (95% CI: 0.41-0.65, P<0.001), 7.17 (95% CI: 4.77-10.79, P<0.001), and 2.86 (95% CI: 2.33-3.53, P<0.001), respectively. Individuals in the highest tertile of the glycan score own an increased risk (OR: 11.41), compared with those in the lowest. The average multi-class AUC are 0.822 (95% CI: 0.786-0.849). Findings are verified in the validation population, with an average AUC of 0.807 (95% CI: 0.758-0.864).

Discussion

Our study demonstrated that IgG N-glycans and the proposed glycan score appear to be promising predictive markers for ESCC, contributing to the early prevention of esophageal cancer. From the perspective of biological mechanism, IgG fucosylation and mannosylation might involve in the carcinogenesis progression of ESCC, and provide potential therapeutic targets for personalized interventions of cancer progression.

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

Objectives

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.

Methods

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.

Results

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.

Conclusions

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.

Supplementary information

The online version contains supplementary material available at 10.1007/s13167-022-00311-3.

Role of liver parameters in diabetes mellitus - a narrative review

Diabetes mellitus is characterized by hyperglycemia and abnormalities in insulin secretion and function. This review article focuses on various liver parameters, including albumin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), alpha fetoprotein (AFP), alpha 1 antitrypsin (AAT), ammonia, bilirubin, bile acid, gamma-glutamyl transferase (GGT), immunoglobulin, lactate dehydrogenase (LDH), and total protein. These parameters play significant roles in the development of different types of diabetes such as type 1 diabetes (T1DM), type 2 diabetes (T2DM) and gestational diabetes (GDM). The article highlights that low albumin levels may indicate inflammation, while increased ALT and AST levels are associated with liver inflammation or injury, particularly in non-alcoholic fatty liver disease (NAFLD). Elevated ALP levels can be influenced by liver inflammation, biliary dysfunction, or bone metabolism changes. High bilirubin levels are independently linked to albuminuria in T1DM and an increased risk of T2DM. Elevated GGT levels are proposed as markers of oxidative stress and liver dysfunction in T2DM. In GDM, decreased serum AFP levels may indicate impaired embryo growth. Decreased AFP levels in T2DM can hinder the detection of hepatocellular carcinoma. Hyperammonemia can cause encephalopathy in diabetic ketoacidosis, and children with T1DM and attention deficit hyperactivity disorder often exhibit higher ammonia levels. T2DM disrupts the regulation of nitrogen-related metabolites, leading to increased blood ammonia levels. Bile acids affect glucose regulation by activating receptors on cell surfaces and nuclei, and changes in bile acid metabolism are observed in T2DM. Increased LDH activity reflects metabolic disturbances in glucose utilization and lactate production, contributing to diabetic complications. Poor glycemic management may be associated with elevated levels of IgA and IgG serum antibodies, and increased immunoglobulin levels are also associated with T2DM.

Immunoglobulin G N-glycan, inflammation and type 2 diabetes in East Asian and European populations: a Mendelian randomization study

Background

Immunoglobulin G (IgG) N-glycans have been shown to be associated with the risk of type 2 diabetes (T2D) and its risk factors. However, whether these associations reflect causal effects remain unclear. Furthermore, the associations of IgG N-glycans and inflammation are not fully understood.

Methods

We examined the causal associations of IgG N-glycans with inflammation (C-reactive protein (CRP) and fibrinogen) and T2D using two-sample Mendelian randomization (MR) analysis in East Asian and European populations. Genetic variants from IgG N-glycan quantitative trait loci (QTL) data were used as instrumental variables. Two-sample MR was conducted for IgG N-glycans with inflammation (75,391 and 18,348 participants of CRP and fibrinogen in the East Asian population, 204,402 participants of CRP in the European population) and T2D risk (77,418 cases and 356,122 controls of East Asian ancestry, 81,412 cases and 370,832 controls of European ancestry).

Results

After correcting for multiple testing, in the East Asian population, genetically determined IgG N-glycans were associated with a higher risk of T2D, the odds ratios (ORs) were 1.009 for T2D per 1- standard deviation (SD) higher GP5, 95% CI = 1.003–1.015; P = 0.0019; and 1.013 for T2D per 1-SD higher GP13, 95% CI = 1.006–1.021; P = 0.0005. In the European population, genetically determined decreased GP9 was associated with T2D (OR = 0.899 per 1-SD lower GP9, 95% CI: 0.845–0.957). In addition, there was suggestive evidence that genetically determined IgG N-glycans were associated with CRP in both East Asian and European populations after correcting for multiple testing, but no associations were found between IgG N-glycans and fibrinogen. There was limited evidence of heterogeneity and pleiotropy bias.

Conclusions

Our results provided novel genetic evidence that IgG N-glycans are causally associated with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00543-z.

Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease

OBJECTIVE

N-glycosylation is a functional posttranslational modification of immunoglobulins (Igs). We hypothesized that specific IgG N-glycans are associated with incident type 2 diabetes and cardiovascular disease (CVD).

RESEARCH DESIGN AND METHODS

We performed case-cohort studies within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (2,127 in the type 2 diabetes subcohort [741 incident cases]; 2,175 in the CVD subcohort [417 myocardial infarction and stroke cases]). Relative abundances of 24 IgG N-glycan peaks (IgG-GPs) were measured by ultraperformance liquid chromatography, and eight glycosylation traits were derived based on structural similarity. End point-associated IgG-GPs were preselected with fractional polynomials, and prospective associations were estimated in confounder-adjusted Cox models. Diabetes risk associations were validated in three independent studies.

RESULTS

After adjustment for confounders and multiple testing correction, IgG-GP7, IgG-GP8, IgG-GP9, IgG-GP11, and IgG-GP19 were associated with type 2 diabetes risk. A score based on these IgG-GPs was associated with a higher diabetes risk in EPIC-Potsdam and independent validation studies (843 total cases, 3,149 total non-cases, pooled estimate per SD increase 1.50 [95% CI 1.37-1.64]). Associations of IgG-GPs with CVD risk differed between men and women. In women, IgG-GP9 was inversely associated with CVD risk (hazard ratio [HR] per SD 0.80 [95% CI 0.65-0.98]). In men, a weighted score based on IgG-GP19 and IgG-GP23 was associated with higher CVD risk (HR per SD 1.47 [95% CI 1.20-1.80]). In addition, several derived traits were associated with cardiometabolic disease incidence.

CONCLUSIONS

Selected IgG N-glycans are associated with cardiometabolic risk beyond classic risk factors, including clinical biomarkers.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Expression Profile of Immunoglobulin G Glycosylation in Children With Epilepsy in Han Nationality

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 epilepsy.

METHODS

Patients were recruited in Taian, Shandong Province from December 2019 to March 2020. Serum IgG glycome composition was analyzed by hydrophilic interaction liquid chromatography with ultra-high-performance liquid chromatography approach.

RESULTS

The proportion of fucosylated glycans in total IgG glycans was 93.72% in the epilepsy patients, which was significantly lower than that in the control group (94.94%). A lower level of total monogalactosylated and digalactosylated glycans were observed in the epilepsy patients group (30.76 and 40.14%) than that in the controls (36.17 and 42.69%). There was no significant difference between the two groups in bisected GlcNAc glycans and sialylated glycans.

CONCLUSION

The decrease of core fucosylation and galactosylation may promote the inflammatory reaction of the body and participate in the occurrence of epilepsy in children.

IgG N-glycans

Glycosylation, one of the most common post-translational modifications in mammalian cells, impacts many biological processes such as cell adhesion, proliferation and differentiation. As the most abundant glycoprotein in human serum, immunoglobulin G (IgG) plays a vital role in immune response and protection. There is a growing body of evidence suggests that IgG structure and function are modulated by attached glycans, especially N-glycans, and aberrant glycosylation is associated with disease states. In this chapter, we review IgG glycan repertoire and function, strategies for profiling IgG N-glycome and recent studies. Mass spectrometry (MS) based techniques are the most powerful tools for profiling IgG glycome. IgG glycans can be divided into high-mannose, biantennary complex and hybrid types, modified with mannosylation, core-fucosylation, galactosylation, bisecting GlcNAcylation, or sialylation. Glycosylation of IgG affects antibody half-life and their affinity and avidity for antigens, regulates crystallizable fragment (Fc) structure and Fcγ receptor signaling, as well as antibody effector function. Because of their critical roles, IgG N-glycans appear to be promising biomarkers for various disease states. Specific IgG glycosylation can convert a pro-inflammatory response to an anti-inflammatory activity. Accordingly, IgG glycoengineering provides a powerful approach to potentially develop effective drugs and treat disease. Based on the understanding of the functional role of IgG glycans, the development of vaccines with enhanced capacity and long-term protection are possible in the near future.

The Rapidly Expanding Nexus of Immunoglobulin G N-Glycomics, Suboptimal Health Status, and Precision Medicine

Immunoglobulin G is a prevalent glycoprotein, whose downstream immune responses are partially mediated by the N-glycans within the fragment crystallisable domain. Collectively termed the N-glycome, it is considered a complex intermediate phenotype: an amalgamation of genetic predisposition, environmental exposure, and health behaviours over the life-course. Thus, the immunoglobulin G N-glycome may provide an indication of health status on the spectrum from health to disease and infirmary. Although variability exists within and between populations, composition of the immunoglobulin G N-glycome remains stable over short periods of time. This underscores the potential of harnessing the immunoglobulin G N-glycome as an ideal tool for preclinical disease risk prediction, stratification, and prognosis through the development of precise dynamic biomarkers.

Plasma N-glycome shows continuous deterioration as the diagnosis of insulin resistance approaches

INTRODUCTION

Prediction of type 2 diabetes mellitus (T2DM) and its preceding factors, such as insulin resistance (IR), is of great importance as it may allow delay or prevention of onset of the disease. Plasma protein N-glycome has emerged as a promising predictive biomarker. In a prospective longitudinal study, we included patients with a first diagnosis of impaired glucose metabolism (IR or T2DM) to investigate the N-glycosylation's predictive value years before diabetes development.

RESEARCH DESIGN AND METHODS

Plasma protein N-glycome was profiled by hydrophilic interaction ultra-performance liquid chromatography in 534 TwinsUK participants free from disease at baseline. This included 89 participants with incident diagnosis of IR or T2DM during the follow-up period (7.14±3.04 years) whose last sample prior to diagnosis was compared using general linear regression with 445 age-matched unrelated controls. Findings were replicated in an independent cohort. Changes in N-glycome have also been presented in connection with time to diagnosis.

RESULTS

Eight groups of plasma N-glycans were different between incident IR or T2DM cases and controls (p<0.05) after adjusting for multiple testing using Benjamini-Hochberg correction. These differences were noticeable up to 10 years prior to diagnosis and are changing continuously as becoming more expressed toward the diagnosis. The prediction model was built using significant glycan traits, displaying a discriminative performance with an area under the receiver operating characteristic curve of 0.77.

CONCLUSIONS

In addition to previous studies, we showed the diagnostic potential of plasma N-glycome in the prediction of both IR and T2DM development years before the clinical manifestation and indicated the continuous deterioration of N-glycome toward the diagnosis.

Variation of IgG N-linked glycosylation profile in diabetic retinopathy

BACKGROUND

The relationship of immunoglobulin G (IgG) glycosylation with diabetes and diabetic nephropathy has been reported, but its role in diabetic retinopathy (DR) remains unclear. We aimed to investigate and validate the association of IgG glycosylation with DR.

METHODS

We analyzed the IgG N-linked glycosylation profile and primarily selected candidate glycans by lasso (least absolute shrinkage and selection operator) regression analysis in the discovery population. The findings were validated in the replication population using a binary logistics model. The association between the significant glycosylation panel and clinical features was illustrated with Spearman's coefficient. The results were confirmed by sensitivity analyses.

RESULTS

Among 16 selected glycan candidates using lasso, two IgG glycans (GP15, GP20) and two derived traits (IGP32, IGP54) were identified and validated to be significantly associated with DR (P < .05), and the combined adjusted odds ratios (ORs) were 0.587, 0.613, 1.970, and 0.593, respectively. The glycosylation panel showed a weak correlation with clinical features, except for age. In addition, the results remained consistent when the subjects with prediabetes were excluded from the controls, and the adjusted ORs were 0.677, 0.738, 1.597, and 0.678 in the whole population. Furthermore, in the 1:3 rematched population, a significant association was observed, apart from GP20.

CONCLUSIONS

The IgG glycosylation profile, reflecting an aging and pro-inflammatory status, was significantly associated with DR. The variation in the IgG glycome deserves more attention in diabetic complications.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

Association of dementia with immunoglobulin G N-glycans in a Chinese Han Population

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.

Immunoglobulin G Glycosylation in Diseases

Changes in immunoglobulin G (IgG) glycosylation pattern have been observed in a vast array of auto- and alloimmune, infectious, cardiometabolic, malignant, and other diseases. This chapter contains an updated catalog of over 140 studies within which IgG glycosylation analysis was performed in a disease setting. Since the composition of IgG glycans is known to modulate its effector functions, it is suggested that a changed IgG glycosylation pattern in patients might be involved in disease development and progression, representing a predisposition and/or a functional effector in disease pathology. In contrast to the glycopattern of bulk serum IgG, which likely relates to the systemic inflammatory background, the glycosylation profile of antigen-specific IgG probably plays a direct role in disease pathology in several infectious and allo- and autoimmune antibody-dependent diseases. Depending on the specifics of any given disease, IgG glycosylation read-out might therefore in the future be developed into a useful clinical biomarker or a supplementary to currently used biomarkers.

Glycosylation Profiling as a Biomarker of Suboptimal Health Status for Chronic Disease Stratification

WHO defines health as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity." We coined and defined suboptimal health status (SHS) as a subclinical, reversible stage of the pre-chronic disease. SHS is a physical state between health and disease, characterized by health complaints, general weakness, chronic fatigue, and low energy levels. We have developed an instrument to measure SHS, Suboptimal Health Status Questionnaire-25 (SHSQ-25), a self-reported survey assessing five health components that has been validated in various ethnical populations. Our studies suggest that SHS is associated with the major components of cardiovascular health and the early onset of metabolic diseases. Besides subjective measure of health (SHS), glycans are conceived as objective biomarkers of SHS. Glycans are complex and branching carbohydrate moieties attached to proteins, participating in inflammatory regulation and chronic disease pathogenesis. We have been investigating the role of glycans and SHS in multiple cardiometabolic diseases in different ethnical populations (African, Chinese, and Caucasian). Here we present case studies to prove that a combination of subjective health measure (SHS) with objective health measure (glycans) represents a window of opportunity to halt or reverse the progression of chronic diseases.

Protein Glycosylation in Diabetes

Diabetes mellitus is a group of metabolic disorders characterized by the presence of hyperglycaemia. Due to its high prevalence and substantial heterogeneity, many studies have been investigating markers that could identify predisposition for the disease development, differentiate between the various subtypes, establish early diagnosis, predict complications or represent novel therapeutic targets. N-glycans, complex oligosaccharide molecules covalently linked to proteins, emerged as potential markers and functional effectors of various diabetes subtypes, appearing to have the capacity to meet these requirements. For instance, it has been shown that N-glycome changes in patients with type 2 diabetes and that N-glycans can even identify individuals with an increased risk for its development. Moreover, genome-wide association studies identified glycosyltransferase genes as candidate causal genes for both type 1 and type 2 diabetes. N-glycans have also been suggested to have a major role in preventing the impairment of glucose-stimulated insulin secretion by modulating cell surface expression of glucose transporters. In this chapter we aimed to describe four major diabetes subtypes: type 1, type 2, gestational and monogenic diabetes, giving an overview of suggested role for N-glycosylation in their development, diagnosis and management.

Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell

Precision/personalized medicine is a hot topic in health care. Often presented with the motto "the right drug, for the right patient, at the right dose, and the right time," precision medicine is a theory for rational therapeutics as well as practice to individualize health interventions (e.g., drugs, food, vaccines, medical devices, and exercise programs) using biomarkers. Yet, an alien visitor to planet Earth reading the contemporary textbooks on diagnostics might think precision medicine requires only two biomolecules omnipresent in the literature: nucleic acids (e.g., DNA) and proteins, known as the first and second alphabet of biology, respectively. However, the precision/personalized medicine community has tended to underappreciate the third alphabet of life, the "sugar code" (i.e., the information stored in glycans, glycoproteins, and glycolipids). This article brings together experts in precision/personalized medicine science, pharmacoglycomics, emerging technology governance, cultural studies, contemporary art, and responsible innovation to critically comment on the sociomateriality of the three alphabets of life together. First, the current transformation of targeted therapies with personalized glycomedicine and glycan biomarkers is examined. Next, we discuss the reasons as to why unraveling of the sugar code might have lagged behind the DNA and protein codes. While social scientists have historically noted the importance of constructivism (e.g., how people interpret technology and build their values, hopes, and expectations into emerging technologies), life scientists relied on the material properties of technologies in explaining why some innovations emerge rapidly and are more popular than others. The concept of sociomateriality integrates these two explanations by highlighting the inherent entanglement of the social and the material contributions to knowledge and what is presented to us as reality from everyday laboratory life. Hence, we present a hypothesis based on a sociomaterial conceptual lens: because materiality and synthesis of glycans are not directly driven by a template, and thus more complex and open ended than sequencing of a finite length genome, social construction of expectations from unraveling of the sugar code versus the DNA code might have evolved differently, as being future-uncertain versus future-proof, respectively, thus potentially explaining the "sugar lag" in precision/personalized medicine diagnostics over the past decades. We conclude by introducing systems scientists, physicians, and biotechnology industry to the concept, practice, and value of responsible innovation, while glycomedicine and other emerging biomarker technologies (e.g., metagenomics and pharmacomicrobiomics) transition to applications in health care, ecology, pharmaceutical/diagnostic industries, agriculture, food, and bioengineering, among others.